Biomarker Discovery for Asthma Phenotyping: from Gene Expression to the Clinic

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Biomarker discovery for asthma phenotyping: From gene expression to the clinic

Wagener, A.H.

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Biomarker discovery for asthma phenotyping from gene expression to the clinic ARIANE H. WAGENER

Biomarker discovery for asthma phenotyping: from gene expression to the clinic

ISBN: 978-94-6169-778-3

Layout and printing: Optima Grafische Communicatie, Rotterdam, The Netherlands Biomarker discovery for asthma phenotyping: from gene expression to the clinic

ACADEMISCH PROEFSCHRIFT

ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. D.C. van den Boom ten overstaan van een door het College voor Promoties ingestelde commissie, in het openbaar te verdedigen in de Agnietenkapel op dinsdag 26 januari 2016, te 14:00 uur

door Ariane Heleen Wagener

geboren te Leiden Promotiecommissie

Promotores: Prof. dr. P.J. Sterk Universiteit van Amsterdam Prof. dr. A.H. Zwinderman Universiteit van Amsterdam

Copromotor: Dr. C.M. van Drunen Universiteit van Amsterdam

Overige leden: Prof. dr. F. Baas Universiteit van Amsterdam Prof. dr. W.J. Fokkens Universiteit van Amsterdam Prof. dr. M.D. de Jong Universiteit van Amsterdam Dr. A. ten Brinke Medisch Centrum Leeuwarden Prof. dr. F.J. van Schooten Universiteit Maastricht Prof. R. Djukanovic University of Southampton

Faculteit der Geneeskunde Contents

Chapter 1 General Introduction 7

Chapter 2 Towards composite molecular signatures in the phenotyping of 15 asthma

Chapter 3 The impact of allergic rhinitis and asthma on human nasal and 33 bronchial epithelial gene expression

Chapter 4 dsRNA-induced changes in gene expression profiles of primary 147 nasal and bronchial epithelial cells from patients with asthma, rhinitis and controls

Chapter 5 External validation of blood eosinophils, FENO and serum 197 periostin as surrogates for sputum eosinophils in asthma

Chapter 6 Predicting eosinophilic airway inflammation in asthma using 219 exhaled breath profiling

Chapter 7 Summary and General Discussion 235

Chapter 8 Nederlandse Samenvatting 251

Appendices Contributing Authors 257

List of Publications 263

Dankwoord / Acknowledgements 265

Curriculum Vitae 267

CHAPTER 1 General Introduction

Asthma phenotypes

Asthma is highly complex with respect to pathophysiology and response to treatment. Only recently, asthma was defined as a syndrome (1;2), and by characterization multiple asthma phenotypes were recognized (3-6). So far, the phenotypic characterization of asthma has been limited to clinical symptoms, age of onset, lung function, gender, medication use, general inflammatory markers, body mass index (BMI), nasal polyps and sinusitis. Since the comorbidity of the upper airway diseases in asthma are highly prevalent, upper respiratory tract symptoms are included when studying asthma phenotypes. According to epidemiological studies, the majority of patients with asthma have concomitant allergic rhinitis and the presence of allergic rhinitis is an independent risk factor for development of asthma (7). This frequent co-existence of allergic rhinitis and asthma has been referred to as “united airways disease”, suggesting a single inflammatory process that causes both upper and lower airway diseases (8). A better molecular understanding of this biological complex disease will allow for discovery of various disease phenotypes and the mechanisms driving the inflammatory processes involved.

Unmet needs

Eventually, asthma profiling will lead to phenotypic targeted treatment, one of the major unmet needs for asthma. Previous studies have shown that sputum eosinophils are predictive of treatment responsiveness and disease outcome (9). Because of the limitations of sputum induction, several studies have tried to find alternative markers for sputum eosinophils. Blood differential cell counts, fractional exhaled nitric oxide (FENO) and serum periostin have been considered in various studies as surrogate markers to diagnose airway eosinophilia, even though a recent meta-analysis was still inconclusive (10). Recently, blood eosinophil count was successfully used to identify patients with eosinophilic asthma responsive to anti-IL-5 treatment (11;12). Furthermore, periostin was demonstrated to be a predictive biomarker for the effectiveness of anti-IL-13 therapy (13). This suggests that inflammatory biomarkers should be used in asthma management. Unfortunately, limited progress has been made in the discovery of new useful clinical biomarkers and further validation of existing biomarkers is needed (14). A second unmet need is prevention and improved treatment of asthma exacerbations. The continuous occurrence of acute exacerbations despite optimal asthma management imposes considerable morbidity on patients and is a major economic burden (15). The most common cause of asthma exacerbations are viral respiratory tract infections. The upper airway is the first line of defence, being constantly exposed to various viruses, bacteria, and allergens. In case of a viral upper respiratory tract infection, patients with

General Introduction 9 asthma have increased risk of developing a lower respiratory tract infection with more severe symptoms as compared to the same type of infection in healthy individuals (16). To identify new targets for prevention and therapy, studies are needed to increase our understanding of the mechanisms of virus induced asthma exacerbations. A recent trial showed inhaled IFN-β as potential treatment for deterioration of asthma symptoms caused by respiratory viruses. This therapy is based on studies examining bronchial epithelial cells from patients with asthma having an impaired interferon production in response to viruses (17-19). More clinical studies are needed to further our understanding and identify new targets.

Biomarker discovery

To increase the understanding of asthma and discover new biomarkers, knowledge of the molecular mechanisms involved is required. By now, high-throughput omics technologies are available to quantify gene expression (transcriptomics), proteins (proteomics), lipids (lipidomics) along with other metabolites (metabolomics) in blood, urine and exhaled air (breathomics). In general, biomarker studies can either analyse specific predefined biomarkers, or use an unbiased approach which is more statistically based to allow for the discovery of new biomarkers. An experimental design using omics technology often involves a hypothesis-generating component, studying large comprehensive datasets for new insights or diagnostics in disease instead of reducing explanations to specific identified targets. In this thesis, we apply both transcriptomics analysis and breathomics analysis to increase our understanding and search for surrogate biomarkers. We use microarrays for high-throughput quantification of RNA transcripts because this is the present state-of-the-art method for biomarker discovery. Transcriptomics analysis can be used to study gene expression of samples composed of an isolated cell type or samples of heterogeneous cellular composition; however, analysing mixed cell types will make interpretation of results difficult. Breathomics was more recently introduced and may offer a noninvasive easy-to-use method capturing composite molecular signatures in exhaled air. Using these methods will allow further characterization of complex diseases such as asthma, and will potentially offer biomarker discovery (20).

Validation

Validation is an essential part of modern research, including validation of techniques or tools, statistical analysis and populations. When identifying or testing biomarkers to diagnose or phenotype disease, validation of all these elements are required and

10 Chapter 1 once markers have been identified external validation is essential. Several international guidelines have been published to improve the quality and standardize the reporting of studies. The guidelines on STAndards for the Reporting of Diagnostic accuracy studies (STARD) was initiated to improve the reporting of studies on diagnostic accuracy (21), and the recently published Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) initiative help to improve reporting of prediction model studies (22). In this thesis we firstly review several elements of validation for trancriptomics analysis and breathomics analysis. Next, we use various methods to validate elements of the clinical studies, which are further discussed in the final chapter.

Objectives of this thesis

1. To review and compare transcriptomics by microarrays and next-generation RNA sequencing. 2. To review breathomics as a non-invasive tool. 3. To define the gene expression profiles of upper and lower airway epithelial cells of the same individuals with and without upper or lower airways disease. 4. To examine the impact of allergic rhinitis with or without allergic asthma on the gene expression profiles of the upper and lower airway epithelium. 5. To define the gene expression profiles of upper and lower airway epithelial cells of the same individuals with and without upper or lower airways disease after stimulation with double-stranded RNA (dsRNA), a surrogate marker for viruses. 6. To examine the impact of allergic rhinitis with or without allergic asthma on the gene expression profiles of the upper and lower airway epithelium after stimulation with dsRNA.

7. To quantify the mutual relationships of blood eosinophils, exhaled nitric oxide (FENO) and serum periostin with sputum eosinophils by external validation in two independent cohorts of patients with mild to severe asthma. 8. To study and validate the relationship of breathprints analysed by a composite electronic nose (eNose) platform with sputum eosinophils in patients with mild to severe asthma.

General Introduction 11 Outline of this thesis

Chapter 2 addresses the concept of transcriptomics analysis by microarrays and next-generation RNA sequencing, including the strengths and limitations, and reviews breathomics as a patient-friendly method. In chapter 3 the transcriptomic profiles of isolated upper and lower airway epithelial cells are compared between patients with allergic rhinitis with or without concomitant asthma and healthy individuals. Chapter 4 describes the effect of dsRNA on the transcriptomic profiles of airway epithelial cells by comparing gene expression profiles of poly(I:C)-induced nasal and bronchial epithelial cells of patients with allergic rhinitis with or without concomitant asthma and healthy individuals.

In chapter 5 blood eosinophils, FENO and serum periostin are analysed as surrogate biomarkers for sputum eosinophils by external validation in two independent cohorts of patients with various severities of asthma. Furthermore, in chapter 6 breathprints obtained by a composite eNose are validated to predict sputum eosinophilia in asthma. Finally, in chapter 7 the main findings of this thesis and research implications are sum- marized and discussed.

12 Chapter 1 References

(1) Global Initiative for Asthma (GINA). Global (11) Bel EH, Wenzel SE, Thompson PJ, Prazma Strategy for Asthma Management and Pre- CM, Keene ON, Yancey SW, et al. Oral gluco- vention. http://www.ginasthma.org/ . 2012. corticoid-sparing effect of mepolizumab in (2) National Institutes of Health: National Heart eosinophilic asthma. N Engl J Med 2014 Sep LaBI. Expert panel report 3: guidelines for the 25;371(13):1189‑97. diagnosis and management of asthma. http:// (12) Ortega HG, Liu MC, Pavord ID, Brusselle GG, www.nhlbi.nih.gov/guidelines/asthma/. FitzGerald JM, Chetta A, et al. Mepolizumab 2007. treatment in patients with severe eosinophilic (3) Haldar P, Pavord ID, Shaw DE, Berry MA, asthma. N Engl J Med 2014 Sep 25;371(13): Thomas M, Brightling CE, et al. Cluster analysis 1198‑207. and clinical asthma phenotypes. Am J Respir (13) Corren J, Lemanske RF, Hanania NA, Korenblat Crit Care Med 2008 Aug 1;178(3):218‑24. PE, Parsey MV, Arron JR, et al. Lebrikizumab (4) Moore WC, Meyers DA, Wenzel SE, Teague WG, treatment in adults with asthma. N Engl J Med Li H, Li X, et al. Identification of asthma phe- 2011 Sep 22;365(12):1088‑98. notypes using cluster analysis in the Severe (14) Poste G. Bring on the biomarkers. Nature 2011 Asthma Research Program. Am J Respir Crit Jan 13;469(7329):156‑7. Care Med 2010 Feb 15;181(4):315‑23. (15) Jackson DJ, Sykes A, Mallia P, Johnston SL. (5) Simpson JL, Scott R, Boyle MJ, Gibson PG. In- Asthma exacerbations: origin, effect, and flammatory subtypes in asthma: assessment prevention. J Allergy Clin Immunol 2011 Dec; and identification using induced sputum. 128(6):1165‑74. Respirology 2006 Jan;11(1):54‑61. (16) Corne JM, Marshall C, Smith S, Schreiber J, (6) Wu W, Bleecker E, Moore W, Busse WW, Castro Sanderson G, Holgate ST, et al. Frequency, M, Chung KF, et al. Unsupervised phenotyping severity, and duration of rhinovirus infections of Severe Asthma Research Program partici- in asthmatic and non-asthmatic individuals: a pants using expanded lung data. J Allergy Clin longitudinal cohort study. Lancet 2002 Mar 9; Immunol 2014 May;133(5):1280‑8. 359(9309):831‑4. (7) Khan DA. Allergic rhinitis and asthma: (17) Contoli M, Message SD, Laza-Stanca V, epidemiology and common pathophysiology. Edwards MR, Wark PA, Bartlett NW, et al. Role Allergy Asthma Proc 2014 Sep;35(5):357‑61. of deficient type III interferon-lambda produc- (8) Togias A. Rhinitis and asthma: evidence for tion in asthma exacerbations. Nat Med 2006 respiratory system integration. J Allergy Clin Sep;12(9):1023‑6. Immunol 2003 Jun;111(6):1171‑83. (18) Sykes A, Macintyre J, Edwards MR, Del RA, (9) Petsky HL, Cates CJ, Lasserson TJ, Li AM, Turner Haas J, Gielen V, et al. Rhinovirus-induced C, Kynaston JA, et al. A systematic review and interferon production is not deficient in well meta-analysis: tailoring asthma treatment on controlled asthma. Thorax 2014 Mar;69(3): eosinophilic markers (exhaled nitric oxide or 240‑6. sputum eosinophils). Thorax 2012 Mar;67(3): (19) Wark PA, Johnston SL, Bucchieri F, Powell R, 199‑208. Puddicombe S, Laza-Stanca V, et al. Asthmatic (10) Korevaar DA, Westerhof GA, Wang J, Cohen JF, bronchial epithelial cells have a deficient Spijker R, Sterk PJ, et al. Diagnostic accuracy innate immune response to infection with of minimally invasive markers for detection rhinovirus. J Exp Med 2005 Mar 21;201(6): of airway eosinophilia in asthma: a systematic 937‑47. review and meta-analysis. Lancet Respir Med (20) Wheelock CE, Goss VM, Balgoma D, Nicholas 2015 Apr;3(4):290‑300. B, Brandsma J, Skipp PJ, et al. Application of

General Introduction 13 ‘omics technologies to biomarker discovery in (22) Collins GS, Reitsma JB, Altman DG, Moons infl ammatory lung diseases. Eur Respir J 2013 KG. Transparent Reporting of a multivariable Sep; 42(3): 802-25. prediction model for Individual Prognosis or (21) Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis Diagnosis (TRIPOD): the TRIPOD statement. CA, Glasziou PP, Irwig LM, et al. The STARD Ann Intern Med 2015 Jan 6; 162(1): 55-63. statement for reporting studies of diagnostic accuracy: explanation and elaboration. Ann Intern Med 2003 Jan 7; 138(1): W1-12.

14 Chapter 1 CHAPTER 2 Towards composite molecular signatures in the phenotyping of asthma

Ariane H. Wagener, Ching Yong Yick, Paul Brinkman, Marc P. van der Schee, Niki Fens, Peter J. Sterk

Ann Am Thorac Soc 2013;10 Suppl:S197-205 Abstract

The complex biology of respiratory diseases such as asthma is currently feeding the discovery of various disease phenotypes. Although the clinical management of asthma phenotypes by using a single biomarker (e.g. sputum eosinophils) is already very successful, emerging evidence shows the requirement of multi-scale, high-dimensional biological and clinical measurements in order to capture the complexity of various asthma phenotypes. High-throughput ‘omics’ technologies including transcriptomics, proteomics, lipidomics and metabolomics are increasingly standardized for biomarker discovery in asthma. The leading principle is obeying available guidelines on ‘omics’ analysis, thereby strictly limiting false discovery. In this review we first address the concept of transcriptomics using either microarrays or next-generation RNA sequencing and their applications in asthma, highlighting the strengths and limitations of both techniques. Next we review metabolomics in exhaled air (breathomics) as a non-invasive alternative for sampling the airways directly. These developments will inevitably lead to the integration of molecular signatures in the phenotyping of asthma and other diseases.

16 Chapter 2 Biomarker signatures

Respiratory diseases exhibit far from simple pathophysiology, which has hampered progress in this prominent medical field. The most prevalent respiratory diseases are chronic, exhibiting multiple pathogenetic mechanisms, various pathophysiological pathways in parallel and diverse clinical expressions. This complexity is not even stable and appears to vary during the course of these diseases. Inevitably, this leads to various disease phenotypes. It is increasingly recognised that capturing those phenotypes is a prerequisite for adequate assessment, monitoring and treatment. Nevertheless, most guidelines on chronic respiratory diseases are still based on establishing traditional diagnoses such as asthma and chronic obstructive pulmonary disease (COPD).

Complex phenotypes A phenotype can be defined as the composite of observable characteristics of an organ- ism, resulting from interaction between its genetic make-up and environmental influences, which is relatively stable but not invariable with time. This definition does not allow a strict separation between adapted (health) and non-adapted (disease) phenotypes. It merely provides the tools for a phenomenological description of living organisms in health or various diseased states. The physicist and Nobelist Erwin Schrödinger recognized about 70 years ago that life must be complex and non-linear, allowing emergent phenomena that might be interpreted healthy and disease states (1). Based on this non-linearity it can be predicted that it takes more than a few clinical and serum markers to capture the true biomedical entity and time fluctuations of complex diseases (2). This is likely to require multi-scale, high-dimensional biological as well as clinical measurements (3). For centuries clinicians have been familiar with integrating clinical information in health and disease (Table 1). When taking asthma as the example, single symptoms (e.g. wheezing) represent the cornerstone of the diagnostic process. Second, multiple disease features in combination (e.g. the asthma control questionnaire ACQ, or a Th2- high profile) are considered to be even more informative. And finally, the most valuable medical information relies on pattern recognition of composite information (e.g. exacerbation or inflammation). The latter pattern recognition is principally empiric and relies on repeated training and validation. All doctors feel they can establish an exacerbation of asthma, whilst after long efforts the definition of an exacerbation has only recently been distilled (4).

Biomarkers In general, the promise of delivering valuable cellular and molecular biomarkers to the clinic has not been met (5). Asthma seems to be amongst the exceptions to the rule, since sputum eosinophils appear to be predictive in guiding asthma treatment (6).

Composite Molecular Biomarkers in Asthma 17 Table 1. From single to composite biomarkers Single biomarker Biomarker panel Composite signature Molecular SNP Oxidative Genomics

FENO stress Transcriptomics Periostin Metabolomics Cellular Eosinophil FACS Differential counts Th2-high cell counts profile Histological Reticular Extracellular matrix Inflammation layer composition Remodelling thickness

Functional FEV1 Variable Exercise intolerance airways obstruction Clinical Wheezing ACQ Exacerbation From single to composite biomarkers: examples from respiratory research. Diseases and disease states are defined by combining various markers from the clinical level (bottom) towards the molecular level (top). Such disease markers can be derived from singular features (left), panels of combined disease markers (middle) or composite high-dimensional signatures or fingerprints (right). The latter are based on pattern recognition. Such composite patterns (e.g. an ‘exacerbation’) have been, and still are, clinically very effective in disease management. Based on the complex, non-linear biology in health and disease it can be postulated that composite molecular signatures will also provide more useful phenotypic information than singular molecular biomarkers.

SNP, single nucleotide polymorphism; FENO, fractional concentration of expired nitric oxide; FACS, fluores- cence-activated cell sorting; Th2, T-helper type 2 phenotype; FEV1, forced expiratory volume in one-second as measured by spirometry; ACQ, asthma control questionnaire.

What is hampering further progress in biomarker development? As indicated above, based on the complex non-linear underlying biology it can be predicted that personal ‘omics’ profiling is required to reveal medical phenotypes (7). Computational pattern recognition of such biomarker signatures will then be analogous to powerful clinical pattern recognition of complex entities (Table 1). Therefore, it can be envisaged that high-throughput ‘omics’ technologies will allow a step change in biomarker discovery and application in respiratory medicine (8). The first evidence that this approach can be successful in differential diagnoses is emerging (9). Subsequently, these technologies need to be applied in the subphenotyping of patients with airways diseases, such as asthma. The current requirement is to rigorously standardize the application and analysis of these ‘omics’ technologies in the discovery of biomarker signatures. Fortunately, there are recent recommendations available on the computational and staged validation of ‘omics’ biomarker signatures (10). This also includes strict strategies to limit false discoveries (11). It is envisaged that in this way biomarker signatures will gradually enter clinical medicine, and asthma phenotyping in particular.

18 Chapter 2 The current review focuses on the strengths and limitations of transcriptomics by microarrays and next generation RNA-sequencing. In addition, we will shortly address metabolomics in exhaled air as a patient-friendly option for the clinic.

Transcriptomics analysis by microarrays

Gene transcription is a determinant of the phenotypic manifestation. Measurement technologies for profiling RNA, using e.g. reverse-transcription PCR and Northern blots, have been available for years. But the ability of high-throughput quantification of the transcriptome (RNA transcripts) was first made possible by microarrays (12), and has been used successfully since with more than 40,000 citations in PubMed (13). Microar- rays are based on patches of short oligonucleotide probes which are complimentary to the studied transcripts. In brief, RNA is extracted from the material to be investigated and labeled with fluorescent dyes. The core principal is the hybridization of the studied transcripts to the array. Because the transcripts are fluorescently labeled, the light inten- sity scanned is a measure of gene expression. In this way, variations in gene expression of a large number of genes can be studied simultaneously. Since microarrays have been widely used by many groups, the increasing experience has revealed the limitations and biases of microarray data, which has led to adaptations in study design and analyses (13). After formulating the research question, the sample needs to be carefully selected and a power calculation must be performed beforehand (14). For conducting a study, new samples can be collected, though existing publicly available data can also be used to answer a specific research question, e.g. NCBI Gene expression Omnibus (GEO). Regardless of how the data is obtained, the original samples used need to correspond to the research question and to specific quality requirements which will be further discussed. First of all, the RNA quality has to be taken into account, because adjustments for variable and low quality RNA have been developed to extend sample suitability for analysis (15). Next, deviations in the sample collection and processing protocols can have large impact on the omics results. Although an accurate clinical design is the most important strategy to minimize varying factors among samples, normalization steps in the data analysis are mandatory to reduce external noise (16). In gene expression analysis, usually two different groups of tissue samples or conditions are compared, generating a huge amount of data with an expected large number of false positive results. Adjustment for multiple comparisons to control the false discovery rate (FDR) for differentially expressed individual genes is essential, with the Benjamini and Hochberg’s method (17) being the most popular form. Traditional statistical tests such as t-test or the Wilcoxon test have been replaced by newly developed tests that are more appropriate for the analysis of microarray data, such as the empirical Bayes

Composite Molecular Biomarkers in Asthma 19 test (18) that borrows information across genes. In addition, the change in gene expression is represented by the log fold change calculated. Although criteria for both p-value and fold change are more and more required to be taken into account for differentially expressed genes, and several approaches to this issue are suggested (19;20), there is no consensus yet as to the exact criteria. A gene that is statistically differentially expressed between two conditions with a larger fold change difference might not necessarily have a larger impact within a molecular pathway.

Interpretation Finally, the interpretation of the results is yet another challenge, because of the usual ‘overdoses’ of data generated. Cluster analysis is one way to reduce the data into subgroups of related genes in an unbiased way, though evaluation of the stability of the obtained clusters is needed (21). Commonly used examples of clustering are hierarchi- cal clustering, k-means clustering and self-organizing maps (22). Different from the analysis on individual gene differences, the analysis of gene signatures combines gene expression of a group of genes and can be used for disease prediction and phenotype discovery. Since many reported molecular signatures have failed reproducibility, specific statistical strategies and validation of a signature is of high importance to reduce false signature discovery (10). Furthermore, network-based approaches are attractive in view of studying function and relationships between genes, instead of studying individual genes. First of all, features can be mapped in known pathways, as used in the Gene Set Enrichement Analsysis (GSEA) (23). A list of known pathways is generated with assigned scores, referring to if the pathway is likely to be differentially expressed. Secondly molecular features can be mapped in more unbiased interaction networks, such as protein- protein or protein-DNA networks (Figure 1), showing closely connected genes within a pathway. More methods are available for analyzing gene expression data since this field is rapidly expanding (24). In pulmonary diseases transcriptomics analysis using microarrays have shown to be promising in biomarker discovery and to improve our understanding of the disease. Concerning biomarker discovery, gene expression profiling of epithelial brushings in asthma identified distinct subtypes of patients with mild to moderate asthma with a Th2-high or Th2-low phenotype (25). Subsequently, patients with severe asthma with high levels of periostin, corresponding to the Th2-high phenotype, appeared to be those who responded to anti-IL13 treatment (26). To examine mechanisms of disease pathogenesis, the effect of cigarette smoke on transcriptome patterns in bronchial epithelial cells of smokers with and without COPD revealed a role for oxidative stress responses in patients with COPD (27). We have recently used microarrays to study the upper and lower airway epithelium transcriptome of patients with asthma and healthy controls in response to a synthetic analog of viral dsRNA, and observed fewer genes differen-

20 Chapter 2 MMP9 MMP1

IL6

CCL5 IL8

TLR3

STAT5A

STAT1 CDK1

IL15 IRF1

Figure 1. Microarray data analysis Example of a direct interaction network (Genespring GX12) of genes differentially expressed in the upper airway epithelium of patients with asthma in response to ex-vivo dsRNA as obtained by microarray analysis (Affymetrix Human Genome U133+ PM Genechip Array). The figure shows connected genes (yellow dots) involved in the extracellular matrix, the cellular membrane, the intracellular compartment, and the nucleus (from top to bottom). The network analysis revealed a number of genes that were highly connected to other genes in the network. These highly connected genes, the key components in the network, are encircled and enlarged. MMP1, matrix metallopeptidase-1;, MMP9, matrix metallopeptidase-9; IL6, interleukin-6; IL8, interleukin-8; STAT5A, signal transducer and activator of transcription-5A; CDK1, cyclin-dependent kinase-1; IRF1, interferon regulatory factor-1; IL15, interleukin-15; STAT1, signal transducer and activator of transcription-1; TLR3, toll-like receptor-3; CCL5, chemokine ligand-5. tially expressed in asthma and a diminished response in the upper airways of patients with asthma as compared to controls (28). Furthermore, gene expression analysis has shown to improve our understanding of the mechanisms of treatment resistance. Gene profiling of bronchoalveolar lavage (BAL) cells of patients with corticosteroid-resistant (CR) asthma and corticosteroid-sensitive (CS) asthma identified genes supporting involvement of endotoxin (LPS) and classical macrophage activation in corticosteroid resistance in asthma (29).

Composite Molecular Biomarkers in Asthma 21 Taken together, microarray analysis of biological samples is providing highly useful data for hypothesis generating purposes in asthma. This technology may eventually also serve clinical subphenotyping, since already 3 subtypes related to both clinical asthma status and airway inflammation were identified by induced sputum gene expression profiles, including the inflammatory pathways involved (30). Table 2 summarizes the strengths and limitations of transcriptomics analysis by microarrays.

Transcriptomics analysis by Gene sequencing

With gene sequencing the sequence of the nucleotide bases that form the DNA is determined. Already in 1977 gene sequencing was introduced by Frederick Sanger (31). This first-generation sequencing method is also called the dideoxy or chain termination sequencing. In short, the template of the DNA molecule is copied repeatedly. Modified nucleotides, also called chain terminators, are added to the reaction, which will termi- nate the copy process when incorporated in the copied DNA. Due to the fact that copy- ing begins at a fixed location of the template DNA, but terminates randomly through the incorporation of chain terminators by chance, copy DNA with various lengths will be obtained. By comparing these DNA fragments also known as reads, the original DNA nucleotide sequence can be determined. In the meantime gene sequencing has undergone many technological advances resulting in the development of next-generation high-throughput gene sequencing techniques, which embroider on the Sanger method. One of the most powerful recent next-generation gene sequencing techniques is transcriptome sequencing (RNA-Seq), which allows a detailed characterization of gene expression profiles at the tissue level (32). Particularly in complex disorders such as asthma and COPD this technology has the potential to discover gene expression profiles that are characteristic of the disease and thus can improve our understanding of the cellular and molecular pathways involved in disease (33;34). In contrast to microarray chips, RNA-Seq allows an unbiased analysis of the transcriptome as it is not dependent on predefined probe sets and is therefore not limited to a selection of known genes or nucleotide sequences (13). Consequently, RNA-Seq facilitates the discovery and characterization of novel, disease-related genes. The workflow of a typical RNA-Seq process and the method used for the subsequent analysis of the sequence data are highly dependent on the research question. In general, the workflow for RNA-Seq can be divided into 3 steps. In the 1st step, RNA is isolated from which cDNA-libraries are constructed. Various methods can be used including the Ova- tion RNA-Seq System (NuGEN, San Carlos, CA, US), which has been successfully applied in our gene expression studies (34;35). This is followed by the actual sequencing of the

22 Chapter 2 Table 2. Strengths and limitations per technique Transcriptomics Transcriptomics Breathomics analysis by analysis by gene microarrays sequencing Strengths Maturity of experimental design and ✓ analyses High-throughput, quantitative gene ✓ ✓ analysis Low running costs ✓ ✓ (in comparison to (applies for RNA-seq) eNose) Unbiased, not bound to known gene ✓ transcripts High dynamic range for detection of very ✓ low or high expressed genes Requires only small amount of RNA ✓ Non-invasive method allowing ✓ measurements in infants and elderly Signals in asthma have demonstrated ✓ (49;54) adequate repeatability Design tailor made devices for specific ✓ diseases based on previous results Limitations Limited to known gene transcripts ✓ Enormous amount of clinically significant ✓ ✓ ✓ and insignificant data generated (in case of GC-MS) Sensitive processing with high technical ✓ background noise Extensive demand on bioinformatics ✓ (55) and – statistics for storage, processing analysis and interpretation Insufficient sequencing depth/coverage ✓ may hamper the interpretation High costs, although decreasing ✓ Time-consuming ✓ ✓ ✓ (in case of GC-MS) No international standard for sampling ✓ method eNose sensor signals are not identical ✓ between devices, complicating mapping of breathprints between centres This table summarizes strengths and limitations per reviewed technique. RNA-seq, transcriptome sequencing; eNose, electronic nose; GC-MS, gas chromatography mass spectrometry.

Composite Molecular Biomarkers in Asthma 23 Figure 2. Workflow RNA-Seq This figure shows the typical workflow of a RNA-Seq-study. The first step comprises the preparation of amplified and purified cDNA from the isolated RNA from the study samples. Next, libraries of cDNA are constructed, followed by the actual sequencing of the samples yielding sequence reads. The figure de- picted in step 1 shows a summary of the pyrosequencing chemical reaction, which forms the basis of the gene sequencing method by the GS FLX System (454/Roche). Millions of copies of a single clonal frag- ment are contained on each DNA capture bead (left). In the second step, the sequence reads are mapped against the reference DNA, e.g. the human genome, enabling the identification of the specific genes pres-

ent in the sequenced samples and the quantification of those genes. APS, adenosine 5’ phosphosulfate; PPI, pyrophosphate.

cDNA-libraries, which will yield sequence reads of various base pair (bp) lengths (Figure 2). In step 2, these reads are mapped to the reference DNA, e.g. the human genome. This enables identification of the specific genes that were present in the sequenced samples in step 1. Furthermore, it allows a quantification of those identified genes, because the more reads of a specific gene are present, the more that gene is expressed. One of the methods used for mapping is the consensus approach, which is in its concept similar to the serial analysis of gene expression (SAGE) method (33). In short, each sequence read is aligned with the reference genome. However, a sequence read may align to multiple locations of the reference genome due to their short bp length compared to the reference. To identify the actual site of origin in the reference genome, the sequence read is put together with other sequence reads that contain overlapping DNA sequences to undergo multiple alignments. This will result in the formation of a contig, which is a contiguous sequence constructed from many clone sequences (36). The eventual bp length of a contig will thus be determined by the length of the sequence tags with overlapping DNA sequences. With an overall longer bp length than the individual sequence tags with which it was constructed, the contig will point towards the actual site of origin

24 Chapter 2 when aligned to the reference genome. After it has been ascertained which genes were expressed in the sequenced samples, statistical analyses are performed during step 3. One way to analyse the data is to determine the function of an individual gene and associate it with the disease under investigation, e.g. asthma. Additionally, as already discussed above in the Interpretation section concerning microarray data, the set of differentially expressed genes can be used to identify gene networks by pathway analyses. These gene networks may clarify what biochemical processes are differently regulated leading to the manifestation of asthma. Next-generation high-throughput gene sequencing has become increasingly accessible for research and even clinical purposes mainly due to the significant increase in sample numbers that can be simultaneously sequenced, and decrease in costs and time needed to perform a sequencing analysis (37). Therefore, gene sequencing presents a multitude of possibilities to increase our understanding of many more complex diseases besides asthma and COPD (3;38). When applying gene sequencing, we have recently found 46 genes to be differentially expressed between endobronchial biopsies from asthmatics and controls. This included periostin, pendrin and BLC2 with 10 gene networks (34). The 3 networks with the highest network scores comprised: a) BLC2, MAPK1, NF-kB, p38MAPK, TGF-β, b) STAT3, periostin, STAU2, and c) EGFR and SLC26A4. In a second study we examined whether systemic glucocorticoids affect gene expression of bronchial smooth muscle in asthma, demonstrating 15 significantly changes genes (35). The changes in two of those appeared to be associated with accompanying changes in bronchial hyperresponsiveness, strongly suggesting that glucocorticoids also exert their beneficial effects through activity on bronchial smooth muscle. Hence, by implementing such a sophisticated state-of-the-art biochemical technology in characterizing a disease, breakthroughs in the treatment of diseases may be reached through the development of targeted therapies. Although RNA-Seq holds many advantages, there are also some drawbacks to this novel technique compared to e.g. qPCR methods. Table 2 points out both limitations and strengths of this technique.

Breathomics

Respiratory medicine is in a privileged position when it concerns non-invasive access to composite molecular samples. Exhaled breath contains a complex gas mixture of volatile organic compounds (VOCs) (39) as well as a composite of non-volatile compounds derived from exhaled breath condensate (EBC) (40). These metabolites are derived from both systemic and local metabolic, inflammatory and oxidative processes. The term ‘breathomics’ has recently been coined to cover metabolomics approaches in exhaled

Composite Molecular Biomarkers in Asthma 25 air. Even though multiple labs have had trouble in the validation of specific biomarkers in EBC (40), recent metabolomics strategies in EBC have been very successful. This includes metabolomics by NMR spectroscopy (41) as well as metabolomics by liquid chromatography and mass spectrometry (LC-MS) (42). Hence, ‘omics’ technologies have opened new avenues for EBC, which require stringent validation. The advantage for breathomics is likely to reside in the assessment of exhaled VOCs. The standard for detecting individual molecular compounds in a VOC mixture is gas chromatography mass spectrometry (GC-MS) (39). GC-MS has been employed in the discovery of biomarkers for inflammatory airway diseases, such as asthma (43) and COPD (44). The VOCs that have been associated with the presence of asthma, COPD or lung cancer are visualized in Figure 3. This shows that these diseases are characterized with partially overlapping combinations of multiple VOCs, thereby highlighting the need for establishing molecular signatures. Interestingly, in asthma and COPD the exhaled VOC profiles appear to be associated with the inflammatory phenotype (eosinophilic

Figure 3. Volatile organic compounds in pulmonary diseases Exhaled volatile organic compound associated with asthma, COPD and/or lung cancer. Compilation of data published in the literature. The lines between the compounds and the diseases represent associations published in the literature. The type of compound (hydrocarbons, aldehydes, ketones, alcohols, cyclic) is mentioned next to the compounds.

26 Chapter 2 or neutrophilic) (44;45). This suggests that breathomics is suitable for non-invasive subphenotyping of inflammatory airway diseases. Pattern recognition of exhaled VOCs can also be accomplished by electronic noses. Electronic noses (eNoses) are based on arrays of nano-sensors that capture various combinations of VOCs, which allows exhaled air fingerprinting (breathprints) rather than identification of individual chemical constituents (46;47). The nano-sensors are sensi-

Figure 4. Breathprint Spider chart of the breathprints of exhaled air collected from 1 patient with severe asthma and 1 healthy control. The exhaled air is analysed by a composite eNose platform that integrates different types of eNoses to measure breathprints in parallel, developed for the U-BIOPRED group. The platform array consists of 190 sensors from 4 different types of eNoses using: 1) carbon-polymer sensors, 2) quartz microbalance metalloporphyrins sensors, 3) metal oxide semiconductor sensors, and 4) field asymmetric ion mobility spectrometry. Every marker in the chart is the signal of one sensor. The signals of the 190 sensors are dis- played, normalized towards an arbitrary unit at a scale between 0 (centre) and 100 (outer circle). The different breathprints of the two subjects can be distinguished.

Composite Molecular Biomarkers in Asthma 27 tive to partly overlapping fractions of the VOC mixtures (breathprint) and are based on conducting polymers, metal oxide, metal oxide field effect transistors, surface or bulk acoustic waves, optical sensors, colorimetric sensors, ion mobility spectrometry, infrared spectroscopy, gold nanoparticles, and GC-MS (Figure 4) (46). The pattern recognition algorithms require training and validation and provide probabilistic evidence in favour of (positive predictive value) or against (negative predictive value) particular medical conditions. Such probabilistic evidence is well suited for clinical diagnostics, phenotyping and monitoring, making eNoses a potentially cheap and real-time metabolomics tool in the clinic. The research application of breathomics in (respiratory) medicine is rapidly expanding, in particular in infectious diseases, lung cancer and airway diseases (47;48). When focusing on asthma, studies conducted by GC-MS or various eNose sensor systems indicate that asthmatics can be discriminated from healthy controls with accuracies between 80-100% (49). Interestingly, asthma patients can also be discriminated from those with COPD. When selecting the non-overlapping extremes amongst patients with a gold-standard diagnosis of asthma or COPD the accuracy by eNose reached 95% (50). Subsequently, when allowing overlap between patients with asthma and COPD (both featuring fixed airflow limitation) the accuracy of separating the two diseases by eNose remained 88% (51). Such external validation in newly recruited (overlapping) patients from different hospitals is essential for limiting the false discovery rate and establishing diagnostic accuracy (10;11). With regard to the capabilities of eNoses to phenotype patients with asthma, preliminary data indicate that eosinophilic and non-eosinophilic asthma can be discriminated when using a composite eNose platform that integrates different types of eNoses in parallel (52). And notably, in a recent study focusing on the prediction of oral glucocorticoid responsiveness amongst patients with asthma, eNose measurements performed even better than sputum eosinophils (53). This suggests that composite molecular signatures can perform better than single biomarkers in the phenotyping of patients with asthma. As indicated above, this may not be surprising. Table 2 summarizes the strengths and limitations of breathomics.

Conclusions

When considering the complex biology of health and disease it can be envisaged that composite molecular fingerprints have the best prospect as biomarkers in the phenotyping of patients. Indeed, recent application of ‘omics’ technologies (e.g. transcriptomics, breathomics) has not only provided signatures of asthma but also of relevant subphenotypes of the disease. For signature discovery, the current state-of-the-art method is transcriptomics analysis using microarrays, especially because of its maturity

28 Chapter 2 of experimental design and analysis, and available data for comparisons and validation. Though, because RNA sequencing enables higher dynamic detection ranges and a more unbiased analysis, this method will eventually be preferable when costs have decreased and experience has increased. Breathomics is a none-invasive method with diagnostic potential. However, sampling methods and devices need to be standardized to enable comparisons with other centers and validate results. Each of the applied platforms has its strengths and limitations that need to be taken into account in each and every study. The leading principle for this is obeying available guidelines on the process of molecular signature discovery in medicine, thereby strictly limiting false-positive results (10;11). This will inevitably lead to the integration of molecular signatures in the phenotyping of asthma and other diseases (3;7;8).

Composite Molecular Biomarkers in Asthma 29 References

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32 Chapter 2 CHAPTER 3 The impact of allergic rhinitis and asthma on human nasal and bronchial epithelial gene expression

Ariane H. Wagener, Aeilko H. Zwinderman, Silvia Luiten, Wytske J. Fokkens, Elisabeth H. Bel, Peter J. Sterk, Cornelis M. van Drunen

PLoS One 2013;8(11):e80257 Abstract

Background The link between upper and lower airways in patients with both asthma and allergic rhinitis is still poorly understood. As the biological complexity of these disorders can be captured by gene expression profiling we hypothesized that the clinical expression of rhinitis and/or asthma is related to differential gene expression between upper and lower airways epithelium.

Objective Defining gene expression profiles of primary nasal and bronchial epithelial cells from the same individuals and examining the impact of allergic rhinitis with and without concomitant allergic asthma on expression profiles.

Methods This cross-sectional study included 18 subjects (6 allergic asthma and allergic rhinitis; 6 allergic rhinitis; 6 healthy controls). The estimated false discovery rate comparing 6 subjects per group was approximately 5%. RNA was extracted from isolated and cultured epithelial cells from bronchial brushings and nasal biopsies, and analyzed by microarray (Affymetrix U133+ PM Genechip Array). Data were analysed using R and Bioconductor Limma package. For gene ontology GeneSpring GX12 was used.

Results The study was successfully completed by 17 subjects (6 allergic asthma and allergic rhinitis; 5 allergic rhinitis; 6 healthy controls). Using correction for multiple testing, 1988 genes were differentially expressed between healthy lower and upper airway epithelium, whereas in allergic rhinitis with or without asthma this was only 40 and 301 genes, respectively. Genes influenced by allergic rhinitis with or without asthma were linked to lung development, remodeling, regulation of peptidases and normal epithelial barrier functions.

Conclusions Differences in epithelial gene expression between the upper and lower airway epithelium, as observed in healthy subjects, largely disappear in patients with allergic rhinitis with or without asthma, whilst new differences emerge. The present data identify several pathways and genes that might be potential targets for future drug development.

34 Chapter 3 Introduction

Asthma and rhinitis are highly prevalent and interrelated diseases (1). The nature of this relationship is still poorly understood, although similar mechanisms driving the inflammatory process have been postulated (2;3). According to the updated Allergic Rhinitis and its Impact on Asthma (ARIA) – World Health Organisation (WHO) workshop, one of the main challenges in the field of allergic diseases such as rhinitis and asthma is to capture their complexity through unsupervised approaches (1). Such approaches may identify mechanistic pathways that allow the development of personalized medicine in these co-morbid diseases. Although the majority of patients with asthma and rhinitis can be successfully treated with standard therapy, not all patients can be controlled with current treatments. The efficacy of treatment might increase by developing new medications that specifically target mechanisms upstream to disease-specific pathways as opposed to current therapies that are mostly directed to downstream effector molecules and/or cells. The airway epithelium is appreciated to play a key role in the regulation of airway inflammation and immune responses (4-6). Epithelial cells are the first cells that encounter environmental triggers, including pathogens and allergens, and are targets for inhaled therapies. Therefore, thorough understanding of epithelial activity as intermediate between environment and immune system is needed in patients with allergic rhinitis, allergic asthma and controls (7). Gene expression profiling is the most widespread application of unsupervised analysis of complex diseases (8;9). Gene expression profiling is well suited for identifying genes involved in the pathogenesis of inflammatory diseases such as asthma and rhinitis. Expression profiles of bronchial epithelial cells have already been used to classify subjects with asthma on the basis of high or low expression of IL-13-inducible genes (10), and similarly to identify genes involved in environmental determinants in asthma (11). Furthermore, clear differences in expression pattern were found between nasal epithelial cells isolated from healthy and allergic individuals at baseline and between their responses to allergen exposure (12). In this study we have analysed the expression profiles of airway epithelial cells of upper and lower airways in single individuals. We hypothesized that 1) differences in gene expression profiles between upper and lower airway epithelium provide insight into organ specific activity in allergic rhinitis and asthma, and that 2) defining the molecular processes in airway epithelia derived from patients with allergic rhinitis and/or allergic asthma will identify possible mechanisms of interaction. To that end, we compared the gene expression profiles between upper and lower airway epithelium in healthy individuals and studied the impact of allergic disease on these profiles by examining the

Gene Expression of Airway Epithelium 35 differences of these profiles with those in patients with allergic rhinitis with or without concomitant allergic asthma.

Methods

(see the Methods section of the Supporting Information File)

Ethics Statement The study was approved by the hospital Medical Ethics Committee of the Academic Medical Centre in Amsterdam, and the study was registered in the Netherlands trial register (www.trialregister.nl) with identifier NTR2125. All patients gave written informed consent.

Subjects This study included 18 subjects (>18 y) divided into three groups: 1) 6 patients with persistent, moderate to severe allergic rhinitis (13) and intermittent or mild persistent asthma (14), 2) 6 patients with persistent, moderate to severe allergic rhinitis (13) without asthma and 3) 6 healthy controls. Patients with allergic rhinitis had nasal symptoms for more than 4 days a week during more than 4 consecutive weeks (13). Patients with

asthma had episodic chest symptoms with airway hyperresponsiveness (PC20 methacholine ≤ 8 mg/mL) (15) according to the standardized tidal volume method (16). Al- lergic status was based on the presence of a positive skin prick test response (>3mm wheal) to common allergens. All patients with asthma and/or rhinitis were sensitized to at least one allergen. Patients had refrained from using any medication for their asthma, rhinitis or allergy in the four weeks prior to the visit when biopsies and brushings were taken. Healthy controls had no previous history of lung disease, had normal spirometric

results without airway hyperresponsiveness (PC20 methacholine > 8 mg/mL) and were not allergic. None of the subjects were current smokers, had smoked within 12 months prior to the study, nor had a smoking history of ≥5 pack years. Subjects did not have any signs of a respiratory infection at the time of study visits. In the case of a respiratory infection, a 6-week recovery period was taken into account.

Design This study had a cross-sectional design with two study visits. At the first visit, subjects were screened for eligibility with inclusion and exclusion criteria. At the second visit, at least 14 days after the first visit, a fiberoptic bronchoscopy was performed using 1% lignocaine for the local anaesthesia of the larynx and lower airways during which 4

36 Chapter 3 bronchial brushings were taken. Subsequently, 4 nasal biopsies were taken from the lower edge of the inferior turbinate. Local anaesthesia was achieved by application of adrenalin and cocaine under the inferior turbinate without touching the biopsy site.

Primary epithelial cell culture and microarray Affymetrix Primary nasal and bronchial epithelial cells were isolated from nasal biopsies and bronchial brushings and cultured. RNA was isolated and Human Genome U133+ PM Genechip Array (Affymetrix inc., Santa Clara, CA, USA) was used for microarray analysis of genes. See the Methods section of the Supporting Information File for a detailed description of the primary epithelial cell culture, RNA extraction, and Microarray Affymetrix U133+ PM.

Microarray data analysis and statistics Array images were analyzed by Affymetrix Expression Console using the robust multichip analysis (RMA) algorithm. The normalized data were further analysed using R (version 2.9) and the Bioconductor Limma package (17). Statistical analysis for assessing the differential gene expression was performed using the eBayes function to calculate moderated paired t-statistics after the linear model fit. All p-values were adjusted for false discovery rate correction (18). All probe sets were included in the analysis. The full microarray data was uploaded to the Gene Expression Omnibus (GEO) with accession number GSE44037. Gene ontology (GO) was done using GeneSpring GX12 (Agilent Technologies, Am- stelveen, The Netherlands), which we used with subsets to investigate the overrepresentation of gene ontology groups (p-value<0.05, adjusted for multiple testing by Benjamini-Yekutieli (19)). Cluster analysis was done on all probe sets that were significantly differentially expressed between upper and lower airways (excluding probe sets that showed a lower than 2 fold difference in the healthy airway) by transforming the means of the expression values for a gene in the six groups (healthy, rhinitis, rhinitis and asthma, upper or lower airways) to Z-scores and using unsupervised K-means clustering. The latter was applied to differentiate patterns of gene expression between the six groups. Furthermore, network analysis was performed on the same set of genes using NLP Network Discovery (GeneSpring GX12, Agilent Technologies, Amstelveen, The Netherlands) that derives its relations from PubMed. A direct interaction network was built that captures relations based on regulation, connecting the genes entered into the programme. The sample size was estimated with a custom made algorithm for microarray studies published previously (20). In order to calculate the sample size, data from two studies were applied (12;21). With 18 patients in total, comparing three groups of 6 subjects,

Gene Expression of Airway Epithelium 37 and a significance level of 0.0001, this study had a False Discovery Rate of approximately 5% for detecting at least a 1.5-fold difference in gene expression.

Results

Nine differentially expressed genes identified from the results of these microarray experiments were validated by independent real time PCR on the same starting material used for the microarray analysis (see the Results section, Table S1 and Figure S1 of the Supporting Information File).

Differential gene expression in nasal and bronchial epithelium Successful gene expression profiling was obtained in paired nasal and bronchial epithelium samples of 6 healthy controls, 5 patients with allergic rhinitis (1 patient was removed because of insufficient RNA in the nasal sample), and 6 patients with both allergic rhinitis and allergic asthma. The baseline characteristics of the subjects included in the study are presented in Table 1. Using the p-value adjusted for multiple testing (< 0.05), we identified 1988 genes (2705 out of 41976 probe sets) of which differential expression was statistically significant between healthy nasal and healthy bronchial epithelium, 301 genes between nasal and bronchial epithelium of patients with allergic rhinitis, and 40 genes between nasal and bronchial epithelium from patients with allergic rhinitis and asthma (see the Results section, Table S2, Table S3, Table S4, Table S5, Table S6 and Table S7 of the Supporting Information File). Notably, in patients with allergic rhinitis, with or without concomitant asthma, significantly fewer genes were differentially expressed between upper and lower airways as compared to healthy controls (see Figure 1).

Table 1. Baseline characteristics Allergic Asthma Allergic Rhinitis Healthy & Rhinitis N=6 N=5 N=6 Age* 24 (20-25) 24 (22-26) 26 (21-30) Female gender (n) 6 3 5

Prebronchodilator FEV1% predicted† 102 (11.4) 112 (12.8) 111 (9.3)

PC20‡ 0.4 (0.3) 1.17 (0.05) >16** * Median (range) † Mean (Standard Deviation) ‡ Geometric Mean (Geometric Standard Deviation) **No 20% drop in FEV1 at highest concentration of Methacholine 16 mg/mL

38 Chapter 3 Figure 1. Venn diagram Venn diagram of the significantly differentially expressed genes between upper and lower airways.

Functional characterization of expression differences between upper and lower airways Among genes with significantly higher expression in healthy bronchial epithelial cells as compared to healthy nasal epithelial cells, there was significant enrichment of the Gene Ontology (GO)-classes receptor activity, enzyme binding, cell communication, and developmental process (see Table S8 of the Supporting Information File). Among genes with higher expression in healthy nasal epithelium, the GO-classes cell adhesion, calcium ion binding, and epithelial cell differentiation (see Table S9 of the Supporting Informa- tion File) were significantly enriched. In patients with allergic rhinitis alone, amongst the genes with higher expression in bronchial epithelial cells, the GO-class regulation of signal transduction was enriched (see Table S10 of the Supporting Information File) and in the group of genes with higher expression in nasal epithelial cells, the GO-class metal ion binding was enriched (see Table S11 of the Supporting Information File). None of the 40 genes that were differentially expressed between the upper and lower airways of patients with both allergic rhinitis and asthma could be assigned to any GO-class.

Refining the patterns of differential gene expression The differences in expression of genes between upper and lower airways were less prominent in patients as compared to controls. By minimizing within-cluster variance and maximizing between-cluster variance, the K-means clustering grouped genes in 9 clusters based on their expression pattern in healthy, allergic rhinitis and allergic asthma patients (see Figure 2). To get more insight whether these clusters were linked to specific molecular functions, we investigated whether the genes in these clusters were significantly enriched for any Gene Ontology-classes. See Table S12 of the Sup- porting Information File for the following results. Clusters 1, 3, 7 and 9 consist mainly of genes that are differentially expressed in healthy controls. For genes in cluster 1 we

Gene Expression of Airway Epithelium 39 Figure 2. K-means clustering Every three figures per row represent one cluster. The cluster is mentioned above the first figure. Every first figure are results for healthy subjects; every second figure for patients with rhinitis only; every third figure for patients with both asthma and rhinitis. B, expression level in bronchial epithelium; N, expression level in nasal epithelium.

40 Chapter 3 Figure 2. K-means clustering (continued)

Gene Expression of Airway Epithelium 41 Figure 2. K-means clustering (continued)

42 Chapter 3 found the GO-class developmental process enriched, for cluster 3 the classes peptidase regulator activity and epidermis development, and for cluster 7 immune response. Clusters 2, 4 and 5 consist of a mix of genes that are differentially expressed in healthy controls, in allergic rhinitis and overlap between these 2 groups. For genes within cluster 4 the GO-class anatomical structure morphogenesis was enriched and for cluster 5 we found several family members of UDP-glucuronosyltransferases belonging to the GO-class of retinoic acid binding. Finally, clusters 6 and 8 consist mainly of genes that are uniquely differentially expressed in patients with allergic rhinitis. No GO-class was significantly enriched among the genes belonging to clusters 2, 6, 8 and 9.

The regulatory network of the expression differences Network analysis revealed a number of genes that were connected to more than 5% of the other genes in the network (hubs) (see Figure 3). This implies that a substantial part of the genes in the network are linked to hub genes that have been studied themselves in relation to signal transduction and remodelling in allergic asthma (EDN1, IL8, STAT1, JAK2), and genes that are involved in development and differentiation (RUNX2, WNT5A, EPHB2, CDKN2A) (22-28). In the upper right-hand corner of the network, a group of linked transcription factors can be identified (FOXP2, FOXA1, FOXA2, NKX2-1, GATA6, SPDEF, FOXD1, CITED2, SFRP1), several of which are known to be involved in lung development (29). Furthermore, surrounding hubs EDN1, JAK2 and IL8 a remarkable number of cytokines can be identified (CXCL1, CXCL2, CXCL5, CXCL10, CXCL11, CXCL17, IL11, IL24, IL33).

Discussion

This study shows that in healthy individuals substantial differences exist in gene expression between the epithelia from upper and lower airways but that these differences are smaller in patients with allergic rhinitis and almost disappear in those with concomitant allergic asthma. Hence, we observed influence of disease on the patterns of gene expression in upper and lower airways. Genes that are influenced by allergic rhinitis and asthma are linked to genes known to be involved in lung development, remodelling, regulation of peptidases, and normal epithelial barrier functions. Additionally, new players are identified. The gene expression patterns in the epithelia of upper and lower airways suggest that allergic inflammation of the upper airways also affects the lower airways. To our knowledge, this is the first study that extensively profiles gene expression of the combined upper and lower airways epithelium by microarray in healthy individuals and patients with allergic rhinitis, either with or without allergic asthma. Some studies have investigated upper and lower airway epithelium but these have been limited to the

Gene Expression of Airway Epithelium 43 Regulation interaction network 3. Regulation interaction igure F Colours correspond to the Venn diagram (Figure 1): yellow genes, healthy specific;green genes, allergic rhinitis specific; blue genes, allergic rhinitis & asthma specific; rhinitis & asthma. and allergic healthy overlap genes, rhinitis; red and allergic healthy overlap purple genes,

44 Chapter 3 impact of smoking (30;31) and cystic fibrosis (32). Previously, our group has focused exclusively on primary nasal epithelial cells from (house dust mite) allergic rhinitis patients (12) and on the effect of different allergens on a lung epithelial cell line (33;34). Similar to these previous experiments, we chose to isolate and culture epithelial cells, thereby eliminating contamination of the gene expression profiles by other (inflammatory) cell- types. Our study may have some limitations. Firstly, even though relative small sample sizes are commonly used in these kind of studies (35), it will affect the outcome of our study. Notwithstanding that our current application of a correction of multiple testing allowed the identification of many differentially expressed genes, a larger sample size would obviously have allowed capturing of even smaller differences. In addition, the group of patients with allergic rhinitis included five patients, whereas the other groups contained six patients. This leads to reduction of power of the paired t-test, and therefore the number of significantly differentially expressed genes in the allergic rhinitis group is underestimated as compared to the two other groups. Therefore, we randomly excluded one sample from each of the other two groups, resulting in a reduction of the number of significant probe sets by on average 700. When applying this correction to the results of the allergic rhinitis group, we might expect to have found 1081 probe sets if we had six samples. However, these results show that patients with allergic rhinitis still have significantly less genes differentially expressed between upper and lower airways as compared to healthy controls (1081 versus 2705 probe sets, respectively). To further mitigate these possible effects, we have used the power of our design to focus our analysis on paired differences between upper and lower airways in single individuals rather than differences between nose or lung between individuals of different groups. In addition to the original power calculation mentioned in the Method section, the Ben- jamini and Hochberg correction for multiple testing was applied because of the model used. This correction uses a smaller significance level, inevitably reducing the power of the analysis. But it primarily limits the risk of false positive differentially expressed genes between upper and lower airways. Furthermore, there was a difference in the distribution of gender and age between the groups that may have had an effect on the results. Therefore, we re-analyzed the data for associations with gender and age. In nose and bronchial epithelium, expression of 50 and 42 probe sets, respectively, was significantly associated with sex and none of the probe sets was significantly associated with age for neither nose nor bronchial epithelium. Furthermore, the difference between nose and bronchial expression per probe was not significantly associated with neither sex nor age for any probe (data not shown). Finally, we cannot ensure that the expression profile observed after epithelial cell culturing was fully preserved as compared to the expression in vivo. Alternative procedures to obtain epithelial cells such as laser capture or direct measurement after isolation might

Gene Expression of Airway Epithelium 45 mitigate these effects of cell culturing, but could introduce new biases introduced by contamination by other cell types and/or the (enzymatic) isolation procedure itself. However, as we compared epithelial cells from the same individuals, culturing of these cells has probably affected nose and lung epithelial cells in a similar fashion, thereby reducing a possible bias. A major finding of our study is the impact of allergic disease, in particular allergic rhinitis, on the differences in epithelial gene expression between upper and lower airways. In the patients with allergic rhinitis, many of the differences between the epithelia of upper and lower airways have disappeared as is shown by Figure 1. This may be expected in case of increased variation of gene expression in the nasal epithelium induced by either up or down regulation. However, according to clusters 3, 6, 7, 8 and 9 of the K-means clustering the gene expression is altered in the lower airways of patients with allergic rhinitis. Hence, although allergic rhinitis is phenotypically restricted to the upper airways, it does impact the lower airways as well. As all of the allergic asthma patients in the present study suffered from allergic rhinitis as well, it is not surprising that also in these patients the majority of differences between upper and lower airways have disappeared as observed in Figure 1. A previous study by our group on changes in gene expression of upper airway epithelium in response to house dust mite showed less changes in patients with allergic rhinitis as compared to controls (12). This absence of differentially expressed genes in allergic rhinitis was explained by the presence of an activated state before stimulation. Fewer differences in gene expression between upper and lower airway epithelium in allergic disease could also be explained by this principle, showing an activated state of genes in both upper and lower airways and thereby diminishing differences. Genes belonging to K-means cluster 3 that were differentially expressed between healthy upper and lower airways are linked to the GO-class regulation of peptidase activity. This suggests that parts of the differences between healthy upper and lower airways is attributed to the genes of this cluster, and that both allergic rhinitis with or without asthma affect these healthy differences in gene expression between upper and lower airways. These results fit in with an imbalance between peptidase inhibitors and peptidases in asthma that influence inflammation in the airways (36). The peptidase inhibitor PI3 is one of these genes in cluster 3, which has previously been shown to preserve airway epithelium integrity during inflammation (37). Furthermore, mutations in the serine peptidase inhibitor SPINK5 have been associated with asthma (38) and SPINK5 was suggested to play a role in mucin production [(39). UDP-glucuronosyltransferase genes in cluster 5 were differentially expressed between healthy upper and lower airways. These genes have not previously been linked to allergy. However, due to their ability to bind retinoic acid, they could be part of the mechanism by which retinoids influence immune regulation (40).

46 Chapter 3 In our study, the regulation interaction network showed several interconnected transcription factors of which the Forkhead family members (FOXP2, FOXA1, FOXA2), NKX2-1, and GATA6 are known to be involved in lung development [29]. The majority of these transcription factors are only different in expression between healthy upper and lower airways (see Figure 3: yellow), and not in allergic rhinitis with or without asthma. These results support the hypothesis that the different embryologic origins of the nose and bronchi genes involved in the development might be responsible for the differences observed in remodelling between the nose and bronchi in asthma and rhinitis (41). In the adult lung NKX2-1 was shown to inhibit aeroallergen-induced airway mucous cell metaplasia, in part, by the inhibition of SPDEF and by maintaining expression of FOXA2. Moreover, reduced expression of airway epithelial FOXA2 and NKX2-1 expression was observed in patients with asthma (42;43). In the upper left-hand corner of the network (Figure 3) SPINK6, SPINK5, KLK5, and KLK8 are shown linked to each other, which have been suggested to be involved in the main- tenance of normal epithelial barrier functions (44). These genes are different in expression between healthy upper and lower airways alone, and therefore imply an altered expression in patients with allergic rhinitis with or without asthma. Focusing on the genes that act as hubs in the gene interaction network, EDN1, IL8, WN- T5A, EPHB2 and CDKN2A are all genes that attribute to the normal differences between healthy upper and lower airways (see Figure 3: yellow) Therefore, they are affected by allergic rhinitis with or without asthma. Previously, EDN1 was found increased in the airway epithelium of patients with asthma (45) where it may play a role in airway remodelling (22). EPHB2 was found to be overexpressed in the lung in response to LPS and was suggested to contribute to the disruption of the epithelial barrier (46). Our results confirm an influence of disease on the expression of EDN1 and EPHB2. Although RUNX2 is a widely expressed transcription factor, RUNX2 might be a new gene in the field of allergy, since its function now is only well understood in bone development (23). Interestingly, IL33 is found in the network, which was differentially expressed between upper and lower airways of patients with allergic rhinitis with asthma. Like TSLP and IL25 (which were not differentially expressed between upper and lower airways), more recently IL33 is known to be an epithelial cytokine that induces TH2-associated cytokines and is suggested to function as an endogenous ‘alarmin’, to alert the immune system in response to tissue injury or infection (47;48). Previously, high levels of IL33 have been observed in the bronchial epithelium from patients with asthma when compared with healthy controls (49). The currently observed disease-related differences in gene expression between upper and lower airways may have clinical implications. First, these results help to understand the mechanism of the mutual interaction between asthma and rhinitis, for which there

Gene Expression of Airway Epithelium 47 is considerable clinical evidence. Secondly, the current analysis identified several new genes and pathways that might be potential targets for treatment of patients with combined upper and lower airway disease. It provides the opportunity to increase treatment efficacy by targeting the mechanisms upstream of the classic Th2-driven pathways. In conclusion, we have shown that there are significant differences in gene expression between the upper and lower airway epithelium of healthy individuals and that the number of differences is significantly less in patients with allergic rhinitis with or without asthma. Moreover, allergic rhinitis seems to influence epithelial gene expression in both the upper and lower airways. Our unbiased approach has confirmed the role of some genes that have been previously described, but also identified new genes. This data represents the first step in understanding how epithelial differences (and similarities) may affect the interaction of local mucosal tissues with environmental factors, and the molecular link between the upper and lower airways in allergic rhinitis and asthma.

48 Chapter 3 References

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Gene Expression of Airway Epithelium 51

CHAPTER 3 Supporting Information File The impact of allergic rhinitis and asthma on human nasal and bronchial epithelial gene expression

Methods

Primary epithelial cell culture Primary cells were obtained by first digesting the biopsies and brushings with collagenase 4 (Worthington Biochemical Corp., Lakewood, NJ, USA) for 1 hour in Hanks’ balanced salt solution (Sigma-Aldrich, Zwijndrecht, The Netherlands). Subsequently cells were washed with Hanks’ balanced salt solution (HBSS) and resuspended in bronchial epithelial growth medium (BEGM) (Invitrogen, Breda, The Netherlands) and seeded in one well of a 6 wells plate. Cells were grown in fully humidified air containing 5% CO2 at 37°C, and culture medium was replaced every other day. Cells were cultured to 80% confluence and were pre-incubated with bronchial epithelial basal medium (BEBM) for 48 hours prior to the removement of supernatant and RNA extraction. For bronchial epithelial cells it took 14 days on average, and for nasal epithelial cells it took 24 days on average to grow to 80% confluence. There was no difference in time of culture between the three subject groups.

RNA extraction Total RNA from each sample was extracted using Trizol (Life Technologies Inc., Gaiters- burg, MD, USA) using manufacturer’s protocol, followed by purification by nucleospin RNA II (Machery-Nagel, Düren, Germany). RNA concentration of all samples was measured on the nanodrop ND-1000 (NanoDrop Technologies Inc., Wilmington, DE, USA). The quality of the RNA was checked by using Agilent 2100 bio-analyser (Agilent Technologies, Palo Alto, CA, USA). All RIN scores were ≥9.5.

Microarray Affymetrix U133+ MP Human Genome U133+ PM Genechip Array (Affymetrix inc., Santa Clara, CA, USA) representing more than 47,000 transcripts and variants, including over 33,000 well- characterized genes, was used in the analysis of the genes. The MicroArray Department (MAD) of the University of Amsterdam, a fully licensed microarray technologies centre for Affymetrix Genechip® platforms, performed the technical handling and the quality control of the microarray experiments. The quality of the images was checked by visual inspection and all raw data passed quality criteria based on borderplots, pseudocolor slide images, RNA degradation plots, box and density plots, RI plots (against a pseudoreference), correlation and PCA plots.

NLP network discovery Network analysis was performed on the same set of genes using NLP Network Discovery (GeneSpring GX12, Agilent Technologies, Amstelveen, The Netherlands) that derives its relations from PubMed. A direct interaction network was built that captures relations

Gene Expression of Airway Epithelium 55 based on regulation, connecting the genes entered into the programme. In more detail, the majority of relations in the GeneSpring Interaction database are derived using a Natural Language Processing (NLP) algorithm that runs on published Medline abstracts. NLP is based on a ‘‘deep parsing” method and is driven by an elaborate sentence grammar that maximizes accuracy and has control over different aspects of a sentence without compromising recall. The NLP system operates on a sentence-by-sentence manner and extracts only those relations that are completely within a sentence. There are four main phases: 1) Entity recognition by consulting entity dictionaries, taking into account that there are variations in how terms appear in literature. 2) Using a set of rules, the syntactic tree structure of the sentence is derived using context free grammar rules for English, breaking up the sentence into its underlying linguistic constituents and capturing the functional roles of different parts of the sentence. 3) A semantic analysis mapping all words of interest to semantic concepts and identifying which entity regulates another entity using the sentence structure imposed by the syntax tree. The relationships captured by the semantic tree are only direct relationships (finds relations that connect the selected entities by the previous NLP system). 4) Semantic interference: the semantic tree captures specific concepts from a sentence after which GeneSpring has to make inferences across these semantic concepts, using agents in one relationship to fill the missing holes in other relationships. GeneSpring extracts relations by searching the resulting semantic network for relation nodes that contain all the required arguments. A signature is created for each relation depending upon the participants, their roles, and their mechanisms, and references to the relation are added. The relationships captured by the semantic tree are only direct relationships, which find relations that connect the selected entities by the NLP system that was previously explained. The relation represents molecular interactions between the entities and is characterized by a set of participating entities. We used Regulation as relation, which is the most basic relation type. In GeneSpring an entity A ‘‘regulates” another entity B, if A has some influence on B. The participant entities in the Regulation relation are ‘‘regulator”, ‘‘target”, and ‘‘modulator”. Each participant either has a positive, negative, or unknown effect. Depending on the source of the relation information, each relation is assigned a Rela- tion score. This property indicates a confidence matrix on the quality of relations in the Interaction Database in GeneSpring. NLP-derived relations are graded on a scale of 1-9, the best being 9 and the weakest being 1. The score properties are internally calculated

56 Chapter 3 based on the number of references and the syntax of the sentences. We used 9 as Rela- tion score for our network discovery.

Real-time polymerase chain reaction and analysis Quantitative real-time PCR was used to validate the differential expression of selected genes. We chose a set of genes that represent a complete range of fold change values, capturing genes that were either higher expressed in the upper or lower airways. PCR was performed on Bio-Rad CFX96 real-time PCR detection system (Bio-Rad, Veenendaal, The Netherlands). SYBR® Green primer sequences for IL13-Rα2, EREG, PDE4D, IL1-β, IP-10, TIMP2, IL8, β –actin and GAPDH were obtained from Sigma-Aldrich (Sigma-Aldrich, Zwi- jndrecht, The Netherlands). The following primers were used: IL13-Rα2; sense: TGC-TCA- GAT-GAC-GGA-ATT-TGG, antisense: TGG-TAG-CCA-GAA-ACG-TAG-CAA-AG, EREG; sense: ATC-CTG-GCA-TGT-GCT-AGG-GT, antisense: GTG-CTC-CAG-AGG-TCA-GCC-AT, PDE4D; sense: GGC-CTC-CAA-CAA-GTT-TAA-AA, antisense: ACC-AGA-CAA-CTC-TGC-TAT-TCT, IL1-β; sense: GGA-TAT-GGA-GCA-ACA-AGT-GG, antisense: ATG-TAC-CAG-TTG-GGG-AAC- TG, IP-10; sense: TGA-AAT-TAT-TCC-TGC-AAG-CCA-AT, antisense: CAG-ACA-TCT-CTT- CTC-ACC-CTT-CTT-T, TIMP2; sense: ATA-AGC-AGG-CCT-CCA-ACG-C, antisense: GAG- CTG-GAC-CAG-TCG-AAA-CC, IL8; sense: CCA-CAC-TGC-GCC-AAC-ACA-GAA-ATT-ATT-G, antisense: GCC-CTC-TTC-AAA-AAC-TTC-TCC-ACA-ACC-C, β –actin; sense: TGA-GCG-CGG- CTA-CAG-CTT, antisense: TCC-TTA-ATG-TCA-CGC-ACG-ATT-T, GAPDH; sense: GAA-GGT- GAA-GGT-CGG-AGT-C, antisense: GAA-GAT-GGT-GAT-GGG-ATT-TC. For ATF3 and DUSP1 we used TaqMan® gene expression assays from Applied Biosystems (Nieuwerkerk a/d IJssel, The Netherlands) with the following assay IDs: ATF3; HS00231069_M1, DUSP1; HS006102757_G1. Correlations between fold changes (FC) within the microarray data and the real-time PCR data were determined using Pearson’s correlation.

Results

Validation of microarray data The results of this microarray experiment were validated by independent real time PCR on the same starting material used for the microarray analysis. We first determined the expression of the housekeeping genes (ACTB and GAPDH) which was not affected by type of tissue (upper or lower airway) or condition (healthy, asthma or rhinitis). A random selection of 9 genes was used that showed a significant different expression between upper and lower airways in at least one of the subject groups. Table S1 shows the ratios calculated from the microarray data and the real-time PCR-derived expression. Statistical analysis revealed a high level of correspondence (R=0.92, P<0.0001), pointing

Gene Expression of Airway Epithelium 57 towards a correlation of 85% (R2=0.85) between the microarray data and the real-time PCR (Figure S1).

Differential gene expression in nasal and bronchial epithelium There were substantial differences in gene expression between the epithelia from upper and lower airways of healthy individuals. These differences were smaller in patients with allergic rhinitis and even smaller in those with concomitant allergic asthma. Using a cut-off of adjusted p < 0.05 we identified 2705 out of 41976 probe sets that were statistically differentially expressed between healthy nasal and healthy bronchial epithelium. These 2705 probe sets correspond to 1988 uniquely annotated genes, of which 979 genes (Table S2) were expressed higher in the bronchial epithelium as compared to the nasal epithelium and 1009 genes (Table S3) were expressed higher in the nasal epithelium as compared to the bronchial epithelium. In patients with allergic rhinitis we identified 381 probe sets that were statistically differentially expressed between nasal and bronchial epitheliums. These 381 probe sets correspond to 301 uniquely annotated genes, of which 138 genes (Table S4) were expressed higher in the bronchial epithelium as compared to the nasal epithelium, and 163 genes (Table S5) were expressed higher in the nasal epithelium as compared to the bronchial epithelium. Finally, we identified just 47 probe sets that were statistically differentially expressed between nasal and bronchial epithelium from patients with allergic asthma and rhinitis. This original set of 47 probe sets correspond to 40 uniquely annotated genes, of which 25 genes (Table S6) were expressed higher in the bronchial epithelium as compared to the nasal epithelium, and 15 genes (Table S7) were expressed higher in the nasal epithelium as compared to the bronchial epithelium.

58 Chapter 3 Table S1. Validatory PCR of housekeeping genes and significantly different genes Healthy Allergic rhinitis Allergic rhinitis & asthma PCR FC Microarray FC PCR FC Microarray FC PCR FC Microarray FC ACTB -1.1 -1.1 -1.3 -1.1 -1.0 -1.0 GAPDH 1.0 -1.0 1.3 1.1 -1.2 -1.0 ATF3 -3.4 -2.2 -2.7 -2.1 -2.8 -1.8 CXCL10 8.0 7.6 3.0 2.7 4.0 2.7 DUSP1 -2.5 -2.6 -2.0 -3.3 -1.6 -1.6 EREG 1.6 1.8 -1.9 -2.2 -1.1 1.2 IL13RA2 4.5 5.7 1.9 2.4 6.9 9.7 IL1B 1.4 1.6 1.3 1.1 -1.4 -1.0 IL8 -6.5 -5.9 1.0 -1.1 -6.0 -2.6 PDE4D -1.6 -1.3 -1.3 -1.5 -2.7 -1.2 TIMP2 1.5 1.6 1.1 -1.2 1.6 1.5 PCR expression is given as fold change (FC) between upper and lower airways.

Gene Expression of Airway Epithelium 59 Table S2. Genes that were significantly higher expressed by healthy bronchial epithelial Gene alias FC Gene name/description P-value Gene ID ATP-binding cassette, sub-family G (WHITE), ABCG1 1.84 member 1 8.17E-04 204567_PM_s_at ABHD2 1.21 abhydrolase domain containing 2 4.84E-02 205566_PM_at ABLIM3 1.93 actin binding LIM protein family, member 3 7.78E-03 205730_PM_s_at ABR 1.52 active BCR-related gene 1.47E-02 212895_PM_s_at ABT1 1.20 activator of basal transcription 1 4.91E-02 218405_PM_at ABTB2 1.36 ankyrin repeat and BTB (POZ) domain containing 2 3.61E-02 213497_PM_at ACACA 1.28 acetyl-CoA carboxylase alpha 2.29E-02 214358_PM_at ACOT9 1.25 acyl-CoA thioesterase 9 4.49E-02 221641_PM_s_at ACSL4 1.46 Acyl-CoA synthetase long-chain family member 4 4.94E-03 202422_PM_s_at ACTA2 1.62 Actin, alpha 2, smooth muscle, aorta 5.47E-03 200974_PM_at ACYP1 1.34 acylphosphatase 1, erythrocyte (common) type 4.88E-02 205260_PM_s_at ADAM28 2.15 ADAM metallopeptidase domain 28 3.10E-02 205997_PM_at ADAM9 1.72 ADAM metallopeptidase domain 9 (meltrin gamma) 2.93E-03 1555326_PM_a_at ADAM metallopeptidase with thrombospondin type ADAMTS1 2.42 1 motif, 1 3.87E-03 222486_PM_s_at ADRB2 1.43 adrenergic, beta-2-, receptor, surface 1.21E-02 206170_PM_at ADSSL1 1.74 Adenylosuccinate synthase like 1 4.77E-03 226325_PM_at AFAP1L1 1.75 actin filament associated protein 1-like 1 7.81E-03 226955_PM_at AFF1 1.40 AF4/FMR2 family, member 1 5.78E-03 201924_PM_at AGFG1 1.35 ArfGAP with FG repeats 1 1.44E-02 226561_PM_at AGR2 4.12 anterior gradient homolog 2 (Xenopus laevis) 1.58E-02 209173_PM_at AHCTF1 1.27 AT hook containing transcription factor 1 4.83E-02 226115_PM_at AHNAK2 1.23 AHNAK nucleoprotein 2 4.30E-02 1558378_PM_a_at AKAP12 13.17 A kinase (PRKA) anchor protein 12 4.55E-06 227530_PM_at V-akt murine thymoma viral oncogene homolog 3 AKT3 1.33 (protein kinase B, gamma) 2.89E-02 212609_PM_s_at asparagine-linked glycosylation 13 homolog (S. ALG13 1.42 cerevisiae) 2.98E-02 219015_PM_s_at ALOX5 1.40 arachidonate 5-lipoxygenase 3.71E-02 204446_PM_s_at ANGPTL2 1.24 angiopoietin-like 2 2.96E-02 213001_PM_at ANKRD20A1 /// ANKRD20A2 /// ANKRD20A3 /// ANKRD20A4 /// ANKRD20A5 /// C21orf81 /// LOC100132733 /// LOC644339 1.75 members of ankyrin repeat domain 20 family 1.26E-02 1569607_PM_s_at ANKRD40 1.21 Ankyrin repeat domain 40 3.96E-02 227064_PM_at ANKRD6 1.32 ankyrin repeat domain 6 1.37E-02 204672_PM_s_at ANKRD9 1.32 Ankyrin repeat domain 9 3.91E-02 230972_PM_at ankyrin repeat and sterile alpha motif domain ANKS6 1.55 containing 6 2.42E-03 235903_PM_at ANO4 2.15 Anoctamin 4 4.94E-03 236420_PM_s_at ANTXR2 1.82 anthrax toxin receptor 2 3.03E-02 228573_PM_at ANXA11 1.49 annexin A11 3.84E-02 214783_PM_s_at

60 Chapter 3 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID AOX1 1.87 aldehyde oxidase 1 9.95E-03 205083_PM_at AP1S3 1.65 adaptor-related protein complex 1, sigma 3 subunit 2.56E-02 1555733_PM_s_at AP2B1 1.28 adaptor-related protein complex 2, beta 1 subunit 1.76E-02 200615_PM_s_at APAF1 1.40 apoptotic peptidase activating factor 1 3.35E-02 211554_PM_s_at APLN 1.27 apelin 2.11E-02 244166_PM_at APLP2 1.24 Amyloid beta (A4) precursor-like protein 2 2.45E-02 208703_PM_s_at AR 1.22 androgen receptor 3.95E-02 226192_PM_at ArfGAP with RhoGAP domain, ankyrin repeat and ARAP2 1.85 PH domain 2 1.63E-02 214102_PM_at ARG2 1.64 arginase, type II 4.70E-03 203945_PM_at ARHGAP29 1.31 Rho GTPase activating protein 29 2.09E-02 203910_PM_at ARHGAP5 1.76 Rho GTPase activating protein 5 4.88E-02 235635_PM_at ARHGEF10 1.31 Rho guanine nucleotide exchange factor (GEF) 10 2.09E-02 216620_PM_s_at ARHGEF12 1.41 Rho guanine nucleotide exchange factor (GEF) 12 5.48E-03 201335_PM_s_at ARHGEF16 1.39 Rho guanine nucleotide exchange factor (GEF) 16 2.02E-02 208009_PM_s_at Rho/Rac guanine nucleotide exchange factor (GEF) ARHGEF18 1.32 18 4.50E-02 213039_PM_at ARID3B 1.45 AT rich interactive domain 3B (BRIGHT-like) 1.28E-02 218964_PM_at ARMC8 1.32 Armadillo repeat containing 8 3.69E-02 1555281_PM_x_at ARRDC1 1.23 arrestin domain containing 1 4.04E-02 226405_PM_s_at ARSJ 1.51 arylsulfatase family, member J 3.39E-03 219973_PM_at ArfGAP with SH3 domain, ankyrin repeat and PH ASAP1 1.21 domain 1 4.65E-02 224790_PM_at ASB1 1.37 ankyrin repeat and SOCS box-containing 1 1.59E-02 212819_PM_at ASPH 1.57 Aspartate beta-hydroxylase 7.20E-03 209135_PM_at ASXL1 1.34 additional sex combs like 1 (Drosophila) 7.47E-03 242439_PM_s_at ATF3 2.16 activating transcription factor 3 1.31E-02 202672_PM_s_at activating transcription factor 7 interacting protein ATF7IP2 1.38 2 3.81E-02 228381_PM_at ATG5 1.34 ATG5 autophagy related 5 homolog (S. cerevisiae) 2.11E-02 202512_PM_s_at ATL1 2.50 atlastin GTPase 1 1.81E-02 223340_PM_at ATPase, H+/K+ transporting, nongastric, alpha ATP12A 3.91 polypeptide 3.84E-02 207367_PM_at ATP2C2 1.57 ATPase, Ca++ transporting, type 2C, member 2 3.81E-03 214798_PM_at ATP8B1 1.30 ATPase, class I, type 8B, member 1 3.40E-02 238055_PM_at ATXN2L 1.27 ataxin 2-like 2.09E-02 207798_PM_s_at AXL 1.32 AXL receptor tyrosine kinase 6.91E-03 202686_PM_s_at UDP-Gal:betaGlcNAc beta 1,4- galactosyltransferase, B4GALT1 1.55 polypeptide 1 2.38E-02 216627_PM_s_at UDP-Gal:betaGlcNAc beta 1,4- galactosyltransferase, B4GALT6 1.36 polypeptide 6 1.76E-02 235333_PM_at BAIAP2 1.42 BAI1-associated protein 2 2.86E-02 205294_PM_at BCAR3 1.64 breast cancer anti-estrogen resistance 3 2.55E-03 204032_PM_at BCL10 1.46 B-cell CLL/lymphoma 10 2.48E-03 205263_PM_at BCL2L1 2.00 BCL2-like 1 1.04E-03 215037_PM_s_at BCOR 1.31 BCL6 co-repressor 4.88E-02 219433_PM_at BCR 1.32 breakpoint cluster region 4.75E-02 226602_PM_s_at

Gene Expression of Airway Epithelium 61 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID BEND7 1.64 BEN domain containing 7 4.48E-02 227341_PM_at BHLHE40 1.43 basic helix-loop-helix family, member e40 5.51E-03 201170_PM_s_at BIK 1.76 BCL2-interacting killer (apoptosis-inducing) 2.48E-02 205780_PM_at BLMH 1.74 bleomycin hydrolase 1.21E-02 202179_PM_at BLVRB 1.42 biliverdin reductase B (flavin reductase (NADPH)) 1.66E-02 202201_PM_at BMPR1B 2.40 bone morphogenetic protein receptor, type IB 1.72E-03 229975_PM_at BPGM 1.70 2,3-bisphosphoglycerate mutase 1.25E-02 203502_PM_at BRF1 homolog, subunit of RNA polymerase III BRF1 1.23 transcription initiation factor IIIB (S. cerevisiae) 4.90E-02 215676_PM_at BTG3 1.56 BTG family, member 3 7.58E-03 215425_PM_at BTN2A1 1.28 butyrophilin, subfamily 2, member A1 3.56E-02 215493_PM_x_at C10orf35 1.38 chromosome 10 open reading frame 35 2.06E-02 226313_PM_at C10orf47 2.07 chromosome 10 open reading frame 47 3.35E-03 230051_PM_at C11orf17 /// chromosome 11 open reading frame 17 /// NUAK NUAK2 1.53 family, SNF1-like kinase, 2 8.01E-03 220987_PM_s_at C11orf75 1.86 chromosome 11 open reading frame 75 1.54E-02 219806_PM_s_at C12orf39 1.41 chromosome 12 open reading frame 39 3.03E-02 229778_PM_at C12orf49 1.39 chromosome 12 open reading frame 49 2.01E-02 222767_PM_s_at C12orf54 1.62 chromosome 12 open reading frame 54 3.95E-02 240353_PM_s_at C14orf139 2.39 chromosome 14 open reading frame 139 4.55E-03 219563_PM_at C15orf39 1.38 chromosome 15 open reading frame 39 3.12E-02 204495_PM_s_at C15orf48 2.66 chromosome 15 open reading frame 48 1.60E-04 223484_PM_at C16orf45 2.00 chromosome 16 open reading frame 45 2.54E-04 212736_PM_at C16orf52 1.28 Chromosome 16 open reading frame 52 4.83E-02 230721_PM_at C16orf74 1.69 chromosome 16 open reading frame 74 1.26E-02 227806_PM_at C17orf68 1.41 chromosome 17 open reading frame 68 1.82E-02 235523_PM_at C18orf54 1.31 chromosome 18 open reading frame 54 3.25E-02 241733_PM_at C19orf21 1.47 chromosome 19 open reading frame 21 8.01E-03 212925_PM_at C19orf42 1.49 chromosome 19 open reading frame 42 4.57E-03 221988_PM_at C19orf46 2.74 chromosome 19 open reading frame 46 3.87E-05 235515_PM_at C19orf61 1.34 chromosome 19 open reading frame 61 4.27E-02 221335_PM_x_at C1orf133 3.01 chromosome 1 open reading frame 133 1.60E-04 230121_PM_at C1orf201 1.32 chromosome 1 open reading frame 201 4.35E-02 227694_PM_at C1orf77 1.34 chromosome 1 open reading frame 77 2.54E-02 209927_PM_s_at C1orf97 1.28 chromosome 1 open reading frame 97 4.59E-02 224444_PM_s_at C3orf16 1.73 chromosome 3 open reading frame 16 2.24E-03 1561927_PM_at C3orf52 2.05 chromosome 3 open reading frame 52 3.37E-04 219474_PM_at C3orf67 1.63 chromosome 3 open reading frame 67 1.75E-02 239697_PM_x_at C4orf19 1.91 chromosome 4 open reading frame 19 1.67E-02 219450_PM_at C5orf32 1.36 chromosome 5 open reading frame 32 1.83E-02 224707_PM_at C6orf106 1.20 chromosome 6 open reading frame 106 4.27E-02 217925_PM_s_at C6orf168 1.78 chromosome 6 open reading frame 168 3.87E-03 232067_PM_at C6orf211 1.20 chromosome 6 open reading frame 211 4.90E-02 218195_PM_at C6orf223 1.81 chromosome 6 open reading frame 223 2.45E-02 230944_PM_at C7orf46 1.44 chromosome 7 open reading frame 46 4.06E-02 228600_PM_x_at C7orf47 1.25 chromosome 7 open reading frame 47 4.32E-02 226434_PM_at C8orf4 1.25 chromosome 8 open reading frame 4 4.05E-02 218541_PM_s_at

62 Chapter 3 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID C8orf73 1.28 chromosome 8 open reading frame 73 4.27E-02 227672_PM_at C9orf125 1.41 chromosome 9 open reading frame 125 1.68E-02 224458_PM_at C9orf167 1.37 chromosome 9 open reading frame 167 3.78E-02 233589_PM_x_at C9orf30 1.50 chromosome 9 open reading frame 30 6.91E-03 1555841_PM_at C9orf64 1.24 chromosome 9 open reading frame 64 4.65E-02 235940_PM_at C9orf72 1.46 chromosome 9 open reading frame 72 3.10E-02 1553133_PM_at CA9 1.37 carbonic anhydrase IX 2.86E-02 205199_PM_at CADM1 1.61 cell adhesion molecule 1 2.38E-02 209031_PM_at CADPS2 1.51 Ca++-dependent secretion activator 2 1.72E-03 219572_PM_at CALML4 2.36 calmodulin-like 4 1.64E-03 221879_PM_at CAPN2 1.52 calpain 2, (m/II) large subunit 1.04E-02 214888_PM_at CAPNS2 2.23 calpain, small subunit 2 5.89E-03 223832_PM_s_at CAPRIN2 1.53 caprin family member 2 1.32E-02 218456_PM_at CAPS 1.46 calcyphosine 5.54E-03 231729_PM_s_at CARD11 2.08 caspase recruitment domain family, member 11 8.14E-04 223514_PM_at CASKIN1 1.31 CASK interacting protein 1 2.99E-02 1569737_PM_a_at CASP3 1.40 Caspase 3, apoptosis-related cysteine peptidase 7.36E-03 202763_PM_at CAV2 1.24 Caveolin 2 2.82E-02 203323_PM_at CCBE1 8.61 collagen and calcium binding EGF domains 1 7.41E-05 229641_PM_at CCBL1 1.34 cysteine conjugate-beta lyase, cytoplasmic 3.00E-02 206037_PM_at CCDC124 1.20 coiled-coil domain containing 124 4.91E-02 225454_PM_at CCDC50 1.62 coiled-coil domain containing 50 1.49E-02 226713_PM_at CCNG2 1.57 cyclin G2 8.41E-03 211559_PM_s_at CCPG1 2.07 cell cycle progression 1 8.62E-03 222156_PM_x_at CD274 1.62 CD274 molecule 3.69E-02 227458_PM_at CD99 1.40 CD99 molecule 4.94E-02 201028_PM_s_at CD99L2 1.60 CD99 molecule-like 2 5.38E-03 233825_PM_s_at CDC42BPA 1.26 CDC42 binding protein kinase alpha (DMPK-like) 4.40E-02 214464_PM_at CDC42EP2 1.90 CDC42 effector protein (Rho GTPase binding) 2 3.57E-03 214014_PM_at CDC42SE2 1.25 CDC42 small effector 2 2.49E-02 229026_PM_at CDH11 2.32 Cadherin 11, type 2, OB-cadherin (osteoblast) 1.70E-02 236179_PM_at CDH26 6.00 cadherin 26 7.58E-06 232306_PM_at CDK13 1.22 Cyclin-dependent kinase 13 3.04E-02 228991_PM_at CDK17 1.55 cyclin-dependent kinase 17 1.53E-02 221918_PM_at CDKN1C 4.21 cyclin-dependent kinase inhibitor 1C (p57, Kip2) 7.87E-03 213348_PM_at CDR2 1.34 cerebellar degeneration-related protein 2, 62kDa 6.18E-03 209501_PM_at CDV3 1.28 CDV3 homolog (mouse) 3.88E-02 213548_PM_s_at carcinoembryonic antigen-related cell adhesion CEACAM5 4.14 molecule 5 2.63E-02 201884_PM_at carcinoembryonic antigen-related cell adhesion CEACAM6 3.76 molecule 6 (non-specific cross reacting antigen) 2.08E-02 211657_PM_at CELF1 1.23 CUGBP, Elav-like family member 1 3.69E-02 1555467_PM_a_at CEP135 1.42 centrosomal protein 135kDa 3.72E-02 206003_PM_at CEP170 1.65 centrosomal protein 170kDa 3.00E-02 212746_PM_s_at CERK 1.45 ceramide kinase 4.73E-02 218421_PM_at CFLAR 1.81 CASP8 and FADD-like apoptosis regulator 2.38E-03 210564_PM_x_at CGGBP1 1.39 CGG triplet repeat binding protein 1 3.45E-03 206861_PM_s_at

Gene Expression of Airway Epithelium 63 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID CGN 2.17 cingulin 2.19E-03 223232_PM_s_at CHRNB1 1.64 cholinergic receptor, nicotinic, beta 1 (muscle) 5.23E-03 206703_PM_at carbohydrate (N-acetylgalactosamine 4-0) CHST9 3.26 sulfotransferase 9 1.18E-03 224400_PM_s_at CIB1 1.36 calcium and integrin binding 1 (calmyrin) 1.74E-02 201953_PM_at CLASP2 1.39 Cytoplasmic linker associated protein 2 1.55E-02 212308_PM_at CLDN12 1.38 claudin 12 6.06E-03 223249_PM_at CLDN4 1.96 Claudin 4 3.91E-03 201428_PM_at CLDN7 1.68 claudin 7 9.70E-04 202790_PM_at CLDND1 1.30 claudin domain containing 1 1.99E-02 208925_PM_at CLEC11A 1.44 C-type lectin domain family 11, member A 1.05E-02 211709_PM_s_at CLIC6 2.15 chloride intracellular channel 6 3.59E-02 227742_PM_at CAP-GLY domain containing linker protein family, CLIP4 1.35 member 4 4.81E-02 219944_PM_at CLK3 1.29 CDC-like kinase 3 1.49E-02 202140_PM_s_at CKLF-like MARVEL transmembrane domain CMTM8 1.75 containing 8 1.74E-03 235099_PM_at CNIH4 1.44 cornichon homolog 4 (Drosophila) 6.87E-03 222721_PM_at CNOT4 1.36 CCR4-NOT transcription complex, subunit 4 3.71E-02 210203_PM_at CNST 1.33 consortin, connexin sorting protein 2.10E-02 225550_PM_at COBL 2.29 cordon-bleu homolog (mouse) 1.64E-02 213050_PM_at COL13A1 1.83 collagen, type XIII, alpha 1 4.92E-02 211343_PM_s_at COL4A4 1.63 Collagen, type IV, alpha 4 9.53E-03 229779_PM_at COL4A6 2.10 collagen, type IV, alpha 6 7.67E-04 210945_PM_at CORO1C 1.26 coronin, actin binding protein, 1C 2.04E-02 222409_PM_at CORO2A 1.35 coronin, actin binding protein, 2A 2.07E-02 227177_PM_at CPNE8 1.45 copine VIII 7.62E-03 241706_PM_at CREB5 1.77 CAMP responsive element binding protein 5 7.48E-03 229228_PM_at CRIP1 2.01 cysteine-rich protein 1 (intestinal) 5.85E-03 205081_PM_at colorectal neoplasia differentially expressed (non- CRNDE 1.34 protein coding) 2.59E-02 238021_PM_s_at chondroitin sulfate CSGALNACT2 1.77 N-acetylgalactosaminyltransferase 2 8.43E-03 218871_PM_x_at chondroitin sulfate N-acetylgalactosaminyltransferase 2 /// novel CSGALNACT2 /// protein similar to chondroitin sulfate GalNAcT-2 LOC644504 1.99 (GALNACT-2) 1.74E-03 222235_PM_s_at CSNK1D 1.27 casein kinase 1, delta 1.76E-02 207945_PM_s_at CSRNP1 1.82 cysteine-serine-rich nuclear protein 1 1.60E-02 225557_PM_at CST6 1.43 cystatin E/M 2.23E-02 231248_PM_at CTBP2 1.29 C-terminal binding protein 2 3.88E-02 201219_PM_at CTD (carboxy-terminal domain, RNA polymerase II, CTDSP2 1.41 polypeptide A) small phosphatase 2 2.68E-02 208735_PM_s_at catenin (cadherin-associated protein), alpha 1, CTNNA1 1.32 102kDa 1.57E-02 1558214_PM_s_at CTSS 2.36 cathepsin S 4.43E-02 232617_PM_at CUL4A 1.34 Cullin 4A 1.69E-02 227757_PM_at CUX2 2.54 cut-like homeobox 2 1.30E-02 213920_PM_at

64 Chapter 3 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID CWC27 spliceosome-associated protein homolog CWC27 1.22 (S. cerevisiae) 4.89E-02 223337_PM_at CXADR 1.35 coxsackie virus and adenovirus receptor 4.31E-02 1555716_PM_a_at chemokine (C-X-C motif) ligand 1 (melanoma CXCL1 2.73 growth stimulating activity, alpha) 3.77E-03 204470_PM_at CXCL17 16.06 chemokine (C-X-C motif) ligand 17 1.93E-05 226960_PM_at CXCL2 2.49 chemokine (C-X-C motif) ligand 2 6.51E-03 209774_PM_x_at chemokine (C-X-C motif) ligand 6 (granulocyte CXCL6 1.45 chemotactic protein 2) 2.17E-02 206336_PM_at CXCR7 2.10 chemokine (C-X-C motif) receptor 7 2.01E-02 232746_PM_at CXXC5 1.81 CXXC finger 5 1.63E-02 224516_PM_s_at Cytochrome P450, family 2, subfamily E, CYP2E1 2.73 polypeptide 1 1.98E-02 209975_PM_at cytochrome P450, family 2, subfamily S, polypeptide CYP2S1 2.07 1 3.73E-04 223385_PM_at CYR61 2.17 cysteine-rich, angiogenic inducer, 61 1.79E-04 210764_PM_s_at dual adaptor of phosphotyrosine and DAPP1 1.35 3-phosphoinositides 2.17E-02 222858_PM_s_at DCAF7 1.26 DDB1 and CUL4 associated factor 7 2.34E-02 221745_PM_at DDAH1 3.13 Dimethylarginine dimethylaminohydrolase 1 3.14E-05 209094_PM_at DHRS3 1.57 dehydrogenase/reductase (SDR family) member 3 2.85E-02 202481_PM_at DIP2 disco-interacting protein 2 homolog A DIP2A 1.28 (Drosophila) 1.39E-02 1561286_PM_a_at DIP2 disco-interacting protein 2 homolog C DIP2C 2.35 (Drosophila) 4.50E-04 212503_PM_s_at DISC1 /// TSNAX- DISC1 1.26 disrupted in schizophrenia 1 /// TSNAX-DISC1 gene 3.25E-02 206090_PM_s_at DKK2 1.65 dickkopf homolog 2 (Xenopus laevis) 1.36E-02 219908_PM_at DLG1 1.40 Discs, large homolog 1 (Drosophila) 4.59E-02 202515_PM_at DMRT2 1.58 doublesex and mab-3 related transcription factor 2 4.41E-02 223704_PM_s_at DMRTA2 3.61 DMRT-like family A2 1.02E-02 1558856_PM_at DNAJA4 2.77 DnaJ (Hsp40) homolog, subfamily A, member 4 6.36E-04 225061_PM_at DNAJB5 1.55 DnaJ (Hsp40) homolog, subfamily B, member 5 4.30E-02 207453_PM_s_at DNAJC10 1.37 DnaJ (Hsp40) homolog, subfamily C, member 10 2.01E-02 221782_PM_at DNAJC18 1.34 DnaJ (Hsp40) homolog, subfamily C, member 18 4.54E-02 227169_PM_at DNMBP 1.41 dynamin binding protein 5.21E-03 212838_PM_at DOCK4 2.29 dedicator of cytokinesis 4 4.02E-03 205003_PM_at DOCK5 1.42 Dedicator of cytokinesis 5 4.11E-03 230263_PM_s_at DOK7 2.34 docking protein 7 2.06E-03 240633_PM_at DPP9 1.84 dipeptidyl-peptidase 9 3.03E-03 231957_PM_s_at DPY19L1 1.53 Dpy-19-like 1 (C. elegans) 1.25E-03 212792_PM_at DPYSL3 2.01 dihydropyrimidinase-like 3 6.15E-03 201431_PM_s_at DSG2 1.33 desmoglein 2 3.15E-02 1553105_PM_s_at DST 1.57 dystonin 9.45E-03 216918_PM_s_at DTNA 1.53 dystrobrevin, alpha 3.75E-02 205741_PM_s_at DUSP1 2.59 dual specificity phosphatase 1 3.87E-03 201041_PM_s_at DUSP5 1.76 dual specificity phosphatase 5 1.71E-02 209457_PM_at

Gene Expression of Airway Epithelium 65 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID DUSP6 1.53 dual specificity phosphatase 6 1.86E-02 208893_PM_s_at DUSP7 1.29 dual specificity phosphatase 7 3.71E-02 214793_PM_at ECE1 1.45 endothelin converting enzyme 1 4.92E-03 201749_PM_at ECT2 1.60 Epithelial cell transforming sequence 2 oncogene 4.21E-03 234992_PM_x_at EDIL3 3.16 EGF-like repeats and discoidin I-like domains 3 3.38E-02 225275_PM_at EDN1 3.62 endothelin 1 6.06E-05 1564630_PM_at endonuclease/exonuclease/phosphatase family EEPD1 1.33 domain containing 1 1.45E-02 225630_PM_at EFHA2 1.23 EF-hand domain family, member A2 4.05E-02 238458_PM_at EFHD2 1.30 EF-hand domain family, member D2 2.51E-02 217992_PM_s_at EHBP1L1 1.42 EH domain binding protein 1-like 1 2.49E-02 91703_PM_at EHD1 1.49 EH-domain containing 1 2.80E-02 222221_PM_x_at EHF 1.37 ets homologous factor 4.79E-03 225645_PM_at EIF1 1.48 Eukaryotic translation initiation factor 1 1.27E-02 228967_PM_at EIF2C2 1.38 eukaryotic translation initiation factor 2C, 2 1.70E-02 225569_PM_at ELF5 3.67 E74-like factor 5 (ets domain transcription factor) 3.61E-03 220625_PM_s_at ELK4 1.22 ELK4, ETS-domain protein (SRF accessory protein 1) 4.57E-02 206919_PM_at ELL2 1.33 elongation factor, RNA polymerase II, 2 2.50E-02 226982_PM_at EML4 1.36 echinoderm microtubule associated protein like 4 2.24E-02 228674_PM_s_at EMP3 1.82 epithelial membrane protein 3 6.59E-03 203729_PM_at egf-like module containing, mucin-like, hormone EMR2 1.75 receptor-like 2 1.24E-02 207610_PM_s_at ENDOG 1.24 endonuclease G 3.00E-02 204824_PM_at ENO2 2.80 enolase 2 (gamma, neuronal) 5.51E-03 201313_PM_at EPB41L4A 1.33 erythrocyte membrane protein band 4.1 like 4A 9.79E-03 220119_PM_at EPCAM 2.03 epithelial cell adhesion molecule 1.30E-02 201839_PM_s_at EPHA2 1.74 EPH receptor A2 2.33E-03 203499_PM_at EPHB2 2.82 EPH receptor B2 3.28E-03 209589_PM_s_at epidermal growth factor receptor pathway EPS8 2.30 substrate 8 1.95E-02 202609_PM_at endoplasmic reticulum-golgi intermediate ERGIC1 1.38 compartment (ERGIC) 1 1.39E-02 223847_PM_s_at ERN1 2.19 endoplasmic reticulum to nucleus signaling 1 3.41E-03 235745_PM_at ESPN 1.53 espin 1.97E-03 223549_PM_s_at ETV4 1.23 ets variant 4 3.53E-02 1554576_PM_a_at EVPLL /// envoplakin-like /// similar to chromosome 2 open LOC100132977 1.71 reading frame 27 3.71E-02 236933_PM_at EYA1 1.63 eyes absent homolog 1 (Drosophila) 2.31E-02 214608_PM_s_at EYA4 16.74 eyes absent homolog 4 (Drosophila) 1.56E-06 238877_PM_at F11R 1.29 F11 receptor 2.52E-02 222354_PM_at coagulation factor VIII-associated (intronic transcript) 1 /// coagulation factor VIII-associated F8A1 /// F8A2 /// (intronic transcript) 2 /// coagulation factor VIII- F8A3 1.40 associated (intronic transcript) 3 2.98E-02 203274_PM_at FA2H 3.29 fatty acid 2-hydroxylase 1.13E-02 219429_PM_at FAAH2 1.36 fatty acid amide hydrolase 2 8.70E-03 230792_PM_at FAM102B 1.62 family with sequence similarity 102, member B 3.88E-02 226568_PM_at

66 Chapter 3 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID FAM107B 3.22 family with sequence similarity 107, member B 5.68E-04 223058_PM_at FAM119A 1.71 family with sequence similarity 119, member A 1.80E-03 235177_PM_at FAM131A 1.33 family with sequence similarity 131, member A 3.45E-02 221904_PM_at FAM155B 1.47 family with sequence similarity 155, member B 2.31E-02 206299_PM_at FAM171A1 1.64 family with sequence similarity 171, member A1 9.13E-03 212771_PM_at FAM174B 2.23 family with sequence similarity 174, member B 1.83E-04 221880_PM_s_at FAM24B 1.78 family with sequence similarity 24, member B 2.20E-02 231146_PM_at FAM65A 1.37 family with sequence similarity 65, member A 3.84E-02 45749_PM_at FAM83A 1.56 family with sequence similarity 83, member A 1.73E-02 238460_PM_at FAM91A2 /// FLJ39739 /// LOC100132057 family with sequence similarity 91, member A2 /// /// hypothetical FLJ39739 /// similar to Neuroblastoma LOC100286793 breakpoint family member 6-like protein /// /// LOC728855 /// hypothetical LOC100286793 /// hypothetical LOC728875 1.71 LOC728855 /// hypothetical LOC728875 5.55E-03 1568609_PM_s_at FAS 1.92 Fas (TNF receptor superfamily, member 6) 4.65E-04 204781_PM_s_at FAT4 2.63 FAT tumor suppressor homolog 4 (Drosophila) 4.22E-03 219427_PM_at FBXL14 1.46 F-box and leucine-rich repeat protein 14 6.13E-03 213145_PM_at FBXL7 2.21 F-box and leucine-rich repeat protein 7 2.65E-04 213249_PM_at FBXO33 1.22 F-box protein 33 4.63E-02 227521_PM_at FERMT2 1.38 fermitin family homolog 2 (Drosophila) 3.71E-02 209210_PM_s_at FGD6 1.59 FYVE, RhoGEF and PH domain containing 6 7.44E-03 1555137_PM_a_at FGF13 1.45 fibroblast growth factor 13 2.30E-03 205110_PM_s_at FGF18 1.33 fibroblast growth factor 18 1.67E-02 206986_PM_at FGF5 3.56 fibroblast growth factor 5 4.67E-03 208378_PM_x_at FGFR3 2.38 fibroblast growth factor receptor 3 9.08E-03 204379_PM_s_at FHL1 1.70 four and a half LIM domains 1 3.39E-02 201539_PM_s_at FIP1L1 1.35 FIP1 like 1 (S. cerevisiae) 6.15E-03 1554424_PM_at FKBP1B /// FK506 binding protein 1B, 12.6 kDa /// major MFSD2B 1.38 facilitator superfamily domain containing 2B 2.45E-02 209931_PM_s_at FLJ10357 1.77 protein SOLO 9.88E-03 58780_PM_s_at FLJ27352 1.75 hypothetical LOC145788 1.91E-02 243309_PM_at FLJ35776 1.75 Hypothetical LOC649446 3.66E-03 238432_PM_at FLJ37453 1.46 hypothetical LOC729614 3.83E-02 227593_PM_at FLJ45340 /// FLJ45445 /// LOC100133150 hypothetical LOC402483 /// hypothetical /// LOC399844 /// hypothetical LOC100133150 /// LOC100287274 hypothetical LOC100287274 /// hypothetical /// LOC653340 1.46 LOC653340 4.48E-02 225899_PM_x_at FOSL1 1.60 FOS-like antigen 1 1.00E-02 204420_PM_at FOXA1 4.68 Forkhead box A1 4.55E-06 204667_PM_at FOXA2 2.37 forkhead box A2 8.19E-03 40284_PM_at FOXD1 3.64 forkhead box D1 2.88E-02 206307_PM_s_at FOXE1 3.16 forkhead box E1 (thyroid transcription factor 2) 1.49E-02 206912_PM_at FOXL1 1.98 forkhead box L1 2.28E-02 243409_PM_at FOXP2 2.54 forkhead box P2 5.08E-03 235201_PM_at

Gene Expression of Airway Epithelium 67 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID FRMD5 1.95 FERM domain containing 5 4.71E-03 230831_PM_at FSTL3 1.53 follistatin-like 3 (secreted glycoprotein) 9.86E-03 203592_PM_s_at FUCA1 2.06 fucosidase, alpha-L- 1, tissue 6.39E-04 202838_PM_at FUT2 2.19 fucosyltransferase 2 (secretor status included) 1.27E-03 210608_PM_s_at fucosyltransferase 4 (alpha (1,3) fucosyltransferase, FUT4 2.25 myeloid-specific) 8.01E-04 209892_PM_at FUT6 2.01 fucosyltransferase 6 (alpha (1,3) fucosyltransferase) 4.23E-02 210399_PM_x_at FUT8 1.36 fucosyltransferase 8 (alpha (1,6) fucosyltransferase) 2.77E-02 1554930_PM_a_at FZD10 2.17 frizzled homolog 10 (Drosophila) 1.37E-02 219764_PM_at FZD5 1.39 frizzled homolog 5 (Drosophila) 2.09E-02 221245_PM_s_at G0S2 2.85 G0/G1switch 2 2.08E-02 213524_PM_s_at GTPase activating protein (SH3 domain) binding G3BP2 1.26 protein 2 3.80E-02 208840_PM_s_at GABRB3 1.86 gamma-aminobutyric acid (GABA) A receptor, beta 3 1.11E-02 229724_PM_at GADD45B 1.54 Growth arrest and DNA-damage-inducible, beta 1.09E-02 207574_PM_s_at GALC 1.38 galactosylceramidase 2.41E-02 204417_PM_at GALM 1.45 galactose mutarotase (aldose 1-epimerase) 1.58E-02 234974_PM_at GAS6 1.66 growth arrest-specific 6 3.01E-03 202177_PM_at GATA6 2.63 GATA binding protein 6 1.36E-02 210002_PM_at GBA2 1.40 glucosidase, beta (bile acid) 2 2.81E-02 224627_PM_at globoside alpha-1,3-N- GBGT1 1.42 acetylgalactosaminyltransferase 1 1.26E-02 231780_PM_at glucosaminyl (N-acetyl) transferase 2, I-branching GCNT2 1.71 enzyme (I blood group) 1.55E-02 230788_PM_at GDA 4.56 guanine deaminase 2.55E-03 224209_PM_s_at GDE1 1.25 glycerophosphodiester phosphodiesterase 1 2.98E-02 226214_PM_at GDI1 1.23 GDP dissociation inhibitor 1 3.15E-02 201864_PM_at G protein-coupled receptor kinase interacting GIT2 1.82 ArfGAP 2 4.05E-03 204982_PM_at GLB1L3 3.91 galactosidase, beta 1-like 3 2.35E-04 1569886_PM_a_at GLRX 3.46 glutaredoxin (thioltransferase) 2.68E-04 206662_PM_at GLUL 1.39 glutamate-ammonia ligase 1.10E-02 217202_PM_s_at guanine nucleotide binding protein (G protein), GNA15 1.45 alpha 15 (Gq class) 5.78E-03 205349_PM_at GNAS 1.52 GNAS complex locus 2.67E-02 229274_PM_at guanine nucleotide binding protein (G protein), GNG11 1.46 gamma 11 2.66E-02 204115_PM_at GOLM1 1.96 golgi membrane protein 1 1.72E-02 217771_PM_at GPC4 1.84 glypican 4 1.50E-02 204984_PM_at GPR110 2.41 G protein-coupled receptor 110 1.23E-02 236489_PM_at GPR126 1.75 G protein-coupled receptor 126 6.33E-03 213094_PM_at GPR153 1.26 G protein-coupled receptor 153 3.17E-02 64942_PM_at G protein-coupled receptor 37 (endothelin receptor GPR37 3.43 type B-like) 1.69E-03 209631_PM_s_at GPR39 2.44 G protein-coupled receptor 39 9.87E-05 229105_PM_at G protein-coupled receptor, family C, group 5, GPRC5A 3.85 member A 2.24E-04 203108_PM_at

68 Chapter 3 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID GPX3 1.54 glutathione peroxidase 3 (plasma) 3.44E-02 201348_PM_at GRB10 2.17 growth factor receptor-bound protein 10 2.93E-03 209409_PM_at GRK5 1.54 G protein-coupled receptor kinase 5 1.67E-02 204396_PM_s_at GULP1 2.05 GULP, engulfment adaptor PTB domain containing 1 3.80E-04 204237_PM_at H19, imprinted maternally expressed transcript H19 8.70 (non-protein coding) 2.32E-03 224646_PM_x_at HCLS1 2.02 hematopoietic cell-specific Lyn substrate 1 3.05E-02 202957_PM_at HDAC9 1.22 histone deacetylase 9 4.71E-02 205659_PM_at HDGFRP3 1.31 hepatoma-derived growth factor, related protein 3 4.65E-02 209525_PM_at haloacid dehalogenase-like hydrolase domain HDHD1A 1.36 containing 1A 5.66E-03 203974_PM_at HEG1 1.45 HEG homolog 1 (zebrafish) 1.89E-03 213069_PM_at HES4 1.38 hairy and enhancer of split 4 (Drosophila) 4.23E-02 227347_PM_x_at HEY1 2.55 hairy/enhancer-of-split related with YRPW motif 1 5.31E-04 218839_PM_at HIST2H4A /// HIST2H4B 1.50 histone cluster 2, H4a /// histone cluster 2, H4b 9.90E-03 207046_PM_at HLA-DQB1 4.34 major histocompatibility complex, class II, DQ beta 1 4.66E-04 209480_PM_at HLA-DQB1 /// HLA-DQB2 /// members of or similar to major histocompatibility LOC100294318 2.29 complex, class II, DQ beta 1.09E-02 212999_PM_x_at major histocompatibility complex, class II, DQ beta 1 HLA-DQB1 /// /// similar to major histocompatibility complex, class LOC100294318 3.97 II, DQ beta 1 8.14E-04 212998_PM_x_at HLA-DRB1 /// HLA-DRB3 /// HLA-DRB4 /// HLA-DRB5 /// LOC100133661 /// members of or similar to major histocompatibility LOC100294036 2.40 complex, class II, DR beta 4.84E-02 215193_PM_x_at HLA-DRB1 /// members of major histocompatibility complex, class HLA-DRB4 2.55 II, DR beta 2.31E-02 209312_PM_x_at HLA-G 1.46 major histocompatibility complex, class I, G 1.52E-02 211530_PM_x_at HMGB3 2.04 high-mobility group box 3 1.58E-04 203744_PM_at HMGB3L1 1.91 high-mobility group box 3-like 1 1.32E-03 216548_PM_x_at HMHA1 1.53 histocompatibility (minor) HA-1 6.17E-03 212873_PM_at HN1 1.38 hematological and neurological expressed 1 2.69E-02 222396_PM_at HNMT 2.35 histamine N-methyltransferase 5.14E-03 204112_PM_s_at HNRNPH1 1.28 Heterogeneous nuclear ribonucleoprotein H1 (H) 3.50E-02 213470_PM_s_at HOOK3 1.23 hook homolog 3 (Drosophila) 3.95E-02 236192_PM_at HOXA1 3.11 homeobox A1 6.98E-03 214639_PM_s_at HRASLS 1.44 HRAS-like suppressor 2.34E-02 219983_PM_at Heparan sulfate (glucosamine) 3-O-sulfotransferase HS3ST1 1.75 1 2.25E-02 205466_PM_s_at heparan sulfate (glucosamine) 3-O-sulfotransferase HS3ST2 2.32 2 6.58E-03 219697_PM_at HS6ST2 6.56 heparan sulfate 6-O-sulfotransferase 2 1.50E-04 230030_PM_at HSD11B1 2.87 hydroxysteroid (11-beta) dehydrogenase 1 4.87E-03 205404_PM_at

Gene Expression of Airway Epithelium 69 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID HSF2BP 1.36 heat shock transcription factor 2 binding protein 4.37E-02 207020_PM_at ICA1 2.68 islet cell autoantigen 1, 69kDa 2.50E-04 210547_PM_x_at ICAM2 1.47 intercellular adhesion molecule 2 4.30E-02 213620_PM_s_at ICAM3 1.34 intercellular adhesion molecule 3 2.97E-02 204949_PM_at intercellular adhesion molecule 4 (Landsteiner- ICAM4 2.10 Wiener blood group) 8.43E-03 207194_PM_s_at IDI1 1.30 isopentenyl-diphosphate delta isomerase 1 1.84E-02 204615_PM_x_at IER3 1.33 immediate early response 3 6.37E-03 201631_PM_s_at IFNAR1 1.28 Interferon (alpha, beta and omega) receptor 1 4.32E-02 225661_PM_at IFRD1 1.26 interferon-related developmental regulator 1 4.02E-02 202147_PM_s_at insulin-like growth factor 2 (somatomedin A) /// INS- IGF2 /// INS-IGF2 1.94 IGF2 readthrough transcript 2.56E-02 202409_PM_at IGF2BP2 1.35 insulin-like growth factor 2 mRNA binding protein 2 4.47E-02 223963_PM_s_at IGFBP4 1.92 insulin-like growth factor binding protein 4 1.01E-03 201508_PM_at IL11 2.07 interleukin 11 1.30E-02 206924_PM_at IL1RL1 6.40 Interleukin 1 receptor-like 1 4.66E-04 242809_PM_at IL1RN 1.52 interleukin 1 receptor antagonist 2.59E-03 212659_PM_s_at IL23A 2.69 Interleukin 23, alpha subunit p19 9.36E-03 220054_PM_at interleukin 6 signal transducer (gp130, oncostatin IL6ST 1.40 M receptor) 4.88E-02 212196_PM_at IL8 5.88 interleukin 8 7.71E-03 211506_PM_s_at ILK 1.33 integrin-linked kinase 2.79E-02 201234_PM_at IMPDH1 1.29 IMP (inosine 5'-monophosphate) dehydrogenase 1 1.58E-02 204169_PM_at INADL 1.25 InaD-like (Drosophila) 4.57E-02 239173_PM_at INF2 1.61 inverted formin, FH2 and WH2 domain containing 1.86E-02 224469_PM_s_at inositol polyphosphate-4-phosphatase, type II, INPP4B 1.49 105kDa 2.55E-02 205376_PM_at INPP5A 1.31 inositol polyphosphate-5-phosphatase, 40kDa 1.79E-02 203006_PM_at INSIG1 1.40 insulin induced gene 1 3.68E-02 201626_PM_at INSR 1.57 insulin receptor 8.26E-03 226216_PM_at IQCD 1.57 IQ motif containing D 2.45E-02 1552540_PM_s_at IRAK3 1.34 interleukin-1 receptor-associated kinase 3 3.03E-02 220034_PM_at IRS1 1.70 insulin receptor substrate 1 6.98E-03 204686_PM_at IRX5 1.35 iroquois homeobox 5 1.70E-02 210239_PM_at ISG20 2.41 interferon stimulated exonuclease gene 20kDa 2.16E-02 204698_PM_at integrin, alpha 2 (CD49B, alpha 2 subunit of VLA-2 ITGA2 2.02 receptor) 3.43E-03 205032_PM_at integrin, beta 1 (fibronectin receptor, beta ITGB1 1.28 polypeptide, antigen CD29 includes MDF2, MSK12) 2.46E-02 1553530_PM_a_at ITPKC 1.26 inositol 1,4,5-trisphosphate 3-kinase C 2.87E-02 213076_PM_at JAK2 1.53 Janus kinase 2 4.09E-03 205842_PM_s_at JOSD1 1.35 Josephin domain containing 1 1.55E-02 201751_PM_at JPH1 1.48 junctophilin 1 3.55E-02 229139_PM_at JUB 1.46 Jub, ajuba homolog (Xenopus laevis) 1.22E-02 243446_PM_at JUN 1.39 jun oncogene 2.07E-02 201465_PM_s_at KAL1 1.75 Kallmann syndrome 1 sequence 3.28E-03 205206_PM_at KANK2 1.61 KN motif and ankyrin repeat domains 2 1.09E-03 218418_PM_s_at

70 Chapter 3 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID KBTBD2 1.23 kelch repeat and BTB (POZ) domain containing 2 3.71E-02 212447_PM_at potassium inwardly-rectifying channel, subfamily J, KCNJ15 2.40 member 15 3.04E-04 210119_PM_at potassium large conductance calcium-activated KCNMA1 3.31 channel, subfamily M, alpha member 1 1.52E-03 221584_PM_s_at potassium voltage-gated channel, KQT-like KCNQ1 1.71 subfamily, member 1 6.51E-03 204487_PM_s_at potassium voltage-gated channel, KQT-like KCNQ5 1.42 subfamily, member 5 4.83E-02 244623_PM_at potassium channel tetramerisation domain KCTD12 1.84 containing 12 1.08E-03 212188_PM_at Potassium channel tetramerisation domain KCTD5 1.31 containing 5 1.73E-02 222645_PM_s_at KH domain containing, RNA binding, signal KHDRBS3 1.52 transduction associated 3 6.33E-03 209781_PM_s_at KIAA0495 1.28 KIAA0495 2.61E-02 213340_PM_s_at KIAA0649 1.51 KIAA0649 4.71E-03 203955_PM_at KIAA1199 1.65 KIAA1199 1.00E-02 212942_PM_s_at KIAA1217 1.26 KIAA1217 2.84E-02 232762_PM_at KIAA1244 3.26 KIAA1244 1.06E-04 228051_PM_at KISS1R 1.42 KISS1 receptor 4.85E-02 242517_PM_at KLF12 1.48 Kruppel-like factor 12 2.73E-02 227261_PM_at KLF7 1.45 Kruppel-like factor 7 (ubiquitous) 4.77E-02 238482_PM_at KLHDC5 1.45 kelch domain containing 5 5.15E-03 225963_PM_at KREMEN1 1.36 kringle containing transmembrane protein 1 3.08E-02 227250_PM_at KRT13 5.16 keratin 13 4.85E-03 207935_PM_s_at KRT18 1.95 keratin 18 6.05E-04 201596_PM_x_at KRT19 7.71 keratin 19 5.68E-04 201650_PM_at KRT31 1.95 keratin 31 1.36E-02 206677_PM_at KRT8 1.68 keratin 8 1.31E-03 209008_PM_x_at KRTCAP3 1.86 keratinocyte associated protein 3 4.73E-03 235148_PM_at LACTB2 1.45 lactamase, beta 2 1.42E-02 218701_PM_at LAMB3 1.26 laminin, beta 3 1.78E-02 209270_PM_at LAMC2 2.00 laminin, gamma 2 2.33E-02 207517_PM_at LARP1B 1.31 La ribonucleoprotein domain family, member 1B 3.33E-02 226750_PM_at LARP6 1.34 La ribonucleoprotein domain family, member 6 3.24E-02 218651_PM_s_at LASS2 1.30 LAG1 homolog, ceramide synthase 2 2.30E-02 222212_PM_s_at LASS6 1.34 LAG1 homolog, ceramide synthase 6 2.65E-02 212446_PM_s_at LBH 3.35 limb bud and heart development homolog (mouse) 6.42E-05 221011_PM_s_at LBR 1.43 lamin B receptor 7.42E-03 201795_PM_at LCORL 1.48 ligand dependent nuclear receptor corepressor-like 6.15E-03 232293_PM_at LDLR 1.41 low density lipoprotein receptor 6.16E-03 217173_PM_s_at LIFR 1.45 leukemia inhibitory factor receptor alpha 1.72E-02 225575_PM_at LIMA1 1.57 LIM domain and actin binding 1 1.07E-02 222456_PM_s_at LIMS3 /// LIMS3- LIM and senescent cell antigen-like domains 3 LOC440895 /// /// LIMS3-LOC440895 read-through /// LIM and LOC440895 2.51 senescent cell antigen-like domains 3-like 5.63E-03 229095_PM_s_at

Gene Expression of Airway Epithelium 71 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID LIX1L 1.61 Lix1 homolog (mouse)-like 2.60E-02 225793_PM_at LLGL2 1.50 lethal giant larvae homolog 2 (Drosophila) 5.47E-03 1554006_PM_a_at LMO2 1.99 LIM domain only 2 (rhombotin-like 1) 4.66E-04 204249_PM_s_at LMO7 2.21 LIM domain 7 6.51E-03 242722_PM_at LMTK2 1.29 lemur tyrosine kinase 2 2.15E-02 226375_PM_at LOC100130175 hypothetical protein LOC100130175 /// non-protein /// NCRNA00081 1.35 coding RNA 81 3.00E-02 213220_PM_at LOC100130938 2.05 hypothetical LOC100130938 1.80E-03 230574_PM_at LOC100132167 1.60 similar to hCG1993567 1.42E-02 224519_PM_at LOC100132288 1.75 hypothetical protein LOC100132288 1.74E-03 229748_PM_x_at LOC100132288 hypothetical protein LOC100132288 /// MAFF /// MAFIP 1.48 interacting protein 4.33E-02 227330_PM_x_at LOC100286909 1.74 Hypothetical protein LOC100286909 1.36E-02 228528_PM_at LOC100287558 2.08 Hypothetical protein LOC100287558 5.85E-03 1569338_PM_at LOC100288387 1.37 similar to c-jun 3.36E-02 213281_PM_at LOC100293492 hypothetical protein LOC100293492 /// similar /// LOC389906 to Serine/threonine-protein kinase PRKX (Protein /// LOC441528 /// kinase PKX1) /// hypothetical protein LOC441528 /// LOC729162 1.38 similar to hCG1981372 2.90E-02 1558045_PM_a_at similar to single Ig IL-1R-related molecule /// single LOC100294402 immunoglobulin and toll-interleukin 1 receptor /// SIGIRR 2.22 (TIR) domain 4.92E-04 52940_PM_at LOC158402 2.06 hypothetical protein LOC158402 5.04E-04 236769_PM_at LOC202181 1.52 hypothetical protein LOC202181 1.96E-02 232309_PM_at LOC284600 1.21 hypothetical protein LOC284600 4.32E-02 1559083_PM_x_at LOC284900 1.52 hypothetical LOC284900 4.32E-03 244189_PM_at LOC338620 1.75 hypothetical protein LOC338620 1.59E-03 230930_PM_at similar to solute carrier family 16 (monocarboxylic LOC346887 1.53 acid transporters), member 14 1.14E-02 235205_PM_at LOC389834 1.58 ankyrin repeat domain 57 pseudogene 2.75E-02 226558_PM_at LOC390940 1.68 similar to R28379_1 4.11E-03 213556_PM_at LOC401074 2.27 hypothetical LOC401074 6.72E-03 1559827_PM_at LOC439990 1.61 hypothetical gene supported by BC009626 1.06E-02 1569322_PM_at LOC440335 1.84 hypothetical LOC440335 2.69E-03 229599_PM_at LOC440894 1.84 hypothetical protein LOC440894 2.02E-02 242222_PM_at LOC440895 1.25 LIM and senescent cell antigen-like domains 3-like 3.28E-02 215247_PM_at LOC541471 /// hypothetical LOC541471 /// non-protein coding NCRNA00152 1.25 RNA 152 3.88E-02 225799_PM_at LOC643008 1.70 hypothetical protein LOC643008 1.82E-02 229740_PM_at LOC651250 1.43 hypothetical LOC651250 3.57E-03 225055_PM_at similar to solute carrier family 6 member 8 /// solute carrier family 6 (neurotransmitter transporter, LOC653562 /// creatine), member 10 (pseudogene) /// solute SLC6A10P /// carrier family 6 (neurotransmitter transporter, SLC6A8 1.37 creatine), member 8 2.09E-02 215812_PM_s_at LOC727820 1.56 hypothetical protein LOC727820 3.96E-02 227383_PM_at LOC728342 1.72 Hypothetical protein LOC728342 7.70E-03 239319_PM_at

72 Chapter 3 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID LOC728392 /// hypothetical protein LOC728392 /// NLR family, NLRP1 1.78 pyrin domain containing 1 8.77E-03 218380_PM_at LOC728613 1.67 programmed cell death 6 pseudogene 6.87E-03 1569110_PM_x_at LOC728855 1.75 hypothetical LOC728855 1.93E-03 222001_PM_x_at similar to Myosin phosphatase Rho-interacting protein (Rho-interacting protein 3) (M-RIP) (RIP3) LOC729143 /// (p116Rip) /// myosin phosphatase Rho interacting MPRIP 1.31 protein 2.73E-02 214694_PM_at LOC729810 1.26 hypothetical protein LOC729810 4.94E-02 229200_PM_at LPAR1 2.09 lysophosphatidic acid receptor 1 2.98E-03 204037_PM_at LPCAT4 1.25 lysophosphatidylcholine acyltransferase 4 4.30E-02 239609_PM_s_at LPPR1 1.70 lipid phosphate phosphatase-related protein type 1 3.72E-02 219732_PM_at leucine-rich repeats and calponin homology (CH) LRCH1 1.24 domain containing 1 3.07E-02 226795_PM_at LRG1 1.64 leucine-rich alpha-2-glycoprotein 1 1.11E-02 228648_PM_at LRMP 2.21 lymphoid-restricted membrane protein 7.36E-03 204674_PM_at LRRC8A 1.42 leucine rich repeat containing 8 family, member A 8.55E-03 233487_PM_s_at LRRC8C 1.96 leucine rich repeat containing 8 family, member C 5.84E-03 228314_PM_at latent transforming growth factor beta binding LTBP1 1.62 protein 1 2.45E-02 202728_PM_s_at v-maf musculoaponeurotic fibrosarcoma oncogene MAFF 1.51 homolog F (avian) 5.14E-03 36711_PM_at v-maf musculoaponeurotic fibrosarcoma oncogene MAFG 1.25 homolog G (avian) 2.39E-02 204970_PM_s_at v-maf musculoaponeurotic fibrosarcoma oncogene MAFK 1.65 homolog K (avian) 1.01E-02 226206_PM_at mucosa associated lymphoid tissue lymphoma MALT1 1.24 translocation gene 1 2.38E-02 210018_PM_x_at MAN2A1 1.36 mannosidase, alpha, class 2A, member 1 2.67E-02 226538_PM_at MAP2K1 1.30 mitogen-activated protein kinase kinase 1 2.21E-02 202670_PM_at MAP3K9 1.61 mitogen-activated protein kinase kinase kinase 9 1.29E-02 213927_PM_at MAPK13 1.55 mitogen-activated protein kinase 13 2.12E-03 210058_PM_at MAPK6 1.26 mitogen-activated protein kinase 6 2.63E-02 207121_PM_s_at MATN3 1.60 matrilin 3 1.40E-02 206091_PM_at membrane bound O-acyltransferase domain MBOAT2 1.49 containing 2 1.40E-02 213288_PM_at MCPH1 1.57 microcephalin 1 7.15E-03 228778_PM_at MECOM 1.87 MDS1 and EVI1 complex locus 1.83E-02 226420_PM_at MESDC1 1.49 mesoderm development candidate 1 1.03E-02 223264_PM_at met proto-oncogene (hepatocyte growth factor MET 1.41 receptor) 4.98E-03 203510_PM_at MFSD10 1.31 major facilitator superfamily domain containing 10 3.00E-02 209215_PM_at mannosyl (alpha-1,6-)-glycoprotein beta-1,2-N- MGAT2 1.28 acetylglucosaminyltransferase 3.03E-02 211061_PM_s_at MGC16121 2.63 hypothetical protein MGC16121 2.23E-02 228235_PM_at MGC16121 /// MIR503 2.37 hypothetical protein MGC16121 /// microRNA 503 4.75E-02 227488_PM_at MGLL 1.28 monoglyceride lipase 4.44E-02 211026_PM_s_at

Gene Expression of Airway Epithelium 73 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID MIB1 1.24 Mindbomb homolog 1 (Drosophila) 4.58E-02 224722_PM_at MIB2 1.71 mindbomb homolog 2 (Drosophila) 1.24E-02 228261_PM_at MICALL2 1.57 MICAL-like 2 2.08E-02 1555862_PM_s_at MID1 1.28 midline 1 (Opitz/BBB syndrome) 3.28E-02 203636_PM_at MID1 interacting protein 1 (gastrulation specific G12 MID1IP1 1.20 homolog (zebrafish)) 4.44E-02 218251_PM_at MITF 2.07 microphthalmia-associated transcription factor 6.47E-03 226066_PM_at MOCS1 1.23 molybdenum cofactor synthesis 1 4.56E-02 213181_PM_s_at MPZL2 1.31 myelin protein zero-like 2 2.34E-02 203779_PM_s_at macrophage stimulating 1 receptor (c-met-related MST1R 2.21 tyrosine kinase) 2.26E-03 205455_PM_at MSTO1 1.31 misato homolog 1 (Drosophila) 2.96E-02 222584_PM_at MSTO1 /// misato homolog 1 (Drosophila) /// misato homolog MSTO2P 1.44 2 pseudogene 1.91E-02 224233_PM_s_at MSX1 1.34 Msh homeobox 1 1.78E-02 205932_PM_s_at MT1E 1.33 metallothionein 1E 1.69E-02 216336_PM_x_at MT1F 1.37 metallothionein 1F 1.73E-02 217165_PM_x_at MT1G 1.39 Metallothionein 1G 3.34E-02 204745_PM_x_at metallothionein 1H /// metallothionein 1 MT1H /// MT1P2 1.35 pseudogene 2 1.23E-02 206461_PM_x_at MT1P2 1.27 metallothionein 1 pseudogene 2 2.52E-02 211456_PM_x_at MT1X 1.27 metallothionein 1X 3.24E-02 204326_PM_x_at MT2A 1.28 metallothionein 2A 1.89E-02 212185_PM_x_at MTP18 1.63 mitochondrial protein 18 kDa 2.14E-02 223172_PM_s_at MUC1 3.10 mucin 1, cell surface associated 2.24E-02 213693_PM_s_at MUC3B 1.23 mucin 3B, cell surface associated 3.88E-02 214898_PM_x_at MUM1L1 2.98 melanoma associated antigen (mutated) 1-like 1 1.09E-02 229160_PM_at MUS81 1.22 MUS81 endonuclease homolog (S. cerevisiae) 3.21E-02 218463_PM_s_at MXD1 1.50 MAX dimerization protein 1 1.51E-02 228846_PM_at MYADM 1.46 myeloid-associated differentiation marker 7.11E-03 225673_PM_at MYEOV 1.95 myeloma overexpressed 4.29E-02 227342_PM_s_at MYH14 1.66 myosin, heavy chain 14, non-muscle 9.73E-03 234290_PM_x_at MYLIP 1.64 myosin regulatory light chain interacting protein 2.98E-02 228098_PM_s_at MYO10 1.76 myosin X 2.17E-02 1554026_PM_a_at MYO5B 1.46 myosin VB 4.53E-02 225299_PM_at MYO5C 2.49 myosin VC 5.93E-03 218966_PM_at N4BP2L2 1.27 NEDD4 binding protein 2-like 2 2.27E-02 202258_PM_s_at NAGS 1.75 N-acetylglutamate synthase 6.24E-03 229432_PM_at NAMPT 1.26 Nicotinamide phosphoribosyltransferase 2.68E-02 1555167_PM_s_at NAT14 1.29 N-acetyltransferase 14 (GCN5-related, putative) 3.28E-02 223284_PM_at NAT6 1.29 N-acetyltransferase 6 (GCN5-related) 4.23E-02 210874_PM_s_at NCEH1 1.86 neutral cholesterol ester hydrolase 1 1.79E-02 225847_PM_at NCF2 2.63 neutrophil cytosolic factor 2 2.24E-04 209949_PM_at N-deacetylase/N-sulfotransferase (heparan NDST1 1.29 glucosaminyl) 1 2.99E-02 1554010_PM_at NADH dehydrogenase (ubiquinone) 1 alpha NDUFA4L2 2.03 subcomplex, 4-like 2 2.80E-02 218484_PM_at

74 Chapter 3 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID NEIL1 1.37 nei endonuclease VIII-like 1 (E. coli) 1.21E-02 219396_PM_s_at NET1 1.53 neuroepithelial cell transforming 1 6.58E-03 201829_PM_at NEURL1B 2.86 neuralized homolog 1B (Drosophila) 8.91E-04 225355_PM_at nuclear factor of activated T-cells, cytoplasmic, NFATC1 1.41 calcineurin-dependent 1 1.85E-02 211105_PM_s_at NFYB 1.24 nuclear transcription factor Y, beta 3.53E-02 218129_PM_s_at Nance-Horan syndrome (congenital cataracts and NHS 1.31 dental anomalies) 3.26E-02 228933_PM_at non imprinted in Prader-Willi/Angelman syndrome NIPA1 1.43 1 5.85E-03 225752_PM_at NIPAL3 1.34 NIPA-like domain containing 3 4.79E-02 214579_PM_at NKX2-1 3.76 NK2 homeobox 1 4.19E-04 231315_PM_at NKX2-8 1.40 NK2 homeobox 8 2.38E-02 207451_PM_at NKX3-1 1.28 NK3 homeobox 1 4.60E-02 209706_PM_at NLRP1 2.20 NLR family, pyrin domain containing 1 6.35E-03 211824_PM_x_at NLRP2 5.58 NLR family, pyrin domain containing 2 1.21E-02 221690_PM_s_at NPC1 1.28 Niemann-Pick disease, type C1 2.97E-02 202679_PM_at NR3C2 2.71 nuclear receptor subfamily 3, group C, member 2 1.97E-02 205259_PM_at NRAS 1.40 neuroblastoma RAS viral (v-ras) oncogene homolog 5.57E-03 202647_PM_s_at NRIP3 2.04 nuclear receptor interacting protein 3 1.23E-02 219557_PM_s_at NRP2 1.34 neuropilin 2 2.51E-02 210842_PM_at NRXN3 1.91 neurexin 3 4.53E-02 229649_PM_at NT5E 2.36 5'-nucleotidase, ecto (CD73) 2.77E-04 203939_PM_at NTHL1 1.31 nth endonuclease III-like 1 (E. coli) 4.16E-02 209731_PM_at NTNG1 1.82 netrin G1 3.84E-02 236088_PM_at OAF 1.50 OAF homolog (Drosophila) 4.11E-03 225510_PM_at OCEL1 1.26 occludin/ELL domain containing 1 3.88E-02 205441_PM_at OCIAD2 1.28 OCIA domain containing 2 2.35E-02 225314_PM_at ODC1 1.98 Ornithine decarboxylase 1 4.58E-02 200790_PM_at ODF2L 1.49 outer dense fiber of sperm tails 2-like 4.31E-02 230926_PM_s_at OSBPL3 1.52 oxysterol binding protein-like 3 7.74E-03 209626_PM_s_at OSMR 1.39 oncostatin M receptor 3.74E-02 1554008_PM_at OTUD7B 1.33 OTU domain containing 7B 2.03E-02 227436_PM_at OXTR 2.61 oxytocin receptor 2.35E-03 206825_PM_at P2RY2 1.72 purinergic receptor P2Y, G-protein coupled, 2 7.95E-03 206277_PM_at PADI1 2.53 peptidyl arginine deiminase, type I 5.47E-03 223739_PM_at platelet-activating factor acetylhydrolase 1b, PAFAH1B3 1.31 catalytic subunit 3 (29kDa) 2.99E-02 203228_PM_at PANK4 1.28 pantothenate kinase 4 2.39E-02 218771_PM_at PANX2 1.31 Pannexin 2 2.44E-02 239067_PM_s_at PAPOLA 1.26 poly(A) polymerase alpha 4.83E-02 212720_PM_at PAQR8 1.57 progestin and adipoQ receptor family member VIII 2.09E-02 227626_PM_at par-6 partitioning defective 6 homolog beta (C. PARD6B 1.79 elegans) 7.14E-03 235165_PM_at PAWR 1.55 PRKC, apoptosis, WT1, regulator 2.88E-03 229515_PM_at PAX9 1.50 paired box 9 2.63E-02 207059_PM_at PCDH20 2.32 protocadherin 20 2.69E-02 232054_PM_at

Gene Expression of Airway Epithelium 75 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID PCDH7 4.14 protocadherin 7 1.44E-05 228640_PM_at PCDHA1 /// PCDHA10 /// PCDHA11 /// PCDHA12 /// PCDHA13 /// PCDHA2 /// PCDHA3 /// PCDHA4 /// PCDHA5 /// PCDHA6 /// PCDHA7 /// PCDHA8 /// PCDHA9 /// PCDHAC1 /// PCDHAC2 2.94 members of protocadherin alpha 1.62E-03 223435_PM_s_at PCGF3 1.56 polycomb group ring finger 3 1.41E-02 238084_PM_at phosphodiesterase 4D, cAMP-specific PDE4D 1.34 (phosphodiesterase E3 dunce homolog, Drosophila) 2.17E-02 204491_PM_at PDE9A 2.71 phosphodiesterase 9A 2.31E-03 205593_PM_s_at PDK3 1.44 pyruvate dehydrogenase kinase, isozyme 3 6.49E-03 228959_PM_at PDLIM5 1.40 PDZ and LIM domain 5 1.98E-02 211681_PM_s_at PEAR1 1.88 platelet endothelial aggregation receptor 1 4.75E-02 228618_PM_at PELO 1.55 pelota homolog (Drosophila) 3.57E-02 226731_PM_at PENK 1.21 proenkephalin 3.52E-02 213791_PM_at PGK1 1.34 phosphoglycerate kinase 1 3.74E-02 200737_PM_at PHACTR3 10.19 phosphatase and actin regulator 3 3.28E-05 227949_PM_at PHC2 1.37 polyhomeotic homolog 2 (Drosophila) 1.47E-02 200919_PM_at PHF10 1.25 PHD finger protein 10 4.96E-02 219126_PM_at PHF19 1.37 PHD finger protein 19 2.49E-02 227211_PM_at PHKA1 1.27 phosphorylase kinase, alpha 1 (muscle) 4.46E-02 205450_PM_at pleckstrin homology-like domain, family A, member PHLDA2 1.47 2 5.00E-03 209803_PM_s_at PHTF2 1.53 putative homeodomain transcription factor 2 1.65E-02 215286_PM_s_at PIM1 1.28 pim-1 oncogene 3.19E-02 209193_PM_at Protein kinase (cAMP-dependent, catalytic) inhibitor PKIA 2.21 alpha 2.32E-03 204612_PM_at protein kinase (cAMP-dependent, catalytic) inhibitor PKIB 1.91 beta 2.75E-02 223551_PM_at PLAGL2 1.25 pleiomorphic adenoma gene-like 2 3.03E-02 202925_PM_s_at PLAUR 1.60 plasminogen activator, urokinase receptor 1.85E-02 214866_PM_at PLCB1 2.31 phospholipase C, beta 1 (phosphoinositide-specific) 5.78E-03 213222_PM_at phosphatidylinositol-specific phospholipase C, X PLCXD2 1.93 domain containing 2 1.80E-02 235230_PM_at PLEC 1.55 plectin 4.54E-03 216971_PM_s_at PLEK2 1.43 pleckstrin 2 2.82E-02 218644_PM_at pleckstrin homology domain containing, family A PLEKHA2 1.41 (phosphoinositide binding specific) member 2 3.96E-02 238013_PM_at

76 Chapter 3 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID pleckstrin homology domain containing, family G PLEKHG2 1.22 (with RhoGef domain) member 2 3.77E-02 233986_PM_s_at pleckstrin homology domain containing, family G PLEKHG3 1.27 (with RhoGef domain) member 3 2.98E-02 212823_PM_s_at pleckstrin homology domain containing, family O PLEKHO1 2.08 member 1 6.88E-03 218223_PM_s_at PLK3 1.36 Polo-like kinase 3 (Drosophila) 1.99E-02 204958_PM_at PLLP 3.41 plasma membrane proteolipid (plasmolipin) 1.83E-04 204519_PM_s_at PLS1 1.92 plastin 1 1.28E-03 205190_PM_at PLXNA2 1.69 plexin A2 6.57E-04 213030_PM_s_at PM20D2 1.53 Peptidase M20 domain containing 2 6.72E-03 225421_PM_at prostate transmembrane protein, androgen induced PMEPA1 2.24 1 1.68E-03 222449_PM_at PODXL 10.45 podocalyxin-like 5.03E-03 201578_PM_at POLD4 1.25 polymerase (DNA-directed), delta 4 3.73E-02 202996_PM_at PORCN 1.57 porcupine homolog (Drosophila) 2.57E-02 219483_PM_s_at PP14571 1.91 similar to hCG1777210 1.31E-02 214858_PM_at phosphatidic acid phosphatase type 2 domain PPAPDC1B 1.28 containing 1B 2.08E-02 226150_PM_at PPARD 1.65 peroxisome proliferator-activated receptor delta 1.11E-03 210636_PM_at PPARG 1.44 peroxisome proliferator-activated receptor gamma 1.88E-02 208510_PM_s_at protein tyrosine phosphatase, receptor type, f polypeptide (PTPRF), interacting protein (liprin), PPFIA4 1.38 alpha 4 3.00E-02 214978_PM_s_at protein phosphatase 1, regulatory (inhibitor) PPP1R15A 1.62 subunit 15A 1.61E-03 37028_PM_at protein phosphatase 1, regulatory (inhibitor) PPP1R16A 1.26 subunit 16A 4.50E-02 225203_PM_at protein phosphatase 1, regulatory (inhibitor) PPP1R1C 1.76 subunit 1C 2.73E-03 228646_PM_at PPP2R1B 1.22 protein phosphatase 2, regulatory subunit A, beta 4.50E-02 222351_PM_at PPP2R2A 1.28 protein phosphatase 2, regulatory subunit B, alpha 3.25E-02 228013_PM_at protein phosphatase 3, catalytic subunit, beta PPP3CB 1.27 isozyme 3.84E-02 202432_PM_at protein phosphatase 3, catalytic subunit, gamma PPP3CC 1.73 isozyme 1.02E-03 32541_PM_at PPP4R4 1.68 protein phosphatase 4, regulatory subunit 4 8.26E-03 220673_PM_s_at PPTC7 1.37 PTC7 protein phosphatase homolog (S. cerevisiae) 2.55E-02 235744_PM_at PRDM16 1.66 PR domain containing 16 3.77E-03 232424_PM_at protein kinase, AMP-activated, alpha 1 catalytic PRKAA1 1.22 subunit 4.81E-02 225985_PM_at protein kinase, AMP-activated, alpha 2 catalytic PRKAA2 2.90 subunit 1.93E-03 227892_PM_at PRKCD 1.25 protein kinase C, delta 2.50E-02 202545_PM_at PRMT2 1.39 protein arginine methyltransferase 2 4.72E-02 228722_PM_at PRR5L 1.56 proline rich 5 like 2.54E-03 219383_PM_at PRSS23 1.63 Protease, serine, 23 1.00E-02 202458_PM_at PSD3 1.51 pleckstrin and Sec7 domain containing 3 1.67E-02 218613_PM_at

Gene Expression of Airway Epithelium 77 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID PSG1 1.68 pregnancy specific beta-1-glycoprotein 1 1.14E-03 208257_PM_x_at pregnancy specific beta-1-glycoprotein 7 (gene/ PSG7 1.35 pseudogene) 2.79E-02 205602_PM_x_at psiTPTE22 2.74 TPTE pseudogene 3.75E-03 1569348_PM_at proteasome (prosome, macropain) 26S subunit, PSMD2 1.31 non-ATPase, 2 3.46E-02 200830_PM_at Proteasome (prosome, macropain) 26S subunit, PSMD7 1.38 non-ATPase, 7 2.63E-02 238738_PM_at Proteasome (prosome, macropain) activator subunit PSME4 1.22 4 4.29E-02 212219_PM_at PTAFR 3.11 platelet-activating factor receptor 4.90E-03 227184_PM_at protein prenyltransferase alpha subunit repeat PTAR1 1.37 containing 1 3.40E-02 235484_PM_at PTGER4 2.49 prostaglandin E receptor 4 (subtype EP4) 3.77E-04 204897_PM_at prostaglandin-endoperoxide synthase 2 PTGS2 2.93 (prostaglandin G/H synthase and cyclooxygenase) 2.12E-03 204748_PM_at PTK2 1.31 PTK2 protein tyrosine kinase 2 3.88E-02 241453_PM_at PTK6 3.86 PTK6 protein tyrosine kinase 6 4.57E-03 206482_PM_at PTN 1.76 pleiotrophin 1.32E-03 209466_PM_x_at protein tyrosine phosphatase-like (proline instead PTPLA 1.54 of catalytic arginine), member A 3.75E-03 219654_PM_at PTPRD 1.32 protein tyrosine phosphatase, receptor type, D 2.09E-02 214043_PM_at PVRL3 1.64 poliovirus receptor-related 3 1.55E-03 213325_PM_at QSOX1 1.77 quiescin Q6 sulfhydryl oxidase 1 7.35E-04 201482_PM_at RAB11FIP1 2.19 RAB11 family interacting protein 1 (class I) 4.22E-03 225177_PM_at RAB11FIP4 1.33 RAB11 family interacting protein 4 (class II) 7.42E-03 224482_PM_s_at RAB3B 1.82 RAB3B, member RAS oncogene family 4.57E-03 205924_PM_at RAD18 1.41 RAD18 homolog (S. cerevisiae) 3.46E-02 238670_PM_at RAF1 1.25 v-raf-1 murine leukemia viral oncogene homolog 1 3.88E-02 1557675_PM_at RAP1GAP2 1.75 RAP1 GTPase activating protein 2 2.50E-02 213280_PM_at Ras association (RalGDS/AF-6) and pleckstrin RAPH1 1.57 homology domains 1 3.29E-02 231075_PM_x_at RARA 1.42 retinoic acid receptor, alpha 5.47E-03 203749_PM_s_at RASA2 1.55 RAS p21 protein activator 2 1.78E-02 206636_PM_at RASA3 1.54 RAS p21 protein activator 3 6.47E-03 225562_PM_at RASAL2 1.46 RAS protein activator like 2 2.55E-03 227036_PM_at RASD1 1.99 RAS, dexamethasone-induced 1 3.25E-02 223467_PM_at RASGEF1A 6.75 RasGEF domain family, member 1A 2.07E-02 230563_PM_at Ras association (RalGDS/AF-6) domain family RASSF5 1.32 member 5 1.84E-02 1554834_PM_a_at RBM47 1.51 RNA binding motif protein 47 4.63E-03 218035_PM_s_at recombination signal binding protein for RBPJ 1.36 immunoglobulin kappa J region 5.46E-03 211974_PM_x_at regulatory factor X, 3 (influences HLA class II RFX3 1.64 expression) 9.32E-03 230403_PM_at RGMB 3.01 RGM domain family, member B 3.45E-04 227339_PM_at RGNEF 1.35 190 kDa guanine nucleotide exchange factor 1.18E-02 1554003_PM_at RGS12 1.44 regulator of G-protein signaling 12 1.00E-02 209637_PM_s_at

78 Chapter 3 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID RGS2 1.46 regulator of G-protein signaling 2, 24kDa 4.05E-02 202388_PM_at RHBDL2 1.50 rhomboid, veinlet-like 2 (Drosophila) 2.45E-02 1554897_PM_s_at RHOBTB3 2.93 Rho-related BTB domain containing 3 2.26E-03 225202_PM_at RHOC 1.24 Ras homolog gene family, member C 4.76E-02 200885_PM_at RHOF 2.49 ras homolog gene family, member F (in filopodia) 3.33E-02 219045_PM_at RHPN2 1.57 rhophilin, Rho GTPase binding protein 2 8.26E-03 227196_PM_at RICH2 1.89 Rho-type GTPase-activating protein RICH2 1.80E-03 205414_PM_s_at RIMS2 2.00 regulating synaptic membrane exocytosis 2 6.79E-03 206137_PM_at RIT1 1.28 Ras-like without CAAX 1 1.62E-02 236224_PM_at RND1 1.71 Rho family GTPase 1 3.29E-02 210056_PM_at RNF114 1.26 ring finger protein 114 1.75E-02 200867_PM_at RNF128 5.56 ring finger protein 128 5.58E-04 219263_PM_at RNF138 1.35 ring finger protein 138 2.50E-02 239143_PM_x_at RNF144B 1.52 ring finger protein 144B 4.32E-02 239704_PM_at RNF24 1.31 ring finger protein 24 3.80E-02 210706_PM_s_at RNF7 1.29 Ring finger protein 7 3.84E-02 224394_PM_at roundabout, axon guidance receptor, homolog 2 ROBO2 1.76 (Drosophila) 3.91E-03 226766_PM_at ROD1 1.19 ROD1 regulator of differentiation 1 (S. pombe) 4.77E-02 224617_PM_at RPH3AL 1.52 rabphilin 3A-like (without C2 domains) 4.22E-03 221614_PM_s_at RPS16P5 1.32 ribosomal protein S16 pseudogene 5 4.32E-02 1566079_PM_at RRAS 1.31 related RAS viral (r-ras) oncogene homolog 2.80E-02 212647_PM_at RUFY2 1.32 RUN and FYVE domain containing 2 2.17E-02 235345_PM_at RUNX2 2.67 runt-related transcription factor 2 9.15E-04 232231_PM_at RUSC2 1.35 RUN and SH3 domain containing 2 3.89E-02 213066_PM_at S100A13 1.25 S100 calcium binding protein A13 3.00E-02 202598_PM_at S100A4 2.15 S100 calcium binding protein A4 1.21E-02 203186_PM_s_at S100P 2.32 S100 calcium binding protein P 2.45E-02 204351_PM_at SAMD4A 1.99 sterile alpha motif domain containing 4A 7.17E-03 215495_PM_s_at SAMD5 2.41 sterile alpha motif domain containing 5 6.58E-03 228653_PM_at SAT1 1.27 spermidine/spermine N1-acetyltransferase 1 3.10E-02 213988_PM_s_at SATB1 1.82 SATB homeobox 1 4.09E-03 203408_PM_s_at SATB2 1.54 SATB homeobox 2 5.85E-03 213435_PM_at SBF1 1.25 SET binding factor 1 4.29E-02 212393_PM_at SCCPDH 1.82 saccharopine dehydrogenase (putative) 2.90E-02 201825_PM_s_at SCHIP1 1.57 schwannomin interacting protein 1 1.24E-02 204030_PM_s_at SCNN1A 1.70 sodium channel, nonvoltage-gated 1 alpha 1.02E-02 203453_PM_at SDC2 2.38 syndecan 2 1.27E-03 212154_PM_at SDCBP2 1.57 syndecan binding protein (syntenin) 2 2.97E-02 233565_PM_s_at SDCCAG8 2.29 Serologically defined colon cancer antigen 8 1.32E-02 227785_PM_at SEC62 1.29 SEC62 homolog (S. cerevisiae) 2.46E-02 225352_PM_at SEL1L3 1.56 Sel-1 suppressor of lin-12-like 3 (C. elegans) 2.31E-03 212311_PM_at sema domain, immunoglobulin domain (Ig), short SEMA3A 2.75 basic domain, secreted, (semaphorin) 3A 7.39E-04 206805_PM_at sema domain, immunoglobulin domain (Ig), transmembrane domain (TM) and short cytoplasmic SEMA4D 1.48 domain, (semaphorin) 4D 1.72E-02 203528_PM_at

Gene Expression of Airway Epithelium 79 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID semaphorin 7A, GPI membrane anchor (John Milton SEMA7A 2.01 Hagen blood group) 6.61E-03 230345_PM_at SEPP1 10.92 Selenoprotein P, plasma, 1 4.96E-06 201427_PM_s_at SEPT10 1.33 septin 10 3.91E-02 214720_PM_x_at SERTAD4 3.48 SERTA domain containing 4 8.27E-05 230660_PM_at SESTD1 1.43 SEC14 and spectrin domains 1 5.94E-03 227041_PM_at SETBP1 2.35 SET binding protein 1 5.68E-04 227478_PM_at SFRS12IP1 1.62 SFRS12-interacting protein 1 5.24E-03 235390_PM_at SFTA3 4.39 surfactant associated 3 3.05E-03 228979_PM_at sarcoglycan, beta (43kDa dystrophin-associated SGCB 1.35 glycoprotein) 1.67E-02 226112_PM_at SGPP2 1.64 sphingosine-1-phosphate phosphotase 2 1.67E-02 244780_PM_at SH2D3A 1.55 SH2 domain containing 3A 4.77E-03 219513_PM_s_at SH3D20 1.97 SH3 domain containing 20 2.31E-03 1554594_PM_at SH3KBP1 1.29 SH3-domain kinase binding protein 1 1.21E-02 235692_PM_at SH3RF3 1.37 SH3 domain containing ring finger 3 3.84E-02 228461_PM_at SHANK2 2.03 SH3 and multiple ankyrin repeat domains 2 7.89E-04 213307_PM_at SIPA1 1.24 signal-induced proliferation-associated 1 3.93E-02 204164_PM_at SIX1 1.63 SIX homeobox 1 1.99E-02 205817_PM_at SIX4 1.46 SIX homeobox 4 1.67E-02 229796_PM_at SKAP2 2.96 Src kinase associated phosphoprotein 2 4.26E-04 204362_PM_at SLAMF9 2.86 SLAM family member 9 1.23E-02 1553769_PM_at solute carrier family 12 (potassium/chloride SLC12A7 2.19 transporters), member 7 1.83E-03 218066_PM_at solute carrier family 1 (neuronal/epithelial high affinity glutamate transporter, system Xag), member SLC1A1 2.10 1 1.71E-02 213664_PM_at Solute carrier family 1 (glutamate/neutral amino SLC1A4 2.39 acid transporter), member 4 7.82E-04 212810_PM_s_at SLC25A37 1.50 solute carrier family 25, member 37 7.54E-03 222528_PM_s_at Solute carrier family 2 (facilitated glucose SLC2A8 1.22 transporter), member 8 3.71E-02 218985_PM_at SLC30A7 1.41 solute carrier family 30 (zinc transporter), member 7 1.69E-02 239596_PM_at solute carrier family 36 (proton/amino acid SLC36A4 1.40 symporter), member 4 9.23E-03 234978_PM_at SLC38A4 2.06 solute carrier family 38, member 4 1.72E-02 220786_PM_s_at Solute carrier family 40 (iron-regulated transporter), SLC40A1 1.58 member 1 4.94E-02 223044_PM_at SLC44A2 1.38 solute carrier family 44, member 2 2.72E-02 224609_PM_at SLC44A4 2.10 solute carrier family 44, member 4 1.79E-03 205597_PM_at SLC44A5 2.78 solute carrier family 44, member 5 8.53E-03 235763_PM_at solute carrier family 4, sodium borate transporter, SLC4A11 2.69 member 11 1.61E-03 223748_PM_at solute carrier family 4, sodium bicarbonate SLC4A7 1.45 cotransporter, member 7 9.03E-03 209884_PM_s_at SLC7A6OS 1.25 solute carrier family 7, member 6 opposite strand 4.43E-02 229153_PM_at solute carrier family 9 (sodium/hydrogen SLC9A3R1 1.49 exchanger), member 3 regulator 1 1.12E-02 201349_PM_at

80 Chapter 3 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID SLFN11 4.62 schlafen family member 11 3.46E-03 226743_PM_at SLFN12 2.34 schlafen family member 12 9.06E-03 219885_PM_at SLMAP 1.26 sarcolemma associated protein 4.03E-02 222924_PM_at SMAD3 1.53 SMAD family member 3 1.09E-03 218284_PM_at SMAD4 1.29 SMAD family member 4 4.41E-02 235725_PM_at SWI/SNF related, matrix associated, actin dependent SMARCA1 1.46 regulator of chromatin, subfamily a, member 1 5.52E-03 203875_PM_at Smith-Magenis syndrome chromosome region, SMCR7 1.39 candidate 7 3.14E-02 235896_PM_s_at SMOC2 1.63 SPARC related modular calcium binding 2 2.44E-02 223235_PM_s_at SMURF1 1.26 SMAD specific E3 ubiquitin protein ligase 1 1.49E-02 212666_PM_at SMURF2 1.70 SMAD specific E3 ubiquitin protein ligase 2 2.93E-03 227489_PM_at SNAP23 1.55 Synaptosomal-associated protein, 23kDa 4.89E-02 209131_PM_s_at small nuclear RNA activating complex, polypeptide SNAPC1 1.90 1, 43kDa 9.78E-03 205443_PM_at synuclein, alpha (non A4 component of amyloid SNCA 1.60 precursor) 1.78E-02 236081_PM_at SNX9 1.24 sorting nexin 9 3.10E-02 223027_PM_at SOBP 8.37 sine oculis binding protein homolog (Drosophila) 4.54E-05 218974_PM_at SOX4 1.23 SRY (sex determining region Y)-box 4 3.36E-02 213665_PM_at SOX7 1.31 SRY (sex determining region Y)-box 7 2.45E-02 224013_PM_s_at SPAG4 1.68 sperm associated antigen 4 4.44E-02 219888_PM_at SPATA13 1.61 spermatogenesis associated 13 1.13E-02 225564_PM_at SPATS2 1.50 spermatogenesis associated, serine-rich 2 1.84E-02 222594_PM_s_at SPATS2L 1.42 Spermatogenesis associated, serine-rich 2-like 2.48E-02 222154_PM_s_at SAM pointed domain containing ets transcription SPDEF 7.03 factor 2.68E-04 220192_PM_x_at SPESP1 2.53 sperm equatorial segment protein 1 2.59E-02 229352_PM_at sparc/osteonectin, cwcv and kazal-like domains SPOCK1 3.21 proteoglycan (testican) 1 2.39E-03 202363_PM_at sparc/osteonectin, cwcv and kazal-like domains SPOCK3 3.37 proteoglycan (testican) 3 6.12E-03 235342_PM_at SPRED1 1.37 sprouty-related, EVH1 domain containing 1 3.48E-02 235074_PM_at SPRN 1.21 Shadow of prion protein homolog (zebrafish) 2.90E-02 238331_PM_at SPTBN1 1.52 spectrin, beta, non-erythrocytic 1 2.26E-03 200672_PM_x_at SRCAP 1.35 Snf2-related CREBBP activator protein 4.75E-02 213667_PM_at SRPX2 2.91 sushi-repeat-containing protein, X-linked 2 9.93E-03 205499_PM_at SSFA2 1.60 sperm specific antigen 2 4.24E-03 229744_PM_at SSH1 1.36 slingshot homolog 1 (Drosophila) 2.69E-02 221752_PM_at ST3GAL5 2.01 ST3 beta-galactoside alpha-2,3-sialyltransferase 5 6.51E-04 203217_PM_s_at ST6 (alpha-N-acetyl-neuraminyl-2,3-beta- galactosyl-1,3)-N-acetylgalactosaminide alpha-2,6- ST6GALNAC1 11.21 sialyltransferase 1 3.16E-06 227725_PM_at signal transducing adaptor molecule (SH3 domain STAM 1.29 and ITAM motif) 1 1.21E-02 203544_PM_s_at signal transducing adaptor molecule (SH3 domain STAM2 1.24 and ITAM motif) 2 3.63E-02 208194_PM_s_at STAMBPL1 1.91 STAM binding protein-like 1 6.08E-04 227607_PM_at

Gene Expression of Airway Epithelium 81 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID STARD3NL 1.28 STARD3 N-terminal like 1.37E-02 223065_PM_s_at STK17A 1.51 serine/threonine kinase 17a 2.10E-02 202694_PM_at STK17B 2.68 serine/threonine kinase 17b 2.55E-03 205214_PM_at serine threonine kinase 39 (STE20/SPS1 homolog, STK39 1.32 yeast) 4.02E-02 202786_PM_at STOM 1.57 stomatin 1.08E-03 201061_PM_s_at STRA13 1.22 stimulated by retinoic acid 13 homolog (mouse) 4.32E-02 209478_PM_at STS 1.43 steroid sulfatase (microsomal), isozyme S 3.03E-02 203769_PM_s_at STX1A 1.85 syntaxin 1A (brain) 1.18E-03 204729_PM_s_at STX2 1.40 syntaxin 2 4.41E-02 213434_PM_at SUPT6H 1.25 suppressor of Ty 6 homolog (S. cerevisiae) 4.32E-02 1554311_PM_a_at SUSD1 1.69 sushi domain containing 1 1.67E-02 226264_PM_at SYK 2.07 spleen tyrosine kinase 1.52E-03 226068_PM_at SYNPO 1.87 synaptopodin 2.32E-03 235914_PM_at SYT17 1.57 synaptotagmin XVII 2.15E-02 205613_PM_at SYTL4 2.17 Synaptotagmin-like 4 3.15E-02 229991_PM_s_at TACC1 1.51 transforming, acidic coiled-coil containing protein 1 5.47E-03 1554690_PM_a_at TAGLN3 2.92 transgelin 3 1.52E-03 204743_PM_at TBRG1 1.33 transforming growth factor beta regulator 1 8.95E-03 225819_PM_at TBX1 1.61 T-box 1 2.60E-03 236926_PM_at TC2N 1.42 tandem C2 domains, nuclear 3.57E-03 234970_PM_at TFF3 1.94 trefoil factor 3 (intestinal) 3.95E-03 204623_PM_at tissue factor pathway inhibitor (lipoprotein- TFPI 7.57 associated coagulation inhibitor) 3.47E-05 213258_PM_at TFPI2 2.21 tissue factor pathway inhibitor 2 8.16E-04 209277_PM_at TFPT 1.32 TCF3 (E2A) fusion partner (in childhood Leukemia) 1.58E-02 218996_PM_at TGFA 1.35 transforming growth factor, alpha 1.93E-02 205015_PM_s_at TGFBR1 1.23 transforming growth factor, beta receptor 1 4.16E-02 224793_PM_s_at transforming growth factor, beta receptor II TGFBR2 1.57 (70/80kDa) 6.38E-03 208944_PM_at TGFBR3 3.29 transforming growth factor, beta receptor III 6.05E-04 226625_PM_at transglutaminase 2 (C polypeptide, protein- TGM2 1.90 glutamine-gamma-glutamyltransferase) 3.95E-02 211003_PM_x_at TICAM2 /// toll-like receptor adaptor molecule 2 /// TMED7- TMED7-TICAM2 1.38 TICAM2 readthrough 4.71E-02 239431_PM_at translocase of inner mitochondrial membrane 50 TIMM50 1.26 homolog (S. cerevisiae) 3.15E-02 217612_PM_at TIPARP 1.42 TCDD-inducible poly(ADP-ribose) polymerase 9.32E-03 212665_PM_at TLL2 1.57 tolloid-like 2 3.54E-02 215008_PM_at TM9SF3 1.26 Transmembrane 9 superfamily member 3 2.30E-02 224755_PM_at TMC4 1.47 transmembrane channel-like 4 2.11E-02 226403_PM_at TMC6 1.52 Transmembrane channel-like 6 9.42E-03 204328_PM_at TMC7 1.31 transmembrane channel-like 7 2.69E-02 220021_PM_at TMCC1 1.31 transmembrane and coiled-coil domain family 1 4.75E-02 213352_PM_at TMCO3 1.45 Transmembrane and coiled-coil domains 3 2.85E-03 226050_PM_at transmembrane emp24 protein transport domain TMED5 1.46 containing 5 5.47E-03 242263_PM_at

82 Chapter 3 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID TMEM136 1.34 transmembrane protein 136 4.59E-02 1554076_PM_s_at TMEM170A 1.24 Transmembrane protein 170A 3.79E-02 227586_PM_at TMEM171 1.34 transmembrane protein 171 4.79E-02 240770_PM_at TMEM191A 1.33 transmembrane protein 191A 3.81E-02 223628_PM_at TMEM22 1.45 transmembrane protein 22 4.32E-02 219569_PM_s_at TMEM223 1.41 transmembrane protein 223 1.32E-02 220934_PM_s_at TMEM30B 1.27 transmembrane protein 30B 2.22E-02 213285_PM_at TMEM40 1.76 transmembrane protein 40 7.47E-03 219503_PM_s_at TMEM41B 1.35 transmembrane protein 41B 3.15E-02 212623_PM_at TMEM55A 1.26 transmembrane protein 55A 2.18E-02 226338_PM_at TMEM61 1.70 transmembrane protein 61 1.24E-03 230822_PM_at TMEM71 1.37 transmembrane protein 71 4.96E-02 238429_PM_at TMEM8A 1.59 transmembrane protein 8A 1.74E-03 222718_PM_at TMEM92 2.09 transmembrane protein 92 2.00E-02 235245_PM_at TMPRSS11D 3.10 transmembrane protease, serine 11D 4.97E-03 207602_PM_at TMPRSS4 2.68 transmembrane protease, serine 4 1.18E-03 218960_PM_at TNC 1.30 tenascin C 2.49E-02 201645_PM_at TNFAIP3 1.80 tumor necrosis factor, alpha-induced protein 3 2.54E-02 202643_PM_s_at tumor necrosis factor receptor superfamily, member TNFRSF10A 1.37 10a 3.25E-02 231775_PM_at tumor necrosis factor receptor superfamily, member TNFRSF10B 1.46 10b 8.83E-03 209294_PM_x_at tumor necrosis factor receptor superfamily, member TNFRSF12A 1.28 12A 2.63E-02 218368_PM_s_at tumor necrosis factor receptor superfamily, member TNFRSF21 1.51 21 2.55E-03 218856_PM_at TNFSF12- TNFSF13 /// TNFSF12-TNFSF13 readthrough /// tumor necrosis TNFSF13 1.34 factor (ligand) superfamily, member 13 4.86E-02 209500_PM_x_at tumor necrosis factor (ligand) superfamily, member TNFSF9 1.75 9 2.82E-03 206907_PM_at TOMM34 1.43 translocase of outer mitochondrial membrane 34 1.67E-02 201870_PM_at TOR1AIP1 1.34 torsin A interacting protein 1 5.47E-03 240310_PM_at TOX3 3.64 TOX high mobility group box family member 3 6.89E-03 214774_PM_x_at TP53TG3 /// TP53TG3B 1.37 TP53 target 3 /// TP53 target 3B 1.55E-02 220167_PM_s_at TPCN1 1.54 two pore segment channel 1 4.83E-02 217914_PM_at TPM3 1.38 tropomyosin 3 8.86E-03 238065_PM_at TRAF4 1.36 TNF receptor-associated factor 4 2.93E-02 242473_PM_at TRIB1 1.48 tribbles homolog 1 (Drosophila) 6.49E-03 202241_PM_at TRIM61 1.74 tripartite motif-containing 61 6.13E-03 238990_PM_x_at TRIM7 1.81 tripartite motif-containing 7 2.42E-03 239694_PM_at transient receptor potential cation channel, TRPC6 1.84 subfamily C, member 6 4.71E-02 217287_PM_s_at TSC22D1 1.48 TSC22 domain family, member 1 5.74E-03 235315_PM_at TSPAN1 5.22 tetraspanin 1 1.74E-05 209114_PM_at TSPAN12 2.26 tetraspanin 12 1.36E-02 219274_PM_at

Gene Expression of Airway Epithelium 83 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID TSPAN13 1.49 tetraspanin 13 5.48E-03 217979_PM_at TSPAN14 1.35 tetraspanin 14 8.52E-03 221002_PM_s_at TSPAN15 1.84 tetraspanin 15 9.03E-04 218693_PM_at TSPAN3 1.40 tetraspanin 3 5.31E-03 200973_PM_s_at TTBK2 1.49 Tau tubulin kinase 2 7.49E-03 1554294_PM_s_at TTC7A 1.32 tetratricopeptide repeat domain 7A 1.45E-02 224923_PM_at TTC9 2.71 tetratricopeptide repeat domain 9 1.40E-03 213172_PM_at TWIST1 9.30 twist homolog 1 (Drosophila) 1.56E-06 213943_PM_at TWIST2 3.70 twist homolog 2 (Drosophila) 7.17E-03 229404_PM_at TXNRD1 1.56 thioredoxin reductase 1 1.72E-02 201266_PM_at UBASH3B 1.21 ubiquitin associated and SH3 domain containing B 4.14E-02 238462_PM_at UBL3 1.46 ubiquitin-like 3 4.07E-03 201535_PM_at UCK2 1.91 uridine-cytidine kinase 2 1.44E-02 209825_PM_s_at UEVLD 1.29 UEV and lactate/malate dehyrogenase domains 3.87E-02 1554397_PM_s_at UGT1A1 /// UGT1A10 /// UGT1A3 /// UGT1A4 /// UGT1A5 /// UGT1A6 /// UGT1A7 /// UGT1A8 /// members of UDP glucuronosyltransferase 1 family, UGT1A9 3.52 polypeptide A 7.87E-03 215125_PM_s_at UGT1A1 /// UGT1A10 /// UGT1A4 /// UGT1A6 /// UGT1A8 /// members of UDP glucuronosyltransferase 1 family, UGT1A9 3.49 polypeptide A 5.47E-03 204532_PM_x_at UDP glucuronosyltransferase 1 family, polypeptide UGT1A6 3.39 A6 7.49E-03 206094_PM_x_at UHRF2 1.37 ubiquitin-like with PHD and ring finger domains 2 2.27E-02 225610_PM_at USP25 1.32 ubiquitin specific peptidase 25 1.90E-02 223167_PM_s_at VAV3 3.58 vav 3 guanine nucleotide exchange factor 3.95E-03 218807_PM_at VEZF1 1.69 vascular endothelial zinc finger 1 9.11E-04 202172_PM_at VILL 2.45 villin-like 5.85E-03 209950_PM_s_at VLDLR 1.57 very low density lipoprotein receptor 1.09E-02 209822_PM_s_at vesicular, overexpressed in cancer, prosurvival VOPP1 1.41 protein 1 2.85E-03 208091_PM_s_at vacuolar protein sorting 37 homolog B (S. VPS37B 1.33 cerevisiae) 3.88E-02 221704_PM_s_at vacuolar protein sorting 37 homolog C (S. VPS37C 1.24 cerevisiae) 2.17E-02 1560060_PM_s_at VSIG10 1.27 V-set and immunoglobulin domain containing 10 4.09E-02 1553991_PM_s_at VSTM2L 1.29 V-set and transmembrane domain containing 2 like 4.86E-02 226973_PM_at VWDE 1.54 von Willebrand factor D and EGF domains 3.63E-02 239552_PM_at WW domain binding protein 4 (formin binding WBP4 1.25 protein 21) 4.23E-02 203598_PM_s_at

84 Chapter 3 Table S2. (continued) Gene alias FC Gene name/description P-value Gene ID WDR26 1.20 WD repeat domain 26 4.37E-02 224898_PM_at WDR35 1.61 WD repeat domain 35 5.51E-03 226890_PM_at WHSC1 1.44 Wolf-Hirschhorn syndrome candidate 1 3.90E-02 223472_PM_at WIPF1 3.90 WAS/WASL interacting protein family, member 1 3.23E-03 202664_PM_at wingless-type MMTV integration site family, WNT7A 2.27 member 7A 5.26E-05 210248_PM_at wingless-type MMTV integration site family, WNT7B 1.30 member 7B 4.96E-02 238105_PM_x_at wingless-type MMTV integration site family, WNT9A 1.80 member 9A 1.42E-02 230643_PM_at WSB2 1.26 WD repeat and SOCS box-containing 2 1.37E-02 213734_PM_at WWC1 1.34 WW and C2 domain containing 1 1.13E-02 241950_PM_at XBP1 1.23 X-box binding protein 1 4.44E-02 200670_PM_at YIF1B 1.22 Yip1 interacting factor homolog B (S. cerevisiae) 4.07E-02 231211_PM_s_at ZBED2 1.88 zinc finger, BED-type containing 2 1.36E-02 219836_PM_at ZBTB10 2.64 zinc finger and BTB domain containing 10 6.41E-04 219312_PM_s_at ZBTB38 1.41 zinc finger and BTB domain containing 38 4.94E-02 225512_PM_at ZDHHC2 2.04 zinc finger, DHHC-type containing 2 5.04E-04 222731_PM_at ZEB1 1.37 zinc finger E-box binding homeobox 1 2.27E-02 212764_PM_at ZFAND2A 1.25 zinc finger, AN1-type domain 2A 3.61E-02 226650_PM_at ZFHX3 1.51 Zinc finger homeobox 3 1.62E-02 226137_PM_at ZFP36L1 1.82 zinc finger protein 36, C3H type-like 1 1.01E-03 211965_PM_at ZFPM2 1.93 zinc finger protein, multitype 2 1.36E-02 219778_PM_at ZG16B 1.78 zymogen granule protein 16 homolog B (rat) 1.57E-02 228058_PM_at ZKSCAN5 1.33 zinc finger with KRAB and SCAN domains 5 3.03E-02 203730_PM_s_at ZMYM6 1.31 zinc finger, MYM-type 6 4.94E-02 213698_PM_at ZNF143 1.40 zinc finger protein 143 6.15E-03 221873_PM_at ZNF148 1.47 zinc finger protein 148 2.23E-02 230821_PM_at ZNF165 1.54 zinc finger protein 165 4.57E-03 206683_PM_at ZNF193 1.45 zinc finger protein 193 4.26E-03 205181_PM_at ZNF219 1.30 Zinc finger protein 219 4.98E-02 222864_PM_s_at ZNF280B 1.40 zinc finger protein 280B 3.81E-02 229360_PM_at ZNF354A 1.29 zinc finger protein 354A 4.29E-02 205427_PM_at ZNF468 1.25 zinc finger protein 468 3.29E-02 214751_PM_at ZNF655 1.74 zinc finger protein 655 1.20E-03 223302_PM_s_at ZNF702P 2.41 zinc finger protein 702 (pseudogene) 9.07E-03 206557_PM_at ZNF711 1.44 zinc finger protein 711 4.86E-02 228988_PM_at ZPLD1 1.58 zona pellucida-like domain containing 1 2.67E-02 1561969_PM_at ZSCAN18 1.29 zinc finger and SCAN domain containing 18 3.76E-02 232866_PM_at ZSWIM6 1.34 zinc finger, SWIM-type containing 6 1.17E-02 226208_PM_at ZXDA 1.39 zinc finger, X-linked, duplicated A 2.07E-02 243521_PM_at ZXDB 1.88 zinc finger, X-linked, duplicated B 4.22E-03 228005_PM_at ZXDC 1.68 ZX D family zinc finger C 4.31E-02 230209_PM_at Given are abbreviation (Gene alias), fold change (FC), short description (Gene name/description), P-value, and probe ID (Gene ID).

Gene Expression of Airway Epithelium 85 Table S3. Genes that were significantly higher expressed by healthy nasal epithelial cells Gene alias FC Gene name/description P-value Gene ID AASDH 1.35 aminoadipate-semialdehyde dehydrogenase 1.18E-02 228041_PM_at ATP-binding cassette, sub-family A (ABC1), ABCA12 3.04 member 12 7.67E-04 215465_PM_at ABHD14B 1.37 abhydrolase domain containing 14B 1.26E-02 224821_PM_at ABHD6 1.41 abhydrolase domain containing 6 2.37E-02 221552_PM_at ACAA2 3.61 acetyl-CoA acyltransferase 2 3.75E-03 202003_PM_s_at ACP2 1.38 acid phosphatase 2, lysosomal 3.57E-02 202767_PM_at ACP5 2.16 acid phosphatase 5, tartrate resistant 6.49E-04 204638_PM_at ACPP 1.60 acid phosphatase, prostate 2.69E-03 204393_PM_s_at ACTG2 6.16 actin, gamma 2, smooth muscle, enteric 2.60E-03 202274_PM_at ADAMTSL4 1.51 ADAMTS-like 4 2.09E-02 220578_PM_at ADAP2 2.25 ArfGAP with dual PH domains 2 3.04E-04 222876_PM_s_at Adenosine deaminase, RNA-specific, B1 (RED1 ADARB1 2.48 homolog rat) 3.51E-03 203865_PM_s_at ADCY7 1.73 adenylate cyclase 7 2.95E-02 203741_PM_s_at alcohol dehydrogenase 7 (class IV), mu or sigma ADH7 2.49 polypeptide 1.52E-02 210505_PM_at ADM 1.54 adrenomedullin 2.99E-02 202912_PM_at AEBP1 3.08 AE binding protein 1 2.34E-02 201792_PM_at AFAP1L2 1.29 actin filament associated protein 1-like 2 1.12E-02 226829_PM_at AHCYL2 1.41 adenosylhomocysteinase-like 2 3.80E-03 212814_PM_at AHR 1.39 aryl hydrocarbon receptor 4.32E-02 202820_PM_at AJAP1 1.47 adherens junctions associated protein 1 1.69E-02 206460_PM_at aldo-keto reductase family 1, member C3 AKR1C3 1.82 (3-alpha hydroxysteroid dehydrogenase, type II) 1.98E-02 209160_PM_at ALDH18A1 1.23 aldehyde dehydrogenase 18 family, member A1 3.88E-02 222416_PM_at ALDH1L2 3.57 aldehyde dehydrogenase 1 family, member L2 2.38E-03 231202_PM_at ALDH3B2 2.97 aldehyde dehydrogenase 3 family, member B2 1.52E-03 204942_PM_s_at ALDH4A1 1.32 aldehyde dehydrogenase 4 family, member A1 4.43E-02 203722_PM_at ALDH6A1 1.36 aldehyde dehydrogenase 6 family, member A1 1.00E-02 221589_PM_s_at asparagine-linked glycosylation 10, alpha-1,2- ALG10 1.34 glucosyltransferase homolog (S. pombe) 2.56E-02 1552306_PM_at ALKBH2 1.34 alkB, alkylation repair homolog 2 (E. coli) 1.22E-02 225625_PM_at ALOX12B 2.23 arachidonate 12-lipoxygenase, 12R type 4.86E-02 207381_PM_at ALOX15B 2.81 arachidonate 15-lipoxygenase, type B 5.54E-03 206714_PM_at ANAPC5 1.22 anaphase promoting complex subunit 5 4.09E-02 211036_PM_x_at ANAPC7 1.35 anaphase promoting complex subunit 7 1.81E-02 225521_PM_at ANGEL2 1.25 angel homolog 2 (Drosophila) 3.88E-02 221826_PM_at ANK3 1.78 ankyrin 3, node of Ranvier (ankyrin G) 5.30E-03 209442_PM_x_at ANKH 1.34 ankylosis, progressive homolog (mouse) 1.84E-02 223092_PM_at ANKRD22 1.60 ankyrin repeat domain 22 1.30E-02 238439_PM_at ANO1 3.34 anoctamin 1, calcium activated chloride channel 2.45E-02 218804_PM_at ANPEP 1.98 Alanyl (membrane) aminopeptidase 8.01E-03 202888_PM_s_at ANUBL1 1.30 AN1, ubiquitin-like, homolog (Xenopus laevis) 2.44E-02 223624_PM_at ANXA6 3.28 annexin A6 8.85E-03 200982_PM_s_at APOE 1.88 apolipoprotein E 5.30E-03 203382_PM_s_at APOO 1.40 apolipoprotein O 8.47E-03 221620_PM_s_at

86 Chapter 3 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID ARHGAP1 1.26 Rho GTPase activating protein 1 3.30E-02 202117_PM_at ARHGAP18 1.90 Rho GTPase activating protein 18 4.90E-04 225173_PM_at ARHGAP28 1.63 Rho GTPase activating protein 28 1.67E-02 227911_PM_at Rho guanine nucleotide exchange factor (GEF) ARHGEF37 1.60 37 6.33E-03 227717_PM_at Cdc42 guanine nucleotide exchange factor ARHGEF9 1.55 (GEF) 9 4.08E-03 203264_PM_s_at ARID1B 1.24 AT rich interactive domain 1B (SWI1-like) 3.61E-02 225181_PM_at ARMCX1 1.83 armadillo repeat containing, X-linked 1 1.52E-03 218694_PM_at ARRDC3 1.56 arrestin domain containing 3 1.34E-02 224797_PM_at ARSI 3.09 arylsulfatase family, member I 2.00E-04 230275_PM_at ARV1 1.46 ARV1 homolog (S. cerevisiae) 5.07E-03 223223_PM_at N-acylsphingosine amidohydrolase (acid ASAH1 1.31 ceramidase) 1 3.09E-02 213902_PM_at ASAM 8.12 adipocyte-specific adhesion molecule 1.50E-04 228082_PM_at ArfGAP with SH3 domain, ankyrin repeat and PH ASAP3 1.43 domain 3 3.74E-02 222236_PM_s_at ASMTL 1.37 acetylserotonin O-methyltransferase-like 8.53E-03 36553_PM_at ASPRV1 6.49 aspartic peptidase, retroviral-like 1 5.43E-03 235514_PM_at ATG9 autophagy related 9 homolog B (S. ATG9B 1.34 cerevisiae) 1.68E-02 229252_PM_at ATL2 1.26 atlastin GTPase 2 4.02E-02 222700_PM_at ATMIN 1.29 ATM interactor 1.05E-02 201855_PM_s_at ATPase, Na+/K+ transporting, alpha 1 ATP1A1 1.29 polypeptide 1.82E-02 220948_PM_s_at ATP2B1 1.35 ATPase, Ca++ transporting, plasma membrane 1 7.44E-03 215716_PM_s_at ATP2B4 1.30 ATPase, Ca++ transporting, plasma membrane 4 3.02E-02 212135_PM_s_at ATP2C1 1.20 ATPase, Ca++ transporting, type 2C, member 1 4.58E-02 212255_PM_s_at ATPase, H+ transporting, lysosomal 42kDa, V1 1553989_PM_a_ ATP6V1C2 1.94 subunit C2 1.09E-02 at UDP-GlcNAc:betaGal beta-1,3-N- B3GNT4 1.22 acetylglucosaminyltransferase 4 4.47E-02 221240_PM_s_at B4GALNT3 1.71 beta-1,4-N-acetyl-galactosaminyl transferase 3 5.47E-03 229909_PM_at BACE1 1.59 beta-site APP-cleaving enzyme 1 2.35E-02 217904_PM_s_at BAG1 1.61 BCL2-associated athanogene 2.07E-02 229720_PM_at butyrobetaine (gamma), 2-oxoglutarate dioxygenase (gamma-butyrobetaine BBOX1 5.51 hydroxylase) 1 1.88E-03 205363_PM_at BC036928 1.24 hypothetical protein BC036928 4.77E-02 231260_PM_at basal cell adhesion molecule (Lutheran blood BCAM 1.37 group) 2.78E-02 40093_PM_at branched chain amino-acid transaminase 1, BCAT1 4.44 cytosolic 1.62E-05 226517_PM_at branched chain keto acid dehydrogenase E1, BCKDHB 1.49 beta polypeptide 1.54E-02 210653_PM_s_at BCL11A 1.36 B-cell CLL/lymphoma 11A (zinc finger protein) 2.73E-02 219497_PM_s_at BCL11B 2.02 B-cell CLL/lymphoma 11B (zinc finger protein) 2.64E-03 222895_PM_s_at BCL2L11 1.42 BCL2-like 11 (apoptosis facilitator) 3.43E-02 225606_PM_at

Gene Expression of Airway Epithelium 87 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID BCL2L13 1.34 BCL2-like 13 (apoptosis facilitator) 8.41E-03 217955_PM_at BCL2L2 1.28 BCL2-like 2 3.81E-02 209311_PM_at BCL7A 1.29 B-cell CLL/lymphoma 7A 3.25E-02 203796_PM_s_at BEX1 3.17 brain expressed, X-linked 1 6.72E-03 218332_PM_at BEX2 1.33 brain expressed X-linked 2 3.23E-02 224367_PM_at BGN 1.29 biglycan 3.19E-02 201261_PM_x_at basic, immunoglobulin-like variable motif BIVM 1.27 containing 4.09E-02 222761_PM_at bactericidal/permeability-increasing protein- BPIL2 2.88 like 2 8.36E-04 1555773_PM_at brain and reproductive organ-expressed BRE 1.30 (TNFRSF1A modulator) 2.48E-02 205550_PM_s_at BTBD11 1.56 BTB (POZ) domain containing 11 7.58E-03 228570_PM_at BVES 2.05 blood vessel epicardial substance 1.32E-03 228783_PM_at C10orf125 1.68 chromosome 10 open reading frame 125 1.86E-02 230259_PM_at C10orf57 1.40 chromosome 10 open reading frame 57 1.96E-02 218174_PM_s_at C10orf99 3.62 chromosome 10 open reading frame 99 1.11E-03 227736_PM_at C12orf28 2.61 chromosome 12 open reading frame 28 1.98E-02 1556267_PM_at C14orf1 1.25 chromosome 14 open reading frame 1 3.08E-02 217188_PM_s_at C14orf101 1.32 chromosome 14 open reading frame 101 2.60E-02 225675_PM_at C14orf128 1.51 chromosome 14 open reading frame 128 9.78E-03 228889_PM_at C14orf45 1.65 chromosome 14 open reading frame 45 1.67E-02 220173_PM_at C16orf70 1.30 chromosome 16 open reading frame 70 4.05E-02 223440_PM_at C18orf10 1.34 chromosome 18 open reading frame 10 1.86E-02 212055_PM_at C18orf21 1.25 chromosome 18 open reading frame 21 3.43E-02 223526_PM_at C1orf107 1.58 chromosome 1 open reading frame 107 3.06E-02 220251_PM_at C1orf131 1.27 chromosome 1 open reading frame 131 2.96E-02 226242_PM_at C1orf163 1.54 chromosome 1 open reading frame 163 4.45E-02 222883_PM_at C1orf216 1.41 chromosome 1 open reading frame 216 3.28E-02 212791_PM_at C1orf59 1.43 chromosome 1 open reading frame 59 1.15E-02 225841_PM_at C1R 4.60 complement component 1, r subcomponent 4.67E-03 212067_PM_s_at C1S 7.12 complement component 1, s subcomponent 9.28E-03 208747_PM_s_at C20orf108 1.49 chromosome 20 open reading frame 108 5.81E-03 224690_PM_at C21orf33 1.22 chromosome 21 open reading frame 33 3.75E-02 202217_PM_at C21orf63 1.89 chromosome 21 open reading frame 63 3.07E-04 227188_PM_at C21orf91 1.33 chromosome 21 open reading frame 91 2.36E-02 220941_PM_s_at C21orf96 9.85 chromosome 21 open reading frame 96 2.68E-04 220918_PM_at C2CD4A 1.40 C2 calcium-dependent domain containing 4A 2.23E-02 241031_PM_at C2orf18 1.59 chromosome 2 open reading frame 18 6.17E-03 225695_PM_at C2orf74 1.33 chromosome 2 open reading frame 74 2.54E-02 1568658_PM_at C3 3.30 complement component 3 2.21E-02 217767_PM_at C3orf1 1.23 chromosome 3 open reading frame 1 2.86E-02 223004_PM_s_at C3orf14 1.32 chromosome 3 open reading frame 14 2.38E-02 219288_PM_at C3orf34 1.47 chromosome 3 open reading frame 34 2.89E-02 230860_PM_at C4orf32 1.25 chromosome 4 open reading frame 32 3.44E-02 227856_PM_at C4orf33 1.33 chromosome 4 open reading frame 33 2.29E-02 1552370_PM_at C4orf48 1.24 chromosome 4 open reading frame 48 3.88E-02 229860_PM_x_at

88 Chapter 3 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID C4orf49 2.97 chromosome 4 open reading frame 49 1.88E-03 223734_PM_at C5orf33 1.31 chromosome 5 open reading frame 33 2.76E-02 228594_PM_at 1554195_PM_a_ C5orf46 7.41 chromosome 5 open reading frame 46 4.22E-03 at C5orf62 2.61 chromosome 5 open reading frame 62 5.51E-03 223276_PM_at C6orf105 2.30 chromosome 6 open reading frame 105 1.18E-03 229070_PM_at C6orf192 1.57 chromosome 6 open reading frame 192 6.13E-03 226301_PM_at C7orf60 1.55 chromosome 7 open reading frame 60 5.84E-03 228149_PM_at C8orf48 2.04 chromosome 8 open reading frame 48 9.56E-03 236634_PM_at C9orf3 1.58 Chromosome 9 open reading frame 3 6.62E-03 212848_PM_s_at C9orf40 1.28 chromosome 9 open reading frame 40 4.91E-02 218904_PM_s_at C9orf91 1.27 chromosome 9 open reading frame 91 2.31E-02 221865_PM_at C9orf95 1.51 chromosome 9 open reading frame 95 3.08E-03 219147_PM_s_at CA2 2.81 carbonic anhydrase II 1.86E-02 209301_PM_at chaperone, ABC1 activity of bc1 complex CABC1 1.38 homolog (S. pombe) 1.70E-02 218168_PM_s_at CALB2 1.34 calbindin 2 2.15E-02 205428_PM_s_at CALCOCO2 1.23 calcium binding and coiled-coil domain 2 2.13E-02 235076_PM_at CALHM2 1.32 calcium homeostasis modulator 2 2.89E-02 221565_PM_s_at CALML5 2.44 calmodulin-like 5 2.20E-02 220414_PM_at calcium/calmodulin-dependent protein kinase CAMK1D 1.40 ID 4.83E-02 235626_PM_at calcium/calmodulin-dependent protein kinase CAMK2D 1.58 II delta 5.89E-03 224994_PM_at CAPN12 1.35 calpain 12 4.98E-02 228705_PM_at 1552701_PM_a_ CARD16 1.87 caspase recruitment domain family, member 16 3.22E-02 at caspase recruitment domain family, member 16 /// caspase 1, apoptosis-related cysteine 1552703_PM_s_ CARD16 /// CASP1 2.27 peptidase (interleukin 1, beta, convertase) 2.54E-03 at CARD18 18.20 caspase recruitment domain family, member 18 1.40E-04 231733_PM_at cysteinyl-tRNA synthetase 2, mitochondrial CARS2 1.34 (putative) 2.97E-02 218153_PM_at caspase 1, apoptosis-related cysteine peptidase CASP1 2.81 (interleukin 1, beta, convertase) 1.78E-04 206011_PM_at CASP4 1.90 caspase 4, apoptosis-related cysteine peptidase 8.10E-04 213596_PM_at CAT 1.39 Catalase 3.57E-02 201432_PM_at CBR1 1.28 carbonyl reductase 1 4.91E-02 209213_PM_at 1553972_PM_a_ CBS 1.41 cystathionine-beta-synthase 4.79E-02 at chromobox homolog 2 (Pc class homolog, CBX2 2.05 Drosophila) 3.97E-03 226473_PM_at CBX6 1.56 chromobox homolog 6 1.21E-02 202047_PM_s_at CC2D2A 1.65 coiled-coil and C2 domain containing 2A 3.98E-02 234936_PM_s_at CCBL2 1.25 cysteine conjugate-beta lyase 2 2.64E-02 209472_PM_at CCDC115 1.36 coiled-coil domain containing 115 1.06E-02 224946_PM_s_at CCDC41 1.30 coiled-coil domain containing 41 4.83E-02 219644_PM_at CCDC51 1.37 coiled-coil domain containing 51 1.88E-02 218722_PM_s_at

Gene Expression of Airway Epithelium 89 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID CCDC8 3.71 coiled-coil domain containing 8 5.63E-03 223495_PM_at CD109 1.31 CD109 molecule 3.97E-02 226545_PM_at CD36 1.82 CD36 molecule (thrombospondin receptor) 3.93E-02 209555_PM_s_at CDC25B 1.77 cell division cycle 25 homolog B (S. pombe) 6.72E-03 201853_PM_s_at CDHR1 1.26 cadherin-related family member 1 4.27E-02 1555019_PM_at CDK20 1.30 cyclin-dependent kinase 20 2.17E-02 205271_PM_s_at cyclin-dependent kinase inhibitor 2A CDKN2A 4.04 (melanoma, p16, inhibits CDK4) 5.30E-03 207039_PM_at CDSN 2.34 corneodesmosin 1.69E-02 206192_PM_at cadherin, EGF LAG seven-pass G-type receptor 2 CELSR2 1.42 (flamingo homolog, Drosophila) 2.07E-02 36499_PM_at CEMP1 1.39 Cementum protein 1 2.31E-02 227841_PM_at CGNL1 2.12 cingulin-like 1 1.33E-02 225817_PM_at coiled-coil-helix-coiled-coil-helix domain CHCHD10 1.40 containing 10 6.72E-03 224932_PM_at CHD2 1.23 Chromodomain helicase DNA binding protein 2 3.75E-02 244443_PM_at Cbp/p300-interacting transactivator, with Glu/ CITED2 2.74 Asp-rich carboxy-terminal domain, 2 5.38E-04 209357_PM_at CLCA2 1.80 chloride channel accessory 2 4.57E-03 206166_PM_s_at CLDN11 7.58 claudin 11 7.42E-03 228335_PM_at CLDN17 2.24 claudin 17 3.54E-02 221328_PM_at CLIC3 1.30 chloride intracellular channel 3 1.05E-02 219529_PM_at CLIC4 1.54 chloride intracellular channel 4 6.62E-03 201560_PM_at CLIP3 1.35 CAP-GLY domain containing linker protein 3 1.89E-02 212358_PM_at CLPX 1.25 ClpX caseinolytic peptidase X homolog (E. coli) 1.81E-02 223507_PM_at CNFN 3.26 cornifelin 4.29E-04 224329_PM_s_at connector enhancer of kinase suppressor of CNKSR2 1.41 Ras 2 3.55E-02 229116_PM_at CNKSR3 1.51 CNKSR family member 3 2.54E-02 227481_PM_at CNP 1.30 2',3'-cyclic nucleotide 3' phosphodiesterase 2.50E-02 208912_PM_s_at CNTN1 2.26 Contactin 1 4.55E-03 227202_PM_at CNTN3 2.12 contactin 3 (plasmacytoma associated) 3.19E-02 229831_PM_at CNTNAP3 1.71 contactin associated protein-like 3 3.32E-02 223796_PM_at COL12A1 3.21 collagen, type XII, alpha 1 6.49E-03 225664_PM_at COL4A1 4.39 collagen, type IV, alpha 1 1.93E-03 211981_PM_at COL4A2 4.29 collagen, type IV, alpha 2 9.63E-03 211964_PM_at COL6A1 9.89 collagen, type VI, alpha 1 1.41E-04 213428_PM_s_at catechol-O-methyltransferase domain COMTD1 1.47 containing 1 2.37E-02 226870_PM_at COX5B 1.28 Cytochrome c oxidase subunit Vb 2.15E-02 202343_PM_x_at cytochrome c oxidase subunit VIIa polypeptide COX7A1 1.95 1 (muscle) 4.81E-02 204570_PM_at CPA4 3.01 carboxypeptidase A4 4.57E-02 205832_PM_at CPE 3.69 carboxypeptidase E 3.66E-03 201116_PM_s_at CPS1 2.83 carbamoyl-phosphate synthase 1, mitochondrial 6.14E-05 204920_PM_at CPT1A 1.40 carnitine palmitoyltransferase 1A (liver) 3.52E-02 203633_PM_at CPT2 1.50 carnitine palmitoyltransferase 2 2.26E-03 204263_PM_s_at

90 Chapter 3 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID CRBN 1.28 cereblon 2.05E-02 222533_PM_at CREG1 2.53 cellular repressor of E1A-stimulated genes 1 7.67E-04 201200_PM_at cysteine-rich secretory protein LCCL domain CRISPLD1 1.57 containing 1 3.00E-02 223475_PM_at CRNN 2.48 cornulin 4.83E-02 220090_PM_at CRYAB 6.83 crystallin, alpha B 1.39E-04 209283_PM_at CSAD 1.34 cysteine sulfinic acid decarboxylase 3.38E-02 221139_PM_s_at chondroitin sulfate CSGALNACT1 2.24 N-acetylgalactosaminyltransferase 1 3.27E-02 219049_PM_at CSPG4 3.27 chondroitin sulfate proteoglycan 4 6.51E-03 214297_PM_at CSRNP3 1.40 cysteine-serine-rich nuclear protein 3 4.66E-02 235355_PM_at CSRP2BP 1.83 CSRP2 binding protein 4.66E-04 225432_PM_s_at cleavage stimulation factor, 3' pre-RNA, subunit CSTF1 1.24 1, 50kDa 2.38E-02 202190_PM_at CTSC 2.71 cathepsin C 5.20E-03 225646_PM_at CTSK 2.02 cathepsin K 7.58E-03 202450_PM_s_at CTSL1 1.42 cathepsin L1 5.16E-03 202087_PM_s_at cell wall biogenesis 43 C-terminal homolog (S. CWH43 4.20 cerevisiae) 5.85E-05 220724_PM_at CXCL10 7.56 chemokine (C-X-C motif) ligand 10 2.44E-02 204533_PM_at CXCL11 8.28 chemokine (C-X-C motif) ligand 11 2.42E-03 211122_PM_s_at CXCL14 1.31 chemokine (C-X-C motif) ligand 14 3.90E-02 237038_PM_at CXCL5 2.45 chemokine (C-X-C motif) ligand 5 1.80E-03 214974_PM_x_at CYB5D1 1.37 cytochrome b5 domain containing 1 3.81E-02 226833_PM_at CYB5R1 1.43 cytochrome b5 reductase 1 1.14E-02 202263_PM_at CYB5R2 2.72 cytochrome b5 reductase 2 3.77E-04 220230_PM_s_at CYBRD1 2.29 cytochrome b reductase 1 6.88E-03 222453_PM_at CYGB 2.97 cytoglobin 4.37E-03 226632_PM_at cytochrome P450, family 1, subfamily B, CYP1B1 2.80 polypeptide 1 3.00E-02 202437_PM_s_at cytochrome P450, family 26, subfamily B, CYP26B1 3.13 polypeptide 1 2.74E-03 219825_PM_at cytochrome P450, family 39, subfamily A, 1553977_PM_a_ CYP39A1 1.40 polypeptide 1 4.72E-02 at DNA segment on chromosome 4 (unique) 234 D4S234E /// FOXP1 1.67 expressed sequence /// forkhead box P1 4.61E-03 213533_PM_at disabled homolog 2, mitogen-responsive DAB2 2.26 phosphoprotein (Drosophila) 1.01E-03 201280_PM_s_at DAPK1 3.53 death-associated protein kinase 1 1.61E-03 203139_PM_at DBC1 4.04 deleted in bladder cancer 1 7.79E-04 205818_PM_at diazepam binding inhibitor (GABA receptor DBI 1.39 modulator, acyl-CoA binding protein) 1.02E-02 209389_PM_x_at DCAF6 1.26 DDB1 and CUL4 associated factor 6 3.08E-02 217908_PM_s_at DCBLD1 1.75 discoidin, CUB and LCCL domain containing 1 6.45E-03 226609_PM_at DDX58 2.12 DEAD (Asp-Glu-Ala-Asp) box polypeptide 58 1.21E-02 242961_PM_x_at DEM1 1.31 defects in morphology 1 homolog (S. cerevisiae) 1.58E-02 222902_PM_s_at DENND1A 1.38 DENN/MADD domain containing 1A 1.95E-02 219763_PM_at DEPDC7 3.53 DEP domain containing 7 1.48E-03 228293_PM_at

Gene Expression of Airway Epithelium 91 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID diacylglycerol O-acyltransferase homolog 2 DGAT2 1.54 (mouse) 1.77E-02 224327_PM_s_at DGCR14 1.27 DiGeorge syndrome critical region gene 14 3.81E-02 204383_PM_at DHDH 1.58 dihydrodiol dehydrogenase (dimeric) 1.01E-02 231416_PM_at dehydrogenase/reductase (SDR family) member DHRS1 1.54 1 3.01E-03 213279_PM_at dehydrogenase/reductase (SDR family) member 4 /// dehydrogenase/reductase (SDR family) DHRS4 /// DHRS4L2 1.23 member 4 like 2 4.98E-02 218021_PM_at DIRC2 1.39 disrupted in renal carcinoma 2 1.90E-02 226026_PM_at DIXDC1 1.65 DIX domain containing 1 3.25E-02 214724_PM_at DLK2 1.81 delta-like 2 homolog (Drosophila) 1.14E-02 220262_PM_s_at DLX1 2.24 distal-less homeobox 1 6.79E-03 242138_PM_at DLX2 2.27 distal-less homeobox 2 1.08E-03 207147_PM_at DLX5 3.27 distal-less homeobox 5 1.41E-04 213707_PM_s_at DLX6 1.55 distal-less homeobox 6 7.87E-03 239309_PM_at DLX6AS 1.33 DLX6 antisense RNA (non-protein coding) 4.37E-02 230882_PM_at DMD 2.16 Dystrophin 7.90E-04 203881_PM_s_at DMKN 1.50 dermokine 4.54E-03 226926_PM_at DNAH5 4.25 dynein, axonemal, heavy chain 5 7.17E-03 243938_PM_x_at DNER 1.88 delta/notch-like EGF repeat containing 2.75E-02 226281_PM_at DOCK11 2.41 dedicator of cytokinesis 11 1.01E-03 226875_PM_at DPH5 1.44 DPH5 homolog (S. cerevisiae) 3.44E-02 222360_PM_at DSC1 1.88 desmocollin 1 9.68E-03 207324_PM_s_at DSC2 2.35 desmocollin 2 1.08E-03 204750_PM_s_at DSC3 1.47 desmocollin 3 8.28E-03 206033_PM_s_at DSG1 37.49 desmoglein 1 1.47E-05 206642_PM_at DSG3 1.96 desmoglein 3 (pemphigus vulgaris antigen) 1.13E-02 205595_PM_at DTWD1 1.47 DTW domain containing 1 1.00E-02 219291_PM_at dihydrouridine synthase 2-like, SMM1 homolog DUS2L 1.32 (S. cerevisiae) 1.98E-02 219486_PM_at DUSP28 1.56 dual specificity phosphatase 28 1.78E-02 229211_PM_at dual-specificity tyrosine-(Y)-phosphorylation DYRK2 1.32 regulated kinase 2 4.81E-02 202971_PM_s_at DYX1C1 1.31 dyslexia susceptibility 1 candidate 1 4.57E-02 241713_PM_s_at DZIP1 2.87 DAZ interacting protein 1 4.02E-04 204557_PM_s_at ECHDC3 2.34 enoyl CoA hydratase domain containing 3 1.39E-02 219298_PM_at extracellular matrix protein 2, female organ and ECM2 1.32 adipocyte specific 2.17E-02 206101_PM_at enhancer of mRNA decapping 3 homolog (S. EDC3 1.25 cerevisiae) 3.37E-02 226042_PM_at EEF2K 1.23 eukaryotic elongation factor-2 kinase 4.50E-02 225545_PM_at EFNB3 1.31 ephrin-B3 3.15E-02 205031_PM_at EFS 1.46 embryonal Fyn-associated substrate 3.83E-02 204400_PM_at EGFL6 4.00 EGF-like-domain, multiple 6 8.02E-03 219454_PM_at enoyl-CoA, hydratase/3-hydroxyacyl CoA EHHADH 1.35 dehydrogenase 1.55E-02 205222_PM_at

92 Chapter 3 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID eukaryotic translation initiation factor 3, subunit EIF3K 1.26 K 2.18E-02 221494_PM_x_at ELAC1 1.53 elaC homolog 1 (E. coli) 4.08E-02 222869_PM_s_at ELAV (embryonic lethal, abnormal vision, ELAVL2 21.73 Drosophila)-like 2 (Hu antigen B) 1.40E-05 228260_PM_at elongation of very long chain fatty acids (FEN1/ ELOVL4 1.79 Elo2, SUR4/Elo3, yeast)-like 4 2.85E-03 219532_PM_at ELOVL family member 7, elongation of long ELOVL7 1.32 chain fatty acids (yeast) 3.99E-02 227180_PM_at essential meiotic endonuclease 1 homolog 2 (S. EME2 1.28 pombe) 2.09E-02 1556024_PM_at ENAH 1.29 Enabled homolog (Drosophila) 2.86E-02 222433_PM_at ENDOD1 1.74 endonuclease domain containing 1 9.84E-03 212573_PM_at ENDOU 1.75 endonuclease, polyU-specific 1.34E-02 206605_PM_at ENOSF1 1.36 enolase superfamily member 1 2.19E-02 204143_PM_s_at EPB41L3 1.65 erythrocyte membrane protein band 4.1-like 3 1.45E-02 212681_PM_at EPHA4 3.00 EPH receptor A4 5.31E-04 206114_PM_at EPHB3 1.70 EPH receptor B3 5.51E-03 1438_PM_at EPHX2 1.44 epoxide hydrolase 2, cytoplasmic 8.16E-03 209368_PM_at EPHX3 1.94 epoxide hydrolase 3 2.40E-03 220013_PM_at EPM2AIP1 1.60 EPM2A (laforin) interacting protein 1 7.71E-03 227847_PM_at EPRS 1.23 glutamyl-prolyl-tRNA synthetase 4.32E-02 200842_PM_s_at epidermal growth factor receptor pathway EPS15L1 1.40 substrate 15-like 1 2.96E-02 231926_PM_at EPS8L2 1.23 EPS8-like 2 4.24E-02 218180_PM_s_at v-erb-b2 erythroblastic leukemia viral oncogene homolog 2, neuro/glioblastoma derived ERBB2 1.35 oncogene homolog (avian) 3.71E-02 216836_PM_s_at EREG 1.79 epiregulin 1.74E-03 205767_PM_at ERP27 3.04 endoplasmic reticulum protein 27 3.73E-04 227450_PM_at ESR1 1.27 estrogen receptor 1 2.31E-02 205225_PM_at ESYT3 1.41 extended synaptotagmin-like protein 3 8.01E-03 239770_PM_at ETFB 1.26 electron-transfer-flavoprotein, beta polypeptide 3.13E-02 202942_PM_at electron-transferring-flavoprotein ETFDH 1.38 dehydrogenase 2.29E-02 205530_PM_at V-ets erythroblastosis virus E26 oncogene ETS2 1.32 homolog 2 (avian) 1.93E-02 201328_PM_at EVL 1.45 Enah/Vasp-like 1.14E-02 217838_PM_s_at EXOG 1.35 endo/exonuclease (5'-3'), endonuclease G-like 4.17E-02 205521_PM_at EXOSC5 1.37 exosome component 5 1.11E-02 218481_PM_at EXPH5 1.67 Exophilin 5 2.89E-02 213929_PM_at fatty acid binding protein 3, muscle and heart FABP3 1.46 (mammary-derived growth inhibitor) 3.08E-02 205738_PM_s_at fatty acid binding protein 5 (psoriasis- FABP5 3.31 associated) 2.65E-04 202345_PM_s_at Fumarylacetoacetate hydrolase FAH 1.42 (fumarylacetoacetase) 2.25E-02 202862_PM_at FAM110B 1.44 family with sequence similarity 110, member B 5.85E-03 221959_PM_at

Gene Expression of Airway Epithelium 93 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID FAM134B 1.44 family with sequence similarity 134, member B 3.93E-02 218510_PM_x_at FAM135A 1.23 family with sequence similarity 135, member A 3.69E-02 223497_PM_at FAM156A /// FAM156B 1.29 members of family with sequence similarity 156 9.96E-03 223203_PM_at FAM167A 1.50 Family with sequence similarity 167, member A 2.55E-02 226614_PM_s_at FAM169A 1.60 family with sequence similarity 169, member A 1.99E-03 235048_PM_at family with sequence similarity 19 (chemokine FAM19A2 1.21 (C-C motif)-like), member A2 4.31E-02 241399_PM_at FAM200B 1.23 family with sequence similarity 200, member B 3.77E-02 227466_PM_at FAM21A /// FAM21B /// FAM21C 1.28 members of family with sequence similarity 21 4.89E-02 212370_PM_x_at FAM21A /// FAM21B /// FAM21C /// FAM21D 1.24 members of family with sequence similarity 21 4.37E-02 212929_PM_s_at FAM21A /// FAM21C /// FAM21D 1.25 members of family with sequence similarity 21 4.82E-02 214946_PM_x_at FAM21C /// FAM21D 1.30 members of family with sequence similarity 21 1.54E-02 211068_PM_x_at FAM46B 1.66 family with sequence similarity 46, member B 1.56E-02 229518_PM_at FAM49A 1.65 family with sequence similarity 49, member A 2.74E-02 209683_PM_at FAM83B 1.57 family with sequence similarity 83, member B 3.85E-03 1563900_PM_at FAM84A 1.65 Family with sequence similarity 84, member A 1.37E-02 231439_PM_at FAM89A 1.85 family with sequence similarity 89, member A 4.17E-03 226448_PM_at FAM8A1 1.28 family with sequence similarity 8, member A1 1.86E-02 203420_PM_at FAP 12.49 fibroblast activation protein, alpha 8.27E-05 209955_PM_s_at FAT1 1.35 FAT tumor suppressor homolog 1 (Drosophila) 2.40E-02 201579_PM_at FAT2 1.99 FAT tumor suppressor homolog 2 (Drosophila) 1.42E-03 208153_PM_s_at FBLN2 1.53 fibulin 2 4.61E-03 203886_PM_s_at FBXO32 2.43 F-box protein 32 4.17E-02 225803_PM_at FBXO4 1.43 F-box protein 4 2.64E-02 223493_PM_at FCHSD2 1.39 FCH and double SH3 domains 2 3.75E-02 203620_PM_s_at FECH 1.34 ferrochelatase 9.16E-03 203116_PM_s_at FGF2 1.91 fibroblast growth factor 2 (basic) 1.18E-02 204422_PM_s_at FGFR2 1.70 fibroblast growth factor receptor 2 1.92E-02 203639_PM_s_at FIBIN 1.64 fin bud initiation factor homolog (zebrafish) 2.31E-02 226769_PM_at FIGN 1.47 fidgetin 2.21E-02 238964_PM_at FKBP10 1.75 FK506 binding protein 10, 65 kDa 9.32E-03 219249_PM_s_at FLI1 2.42 Friend leukemia virus integration 1 2.72E-02 204236_PM_at FLJ13744 1.76 hypothetical FLJ13744 2.39E-02 1553413_PM_at FLJ22536 1.27 hypothetical locus LOC401237 4.12E-02 229280_PM_s_at FMO4 1.42 flavin containing monooxygenase 4 2.49E-02 206263_PM_at Forkhead box C2 (MFH-1, mesenchyme forkhead FOXC2 2.70 1) 1.32E-03 239058_PM_at FOXG1 96.51 forkhead box G1 5.33E-07 206018_PM_at FAD-dependent oxidoreductase domain FOXRED2 1.31 containing 2 4.32E-02 231846_PM_at FRAS1 1.65 Fraser syndrome 1 1.51E-02 226145_PM_s_at FRMD8 1.62 FERM domain containing 8 9.75E-03 227964_PM_at FST 1.73 follistatin 5.12E-03 207345_PM_at

94 Chapter 3 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID FXN 1.39 frataxin 3.03E-02 205565_PM_s_at FXYD domain containing ion transport regulator FXYD3 1.54 3 1.90E-02 202488_PM_s_at FYN 1.94 FYN oncogene related to SRC, FGR, YES 1.31E-03 212486_PM_s_at FZD7 2.89 frizzled homolog 7 (Drosophila) 1.59E-03 203706_PM_s_at GAA 1.50 glucosidase, alpha 1.05E-02 202812_PM_at GAB1 1.37 GRB2-associated binding protein 1 3.46E-02 225998_PM_at gamma-aminobutyric acid (GABA) A receptor, GABRE 1.49 epsilon 1.32E-02 204537_PM_s_at GAS1 10.88 growth arrest-specific 1 3.14E-05 204457_PM_s_at GATA3 3.64 GATA binding protein 3 4.39E-03 209604_PM_s_at glycine cleavage system protein H (aminomethyl GCSH /// carrier) /// glycine cleavage system protein H LOC100329108 1.26 pseudogene 3.95E-02 213129_PM_s_at ganglioside-induced differentiation-associated GDAP1 1.82 protein 1 2.97E-02 226269_PM_at golgi-associated, gamma adaptin ear containing, GGA2 1.34 ARF binding protein 2 9.01E-03 213772_PM_s_at GGCT 1.26 gamma-glutamylcyclotransferase 4.67E-02 215380_PM_s_at GJA5 2.41 gap junction protein, alpha 5, 40kDa 1.42E-02 226701_PM_at GJC1 3.60 gap junction protein, gamma 1, 45kDa 3.28E-02 228776_PM_at GLIPR2 2.47 GLI pathogenesis-related 2 2.93E-03 225602_PM_at GLS 1.68 glutaminase 1.01E-02 203158_PM_s_at GLT8D2 2.26 glycosyltransferase 8 domain containing 2 3.29E-02 227070_PM_at GLTP 1.74 glycolipid transfer protein 1.83E-03 219267_PM_at guanine nucleotide binding protein (G protein), GNB4 1.25 beta polypeptide 4 3.98E-02 225710_PM_at GOLGA1 1.31 golgin A1 2.22E-02 203383_PM_s_at GOLGA7B 1.68 golgin A7 family, member B 1.10E-02 228068_PM_at Golgi-associated PDZ and coiled-coil motif GOPC 1.61 containing 1.47E-03 227215_PM_at GPC6 4.57 glypican 6 1.16E-03 227059_PM_at GPM6B 2.10 glycoprotein M6B 9.08E-03 209170_PM_s_at GPNMB 5.52 glycoprotein (transmembrane) nmb 5.50E-03 201141_PM_at GPR56 1.33 G protein-coupled receptor 56 4.41E-02 212070_PM_at GPR85 1.56 G protein-coupled receptor 85 2.31E-02 234303_PM_s_at G-protein signaling modulator 1 (AGS3-like, C. GPSM1 1.33 elegans) 1.45E-02 226043_PM_at G-protein signaling modulator 2 (AGS3-like, C. GPSM2 1.26 elegans) 4.69E-02 230002_PM_at GPX7 1.29 glutathione peroxidase 7 4.63E-02 213170_PM_at GRAMD2 1.73 GRAM domain containing 2 1.39E-02 229616_PM_s_at GRB14 1.56 growth factor receptor-bound protein 14 1.21E-02 206204_PM_at GRHL1 1.42 grainyhead-like 1 (Drosophila) 2.43E-02 222830_PM_at General transcription factor IIH, polypeptide 1, GTF2H1 1.32 62kDa 2.42E-02 202451_PM_at GUCY1A3 3.14 guanylate cyclase 1, soluble, alpha 3 3.44E-03 227235_PM_at GXYLT2 1.60 glucoside xylosyltransferase 2 2.09E-02 235371_PM_at

Gene Expression of Airway Epithelium 95 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID GYG1 1.35 glycogenin 1 1.25E-02 201554_PM_x_at H2BFS 1.43 H2B histone family, member S 3.84E-02 208579_PM_x_at HAS3 1.30 hyaluronan synthase 3 4.75E-02 223541_PM_at HERC6 3.06 Hect domain and RLD 6 2.38E-02 219352_PM_at HIG1 hypoxia inducible domain family, member HIGD1A 1.28 1A 2.51E-02 242317_PM_at HIP1R /// huntingtin interacting protein 1 related /// LOC100294412 1.30 similar to KIAA0655 protein 3.73E-02 209558_PM_s_at HIPK2 1.25 homeodomain interacting protein kinase 2 3.43E-02 225368_PM_at HIST1H2AJ 1.25 histone cluster 1, H2aj 3.98E-02 208583_PM_x_at HIST1H2BF 1.41 histone cluster 1, H2bf 3.51E-02 208490_PM_x_at HIST1H2BI 1.32 histone cluster 1, H2bi 2.66E-02 208523_PM_x_at HIST1H2BK 1.42 histone cluster 1, H2bk 4.37E-02 209806_PM_at HIST1H4J 1.36 histone cluster 1, H4j 1.46E-02 214463_PM_x_at HIST1H4J /// HIST1H4K 1.36 members of histone cluster 1 3.51E-02 208580_PM_x_at high mobility group nucleosomal binding HMGN3 1.60 domain 3 4.39E-03 209377_PM_s_at HR 3.15 hairless homolog (mouse) 1.57E-03 241355_PM_at HRSP12 1.22 Heat-responsive protein 12 4.32E-02 203790_PM_s_at HSD17B2 2.37 hydroxysteroid (17-beta) dehydrogenase 2 9.80E-04 204818_PM_at HSD17B4 1.30 hydroxysteroid (17-beta) dehydrogenase 4 2.81E-02 201413_PM_at HSPA12A 2.28 heat shock 70kDa protein 12A 2.47E-04 214434_PM_at HSPB1 1.51 heat shock 27kDa protein 1 1.31E-02 201841_PM_s_at HSPB2 1.51 heat shock 27kDa protein 2 2.82E-03 205824_PM_at HSPC159 1.56 galectin-related protein 1.50E-02 226188_PM_at HTRA1 2.33 HtrA serine peptidase 1 3.21E-03 201185_PM_at inhibitor of DNA binding 2, dominant negative ID2 1.93 helix-loop-helix protein 5.31E-03 201565_PM_s_at inhibitor of DNA binding 3, dominant negative ID3 1.72 helix-loop-helix protein 4.36E-03 207826_PM_s_at IFI30 1.87 interferon, gamma-inducible protein 30 2.55E-03 201422_PM_at IFI6 6.41 interferon, alpha-inducible protein 6 3.44E-02 204415_PM_at interferon-induced protein with IFIT1 9.17 tetratricopeptide repeats 1 4.26E-02 203153_PM_at IFNA4 1.19 interferon, alpha 4 4.95E-02 207964_PM_x_at intraflagellar transport 122 homolog IFT122 1.44 (Chlamydomonas) 2.82E-03 220744_PM_s_at intraflagellar transport 46 homolog IFT46 1.28 (Chlamydomonas) 2.07E-02 218483_PM_s_at insulin-like growth factor 2 mRNA binding IGF2BP3 4.89 protein 3 1.78E-03 203819_PM_s_at IGF2R 1.28 insulin-like growth factor 2 receptor 4.94E-02 201392_PM_s_at IGFBP6 3.60 insulin-like growth factor binding protein 6 2.45E-02 203851_PM_at IGFL1 2.97 IGF-like family member 1 6.51E-03 239430_PM_at IGFL2 5.75 IGF-like family member 2 3.44E-02 231148_PM_at IGSF3 1.49 immunoglobulin superfamily, member 3 5.28E-03 202421_PM_at IL15 1.58 interleukin 15 4.32E-02 205992_PM_s_at

96 Chapter 3 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID IL17RA 1.39 interleukin 17 receptor A 8.12E-03 229101_PM_at IL17RD 1.54 interleukin 17 receptor D 1.88E-03 227997_PM_at IL1B 1.60 interleukin 1, beta 1.18E-02 39402_PM_at IL1F5 3.00 interleukin 1 family, member 5 (delta) 4.77E-04 222223_PM_s_at IL20 1.52 interleukin 20 2.21E-02 224071_PM_at IL20RB 1.51 interleukin 20 receptor beta 1.78E-02 228575_PM_at IL22RA1 1.53 interleukin 22 receptor, alpha 1 1.10E-02 220056_PM_at IMPA2 3.03 inositol(myo)-1(or 4)-monophosphatase 2 4.32E-03 203126_PM_at IMPACT 1.52 Impact homolog (mouse) 3.74E-03 218637_PM_at ING4 1.26 inhibitor of growth family, member 4 3.25E-02 218234_PM_at IRX1 3.38 iroquois homeobox 1 6.36E-04 230472_PM_at IRX4 19.69 iroquois homeobox 4 1.56E-06 220225_PM_at integrin, alpha 4 (antigen CD49D, alpha 4 ITGA4 2.30 subunit of VLA-4 receptor) 1.58E-02 213416_PM_at Integrin, beta-like 1 (with EGF-like repeat ITGBL1 1.83 domains) 5.16E-03 205422_PM_s_at IVL 2.61 involucrin 2.69E-03 214599_PM_at IVNS1ABP 1.49 influenza virus NS1A binding protein 4.00E-02 201362_PM_at JAK1 1.24 Janus kinase 1 4.02E-02 201648_PM_at JAM3 6.72 junctional adhesion molecule 3 1.33E-03 212813_PM_at JAZF1 1.47 JAZF zinc finger 1 1.13E-02 225798_PM_at JMJD7-PLA2G4B /// JMJD7-PLA2G4B readthrough /// phospholipase PLA2G4B 1.76 A2, group IVB (cytosolic) 6.35E-03 219095_PM_at junction mediating and regulatory protein, p53 JMY 1.35 cofactor 4.13E-02 226352_PM_at JPH2 1.84 junctophilin 2 5.14E-03 229578_PM_at JUP 1.25 junction plakoglobin 2.72E-02 201015_PM_s_at KANK4 11.68 KN motif and ankyrin repeat domains 4 4.11E-03 229125_PM_at KAZ 1.74 kazrin 5.47E-03 213478_PM_at KBTBD6 1.35 kelch repeat and BTB (POZ) domain containing 6 3.79E-02 226479_PM_at potassium voltage-gated channel, subfamily G, KCNG1 1.60 member 1 4.59E-03 214595_PM_at potassium channel tetramerisation domain KCTD1 1.50 containing 1 1.94E-02 226246_PM_at potassium channel tetramerisation domain KCTD18 1.29 containing 18 1.73E-02 226493_PM_at potassium channel tetramerisation domain KCTD4 3.43 containing 4 2.40E-03 239787_PM_at KDELC1 1.46 KDEL (Lys-Asp-Glu-Leu) containing 1 1.13E-02 219479_PM_at KDSR 1.28 3-ketodihydrosphingosine reductase 3.19E-02 229850_PM_at KIAA0141 1.28 KIAA0141 4.75E-02 227056_PM_at KIAA0528 1.31 KIAA0528 1.78E-02 212943_PM_at KIAA0922 1.37 KIAA0922 1.60E-02 209760_PM_at KIAA1609 1.38 KIAA1609 2.29E-02 65438_PM_at KIAA1644 1.92 KIAA1644 4.22E-03 221901_PM_at KIAA1737 1.41 KIAA1737 6.38E-03 225623_PM_at KIAA1919 1.34 KIAA1919 1.59E-02 242851_PM_at

Gene Expression of Airway Epithelium 97 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID KIF1C 1.58 kinesin family member 1C 1.55E-02 238477_PM_at KIF7 1.35 kinesin family member 7 1.36E-02 229405_PM_at KIFAP3 1.27 kinesin-associated protein 3 2.82E-02 203333_PM_at KLC3 1.57 kinesin light chain 3 2.59E-03 239853_PM_at KLHDC8B 1.51 kelch domain containing 8B 2.02E-02 225755_PM_at KLK10 2.18 kallikrein-related peptidase 10 1.67E-02 215808_PM_at KLK5 4.24 kallikrein-related peptidase 5 1.08E-03 222242_PM_s_at 1552319_PM_a_ KLK8 2.25 kallikrein-related peptidase 8 5.84E-03 at kallikrein-related peptidase 8 /// kallikrein- KLK8 /// KLK9 2.24 related peptidase 9 1.56E-02 233687_PM_s_at killer cell lectin-like receptor subfamily G, KLRG2 1.74 member 2 1.02E-02 244264_PM_at kynurenine 3-monooxygenase (kynurenine KMO 3.38 3-hydroxylase) 2.09E-02 205306_PM_x_at KRCC1 1.44 lysine-rich coiled-coil 1 5.31E-03 233329_PM_s_at KRT1 16.08 keratin 1 5.17E-04 205900_PM_at KRT10 1.67 keratin 10 2.45E-02 210633_PM_x_at KRT14 1.44 keratin 14 2.64E-03 209351_PM_at KRT15 1.58 keratin 15 2.31E-02 204734_PM_at KRT16 1.67 keratin 16 5.29E-03 209800_PM_at KRT23 4.30 keratin 23 (histone deacetylase inducible) 5.71E-04 218963_PM_s_at KRT6B 1.65 keratin 6B 2.54E-03 213680_PM_at KRT75 4.96 keratin 75 7.36E-03 207065_PM_at KRT81 11.69 keratin 81 4.22E-04 213711_PM_at KRTDAP 25.43 keratinocyte differentiation-associated protein 5.80E-05 230835_PM_at KSR1 1.42 kinase suppressor of ras 1 8.08E-03 235252_PM_at KTELC1 1.35 KTEL (Lys-Tyr-Glu-Leu) containing 1 7.17E-03 218587_PM_s_at L1TD1 5.92 LINE-1 type transposase domain containing 1 1.03E-03 219955_PM_at LACTB 1.46 lactamase, beta 4.51E-02 1552485_PM_at LAMA1 24.93 laminin, alpha 1 1.47E-06 227048_PM_at LAMP2 1.46 lysosomal-associated membrane protein 2 6.10E-03 203041_PM_s_at LanC lantibiotic synthetase component C-like 1 LANCL1 1.38 (bacterial) 2.78E-03 202020_PM_s_at LAPTM4A 1.29 lysosomal protein transmembrane 4 alpha 2.02E-02 200673_PM_at 1554252_PM_a_ LASS3 4.52 LAG1 homolog, ceramide synthase 3 1.79E-04 at LCE3D 3.64 late cornified envelope 3D 2.51E-02 224328_PM_s_at LCP1 6.91 lymphocyte cytosolic protein 1 (L-plastin) 3.05E-03 208885_PM_at Low density lipoprotein receptor class A domain LDLRAD3 1.33 containing 3 4.65E-02 234985_PM_at LEPROTL1 1.31 leptin receptor overlapping transcript-like 1 8.95E-03 202595_PM_s_at leucine zipper-EF-hand containing 1552546_PM_a_ LETM2 2.63 transmembrane protein 2 4.22E-03 at LHFPL2 2.18 lipoma HMGIC fusion partner-like 2 6.90E-03 212658_PM_at LIAS 1.65 lipoic acid synthetase 3.00E-02 214045_PM_at LINS1 1.37 lines homolog 1 (Drosophila) 2.54E-02 1554455_PM_at

98 Chapter 3 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID LIPA 1.44 lipase A, lysosomal acid, cholesterol esterase 2.23E-02 201847_PM_at LITAF 1.24 lipopolysaccharide-induced TNF factor 2.89E-02 200704_PM_at LMCD1 1.85 LIM and cysteine-rich domains 1 1.24E-02 218574_PM_s_at LOC100129502 1.43 hypothetical protein LOC100129502 6.38E-03 228791_PM_at LOC100132891 2.12 hypothetical protein LOC100132891 3.98E-02 228438_PM_at LOC100133660 1.81 Hypothetical LOC100133660 1.54E-02 230082_PM_at LOC100144603 1.34 hypothetical transcript 2.44E-02 238557_PM_at LOC100287482 1.46 Similar to hCG2038584 1.01E-02 235736_PM_at LOC100288152 1.50 Hypothetical protein LOC100288152 1.49E-02 226125_PM_at LOC100288294 1.24 Hypothetical protein LOC100288294 2.92E-02 243328_PM_at LOC100288911 1.48 hypothetical protein LOC100288911 4.12E-02 236657_PM_at LOC134466 2.69 zinc finger protein 300 pseudogene 1.24E-02 244289_PM_at LOC150166 1.73 hypothetical protein LOC150166 2.01E-02 229295_PM_at 1563445_PM_x_ LOC1518 1.41 cathepsin L1 pseudogene 1.24E-02 at LOC203274 1.77 Hypothetical protein LOC203274 1.45E-02 232034_PM_at LOC253039 1.78 hypothetical LOC253039 2.40E-03 231828_PM_at LOC283267 1.69 hypothetical LOC283267 2.32E-03 226793_PM_at LOC284023 1.74 hypothetical protein LOC284023 3.17E-03 238096_PM_at LOC339290 1.39 hypothetical LOC339290 4.44E-02 228160_PM_at LOC400931 1.49 hypothetical LOC400931 1.36E-03 241464_PM_s_at LOC441259 /// PMS2L1 /// PMS2L14 PMS2 postmeiotic segregation increased 2-like /// PMS2L2 /// PMS2L5 1.27 cluster 3.33E-02 215667_PM_x_at LOC642852 1.51 hypothetical LOC642852 1.70E-02 226995_PM_at LOC645323 1.39 hypothetical LOC645323 1.27E-02 230272_PM_at LOC646014 1.59 Hypothetical protein LOC646014 2.65E-02 238715_PM_at LOX 1.43 lysyl oxidase 1.10E-02 215446_PM_s_at LPCAT2 1.53 lysophosphatidylcholine acyltransferase 2 1.07E-02 227889_PM_at LPHN2 1.77 latrophilin 2 5.75E-03 206953_PM_s_at LRRC10B 1.34 leucine rich repeat containing 10B 1.98E-02 236666_PM_s_at LRRC16A 1.61 leucine rich repeat containing 16A 9.54E-03 219573_PM_at LRRC57 1.26 leucine rich repeat containing 57 2.22E-02 229232_PM_at leucine rich repeat containing 8 family, member LRRC8D 1.47 D 1.64E-03 218684_PM_at leucine rich repeat containing 8 family, member LRRC8E 1.51 E 2.69E-02 220174_PM_at LRRFIP2 1.30 Leucine rich repeat (in FLII) interacting protein 2 1.72E-02 218364_PM_at LTB4R 1.54 leukotriene B4 receptor 3.43E-02 236172_PM_at latent transforming growth factor beta binding LTBP3 1.41 protein 3 2.17E-02 219922_PM_s_at LY6G6C 1.52 lymphocyte antigen 6 complex, locus G6C 3.45E-02 207114_PM_at LYPD3 2.01 LY6/PLAUR domain containing 3 8.03E-03 204952_PM_at LYPD5 1.43 LY6/PLAUR domain containing 5 4.52E-02 236039_PM_at LYPD6B 1.54 LY6/PLAUR domain containing 6B 1.51E-02 228360_PM_at LYPLAL1 1.30 lysophospholipase-like 1 2.63E-02 226851_PM_at LYRM2 1.22 LYR motif containing 2 3.07E-02 227712_PM_at

Gene Expression of Airway Epithelium 99 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID LysM, putative peptidoglycan-binding, domain LYSMD4 1.37 containing 4 8.26E-03 228954_PM_at MAB21L1 1.77 mab-21-like 1 (C. elegans) 1.96E-02 206163_PM_at MAEA 1.36 macrophage erythroblast attacher 2.53E-02 207922_PM_s_at v-maf musculoaponeurotic fibrosarcoma MAFB 2.18 oncogene homolog B (avian) 5.78E-03 218559_PM_s_at metastasis associated lung adenocarcinoma MALAT1 1.38 transcript 1 (non-protein coding) 5.69E-03 223578_PM_x_at MAML3 1.46 mastermind-like 3 (Drosophila) 1.36E-02 242794_PM_at MANSC1 1.43 MANSC domain containing 1 3.40E-02 220945_PM_x_at MAP2K5 1.22 Mitogen-activated protein kinase kinase 5 4.22E-02 211370_PM_s_at MAP3K1 1.32 mitogen-activated protein kinase kinase kinase 1 7.81E-03 225927_PM_at MARCH3 2.11 membrane-associated ring finger (C3HC4) 3 1.15E-02 213256_PM_at MARCH8 1.36 membrane-associated ring finger (C3HC4) 8 3.16E-02 221824_PM_s_at MATR3 1.78 Matrin 3 3.42E-03 242260_PM_at MBD4 1.30 methyl-CpG binding domain protein 4 1.17E-02 209579_PM_s_at MBNL3 1.37 muscleblind-like 3 (Drosophila) 3.91E-02 229498_PM_at MCEE 1.47 methylmalonyl CoA epimerase 1.29E-02 226238_PM_at MCOLN3 1.35 Mucolipin 3 3.72E-02 220484_PM_at MDM1 1.30 Mdm1 nuclear protein homolog (mouse) 3.00E-02 213761_PM_at MED12 1.26 mediator complex subunit 12 2.57E-02 211342_PM_x_at MEG3 2.86 maternally expressed 3 (non-protein coding) 1.24E-02 210794_PM_s_at MEGF9 1.79 multiple EGF-like-domains 9 1.93E-03 212830_PM_at MEOX1 2.50 mesenchyme homeobox 1 2.81E-02 205619_PM_s_at MEST 2.60 mesoderm specific transcript homolog (mouse) 3.87E-03 202016_PM_at METTL8 1.39 methyltransferase like 8 1.87E-02 220007_PM_at MFAP2 2.16 microfibrillar-associated protein 2 1.11E-02 203417_PM_at MFAP3L 2.13 microfibrillar-associated protein 3-like 7.83E-03 205442_PM_at MFAP5 4.23 microfibrillar associated protein 5 2.80E-03 213765_PM_at MGC87042 1.70 STEAP family protein MGC87042 3.73E-02 217553_PM_at MGC9913 1.83 hypothetical protein MGC9913 4.93E-03 244740_PM_at MIA 1.92 melanoma inhibitory activity 4.57E-03 206560_PM_s_at MINK1 1.25 misshapen-like kinase 1 (zebrafish) 2.15E-02 214246_PM_x_at myeloid/lymphoid or mixed-lineage leukemia MLLT10 1.36 (trithorax homolog, Drosophila) 3.15E-02 230122_PM_at methylmalonic aciduria (cobalamin deficiency) MMAA 1.24 cblA type 3.43E-02 236347_PM_at MME 3.56 membrane metallo-endopeptidase 9.57E-03 203434_PM_s_at MMP28 2.92 matrix metallopeptidase 28 6.84E-03 239272_PM_at matrix metallopeptidase 3 (stromelysin 1, MMP3 5.73 progelatinase) 1.08E-02 205828_PM_at MOXD1 1.91 monooxygenase, DBH-like 1 7.67E-04 209708_PM_at MPND 1.32 MPN domain containing 1.43E-02 233651_PM_s_at MPP1 1.47 membrane protein, palmitoylated 1, 55kDa 1.20E-02 202974_PM_at MRAS 1.42 muscle RAS oncogene homolog 1.70E-02 206538_PM_at MRC2 2.74 mannose receptor, C type 2 1.22E-03 37408_PM_at MRGPRX3 3.07 MAS-related GPR, member X3 2.04E-02 1553293_PM_at

100 Chapter 3 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID MSRB2 1.28 methionine sulfoxide reductase B2 1.78E-02 218773_PM_s_at MSRB3 1.57 methionine sulfoxide reductase B3 2.97E-02 225782_PM_at MSX2 2.32 msh homeobox 2 2.12E-03 210319_PM_x_at MT1M 2.00 metallothionein 1M 4.19E-02 217546_PM_at MTA3 1.28 metastasis associated 1 family, member 3 4.91E-02 223311_PM_s_at MTCH2 1.25 mitochondrial carrier homolog 2 (C. elegans) 2.19E-02 222403_PM_at MTERFD3 1.49 MTERF domain containing 3 1.77E-02 225346_PM_at MTG1 1.25 mitochondrial GTPase 1 homolog (S. cerevisiae) 3.10E-02 212767_PM_at MTUS1 1.29 Microtubule associated tumor suppressor 1 3.71E-02 239576_PM_at MUCL1 1.63 mucin-like 1 3.59E-02 1553602_PM_at myxovirus (influenza virus) resistance 1, MX1 6.30 interferon-inducible protein p78 (mouse) 4.76E-02 202086_PM_at MYH10 1.34 myosin, heavy chain 10, non-muscle 2.17E-02 213067_PM_at MYLK 12.36 myosin light chain kinase 1.59E-03 224823_PM_at myosin XVIIIA /// TGFB1-induced anti-apoptotic MYO18A /// TIAF1 1.21 factor 1 3.44E-02 202039_PM_at MYO7A 1.22 myosin VIIA 4.36E-02 33197_PM_at NGFI-A binding protein 1 (EGR1 binding protein NAB1 1.68 1) 2.55E-03 209272_PM_at NADSYN1 1.22 NAD synthetase 1 4.02E-02 232946_PM_s_at NAP1L5 2.41 nucleosome assembly protein 1-like 5 1.27E-02 228063_PM_s_at N-ethylmaleimide-sensitive factor attachment NAPA 1.28 protein, alpha 4.10E-02 208751_PM_at NAV1 1.58 neuron navigator 1 7.15E-03 224772_PM_at NCK1 1.49 NCK adaptor protein 1 1.64E-02 244487_PM_at NCOA3 1.20 nuclear receptor coactivator 3 3.83E-02 207700_PM_s_at NCRNA00162 3.79 non-protein coding RNA 162 6.13E-03 1559254_PM_at NADH dehydrogenase (ubiquinone) Fe-S protein NDUFS2 1.20 2, 49kDa (NADH-coenzyme Q reductase) 3.91E-02 201966_PM_at NEFH 1.79 neurofilament, heavy polypeptide 2.30E-03 33767_PM_at NEFL 4.84 neurofilament, light polypeptide 1.24E-02 221805_PM_at NEFM 2.66 neurofilament, medium polypeptide 7.19E-03 205113_PM_at NFIB 1.43 Nuclear factor I/B 3.95E-03 209290_PM_s_at NID1 1.61 nidogen 1 3.98E-02 202007_PM_at NID2 2.76 nidogen 2 (osteonidogen) 1.55E-03 204114_PM_at NIPAL4 1.97 NIPA-like domain containing 4 3.13E-03 230188_PM_at NIPSNAP3A 1.40 nipsnap homolog 3A (C. elegans) 2.63E-02 224436_PM_s_at NKAPL 1.44 NFKB activating protein-like 3.77E-03 229340_PM_at NLRX1 1.55 NLR family member X1 2.19E-03 219680_PM_at 1556029_PM_s_ NMNAT2 1.39 nicotinamide nucleotide adenylyltransferase 2 1.50E-02 at NMRAL1 1.50 NmrA-like family domain containing 1 2.32E-03 223206_PM_s_at NNMT 15.80 Nicotinamide N-methyltransferase 2.56E-05 202237_PM_at nucleotide-binding oligomerization domain NOD2 3.52 containing 2 2.24E-04 220066_PM_at NOTCH2 1.32 Notch homolog 2 (Drosophila) 7.81E-03 202443_PM_x_at NOTCH3 1.45 Notch homolog 3 (Drosophila) 6.68E-03 203238_PM_s_at

Gene Expression of Airway Epithelium 101 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID NPAS2 2.12 neuronal PAS domain protein 2 1.39E-04 213462_PM_at NPNT 1.61 nephronectin 3.73E-03 225911_PM_at NRBF2 1.53 nuclear receptor binding factor 2 1.52E-03 221803_PM_s_at NTRK2 1.22 neurotrophic tyrosine kinase, receptor, type 2 3.80E-02 221795_PM_at nudix (nucleoside diphosphate linked moiety NUDT6 1.71 X)-type motif 6 1.21E-02 220183_PM_s_at ODF3B 1.63 outer dense fiber of sperm tails 3B 6.51E-03 238327_PM_at ODZ2 1.38 odz, odd Oz/ten-m homolog 2 (Drosophila) 1.34E-02 231867_PM_at ODZ3 1.82 Odz, odd Oz/ten-m homolog 3 (Drosophila) 5.28E-03 219523_PM_s_at OGFRL1 1.35 opioid growth factor receptor-like 1 1.24E-02 219582_PM_at OMA1 homolog, zinc metallopeptidase (S. OMA1 1.47 cerevisiae) 8.01E-03 226019_PM_at olfactory receptor, family 2, subfamily L, member OR2L1P 1.23 1 pseudogene 2.65E-02 1567242_PM_at OSBPL10 1.70 oxysterol binding protein-like 10 2.32E-03 219073_PM_s_at OSR2 2.38 odd-skipped related 2 (Drosophila) 6.55E-04 213568_PM_at OXER1 1.22 oxoeicosanoid (OXE) receptor 1 3.56E-02 1553222_PM_at PABPC4L 1.79 poly(A) binding protein, cytoplasmic 4-like 2.31E-02 238865_PM_at PANK1 1.47 pantothenate kinase 1 1.01E-02 226649_PM_at PAQR3 1.32 progestin and adipoQ receptor family member III 3.92E-02 213372_PM_at PARP12 1.89 poly (ADP-ribose) polymerase family, member 12 3.47E-02 218543_PM_s_at PARVB 1.63 parvin, beta 7.09E-03 37966_PM_at PAX3 5.49 paired box 3 1.62E-05 231666_PM_at PAX6 10.29 paired box 6 3.16E-06 235795_PM_at PCBP4 1.38 poly(rC) binding protein 4 5.24E-03 209361_PM_s_at PCDH18 1.63 protocadherin 18 2.60E-03 225975_PM_at PCDHB10 1.39 protocadherin beta 10 2.45E-02 223854_PM_at PCDHB14 1.81 protocadherin beta 14 3.03E-02 231726_PM_at

102 Chapter 3 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID PCDHGA1 /// PCDHGA10 /// PCDHGA11 /// PCDHGA12 /// PCDHGA2 /// PCDHGA3 /// PCDHGA4 /// PCDHGA5 /// PCDHGA6 /// PCDHGA7 /// PCDHGA8 /// PCDHGA9 /// PCDHGB1 /// PCDHGB2 /// PCDHGB3 /// PCDHGB4 /// PCDHGB5 /// PCDHGB6 /// PCDHGB7 /// PCDHGC3 /// PCDHGC4 /// PCDHGC5 1.34 protocadherin gamma subfamily 1.70E-02 211066_PM_x_at PCDHGA11 /// PCDHGA12 /// PCDHGA6 /// PCDHGB3 /// PCDHGB4 /// PCDHGB5 /// PCDHGB6 /// PCDHGB7 /// PCDHGC3 /// PCDHGC4 /// PCDHGC5 1.44 protocadherin gamma subfamily 2.97E-02 205717_PM_x_at PCLO 1.53 piccolo (presynaptic cytomatrix protein) 4.02E-03 213558_PM_at PCNT 1.21 pericentrin 4.32E-02 203660_PM_s_at PCSK5 1.71 Proprotein convertase subtilisin/kexin type 5 2.19E-03 205559_PM_s_at PCSK6 1.62 Proprotein convertase subtilisin/kexin type 6 3.07E-02 210553_PM_x_at PCYOX1L 1.71 prenylcysteine oxidase 1 like 9.52E-04 218953_PM_s_at PCYT1A 1.38 Phosphate cytidylyltransferase 1, choline, alpha 2.98E-02 204210_PM_s_at PDE4DIP 1.75 phosphodiesterase 4D interacting protein 2.76E-02 212390_PM_at PDGFD 1.44 platelet derived growth factor D 4.02E-03 219304_PM_s_at PDK2 1.43 pyruvate dehydrogenase kinase, isozyme 2 1.42E-02 213724_PM_s_at pyruvate dehydrogenase phosphatase PDPR 1.31 regulatory subunit 3.69E-02 224902_PM_at PDZRN3 1.39 PDZ domain containing ring finger 3 9.14E-03 212915_PM_at PEG10 2.26 paternally expressed 10 2.98E-02 212094_PM_at PEPD 1.49 peptidase D 1.46E-02 202108_PM_at PERP 1.33 PERP, TP53 apoptosis effector 3.80E-02 236009_PM_at PEX12 1.25 peroxisomal biogenesis factor 12 4.23E-02 205094_PM_at PEX3 1.55 peroxisomal biogenesis factor 3 6.87E-03 203972_PM_s_at

Gene Expression of Airway Epithelium 103 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID PEX5 1.21 peroxisomal biogenesis factor 5 4.25E-02 203244_PM_at 6-phosphofructo-2-kinase/fructose-2,6- PFKFB2 1.41 biphosphatase 2 7.37E-03 209992_PM_at PGAP2 1.38 post-GPI attachment to proteins 2 2.63E-02 215293_PM_s_at PGLYRP4 1.70 peptidoglycan recognition protein 4 6.98E-03 220944_PM_at PGM2 1.55 phosphoglucomutase 2 5.06E-03 225366_PM_at PGRMC2 1.56 progesterone receptor membrane component 2 5.78E-03 213227_PM_at PHACTR2 1.31 phosphatase and actin regulator 2 2.76E-02 244774_PM_at PH domain and leucine rich repeat protein PHLPP1 1.38 phosphatase 1 1.45E-02 212719_PM_at PI15 1.80 peptidase inhibitor 15 5.00E-03 229947_PM_at PI3 3.74 peptidase inhibitor 3, skin-derived 1.95E-02 203691_PM_at phosphatidylinositol glycan anchor biosynthesis, PIGX 1.46 class X 1.14E-02 1552291_PM_at phosphoinositide-3-kinase, class 2, beta PIK3C2B 1.81 polypeptide 1.45E-02 204484_PM_at phosphoinositide-3-kinase, regulatory subunit PIK3R3 2.05 3 (gamma) 2.60E-02 202743_PM_at PILRB 1.38 paired immunoglobin-like type 2 receptor beta 9.69E-03 220954_PM_s_at PION 1.76 Pigeon homolog (Drosophila) 4.92E-03 213142_PM_x_at plakophilin 1 (ectodermal dysplasia/skin fragility PKP1 1.46 syndrome) 2.17E-02 221854_PM_at PKP3 1.43 plakophilin 3 4.55E-03 209873_PM_s_at PL-5283 1.23 PL-5283 protein 3.13E-02 224752_PM_at phospholipase A2, group IVA (cytosolic, calcium- PLA2G4A 1.91 dependent) 1.01E-02 210145_PM_at phospholipase A2, group VII (platelet-activating PLA2G7 1.67 factor acetylhydrolase, plasma) 5.12E-03 206214_PM_at PLAC2 2.72 placenta-specific 2 (non-protein coding) 6.97E-04 229385_PM_s_at PLAT 6.48 plasminogen activator, tissue 5.38E-03 201860_PM_s_at PLCD1 1.35 phospholipase C, delta 1 2.51E-02 205125_PM_at phospholipase C, gamma 2 PLCG2 1.50 (phosphatidylinositol-specific) 7.81E-03 204613_PM_at phosphatidylinositol-specific phospholipase C, X PLCXD1 1.37 domain containing 1 1.24E-02 218951_PM_s_at PLD1 1.39 phospholipase D1, phosphatidylcholine-specific 3.15E-02 226636_PM_at PLD2 1.33 phospholipase D2 3.81E-02 209643_PM_s_at 1563933_PM_a_ PLD5 5.25 phospholipase D family, member 5 1.24E-03 at pleckstrin homology domain containing, family PLEKHF1 2.06 F (with FYVE domain) member 1 3.73E-04 219566_PM_at PLIN2 2.97 Perilipin 2 3.77E-04 209122_PM_at PLK1S1 1.26 polo-like kinase 1 substrate 1 3.71E-02 228290_PM_at PLSCR4 1.83 phospholipid scramblase 4 2.64E-03 218901_PM_at PLXDC2 3.19 plexin domain containing 2 1.66E-03 227276_PM_at PMP22 1.35 peripheral myelin protein 22 4.98E-02 210139_PM_s_at PNLIPRP3 9.51 pancreatic lipase-related protein 3 1.79E-04 1558846_PM_at PNMAL1 2.49 PNMA-like 1 1.75E-03 218824_PM_at

104 Chapter 3 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID PNPLA3 1.46 patatin-like phospholipase domain containing 3 4.97E-02 220675_PM_s_at PNPO 1.43 pyridoxamine 5'-phosphate oxidase 5.51E-03 222653_PM_at Polymerase (RNA) III (DNA directed) polypeptide POLR3G 1.82 G (32kD) 3.88E-02 206653_PM_at polymerase (RNA) III (DNA directed) polypeptide POLR3H 1.35 H (22.9kD) 2.80E-02 225682_PM_s_at POPDC3 2.42 popeye domain containing 3 6.72E-03 219926_PM_at POU2AF1 1.38 POU class 2 associating factor 1 7.20E-03 205267_PM_at PPAP2A 1.24 phosphatidic acid phosphatase type 2A 1.87E-02 209147_PM_s_at peroxisome proliferator-activated receptor PPARGC1B 1.76 gamma, coactivator 1 beta 2.10E-02 232181_PM_at PTPRF interacting protein, binding protein 2 PPFIBP2 1.68 (liprin beta 2) 7.78E-03 212841_PM_s_at PPIC 1.25 peptidylprolyl isomerase C (cyclophilin C) 2.95E-02 204517_PM_at protein phosphatase, Mg2+/Mn2+ dependent, PPM1D 1.20 1D 4.71E-02 204566_PM_at protein phosphatase, Mg2+/Mn2+ dependent, PPM1F 1.25 1F 4.94E-02 203063_PM_at protein phosphatase 1, regulatory (inhibitor) PPP1R14A 4.41 subunit 14A 6.06E-05 227006_PM_at protein phosphatase 1, regulatory (inhibitor) PPP1R3C 2.86 subunit 3C 6.45E-03 204284_PM_at PRCD 1.42 progressive rod-cone degeneration 5.85E-03 230015_PM_at PREPL 1.53 prolyl endopeptidase-like 1.41E-02 212216_PM_at PRICKLE1 2.67 Prickle homolog 1 (Drosophila) 1.36E-02 226065_PM_at PRICKLE2 2.88 prickle homolog 2 (Drosophila) 1.01E-03 225968_PM_at PRKXP1 1.44 protein kinase, X-linked, pseudogene 1 2.27E-02 235987_PM_at PRMT8 1.98 protein arginine methyltransferase 8 2.51E-03 230839_PM_at PRR16 2.17 proline rich 16 7.89E-04 220014_PM_at PRR9 5.28 proline rich 9 2.80E-02 237732_PM_at Proline rich Gla (G-carboxyglutamic acid) 4 PRRG4 2.05 (transmembrane) 1.83E-03 207291_PM_at PSORS1C2 1.92 psoriasis susceptibility 1 candidate 2 2.05E-02 220635_PM_at proline-serine-threonine phosphatase PSTPIP2 1.49 interacting protein 2 1.47E-02 219938_PM_s_at PTCD2 1.48 pentatricopeptide repeat domain 2 3.17E-02 1555910_PM_at PTER 1.48 phosphotriesterase related 4.37E-02 222798_PM_at PTGES 2.93 prostaglandin E synthase 1.18E-03 210367_PM_s_at PTK7 1.34 PTK7 protein tyrosine kinase 7 1.99E-02 207011_PM_s_at protein tyrosine phosphatase-like (proline PTPLB 1.50 instead of catalytic arginine), member b 3.80E-02 227741_PM_at protein tyrosine phosphatase, non-receptor type PTPN4 1.41 4 (megakaryocyte) 8.43E-03 205171_PM_at protein tyrosine phosphatase, receptor-type, Z PTPRZ1 13.11 polypeptide 1 6.06E-05 204469_PM_at PVRL4 1.46 poliovirus receptor-related 4 1.72E-02 223540_PM_at PXDNL 1.26 peroxidasin homolog (Drosophila)-like 2.44E-02 241942_PM_at PXMP4 1.44 peroxisomal membrane protein 4, 24kDa 4.90E-03 238746_PM_at

Gene Expression of Airway Epithelium 105 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID PYGB 1.33 phosphorylase, glycogen 4.30E-02 201481_PM_s_at QDPR 1.39 Quinoid dihydropteridine reductase 1.38E-02 209123_PM_at RAB38 1.58 RAB38, member RAS oncogene family 1.22E-02 219412_PM_at RAB3IP 1.56 RAB3A interacting protein (rabin3) 1.88E-02 231399_PM_at RAB4A 1.23 RAB4A, member RAS oncogene family 4.35E-02 203581_PM_at RAB4A, member RAS oncogene family /// RAB4A /// SPHAR 1.28 S-phase response (cyclin related) 3.10E-02 206272_PM_at RAB6B 1.35 RAB6B, member RAS oncogene family 4.47E-02 225259_PM_at RAB7B 1.68 RAB7B, member RAS oncogene family 3.00E-02 230266_PM_at RAB9A 1.36 RAB9A, member RAS oncogene family 9.11E-03 221808_PM_at 1552777_PM_a_ RAET1E 1.36 retinoic acid early transcript 1E 2.25E-02 at RAGE 1.54 renal tumor antigen 3.14E-02 205130_PM_at RALGPS2 1.22 Ral GEF with PH domain and SH3 binding motif 2 4.81E-02 232112_PM_at RAPGEF5 1.46 Rap guanine nucleotide exchange factor (GEF) 5 2.79E-02 204681_PM_s_at RAS guanyl releasing protein 2 (calcium and RASGRP2 1.62 DAG-regulated) 4.55E-03 214369_PM_s_at RASL11B 1.50 RAS-like, family 11, member B 2.94E-02 219142_PM_at RAVER2 1.44 ribonucleoprotein, PTB-binding 2 1.65E-02 231851_PM_at RBKS 1.52 ribokinase 5.85E-03 57540_PM_at RBM43 1.89 RNA binding motif protein 43 2.81E-02 228304_PM_at RBMXL1 1.57 RNA binding motif protein, X-linked-like 1 6.15E-03 227748_PM_at RCAN1 1.36 regulator of calcineurin 1 4.91E-02 208370_PM_s_at RDH12 2.28 retinol dehydrogenase 12 (all-trans/9-cis/11-cis) 2.22E-02 242998_PM_at reversion-inducing-cysteine-rich protein with RECK 1.65 kazal motifs 2.44E-02 205407_PM_at REEP4 1.32 receptor accessory protein 4 1.21E-02 218777_PM_at regulatory factor X, 2 (influences HLA class II RFX2 1.68 expression) 1.23E-02 226872_PM_at regulatory factor X-associated ankyrin- RFXANK 1.29 containing protein 2.45E-02 202758_PM_s_at RHCG 2.18 Rh family, C glycoprotein 3.50E-02 219554_PM_at RHOJ 2.06 ras homolog gene family, member J 1.70E-02 235489_PM_at RIN2 1.21 Ras and Rab interactor 2 3.81E-02 209684_PM_at required for meiotic nuclear division 5 homolog RMND5A 1.33 A (S. cerevisiae) 1.56E-02 212482_PM_at RNF135 1.57 ring finger protein 135 4.99E-03 223591_PM_at RNF144A 1.40 ring finger protein 144A 3.75E-02 204040_PM_at RNF217 1.46 ring finger protein 217 4.13E-02 235492_PM_at RNPC3 1.29 RNA-binding region (RNP1, RRM) containing 3 2.73E-02 226975_PM_at RPL22L1 1.27 ribosomal protein L22-like 1 3.80E-02 225541_PM_at RPP40 1.48 ribonuclease P/MRP 40kDa subunit 4.23E-02 213427_PM_at ribosomal protein S6 kinase, 90kDa, polypeptide RPS6KA2 4.14 2 5.68E-04 212912_PM_at RPTN 4.68 repetin 4.61E-03 1553454_PM_at RNA polymerase I transcription factor homolog RRN3P1 1.30 (S. cerevisiae) pseudogene 1 2.52E-02 215211_PM_at

106 Chapter 3 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID RSU1 1.24 Ras suppressor protein 1 3.37E-02 201980_PM_s_at RUNDC3B 1.83 RUN domain containing 3B 1.15E-02 241703_PM_at RUNX3 1.69 runt-related transcription factor 3 1.52E-02 204198_PM_s_at RWDD2B 1.31 RWD domain containing 2B 3.95E-02 218377_PM_s_at S100A12 5.17 S100 calcium binding protein A12 1.29E-04 205863_PM_at S100A7 16.15 S100 calcium binding protein A7 5.52E-03 205916_PM_at S100A8 1.83 S100 calcium binding protein A8 1.42E-02 202917_PM_s_at S100A9 1.75 S100 calcium binding protein A9 1.69E-02 203535_PM_at SAA1 /// SAA2 4.05 serum amyloid A1 /// serum amyloid A2 3.76E-02 208607_PM_s_at SASH1 1.76 SAM and SH3 domain containing 1 6.88E-03 226022_PM_at SBSN 3.12 suprabasin 7.60E-04 235272_PM_at SC65 1.58 synaptonemal complex protein SC65 1.93E-03 204078_PM_at SCARB1 1.84 Scavenger receptor class B, member 1 4.67E-03 201819_PM_at SCRN1 1.26 secernin 1 2.68E-02 201462_PM_at SDK2 1.28 Sidekick homolog 2 (chicken) 4.42E-02 242064_PM_at short chain dehydrogenase/reductase family 9C, SDR9C7 2.04 member 7 5.74E-03 1553077_PM_at SDSL 1.54 serine dehydratase-like 4.79E-03 228274_PM_at SELM 3.77 selenoprotein M 4.38E-03 226051_PM_at sema domain, seven thrombospondin repeats (type 1 and type 1-like), transmembrane domain (TM) and short cytoplasmic domain, SEMA5B 1.45 (semaphorin) 5B 1.52E-02 223610_PM_at serpin peptidase inhibitor, clade A (alpha-1 SERPINA3 1.82 antiproteinase, antitrypsin), member 3 3.15E-02 202376_PM_at serpin peptidase inhibitor, clade B (ovalbumin), SERPINB13 1.90 member 13 3.75E-02 211362_PM_s_at serpin peptidase inhibitor, clade B (ovalbumin), SERPINB3 2.93 member 3 2.68E-02 209719_PM_x_at serpin peptidase inhibitor, clade H (heat shock protein 47), member 1, (collagen binding protein SERPINH1 1.50 1) 1.03E-02 207714_PM_s_at SESN1 1.65 sestrin 1 5.81E-03 218346_PM_s_at SETDB2 1.31 SET domain, bifurcated 2 3.35E-02 235339_PM_at SET domain and mariner transposase fusion SETMAR 1.56 gene 5.24E-03 206554_PM_x_at SEZ6L2 1.44 seizure related 6 homolog (mouse)-like 2 1.47E-02 233337_PM_s_at SF3B3 1.57 splicing factor 3b, subunit 3, 130kDa 1.01E-02 200688_PM_at SFRP1 17.30 Secreted frizzled-related protein 1 3.70E-05 202037_PM_s_at SFRS2B 1.34 splicing factor, arginine/serine-rich 2B 1.42E-02 238929_PM_at SFRS6 1.33 splicing factor, arginine/serine-rich 6 4.71E-02 206108_PM_s_at SH3BP5 1.68 SH3-domain binding protein 5 (BTK-associated) 1.25E-03 201811_PM_x_at SHROOM1 1.39 shroom family member 1 1.40E-02 239435_PM_x_at SIDT2 1.65 SID1 transmembrane family, member 2 2.26E-03 56256_PM_at SIK2 1.24 salt-inducible kinase 2 4.64E-02 213221_PM_s_at SIRPA 1.22 signal-regulatory protein alpha 3.72E-02 202896_PM_s_at SIX3 10.36 SIX homeobox 3 8.41E-06 206634_PM_at SKP2 1.37 S-phase kinase-associated protein 2 (p45) 6.98E-03 203625_PM_x_at

Gene Expression of Airway Epithelium 107 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID solute carrier family 12 (potassium/chloride SLC12A8 1.30 transporters), member 8 2.88E-02 219874_PM_at solute carrier family 13 (sodium-dependent SLC13A5 1.51 citrate transporter), member 5 4.51E-02 228844_PM_at solute carrier family 16, member 1 SLC16A1 1.42 (monocarboxylic acid transporter 1) 8.58E-03 202236_PM_s_at solute carrier family 16, member 6 SLC16A6 1.32 (monocarboxylic acid transporter 7) 3.25E-02 230748_PM_at solute carrier family 16, member 7 SLC16A7 1.72 (monocarboxylic acid transporter 2) 5.47E-03 207057_PM_at solute carrier family 1 (glial high affinity SLC1A3 3.65 glutamate transporter), member 3 1.88E-04 202800_PM_at solute carrier family 24 (sodium/potassium/ SLC24A3 1.49 calcium exchanger), member 3 4.37E-03 57588_PM_at solute carrier family 25 (mitochondrial carrier, SLC25A12 1.32 Aralar), member 12 3.99E-02 203339_PM_at solute carrier family 25 (carnitine/acylcarnitine SLC25A20 1.52 translocase), member 20 1.09E-02 203658_PM_at solute carrier family 26 (sulfate transporter), SLC26A2 1.45 member 2 4.63E-02 205097_PM_at solute carrier family 28 (sodium-coupled SLC28A3 1.28 nucleoside transporter), member 3 2.33E-02 220475_PM_at solute carrier family 2 (facilitated glucose SLC2A1 1.37 transporter), member 1 4.43E-02 201249_PM_at solute carrier family 2 (facilitated glucose SLC2A12 1.89 transporter), member 12 6.68E-03 235050_PM_at members of solute carrier family 2 (facilitated SLC2A14 /// SLC2A3 3.77 glucose transporter) 2.45E-02 222088_PM_s_at solute carrier family 2 (facilitated glucose SLC2A3 3.27 transporter), member 3 2.64E-02 202498_PM_s_at solute carrier family 30 (zinc transporter), SLC30A1 1.32 member 1 2.69E-02 212907_PM_at solute carrier family 35 (CMP-sialic acid SLC35A1 1.44 transporter), member A1 1.70E-02 203306_PM_s_at solute carrier family 35 (UDP-glucuronic acid/ UDP-N-acetylgalactosamine dual transporter), SLC35D1 1.48 member D1 8.73E-03 209713_PM_s_at SLC35F3 4.54 Solute carrier family 35, member F3 2.37E-04 229065_PM_at SLC35F5 1.29 solute carrier family 35, member F5 2.97E-02 225872_PM_at solute carrier family 39 (zinc transporter), SLC39A14 1.47 member 14 1.90E-02 212110_PM_at solute carrier family 39 (zinc transporter), SLC39A2 1.92 member 2 1.54E-02 220413_PM_at solute carrier family 39 (zinc transporter), SLC39A6 1.30 member 6 1.49E-02 202088_PM_at solute carrier family 3 (activators of dibasic and SLC3A2 1.79 neutral amino acid transport), member 2 1.34E-03 200924_PM_s_at SLC46A3 2.61 solute carrier family 46, member 3 1.87E-02 214719_PM_at

108 Chapter 3 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID solute carrier family 48 (heme transporter), SLC48A1 1.48 member 1 7.36E-03 48106_PM_at solute carrier family 5 (sodium-dependent SLC5A6 1.51 vitamin transporter), member 6 7.36E-03 204087_PM_s_at solute carrier family 6 (neutral amino acid SLC6A15 1.54 transporter), member 15 9.13E-03 239352_PM_at solute carrier family 6 (neurotransmitter SLC6A2 2.05 transporter, noradrenalin), member 2 1.50E-04 215715_PM_at solute carrier family 7 (cationic amino acid SLC7A1 1.42 transporter, y+ system), member 1 3.49E-02 212290_PM_at solute carrier family 7 (cationic amino acid SLC7A5 2.70 transporter, y+ system), member 5 7.94E-05 201195_PM_s_at solute carrier family 7 (amino acid transporter, SLC7A8 2.43 L-type), member 8 6.97E-04 216092_PM_s_at solute carrier family 9 (sodium/hydrogen SLC9A9 1.61 exchanger), member 9 1.81E-02 227791_PM_at solute carrier organic anion transporter family, SLCO3A1 1.82 member 3A1 3.73E-03 229776_PM_at SLPI 1.47 secretory leukocyte peptidase inhibitor 4.52E-02 203021_PM_at SMOC1 1.51 SPARC related modular calcium binding 1 1.97E-02 222784_PM_at SMPDL3A 1.36 sphingomyelin phosphodiesterase, acid-like 3A 3.03E-02 213624_PM_at SNX2 1.24 sorting nexin 2 3.36E-02 202113_PM_s_at SNX21 1.36 sorting nexin family member 21 2.90E-02 1553960_PM_at SNX5 1.24 sorting nexin 5 3.57E-02 222417_PM_s_at sortilin-related receptor, L(DLR class) A repeats- SORL1 2.62 containing 2.54E-03 203509_PM_at SOX9 1.71 SRY (sex determining region Y)-box 9 3.37E-04 202935_PM_s_at SP110 2.05 SP110 nuclear body protein 2.58E-02 209762_PM_x_at SP8 8.78 Sp8 transcription factor 7.78E-06 237449_PM_at SPAG16 1.37 sperm associated antigen 16 6.98E-03 219109_PM_at secreted protein, acidic, cysteine-rich SPARC 2.14 (osteonectin) 7.78E-03 212667_PM_at SPATA20 1.41 spermatogenesis associated 20 1.39E-02 218164_PM_at SPINK5 2.83 serine peptidase inhibitor, Kazal type 5 1.36E-02 205185_PM_at 1553973_PM_a_ SPINK6 10.55 serine peptidase inhibitor, Kazal type 6 3.80E-03 at SPNS3 1.21 spinster homolog 3 (Drosophila) 4.19E-02 235900_PM_at SPPL3 1.24 signal peptide peptidase 3 1.93E-02 224640_PM_at SPRR1A 1.27 small proline-rich protein 1A 4.88E-02 213796_PM_at SPRR1B 1.29 small proline-rich protein 1B (cornifin) 3.74E-02 205064_PM_at SPRR2G 17.24 small proline-rich protein 2G 6.19E-04 236119_PM_s_at SPRR4 2.45 small proline-rich protein 4 5.47E-03 1552620_PM_at serine palmitoyltransferase, long chain base SPTLC3 3.32 subunit 3 5.47E-03 227752_PM_at steroid-5-alpha-reductase, alpha polypeptide 1 (3-oxo-5 alpha-steroid delta 4-dehydrogenase SRD5A1 1.78 alpha 1) 2.10E-03 204675_PM_at SRGAP2 1.21 SLIT-ROBO Rho GTPase activating protein 2 4.88E-02 1556202_PM_at

Gene Expression of Airway Epithelium 109 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID SRGAP3 1.67 SLIT-ROBO Rho GTPase activating protein 3 4.16E-03 209794_PM_at SRGN 7.77 serglycin 1.88E-04 201859_PM_at SRPX 1.88 sushi-repeat-containing protein, X-linked 9.52E-04 204955_PM_at SS18 1.32 synovial sarcoma translocation, chromosome 18 1.74E-02 202816_PM_s_at SSPN 1.34 sarcospan (Kras oncogene-associated gene) 2.38E-02 204964_PM_s_at suppression of tumorigenicity 13 (colon ST13 1.25 carcinoma) (Hsp70 interacting protein) 4.93E-02 208666_PM_s_at ST5 1.32 suppression of tumorigenicity 5 2.38E-02 202440_PM_s_at ST6 (alpha-N-acetyl-neuraminyl-2,3-beta- galactosyl-1,3)-N-acetylgalactosaminide alpha- ST6GALNAC2 1.29 2,6-sialyltransferase 2 2.55E-02 204542_PM_at STAC 1.68 SH3 and cysteine rich domain 1.92E-02 205743_PM_at STAG3L1 1.46 stromal antigen 3-like 1 8.00E-03 221191_PM_at stromal antigen 3-like 1 /// stromal antigen STAG3L1 /// STAG3L2 1.48 3-like 2 2.73E-03 223724_PM_s_at StAR-related lipid transfer (START) domain STARD5 1.60 containing 5 2.02E-02 213820_PM_s_at STK19 1.21 serine/threonine kinase 19 4.54E-02 204090_PM_at STYX 1.36 serine/threonine/tyrosine interacting protein 7.71E-03 228853_PM_at SUB1 1.70 SUB1 homolog (S. cerevisiae) 2.59E-03 224587_PM_at synaptonemal complex central element protein 1559960_PM_x_ SYCE1L 1.34 1-like 2.43E-02 at SYNM 2.33 synemin, intermediate filament protein 2.86E-02 212730_PM_at SYT2 1.25 synaptotagmin II 3.48E-02 214903_PM_at SYTL1 1.32 synaptotagmin-like 1 2.17E-02 227134_PM_at TAGAP 2.08 T-cell activation RhoGTPase activating protein 5.46E-03 229723_PM_at TARBP1 1.36 TAR (HIV-1) RNA binding protein 1 1.47E-02 202813_PM_at TBC1D4 1.71 TBC1 domain family, member 4 1.08E-03 203386_PM_at TCEA2 1.30 transcription elongation factor A (SII), 2 3.97E-02 203919_PM_at TCEAL4 1.28 transcription elongation factor A (SII)-like 4 3.72E-02 202371_PM_at TCF25 1.25 transcription factor 25 (basic helix-loop-helix) 2.54E-02 221495_PM_s_at transcription factor 7-like 1 (T-cell specific, TCF7L1 1.83 HMG-box) 1.33E-02 221016_PM_s_at Transcription factor 7-like 2 (T-cell specific, TCF7L2 1.53 HMG-box) 3.77E-03 216035_PM_x_at TCFL5 1.32 Transcription factor-like 5 (basic helix-loop-helix) 3.68E-02 204849_PM_at TCP11L1 1.83 t-complex 11 (mouse)-like 1 2.64E-03 205796_PM_at TEX9 1.60 testis expressed 9 7.15E-03 243198_PM_at transcription factor AP-2 gamma (activating TFAP2C 1.67 enhancer binding protein 2 gamma) 2.79E-03 205286_PM_at TFCP2 1.24 transcription factor CP2 2.54E-02 227637_PM_at TFCP2L1 1.52 transcription factor CP2-like 1 6.58E-03 219735_PM_s_at TFRC 1.27 Transferrin receptor (p90, CD71) 1.78E-02 207332_PM_s_at transforming growth factor, beta receptor TGFBRAP1 1.35 associated protein 1 2.29E-02 205210_PM_at THBS1 1.39 thrombospondin 1 4.67E-02 201107_PM_s_at THBS2 3.79 thrombospondin 2 2.25E-02 203083_PM_at THEM4 1.69 thioesterase superfamily member 4 1.81E-02 229253_PM_at

110 Chapter 3 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID THY1 18.97 Thy-1 cell surface antigen 1.74E-05 208850_PM_s_at TIAM1 1.25 T-cell lymphoma invasion and metastasis 1 3.57E-02 213135_PM_at TIMP2 1.60 TIMP metallopeptidase inhibitor 2 7.87E-03 224560_PM_at TLCD2 1.89 TLC domain containing 2 7.71E-03 241359_PM_at transducin-like enhancer of split 1 (E(sp1) TLE1 1.31 homolog, Drosophila) 3.55E-02 203222_PM_s_at TLR1 1.75 toll-like receptor 1 1.81E-02 210176_PM_at TLR5 1.79 toll-like receptor 5 2.45E-02 210166_PM_at TLR6 1.33 toll-like receptor 6 3.00E-02 239021_PM_at transmembrane emp24 protein transport TMED3 1.28 domain containing 3 2.80E-02 208837_PM_at TMEM117 1.92 transmembrane protein 117 1.78E-02 223594_PM_at TMEM139 3.12 transmembrane protein 139 3.13E-04 227753_PM_at TMEM19 1.38 transmembrane protein 19 2.78E-02 226860_PM_at TMEM47 2.01 transmembrane protein 47 9.44E-03 209656_PM_s_at TMEM54 1.36 transmembrane protein 54 3.88E-02 225536_PM_at TMEM79 1.87 transmembrane protein 79 3.77E-04 223544_PM_at TMEM86A 1.73 transmembrane protein 86A 2.46E-02 242103_PM_at TMPRSS13 1.56 transmembrane protease, serine 13 1.56E-02 223659_PM_at transmembrane and tetratricopeptide repeat TMTC1 6.29 containing 1 2.34E-04 226322_PM_at TNIP1 1.70 TNFAIP3 interacting protein 1 1.38E-02 243423_PM_at TPD52L1 1.78 tumor protein D52-like 1 1.83E-03 210372_PM_s_at TPM1 1.42 Tropomyosin 1 (alpha) 4.30E-02 210987_PM_x_at TPRG1L 1.28 tumor protein p63 regulated 1-like 3.74E-02 224871_PM_at TPST1 2.29 tyrosylprotein sulfotransferase 1 8.01E-03 204140_PM_at translocation associated membrane protein TRAM1L1 1.32 1-like 1 3.84E-02 244334_PM_at TRDMT1 1.24 tRNA aspartic acid methyltransferase 1 3.08E-02 206308_PM_at TRIM14 1.95 tripartite motif-containing 14 6.25E-03 203147_PM_s_at TRIM29 1.53 tripartite motif-containing 29 5.46E-03 202504_PM_at TRIM59 1.58 tripartite motif-containing 59 1.93E-02 235476_PM_at TRIM6 1.74 tripartite motif-containing 6 2.09E-03 223599_PM_at TRPS1 1.58 trichorhinophalangeal syndrome I 2.94E-02 224218_PM_s_at TSPAN9 1.24 tetraspanin 9 4.51E-02 220968_PM_s_at TSTA3 1.22 tissue specific transplantation antigen P35B 2.52E-02 36936_PM_at TTC39A 1.58 tetratricopeptide repeat domain 39A 2.50E-02 210652_PM_s_at TTC39B 1.31 tetratricopeptide repeat domain 39B 1.58E-02 232000_PM_at TTC39C 1.45 tetratricopeptide repeat domain 39C 2.45E-02 238480_PM_at TTLL12 1.24 tubulin tyrosine ligase-like family, member 12 4.34E-02 216251_PM_s_at TTLL7 1.50 tubulin tyrosine ligase-like family, member 7 2.48E-02 219882_PM_at TTYH2 1.55 tweety homolog 2 (Drosophila) 9.78E-03 223741_PM_s_at TUBB2A 1.48 tubulin, beta 2A 3.82E-02 204141_PM_at UBAC1 1.29 UBA domain containing 1 2.77E-02 202151_PM_s_at UNG 1.33 uracil-DNA glycosylase 2.02E-02 202330_PM_s_at URGCP 1.35 upregulator of cell proliferation 3.71E-02 244046_PM_at UROS 1.27 uroporphyrinogen III synthase 3.15E-02 203031_PM_s_at

Gene Expression of Airway Epithelium 111 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID USP11 1.20 ubiquitin specific peptidase 11 4.65E-02 208723_PM_at USP13 1.85 ubiquitin specific peptidase 13 (isopeptidase T-3) 6.57E-04 205356_PM_at USP40 1.55 ubiquitin specific peptidase 40 6.98E-03 225089_PM_at UTP14, U3 small nucleolar ribonucleoprotein, UTP14A 1.34 homolog A (yeast) 4.39E-02 221514_PM_at VANGL1 1.47 vang-like 1 (van gogh, Drosophila) 2.31E-02 229134_PM_at VDR 1.44 Vitamin D (1,25- dihydroxyvitamin D3) receptor 1.23E-02 204254_PM_s_at VGLL3 1.99 vestigial like 3 (Drosophila) 9.49E-04 227399_PM_at VIPR1 1.84 vasoactive intestinal peptide receptor 1 4.39E-03 205019_PM_s_at VNN1 2.60 vanin 1 1.25E-02 205844_PM_at vacuolar protein sorting 36 homolog (S. VPS36 1.32 cerevisiae) 9.23E-03 222478_PM_at WDR41 1.32 WD repeat domain 41 1.82E-02 218055_PM_s_at WDR55 1.26 WD repeat domain 55 4.83E-02 219809_PM_at WDR63 1.41 WD repeat domain 63 3.81E-02 243087_PM_at WDR91 1.42 WD repeat domain 91 3.42E-02 218971_PM_s_at WFDC12 3.84 WAP four-disulfide core domain 12 7.74E-03 1553081_PM_at WFDC5 3.65 WAP four-disulfide core domain 5 5.78E-03 242204_PM_at Wingless-type MMTV integration site family, WNT5A 3.45 member 5A 6.14E-03 213425_PM_at XAF1 4.20 XIAP associated factor 1 4.76E-02 228617_PM_at XG 3.70 Xg blood group 2.32E-03 1554062_PM_at XYLT1 1.67 xylosyltransferase I 2.78E-03 213725_PM_x_at sterile alpha motif and leucine zipper containing ZAK 1.59 kinase AZK 1.09E-03 222757_PM_s_at ZBED1 1.30 zinc finger, BED-type containing 1 2.56E-02 203043_PM_at ZFP42 2.06 zinc finger protein 42 homolog (mouse) 5.31E-03 243161_PM_x_at ZHX1 1.36 zinc fingers and homeoboxes 1 2.48E-02 223213_PM_s_at ZNF10 1.39 zinc finger protein 10 1.26E-02 235366_PM_at ZNF114 1.26 zinc finger protein 114 3.83E-02 1552946_PM_at ZNF12 1.28 zinc finger protein 12 3.19E-02 226015_PM_at ZNF226 1.35 zinc finger protein 226 2.67E-02 233461_PM_x_at ZNF232 1.31 zinc finger protein 232 2.88E-02 219123_PM_at ZNF235 1.30 zinc finger protein 235 2.63E-02 220350_PM_at ZNF253 1.27 zinc finger protein 253 2.21E-02 206900_PM_x_at ZNF30 1.68 zinc finger protein 30 4.39E-03 232014_PM_at ZNF300 1.48 zinc finger protein 300 9.05E-03 228144_PM_at ZNF311 1.46 zinc finger protein 311 6.79E-03 236551_PM_at ZNF32 1.23 zinc finger protein 32 4.23E-02 209538_PM_at ZNF320 1.44 zinc finger protein 320 2.31E-02 229614_PM_at ZNF331 1.44 zinc finger protein 331 6.15E-03 227613_PM_at ZNF362 1.87 zinc finger protein 362 3.87E-03 226820_PM_at ZNF436 1.28 zinc finger protein 436 2.50E-02 226113_PM_at ZNF44 1.48 zinc finger protein 44 2.18E-02 228718_PM_at ZNF471 1.37 zinc finger protein 471 2.75E-02 232117_PM_at ZNF506 1.36 zinc finger protein 506 5.57E-03 238493_PM_at ZNF567 1.33 zinc finger protein 567 1.24E-02 242429_PM_at

112 Chapter 3 Table S3. (continued) Gene alias FC Gene name/description P-value Gene ID ZNF606 1.26 zinc finger protein 606 4.84E-02 219635_PM_at ZNF615 1.35 zinc finger protein 615 2.66E-02 241827_PM_at ZNF618 1.23 zinc finger protein 618 4.43E-02 226592_PM_at ZNF626 1.32 zinc finger protein 626 4.12E-02 1552643_PM_at 1569107_PM_s_ ZNF642 1.27 zinc finger protein 642 3.32E-02 at ZNF667 1.84 zinc finger protein 667 1.18E-02 236635_PM_at ZNF70 1.34 Zinc finger protein 70 3.13E-02 243816_PM_at ZNF706 1.26 zinc finger protein 706 4.97E-02 227132_PM_at ZNF770 1.38 zinc finger protein 770 1.11E-02 225517_PM_at ZNF813 1.45 zinc finger protein 813 2.50E-02 217665_PM_at ZNF827 1.39 Zinc finger protein 827 9.28E-03 228046_PM_at ZNF879 1.46 zinc finger protein 879 2.75E-02 230421_PM_at ZNF883 1.91 zinc finger protein 883 2.31E-03 230876_PM_at Given are abbreviation (Gene alias), fold change (FC), short description (Gene name/description), P-value, and probe ID (Gene ID).

Gene Expression of Airway Epithelium 113 Table S4. Genes that were significantly higher expressed by bronchial epithelial cells from patients with allergic rhinitis Gene alias FC Gene name/description P-value Gene ID ATP-binding cassette, sub-family G (WHITE), ABCG1 4.20 member 1 2.70E-02 204567_PM_s_at ABLIM3 6.36 actin binding LIM protein family, member 3 3.03E-02 205730_PM_s_at AFAP1L1 2.10 actin filament associated protein 1-like 1 3.87E-02 226955_PM_at AHNAK 2.05 AHNAK nucleoprotein 4.82E-02 220016_PM_at ANKRD9 1.77 ankyrin repeat domain 9 2.57E-02 230972_PM_at ARG2 2.12 arginase, type II 4.81E-02 203945_PM_at ArfGAP with SH3 domain, ankyrin repeat and PH ASAP1 1.57 domain 1 4.40E-02 236533_PM_at ATL1 2.00 atlastin GTPase 1 1.60E-02 223340_PM_at ATPase, H+/K+ transporting, nongastric, alpha ATP12A 25.66 polypeptide 3.82E-02 207367_PM_at ATP2C2 6.02 ATPase, Ca++ transporting, type 2C, member 2 4.60E-02 206043_PM_s_at C10orf47 1.76 chromosome 10 open reading frame 47 4.60E-02 230051_PM_at chromosome 11 open reading frame 17 /// NUAK C11orf17 /// NUAK2 1.70 family, SNF1-like kinase, 2 1.65E-02 220987_PM_s_at C14orf139 3.15 chromosome 14 open reading frame 139 4.81E-02 219563_PM_at 1555786_PM_s_ C14orf34 2.05 chromosome 14 open reading frame 34 1.64E-02 at C1orf133 2.15 chromosome 1 open reading frame 133 3.74E-02 230121_PM_at C4orf10 1.74 chromosome 4 open reading frame 10 2.43E-02 214123_PM_s_at CALML4 2.66 calmodulin-like 4 2.92E-02 221879_PM_at calcium/calmodulin-dependent protein kinase CAMK2N1 2.35 II inhibitor 1 3.61E-02 229163_PM_at CAPS 1.72 calcyphosine 3.48E-02 226424_PM_at CDH26 9.65 cadherin 26 1.38E-02 233663_PM_s_at CDKN1C 3.63 cyclin-dependent kinase inhibitor 1C (p57, Kip2) 4.08E-02 219534_PM_x_at carcinoembryonic antigen-related cell adhesion CEACAM1 2.97 molecule 1 (biliary glycoprotein) 3.03E-02 211883_PM_x_at carcinoembryonic antigen-related cell adhesion CEACAM6 5.55 molecule 6 (non-specific cross reacting antigen) 3.95E-02 211657_PM_at CFLAR 2.31 CASP8 and FADD-like apoptosis regulator 1.38E-02 211317_PM_s_at CKLF-like MARVEL transmembrane domain CMTM8 2.13 containing 8 2.08E-02 235099_PM_at CXCL17 10.77 chemokine (C-X-C motif) ligand 17 4.58E-02 226960_PM_at CXXC5 2.92 CXXC finger 5 3.74E-02 222996_PM_s_at dual adaptor of phosphotyrosine and DAPP1 1.57 3-phosphoinositides 3.85E-02 219290_PM_x_at DCDC2 1.62 doublecortin domain containing 2 4.14E-02 222925_PM_at DIDO1 1.50 death inducer-obliterator 1 3.91E-02 213213_PM_at DLG1 1.75 Discs, large homolog 1 (Drosophila) 2.92E-02 217208_PM_s_at DUSP1 3.26 dual specificity phosphatase 1 4.58E-02 201041_PM_s_at ECM1 4.21 extracellular matrix protein 1 2.08E-02 209365_PM_s_at EHF 1.81 ets homologous factor 3.63E-02 232360_PM_at ELF5 7.61 E74-like factor 5 (ets domain transcription factor) 2.61E-02 220625_PM_s_at

114 Chapter 3 Table S4. (continued) Gene alias FC Gene name/description P-value Gene ID ELK3, ETS-domain protein (SRF accessory protein ELK3 1.58 2) 4.48E-02 206127_PM_at EPHA2 1.95 EPH receptor A2 4.48E-02 203499_PM_at EZR 1.72 ezrin 3.90E-02 208621_PM_s_at FA2H 7.44 fatty acid 2-hydroxylase 4.52E-02 219429_PM_at FAM107B 3.30 family with sequence similarity 107, member B 1.16E-02 223059_PM_s_at FAM155B 2.46 family with sequence similarity 155, member B 4.13E-02 206299_PM_at FGD4 1.54 FYVE, RhoGEF and PH domain containing 4 3.71E-02 227948_PM_at FOXA1 3.31 forkhead box A1 3.14E-02 204667_PM_at FOXD1 3.95 forkhead box D1 4.14E-02 206307_PM_s_at FUT2 2.31 fucosyltransferase 2 (secretor status included) 1.60E-02 210608_PM_s_at GALE 1.63 UDP-galactose-4-epimerase 3.72E-02 202528_PM_at GDA 13.96 guanine deaminase 4.12E-02 224209_PM_s_at G protein-coupled receptor kinase interacting GIT2 1.78 ArfGAP 2 3.85E-02 204982_PM_at 1569886_PM_a_ GLB1L3 2.33 galactosidase, beta 1-like 3 3.74E-02 at GLRX 4.14 glutaredoxin (thioltransferase) 2.68E-02 209276_PM_s_at gonadotropin-releasing hormone 1 (luteinizing- GNRH1 1.53 releasing hormone) 4.58E-02 235540_PM_at G protein-coupled receptor, family C, group 5, GPRC5A 3.41 member A 1.83E-02 203108_PM_at 1552628_PM_a_ HERPUD2 1.70 HERPUD family member 2 4.14E-02 at HES4 1.77 hairy and enhancer of split 4 (Drosophila) 3.14E-02 227347_PM_x_at hairy/enhancer-of-split related with YRPW motif HEY1 5.27 1 3.59E-02 44783_PM_s_at IDS 1.66 iduronate 2-sulfatase 4.60E-02 206342_PM_x_at IL1RL1 9.14 interleukin 1 receptor-like 1 4.48E-02 242809_PM_at IL1RN 3.62 interleukin 1 receptor antagonist 4.81E-02 216244_PM_at INADL 2.04 InaD-like (Drosophila) 1.38E-02 239173_PM_at IRS1 1.78 insulin receptor substrate 1 4.42E-02 242979_PM_at ISG20 3.69 interferon stimulated exonuclease gene 20kDa 3.51E-02 204698_PM_at KIAA1199 2.52 KIAA1199 1.60E-02 212942_PM_s_at KRT18 1.91 keratin 18 2.92E-02 201596_PM_x_at LMO7 4.94 LIM domain 7 4.60E-02 242722_PM_at LOC100129406 1.68 hypothetical protein LOC100129406 4.14E-02 240868_PM_at LOC100130938 2.31 hypothetical LOC100130938 3.74E-02 230574_PM_at similar to single Ig IL-1R-related molecule /// LOC100294402 /// single immunoglobulin and toll-interleukin 1 SIGIRR 1.68 receptor (TIR) domain 4.29E-02 52940_PM_at 1555847_PM_a_ LOC284454 1.64 hypothetical protein LOC284454 3.75E-02 at LOC440335 2.25 hypothetical LOC440335 1.60E-02 229599_PM_at LRRFIP1 1.65 leucine rich repeat (in FLII) interacting protein 1 2.92E-02 227513_PM_s_at v-maf musculoaponeurotic fibrosarcoma MAFF 1.91 oncogene homolog F (avian) 4.29E-02 205193_PM_at

Gene Expression of Airway Epithelium 115 Table S4. (continued) Gene alias FC Gene name/description P-value Gene ID v-maf musculoaponeurotic fibrosarcoma MAFK 1.94 oncogene homolog K (avian) 2.20E-02 226206_PM_at MAL 9.05 mal, T-cell differentiation protein 2.92E-02 204777_PM_s_at Metastasis associated lung adenocarcinoma MALAT1 2.95 transcript 1 (non-protein coding) 4.99E-02 228582_PM_x_at MAP3K9 2.49 mitogen-activated protein kinase kinase kinase 9 4.82E-02 213927_PM_at MAPK13 2.09 mitogen-activated protein kinase 13 1.60E-02 210058_PM_at MIB2 2.11 Mindbomb homolog 2 (Drosophila) 3.98E-02 228261_PM_at MITF 1.88 microphthalmia-associated transcription factor 1.60E-02 207233_PM_s_at MLPH 2.27 melanophilin 4.99E-02 218211_PM_s_at MYO5C 3.42 myosin VC 3.10E-02 218966_PM_at NCF2 3.64 neutrophil cytosolic factor 2 4.48E-02 209949_PM_at NLRP1 2.46 NLR family, pyrin domain containing 1 4.87E-02 210113_PM_s_at NT5E 2.15 5'-nucleotidase, ecto (CD73) 1.83E-02 227486_PM_at PADI1 8.60 peptidyl arginine deiminase, type I 3.51E-02 223739_PM_at PCDH7 4.10 protocadherin 7 3.75E-02 228640_PM_at PDCD5 1.69 programmed cell death 5 4.14E-02 227751_PM_at PHACTR3 21.25 phosphatase and actin regulator 3 1.29E-02 227949_PM_at Phosphoinositide-3-kinase, class 2, alpha 1569022_PM_a_ PIK3C2A 1.52 polypeptide 2.92E-02 at PLAG1 2.37 pleiomorphic adenoma gene 1 1.60E-02 205372_PM_at PLCB4 1.89 Phospholipase C, beta 4 3.74E-02 203896_PM_s_at pleckstrin homology domain containing, family PLEKHG5 1.79 G (with RhoGef domain) member 5 3.74E-02 227142_PM_at PTGER4 1.88 prostaglandin E receptor 4 (subtype EP4) 2.69E-02 204897_PM_at 1553114_PM_a_ PTK6 5.20 PTK6 protein tyrosine kinase 6 1.38E-02 at QSOX1 1.99 quiescin Q6 sulfhydryl oxidase 1 4.52E-02 201482_PM_at RASAL2 1.59 RAS protein activator like 2 2.92E-02 227036_PM_at Ras association (RalGDS/AF-6) domain family RASSF6 1.95 member 6 1.83E-02 233463_PM_at RGS12 1.53 regulator of G-protein signaling 12 3.04E-02 209637_PM_s_at 1552502_PM_s_ RHBDL2 2.38 rhomboid, veinlet-like 2 (Drosophila) 1.60E-02 at RIT1 1.48 Ras-like without CAAX 1 3.74E-02 243463_PM_s_at RORA 3.29 RAR-related orphan receptor A 3.44E-02 210479_PM_s_at RUNX2 2.50 runt-related transcription factor 2 2.88E-02 232231_PM_at SDCBP2 3.58 syndecan binding protein (syntenin) 2 2.43E-02 233565_PM_s_at short chain dehydrogenase/reductase family SDR16C5 2.54 16C, member 5 2.20E-02 238017_PM_at SEL1L3 1.42 Sel-1 suppressor of lin-12-like 3 (C. elegans) 4.99E-02 212314_PM_at sema domain, immunoglobulin domain (Ig), SEMA3A 2.36 short basic domain, secreted, (semaphorin) 3A 1.60E-02 206805_PM_at SERTAD4 3.22 SERTA domain containing 4 2.08E-02 230660_PM_at SFRS12IP1 1.85 SFRS12-interacting protein 1 2.43E-02 235390_PM_at SHANK2 3.43 SH3 and multiple ankyrin repeat domains 2 1.60E-02 213308_PM_at SLAMF9 2.73 SLAM family member 9 4.14E-02 1553769_PM_at

116 Chapter 3 Table S4. (continued) Gene alias FC Gene name/description P-value Gene ID SLC44A4 1.90 solute carrier family 44, member 4 4.86E-02 205597_PM_at solute carrier family 4, sodium borate SLC4A11 2.54 transporter, member 11 1.60E-02 223748_PM_at SRPX2 4.05 sushi-repeat-containing protein, X-linked 2 2.58E-02 205499_PM_at SSFA2 2.52 Sperm specific antigen 2 2.68E-02 236207_PM_at SSH3 1.60 slingshot homolog 3 (Drosophila) 4.14E-02 219241_PM_x_at ST3 beta-galactoside alpha-2,3-sialyltransferase ST3GAL1 1.66 1 3.38E-02 225033_PM_at STK17B 2.76 serine/threonine kinase 17b 1.60E-02 205214_PM_at tetratricopeptide repeat, ankyrin repeat and TANC2 1.87 coiled-coil containing 2 3.22E-02 208425_PM_s_at TC2N 1.51 tandem C2 domains, nuclear 4.99E-02 234970_PM_at TEAD3 1.60 TEA domain family member 3 4.14E-02 209454_PM_s_at TMC6 1.68 transmembrane channel-like 6 4.40E-02 204328_PM_at TMEM191A 1.63 transmembrane protein 191A 3.67E-02 223628_PM_at TMEM40 1.66 transmembrane protein 40 2.68E-02 222892_PM_s_at TMEM61 1.79 transmembrane protein 61 2.68E-02 230822_PM_at TMPRSS11D 4.66 transmembrane protease, serine 11D 2.08E-02 207602_PM_at TPCN1 2.10 two pore segment channel 1 4.59E-02 217914_PM_at TPPP 1.87 Tubulin polymerization promoting protein 4.60E-02 230104_PM_s_at TRIB1 2.29 Tribbles homolog 1 (Drosophila) 3.54E-02 202241_PM_at TTBK2 1.62 Tau tubulin kinase 2 4.36E-02 231610_PM_at TTC9 4.96 tetratricopeptide repeat domain 9 4.98E-02 213172_PM_at VLDLR 2.20 very low density lipoprotein receptor 4.14E-02 209822_PM_s_at VWF 1.88 von Willebrand factor 4.38E-02 202112_PM_at WSB1 5.82 WD repeat and SOCS box-containing 1 1.83E-02 201294_PM_s_at ZBED2 2.71 zinc finger, BED-type containing 2 1.60E-02 219836_PM_at ZBTB34 1.46 zinc finger and BTB domain containing 34 4.66E-02 227111_PM_at ZBTB38 1.48 zinc finger and BTB domain containing 38 4.87E-02 236557_PM_at ZDHHC2 1.73 zinc finger, DHHC-type containing 2 3.74E-02 222730_PM_s_at ZFAND6 1.71 Zinc finger, AN1-type domain 6 1.83E-02 222186_PM_at ZNF655 1.99 zinc finger protein 655 3.32E-02 223302_PM_s_at Given are abbreviation (Gene alias), fold change (FC), short description (Gene name/description), P-value, and probe ID (Gene ID).

Gene Expression of Airway Epithelium 117 Table S5. Genes that were significantly higher expressed by nasal epithelial cells from patients with allergic rhinitis Gene alias FC Gene name/description P-value Gene ID AEBP1 4.95 AE binding protein 1 2.00E-02 201792_PM_at ANTXR1 2.13 Anthrax toxin receptor 1 4.52E-02 220092_PM_s_at ANXA6 5.04 annexin A6 1.66E-02 200982_PM_s_at ARHGAP18 2.69 Rho GTPase activating protein 18 2.82E-02 225171_PM_at ARSI 3.04 arylsulfatase family, member I 1.16E-02 230275_PM_at ARV1 1.52 ARV1 homolog (S. cerevisiae) 3.78E-02 223223_PM_at ATPase, Na+/K+ transporting, alpha 1 ATP1A1 1.50 polypeptide 4.13E-02 220948_PM_s_at branched chain amino-acid transaminase 1, BCAT1 3.10 cytosolic 1.60E-02 226517_PM_at branched chain keto acid dehydrogenase E1, BCKDHB 2.05 beta polypeptide 2.08E-02 210653_PM_s_at BCL11A 1.52 B-cell CLL/lymphoma 11A (zinc finger protein) 4.60E-02 219497_PM_s_at BCL11B 1.94 B-cell CLL/lymphoma 11B (zinc finger protein) 3.91E-02 222895_PM_s_at BEX1 5.33 brain expressed, X-linked 1 4.14E-02 218332_PM_at BVES 3.39 blood vessel epicardial substance 2.61E-02 228783_PM_at C16orf5 1.89 chromosome 16 open reading frame 5 3.15E-02 223960_PM_s_at C18orf10 1.59 chromosome 18 open reading frame 10 4.58E-02 212055_PM_at C1orf124 1.57 chromosome 1 open reading frame 124 4.56E-02 223511_PM_at C1orf38 2.07 chromosome 1 open reading frame 38 2.88E-02 207571_PM_x_at C1R 6.27 complement component 1, r subcomponent 2.70E-02 212067_PM_s_at C1S 10.89 complement component 1, s subcomponent 1.50E-02 208747_PM_s_at C21orf96 10.63 chromosome 21 open reading frame 96 3.90E-02 220918_PM_at C3orf34 1.71 chromosome 3 open reading frame 34 4.66E-02 230860_PM_at C4orf49 4.59 chromosome 4 open reading frame 49 4.85E-03 223734_PM_at C5orf62 2.62 chromosome 5 open reading frame 62 1.60E-02 223276_PM_at 1554486_PM_a_ C6orf114 1.64 chromosome 6 open reading frame 114 3.74E-02 at C6orf192 1.71 chromosome 6 open reading frame 192 2.88E-02 226301_PM_at caspase recruitment domain family, member 16 /// caspase 1, apoptosis-related cysteine 1552703_PM_s_ CARD16 /// CASP1 2.13 peptidase (interleukin 1, beta, convertase) 4.56E-02 at caspase 1, apoptosis-related cysteine peptidase CASP1 2.60 (interleukin 1, beta, convertase) 2.55E-02 206011_PM_at CCDC15 1.60 coiled-coil domain containing 15 4.29E-02 220466_PM_at CCDC8 4.66 coiled-coil domain containing 8 4.63E-02 223496_PM_s_at CHPT1 1.89 choline phosphotransferase 1 4.66E-02 230364_PM_at CLDN11 16.71 claudin 11 2.92E-02 228335_PM_at COL12A1 3.38 Collagen, type XII, alpha 1 3.90E-02 225664_PM_at COL4A2 3.56 collagen, type IV, alpha 2 1.83E-02 211966_PM_at COL6A1 11.49 Collagen, type VI, alpha 1 4.34E-02 213428_PM_s_at CPS1 2.75 carbamoyl-phosphate synthase 1, mitochondrial 2.38E-02 217564_PM_s_at crooked neck pre-mRNA splicing factor-like 1 CRNKL1 1.48 (Drosophila) 3.72E-02 219913_PM_s_at CSPG4 3.14 chondroitin sulfate proteoglycan 4 8.30E-03 214297_PM_at CYBRD1 1.83 cytochrome b reductase 1 2.58E-02 222453_PM_at

118 Chapter 3 Table S5. (continued) Gene alias FC Gene name/description P-value Gene ID CYCS 1.91 cytochrome c, somatic 3.08E-02 229415_PM_at cytochrome P450, family 26, subfamily B, CYP26B1 5.20 polypeptide 1 2.41E-02 219825_PM_at DBC1 4.11 deleted in bladder cancer 1 3.22E-02 205818_PM_at DEPDC7 4.99 DEP domain containing 7 2.88E-02 228293_PM_at DMD 1.86 dystrophin 4.14E-02 203881_PM_s_at DNAJB4 1.75 DnaJ (Hsp40) homolog, subfamily B, member 4 4.14E-02 203811_PM_s_at DNMT3B 1.70 DNA (cytosine-5-)-methyltransferase 3 beta 2.18E-02 220668_PM_s_at DST 2.01 dystonin 3.74E-02 212254_PM_s_at DUT 1.83 deoxyuridine triphosphatase 4.58E-02 208955_PM_at DZIP1 2.91 DAZ interacting protein 1 4.25E-02 204557_PM_s_at DZIP3 1.61 DAZ interacting protein 3, zinc finger 4.58E-02 213186_PM_at ECHDC1 1.49 enoyl CoA hydratase domain containing 1 4.59E-02 223087_PM_at EGFL6 6.20 EGF-like-domain, multiple 6 3.22E-02 219454_PM_at ELAV (embryonic lethal, abnormal vision, ELAVL2 13.23 Drosophila)-like 2 (Hu antigen B) 2.80E-02 228260_PM_at FAM110B 1.53 family with sequence similarity 110, member B 4.48E-02 228790_PM_at FAM120C 1.69 family with sequence similarity 120C 4.48E-02 229512_PM_at FAM198B 4.47 family with sequence similarity 198, member B 1.10E-03 223204_PM_at FAP 12.99 fibroblast activation protein, alpha 1.60E-02 209955_PM_s_at FAT2 2.12 FAT tumor suppressor homolog 2 (Drosophila) 2.43E-02 208153_PM_s_at FGFR2 2.28 fibroblast growth factor receptor 2 3.71E-02 203639_PM_s_at FKBP10 1.83 FK506 binding protein 10, 65 kDa 4.14E-02 219249_PM_s_at FLJ13744 2.70 hypothetical FLJ13744 4.46E-02 1553413_PM_at forkhead box C2 (MFH-1, mesenchyme forkhead FOXC2 2.13 1) 1.83E-02 239058_PM_at FRMD4A 2.12 FERM domain containing 4A 3.52E-02 225167_PM_at fragile X mental retardation, autosomal homolog FXR1 1.74 1 4.63E-02 201635_PM_s_at FZD2 1.90 frizzled homolog 2 (Drosophila) 2.43E-02 210220_PM_at UDP-N-acetyl-alpha-D- galactosamine:polypeptide GALNT5 1.62 N-acetylgalactosaminyltransferase 5 (GalNAc-T5) 4.08E-02 236129_PM_at GAS1 11.22 growth arrest-specific 1 2.57E-02 204457_PM_s_at ganglioside-induced differentiation-associated GDAP1 2.30 protein 1 4.14E-02 226269_PM_at golgi-associated, gamma adaptin ear containing, GGA2 1.63 ARF binding protein 2 4.63E-02 208913_PM_at GLI3 1.65 GLI family zinc finger 3 3.79E-02 227376_PM_at GLIPR2 2.84 GLI pathogenesis-related 2 2.08E-02 225604_PM_s_at GLT8D2 3.08 glycosyltransferase 8 domain containing 2 4.24E-03 221447_PM_s_at GPR85 2.71 G protein-coupled receptor 85 4.52E-02 234303_PM_s_at GXYLT2 1.95 glucoside xylosyltransferase 2 4.56E-02 235371_PM_at HFE 1.75 hemochromatosis 2.61E-02 235754_PM_at high mobility group nucleosomal binding HMGN3 2.33 domain 3 3.74E-02 209377_PM_s_at HSPA12A 2.21 heat shock 70kDa protein 12A 1.60E-02 214434_PM_at

Gene Expression of Airway Epithelium 119 Table S5. (continued) Gene alias FC Gene name/description P-value Gene ID HSPA4 1.67 heat shock 70kDa protein 4 4.14E-02 208814_PM_at intraflagellar transport 74 homolog IFT74 1.70 (Chlamydomonas) 4.56E-02 219174_PM_at IL24 2.56 interleukin 24 1.64E-02 206569_PM_at IPO4 1.43 importin 4 4.29E-02 218305_PM_at JAM3 8.70 junctional adhesion molecule 3 4.19E-03 212813_PM_at KANK4 11.55 KN motif and ankyrin repeat domains 4 3.12E-02 229125_PM_at KDELC1 2.28 KDEL (Lys-Asp-Glu-Leu) containing 1 1.60E-02 219479_PM_at KRT75 2.41 keratin 75 3.78E-02 207065_PM_at L1TD1 5.21 LINE-1 type transposase domain containing 1 2.16E-02 219955_PM_at LCP1 7.96 lymphocyte cytosolic protein 1 (L-plastin) 8.46E-03 208885_PM_at leukemia inhibitory factor (cholinergic LIF 2.19 differentiation factor) 4.33E-02 205266_PM_at LOC100127983 1.83 hypothetical protein LOC100127983 4.80E-02 228107_PM_at LOC100132891 4.06 hypothetical protein LOC100132891 3.03E-02 228438_PM_at LOC642852 2.02 hypothetical LOC642852 2.20E-02 226995_PM_at LOC653501 /// ZNF658 zinc finger protein 658 pseudogene /// zinc /// ZNF658B 2.35 finger protein 658 /// zinc finger protein 658B 3.44E-02 231950_PM_at MDM1 2.28 Mdm1 nuclear protein homolog (mouse) 4.82E-02 213761_PM_at MEOX1 2.26 mesenchyme homeobox 1 3.22E-02 205619_PM_s_at MGC21881 1.56 hypothetical locus MGC21881 4.66E-02 228040_PM_at MMP28 2.09 matrix metallopeptidase 28 3.74E-02 219909_PM_at MRC2 2.56 Mannose receptor, C type 2 3.03E-02 37408_PM_at MTUS1 1.80 microtubule associated tumor suppressor 1 2.70E-02 212095_PM_s_at MYLK 11.94 myosin light chain kinase 1.64E-02 202555_PM_s_at NAP1L5 3.29 nucleosome assembly protein 1-like 5 1.85E-02 228062_PM_at N-acyl phosphatidylethanolamine NAPEPLD 1.74 phospholipase D 4.46E-02 226041_PM_at NNMT 14.31 nicotinamide N-methyltransferase 6.85E-03 202237_PM_at N-acetylneuraminate pyruvate lyase NPL 1.58 (dihydrodipicolinate synthase) 2.88E-02 223405_PM_at NQO1 1.59 NAD(P)H dehydrogenase, quinone 1 4.89E-02 201468_PM_s_at OSGEPL1 1.58 O-sialoglycoprotein endopeptidase-like 1 3.74E-02 220631_PM_at PAX3 4.64 paired box 3 1.60E-02 231666_PM_at PCLO 1.83 piccolo (presynaptic cytomatrix protein) 4.56E-02 213558_PM_at PHOSPHO2 1.72 phosphatase, orphan 2 3.08E-02 230434_PM_at PI15 1.95 peptidase inhibitor 15 2.82E-02 229947_PM_at PLAT 12.97 plasminogen activator, tissue 2.08E-02 201860_PM_s_at pleckstrin homology domain containing, family PLEKHF2 1.46 F (with FYVE domain) member 2 4.59E-02 222699_PM_s_at PLSCR4 2.47 phospholipid scramblase 4 2.48E-02 218901_PM_at polymerase (RNA) III (DNA directed) polypeptide POLR3G 2.45 G (32kD) 4.85E-02 206653_PM_at PRICKLE2 3.42 prickle homolog 2 (Drosophila) 1.83E-02 225968_PM_at prostaglandin-endoperoxide synthase 1 (prostaglandin G/H synthase and PTGS1 1.86 cyclooxygenase) 1.60E-02 215813_PM_s_at

120 Chapter 3 Table S5. (continued) Gene alias FC Gene name/description P-value Gene ID PURB 1.64 purine-rich element binding protein B 4.14E-02 226762_PM_at RAD50 1.64 RAD50 homolog (S. cerevisiae) 3.08E-02 209349_PM_at RAD54B 1.79 RAD54 homolog B (S. cerevisiae) 4.66E-02 219494_PM_at RBM43 2.22 RNA binding motif protein 43 4.08E-02 228304_PM_at RUNDC3B 1.56 RUN domain containing 3B 4.52E-02 215321_PM_at SCARB1 2.15 scavenger receptor class B, member 1 2.48E-02 201819_PM_at SELM 2.32 selenoprotein M 3.90E-02 226051_PM_at SEPX1 1.49 selenoprotein X, 1 4.99E-02 217977_PM_at serpin peptidase inhibitor, clade H (heat shock protein 47), member 1, (collagen binding protein SERPINH1 2.46 1) 1.64E-02 207714_PM_s_at SFRP1 5.58 secreted frizzled-related protein 1 2.00E-02 202036_PM_s_at SGCE 2.09 sarcoglycan, epsilon 1.60E-02 204688_PM_at SIX3 6.47 SIX homeobox 3 2.88E-02 206634_PM_at solute carrier family 1 (glial high affinity SLC1A3 3.05 glutamate transporter), member 3 4.59E-02 202800_PM_at solute carrier family 25 (carnitine/acylcarnitine SLC25A20 1.71 translocase), member 20 3.44E-02 203658_PM_at solute carrier family 35 (UDP-glucuronic acid/ UDP-N-acetylgalactosamine dual transporter), SLC35D1 1.71 member D1 2.68E-02 209712_PM_at solute carrier family 39 (zinc transporter), SLC39A14 1.97 member 14 4.30E-02 212110_PM_at solute carrier family 39 (zinc transporter), SLC39A6 1.57 member 6 2.68E-02 202089_PM_s_at solute carrier family 5 (sodium-dependent SLC5A6 1.70 vitamin transporter), member 6 4.59E-02 204087_PM_s_at solute carrier organic anion transporter family, SLCO3A1 1.58 member 3A1 3.22E-02 227367_PM_at small nucleolar RNA host gene 5 (non-protein SNHG5 /// SNORD50A coding) /// small nucleolar RNA, C/D box 50A /// /// SNORD50B 1.95 small nucleolar RNA, C/D box 50B 1.83E-02 244669_PM_at SP110 1.74 SP110 nuclear body protein 3.34E-02 208392_PM_x_at secreted protein, acidic, cysteine-rich SPARC 4.22 (osteonectin) 3.51E-02 200665_PM_s_at steroid-5-alpha-reductase, alpha polypeptide 1 (3-oxo-5 alpha-steroid delta 4-dehydrogenase SRD5A1 1.98 alpha 1) 1.83E-02 210959_PM_s_at SRPRB 1.51 signal recognition particle receptor, B subunit 3.92E-02 222532_PM_at AFFX- signal transducer and activator of transcription HUMISGF3A/ STAT1 1.77 1, 91kDa 3.06E-02 M97935_5_at STEAP3 1.51 STEAP family member 3 3.85E-02 218424_PM_s_at SUB1 1.80 SUB1 homolog (S. cerevisiae) 2.66E-02 221727_PM_at SYNM 3.01 synemin, intermediate filament protein 3.10E-02 212730_PM_at TAF15 RNA polymerase II, TATA box binding TAF15 1.66 protein (TBP)-associated factor, 68kDa 3.15E-02 202840_PM_at transcription factor 7-like 2 (T-cell specific, TCF7L2 1.81 HMG-box) 2.00E-02 212761_PM_at

Gene Expression of Airway Epithelium 121 Table S5. (continued) Gene alias FC Gene name/description P-value Gene ID TCOF1 1.78 Treacher Collins-Franceschetti syndrome 1 2.66E-02 202385_PM_s_at THBS2 6.82 thrombospondin 2 3.08E-02 203083_PM_at THY1 18.03 Thy-1 cell surface antigen 4.63E-04 208850_PM_s_at TLR1 2.42 toll-like receptor 1 3.74E-02 210176_PM_at TMEM5 1.68 transmembrane protein 5 3.74E-02 204807_PM_at TNIP1 2.02 TNFAIP3 interacting protein 1 3.10E-02 243423_PM_at TRIM59 2.59 tripartite motif-containing 59 1.60E-02 235476_PM_at TRIM69 1.93 tripartite motif-containing 69 3.22E-02 1568592_PM_at USP13 2.38 ubiquitin specific peptidase 13 (isopeptidase T-3) 3.10E-02 205356_PM_at VGLL3 1.95 vestigial like 3 (Drosophila) 4.13E-02 220327_PM_at WDR67 2.02 WD repeat domain 67 3.74E-02 214061_PM_at 1555609_PM_a_ ZMAT3 1.60 zinc finger, matrin type 3 3.63E-02 at ZNF124 2.20 zinc finger protein 124 3.22E-02 206928_PM_at ZNF30 1.73 zinc finger protein 30 4.48E-02 232014_PM_at ZNF300 2.03 zinc finger protein 300 4.29E-02 228144_PM_at ZNF362 1.95 zinc finger protein 362 4.14E-02 226820_PM_at ZNF37A 1.59 zinc finger protein 37A 2.88E-02 228711_PM_at ZNF827 1.95 Zinc finger protein 827 4.14E-02 228046_PM_at ZNF879 1.86 Zinc finger protein 879 2.82E-02 230421_PM_at Given are abbreviation (Gene alias), fold change (FC), short description (Gene name/description), P-value, and probe ID (Gene ID).

122 Chapter 3 Table S6. Genes that were significantly higher expressed by bronchial epithelial cells from patients with allergic rhinitis and asthma Gene alias FC Gene name/description P-value Gene ID AKAP12 7.37 A kinase (PRKA) anchor protein 12 4.74E-02 227530_PM_at BST2 3.29 bone marrow stromal cell antigen 2 4.74E-02 201641_PM_at C16orf45 1.73 Chromosome 16 open reading frame 45 4.35E-02 212736_PM_at C1orf133 2.36 chromosome 1 open reading frame 133 1.60E-02 230121_PM_at carbohydrate (N-acetylgalactosamine 4-0) CHST9 2.53 sulfotransferase 9 4.54E-02 223737_PM_x_at DPYSL3 1.86 dihydropyrimidinase-like 3 4.54E-02 201431_PM_s_at FOXA2 1.68 forkhead box A2 3.33E-02 210103_PM_s_at FOXE1 3.63 forkhead box E1 (thyroid transcription factor 2) 4.74E-02 206912_PM_at FUT2 1.87 fucosyltransferase 2 (secretor status included) 3.28E-02 208505_PM_s_at GSN 1.71 Gelsolin (amyloidosis, Finnish type) 2.97E-02 214040_PM_s_at HOXA1 2.61 homeobox A1 2.78E-02 214639_PM_s_at IL33 3.39 interleukin 33 4.54E-02 209821_PM_at JAK2 1.84 Janus kinase 2 4.73E-02 205842_PM_s_at NCF2 2.67 neutrophil cytosolic factor 2 4.54E-02 209949_PM_at NLRP1 2.24 NLR family, pyrin domain containing 1 4.74E-02 211822_PM_s_at PCDH7 2.61 protocadherin 7 1.16E-02 205535_PM_s_at phospholipase C, beta 1 (phosphoinositide- PLCB1 2.24 specific) 1.16E-02 213222_PM_at PSD3 1.59 pleckstrin and Sec7 domain containing 3 4.14E-02 218613_PM_at RIMS2 2.16 regulating synaptic membrane exocytosis 2 4.70E-02 206137_PM_at SERTAD4 2.52 SERTA domain containing 4 4.54E-02 230660_PM_at SKAP2 2.74 Src kinase associated phosphoprotein 2 3.28E-02 204361_PM_s_at SAM pointed domain containing ets SPDEF 5.31 transcription factor 1.16E-02 220192_PM_x_at ST6 (alpha-N-acetyl-neuraminyl-2,3-beta- galactosyl-1,3)-N-acetylgalactosaminide alpha- ST6GALNAC1 9.13 2,6-sialyltransferase 1 1.16E-02 227725_PM_at STOM 1.67 stomatin 4.74E-02 201061_PM_s_at TSPAN1 4.74 tetraspanin 1 4.54E-02 209114_PM_at Given are abbreviation (Gene alias), fold change (FC), short description (Gene name/description), P-value, and probe ID (Gene ID).

Gene Expression of Airway Epithelium 123 Table S7. Genes that were significantly higher expressed by nasal epithelial cells from patients with allergic rhinitis and asthma Gene alias FC Gene name/description P-value Gene ID AHI1 1.71 Abelson helper integration site 1 4.54E-02 221569_PM_at ARMCX1 1.74 armadillo repeat containing, X-linked 1 3.01E-02 218694_PM_at C1orf38 2.05 chromosome 1 open reading frame 38 4.54E-02 210785_PM_s_at CTSC 2.10 cathepsin C 3.30E-02 225646_PM_at ELAV (embryonic lethal, abnormal vision, ELAVL2 3.83 Drosophila)-like 2 (Hu antigen B) 4.74E-02 208427_PM_s_at GLIPR2 1.87 GLI pathogenesis-related 2 4.74E-02 225604_PM_s_at HR 2.41 hairless homolog (mouse) 3.20E-02 241355_PM_at IL13RA2 9.72 interleukin 13 receptor, alpha 2 4.54E-02 206172_PM_at IL1R2 3.15 interleukin 1 receptor, type II 4.14E-02 211372_PM_s_at IRX4 15.72 iroquois homeobox 4 4.54E-02 220225_PM_at phospholipase A2, group IVA (cytosolic, calcium- PLA2G4A 2.11 dependent) 4.74E-02 210145_PM_at PNMAL1 2.28 PNMA-like 1 4.74E-02 218824_PM_at SELM 2.87 selenoprotein M 1.16E-02 226051_PM_at TBC1D4 1.85 TBC1 domain family, member 4 4.54E-02 203387_PM_s_at VGLL3 2.34 vestigial like 3 (Drosophila) 4.54E-02 227399_PM_at Given are abbreviation (Gene alias), fold change (FC), short description (Gene name/description), P-value, and probe ID (Gene ID).

124 Chapter 3 Table S8. Genes that were significantly higher expressed by healthy bronchial epithelial cells sorted by ontology analysis in functional groups Gene alias FC Gene name/description P-value Gene ID receptor activity HLA-DQB1 4.34 major histocompatibility complex, class II, DQ 4.66E-04 209480_PM_at beta 1 HLA-DQB1 /// 2.29 major histocompatibility complex, class II, DQ 1.09E-02 212999_PM_x_at HLA-DQB2 /// family LOC100294318 HLA-DQB1 /// 3.97 major histocompatibility complex, class II, DQ 8.14E-04 212998_PM_x_at LOC100294318 beta 1 HLA-DRB1 /// HLA- 2.40 major histocompatibility complex, class II, DR 4.84E-02 215193_PM_x_at DRB3 /// HLA-DRB4 family /// HLA-DRB5 /// LOC100133661 /// LOC100294036 HLA-DRB1 /// HLA- 2.55 major histocompatibility complex, class II, DR 2.31E-02 209312_PM_x_at DRB4 family metabolism / enzyme binding UGT1A1 /// UGT1A10 3.49 UDP glucuronosyltransferase 1 family 5.47E-03 204532_PM_x_at /// UGT1A4 /// UGT1A6 /// UGT1A8 /// UGT1A9 UGT1A6 3.39 UDP glucuronosyltransferase 1 family, 7.49E-03 206094_PM_x_at polypeptide A6 UGT1A1 /// UGT1A10 3.52 UDP glucuronosyltransferase 1 family 7.87E-03 215125_PM_s_at /// UGT1A3 /// UGT1A4 /// UGT1A5 /// UGT1A6 /// UGT1A7 /// UGT1A8 /// UGT1A9 cell communication ABR 1.52 active BCR-related gene 1.47E-02 212895_PM_s_at ADAM28 2.15 ADAM metallopeptidase domain 28 3.10E-02 205997_PM_at ADAM9 1.72 ADAM metallopeptidase domain 9 (meltrin 2.93E-03 1555326_PM_a_at gamma) ADAMTS1 2.42 ADAM metallopeptidase with thrombospondin 3.87E-03 222486_PM_s_at type 1 motif, 1 ADRB2 1.43 adrenergic, beta-2-, receptor, surface 1.21E-02 206170_PM_at AKAP12 13.17 A kinase (PRKA) anchor protein 12 4.55E-06 227530_PM_at AKT3 1.33 V-akt murine thymoma viral oncogene homolog 2.89E-02 212609_PM_s_at 3 (protein kinase B, gamma) ANGPTL2 1.24 angiopoietin-like 2 2.96E-02 213001_PM_at AP2B1 1.28 adaptor-related protein complex 2, beta 1 1.76E-02 200615_PM_s_at subunit APLN 1.27 Apelin 2.11E-02 244166_PM_at APLP2 1.24 amyloid beta (A4) precursor-like protein 2 2.45E-02 208703_PM_s_at AR 1.22 androgen receptor 3.95E-02 226192_PM_at ARAP2 1.85 ArfGAP with RhoGAP domain, ankyrin repeat 1.63E-02 214102_PM_at and PH domain 2 ARHGAP29 1.31 Rho GTPase activating protein 29 2.09E-02 203910_PM_at

Gene Expression of Airway Epithelium 125 Table S8. (continued) Gene alias FC Gene name/description P-value Gene ID ARHGAP5 1.76 Rho GTPase activating protein 5 4.88E-02 235635_PM_at ARHGEF12 1.41 Rho guanine nucleotide exchange factor (GEF) 5.48E-03 201335_PM_s_at 12 ARHGEF18 1.32 Rho/Rac guanine nucleotide exchange factor 4.50E-02 213039_PM_at (GEF) 18 ASAP1 1.21 ArfGAP with SH3 domain, ankyrin repeat and PH 4.65E-02 224790_PM_at domain 1 ASB1 1.37 ankyrin repeat and SOCS box-containing 1 1.59E-02 212819_PM_at AXL 1.32 AXL receptor tyrosine kinase 6.91E-03 202686_PM_s_at BAIAP2 1.42 BAI1-associated protein 2 2.86E-02 205294_PM_at BCAR3 1.64 breast cancer anti-estrogen resistance 3 2.55E-03 204032_PM_at BCL10 1.46 B-cell CLL/lymphoma 10 2.48E-03 205263_PM_at BCL2L1 2.00 BCL2-like 1 1.04E-03 215037_PM_s_at BCR 1.32 breakpoint cluster region 4.75E-02 226602_PM_s_at BMPR1B 2.40 bone morphogenetic protein receptor, type IB 1.72E-03 229975_PM_at CAPS 1.46 calcyphosine 5.54E-03 231729_PM_s_at CARD11 2.08 caspase recruitment domain family, member 11 8.14E-04 223514_PM_at CASP3 1.40 caspase 3, apoptosis-related cysteine peptidase 7.36E-03 202763_PM_at CAV2 1.24 caveolin 2 2.82E-02 203323_PM_at CD274 1.62 CD274 molecule 3.69E-02 227458_PM_at CEACAM6 3.76 carcinoembryonic antigen-related cell adhesion 2.08E-02 211657_PM_at molecule 6 (non-specific cross reacting antigen) CERK 1.45 ceramide kinase 4.73E-02 218421_PM_at CHRNB1 1.64 cholinergic receptor, nicotinic, beta 1 (muscle) 5.23E-03 206703_PM_at CLDN4 1.96 claudin 4 3.91E-03 201428_PM_at CORO1C 1.26 coronin, actin binding protein, 1C 2.04E-02 222409_PM_at CORO2A 1.35 coronin, actin binding protein, 2A 2.07E-02 227177_PM_at CSNK1D 1.27 casein kinase 1, delta 1.76E-02 207945_PM_s_at CSRNP1 1.82 cysteine-serine-rich nuclear protein 1 1.60E-02 225557_PM_at CXCL1 2.73 chemokine (C-X-C motif) ligand 1 (melanoma 3.77E-03 204470_PM_at growth stimulating activity, alpha) CXCL6 1.45 chemokine (C-X-C motif) ligand 6 (granulocyte 2.17E-02 206336_PM_at chemotactic protein 2) CXCR7 2.10 Chemokine (C-X-C motif) receptor 7 2.01E-02 232746_PM_at CXXC5 1.81 CXXC finger 5 1.63E-02 224516_PM_s_at DAPP1 1.35 dual adaptor of phosphotyrosine and 2.17E-02 222858_PM_s_at 3-phosphoinositides DDAH1 3.13 dimethylarginine dimethylaminohydrolase 1 3.14E-05 209094_PM_at DISC1 /// TSNAX-DISC1 1.26 disrupted in schizophrenia 1 /// TSNAX-DISC1 3.25E-02 206090_PM_s_at gene DKK2 1.65 dickkopf homolog 2 (Xenopus laevis) 1.36E-02 219908_PM_at DPYSL3 2.01 dihydropyrimidinase-like 3 6.15E-03 201431_PM_s_at DST 1.57 dystonin 9.45E-03 216918_PM_s_at DTNA 1.53 dystrobrevin, alpha 3.75E-02 205741_PM_s_at ECT2 1.60 epithelial cell transforming sequence 2 4.21E-03 234992_PM_x_at oncogene EDN1 3.62 endothelin 1 6.06E-05 1564630_PM_at

126 Chapter 3 Table S8. (continued) Gene alias FC Gene name/description P-value Gene ID EML4 1.36 echinoderm microtubule associated protein 2.24E-02 228674_PM_s_at like 4 EMR2 1.75 egf-like module containing, mucin-like, hormone 1.24E-02 207610_PM_s_at receptor-like 2 EPHA2 1.74 EPH receptor A2 2.33E-03 203499_PM_at EPHB2 2.82 EPH receptor B2 3.28E-03 209589_PM_s_at EPS8 2.30 epidermal growth factor receptor pathway 1.95E-02 202609_PM_at substrate 8 ERN1 2.19 endoplasmic reticulum to nucleus signaling 1 3.41E-03 235745_PM_at FAS 1.92 Fas (TNF receptor superfamily, member 6) 4.65E-04 204781_PM_s_at FGF13 1.45 fibroblast growth factor 13 2.30E-03 205110_PM_s_at FGF18 1.33 fibroblast growth factor 18 1.67E-02 206986_PM_at FGF5 3.56 fibroblast growth factor 5 4.67E-03 208378_PM_x_at FGFR3 2.38 fibroblast growth factor receptor 3 9.08E-03 204379_PM_s_at FIP1L1 1.35 FIP1 like 1 (S. cerevisiae) 6.15E-03 1554424_PM_at FKBP1B /// MFSD2B 1.38 FK506 binding protein 1B /// major facilitator 2.45E-02 209931_PM_s_at superfamily domain containing 2B FOXA1 4.68 forkhead box A1 4.55E-06 204667_PM_at FOXA2 2.37 forkhead box A2 8.19E-03 40284_PM_at FOXL1 1.98 forkhead box L1 2.28E-02 243409_PM_at FUT8 1.36 fucosyltransferase 8 (alpha (1,6) 2.77E-02 1554930_PM_a_at fucosyltransferase) FZD10 2.17 frizzled homolog 10 (Drosophila) 1.37E-02 219764_PM_at FZD5 1.39 frizzled homolog 5 (Drosophila) 2.09E-02 221245_PM_s_at G3BP2 1.26 GTPase activating protein (SH3 domain) binding 3.80E-02 208840_PM_s_at protein 2 GABRB3 1.86 gamma-aminobutyric acid (GABA) A receptor, 1.11E-02 229724_PM_at beta 3 GAS6 1.66 growth arrest-specific 6 3.01E-03 202177_PM_at GDI1 1.23 GDP dissociation inhibitor 1 3.15E-02 201864_PM_at GNA15 1.45 guanine nucleotide binding protein (G protein), 5.78E-03 205349_PM_at alpha 15 (Gq class) GNAS 1.52 GNAS complex locus 2.67E-02 229274_PM_at GNG11 1.46 guanine nucleotide binding protein (G protein), 2.66E-02 204115_PM_at gamma 11 GPR110 2.41 G protein-coupled receptor 110 1.23E-02 236489_PM_at GPR126 1.75 G protein-coupled receptor 126 6.33E-03 213094_PM_at GPR153 1.26 G protein-coupled receptor 153 3.17E-02 64942_PM_at GPR37 3.43 G protein-coupled receptor 37 (endothelin 1.69E-03 209631_PM_s_at receptor type B-like) GPR39 2.44 G protein-coupled receptor 39 9.87E-05 229105_PM_at GPRC5A 3.85 G protein-coupled receptor, family C, group 5, 2.24E-04 203108_PM_at member A GRB10 2.17 growth factor receptor-bound protein 10 2.93E-03 209409_PM_at GRK5 1.54 G protein-coupled receptor kinase 5 1.67E-02 204396_PM_s_at GULP1 2.05 GULP, engulfment adaptor PTB domain 3.80E-04 204237_PM_at containing 1 HCLS1 2.02 hematopoietic cell-specific Lyn substrate 1 3.05E-02 202957_PM_at

Gene Expression of Airway Epithelium 127 Table S8. (continued) Gene alias FC Gene name/description P-value Gene ID HEY1 2.55 hairy/enhancer-of-split related with YRPW motif 5.31E-04 218839_PM_at 1 HIST2H4A /// HIST2H4B 1.50 histone cluster 2, H4a /// histone cluster 2, H4b 9.90E-03 207046_PM_at HLA-G 1.46 major histocompatibility complex, class I, G 1.52E-02 211530_PM_x_at HMHA1 1.53 histocompatibility (minor) HA-1 6.17E-03 212873_PM_at IFNAR1 1.28 interferon (alpha, beta and omega) receptor 1 4.32E-02 225661_PM_at IGF2 /// INS-IGF2 1.94 insulin-like growth factor 2 (somatomedin A) /// 2.56E-02 202409_PM_at INS-IGF2 readthrough transcript IGFBP4 1.92 insulin-like growth factor binding protein 4 1.01E-03 201508_PM_at IL11 2.07 interleukin 11 1.30E-02 206924_PM_at IL1RL1 6.40 interleukin 1 receptor-like 1 4.66E-04 242809_PM_at IL1RN 1.52 interleukin 1 receptor antagonist 2.59E-03 212659_PM_s_at IL23A 2.69 interleukin 23, alpha subunit p19 9.36E-03 220054_PM_at IL6ST 1.40 interleukin 6 signal transducer (gp130, 4.88E-02 212196_PM_at oncostatin M receptor) IL8 5.88 interleukin 8 7.71E-03 211506_PM_s_at ILK 1.33 integrin-linked kinase 2.79E-02 201234_PM_at INADL 1.25 InaD-like (Drosophila) 4.57E-02 239173_PM_at INPP4B 1.49 inositol polyphosphate-4-phosphatase, type II 2.55E-02 205376_PM_at INSIG1 1.40 insulin induced gene 1 3.68E-02 201626_PM_at INSR 1.57 insulin receptor 8.26E-03 226216_PM_at IRAK3 1.34 interleukin-1 receptor-associated kinase 3 3.03E-02 220034_PM_at IRS1 1.70 insulin receptor substrate 1 6.98E-03 204686_PM_at ITGA2 2.02 integrin, alpha 2 (CD49B, alpha 2 subunit of 3.43E-03 205032_PM_at VLA-2 receptor) ITGB1 1.28 integrin, beta 1 (fibronectin receptor, beta 2.46E-02 1553530_PM_a_at polypeptide, antigen CD29 includes MDF2, MSK12) JAK2 1.53 Janus kinase 2 4.09E-03 205842_PM_s_at JUN 1.39 jun oncogene 2.07E-02 201465_PM_s_at KCNMA1 3.31 potassium large conductance calcium-activated 1.52E-03 221584_PM_s_at channel, subfamily M, alpha member 1 KCNQ5 1.42 potassium voltage-gated channel, KQT-like 4.83E-02 244623_PM_at subfamily, member 5 KISS1R 1.42 KISS1 receptor 4.85E-02 242517_PM_at KREMEN1 1.36 kringle containing transmembrane protein 1 3.08E-02 227250_PM_at LDLR 1.41 low density lipoprotein receptor 6.16E-03 217173_PM_s_at LIFR 1.45 leukemia inhibitory factor receptor alpha 1.72E-02 225575_PM_at LOC100288387 1.37 similar to c-jun 3.36E-02 213281_PM_at LOC100294402 /// 2.22 similar to single Ig IL-1R-related molecule /// 4.92E-04 52940_PM_at SIGIRR single immunoglobulin and toll-interleukin 1 receptor (TIR) domain LPAR1 2.09 lysophosphatidic acid receptor 1 2.98E-03 204037_PM_at LTBP1 1.62 latent transforming growth factor beta binding 2.45E-02 202728_PM_s_at protein 1 MALT1 1.24 mucosa associated lymphoid tissue lymphoma 2.38E-02 210018_PM_x_at translocation gene 1 MAP2K1 1.30 mitogen-activated protein kinase kinase 1 2.21E-02 202670_PM_at

128 Chapter 3 Table S8. (continued) Gene alias FC Gene name/description P-value Gene ID MAP3K9 1.61 mitogen-activated protein kinase kinase kinase 9 1.29E-02 213927_PM_at MAPK13 1.55 mitogen-activated protein kinase 13 2.12E-03 210058_PM_at MAPK6 1.26 mitogen-activated protein kinase 6 2.63E-02 207121_PM_s_at MET 1.41 met proto-oncogene (hepatocyte growth factor 4.98E-03 203510_PM_at receptor) MIB1 1.24 mindbomb homolog 1 (Drosophila) 4.58E-02 224722_PM_at MIB2 1.71 mindbomb homolog 2 (Drosophila) 1.24E-02 228261_PM_at MITF 2.07 microphthalmia-associated transcription factor 6.47E-03 226066_PM_at MST1R 2.21 macrophage stimulating 1 receptor (c-met- 2.26E-03 205455_PM_at related tyrosine kinase) MSX1 1.34 msh homeobox 1 1.78E-02 205932_PM_s_at MT1H /// MT1P2 1.35 metallothionein 1H /// metallothionein 1 1.23E-02 206461_PM_x_at pseudogene 2 MYO10 1.76 myosin X 2.17E-02 1554026_PM_a_at NAMPT 1.26 nicotinamide phosphoribosyltransferase 2.68E-02 1555167_PM_s_at NDST1 1.29 N-deacetylase/N-sulfotransferase (heparan 2.99E-02 1554010_PM_at glucosaminyl) 1 NET1 1.53 neuroepithelial cell transforming 1 6.58E-03 201829_PM_at NFATC1 1.41 nuclear factor of activated T-cells, cytoplasmic, 1.85E-02 211105_PM_s_at calcineurin-dependent 1 NKX2-1 3.76 NK2 homeobox 1 4.19E-04 231315_PM_at NKX3-1 1.28 NK3 homeobox 1 4.60E-02 209706_PM_at NPC1 1.28 Niemann-Pick disease, type C1 2.97E-02 202679_PM_at NR3C2 2.71 nuclear receptor subfamily 3, group C, member 2 1.97E-02 205259_PM_at NRAS 1.40 neuroblastoma RAS viral (v-ras) oncogene 5.57E-03 202647_PM_s_at homolog NRP2 1.34 neuropilin 2 2.51E-02 210842_PM_at NRXN3 1.91 neurexin 3 4.53E-02 229649_PM_at OSMR 1.39 oncostatin M receptor 3.74E-02 1554008_PM_at OXTR 2.61 oxytocin receptor 2.35E-03 206825_PM_at P2RY2 1.72 purinergic receptor P2Y, G-protein coupled, 2 7.95E-03 206277_PM_at PANX2 1.31 pannexin 2 2.44E-02 239067_PM_s_at PDE4D 1.34 phosphodiesterase 4D, cAMP-specific 2.17E-02 204491_PM_at (phosphodiesterase E3 dunce homolog, Drosophila) PDE9A 2.71 phosphodiesterase 9A 2.31E-03 205593_PM_s_at PDK3 1.44 pyruvate dehydrogenase kinase, isozyme 3 6.49E-03 228959_PM_at PDLIM5 1.40 PDZ and LIM domain 5 1.98E-02 211681_PM_s_at PELO 1.55 Pelota homolog (Drosophila) 3.57E-02 226731_PM_at PENK 1.21 proenkephalin 3.52E-02 213791_PM_at PLAUR 1.60 plasminogen activator, urokinase receptor 1.85E-02 214866_PM_at PLCB1 2.31 phospholipase C, beta 1 (phosphoinositide- 5.78E-03 213222_PM_at specific) PLCXD2 1.93 phosphatidylinositol-specific phospholipase C, X 1.80E-02 235230_PM_at domain containing 2 PLEK2 1.43 pleckstrin 2 2.82E-02 218644_PM_at PLK3 1.36 polo-like kinase 3 (Drosophila) 1.99E-02 204958_PM_at PLLP 3.41 plasma membrane proteolipid (plasmolipin) 1.83E-04 204519_PM_s_at

Gene Expression of Airway Epithelium 129 Table S8. (continued) Gene alias FC Gene name/description P-value Gene ID PLXNA2 1.69 plexin A2 6.57E-04 213030_PM_s_at PMEPA1 2.24 prostate transmembrane protein, androgen 1.68E-03 222449_PM_at induced 1 PORCN 1.57 porcupine homolog (Drosophila) 2.57E-02 219483_PM_s_at PPARD 1.65 peroxisome proliferator-activated receptor delta 1.11E-03 210636_PM_at PPARG 1.44 peroxisome proliferator-activated receptor 1.88E-02 208510_PM_s_at gamma PPP1R15A 1.62 protein phosphatase 1, regulatory (inhibitor) 1.61E-03 37028_PM_at subunit 15A PPP1R1C 1.76 protein phosphatase 1, regulatory (inhibitor) 2.73E-03 228646_PM_at subunit 1C PPP2R2A 1.28 protein phosphatase 2, regulatory subunit B, 3.25E-02 228013_PM_at alpha PPP3CB 1.27 protein phosphatase 3, catalytic subunit, beta 3.84E-02 202432_PM_at isozyme PRKAA1 1.22 protein kinase, AMP-activated, alpha 1 catalytic 4.81E-02 225985_PM_at subunit PRKAA2 2.90 protein kinase, AMP-activated, alpha 2 catalytic 1.93E-03 227892_PM_at subunit PRKCD 1.25 protein kinase C, delta 2.50E-02 202545_PM_at PRMT2 1.39 protein arginine methyltransferase 2 4.72E-02 228722_PM_at PTAFR 3.11 platelet-activating factor receptor 4.90E-03 227184_PM_at PTGER4 2.49 prostaglandin E receptor 4 (subtype EP4) 3.77E-04 204897_PM_at PTK2 1.31 PTK2 protein tyrosine kinase 2 3.88E-02 241453_PM_at PTN 1.76 pleiotrophin 1.32E-03 209466_PM_x_at PTPLA 1.54 protein tyrosine phosphatase-like (proline 3.75E-03 219654_PM_at instead of catalytic arginine), member A PTPRD 1.32 protein tyrosine phosphatase, receptor type, D 2.09E-02 214043_PM_at RAB3B 1.82 RAB3B, member RAS oncogene family 4.57E-03 205924_PM_at RAF1 1.25 V-raf-1 murine leukemia viral oncogene 3.88E-02 1557675_PM_at homolog 1 RAPH1 1.57 Ras association (RalGDS/AF-6) and pleckstrin 3.29E-02 231075_PM_x_at homology domains 1 RARA 1.42 retinoic acid receptor, alpha 5.47E-03 203749_PM_s_at RASA2 1.55 RAS p21 protein activator 2 1.78E-02 206636_PM_at RASA3 1.54 RAS p21 protein activator 3 6.47E-03 225562_PM_at RASAL2 1.46 RAS protein activator like 2 2.55E-03 227036_PM_at RASD1 1.99 RAS, dexamethasone-induced 1 3.25E-02 223467_PM_at RASGEF1A 6.75 RasGEF domain family, member 1A 2.07E-02 230563_PM_at RASSF5 1.32 Ras association (RalGDS/AF-6) domain family 1.84E-02 1554834_PM_a_at member 5 RBPJ 1.36 recombination signal binding protein for 5.46E-03 211974_PM_x_at immunoglobulin kappa J region RGMB 3.01 RGM domain family, member B 3.45E-04 227339_PM_at RGS12 1.44 regulator of G-protein signaling 12 1.00E-02 209637_PM_s_at RGS2 1.46 regulator of G-protein signaling 2 4.05E-02 202388_PM_at RHBDL2 1.50 rhomboid, veinlet-like 2 (Drosophila) 2.45E-02 1554897_PM_s_at RHOC 1.24 ras homolog gene family, member C 4.76E-02 200885_PM_at

130 Chapter 3 Table S8. (continued) Gene alias FC Gene name/description P-value Gene ID RHOF 2.49 ras homolog gene family, member F (in 3.33E-02 219045_PM_at filopodia) RHPN2 1.57 rhophilin, Rho GTPase binding protein 2 8.26E-03 227196_PM_at RICH2 1.89 Rho-type GTPase-activating protein RICH2 1.80E-03 205414_PM_s_at RIT1 1.28 Ras-like without CAAX 1 1.62E-02 236224_PM_at RND1 1.71 Rho family GTPase 1 3.29E-02 210056_PM_at RNF138 1.35 ring finger protein 138 2.50E-02 239143_PM_x_at ROBO2 1.76 roundabout, axon guidance receptor, homolog 3.91E-03 226766_PM_at 2 (Drosophila) RRAS 1.31 related RAS viral (r-ras) oncogene homolog 2.80E-02 212647_PM_at SDCBP2 1.57 syndecan binding protein (syntenin) 2 2.97E-02 233565_PM_s_at SH2D3A 1.55 SH2 domain containing 3A 4.77E-03 219513_PM_s_at SH3D20 1.97 SH3 domain containing 20 2.31E-03 1554594_PM_at SH3KBP1 1.29 SH3-domain kinase binding protein 1 1.21E-02 235692_PM_at SHANK2 2.03 SH3 and multiple ankyrin repeat domains 2 7.89E-04 213307_PM_at SIPA1 1.24 signal-induced proliferation-associated 1 3.93E-02 204164_PM_at SIX1 1.63 SIX homeobox 1 1.99E-02 205817_PM_at SKAP2 2.96 src kinase associated phosphoprotein 2 4.26E-04 204362_PM_at SLC1A1 2.10 solute carrier family 1 (neuronal/epithelial high 1.71E-02 213664_PM_at affinity glutamate transporter, system Xag), member 1 SLC1A4 2.39 solute carrier family 1 (glutamate/neutral amino 7.82E-04 212810_PM_s_at acid transporter), member 4 SLC2A8 1.22 solute carrier family 2 (facilitated glucose 3.71E-02 218985_PM_at transporter), member 8 SLC44A2 1.38 solute carrier family 44, member 2 2.72E-02 224609_PM_at SLC9A3R1 1.49 solute carrier family 9 (sodium/hydrogen 1.12E-02 201349_PM_at exchanger), member 3 regulator 1 SMAD3 1.53 SMAD family member 3 1.09E-03 218284_PM_at SMAD4 1.29 SMAD family member 4 4.41E-02 235725_PM_at SMURF1 1.26 SMAD specific E3 ubiquitin protein ligase 1 1.49E-02 212666_PM_at SMURF2 1.70 SMAD specific E3 ubiquitin protein ligase 2 2.93E-03 227489_PM_at SNCA 1.60 synuclein, alpha (non A4 component of amyloid 1.78E-02 236081_PM_at precursor) SOX4 1.23 SRY (sex determining region Y)-box 4 3.36E-02 213665_PM_at SPOCK1 3.21 sparc/osteonectin, cwcv and kazal-like domains 2.39E-03 202363_PM_at proteoglycan (testican) 1 SPTBN1 1.52 spectrin, beta, non-erythrocytic 1 2.26E-03 200672_PM_x_at STAM 1.29 signal transducing adaptor molecule (SH3 1.21E-02 203544_PM_s_at domain and ITAM motif) 1 STK17A 1.51 serine/threonine kinase 17a 2.10E-02 202694_PM_at STK17B 2.68 serine/threonine kinase 17b 2.55E-03 205214_PM_at STK39 1.32 serine threonine kinase 39 (STE20/SPS1 4.02E-02 202786_PM_at homolog, yeast) STX1A 1.85 syntaxin 1A (brain) 1.18E-03 204729_PM_s_at STX2 1.40 syntaxin 2 4.41E-02 213434_PM_at SYK 2.07 spleen tyrosine kinase 1.52E-03 226068_PM_at TGFA 1.35 transforming growth factor, alpha 1.93E-02 205015_PM_s_at

Gene Expression of Airway Epithelium 131 Table S8. (continued) Gene alias FC Gene name/description P-value Gene ID TGFBR1 1.23 transforming growth factor, beta receptor 1 4.16E-02 224793_PM_s_at TGFBR2 1.57 transforming growth factor, beta receptor II 6.38E-03 208944_PM_at TGFBR3 3.29 transforming growth factor, beta receptor III 6.05E-04 226625_PM_at TGM2 1.90 transglutaminase 2 (C polypeptide, protein- 3.95E-02 211003_PM_x_at glutamine-gamma-glutamyltransferase) TICAM2 /// TMED7- 1.38 toll-like receptor adaptor molecule 2 /// TMED7- 4.71E-02 239431_PM_at TICAM2 TICAM2 readthrough TIMM50 1.26 translocase of inner mitochondrial membrane 50 3.15E-02 217612_PM_at homolog (S. cerevisiae) TIPARP 1.42 TCDD-inducible poly(ADP-ribose) polymerase 9.32E-03 212665_PM_at TNC 1.30 tenascin C 2.49E-02 201645_PM_at TNFRSF10A 1.37 tumor necrosis factor receptor superfamily, 3.25E-02 231775_PM_at member 10a TNFRSF10B 1.46 tumor necrosis factor receptor superfamily, 8.83E-03 209294_PM_x_at member 10b TNFRSF21 1.51 tumor necrosis factor receptor superfamily, 2.55E-03 218856_PM_at member 21 TNFSF12-TNFSF13 /// 1.34 TNFSF12-TNFSF13 readthrough /// tumor 4.86E-02 209500_PM_x_at TNFSF13 necrosis factor (ligand) superfamily, member 13 TNFSF9 1.75 tumor necrosis factor (ligand) superfamily, 2.82E-03 206907_PM_at member 9 TRAF4 1.36 TNF receptor-associated factor 4 2.93E-02 242473_PM_at TRIB1 1.48 tribbles homolog 1 (Drosophila) 6.49E-03 202241_PM_at TSPAN12 2.26 tetraspanin 12 1.36E-02 219274_PM_at TXNRD1 1.56 thioredoxin reductase 1 1.72E-02 201266_PM_at VAV3 3.58 vav 3 guanine nucleotide exchange factor 3.95E-03 218807_PM_at VLDLR 1.57 very low density lipoprotein receptor 1.09E-02 209822_PM_s_at VOPP1 1.41 vesicular, overexpressed in cancer, prosurvival 2.85E-03 208091_PM_s_at protein 1 WNT7A 2.27 wingless-type MMTV integration site family, 5.26E-05 210248_PM_at member 7A WNT7B 1.30 wingless-type MMTV integration site family, 4.96E-02 238105_PM_x_at member 7B WNT9A 1.80 wingless-type MMTV integration site family, 1.42E-02 230643_PM_at member 9A WSB2 1.26 WD repeat and SOCS box-containing 2 1.37E-02 213734_PM_at ZMYM6 1.31 zinc finger, MYM-type 6 4.94E-02 213698_PM_at ZNF219 1.30 zinc finger protein 219 4.98E-02 222864_PM_s_at

developmental process ABT1 1.20 activator of basal transcription 1 4.91E-02 218405_PM_at ACSL4 1.46 acyl-CoA synthetase long-chain family member 4.94E-03 202422_PM_s_at 4 ACTA2 1.62 actin, alpha 2, smooth muscle, aorta 5.47E-03 200974_PM_at AGFG1 1.35 ArfGAP with FG repeats 1 1.44E-02 226561_PM_at APAF1 1.40 apoptotic peptidase activating factor 1 3.35E-02 211554_PM_s_at ARG2 1.64 arginase, type II 4.70E-03 203945_PM_at ASPH 1.57 aspartate beta-hydroxylase 7.20E-03 209135_PM_at

132 Chapter 3 Table S8. (continued) Gene alias FC Gene name/description P-value Gene ID ATL1 2.50 atlastin GTPase 1 1.81E-02 223340_PM_at B4GALT1 1.55 UDP-Gal:betaGlcNAc beta 1,4- 2.38E-02 216627_PM_s_at galactosyltransferase, polypeptide 1 BCOR 1.31 BCL6 co-repressor 4.88E-02 219433_PM_at BIK 1.76 BCL2-interacting killer (apoptosis-inducing) 2.48E-02 205780_PM_at BPGM 1.70 2,3-bisphosphoglycerate mutase 1.25E-02 203502_PM_at C19orf46 2.74 chromosome 19 open reading frame 46 3.87E-05 235515_PM_at CA9 1.37 carbonic anhydrase IX 2.86E-02 205199_PM_at CADM1 1.61 cell adhesion molecule 1 2.38E-02 209031_PM_at CAPN2 1.52 calpain 2, (m/II) large subunit 1.04E-02 214888_PM_at CCBE1 8.61 collagen and calcium binding EGF domains 1 7.41E-05 229641_PM_at CDH11 2.32 cadherin 11, type 2, OB-cadherin (osteoblast) 1.70E-02 236179_PM_at CDK13 1.22 cyclin-dependent kinase 13 3.04E-02 228991_PM_at CDKN1C 4.21 cyclin-dependent kinase inhibitor 1C (p57, Kip2) 7.87E-03 213348_PM_at CELF1 1.23 CUGBP, Elav-like family member 1 3.69E-02 1555467_PM_a_at CIB1 1.36 calcium and integrin binding 1 (calmyrin) 1.74E-02 201953_PM_at CLASP2 1.39 cytoplasmic linker associated protein 2 1.55E-02 212308_PM_at COBL 2.29 cordon-bleu homolog (mouse) 1.64E-02 213050_PM_at COL13A1 1.83 collagen, type XIII, alpha 1 4.92E-02 211343_PM_s_at COL4A4 1.63 collagen, type IV, alpha 4 9.53E-03 229779_PM_at CST6 1.43 Cystatin E/M 2.23E-02 231248_PM_at CTBP2 1.29 C-terminal binding protein 2 3.88E-02 201219_PM_at CTNNA1 1.32 catenin (cadherin-associated protein), alpha 1 1.57E-02 1558214_PM_s_at CXADR 1.35 coxsackie virus and adenovirus receptor 4.31E-02 1555716_PM_a_at CXCL17 16.06 chemokine (C-X-C motif) ligand 17 1.93E-05 226960_PM_at CYR61 2.17 cysteine-rich, angiogenic inducer, 61 1.79E-04 210764_PM_s_at DCAF7 1.26 DDB1 and CUL4 associated factor 7 2.34E-02 221745_PM_at DIP2A 1.28 DIP2 disco-interacting protein 2 homolog A 1.39E-02 1561286_PM_a_at (Drosophila) DLG1 1.40 discs, large homolog 1 (Drosophila) 4.59E-02 202515_PM_at DMRT2 1.58 doublesex and mab-3 related transcription 4.41E-02 223704_PM_s_at factor 2 DMRTA2 3.61 DMRT-like family A2 1.02E-02 1558856_PM_at DUSP6 1.53 dual specificity phosphatase 6 1.86E-02 208893_PM_s_at ECE1 1.45 endothelin converting enzyme 1 4.92E-03 201749_PM_at EDIL3 3.16 EGF-like repeats and discoidin I-like domains 3 3.38E-02 225275_PM_at EHF 1.37 Ets homologous factor 4.79E-03 225645_PM_at ELF5 3.67 E74-like factor 5 (ets domain transcription factor) 3.61E-03 220625_PM_s_at ENDOG 1.24 endonuclease G 3.00E-02 204824_PM_at EPCAM 2.03 epithelial cell adhesion molecule 1.30E-02 201839_PM_s_at ETV4 1.23 ets variant 4 3.53E-02 1554576_PM_a_at EYA1 1.63 eyes absent homolog 1 (Drosophila) 2.31E-02 214608_PM_s_at EYA4 16.74 eyes absent homolog 4 (Drosophila) 1.56E-06 238877_PM_at F11R 1.29 F11 receptor 2.52E-02 222354_PM_at FHL1 1.70 four and a half LIM domains 1 3.39E-02 201539_PM_s_at FOXD1 3.64 forkhead box D1 2.88E-02 206307_PM_s_at FOXE1 3.16 forkhead box E1 (thyroid transcription factor 2) 1.49E-02 206912_PM_at

Gene Expression of Airway Epithelium 133 Table S8. (continued) Gene alias FC Gene name/description P-value Gene ID FOXP2 2.54 forkhead box P2 5.08E-03 235201_PM_at FSTL3 1.53 follistatin-like 3 (secreted glycoprotein) 9.86E-03 203592_PM_s_at GADD45B 1.54 growth arrest and DNA-damage-inducible, beta 1.09E-02 207574_PM_s_at GATA6 2.63 GATA binding protein 6 1.36E-02 210002_PM_at GCNT2 1.71 glucosaminyl (N-acetyl) transferase 2, 1.55E-02 230788_PM_at I-branching enzyme (I blood group) GDA 4.56 guanine deaminase 2.55E-03 224209_PM_s_at GPC4 1.84 glypican 4 1.50E-02 204984_PM_at HDAC9 1.22 histone deacetylase 9 4.71E-02 205659_PM_at HES4 1.38 hairy and enhancer of split 4 (Drosophila) 4.23E-02 227347_PM_x_at HMGB3 2.04 high-mobility group box 3 1.58E-04 203744_PM_at HOOK3 1.23 hook homolog 3 (Drosophila) 3.95E-02 236192_PM_at HOXA1 3.11 homeobox A1 6.98E-03 214639_PM_s_at HSD11B1 2.87 hydroxysteroid (11-beta) dehydrogenase 1 4.87E-03 205404_PM_at IER3 1.33 immediate early response 3 6.37E-03 201631_PM_s_at IFRD1 1.26 interferon-related developmental regulator 1 4.02E-02 202147_PM_s_at IGF2BP2 1.35 insulin-like growth factor 2 mRNA binding 4.47E-02 223963_PM_s_at protein 2 IRX5 1.35 iroquois homeobox 5 1.70E-02 210239_PM_at JPH1 1.48 junctophilin 1 3.55E-02 229139_PM_at KAL1 1.75 Kallmann syndrome 1 sequence 3.28E-03 205206_PM_at KIAA1217 1.26 KIAA1217 2.84E-02 232762_PM_at KLF7 1.45 Kruppel-like factor 7 (ubiquitous) 4.77E-02 238482_PM_at KRT18 1.95 keratin 18 6.05E-04 201596_PM_x_at KRT19 7.71 keratin 19 5.68E-04 201650_PM_at KRT31 1.95 keratin 31 1.36E-02 206677_PM_at LAMB3 1.26 laminin, beta 3 1.78E-02 209270_PM_at LAMC2 2.00 laminin, gamma 2 2.33E-02 207517_PM_at LBH 3.35 limb bud and heart development homolog 6.42E-05 221011_PM_s_at (mouse) LMO2 1.99 LIM domain only 2 (rhombotin-like 1) 4.66E-04 204249_PM_s_at LPPR1 1.70 lipid phosphate phosphatase-related protein 3.72E-02 219732_PM_at type 1 LRG1 1.64 leucine-rich alpha-2-glycoprotein 1 1.11E-02 228648_PM_at LRRC8A 1.42 leucine rich repeat containing 8 family, member 8.55E-03 233487_PM_s_at A MAFF 1.51 v-maf musculoaponeurotic fibrosarcoma 5.14E-03 36711_PM_at oncogene homolog F (avian) MAFG 1.25 v-maf musculoaponeurotic fibrosarcoma 2.39E-02 204970_PM_s_at oncogene homolog G (avian) MAFK 1.65 v-maf musculoaponeurotic fibrosarcoma 1.01E-02 226206_PM_at oncogene homolog K (avian) MAN2A1 1.36 mannosidase, alpha, class 2A, member 1 2.67E-02 226538_PM_at MATN3 1.60 matrilin 3 1.40E-02 206091_PM_at MECOM 1.87 MDS1 and EVI1 complex locus 1.83E-02 226420_PM_at MID1 1.28 midline 1 (Opitz/BBB syndrome) 3.28E-02 203636_PM_at MPZL2 1.31 myelin protein zero-like 2 2.34E-02 203779_PM_s_at

134 Chapter 3 Table S8. (continued) Gene alias FC Gene name/description P-value Gene ID MXD1 1.50 MAX dimerization protein 1 1.51E-02 228846_PM_at MYLIP 1.64 myosin regulatory light chain interacting protein 2.98E-02 228098_PM_s_at NCF2 2.63 neutrophil cytosolic factor 2 2.24E-04 209949_PM_at NHS 1.31 Nance-Horan syndrome (congenital cataracts 3.26E-02 228933_PM_at and dental anomalies) NKX2-8 1.40 NK2 homeobox 8 2.38E-02 207451_PM_at NTNG1 1.82 netrin G1 3.84E-02 236088_PM_at ODC1 1.98 ornithine decarboxylase 1 4.58E-02 200790_PM_at PAFAH1B3 1.31 platelet-activating factor acetylhydrolase 1b, 2.99E-02 203228_PM_at catalytic subunit 3 PAQR8 1.57 progestin and adipoQ receptor family member 2.09E-02 227626_PM_at VIII PARD6B 1.79 par-6 partitioning defective 6 homolog beta (C. 7.14E-03 235165_PM_at elegans) PAX9 1.50 paired box 9 2.63E-02 207059_PM_at PCDHA1 /// PCDHA10 2.94 protocadherin alpha family and protocadherin 1.62E-03 223435_PM_s_at /// PCDHA11 /// alpha subfamily C PCDHA12 /// PCDHA13 /// PCDHA2 /// PCDHA3 /// PCDHA4 /// PCDHA5 /// PCDHA6 /// PCDHA7 /// PCDHA8 /// PCDHA9 /// PCDHAC1 /// PCDHAC2 PHC2 1.37 polyhomeotic homolog 2 (Drosophila) 1.47E-02 200919_PM_at PHF10 1.25 PHD finger protein 10 4.96E-02 219126_PM_at PHLDA2 1.47 pleckstrin homology-like domain, family A, 5.00E-03 209803_PM_s_at member 2 PIM1 1.28 pim-1 oncogene 3.19E-02 209193_PM_at PODXL 10.45 podocalyxin-like 5.03E-03 201578_PM_at PRDM16 1.66 PR domain containing 16 3.77E-03 232424_PM_at PSME4 1.22 proteasome (prosome, macropain) activator 4.29E-02 212219_PM_at subunit 4 PTGS2 2.93 prostaglandin-endoperoxide synthase 2.12E-03 204748_PM_at 2 (prostaglandin G/H synthase and cyclooxygenase) PVRL3 1.64 poliovirus receptor-related 3 1.55E-03 213325_PM_at RFX3 1.64 regulatory factor X, 3 (influences HLA class II 9.32E-03 230403_PM_at expression) RGNEF 1.35 guanine nucleotide exchange factor 1.18E-02 1554003_PM_at RNF114 1.26 ring finger protein 114 1.75E-02 200867_PM_at ROD1 1.19 ROD1 regulator of differentiation 1 (S. pombe) 4.77E-02 224617_PM_at RUNX2 2.67 runt-related transcription factor 2 9.15E-04 232231_PM_at S100A4 2.15 S100 calcium binding protein A4 1.21E-02 203186_PM_s_at SATB1 1.82 SATB homeobox 1 4.09E-03 203408_PM_s_at SATB2 1.54 SATB homeobox 2 5.85E-03 213435_PM_at SDC2 2.38 syndecan 2 1.27E-03 212154_PM_at

Gene Expression of Airway Epithelium 135 Table S8. (continued) Gene alias FC Gene name/description P-value Gene ID SEMA3A 2.75 sema domain, immunoglobulin domain (Ig), 7.39E-04 206805_PM_at short basic domain, secreted, (semaphorin) 3A SEMA4D 1.48 sema domain, immunoglobulin domain (Ig), 1.72E-02 203528_PM_at transmembrane domain ™, short cytoplasmic domain, (semaphorin) 4D SEMA7A 2.01 semaphorin 7A, GPI membrane anchor (John 6.61E-03 230345_PM_at Milton Hagen blood group) SGCB 1.35 sarcoglycan, beta (dystrophin-associated 1.67E-02 226112_PM_at glycoprotein) SIX4 1.46 SIX homeobox 4 1.67E-02 229796_PM_at SLC40A1 1.58 solute carrier family 40 (iron-regulated 4.94E-02 223044_PM_at transporter), member 1 SMARCA1 1.46 SWI/SNF related, matrix associated, actin 5.52E-03 203875_PM_at dependent regulator of chromatin, subfamily a, member 1 SOBP 8.37 sine oculis binding protein homolog 4.54E-05 218974_PM_at (Drosophila) SOX7 1.31 SRY (sex determining region Y)-box 7 2.45E-02 224013_PM_s_at SPDEF 7.03 SAM pointed domain containing ets 2.68E-04 220192_PM_x_at transcription factor SPESP1 2.53 sperm equatorial segment protein 1 2.59E-02 229352_PM_at SPRED1 1.37 sprouty-related, EVH1 domain containing 1 3.48E-02 235074_PM_at SRPX2 2.91 sushi-repeat-containing protein, X-linked 2 9.93E-03 205499_PM_at SSH1 1.36 slingshot homolog 1 (Drosophila) 2.69E-02 221752_PM_at STS 1.43 steroid sulfatase (microsomal), isozyme S 3.03E-02 203769_PM_s_at TACC1 1.51 transforming, acidic coiled-coil containing 5.47E-03 1554690_PM_a_at protein 1 TAGLN3 2.92 transgelin 3 1.52E-03 204743_PM_at TBX1 1.61 T-box 1 2.60E-03 236926_PM_at TLL2 1.57 tolloid-like 2 3.54E-02 215008_PM_at TNFRSF12A 1.28 tumor necrosis factor receptor superfamily, 2.63E-02 218368_PM_s_at member 12A TPM3 1.38 tropomyosin 3 8.86E-03 238065_PM_at TTC7A 1.32 tetratricopeptide repeat domain 7A 1.45E-02 224923_PM_at TWIST1 9.30 twist homolog 1 (Drosophila) 1.56E-06 213943_PM_at TWIST2 3.70 twist homolog 2 (Drosophila) 7.17E-03 229404_PM_at UHRF2 1.37 ubiquitin-like with PHD and ring finger domains 2.27E-02 225610_PM_at 2 VEZF1 1.69 vascular endothelial zinc finger 1 9.11E-04 202172_PM_at WHSC1 1.44 Wolf-Hirschhorn syndrome candidate 1 3.90E-02 223472_PM_at ZEB1 1.37 zinc finger E-box binding homeobox 1 2.27E-02 212764_PM_at ZFHX3 1.51 zinc finger homeobox 3 1.62E-02 226137_PM_at ZFP36L1 1.82 zinc finger protein 36, C3H type-like 1 1.01E-03 211965_PM_at ZFPM2 1.93 zinc finger protein, multitype 2 1.36E-02 219778_PM_at ZNF354A 1.29 zinc finger protein 354A 4.29E-02 205427_PM_at Given are abbreviation (Gene alias), fold change (FC), short description (Gene name/description), P-value, and probe ID (Gene ID).

136 Chapter 3 Table S9. Genes that were significantly higher expressed by healthy nasal epithelial cells sorted by ontology analysis in functional groups Gene alias FC Gene name/description P-value Gene ID Cell adhesion AEBP1 3.08 AE binding protein 1 2.34E-02 201792_PM_at AJAP1 1.47 adherens junctions associated protein 1 1.69E-02 206460_PM_at ATP2C1 1.20 ATPase, Ca++ transporting, type 2C, member 1 4.58E-02 212255_PM_s_at BCAM 1.37 basal cell adhesion molecule (Lutheran blood 2.78E-02 40093_PM_at group) BCL2L11 1.42 BCL2-like 11 (apoptosis facilitator) 3.43E-02 225606_PM_at BVES 2.05 blood vessel epicardial substance 1.32E-03 228783_PM_at CD36 1.82 CD36 molecule (thrombospondin receptor) 3.93E-02 209555_PM_s_at CDHR1 1.26 cadherin-related family member 1 4.27E-02 1555019_PM_at CDSN 2.34 corneodesmosin 1.69E-02 206192_PM_at CELSR2 1.42 cadherin, EGF LAG seven-pass G-type receptor 2 2.07E-02 36499_PM_at (flamingo homolog, Drosophila) CLCA2 1.80 chloride channel accessory 2 4.57E-03 206166_PM_s_at CLDN11 7.58 claudin 11 7.42E-03 228335_PM_at CLDN17 2.24 claudin 17 3.54E-02 221328_PM_at CNTN1 2.26 Contactin 1 4.55E-03 227202_PM_at CNTN3 2.12 contactin 3 (plasmacytoma associated) 3.19E-02 229831_PM_at CNTNAP3 1.71 contactin associated protein-like 3 3.32E-02 223796_PM_at COL12A1 3.21 collagen, type XII, alpha 1 6.49E-03 225664_PM_at COL6A1 9.89 collagen, type VI, alpha 1 1.41E-04 213428_PM_s_at CRNN 2.48 cornulin 4.83E-02 220090_PM_at DCBLD1 1.75 discoidin, CUB and LCCL domain containing 1 6.45E-03 226609_PM_at DSC1 1.88 desmocollin 1 9.68E-03 207324_PM_s_at DSC2 2.35 desmocollin 2 1.08E-03 204750_PM_s_at DSC3 1.47 desmocollin 3 8.28E-03 206033_PM_s_at DSG1 37.49 desmoglein 1 1.47E-05 206642_PM_at DSG3 1.96 desmoglein 3 (pemphigus vulgaris antigen) 1.13E-02 205595_PM_at ECM2 1.32 extracellular matrix protein 2, female organ and 2.17E-02 206101_PM_at adipocyte specific EFS 1.46 embryonal Fyn-associated substrate 3.83E-02 204400_PM_at EGFL6 4.00 EGF-like-domain, multiple 6 8.02E-03 219454_PM_at FAT1 1.35 FAT tumor suppressor homolog 1 (Drosophila) 2.40E-02 201579_PM_at FAT2 1.99 FAT tumor suppressor homolog 2 (Drosophila) 1.42E-03 208153_PM_s_at GPNMB 5.52 glycoprotein (transmembrane) nmb 5.50E-03 201141_PM_at GPR56 1.33 G protein-coupled receptor 56 4.41E-02 212070_PM_at ITGA4 2.30 integrin, alpha 4 (antigen CD49D, alpha 4 1.58E-02 213416_PM_at subunit of VLA-4 receptor) ITGBL1 1.83 integrin, beta-like 1 (with EGF-like repeat 5.16E-03 205422_PM_s_at domains) JUP 1.25 junction plakoglobin 2.72E-02 201015_PM_s_at LAMA1 24.93 laminin, alpha 1 1.47E-06 227048_PM_at LYPD3 2.01 LY6/PLAUR domain containing 3 8.03E-03 204952_PM_at MAEA 1.36 macrophage erythroblast attacher 2.53E-02 207922_PM_s_at MIA 1.92 melanoma inhibitory activity 4.57E-03 206560_PM_s_at NID1 1.61 nidogen 1 3.98E-02 202007_PM_at NID2 2.76 nidogen 2 (osteonidogen) 1.55E-03 204114_PM_at NPNT 1.61 nephronectin 3.73E-03 225911_PM_at

Gene Expression of Airway Epithelium 137 Table S9. (continued) Gene alias FC Gene name/description P-value Gene ID PARVB 1.63 parvin, beta 7.09E-03 37966_PM_at PCDH18 1.63 protocadherin 18 2.60E-03 225975_PM_at PCDHB10 1.39 protocadherin beta 10 2.45E-02 223854_PM_at PCDHB14 1.81 protocadherin beta 14 3.03E-02 231726_PM_at PCDHGA1 /// 1.34 protocadherin gamma subfamily A, B, and C 1.70E-02 211066_PM_x_at PCDHGA10 /// PCDHGA11 /// PCDHGA12 /// PCDHGA2 /// PCDHGA3 /// PCDHGA4 /// PCDHGA5 /// PCDHGA6 /// PCDHGA7 /// PCDHGA8 /// PCDHGA9 /// PCDHGB1 /// PCDHGB2 /// PCDHGB3 /// PCDHGB4 /// PCDHGB5 /// PCDHGB6 /// PCDHGB7 /// PCDHGC3 /// PCDHGC4 /// PCDHGA11 /// 1.44 protocadherin gamma subfamily A, B, and C 2.97E-02 205717_PM_x_at PCDHGA12 /// PCDHGA6 /// PCDHGB3 /// PCDHGB4 /// PCDHGB5 /// PCDHGB6 /// PCDHGB7 /// PCDHGC3 /// PCDHGC4 /// PCDHGC5 PERP 1.33 PERP, TP53 apoptosis effector 3.80E-02 236009_PM_at PKP1 1.46 plakophilin 1 (ectodermal dysplasia/skin fragility 2.17E-02 221854_PM_at syndrome) PKP3 1.43 plakophilin 3 4.55E-03 209873_PM_s_at PTK7 1.34 PTK7 protein tyrosine kinase 7 1.99E-02 207011_PM_s_at PVRL4 1.46 poliovirus receptor-related 4 1.72E-02 223540_PM_at SCARB1 1.84 scavenger receptor class B, member 1 4.67E-03 201819_PM_at SDK2 1.28 sidekick homolog 2 (chicken) 4.42E-02 242064_PM_at SIRPA 1.22 signal-regulatory protein alpha 3.72E-02 202896_PM_s_at SOX9 1.71 SRY (sex determining region Y)-box 9 3.37E-04 202935_PM_s_at SRPX 1.88 sushi-repeat-containing protein, X-linked 9.52E-04 204955_PM_at SSPN 1.34 sarcospan (Kras oncogene-associated gene) 2.38E-02 204964_PM_s_at THBS1 1.39 thrombospondin 1 4.67E-02 201107_PM_s_at THBS2 3.79 thrombospondin 2 2.25E-02 203083_PM_at THY1 18.97 Thy-1 cell surface antigen 1.74E-05 208850_PM_s_at

138 Chapter 3 Table S9. (continued) Gene alias FC Gene name/description P-value Gene ID TSTA3 1.22 tissue specific transplantation antigen P35B 2.52E-02 36936_PM_at VNN1 2.60 vanin 1 1.25E-02 205844_PM_at calcium-ion binding ANXA6 3.28 annexin A6 8.85E-03 200982_PM_s_at C1R 4.60 complement component 1, r subcomponent 4.67E-03 212067_PM_s_at C1S 7.12 complement component 1, s subcomponent 9.28E-03 208747_PM_s_at CALB2 1.34 calbindin 2 2.15E-02 205428_PM_s_at CALML5 2.44 calmodulin-like 5 2.20E-02 220414_PM_at CAPN12 1.35 calpain 12 4.98E-02 228705_PM_at DLK2 1.81 delta-like 2 homolog (Drosophila) 1.14E-02 220262_PM_s_at DNER 1.88 delta/notch-like EGF repeat containing 2.75E-02 226281_PM_at EEF2K 1.23 eukaryotic elongation factor-2 kinase 4.50E-02 225545_PM_at EPS15L1 1.40 epidermal growth factor receptor pathway 2.96E-02 231926_PM_at substrate 15-like 1 FBLN2 1.53 fibulin 2 4.61E-03 203886_PM_s_at FKBP10 1.75 FK506 binding protein 10 9.32E-03 219249_PM_s_at JMJD7-PLA2G4B /// 1.76 JMJD7-PLA2G4B readthrough /// phospholipase 6.35E-03 219095_PM_at PLA2G4B A2, group IVB (cytosolic) LCP1 6.91 lymphocyte cytosolic protein 1 (L-plastin) 3.05E-03 208885_PM_at LPCAT2 1.53 lysophosphatidylcholine acyltransferase 2 1.07E-02 227889_PM_at LTBP3 1.41 latent transforming growth factor beta binding 2.17E-02 219922_PM_s_at protein 3 MEGF9 1.79 multiple EGF-like-domains 9 1.93E-03 212830_PM_at MMP28 2.92 matrix metallopeptidase 28 6.84E-03 239272_PM_at MMP3 5.73 matrix metallopeptidase 3 (stromelysin 1, 1.08E-02 205828_PM_at progelatinase) NOTCH2 1.32 Notch homolog 2 (Drosophila) 7.81E-03 202443_PM_x_at NOTCH3 1.45 Notch homolog 3 (Drosophila) 6.68E-03 203238_PM_s_at PCLO 1.53 piccolo (presynaptic cytomatrix protein) 4.02E-03 213558_PM_at PLA2G4A 1.91 phospholipase A2, group IVA (cytosolic, calcium- 1.01E-02 210145_PM_at dependent) PLCD1 1.35 phospholipase C, delta 1 2.51E-02 205125_PM_at PLSCR4 1.83 phospholipid scramblase 4 2.64E-03 218901_PM_at PRRG4 2.05 proline rich Gla (G-carboxyglutamic acid) 4 1.83E-03 207291_PM_at (transmembrane) RASGRP2 1.62 RAS guanyl releasing protein 2 (calcium and 4.55E-03 214369_PM_s_at DAG-regulated) RPTN 4.68 repetin 4.61E-03 1553454_PM_at S100A12 5.17 S100 calcium binding protein A12 1.29E-04 205863_PM_at S100A7 16.15 S100 calcium binding protein A7 5.52E-03 205916_PM_at S100A8 1.83 S100 calcium binding protein A8 1.42E-02 202917_PM_s_at S100A9 1.75 S100 calcium binding protein A9 1.69E-02 203535_PM_at SLC25A12 1.32 solute carrier family 25 (mitochondrial carrier, 3.99E-02 203339_PM_at Aralar), member 12 SMOC1 1.51 SPARC related modular calcium binding 1 1.97E-02 222784_PM_at SPARC 2.14 secreted protein, acidic, cysteine-rich 7.78E-03 212667_PM_at (osteonectin) SYT2 1.25 synaptotagmin II 3.48E-02 214903_PM_at

Gene Expression of Airway Epithelium 139 Table S9. (continued) Gene alias FC Gene name/description P-value Gene ID epithelial cell differentiation CLIC4 1.54 chloride intracellular channel 4 6.62E-03 201560_PM_at CNFN 3.26 cornifelin 4.29E-04 224329_PM_s_at COL4A1 4.39 collagen, type IV, alpha 1 1.93E-03 211981_PM_at DLX5 3.27 distal-less homeobox 5 1.41E-04 213707_PM_s_at DLX6 1.55 distal-less homeobox 6 7.87E-03 239309_PM_at EREG 1.79 epiregulin 1.74E-03 205767_PM_at ESR1 1.27 estrogen receptor 1 2.31E-02 205225_PM_at FGF2 1.91 fibroblast growth factor 2 (basic) 1.18E-02 204422_PM_s_at FGFR2 1.70 fibroblast growth factor receptor 2 1.92E-02 203639_PM_s_at FZD7 2.89 frizzled homolog 7 (Drosophila) 1.59E-03 203706_PM_s_at ID3 1.72 inhibitor of DNA binding 3, dominant negative 4.36E-03 207826_PM_s_at helix-loop-helix protein IVL 2.61 involucrin 2.69E-03 214599_PM_at KAZ 1.74 kazrin 5.47E-03 213478_PM_at KRT14 1.44 keratin 14 2.64E-03 209351_PM_at LCE3D 3.64 late cornified envelope 3D 2.51E-02 224328_PM_s_at PAX6 10.29 paired box 6 3.16E-06 235795_PM_at RHCG 2.18 Rh family, C glycoprotein 3.50E-02 219554_PM_at SPINK5 2.83 serine peptidase inhibitor, Kazal type 5 1.36E-02 205185_PM_at SPRR1A 1.27 small proline-rich protein 1A 4.88E-02 213796_PM_at SPRR1B 1.29 small proline-rich protein 1B (cornifin) 3.74E-02 205064_PM_at SPRR2G 17.24 small proline-rich protein 2G 6.19E-04 236119_PM_s_at SPRR4 2.45 small proline-rich protein 4 5.47E-03 1552620_PM_at TFCP2L1 1.52 transcription factor CP2-like 1 6.58E-03 219735_PM_s_at WNT5A 3.45 wingless-type MMTV integration site family, 6.14E-03 213425_PM_at member 5A Given are abbreviation (Gene alias), fold change (FC), short description (Gene name/description), P-value, and probe ID (Gene ID).

Table S10. The genes that were significantly higher expressed by bronchial epithelial cells from patients with allergic rhinitis, sorted by ontology analysis in functional groups Gene alias FC Gene name/description P-value Gene ID regulation of signal transduction 202241_ TRIB1 2.29 tribbles homolog 1 (Drosophila) 3.54E-02 PM_at similar to single Ig IL-1R-related molecule /// single LOC100294402 /// immunoglobulin and toll-interleukin 1 receptor (TIR) 52940_ SIGIRR 1.68 domain 4.29E-02 PM_at Given are abbreviation (Gene alias), fold change (FC), short description (Gene name/description), P-value, and probe ID (Gene ID).

140 Chapter 3 Table S11. The genes that were significantly higher expressed by nasal epithelial cells from patients with allergic rhinitis, sorted by ontology analysis in functional groups Gene alias FC Gene name/description P-value Gene ID metal ion binding AEBP1 4.95 AE binding protein 1 2.00E-02 201792_PM_at ANTXR1 2.13 anthrax toxin receptor 1 4.52E-02 220092_PM_s_at ANXA6 5.04 annexin A6 1.66E-02 200982_PM_s_at ARSI 3.04 arylsulfatase family, member I 1.16E-02 230275_PM_at ATP1A1 1.50 ATPase, Na+/K+ transporting, alpha 1 polypeptide 4.13E-02 220948_PM_s_at BCL11A 1.52 B-cell CLL/lymphoma 11A (zinc finger protein) 4.60E-02 219497_PM_s_at BCL11B 1.94 B-cell CLL/lymphoma 11B (zinc finger protein) 3.91E-02 222895_PM_s_at C1orf124 1.57 chromosome 1 open reading frame 124 4.56E-02 223511_PM_at C1R 6.27 complement component 1, r subcomponent 2.70E-02 212067_PM_s_at C1S 10.89 complement component 1, s subcomponent 1.50E-02 208747_PM_s_at CHPT1 1.89 choline phosphotransferase 1 4.66E-02 230364_PM_at CYBRD1 1.83 cytochrome b reductase 1 2.58E-02 222453_PM_at CYCS 1.91 cytochrome c, somatic 3.08E-02 229415_PM_at CYP26B1 5.20 cytochrome P450, family 26, subfamily B, polypeptide 1 2.41E-02 219825_PM_at DMD 1.86 dystrophin 4.14E-02 203881_PM_s_at DNMT3B 1.70 DNA (cytosine-5-)-methyltransferase 3 beta 2.18E-02 220668_PM_s_at DST 2.01 dystonin 3.74E-02 212254_PM_s_at DZIP1 2.91 DAZ interacting protein 1 4.25E-02 204557_PM_s_at DZIP3 1.61 DAZ interacting protein 3, zinc finger 4.58E-02 213186_PM_at EGFL6 6.20 EGF-like-domain, multiple 6 3.22E-02 219454_PM_at FAT2 2.12 FAT tumor suppressor homolog 2 (Drosophila) 2.43E-02 208153_PM_s_at FKBP10 1.83 FK506 binding protein 10 4.14E-02 219249_PM_s_at GLI3 1.65 GLI family zinc finger 3 3.79E-02 227376_PM_at LCP1 7.96 lymphocyte cytosolic protein 1 (L-plastin) 8.46E-03 208885_PM_at LOC653501 /// ZNF658 2.35 family members of zinc finger protein 658 /// ZNF658B 3.44E-02 231950_PM_at MMP28 2.09 matrix metallopeptidase 28 3.74E-02 219909_PM_at MYLK 11.94 myosin light chain kinase 1.64E-02 202555_PM_s_at NAPEPLD 1.74 N-acyl phosphatidylethanolamine phospholipase D 4.46E-02 226041_PM_at OSGEPL1 1.58 O-sialoglycoprotein endopeptidase-like 1 3.74E-02 220631_PM_at PCLO 1.83 piccolo (presynaptic cytomatrix protein) 4.56E-02 213558_PM_at PHOSPHO2 1.72 phosphatase, orphan 2 3.08E-02 230434_PM_at PLEKHF2 1.46 pleckstrin homology domain containing, family F (with FYVE domain) member 2 4.59E-02 222699_PM_s_at PLSCR4 2.47 phospholipid scramblase 4 2.48E-02 218901_PM_at PRICKLE2 3.42 prickle homolog 2 (Drosophila) 1.83E-02 225968_PM_at PTGS1 1.86 prostaglandin-endoperoxide synthase 1 (prostaglandin G/H synthase and cyclooxygenase) 1.60E-02 215813_PM_s_at RAD50 1.64 RAD50 homolog (S. cerevisiae) 3.08E-02 209349_PM_at SEPX1 1.49 selenoprotein X, 1 4.99E-02 217977_PM_at SGCE 2.09 sarcoglycan, epsilon 1.60E-02 204688_PM_at

Gene Expression of Airway Epithelium 141 Table S11. (continued) Gene alias FC Gene name/description P-value Gene ID SP110 1.74 SP110 nuclear body protein 3.34E-02 208392_PM_x_at SPARC 4.22 secreted protein, acidic, cysteine-rich (osteonectin) 3.51E-02 200665_PM_s_at STAT1 1.77 signal transducer and activator of transcription 1 AFFX-HUMISGF3 3.06E-02 A/M97935_5_at STEAP3 1.51 STEAP family member 3 3.85E-02 218424_PM_s_at TAF15 1.66 TAF15 RNA polymerase II, TATA box binding protein (TBP)-associated factor 3.15E-02 202840_PM_at THBS2 6.82 thrombospondin 2 3.08E-02 203083_PM_at TRIM59 2.59 tripartite motif-containing 59 1.60E-02 235476_PM_at TRIM69 1.93 tripartite motif-containing 69 3.22E-02 1568592_PM_at USP13 2.38 ubiquitin specific peptidase 13 (isopeptidase T-3) 3.10E-02 205356_PM_at ZMAT3 1.60 zinc finger, matrin type 3 1555609_PM_a_ 3.63E-02 at ZNF124 2.20 zinc finger protein 124 3.22E-02 206928_PM_at ZNF30 1.73 zinc finger protein 30 4.48E-02 232014_PM_at ZNF300 2.03 zinc finger protein 300 4.29E-02 228144_PM_at ZNF362 1.95 zinc finger protein 362 4.14E-02 226820_PM_at ZNF37A 1.59 zinc finger protein 37A 2.88E-02 228711_PM_at ZNF827 1.95 Zinc finger protein 827 4.14E-02 228046_PM_at ZNF879 1.86 zinc finger protein 879 2.82E-02 230421_PM_at Given are abbreviation (Gene alias), fold change (FC), short description (Gene name/description), P-value, and probe ID (Gene ID).

142 Chapter 3 Table S12. Gene ontology analysis of the genes from the different clusters resulted by the K-means clustering Gene alias Gene name/description Cluster 1: developmental process ADAMTS1 ADAM metallopeptidase with thrombospondin type 1 motif, 1 ATL1 atlastin GTPase 1 BMPR1B bone morphogenetic protein receptor, type IB C19orf46 chromosome 19 open reading frame 46 CARD11 caspase recruitment domain family, member 11 CCBE1 collagen and calcium binding EGF domains 1 CDH11 Cadherin 11, type 2, OB-cadherin (osteoblast) COBL cordon-bleu homolog CXCL17 chemokine (C-X-C motif) ligand 17 CYR61 cysteine-rich, angiogenic inducer, 61 EDIL3 EGF-like repeats and discoidin I-like domains 3 EDN1 endothelin 1 EPHB2 EPH receptor B2 EYA4 eyes absent homolog 4 (Drosophila) FGFR3 fibroblast growth factor receptor 3 FOXA1 Forkhead box A1 FOXE1 forkhead box E1 (thyroid transcription factor 2) FOXP2 forkhead box P2 GATA6 GATA binding protein 6 HLA-DQB1 /// HLA-DQB2 major histocompatibility complex, class II, DR beta family /// LOC100133583 /// LOC100293977 HMGB3 high-mobility group box 3 HOXA1 homeobox A1 IRS1 insulin receptor substrate 1 ITGA2 integrin, alpha 2 (CD49B, alpha 2 subunit of VLA-2 receptor) JAK2 Janus kinase 2 potassium large conductance calcium-activated channel, subfamily M, alpha KCNMA1 member 1 KRT18 keratin 18 KRT19 Keratin 19 MITF microphthalmia-associated transcription factor NKX2-1 NK2 homeobox 1 OXTR oxytocin receptor PLLP plasma membrane proteolipid (plasmolipin) PODXL podocalyxin-like prostaglandin-endoperoxide synthase 2 (prostaglandin G/H synthase and PTGS2 cyclooxygenase)

Gene Expression of Airway Epithelium 143 Table S12. (continued) Gene alias Gene name/description RUNX2 runt-related transcription factor 2 SDC2 syndecan 2 sema domain, immunoglobulin domain (Ig), short basic domain, secreted, SEMA3A (semaphorin) 3A SOBP sine oculis binding protein homolog (Drosophila) SPDEF SAM pointed domain containing ets transcription factor SPOCK1 sparc/osteonectin, cwcv and kazal-like domains proteoglycan (testican) 1 TAGLN3 transgelin 3 TGFBR3 transforming growth factor, beta receptor III TSPAN12 tetraspanin 12 TWIST1 twist homolog 1 (Drosophila) TWIST2 twist homolog 2 (Drosophila) VAV3 vav 3 guanine nucleotide exchange factor

Cluster 3: epidermis development ALOX12B arachidonate 12-lipoxygenase, 12R type CALML5 calmodulin-like 5 CDSN corneodesmosin CNFN cornifelin IVL involucrin LCE3D late cornified envelope 3D

peptidase regulator activity PI3 peptidase inhibitor 3, skin-derived SERPINB3 serpin peptidase inhibitor, clade B (ovalbumin), member 3 SPINK5 serine peptidase inhibitor, Kazal type 5 WFDC12 WAP four-disulfide core domain 12 WFDC5 WAP four-disulfide core domain 5

Cluster 4: anatomical structure morphogenesis ACP5 acid phosphatase 5, tartrate resistant BCL11B B-cell CLL/lymphoma 11B (zinc finger protein) CARD16 /// CASP1 caspase recruitment domain family, member 16 /// caspase 1, apoptosis- related cysteine peptidase (interleukin 1, beta, convertase) caspase 1, apoptosis-related cysteine peptidase (interleukin 1, beta, CASP1 convertase) COL4A1 collagen, type IV, alpha 1 COL4A2 collagen, type IV, alpha 2 CSPG4 chondroitin sulfate proteoglycan 4

144 Chapter 3 Table S12. (continued) Gene alias Gene name/description DLX1 distal-less homeobox 1 DMD Dystrophin EPHA4 EPH receptor A4 FLI1 Friend leukemia virus integration 1 FOXG1 forkhead box G1 GAS1 growth arrest-specific 1 GATA3 GATA binding protein 3 GJC1 gap junction protein, gamma 1, 45kDa IGF2BP3 insulin-like growth factor 2 mRNA binding protein 3 LAMA1 laminin, alpha 1 MEOX1 mesenchyme homeobox 1 MSX2 msh homeobox 2 OSR2 odd-skipped related 2 (Drosophila) PAX3 paired box 3 PAX6 paired box 6 S100A7 S100 calcium binding protein A7 SFRP1 Secreted frizzled-related protein 1 SIX3 SIX homeobox 3 SLC1A3 solute carrier family 1 (glial high affinity glutamate transporter), member 3 SP8 Sp8 transcription factor TCF7L2 Transcription factor 7-like 2 (T-cell specific, HMG-box) THY1 Thy-1 cell surface antigen

Cluster 5: retinoic acid binding UGT1A1 /// UGT1A10 /// UDP glucuronosyltransferase 1 family UGT1A3 /// UGT1A4 /// UGT1A5 /// UGT1A6 /// UGT1A7 /// UGT1A8 /// UGT1A9 UGT1A1 /// UGT1A10 /// UDP glucuronosyltransferase 1 family UGT1A4 /// UGT1A6 /// UGT1A8 /// UGT1A9 UGT1A6 UDP glucuronosyltransferase 1 family, polypeptide A6

Cluster 7: immune response BST2 bone marrow stromal cell antigen 2 CTSS cathepsin S chemokine (C-X-C motif) ligand 1 (melanoma growth stimulating activity, CXCL1 alpha) HLA-DQB1 major histocompatibility complex, class II, DQ beta 1 HLA-DQB1 /// LOC100133583 major histocompatibility complex, class II, DQ beta 1

Gene Expression of Airway Epithelium 145 table s12. (continued) gene alias gene name/description HLA-DRB1 /// HLA-DRB3 major histocompatibility complex, class II, DR family /// HLA-DRB4 /// HLA- DRB5 /// LOC100133661 /// LOC100294036 /// LOC100509582 /// LOC100510495 /// LOC100510519 HLA-DRB1 /// HLA-DRB4 major histocompatibility complex, class II, DR family IL23A interleukin 23, alpha subunit p19 IL8 interleukin 8 PTAFR platelet-activating factor receptor SEMA7A semaphorin 7A, GPI membrane anchor (John Milton Hagen blood group) SYK spleen tyrosine kinase Given are abbreviation (Gene alias), and short description (Gene name/description).

figure s1. Correlation plot of real-time PCR data and microarray results.

146 Chapter 3

CHAPTER 4 dsRNA-induced changes in gene expression pro les of primary nasal and bronchial epithelial cells from patients with asthma, rhinitis and controls

Ariane H. Wagener, Aeilko H. Zwinderman, Silvia Luiten, Wytske J. Fokkens, Elisabeth H. Bel, Peter J. Sterk, Cornelis M. van Drunen

Respiratory Research 2014;15:9 Abstract

Background Rhinovirus infections are the most common cause of asthma exacerbations. The complex responses by airway epithelium to rhinovirus can be captured by gene expression profiling. We hypothesized that: a) upper and lower airway epithelium exhibit differential responses to double-stranded RNA (dsRNA), and b) that this is modulated by the presence of asthma and allergic rhinitis. Objectives: Identification of dsRNA-induced gene expression profiles of primary nasal and bronchial epithelial cells from the same individuals and examining the impact of allergic rhinitis with and without concomitant allergic asthma on expression profiles.

Methods This study had a cross-sectional design including 18 subjects: 6 patients with allergic asthma with concomitant rhinitis, 6 patients with allergic rhinitis, and 6 healthy controls. Comparing 6 subjects per group, the estimated false discovery rate was approximately 5%. RNA was extracted from isolated and cultured primary epithelial cells from nasal biopsies and bronchial brushings stimulated with dsRNA (poly(I:C)), and analyzed by microarray (Affymetrix U133+ PM Genechip Array). Data were analysed using R and the Bioconductor Limma package. Overrepresentation of gene ontology groups were captured by GeneSpring GX12.

Results In total, 17 subjects completed the study successfully (6 allergic asthma with rhinitis, 5 allergic rhinitis, 6 healthy controls). dsRNA-stimulated upper and lower airway epithelium from asthma patients demonstrated significantly fewer induced genes, exhibiting reduced down-regulation of mitochondrial genes. The majority of genes related to viral responses appeared to be similarly induced in upper and lower airways in all groups. However, the induction of several interferon-related genes (IRF3, IFNAR1, IFNB1, IFNGR1, IL28B) was impaired in patients with asthma.

Conclusions dsRNA differentially changes transcriptional profiles of primary nasal and bronchial epithelial cells from patients with allergic rhinitis with or without asthma and controls. Our data suggest that respiratory viruses affect mitochondrial genes, and we identified disease-specific genes that provide potential targets for drug development.

148 Chapter 4 Background

Viral respiratory tract infections are the most common cause of asthma exacerbations (1), with rhinovirus (RV) being the most prominent virus involved. Patients with asthma are not at increased risk of a viral infection as compared to healthy controls, but in case of an upper respiratory infection they are more prone to develop a lower respiratory tract infection with more severe symptoms (2). This suggests that host characteristics are contributing to the clinical responses to virus infections in asthma. The majority of patients with asthma is sensitized to environmental allergens, which is associated with allergic airways inflammation (3). There is increasing evidence of interaction between viral infection and allergic sensitization, with increased risk for a more severe exacerbation if patients with asthma are atopic (4). Since asthma and rhinitis co- exist to variable degrees (5), the host characteristics in upper and lower airways when encountering a respiratory virus are likely to vary to a similar extent. In order to develop effective interventions for the prophylaxis and treatment of virus-induced exacerbations in asthma, it is mandatory to map the responses of both upper and lower airways to respiratory viruses in patients with asthma and/or rhinitis. The upper and lower airway epithelial layer is constantly exposed to viruses, bacteria and allergens, and represents the first line of defence. Experiments with nasal and bronchial epithelial cells from the same individuals suggested greater susceptibility of the lower airways to RV because of differences in electrical resistance and viral replication between upper and lower airway epithelium, though no differences were observed between asthma and healthy controls (6). However, there is increasing evidence that pre- existing asthma affects epithelial cytokine responses to RV, such as impaired interferon (IFN) production and differences in expression of genes involved in immune response and airway remodelling (7-9). Collectively, these studies suggest that the complex role of the airway epithelium in response to viruses is affected by asthma- and allergy-related changes in gene expression. Double-stranded RNA (dsRNA) is produced during RV replication and is an important stimulus of the host immune response (10). Therefore, we hypothesized a) that upper and lower airway epithelium exhibit differential responses to dsRNA infection and b) that this is modulated by the presence of asthma and allergic rhinitis. To that end, we aimed to compare dsRNA-induced gene expression profiles of cultured primary nasal and bronchial epithelial cells obtained from patients with asthma with concomitant allergic rhinitis, patients with allergic rhinitis alone, and healthy controls. The observed gene-expression profiles can be used to delineate the critical pathways that are op- erative in epithelial cells after virus infection in patients with and without pre-existing airways disease.

dsRNA-induced Gene Expression of Airway Epithelium 149 Methods

(see the Methods section of the Supporting Information File)

Subjects In total, 18 subjects (>18 y) were recruited for this study, which is part of a larger project (11). The subjects comprised of three groups: 1) 6 subjects with allergic asthma with concomitant allergic rhinitis, 2) 6 subjects with allergic rhinitis, and 3) 6 healthy controls. Patients with asthma had episodic chest symptoms, controlled or partly con-

trolled disease according to GINA-criteria (12) with airway hyperresponsiveness (PC20 methacholine ≤ 8 mg/mL) according to the standardized tidal volume method (13). All subjects with allergic rhinitis had persistent, moderate to severe disease according to ARIA-criteria (14) with nasal symptoms for more than 4 days a week during more than 4 consecutive weeks. Atopic status was based on the presence of at least one positive skin prick test response (>3mm wheal) to common allergens. Subjects had refrained from using any medication for their asthma, rhinitis or allergy in the four weeks prior to taking biopsies and brushings. Healthy controls had normal spirometric values without

airway hyperresponsiveness (PC20 > 8 mg/mL), did not have a history of lung disease and were not atopic. All subjects were non-smokers or ex-smokers (≥5 pack years). Subjects had not smoked within 12 months prior to the study and they did not have any signs of a respiratory infection at the time of study visits. In the case of a respiratory infection, a 6-week recovery period was taken into account. The study was approved by the hospital Medical Ethics Committee of the Academic Medical Centre in Amsterdam, and the study was registered in the Netherlands trial register (www.trialregister.nl) with identifier NTR2125. All patients gave written informed consent.

Design This cross-sectional study consisted of two study visits. At least 14 days after the screening visit for checking inclusion and exclusion criteria, a fiberoptic bronchoscopy was performed during which 4 bronchial brushings were taken. Local anaesthesia of the larynx and lower airways was achieved using 1% lignocaine. Subsequently, 4 nasal biopsies were taken from the lower edge of the inferior turbinate. Local anaesthesia was achieved by application of adrenalin and cocaine under the inferior turbinate without touching the biopsy site.

150 Chapter 4 Poly(I:C) stimulation of cultured primary epithelial cells Epithelial cells were isolated from bronchial brushings and nasal biopsies as previously described (11). The cells were cultured to 80% confluence and pre-incubated with BEBM prior to stimulation. After 24 hours, the pre-incubation medium was removed and cells were exposed to BEBM containing 20µg/ml Poly(I:C), a synthetic dsRNA, or with BEBM alone (control condition). RNA was extracted from the cells following 24 hours of stimulation. For a detailed description of the primary epithelial cell culture and RNA extraction, see the Methods section of the Supporting Information File.

Analysis and statistics Microarray analysis was done by previously published method (11). In short, Human Genome U133+ PM Genechip Array (Affymetrix inc., Santa Clara, CA, USA) was used for microarray analysis of genes. Next, Affymetrix Expression Console was used to analyze the array images using the robust multichip analysis (RMA) algorithm. Normalized data were further analysed using R (version 2.15) and the Bioconductor Limma package (15). Differential gene expression was measured by empirical Bayes t-statistics and p-values were adjusted for false discovery rate correction (16). The full microarray data was uploaded to the Gene Expression Omnibus (GEO) with accession number GSE51392. GeneSpring GX12 (Agilent Technologies, Amstelveen, The Netherlands) was used for Gene ontology (GO) analysis. To investigate the overrepresentation of gene ontology groups we used the p-value adjusted for multiple testing by Benjamini-Yekutieli (17) (p-value <0.01). To enable validation of the microarray experiment changes in gene expression after poly(I:C) stimulation of nine genes were measured by independent real time PCR on the same starting material used for the microarray analysis (see the Methods section of the Supporting Information File). Sample size estimation was performed by a validated algorithm for microarray studies as published previously by our group (18), using data from two studies from others and ourselves (19;20). This analysis showed that the present study had a False Discovery Rate of approximately 5% for detecting at least a 1.5-fold difference in gene expression when comparing three groups of 6 subjects at a significance level of 0.0001.

Results

The results of the validation by independent real time PCR are presented in Table S1 and Figure S1 of the Supporting Information File.

dsRNA-induced Gene Expression of Airway Epithelium 151 Poly(I:C)-induced changes in airway epithelial cells Sufficient RNA for gene expression profiling was obtained from both nasal and bronchial epithelium of 6 healthy controls, 5 patients with allergic rhinitis (1 patient was excluded because of insufficient RNA in the nasal sample) and 6 patients with both allergic rhinitis and allergic asthma. The baseline characteristics of the subjects included in the study are shown in Table 1 (11). There were no differences between the groups in age and

spirometry (p=0.4 and p=0.3, respectively). As expected, PC20 was significantly lower in the patients with both asthma and rhinitis as compared to those with rhinitis alone and the controls. None of the healthy controls and only 1 out of 5 patients with rhinitis had a

drop of 20% in FEV1 at the highest concentration of methacholine-bromide 19.6 mg/ml. Overall, a strong response was observed after stimulation of the airway epithelial cells with poly(I:C). Using a cut-off of p < 0.05 (adjusted for multiple testing), 10163 and 8342 genes were significantly induced in the healthy upper and lower airway epithelium respectively, 9353 and 5190 genes in patients with allergic rhinitis, and 4919 and 5810 genes in patients with both asthma and allergic rhinitis (see Table S2 of the Supporting Information File). The majority of the most highly up-regulated genes were interferon- related genes (CCL3, CCL4, CCL5, RSAD2, OAS1, OASL, MX1, MX2, IFI6, IFIT1, IFIT3, IFI44, IFI44L, CXCL10, CXCL11, TNFAIP6), which were induced in both upper and lower airways in all subjects (Table 2A and 2B).

Table 1. Baseline characteristics Subjects N = 17 Age* 24 (20-30) Female gender (n) 14

Prebronchodilator FEV1% predicted† 109 (11.0)

PC20‡** 0.35 (0.3) * Median (range) † Mean (Standard Deviation) ‡ Geometric Mean (Geometric Standard Deviation) **Only from patients with both allergic asthma and rhinitis (none of the healthy controls and only 1 out of

5 patients with rhinitis had a drop of 20% in FEV1 at the highest concentration of methacholine-bromide 19.6 mg/ml).

Functional characterization It appeared that ~40% of the poly(I:C)-induced genes was altered in both upper and lower airways in all 3 subject-groups (see Figures 1A and 1B). When studying the functional characterization of these genes, many comparable GO-classes were significantly enriched in the upper and lower airways, e.g. response to virus, apoptotic process, antigen processing and presentation of peptide antigen via MHC class I, and regulation of I-κB/

152 Chapter 4 Figure 1A.

1645 (14%) Healthy Allergic rhinitis Allergic rhinitis & asthma

4009 (35%) 200 (2%) 4309 (38%)

247 872 (8%) (2%) 163 (1%) figure 1A. Venn-diagram of genes up-Figure or down-regulated 1B. in the upper airways.

2333 (25%) Healthy Allergic rhinitis Allergic rhinitis & asthma

1428 (15%) 884 (9%)

3697 (39%)

401 (4%) 477 (5%) 208 (2%)

figure 1B. Venn diagram of genes up- or down-regulated in the lower airways.

NF-κB. The majority of genes related to response to virus were induced in all groups in the same direction (up- or down-regulated) (see Table S3A and S3B of the Supporting Information File). Among the genes assigned to this GO-class were those involved in TLR3-signaling (TLR3, TICAM, TBK1, MYD88, IRAK3), interferons (IFNB1, IFNE, IFNK), various interferon receptors and interferon-induced proteins, cytokines (IL12A, IL23A, IL6) and particular cytokines related to type III interferons (IL28A, IL28B IL29), chemokines (CCL22, CCL4, CCL5), and transcription factors (IRF3, IRF7, IRF9, RELA, FOSL1). There were between-group diff erences in genes related to GO-class response to virus. Among the genes that were induced in all subjects except for patients with asthma were

dsRNA-induced Gene Expression of Airway Epithelium 153 Table 2A. Most highly up-regulated genes in the upper airways Healthy Allergic rhinitis Asthma Gene ID FC adj.P.Val FC adj.P.Val FC adj.P.Val CCL5 517.58 2.27E-06 717.90 1.11E-06 148.81 2.63E-02 RSAD2 260.58 6.48E-06 638.34 9.05E-07 98.63 2.63E-02 CMPK2 151.01 5.93E-05 469.49 4.62E-08 81.61 2.63E-02 OASL 256.41 1.48E-06 442.40 9.31E-08 93.45 2.63E-02 CCL3 277.19 3.04E-06 334.76 2.77E-06 45.69 2.78E-02 C4orf7 249.61 3.42E-07 319.09 3.92E-06 31.69 3.62E-02 MX2 115.45 3.43E-05 287.26 8.56E-08 72.32 2.63E-02 CCL4 255.13 2.38E-06 243.83 6.17E-06 39.32 2.82E-02 IFI44L 89.69 1.32E-04 240.00 5.17E-07 58.14 2.82E-02 APOBEC3A 224.06 6.80E-08 235.49 9.36E-07 40.77 2.81E-02 CXCL11 104.60 3.78E-06 189.03 2.90E-06 70.87 2.63E-02 CXCL10 74.79 3.67E-05 175.30 1.38E-06 72.35 2.63E-02 DEFB4A 169.21 2.86E-07 165.40 4.47E-06 51.52 3.06E-02 ESM1 109.38 7.55E-07 166.63 2.77E-06 34.37 2.78E-02 IFI44 64.88 1.56E-04 164.77 2.77E-06 42.51 3.06E-02 OAS1 73.40 3.58E-05 160.01 9.36E-07 38.28 2.79E-02 IFIT1 57.77 4.51E-04 150.43 2.08E-05 40.36 2.81E-02 IFIT3 84.45 2.91E-05 149.76 2.16E-06 41.00 2.63E-02 LAMP3 88.39 1.71E-05 137.82 5.31E-06 29.48 2.75E-02 TNFAIP6 137.00 4.06E-07 102.91 3.25E-05 27.28 3.28E-02 FC, fold change; adj.P.Val, p-value adjusted for multiple testing

interferon involved genes (IL28B, IFNAR1), CCL22, and FOSL1 with respect to the upper airways, and several interferon involved genes (IRF3, IFNAR1, IFNB1, IFNGR1, IL28B) in the lower airways. The upper airways of patients with asthma with concomitant allergic rhinitis demonstrated significantly fewer poly(I:C)-induced genes. In total, 57% of the induced genes was altered exclusively in the upper airways of either healthy subjects or allergic rhinitis patients and not in the upper airways of patients with asthma. Among these genes many GO classes were significantly overrepresented, amongst which many genes were assigned to metabolic process, mitochondrion and electron transport chain. Up to 2000 genes were assigned to metabolic process of which 347 genes overlap with class mitochondrion (see Table S4 of the Supporting Information File). These mitochondrial genes were mostly down-regulated. The latter class overlaps with genes assigned to the class electron transport chain, including several NADH dehydrogenase subcomplexes. With respect to genes induced in the lower airways, significantly enriched GO-glasses emerged among genes exclusively induced in the lower airways of healthy subjects,

154 Chapter 4 Table 2B. Most highly up-regulated genes in the lower airways Healthy Allergic rhinitis Asthma Gene ID FC adj.P.Val FC adj.P.Val FC adj.P.Val CCL5 736.54 6.09E-08 322.77 1.61E-05 231.87 9.60E-03 CMPK2 395.26 2.56E-08 360.62 6.91E-06 164.40 8.69E-03 RSAD2 363.02 1.47E-07 304.55 6.91E-06 167.47 9.76E-03 CXCL11 315.72 1.08E-07 109.20 1.58E-04 156.95 8.45E-03 IFIT1 307.08 9.93E-08 281.31 2.49E-05 161.84 1.05E-02 IFI44L 274.95 2.91E-08 211.91 1.08E-05 113.56 9.51E-03 CXCL10 263.55 2.97E-06 121.34 5.72E-04 88.92 1.09E-02 OASL 241.59 6.78E-08 138.85 5.11E-05 160.96 8.11E-03 IFI44 236.92 4.06E-09 70.93 1.67E-05 104.82 9.45E-03 MX2 201.46 2.56E-08 163.72 1.64E-05 96.81 8.67E-03 MX1 140.44 1.43E-07 175.11 1.67E-05 67.81 9.45E-03 IFI6 165.88 5.52E-10 123.34 1.24E-05 77.06 9.76E-03 DEFB4A 31.48 3.94E-04 137.90 2.06E-04 25.92 1.11E-02 LAMP3 131.90 2.15E-06 86.23 2.50E-04 50.68 1.39E-02 XAF1 110.43 6.45E-08 98.06 1.67E-05 61.68 7.99E-03 OAS1 109.84 1.13E-07 86.84 5.10E-05 47.06 1.05E-02 APOBEC3A 101.03 3.84E-07 86.19 8.06E-04 74.29 7.44E-03 IFIT3 94.85 9.47E-08 88.51 5.73E-05 56.72 8.56E-03 CCL4 83.19 2.22E-04 20.90 2.27E-02 35.57 1.25E-02 CCL3 69.05 7.38E-04 17.00 4.78E-02 35.62 1.27E-02 FC, fold change; adj.P.Val, p-value adjusted for multiple testing including metabolic process, nucleus and mitochondrion. Among these genes, 915 genes were assigned to the GO-class metabolic process, of which 616 genes match with class nucleus and 191 with class mitochondrion (see Table S5 of the Supporting Information File). Along with the upper airways, the GO-class mitochondrion was overrepresented among genes induced in the lower airways of both healthy controls and allergic rhinitis patients (see Table S6 of the Supporting Information File). In addition, these mitochondrial genes were primarily down-regulated.

Disease-specific gene expression induction We identified genes that were exclusively differentially expressed in patients with asthma and/or allergic rhinitis. We limited to genes that were up- or down-regulated by more than threefold (at least in one of the patient-groups) (see Table 3A & 3B). Among these genes were ciliary gene BBS1, nebulette (NEBL), nucleoside diphosphate kinase (NME7), the ubiquitous protein AHNAK, the calcium-binding S100A7A, myosin light chain kinase (MYLK), the cornulin gene (CRNN), filaggrin (FLG), complement factor B (CFB), bone morphogenetic protein 6 (BMP6), adaptor protein SH3KBP1, endoplasmatic

dsRNA-induced Gene Expression of Airway Epithelium 155 Table 3A. Disease-specific genes induced in the upper airways Gene ID FC rhinitis p-value rhinitis FC asthma p-value asthma Disease-specific LAMA3 10.87 <0.001 1.62 0.031 SH3KBP1 9.12 <0.001 5.13 0.027 NME7 6.44 <0.001 2.68 0.031 ERAP1 5.06 <0.001 3.76 0.026 MFI2 5 <0.001 3.39 0.042 UBASH3B 3.45 <0.001 2.4 0.042 NSD1 3.11 0.001 2.31 0.034 SLC23A2 -3.55 <0.001 -2.22 0.037 ARHGAP5 -3.57 <0.001 -2.12 0.039 ATP6V0A2 -3.79 <0.001 -2.57 0.03 Significant p-value in patients with allergic rhinitis ANKH -3.96 <0.001 -2.48 0.03 with or without asthma WWTR1 -4.03 <0.001 -2.41 0.048 NEBL -4.69 0.001 -3.75 0.039 MYO5A -4.76 <0.001 -2.67 0.033 LAMP2 -5.02 <0.001 -3.05 0.035 AHNAK -5.02 <0.001 -3.33 0.031 RAB22A -5.93 <0.001 -3.18 0.031 PPAT -6.37 <0.001 -2.72 0.044 TFRC -9.93 <0.001 -5.63 0.028 CCNB2 -15.44 <0.001 -5.37 0.04

IQCG 4.48 0.012 1.07 0.6 In patients with allergic BBS1 -3.23 <0.001 -1.05 0.8 rhinitis RBM8A -1.7 0.07 -3.01 0.039 In patients with allergic SSR1 -2.38 0.2 -3.74 0.044 rhinitis with asthma CLN8 -2.53 0.06 -5.34 0.028 FC, fold change; adj.P.Val, p-value adjusted for multiple testing

reticulum-associated aminopeptidase 1 (ERAP1), and lysosome-associated membrane protein 2 (LAMP2).

Discussion

This study shows the poly(I:C)-induced gene expression profiles of both upper and lower airway epithelium of patients with asthma, allergic rhinitis and healthy controls. The transcriptional response to poly(I:C) was characterized by a strong induction of genes. Among these genes were those involved in the response to virus, apoptotic processes and antigen presentation. Although the majority of genes involved in the

156 Chapter 4 Table 3B. Disease-specific genes induced in the lower airways Gene ID FC rhinitis p-value rhinitis FC asthma p-value asthma Disease-specific CFB 42.13 0.001 30.04 0.009 MB 8.95 0.005 2.73 0.017 MAMDC2 3.2 0.009 1.58 0.06 XRCC6BP1 -2.01 0.005 -3.06 0.01 Significant p-value in patients C4orf32 -3.06 0.027 -1.36 0.018 with allergic rhinitis with or MPPE1 -3.31 0.016 -3.83 0.026 without asthma NEBL -3.8 0.009 -3.35 0.012 GPC6 -5.11 0.001 -2.31 0.022 CYP1B1 -6.31 0.027 -2.39 0.027 CLN8 -6.39 0.001 -5 0.011 SHISA2 4.61 0.015 1.29 0.4 S100A7A 4.07 0.017 1.38 0.4 NPFFR2 3.7 0.043 1.26 0.2 RDH10 3.37 0.016 1.1 0.6 BMP6 3.36 0.015 1.11 0.6 RNF141 -3.04 0.005 1.08 0.3 In patients with allergic C12orf28 -3.08 0.037 -1.14 0.4 rhinitis LOC148189 -3.23 0.023 -1.13 0.4 CRNN -3.75 0.021 -1.07 0.9 PCK2 -4.16 0.024 -1.25 0.2 CTH -5.08 0.046 -1.23 0.4 FLG -5.17 0.004 -1.53 0.2 FANCD2 1.03 0.2 -3.03 0.014 In patients with allergic MYLK -1.03 0.5 -3.1 0.005 rhinitis with asthma SSR1 -1.16 0.4 -3.13 0.025 FC, fold change; adj.P.Val, p-value adjusted for multiple testing

response to poly(I:C) were similarly induced in upper and lower airways in all groups, we also observed differential expression, in particular with regard to impaired interferon expression in asthma. Furthermore, in contrast to healthy controls and rhinitis patients, the upper and lower airways of patients with asthma did not show poly(I:C)-induced down-regulation of mitochondrial genes. These findings are indicative of mitochondrial dysfunction in airway epithelium of patients with allergic asthma, and identify genes that may play a role in the altered viral response of diseased upper as well as lower airway epithelium. To our knowledge, this is the first study that extensively profiles gene expression by microarray of the combined upper and lower airways epithelium in response to dsRNA of healthy individuals and patients with allergic rhinitis with or without allergic asthma. In our earlier study we describe the differences in gene expression profiles at baseline levels (11). Interestingly, differential expression between the groups is mainly observed in both upper and lower airways, resulting in primarily comparable responses to dsRNA infection by the upper and lower airway epithelium within subjects. Furthermore, only small differences are observed between healthy controls and allergic rhinitis patients.

dsRNA-induced Gene Expression of Airway Epithelium 157 Apparently, a pre-existing inflammatory background in allergic rhinitis does not grossly affect the response to poly(I:C). This suggests that the inflammatory pathways as induced by allergens and rhinovirus are mostly diverse. Our finding of similar induction of genes involved in inflammatory responses in the airway epithelium in all three groups extends previous results. In a previous study examining the transcriptional response of RV-infected primary bronchial epithelial cells, pro-inflammatory pathways were similarly induced in asthma and controls(7). Our data show that this also holds for allergic rhinitis. Hence, according to these results, the majority of inflammatory genes in epithelial cells are induced by viruses in both the healthy and diseased states. However, this can not be extrapolated to COPD, in which bronchial epithelial cells demonstrated enhanced pro-inflammatory and antiviral reactions to RV as compared to healthy controls (21). Still, we also observed several interferon related genes that were induced in healthy controls and rhinitis patients, though not in asthma patients (especially the lower airways). Interferon-β1 (IFNB1) was significantly up-regulated in all cultures of all groups except for the lower airways of asthma patients. IL28B, known as interferon-λ3, was also significantly induced in both upper and lower airways of allergic rhinitis patients and controls, though not in asthma patients. This impaired induction in asthma was not due to high baseline gene expression prior to stimulation. IFN-βs and IFN-λs play a major role in the host defense against respiratory viral infections (8;22). These results confirm and extend previous studies on RV-infected primary bronchial epithelial cells, demonstrating reduced IFN-β (9) and IFN-λ (8) response in asthma, suggesting a higher susceptibility to viral infections and thereby to exacerbations. This may partly explain the high correlation between viral respiratory tract infections and asthma exacerbations (1). Nevertheless, when considering the most highly up-regulated genes, a considerable proportion of interferon-related genes appear to be induced in all groups. This fits in with very recent data in human bronchial smooth muscle cells, also showing production of IFNs by poly(I:C) (23). Notably, the upregulation of these interferon-related genes tends to be much less in patients with asthma, although a larger fold change difference of a gene might not necessarily be linked to larger impact on a protein pathway. The loss of mitochondrial and other metabolic gene down-regulation to dsRNA in asthma as compared to healthy controls and allergic rhinitis is in keeping with previously reported modifications in mitochondrial/metabolic function in A549 cells and animal models of allergic inflammation. These studies demonstrated that mitochondrial dysfunction exacerbates antigen-driven allergic airway inflammation by increased generation of reactive oxygen species (ROS), which induces oxidative stress in the lungs (24). Environmental factors such as allergens, ozone, and viruses increase ROS production thereby interactively promoting allergic inflammation (25;26). Second, since viral replication is dependent on host resources, down-regulation of mitochondrial function in a

158 Chapter 4 healthy state may prevent energy production to provide this replication. A recent review describes previous studies that have observed modulation of mitochondrial functions during different viral infections (27). That viral replication depends on mitochondrial biogenesis was previously observed during Human Cytomegalovirus infection (28). In- terestingly, this loss of down-regulated genes in our study was observed in both upper and lower airways of patients with asthma, suggesting changed host characteristics of the upper airways in patients with allergic rhinitis plus asthma as compared to those with allergic rhinitis alone. This implies at least an interaction between asthma and rhinitis in the response to respiratory viruses. Since we did not include asthma patients without allergic rhinitis we can only speculate about the role of the presence of allergic rhinitis in asthma. However, in our previous study we found a large impact of allergic rhinitis on the differences in epithelial gene expression between upper and lower airways, influencing the lower airways as well (11). Therefore, we assume that allergic rhinitis affects both upper and lower epithelial responses to viruses in patients with asthma. This would further explain mainly similar responses to dsRNA by both nasal and bronchial epithelium within subject-groups. Among the disease-specific genes that were induced in allergic rhinitis patients with or without asthma but not in healthy controls, there were genes (ERAP1, LAMP2) that have been shown to be involved in antigen presentation (29;30). Furthermore, several genes (SH3KBP1, CRNN, FLG, S100A7A) related to allergic inflammation (31-34) were either induced in allergic rhinitis patients with or without asthma (SH3KB1) or in allergic rhinitis patients only (CRNN, FLG, S100A7A). The genes BMP6, CFB and MYLK have previously been associated with airway inflammation and hyperresponsiveness (35-37). Of these genes, CFB was induced in all patients, whereas BMP6 solely in allergic rhinitis patients and MYLK in allergic rhinitis patients with asthma. The AHNAK gene, induced in allergic rhinitis patients with or without asthma, was previously associated with asthma susceptibility (38). Interestingly, there was also induction of ciliary genes (BBS1, NEBL, NME7) (39-41) of which NEBL and NME7 in allergic rhinitis patients with or without asthma while BBS1 exclusively in patients with allergic rhinitis. Mucociliary clearance is essential for the pulmonary defense (42), and ciliary dysfunction has been previously related to asthma severity (43). The strength of our study is that we have collected primary epithelial cells from both upper and lower airways from the same individuals in three different conditions (healthy, allergic rhinitis, allergic rhinitis and asthma). Furthermore, we were able to extensively analyse gene expression by using microarray, which was confirmed by PCR analysis. Nevertheless, the study has some limitations. Firstly, we included relatively few individuals per group. We carefully calculated this samples size by setting the false- discovery rate at approximately 5%. A larger sample size would have allowed capturing smaller differences in expression profile or greater differences in genes that display a

dsRNA-induced Gene Expression of Airway Epithelium 159 large variation in expression per individual. As a consequence we purposely focused on paired differences before and after poly(I:C) stimulation instead of comparing unpaired expression between the different subject groups. In addition to the original power calculation mentioned, the statistics used to measure differential expression applied the Benjamini and Hochberg adjustment of p-values for multiple testing. This correction uses a smaller significance level, inevitably reducing the power of the analysis. This will have led to false-negative results on poly(I:C)-induced genes, but it purposely limited the risk of false positive discovery. We did not use a real virus as a stimulus, but we used poly(I:C) instead. Although a real virus such as RV would have been preferable, in order to match the in vivo conditions, dsRNA is an adequate surrogate marker for RV. Toll-like receptor 3 (TLR3) is required for the sensing of RV produced dsRNA (10) and the TLR3 ligand poly(I:C) was found previously to be a very effective stimulus of airway epithelial cells (44;45). Since actual steroid exposure will change the expression of many genes, patients were prohibited steroid usage for 4 weeks before sampling. In fact, all allergic rhinitis patients were entirely steroid naïve and only one asthma patient used topical steroids and one asthma patient used inhaled steroids 4 weeks prior to recruitment. We cannot exclude carry-over effects of steroids even over this time span. Finally, culturing of cells will affect gene expression levels since conditions are no longer the same as in the airways. This seems to be inevitable. Alternative procedures to obtain epithelial cells such as laser capture or direct measurement after isolation might mitigate these effects of cell culturing, but will introduce new biases introduced by contamination by other cell types and/or the (enzymatic) isolation procedures themselves. However, as we compared epithelial cells from the same individuals, the standardized culturing of these cells should have affected nose and bronchial epithelial cells similarly. The currently observed disease-related differences in viral-induced gene expression of upper and lower airways between patients with allergic rhinitis and asthma and healthy controls may have clinical implications. First, these results help to understand the mechanistic pathways of the mutual interaction between asthma and rhinitis, for which there is considerable clinical evidence (46). Second, the current analysis identified several new genes whilst confirming other genes from previous findings. This may provide potential targets with respect to mitochondrial dysfunction and interferon involved genes for drug-discovery studies and for treatment of exacerbations in patients with combined upper and lower airway disease.

160 Chapter 4 Conclusions

In conclusion, we demonstrated that there are differences between rhinitis patients with and without asthma in the epithelial expression of dsRNA-induced genes, which are related to interferons and mitochondrial function. This appears to be manifested in both the upper and lower airways, suggesting mainly comparable responses to dsRNA infection in upper and lower airway epithelium within subjects. These data identify host-virus interactions in asthma, rhinitis and controls, which is required for developing targeted preventative and therapeutic interventions in asthma exacerbations.

dsRNA-induced Gene Expression of Airway Epithelium 161 References

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164 Chapter 4 CHAPTER 4 Supporting Information File dsRNA-induced changes in gene expression pro les of primary nasal and bronchial epithelial cells from patients with asthma, rhinitis and controls

Methods

Primary epithelial cell culture Epithelal cell cultures were done as previously described (1). Primary cells were obtained by first digesting the biopsies and brushes with collagenase 4 (Worthington Biochemi- cal Corp., Lakewood, NJ, USA) for 1 hour in Hanks’ balanced salt solution (Sigma-Aldrich, Zwijndrecht, The Netherlands). Subsequently cells were washed with Hanks’ balanced salt solution (HBSS) and resuspended in BEGM (Invitrogen, Breda, The Netherlands) and seeded in one well of a 6 wells plate. Cells were grown in fully humidified air containing

5% CO2 at 37°C, and culture medium was replaced every other day. Cells were cultured to 80% confluence and were pre-incubated with BEBM for 24 hours prior to exposure to BEBM containing 20µg/ml poly(I:C) or with BEBM alone (control condition) for 24 hours before removal of supernatant and RNA extraction. For bronchial epithelial cells it took 14 days on average, and for nasal epithelial cells it took 24 days on average to grow to 80% confluence. There was no difference in time of culture between the three subject groups.

Microarray Affymetrix U133+ MP Microarray analysis was done by previously published method [1]. Human Genome U133+ PM Genechip Array (Affymetrix inc., Santa Clara, CA, USA) representing more than 47,000 transcripts and variants, including over 33,000 well-characterized genes, was used in the analysis of the genes. The MicroArray Department (MAD) of the University of Amsterdam, a fully licensed microarray technologies centre for Affymetrix Genechip® platforms, performed the technical handling and the quality control of the microarray experiments. The quality of the images was checked by visual inspection and all raw data passed quality criteria based on borderplots, pseudocolor slide images, RNA degradation plots, box and density plots, RI plots (against a pseudoreference), correlation and PCA plots.

dsRNA-induced Gene Expression of Airway Epithelium 167 Real-time polymerase chain reaction and analysis Quantitative real-time PCR was used to validate the differential expression of selected genes. A random selection of 9 genes was used that showed a variance of responses to Poly(I:C). PCR was performed on Bio-Rad CFX96 real-time PCR detection system (Bio-Rad, Veenendaal, The Netherlands). SYBR® Green primer sequences for IL13-Rα2, EREG, PDE4D, IL1-β, IP-10, TIMP2, IL8, β –actin and GAPDH were obtained from Sigma- Aldrich (Sigma-Aldrich, Zwijndrecht, The Netherlands). The following primers were used: IL13-Rα2; sense: TGC-TCA-GAT-GAC-GGA-ATT-TGG, antisense: TGG-TAG-CCA-GAA- ACG-TAG-CAA-AG, EREG; sense: ATC-CTG-GCA-TGT-GCT-AGG-GT, antisense: GTG-CTC- CAG-AGG-TCA-GCC-AT, PDE4D; sense: GGC-CTC-CAA-CAA-GTT-TAA-AA, antisense: ACC- AGA-CAA-CTC-TGC-TAT-TCT, IL1-β; sense: GGA-TAT-GGA-GCA-ACA-AGT-GG, antisense: ATG-TAC-CAG-TTG-GGG-AAC-TG, IP-10; sense: TGA-AAT-TAT-TCC-TGC-AAG-CCA-AT, antisense: CAG-ACA-TCT-CTT-CTC-ACC-CTT-CTT-T, TIMP2; sense: ATA-AGC-AGG-CCT- CCA-ACG-C, antisense: GAG-CTG-GAC-CAG-TCG-AAA-CC, IL8; sense: CCA-CAC-TGC-GCC- AAC-ACA-GAA-ATT-ATT-G, antisense: GCC-CTC-TTC-AAA-AAC-TTC-TCC-ACA-ACC-C, β –actin; sense: TGA-GCG-CGG-CTA-CAG-CTT, antisense: TCC-TTA-ATG-TCA-CGC-ACG-ATT- T, GAPDH; sense: GAA-GGT-GAA-GGT-CGG-AGT-C, antisense: GAA-GAT-GGT-GAT-GGG- ATT-TC. For ATF3 and DUSP1 we used TaqMan® gene expression assays from Applied Biosystems (Nieuwerkerk a/d IJssel, The Netherlands) with the following assay IDs: ATF3; HS00231069_M1, DUSP1; HS006102757_G1. Correlations between fold changes (FC) within the microarray data and the real-time PCR data were determined using Pearson’s correlation.

Results

Validation of microarray data The results of this microarray experiment were validated by independent real time PCR on the same starting material used for the microarray analysis. We first determined the expression of the housekeeping genes (ACTB and GAPDH) which were not statistically significantly induced by poly(I:C). Table S1 shows the fold changes (FC) calculated from the microarray data and the real-time PCR-derived expression. Statistical analysis revealed a high level of correspondence (R=0.929, P<0.0001) between the microarray data and the real-time PCR (Figure S1). FCs were logtranformed because of such large variances.

168 Chapter 4 Table S1. Validatory PCR of housekeeping genes and significantly different genes Bronchial epithelial cells Healthy Allergic rhinitis Allergic rhinitis & asthma PCR FC Microarray FC PCR FC Microarray FC PCR FC Microarray FC ACTB 1.16 -1.03 1.52 1.04 1.38 -1.11 GAPDH -1.83 -1.00 -1.82 -1.03 -1.49 -1.03 ATF3 1.43 2.37 -1.78 1.21 -2.10 1.51 CXCL10 568.10 263.55 214.38 121.34 170.31 88.92 DUSP1 5.78 6.71 4.01 2.35 4.96 4.16 EREG 1.37 2.07 -3.59 -1.83 -1.26 1.17 IL13RA2 10.59 14.62 7.32 8.66 7.41 13.44 IL1B 2.83 3.52 1.30 1.75 2.43 3.11 IL8 32.48 13.98 44.45 23.40 26.06 16.60 PDE4D -3.63 -1.33 -6.19 -1.15 -3.81 -1.33 TIMP2 1.50 2.67 1.29 2.39 1.52 2.56

Nasal epithelial cells Healthy Allergic rhinitis Allergic rhinitis & asthma PCR FC Microarray FC PCR FC Microarray FC PCR FC Microarray FC ACTB -1.43 -1.04 1.04 -1.05 -1.03 -1.06 GAPDH -1.92 -1.04 -2.45 -1.06 -1.77 -1.02 ATF3 9.61 5.02 4.35 3.97 1.69 2.75 CXCL10 465.72 74.79 587.32 175.30 161.27 72.35 DUSP1 11.45 17.60 7.48 15.22 5.98 7.17 EREG 3.90 3.13 1.67 3.24 1.03 1.35 IL13RA2 22.16 12.13 17.20 14.39 6.15 5.83 IL1B 5.25 3.33 3.02 4.04 4.14 3.75 IL8 178.73 73.41 122.11 64.77 63.85 23.72 PDE4D -1.09 -1.03 -7.87 -1.29 -1.86 -1.04 TIMP2 3.02 4.25 1.77 5.73 1.31 2.97 PCR expression is given as fold change (FC).

Table S2. dsRNA-induced genes in upper and lower airways Healthy Healthy Rhinitis Rhinitis Asthma Asthma Nose Bronchus Nose Bronchus Nose Bronchus Probesets 17402 13424 15538 7517 6996 8560 P<0.05 Probesets 1255 550 1439 517 517 427 P<0.05 &FC>4 Genes ↑4636 ↑3638 ↑4204 ↑2294 ↑2293 ↑2621 10163 8342 9353 5190 4919 5810 P<0.05 ↓5527 ↓4704 ↓5149 ↓2896 ↓2626 ↓3189 Genes ↑528 ↑274 ↑586 ↑244 ↑275 ↑227 894 401 1037 391 383 319 P<0.05 & FC>4 ↓366 ↓127 ↓451 ↓147 ↓108 ↓92 FC, fold change; P, p-value adjusted for multiple testing

dsRNA-induced Gene Expression of Airway Epithelium 169 Table S3A. Genes assigned to GO-cluster response to virus induced in the upper airways Gene symbol Venn diagram FC Healthy FC Rhinitis FC Asthma C7orf25 /// PSMA2 A 1.30 CFL1 A -1.17 LILRB1 A 1.21 PIM2 A -1.32 POLR3F A -1.22 ACTA2 B -1.27 -1.34 BANF1 B -1.56 -1.59 BECN1 B -1.25 -1.25 BNIP3L B 1.53 1.76 CCL22 B 1.42 1.33 CREBZF B -1.57 -1.53 CYP1A1 B -2.60 -1.73 DNAJC3 B 1.95 1.81 EEF1G /// TUT1 B -1.77 -1.85 ENO1 B -1.33 -1.38 FOSL1 B 3.39 3.90 HBXIP B -1.23 -1.32 IFNAR1 B 1.53 1.39 IL12A B 2.64 2.96 IL28B B 4.53 7.30 LYST B 1.99 1.73 MAVS B -2.00 -1.69 POLR3A B 1.53 1.65 POLR3H B -2.61 -2.44 POLR3K B -2.95 -2.52 TBK1 B 1.83 1.49 ABCE1 C -3.91 -4.42 -2.48 ACE2 C 15.24 12.25 7.55 AP1S1 C -1.73 -1.63 -1.40 APOBEC3F C 2.78 2.80 2.29 APOBEC3G C 11.38 10.82 5.06 BCL2 C -1.24 -1.40 -1.46 BCL3 C 3.08 3.17 2.43 BNIP3 C 2.05 2.05 1.66 BST2 C 45.73 79.99 27.17 C19orf2 C -1.60 -1.90 -1.43 CCDC130 C 1.40 1.41 1.27 CCL4 C 255.13 243.83 39.32 CCL5 C 517.58 717.90 148.81 CCT5 C -3.44 -3.23 -2.21 DDX58 C 25.21 38.03 14.32 DUOX2 C 3.01 3.86 2.03 EIF2AK2 C 4.09 6.12 3.56 GPAM C -4.25 -4.77 -2.70 GTF2F1 C 1.31 1.55 1.33 HERC5 C 46.50 72.10 26.64

170 Chapter 4 Table S3A. (continued) Gene symbol Venn diagram FC Healthy FC Rhinitis FC Asthma HNRNPUL1 C -1.35 -1.37 -1.27 HSPB1 C -1.99 -2.25 -1.80 IFI16 C 1.70 1.59 1.74 IFI35 C 38.88 67.89 27.76 IFI44 C 64.88 164.77 42.51 IFIH1 C 18.03 22.18 10.42 IFITM1 C 8.15 10.90 6.25 IFITM2 C 2.92 2.99 2.45 IFITM3 C 2.27 2.25 1.93 IFNAR2 C 3.40 3.13 2.38 IFNB1 C 3.17 2.77 1.77 IFNE C -1.88 -2.68 -2.45 IFNGR1 C 1.82 1.48 1.68 IFNGR2 C 2.45 2.36 1.99 IFNK C 3.23 4.05 3.67 IL23A C 20.52 24.06 6.43 IL28A C 13.29 15.78 4.49 IL29 C 25.01 20.48 7.40 IL6 C 20.34 11.13 10.02 IRF3 C 1.57 1.56 1.40 IRF7 C 28.26 40.73 16.88 IRF9 C 2.87 3.41 2.94 ISG15 C 23.50 46.89 15.63 ISG20 C 32.65 41.94 14.82 ITCH C 2.67 3.02 2.43 IVNS1ABP C -5.44 -6.14 -2.57 MST1R C 2.95 3.39 2.04 MX1 C 30.17 92.06 21.00 MX2 C 115.45 287.26 72.32 MYD88 C 2.60 2.98 2.37 NLRC5 C 38.61 38.77 12.56 ODC1 C -2.23 -1.78 -2.04 PCBP2 C -1.49 -1.56 -1.38 PLSCR1 C 6.38 8.28 5.22 POLR3B C -1.44 -1.63 -1.45 POLR3C C 1.42 1.30 1.27 POLR3D C 1.70 1.91 1.55 POLR3E C -2.14 -2.32 -1.67 POLR3G C -1.87 -2.15 -1.36 PRKRA C -1.90 -2.11 -1.61 PVR C 1.93 1.81 1.54 RELA C 2.38 2.45 1.98 RPS15A C -8.15 -9.98 -4.19 RSAD2 C 260.58 638.34 98.63 SAMHD1 C 16.36 31.76 12.09 SIVA1 C -2.16 -2.48 -1.57

dsRNA-induced Gene Expression of Airway Epithelium 171 Table S3A. (continued) Gene symbol Venn diagram FC Healthy FC Rhinitis FC Asthma STAT1 C 13.66 17.43 10.47 STAT2 C 3.50 4.78 3.40 STMN1 C -5.68 -4.89 -2.96 TICAM1 C 3.14 3.12 2.38 TLR3 C 11.82 10.00 6.68 TNF C 8.16 6.72 4.38 TRIM11 C 1.73 1.78 1.59 TRIM22 C 4.90 5.16 4.61 TRIM25 C 6.43 8.67 4.13 TRIM5 C 3.81 3.90 2.94 UNC13D C 1.60 1.76 1.53 UNC93B1 C 2.40 3.27 2.33 XPO1 C -1.51 -1.63 -1.41 XPR1 C -1.76 -2.49 -1.23 ZC3HAV1 C 16.13 18.83 9.78 ZNF175 C 1.67 1.80 1.32 ABCC9 E 1.23 CLU E -1.26 DMBT1 E 1.44 MICA /// MICB E 1.21 PSMA2 E -1.27 PTPRC E 1.24 IRAK3 F -1.82 1.38 CDK6 G -1.41 Venn diagram: A, healthy specific; B, overlap healthy–rhinitis; C, overlap all groups; D, overlap healthy– asthma; E, rhinitis specific; F, overlap rhinitis–asthma; G, asthma specific; FC, fold change.

172 Chapter 4 Table S3B. Genes assigned to GO-cluster response to virus induced in the lower airways Gene symbol Venn diagram FC Healthy FC Rhinitis FC Asthma BANF1 A -1.36 BECN1 A -1.23 BNIP3L A 1.30 CXCL12 A -1.20 ENO1 A -1.21 IRF3 A 1.31 MAVS A -1.47 MST1R A 1.37 POLR3D A 1.40 POLR3G A -1.62 PSMA2 A -1.30 RNASEL A -1.35 SIVA1 A -1.73 XPR1 A -1.45 BNIP3 B 1.55 1.69 IFNAR1 B 1.23 1.42 IFNB1 B 1.60 1.47 IFNGR1 B 1.64 1.50 IL28B B 2.40 2.16 LYST B 1.73 1.68 POLR3E B -1.62 -1.93 POLR3K B -2.11 -2.00 ZNF175 B 1.54 1.88 ABCE1 C -2.06 -2.49 -1.89 APOBEC3F C 1.90 1.76 2.11 APOBEC3G C 6.62 5.28 8.11 BCL3 C 2.44 2.45 1.98 BST2 C 24.79 48.02 13.00 C19orf2 C -1.42 -1.56 -1.43 CCL4 C 83.19 20.90 35.57 CCL5 C 736.54 322.77 231.87 CCT5 C -2.10 -1.80 -1.85 CDK6 C -1.46 -1.30 -1.52 CREBZF C -1.29 -1.36 -1.38 CYP1A1 C -1.91 -2.85 -2.10 DDX58 C 28.49 23.14 18.03 DNAJC3 C 1.48 1.36 1.40 DUOX2 C 9.56 4.80 7.87 EEF1G /// TUT1 C -1.53 -1.57 -1.38 EIF2AK2 C 4.63 5.40 3.60 GPAM C -2.90 -2.26 -2.44 HERC5 C 35.87 25.29 27.95 HNRNPUL1 C -1.26 -1.27 -1.25 HSPB1 C -1.53 -1.74 -1.61 IFI35 C 48.10 39.73 31.80 IFI44 C 236.92 70.93 104.82 IFIH1 C 18.21 6.27 12.76 IFITM1 C 14.95 10.61 11.08 IFITM2 C 3.33 3.65 3.48 IFITM3 C 2.97 3.53 2.73 IFNAR2 C 2.43 2.54 2.36 IFNGR2 C 2.25 1.87 2.01 IL23A C 9.34 12.37 7.90

dsRNA-induced Gene Expression of Airway Epithelium 173 Table S3B. (continued) Gene symbol Venn diagram FC Healthy FC Rhinitis FC Asthma IL28A C 4.21 4.48 4.99 IL29 C 6.80 3.95 4.96 IL6 C 8.80 4.92 7.60 IRF7 C 26.30 19.88 20.32 IRF9 C 4.44 3.44 3.67 ISG15 C 49.88 64.58 32.63 ISG20 C 10.51 7.46 8.46 ITCH C 1.93 1.75 1.86 IVNS1ABP C -2.43 -2.16 -2.07 MX1 C 140.44 175.11 67.81 MX2 C 201.46 163.72 96.81 MYD88 C 2.17 2.32 2.19 NLRC5 C 17.88 12.59 11.61 ODC1 C -2.02 -2.87 -2.11 PCBP2 C -1.29 -1.29 -1.31 PLSCR1 C 7.77 7.54 5.70 POLR3A C 1.49 1.61 1.29 PRKRA C -1.59 -1.41 -1.57 RELA C 1.91 1.62 1.69 RPS15A C -4.45 -4.65 -3.17 RSAD2 C 363.02 304.55 167.47 SAMHD1 C 17.56 3.38 13.59 STAT1 C 16.34 6.17 11.13 STAT2 C 3.40 2.97 2.59 TBK1 C 1.44 1.42 1.30 TICAM1 C 2.30 2.15 2.31 TLR3 C 6.70 3.71 5.54 TNF C 4.81 3.95 4.35 TRIM22 C 6.91 9.76 4.63 TRIM25 C 3.96 3.13 3.72 TRIM5 C 2.60 2.55 2.51 UNC13D C 1.50 1.43 1.45 UNC93B1 C 2.52 1.82 2.21 ZC3HAV1 C 12.00 15.83 8.50 ACE2 D 6.49 5.12 ACTA2 D -1.36 -1.38 AP1S1 D -1.46 -1.34 BCL2 D -1.43 -1.42 CCDC130 D 1.26 1.23 FOSL1 D 2.40 1.89 GTF2F1 D 1.25 1.29 IFI16 D 1.50 1.62 IRAK3 D 1.40 1.56 NLRP3 D 1.77 1.46 POLR3H D -1.74 -1.45 PVR D 1.65 1.60 STMN1 D -2.24 -1.93 TRIM11 D 1.59 1.54 XPO1 D -1.25 -1.31 IFNE E -2.22 CLU G -1.35 Venn diagram: A, healthy specific; B, overlap healthy–rhinitis; C, overlap all groups; D, overlap healthy– asthma; E, rhinitis specific; F, overlap rhinitis–asthma; G, asthma specific; FC, fold change.

174 Chapter 4 Table S4. Genes induced in the upper airways of healthy controls and allergic rhinitis patients, assigned to GO cluster Mitochondrion Gene alias Gene name/description AARS2 alanyl-tRNA synthetase 2, mitochondrial (putative) ABCA12 ATP-binding cassette, sub-family A (ABC1), member 12 ABCF2 ATP-binding cassette, sub-family F (GCN20), member 2 ACACB acetyl-CoA carboxylase beta ACAD8 acyl-CoA dehydrogenase family, member 8 ACAD9 acyl-CoA dehydrogenase family, member 9 ACADM acyl-CoA dehydrogenase, C-4 to C-12 straight chain ACADVL acyl-CoA dehydrogenase, very long chain ACN9 ACN9 homolog (S. cerevisiae) ACO2 aconitase 2, mitochondrial ACOT13 acyl-CoA thioesterase 13 ACP6 acid phosphatase 6, lysophosphatidic ACSF2 acyl-CoA synthetase family member 2 ACSL1 acyl-CoA synthetase long-chain family member 1 ACSS1 acyl-CoA synthetase short-chain family member 1 ADCK4 aarF domain containing kinase 4 ADH5 alcohol dehydrogenase 5 (class III), chi polypeptide ADO 2-aminoethanethiol (cysteamine) dioxygenase AIFM1 apoptosis-inducing factor, mitochondrion-associated, 1 AK2 adenylate kinase 2 AK3 adenylate kinase 3 AKAP10 A kinase (PRKA) anchor protein 10 AKT2 v-akt murine thymoma viral oncogene homolog 2 ALDH1B1 aldehyde dehydrogenase 1 family, member B1 ALDH1L1 aldehyde dehydrogenase 1 family, member L1 ALDH1L2 aldehyde dehydrogenase 1 family, member L2 ALDH2 aldehyde dehydrogenase 2 family (mitochondrial) ALDH5A1 aldehyde dehydrogenase 5 family, member A1 ALKBH1 alkB, alkylation repair homolog 1 (E. coli) ALKBH7 alkB, alkylation repair homolog 7 (E. coli) AP2M1 adaptor-related protein complex 2, mu 1 subunit APOA1BP apolipoprotein A-I binding protein ARG2 arginase, type II ARMC10 armadillo repeat containing 10 ATIC 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/IMP cyclohydrolase ATP5B ATP synthase, H+ transporting, mitochondrial F1 complex, beta polypeptide ATP5C1 ATP synthase, H+ transporting, mitochondrial F1 complex, gamma polypeptide 1 ATP5D ATP synthase, H+ transporting, mitochondrial F1 complex, delta subunit ATP5G1 ATP synthase, H+ transporting, mitochondrial F0 complex, subunit C1 (subunit 9) ATP5G2 ATP synthase, H+ transporting, mitochondrial F0 complex, subunit C2 (subunit 9) ATP5G3 ATP synthase, H+ transporting, mitochondrial F0 complex, subunit C3 (subunit 9) ATP5H ATP synthase, H+ transporting, mitochondrial F0 complex, subunit d ATP5I ATP synthase, H+ transporting, mitochondrial F0 complex, subunit E ATP5J ATP synthase, H+ transporting, mitochondrial F0 complex, subunit F6

dsRNA-induced Gene Expression of Airway Epithelium 175 Table S4. (continued) Gene alias Gene name/description ATP5J2 ATP synthase, H+ transporting, mitochondrial F0 complex, subunit F2 ATP5L ATP synthase, H+ transporting, mitochondrial F0 complex, subunit G ATP5S ATP synthase, H+ transporting, mitochondrial F0 complex, subunit s (factor B) ATP5SL ATP5S-like ATPAF1 ATP synthase mitochondrial F1 complex assembly factor 1 BAX BCL2-associated X protein BBOX1 butyrobetaine (gamma), 2-oxoglutarate dioxygenase (gamma-butyrobetaine hydroxylase) 1 BCL2L1 BCL2-like 1 BCS1L BCS1-like (yeast) BDH2 3-hydroxybutyrate dehydrogenase, type 2 BNIP3L BCL2/adenovirus E1B 19kDa interacting protein 3-like BOLA1 bolA homolog 1 (E. coli) BPHL biphenyl hydrolase-like (serine hydrolase) BRP44 brain protein 44 C10orf2 chromosome 10 open reading frame 2 C10orf58 chromosome 10 open reading frame 58 C12orf10 chromosome 12 open reading frame 10 C12orf62 chromosome 12 open reading frame 62 C14orf156 chromosome 14 open reading frame 156 C14orf159 chromosome 14 open reading frame 159 C15orf62 chromosome 15 open reading frame 62 C17orf61 chromosome 17 open reading frame 61 C17orf90 chromosome 17 open reading frame 90 C18orf19 chromosome 18 open reading frame 19 C19orf70 chromosome 19 open reading frame 70 C1orf151 chromosome 1 open reading frame 151 C20orf24 chromosome 20 open reading frame 24 C21orf33 chromosome 21 open reading frame 33 C2orf47 chromosome 2 open reading frame 47 C2orf64 chromosome 2 open reading frame 64 C3orf1 chromosome 3 open reading frame 1 C3orf31 Chromosome 3 open reading frame 31 C4orf46 /// TOMM7 chromosome 4 open reading frame 46 /// translocase of outer mitochondrial membrane 7 homolog (yeast) C5orf54 chromosome 5 open reading frame 54 C6orf57 chromosome 6 open reading frame 57 C7orf55 chromosome 7 open reading frame 55 C7orf55 /// LUC7L2 chromosome 7 open reading frame 55 /// LUC7-like 2 (S. cerevisiae) C9orf46 chromosome 9 open reading frame 46 CA5B carbonic anhydrase VB, mitochondrial CA5BP Carbonic anhydrase VB pseudogene CAV1 caveolin 1, caveolae protein, 22kDa CBARA1 calcium binding atopy-related autoantigen 1 CCBL2 cysteine conjugate-beta lyase 2 CCDC123 coiled-coil domain containing 123

176 Chapter 4 Table S4. (continued) Gene alias Gene name/description CCDC58 coiled-coil domain containing 58 CCT7 chaperonin containing TCP1, subunit 7 (eta) CDS2 /// LOC149832 CDP-diacylglycerol synthase (phosphatidate cytidylyltransferase) 2 CECR5 cat eye syndrome chromosome region, candidate 5 CHCHD1 coiled-coil-helix-coiled-coil-helix domain containing 1 CHCHD2 coiled-coil-helix-coiled-coil-helix domain containing 2 CHCHD7 coiled-coil-helix-coiled-coil-helix domain containing 7 CISD2 CDGSH iron sulfur domain 2 CISD3 CDGSH iron sulfur domain 3 CKMT1A /// CKMT1B creatine kinase, mitochondrial 1A /// creatine kinase, mitochondrial 1B CLN3 ceroid-lipofuscinosis, neuronal 3 COL4A3BP collagen, type IV, alpha 3 (Goodpasture antigen) binding protein COMTD1 catechol-O-methyltransferase domain containing 1 COQ10A coenzyme Q10 homolog A (S. cerevisiae) COQ3 coenzyme Q3 homolog, methyltransferase (S. cerevisiae) COQ5 coenzyme Q5 homolog, methyltransferase (S. cerevisiae) COQ6 coenzyme Q6 homolog, monooxygenase (S. cerevisiae) COQ9 coenzyme Q9 homolog (S. cerevisiae) COX10 COX10 homolog, cytochrome c oxidase assembly protein, heme A: farnesyltransferase (yeast) COX15 COX15 homolog, cytochrome c oxidase assembly protein (yeast) COX4I1 cytochrome c oxidase subunit IV isoform 1 COX4NB COX4 neighbor COX5B cytochrome c oxidase subunit Vb COX6B1 cytochrome c oxidase subunit VIb polypeptide 1 (ubiquitous) COX6C cytochrome c oxidase subunit VIc COX7A2L cytochrome c oxidase subunit VIIa polypeptide 2 like COX7B cytochrome c oxidase subunit VIIb COX7C cytochrome c oxidase subunit VIIc CPOX coproporphyrinogen oxidase CPS1 carbamoyl-phosphate synthase 1, mitochondrial CPT2 carnitine palmitoyltransferase 2 CRAT carnitine O-acetyltransferase CS citrate synthase CYB5B cytochrome b5 type B (outer mitochondrial membrane) CYC1 cytochrome c-1 CYP1A1 cytochrome P450, family 1, subfamily A, polypeptide 1 CYP24A1 cytochrome P450, family 24, subfamily A, polypeptide 1 DAB1 /// OMA1 disabled homolog 1 (Drosophila) /// OMA1 homolog, zinc metallopeptidase (S. cerevisiae) DARS2 aspartyl-tRNA synthetase 2, mitochondrial DBI diazepam binding inhibitor (GABA receptor modulator, acyl-CoA binding protein) DECR1 2,4-dienoyl CoA reductase 1, mitochondrial DHODH dihydroorotate dehydrogenase DHRS4 /// DHRS4L2 dehydrogenase/reductase (SDR family) member 4 /// dehydrogenase/reductase (SDR family) member 4 like 2

dsRNA-induced Gene Expression of Airway Epithelium 177 Table S4. (continued) Gene alias Gene name/description DLD dihydrolipoamide dehydrogenase DLST dihydrolipoamide S-succinyltransferase (E2 component of 2-oxo-glutarate complex) DNAJA3 DnaJ (Hsp40) homolog, subfamily A, member 3 DNAJC19 DnaJ (Hsp40) homolog, subfamily C, member 19 DNLZ DNL-type zinc finger DNM3 dynamin 3 DRG2 developmentally regulated GTP binding protein 2 DYNLL1 dynein, light chain, LC8-type 1 EARS2 glutamyl-tRNA synthetase 2, mitochondrial (putative) ECH1 enoyl CoA hydratase 1, peroxisomal EHHADH enoyl-CoA, hydratase/3-hydroxyacyl CoA dehydrogenase ELAC2 elaC homolog 2 (E. coli) ENDOG endonuclease G ENO1 enolase 1, (alpha) ETFA electron-transfer-flavoprotein, alpha polypeptide ETFB electron-transfer-flavoprotein, beta polypeptide FAHD1 fumarylacetoacetate hydrolase domain containing 1 FAM110B family with sequence similarity 110, member B FAM136A family with sequence similarity 136, member A FAM175A family with sequence similarity 175, member A FAM82B Family with sequence similarity 82, member B FANCG Fanconi anemia, complementation group G FARS2 Phenylalanyl-tRNA synthetase 2, mitochondrial FASTK Fas-activated serine/threonine kinase FDPS farnesyl diphosphate synthase (farnesyl pyrophosphate synthetase, dimethylallyltranstransferase, geranyltranstransferase) FDX1 ferredoxin 1 FECH ferrochelatase FEZ1 fasciculation and elongation protein zeta 1 (zygin I) FIBP fibroblast growth factor (acidic) intracellular binding protein FIS1 fission 1 (mitochondrial outer membrane) homolog (S. cerevisiae) FUNDC2 FUN14 domain containing 2 FXC1 fracture callus 1 homolog (rat) FXN frataxin GABBR1 /// UBD gamma-aminobutyric acid (GABA) B receptor, 1 /// ubiquitin D GAD1 glutamate decarboxylase 1 (brain, 67kDa) GADD45GIP1 growth arrest and DNA-damage-inducible, gamma interacting protein 1 GAS8 growth arrest-specific 8 GBAS glioblastoma amplified sequence GCDH glutaryl-CoA dehydrogenase GHITM growth hormone inducible transmembrane protein GJA1 gap junction protein, alpha 1, 43kDa GK glycerol kinase GK /// GK3P glycerol kinase /// glycerol kinase 3 pseudogene GK3P glycerol kinase 3 pseudogene GLOD4 glyoxalase domain containing 4

178 Chapter 4 Table S4. (continued) Gene alias Gene name/description GLS2 glutaminase 2 (liver, mitochondrial) GLT8D1 Glycosyltransferase 8 domain containing 1 GLYCTK glycerate kinase GM2A GM2 ganglioside activator GNPAT glyceronephosphate O-acyltransferase GPX4 glutathione peroxidase 4 (phospholipid hydroperoxidase) GRAMD4 GRAM domain containing 4 GRN granulin GTF2H4 general transcription factor IIH, polypeptide 4, 52kDa GTPBP3 GTP binding protein 3 (mitochondrial) HCCS holocytochrome c synthase HDDC2 HD domain containing 2 HEBP1 heme binding protein 1 HEBP2 heme binding protein 2 HEMK1 HemK methyltransferase family member 1 HIBADH 3-hydroxyisobutyrate dehydrogenase HINT2 histidine triad nucleotide binding protein 2 HK1 hexokinase 1 HK2 hexokinase 2 HLCS holocarboxylase synthetase (biotin-(proprionyl-CoA-carboxylase (ATP-hydrolysing)) ligase) HRSP12 Heat-responsive protein 12 HSD17B10 hydroxysteroid (17-beta) dehydrogenase 10 HSD17B8 hydroxysteroid (17-beta) dehydrogenase 8 HSP90AB1 heat shock protein 90kDa alpha (cytosolic), class B member 1 HSPE1 heat shock 10kDa protein 1 (chaperonin 10) ICT1 immature colon carcinoma transcript 1 IDH1 Isocitrate dehydrogenase 1 (NADP+), soluble IDH2 isocitrate dehydrogenase 2 (NADP+), mitochondrial IDH3A isocitrate dehydrogenase 3 (NAD+) alpha IDH3B isocitrate dehydrogenase 3 (NAD+) beta IMMP2L IMP2 inner mitochondrial membrane peptidase-like (S. cerevisiae) ISCA1 iron-sulfur cluster assembly 1 homolog (S. cerevisiae) ISOC2 isochorismatase domain containing 2 KARS lysyl-tRNA synthetase KIAA0141 KIAA0141 KMO kynurenine 3-monooxygenase (kynurenine 3-hydroxylase) KRT5 keratin 5 L2HGDH L-2-hydroxyglutarate dehydrogenase LARS2 leucyl-tRNA synthetase 2, mitochondrial LETM1 leucine zipper-EF-hand containing transmembrane protein 1 LETMD1 LETM1 domain containing 1 LGALS3 Lectin, galactoside-binding, soluble, 3 LIMK2 LIM domain kinase 2 LIPT1 lipoyltransferase 1 LONP1 lon peptidase 1, mitochondrial

dsRNA-induced Gene Expression of Airway Epithelium 179 Table S4. (continued) Gene alias Gene name/description LRP5 Low density lipoprotein receptor-related protein 5 LYRM1 LYR motif containing 1 LYRM2 LYR motif containing 2 LYRM4 LYR motif containing 4 LYRM5 LYR motif containing 5 MARS2 methionyl-tRNA synthetase 2, mitochondrial MAT2B Methionine adenosyltransferase II, beta MAVS mitochondrial antiviral signaling protein MCAT malonyl CoA:ACP acyltransferase (mitochondrial) MCEE methylmalonyl CoA epimerase MCL1 myeloid cell leukemia sequence 1 (BCL2-related) ME3 malic enzyme 3, NADP(+)-dependent, mitochondrial MECR mitochondrial trans-2-enoyl-CoA reductase MFF mitochondrial fission factor MIPEP mitochondrial intermediate peptidase MLXIP MLX interacting protein MMACHC methylmalonic aciduria (cobalamin deficiency) cblC type, with homocystinuria MOSC1 MOCO sulphurase C-terminal domain containing 1 MPST mercaptopyruvate sulfurtransferase MPV17 MpV17 mitochondrial inner membrane protein MPV17L2 MPV17 mitochondrial membrane protein-like 2 MRPL1 mitochondrial ribosomal protein L1 MRPL11 mitochondrial ribosomal protein L11 MRPL12 Mitochondrial ribosomal protein L12 MRPL13 mitochondrial ribosomal protein L13 MRPL16 mitochondrial ribosomal protein L16 MRPL18 mitochondrial ribosomal protein L18 MRPL19 mitochondrial ribosomal protein L19 MRPL2 mitochondrial ribosomal protein L2 MRPL20 mitochondrial ribosomal protein L20 MRPL21 mitochondrial ribosomal protein L21 MRPL22 mitochondrial ribosomal protein L22 MRPL23 mitochondrial ribosomal protein L23 MRPL30 mitochondrial ribosomal protein L30 MRPL32 mitochondrial ribosomal protein L32 MRPL35 mitochondrial ribosomal protein L35 MRPL4 mitochondrial ribosomal protein L4 MRPL40 mitochondrial ribosomal protein L40 MRPL41 mitochondrial ribosomal protein L41 MRPL42 mitochondrial ribosomal protein L42 MRPL45 mitochondrial ribosomal protein L45 MRPL48 mitochondrial ribosomal protein L48 MRPL49 mitochondrial ribosomal protein L49 MRPL50 mitochondrial ribosomal protein L50 MRPL51 /// SPTLC1 mitochondrial ribosomal protein L51 /// serine palmitoyltransferase, long chain base subunit 1

180 Chapter 4 Table S4. (continued) Gene alias Gene name/description MRPL55 mitochondrial ribosomal protein L55 MRPL9 mitochondrial ribosomal protein L9 MRPS12 mitochondrial ribosomal protein S12 MRPS14 mitochondrial ribosomal protein S14 MRPS17 /// ZNF713 mitochondrial ribosomal protein S17 /// zinc finger protein 713 MRPS18A mitochondrial ribosomal protein S18A MRPS2 mitochondrial ribosomal protein S2 MRPS21 mitochondrial ribosomal protein S21 MRPS23 mitochondrial ribosomal protein S23 MRPS25 mitochondrial ribosomal protein S25 MRPS27 mitochondrial ribosomal protein S27 MRPS28 mitochondrial ribosomal protein S28 MRPS31 mitochondrial ribosomal protein S31 MRPS33 mitochondrial ribosomal protein S33 MRPS34 mitochondrial ribosomal protein S34 MRPS7 mitochondrial ribosomal protein S7 MRPS9 mitochondrial ribosomal protein S9 MSRB2 methionine sulfoxide reductase B2 MSTO1 misato homolog 1 (Drosophila) MTERFD1 MTERF domain containing 1 MTERFD3 MTERF domain containing 3 MTG1 mitochondrial GTPase 1 homolog (S. cerevisiae) MTHFD1L methylenetetrahydrofolate dehydrogenase (NADP+ dependent) 1-like MTIF2 mitochondrial translational initiation factor 2 MTOR mechanistic target of rapamycin (serine/threonine kinase) MTUS1 Microtubule associated tumor suppressor 1 MUT methylmalonyl CoA mutase MUTYH mutY homolog (E. coli) NCRNA00219 non-protein coding RNA 219 NDUFA1 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 1, 7.5kDa NDUFA10 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 10, 42kDa NDUFA11 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 11, 14.7kDa NDUFA12 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 12 NDUFA13 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 13 NDUFA2 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 2, 8kDa NDUFA3 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 3, 9kDa NDUFA4 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 4, 9kDa NDUFA6 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 6, 14kDa NDUFA7 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 7, 14.5kDa NDUFA8 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 8, 19kDa NDUFA9 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 9, 39kDa NDUFAB1 NADH dehydrogenase (ubiquinone) 1, alpha/beta subcomplex, 1, 8kDa NDUFAF2 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, assembly factor 2 NDUFB3 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 3, 12kDa NDUFB5 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 5, 16kDa NDUFB7 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 7, 18kDa

dsRNA-induced Gene Expression of Airway Epithelium 181 Table S4. (continued) Gene alias Gene name/description NDUFB8 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 8, 19kDa NDUFB9 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 9, 22kDa NDUFC2 NADH dehydrogenase (ubiquinone) 1, subcomplex unknown, 2, 14.5kDa NDUFS5 /// RPL10 NADH dehydrogenase (ubiquinone) Fe-S protein 5, (NADH-coenzyme Q reductase) /// ribosomal protein L10 NDUFS7 NADH dehydrogenase (ubiquinone) Fe-S protein 7, 20kDa (NADH-coenzyme Q reductase) NDUFV1 NADH dehydrogenase (ubiquinone) flavoprotein 1, 51kDa NDUFV3 NADH dehydrogenase (ubiquinone) flavoprotein 3, 10kDa NEFH neurofilament, heavy polypeptide NFS1 NFS1 nitrogen fixation 1 homolog (S. cerevisiae) NFU1 NFU1 iron-sulfur cluster scaffold homolog (S. cerevisiae) NIT2 nitrilase family, member 2 NLRX1 NLR family member X1 NOP14 NOP14 nucleolar protein homolog (yeast) NR3C1 nuclear receptor subfamily 3, group C, member 1 (glucocorticoid receptor) NRAS neuroblastoma RAS viral (v-ras) oncogene homolog NRD1 nardilysin (N-arginine dibasic convertase) NT5DC3 5'-nucleotidase domain containing 3 NUDT13 nudix (nucleoside diphosphate linked moiety X)-type motif 13 NUDT19 nudix (nucleoside diphosphate linked moiety X)-type motif 19 NUDT6 nudix (nucleoside diphosphate linked moiety X)-type motif 6 NUDT9 nudix (nucleoside diphosphate linked moiety X)-type motif 9 OAT ornithine aminotransferase OCIAD1 OCIA domain containing 1 OGDH oxoglutarate (alpha-ketoglutarate) dehydrogenase (lipoamide) OGG1 8-oxoguanine DNA glycosylase OMA1 OMA1 homolog, zinc metallopeptidase (S. cerevisiae) OXA1L oxidase (cytochrome c) assembly 1-like OXR1 oxidation resistance 1 OXSM 3-oxoacyl-ACP synthase, mitochondrial P4HA1 prolyl 4-hydroxylase, alpha polypeptide I PACS2 phosphofurin acidic cluster sorting protein 2 PARG poly (ADP-ribose) glycohydrolase PARK7 Parkinson disease (autosomal recessive, early onset) 7 PARL presenilin associated, rhomboid-like PARS2 prolyl-tRNA synthetase 2, mitochondrial (putative) PCCB propionyl CoA carboxylase, beta polypeptide PCK2 phosphoenolpyruvate carboxykinase 2 (mitochondrial) PDK1 pyruvate dehydrogenase kinase, isozyme 1 PDSS2 prenyl (decaprenyl) diphosphate synthase, subunit 2 PECI peroxisomal D3,D2-enoyl-CoA isomerase PEMT phosphatidylethanolamine N-methyltransferase PERP PERP, TP53 apoptosis effector PET112L PET112-like (yeast) PGAM5 phosphoglycerate mutase family member 5

182 Chapter 4 Table S4. (continued) Gene alias Gene name/description PHYH phytanoyl-CoA 2-hydroxylase PHYHIPL phytanoyl-CoA 2-hydroxylase interacting protein-like PICK1 protein interacting with PRKCA 1 PIGY phosphatidylinositol glycan anchor biosynthesis, class Y PINK1 PTEN induced putative kinase 1 PITRM1 pitrilysin metallopeptidase 1 PMPCA peptidase (mitochondrial processing) alpha PNKD paroxysmal nonkinesigenic dyskinesia POLDIP2 polymerase (DNA-directed), delta interacting protein 2 POLG polymerase (DNA directed), gamma POLG2 polymerase (DNA directed), gamma 2, accessory subunit POLRMT polymerase (RNA) mitochondrial (DNA directed) PON2 paraoxonase 2 PPIF peptidylprolyl isomerase F PPOX protoporphyrinogen oxidase PPP1CA protein phosphatase 1, catalytic subunit, alpha isozyme PPP2CA protein phosphatase 2, catalytic subunit, alpha isozyme PPP3CB protein phosphatase 3, catalytic subunit, beta isozyme PRDX1 peroxiredoxin 1 PRDX2 peroxiredoxin 2 PRDX5 peroxiredoxin 5 PRKACA protein kinase, cAMP-dependent, catalytic, alpha PTGR2 prostaglandin reductase 2 PTRF polymerase I and transcript release factor PTRH1 Peptidyl-tRNA hydrolase 1 homolog (S. cerevisiae) PTRH2 peptidyl-tRNA hydrolase 2 PTS 6-pyruvoyltetrahydropterin synthase PUS1 pseudouridylate synthase 1 PYCR1 pyrroline-5-carboxylate reductase 1 QTRT1 queuine tRNA-ribosyltransferase 1 QTRTD1 queuine tRNA-ribosyltransferase domain containing 1 RAF1 v-raf-1 murine leukemia viral oncogene homolog 1 RAI14 retinoic acid induced 14 RARS2 arginyl-tRNA synthetase 2, mitochondrial RBFA ribosome binding factor A RDBP RD RNA binding protein RDH13 Retinol dehydrogenase 13 (all-trans/9-cis) RG9MTD1 RNA (guanine-9-) methyltransferase domain containing 1 RNF5 ring finger protein 5 RPL9 ribosomal protein L9 RPP21 /// TRIM39 /// ribonuclease P/MRP 21kDa subunit /// tripartite motif-containing 39 /// TRIM39-like TRIM39R protein RPS6KB1 ribosomal protein S6 kinase, 70kDa, polypeptide 1 RPUSD4 RNA pseudouridylate synthase domain containing 4 SAMM50 sorting and assembly machinery component 50 homolog (S. cerevisiae) SARS Seryl-tRNA synthetase

dsRNA-induced Gene Expression of Airway Epithelium 183 Table S4. (continued) Gene alias Gene name/description SCCPDH saccharopine dehydrogenase (putative) SDHA succinate dehydrogenase complex, subunit A, flavoprotein (Fp) SDHA /// SDHAP1 /// succinate dehydrogenase complex, subunit A, flavoprotein (Fp) /// succinate SDHAP2 dehydrogenase complex, subunit A, flavoprotein pseudogene 1 /// succinate dehydrogenase complex, subunit A, flavoprotein pseudogene 2 SDHAF1 succinate dehydrogenase complex assembly factor 1 SDHC succinate dehydrogenase complex, subunit C, integral membrane protein, 15kDa SDHD succinate dehydrogenase complex, subunit D, integral membrane protein SFXN1 sideroflexin 1 SFXN2 sideroflexin 2 SHC1 SHC (Src homology 2 domain containing) transforming protein 1 SIRT5 sirtuin (silent mating type information regulation 2 homolog) 5 (S. cerevisiae) SLC1A3 solute carrier family 1 (glial high affinity glutamate transporter), member 3 SLC25A12 solute carrier family 25 (mitochondrial carrier, Aralar), member 12 SLC25A14 solute carrier family 25 (mitochondrial carrier, brain), member 14 SLC25A25 solute carrier family 25, member 25 SLC25A26 solute carrier family 25, member 26 SLC25A29 solute carrier family 25, member 29 SLC25A3 solute carrier family 25, member 3 SLC25A32 solute carrier family 25, member 32 SLC25A36 Solute carrier family 25, member 36 SLC25A38 solute carrier family 25, member 38 SLC25A39 solute carrier family 25, member 39 SLC25A44 solute carrier family 25, member 44 SLC25A6 solute carrier family 25, member 6 SLC27A3 solute carrier family 27 (fatty acid transporter), member 3 SLIT3 slit homolog 3 (Drosophila) SLMO2 slowmo homolog 2 (Drosophila) SNN stannin SOD1 superoxide dismutase 1, soluble STAR steroidogenic acute regulatory protein STOML2 stomatin (EPB72)-like 2 SUCLG1 succinate-CoA ligase, alpha subunit SURF1 surfeit 1 TATDN3 TatD DNase domain containing 3 TBC1D15 TBC1 domain family, member 15 TBRG4 transforming growth factor beta regulator 4 THG1L tRNA-histidine guanylyltransferase 1-like (S. cerevisiae) TIMM13 translocase of inner mitochondrial membrane 13 homolog (yeast) TIMM17A translocase of inner mitochondrial membrane 17 homolog A (yeast) TIMM22 Translocase of inner mitochondrial membrane 22 homolog (yeast) TIMM23 /// TIMM23B translocase of inner mitochondrial membrane 23 homolog (yeast) /// translocase of inner mitochondrial membrane 23 homolog B (yeast) TIMM8A translocase of inner mitochondrial membrane 8 homolog A (yeast) TMEM126A transmembrane protein 126A TMEM14B /// TMEM14C transmembrane protein 14B /// transmembrane protein 14C

184 Chapter 4 Table S4. (continued) Gene alias Gene name/description TMEM14C transmembrane protein 14C TMEM160 transmembrane protein 160 TMEM223 transmembrane protein 223 TMTC1 transmembrane and tetratricopeptide repeat containing 1 TOMM22 translocase of outer mitochondrial membrane 22 homolog (yeast) TOMM34 translocase of outer mitochondrial membrane 34 TOMM70A translocase of outer mitochondrial membrane 70 homolog A (S. cerevisiae) TP53 tumor protein p53 TRAP1 TNF receptor-associated protein 1 TRIT1 tRNA isopentenyltransferase 1 TRNT1 tRNA nucleotidyl transferase, CCA-adding, 1 TXNDC12 thioredoxin domain containing 12 (endoplasmic reticulum) TXNRD1 thioredoxin reductase 1 UQCC ubiquinol-cytochrome c reductase complex chaperone UQCR10 ubiquinol-cytochrome c reductase, complex III subunit X UQCR11 ubiquinol-cytochrome c reductase, complex III subunit XI UQCRB ubiquinol-cytochrome c reductase binding protein UQCRH ubiquinol-cytochrome c reductase hinge protein UQCRQ ubiquinol-cytochrome c reductase, complex III subunit VII, 9.5kDa USP30 ubiquitin specific peptidase 30 VARS2 valyl-tRNA synthetase 2, mitochondrial (putative) VHL von Hippel-Lindau tumor suppressor WARS2 tryptophanyl tRNA synthetase 2, mitochondrial WASF1 WAS protein family, member 1 YME1L1 YME1-like 1 (S. cerevisiae) YWHAE Tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, epsilon polypeptide YWHAZ tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, zeta polypeptide

dsRNA-induced Gene Expression of Airway Epithelium 185 Table S5. Genes induced in the lower airways of healthy controls, assigned to GO cluster Mitochondrion Gene alias Gene name/description ABCB6 ATP-binding cassette, sub-family B (MDR/TAP), member 6 ACADVL acyl-CoA dehydrogenase, very long chain ACP6 acid phosphatase 6, lysophosphatidic ADH5 alcohol dehydrogenase 5 (class III), chi polypeptide ADO 2-aminoethanethiol (cysteamine) dioxygenase AIFM1 apoptosis-inducing factor, mitochondrion-associated, 1 AK1 adenylate kinase 1 AKT2 v-akt murine thymoma viral oncogene homolog 2 ALDH18A1 aldehyde dehydrogenase 18 family, member A1 ALKBH7 AlkB, alkylation repair homolog 7 (E. coli) ARAF v-raf murine sarcoma 3611 viral oncogene homolog ARSB arylsulfatase B ASS1 argininosuccinate synthase 1 ATP5C1 ATP synthase, H+ transporting, mitochondrial F1 complex, gamma polypeptide 1 ATP5G3 ATP synthase, H+ transporting, mitochondrial F0 complex, subunit C3 (subunit 9) ATP5H ATP synthase, H+ transporting, mitochondrial F0 complex, subunit d ATP5I ATP synthase, H+ transporting, mitochondrial F0 complex, subunit E ATP5J2 ATP synthase, H+ transporting, mitochondrial F0 complex, subunit F2 ATP5SL ATP5S-like ATP6V1A ATPase, H+ transporting, lysosomal 70kDa, V1 subunit A AURKAIP1 aurora kinase A interacting protein 1 BCL2L10 BCL2-like 10 (apoptosis facilitator) BCL2L2 BCL2-like 2 BLOC1S1 biogenesis of lysosomal organelles complex-1, subunit 1 BNIP3L BCL2/adenovirus E1B 19kDa interacting protein 3-like C10orf58 chromosome 10 open reading frame 58 C12orf10 chromosome 12 open reading frame 10 C12orf62 chromosome 12 open reading frame 62 C14orf159 chromosome 14 open reading frame 159 C15orf62 chromosome 15 open reading frame 62 C17orf61 chromosome 17 open reading frame 61 C18orf19 chromosome 18 open reading frame 19 C1orf31 chromosome 1 open reading frame 31 C22orf32 chromosome 22 open reading frame 32 C2orf56 chromosome 2 open reading frame 56 C9orf46 chromosome 9 open reading frame 46 CA5B carbonic anhydrase VB, mitochondrial CCDC142 /// MRPL53 coiled-coil domain containing 142 /// mitochondrial ribosomal protein L53 CCDC58 coiled-coil domain containing 58 CDS2 /// LOC149832 CDP-diacylglycerol synthase (phosphatidate cytidylyltransferase) 2 CHAF1B chromatin assembly factor 1, subunit B (p60) CHCHD1 coiled-coil-helix-coiled-coil-helix domain containing 1 CHCHD2 coiled-coil-helix-coiled-coil-helix domain containing 2 CHCHD4 coiled-coil-helix-coiled-coil-helix domain containing 4 CIDEA cell death-inducing DFFA-like effector a CISD3 CDGSH iron sulfur domain 3

186 Chapter 4 Table S5. (continued) Gene alias Gene name/description CLPX ClpX caseinolytic peptidase X homolog (E. coli) CLTC Clathrin, heavy chain (Hc) COL4A3BP collagen, type IV, alpha 3 (Goodpasture antigen) binding protein COMTD1 catechol-O-methyltransferase domain containing 1 COQ5 coenzyme Q5 homolog, methyltransferase (S. cerevisiae) COQ9 coenzyme Q9 homolog (S. cerevisiae) COX10 homolog, cytochrome c oxidase assembly protein, heme A: COX10 farnesyltransferase (yeast) COX15 COX15 homolog, cytochrome c oxidase assembly protein (yeast) COX16 COX16 cytochrome c oxidase assembly homolog (S. cerevisiae) COX4NB COX4 neighbor COX5B Cytochrome c oxidase subunit Vb COX6B1 cytochrome c oxidase subunit VIb polypeptide 1 (ubiquitous) COX7C cytochrome c oxidase subunit VIIc CRAT carnitine O-acetyltransferase CROT carnitine O-octanoyltransferase CXorf23 chromosome X open reading frame 23 CYB5R1 cytochrome b5 reductase 1 CYB5R3 cytochrome b5 reductase 3 DDX28 DEAD (Asp-Glu-Ala-Asp) box polypeptide 28 DHODH dihydroorotate dehydrogenase DHX29 DEAH (Asp-Glu-Ala-His) box polypeptide 29 DHX30 DEAH (Asp-Glu-Ala-His) box polypeptide 30 DLST dihydrolipoamide S-succinyltransferase (E2 component of 2-oxo-glutarate complex) DNAJC15 DnaJ (Hsp40) homolog, subfamily C, member 15 DNAJC4 DnaJ (Hsp40) homolog, subfamily C, member 4 DPYSL2 dihydropyrimidinase-like 2 DRG2 developmentally regulated GTP binding protein 2 DYNLL1 dynein, light chain, LC8-type 1 EHHADH enoyl-CoA, hydratase/3-hydroxyacyl CoA dehydrogenase ELAC2 elaC homolog 2 (E. coli) ENDOG endonuclease G ENO1 enolase 1, (alpha) FAHD1 fumarylacetoacetate hydrolase domain containing 1 FASTK Fas-activated serine/threonine kinase FOXRED1 FAD-dependent oxidoreductase domain containing 1 FTSJ2 FtsJ homolog 2 (E. coli) FUNDC2 FUN14 domain containing 2 FXC1 fracture callus 1 homolog (rat) FXN frataxin GADD45GIP1 Growth arrest and DNA-damage-inducible, gamma interacting protein 1 GATC Glutamyl-tRNA(Gln) amidotransferase, subunit C homolog (bacterial) GATM Glycine amidinotransferase (L-arginine:glycine amidinotransferase) GHITM growth hormone inducible transmembrane protein GK /// GK3P glycerol kinase /// glycerol kinase 3 pseudogene GK3P glycerol kinase 3 pseudogene GLUL glutamate-ammonia ligase

dsRNA-induced Gene Expression of Airway Epithelium 187 Table S5. (continued) Gene alias Gene name/description GLYCTK glycerate kinase GNPAT glyceronephosphate O-acyltransferase GOT2 glutamic-oxaloacetic transaminase 2, mitochondrial (aspartate aminotransferase 2) GRN granulin GRPEL1 GrpE-like 1, mitochondrial (E. coli) GRPEL2 GrpE-like 2, mitochondrial (E. coli) GSTZ1 glutathione transferase zeta 1 GTF2H4 general transcription factor IIH, polypeptide 4, 52kDa GTPBP5 GTP binding protein 5 (putative) GTPBP8 GTP-binding protein 8 (putative) HEBP2 heme binding protein 2 HEMK1 HemK methyltransferase family member 1 HK2 hexokinase 2 HSCB HscB iron-sulfur cluster co-chaperone homolog (E. coli) HTRA2 HtrA serine peptidase 2 ICT1 immature colon carcinoma transcript 1 IDH1 Isocitrate dehydrogenase 1 (NADP+), soluble IDH3B isocitrate dehydrogenase 3 (NAD+) beta ISCA1 iron-sulfur cluster assembly 1 homolog (S. cerevisiae) ISCA2 iron-sulfur cluster assembly 2 homolog (S. cerevisiae) IVD isovaleryl-CoA dehydrogenase JMJD7 jumonji domain containing 7 KIAA0141 KIAA0141 KIF1B kinesin family member 1B KMO kynurenine 3-monooxygenase (kynurenine 3-hydroxylase) LARS2 leucyl-tRNA synthetase 2, mitochondrial LETM1 leucine zipper-EF-hand containing transmembrane protein 1 LETMD1 LETM1 domain containing 1 LGALS3 lectin, galactoside-binding, soluble, 3 LIMK2 LIM domain kinase 2 LOC100510009 /// Williams-Beuren syndrome chromosome region 16 WBSCR16 LYRM2 LYR motif containing 2 MAVS mitochondrial antiviral signaling protein MCAT malonyl CoA:ACP acyltransferase (mitochondrial) MCL1 myeloid cell leukemia sequence 1 (BCL2-related) MECR mitochondrial trans-2-enoyl-CoA reductase MMACHC methylmalonic aciduria (cobalamin deficiency) cblC type, with homocystinuria MRPL11 mitochondrial ribosomal protein L11 MRPL13 mitochondrial ribosomal protein L13 MRPL16 mitochondrial ribosomal protein L16 MRPL17 mitochondrial ribosomal protein L17 MRPL18 mitochondrial ribosomal protein L18 MRPL20 mitochondrial ribosomal protein L20 MRPL22 mitochondrial ribosomal protein L22 MRPL32 mitochondrial ribosomal protein L32 MRPL33 mitochondrial ribosomal protein L33

188 Chapter 4 Table S5. (continued) Gene alias Gene name/description MRPL36 mitochondrial ribosomal protein L36 MRPL4 mitochondrial ribosomal protein L4 MRPL41 mitochondrial ribosomal protein L41 MRPL43 mitochondrial ribosomal protein L43 MRPL45 mitochondrial ribosomal protein L45 MRPL50 mitochondrial ribosomal protein L50 MRPL55 Mitochondrial ribosomal protein L55 MRPL9 mitochondrial ribosomal protein L9 MRPS12 Mitochondrial ribosomal protein S12 MRPS14 mitochondrial ribosomal protein S14 MRPS15 mitochondrial ribosomal protein S15 MRPS17 /// ZNF713 mitochondrial ribosomal protein S17 /// zinc finger protein 713 MRPS2 mitochondrial ribosomal protein S2 MRPS24 mitochondrial ribosomal protein S24 MRPS26 mitochondrial ribosomal protein S26 MRPS28 mitochondrial ribosomal protein S28 MRPS9 mitochondrial ribosomal protein S9 MSTO1 /// MSTO2P misato homolog 1 (Drosophila) /// misato homolog 2 pseudogene MTFMT mitochondrial methionyl-tRNA formyltransferase MTG1 mitochondrial GTPase 1 homolog (S. cerevisiae) MTOR Mechanistic target of rapamycin (serine/threonine kinase) MUT methylmalonyl CoA mutase NAGS N-acetylglutamate synthase NDUFA1 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 1, 7.5kDa NDUFA11 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 11, 14.7kDa NDUFA12 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 12 NDUFA13 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 13 NDUFA3 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 3, 9kDa NDUFA4 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 4, 9kDa NDUFA8 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 8, 19kDa NDUFAB1 NADH dehydrogenase (ubiquinone) 1, alpha/beta subcomplex, 1, 8kDa NDUFB1 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 1, 7kDa NDUFB3 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 3, 12kDa NDUFB5 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 5, 16kDa NDUFB7 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 7, 18kDa NDUFB9 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 9, 22kDa NADH dehydrogenase (ubiquinone) Fe-S protein 5, 15kDa (NADH-coenzyme Q NDUFS5 /// RPL10 reductase) /// ribosomal protein L10 NADH dehydrogenase (ubiquinone) Fe-S protein 6, 13kDa (NADH-coenzyme Q NDUFS6 reductase) NFS1 NFS1 nitrogen fixation 1 homolog (S. cerevisiae) NLRX1 NLR family member X1 NR3C1 nuclear receptor subfamily 3, group C, member 1 (glucocorticoid receptor) NRAS neuroblastoma RAS viral (v-ras) oncogene homolog NRD1 nardilysin (N-arginine dibasic convertase) NT5C 5', 3'-nucleotidase, cytosolic OAT ornithine aminotransferase

dsRNA-induced Gene Expression of Airway Epithelium 189 Table S5. (continued) Gene alias Gene name/description OCIAD1 OCIA domain containing 1 OXSM 3-oxoacyl-ACP synthase, mitochondrial P4HA1 prolyl 4-hydroxylase, alpha polypeptide I PAM16 presequence translocase-associated motor 16 homolog PANK2 Pantothenate kinase 2 PARG poly (ADP-ribose) glycohydrolase PARL presenilin associated, rhomboid-like PARS2 prolyl-tRNA synthetase 2, mitochondrial (putative) PCCA Propionyl Coenzyme A carboxylase, alpha polypeptide PDK1 pyruvate dehydrogenase kinase, isozyme 1 PDSS2 prenyl (decaprenyl) diphosphate synthase, subunit 2 PECR peroxisomal trans-2-enoyl-CoA reductase PET112L PET112-like (yeast) PIN4 protein (peptidylprolyl cis/trans isomerase) NIMA-interacting, 4 (parvulin) PMPCA peptidase (mitochondrial processing) alpha POLDIP2 polymerase (DNA-directed), delta interacting protein 2 PPP1CA protein phosphatase 1, catalytic subunit, alpha isozyme PPP1CC protein phosphatase 1, catalytic subunit, gamma isozyme PPP3CA protein phosphatase 3, catalytic subunit, alpha isozyme PROSC Proline synthetase co-transcribed homolog (bacterial) PTRH1 peptidyl-tRNA hydrolase 1 homolog (S. cerevisiae) PTRH2 peptidyl-tRNA hydrolase 2 PUS1 pseudouridylate synthase 1 RAB11A RAB11A, member RAS oncogene family RAB3D RAB3D, member RAS oncogene family RAI14 retinoic acid induced 14 RARS2 arginyl-tRNA synthetase 2, mitochondrial RBFA ribosome binding factor A RDBP RD RNA binding protein RDH13 Retinol dehydrogenase 13 (all-trans/9-cis) RNASEL ribonuclease L (2',5'-oligoisoadenylate synthetase-dependent) RNF5 ring finger protein 5 RPP21 /// TRIM39 /// ribonuclease P/MRP 21kDa subunit /// tripartite motif-containing 39 /// TRIM39-like TRIM39R protein SACS spastic ataxia of Charlevoix-Saguenay (sacsin) SARDH Sarcosine dehydrogenase SARS2 seryl-tRNA synthetase 2, mitochondrial SEC61A1 Sec61 alpha 1 subunit (S. cerevisiae) SFXN5 sideroflexin 5 SH3BP5 SH3-domain binding protein 5 (BTK-associated) SIVA1 SIVA1, apoptosis-inducing factor SLC1A3 solute carrier family 1 (glial high affinity glutamate transporter), member 3 SLC25A13 Solute carrier family 25, member 13 (citrin) SLC25A14 solute carrier family 25 (mitochondrial carrier, brain), member 14 SLC25A25 solute carrier family 25, member 25 SLC25A26 solute carrier family 25, member 26 SLC25A29 Solute carrier family 25, member 29

190 Chapter 4 Table S5. (continued) Gene alias Gene name/description SLC25A30 solute carrier family 25, member 30 SLC25A32 solute carrier family 25, member 32 SLC25A38 solute carrier family 25, member 38 SLC25A44 solute carrier family 25, member 44 SLC25A45 solute carrier family 25, member 45 SLC27A1 solute carrier family 27 (fatty acid transporter), member 1 SLC27A3 solute carrier family 27 (fatty acid transporter), member 3 SLMO2 slowmo homolog 2 (Drosophila) SND1 staphylococcal nuclease and tudor domain containing 1 SOD1 superoxide dismutase 1, soluble SRGAP2 SLIT-ROBO Rho GTPase activating protein 2 SSSCA1 Sjogren syndrome/scleroderma autoantigen 1 STAR steroidogenic acute regulatory protein SURF1 surfeit 1 SYNJ2BP synaptojanin 2 binding protein TAOK3 TAO kinase 3 TATDN3 TatD DNase domain containing 3 TBC1D15 TBC1 domain family, member 15 TBRG4 transforming growth factor beta regulator 4 TDRKH tudor and KH domain containing TIMM17A translocase of inner mitochondrial membrane 17 homolog A (yeast) TIMM23 translocase of inner mitochondrial membrane 23 homolog (yeast) TMEM126A transmembrane protein 126A TMEM14B /// TMEM14C transmembrane protein 14B /// transmembrane protein 14C TMEM14C transmembrane protein 14C TMEM186 transmembrane protein 186 TMEM223 transmembrane protein 223 TOMM40 translocase of outer mitochondrial membrane 40 homolog (yeast) TXNIP thioredoxin interacting protein UQCR11 ubiquinol-cytochrome c reductase, complex III subunit XI UQCRC2 ubiquinol-cytochrome c reductase core protein II UQCRFS1 ubiquinol-cytochrome c reductase, Rieske iron-sulfur polypeptide 1 WARS2 tryptophanyl tRNA synthetase 2, mitochondrial ZFHX3 Zinc finger homeobox 3

dsRNA-induced Gene Expression of Airway Epithelium 191 Table S6. Genes induced in the lower airways of healthy controls and allergic rhinitis patients, assigned to GO cluster Mitochondrion Gene alias Gene name/description AASS aminoadipate-semialdehyde synthase ADCK2 aarF domain containing kinase 2 AK3 adenylate kinase 3 AK4 adenylate kinase 4 ATP5J ATP synthase, H+ transporting, mitochondrial F0 complex, subunit F6 ATP5L ATP synthase, H+ transporting, mitochondrial F0 complex, subunit G butyrobetaine (gamma), 2-oxoglutarate dioxygenase (gamma-butyrobetaine BBOX1 hydroxylase) 1 BCAT1 branched chain amino-acid transaminase 1, cytosolic BNIP3 BCL2/adenovirus E1B 19kDa interacting protein 3 C10orf2 chromosome 10 open reading frame 2 C14orf156 chromosome 14 open reading frame 156 C19orf70 chromosome 19 open reading frame 70 C2orf47 chromosome 2 open reading frame 47 C3orf1 chromosome 3 open reading frame 1 C3orf78 small integral membrane protein 4 C4orf14 chromosome 4 open reading frame 14 C6orf203 chromosome 6 open reading frame 203 C7orf55 /// LUC7L2 chromosome 7 open reading frame 55 /// LUC7-like 2 (S. cerevisiae) CCBL2 cysteine conjugate-beta lyase 2 CCT7 chaperonin containing TCP1, subunit 7 (eta) CKB creatine kinase, brain CKMT1A /// CKMT1B creatine kinase, mitochondrial 1A /// creatine kinase, mitochondrial 1B COX11 COX11 cytochrome c oxidase assembly homolog (yeast) COX3 mitochondrially encoded cytochrome c oxidase III COX7A2L cytochrome c oxidase subunit VIIa polypeptide 2 like CPS1 carbamoyl-phosphate synthase 1, mitochondrial CS citrate synthase CYCS cytochrome c, somatic DARS2 aspartyl-tRNA synthetase 2, mitochondrial DHRS1 dehydrogenase/reductase (SDR family) member 1 DLAT dihydrolipoamide S-acetyltransferase EFHD1 EF-hand domain family, member D1 FIS1 fission 1 (mitochondrial outer membrane) homolog (S. cerevisiae) GCAT glycine C-acetyltransferase GCDH glutaryl-CoA dehydrogenase GLRX2 glutaredoxin 2 HERC2 hect domain and RLD 2 KARS lysyl-tRNA synthetase KRT4 keratin 4 LONP1 lon peptidase 1, mitochondrial LYRM4 LYR motif containing 4 MARS2 methionyl-tRNA synthetase 2, mitochondrial MCCC2 Methylcrotonoyl-Coenzyme A carboxylase 2 (beta) METT11D1 methyltransferase like 17

192 Chapter 4 Table S6. (continued) Gene alias Gene name/description METTL12 methyltransferase like 12 MMAA methylmalonic aciduria (cobalamin deficiency) cblA type MPST mercaptopyruvate sulfurtransferase MRPL12 mitochondrial ribosomal protein L12 MRPL2 mitochondrial ribosomal protein L2 MRPL21 mitochondrial ribosomal protein L21 MRPL35 mitochondrial ribosomal protein L35 MRPL42 mitochondrial ribosomal protein L42 MRPS16 mitochondrial ribosomal protein S16 MRPS23 mitochondrial ribosomal protein S23 MRPS25 mitochondrial ribosomal protein S25 MRPS33 mitochondrial ribosomal protein S33 MRPS34 mitochondrial ribosomal protein S34 MRPS35 mitochondrial ribosomal protein S35 MRPS7 mitochondrial ribosomal protein S7 MSTO1 misato homolog 1 (Drosophila) MTERFD1 MTERF domain containing 1 methylenetetrahydrofolate dehydrogenase (NADP+ dependent) 2, MTHFD2 methenyltetrahydrofolate cyclohydrolase MTPAP mitochondrial poly(A) polymerase NAPG N-ethylmaleimide-sensitive factor attachment protein, gamma NDUFA9 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 9, 39kDa NDUFB8 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 8, 19kDa NDUFC1 NADH dehydrogenase (ubiquinone) 1, subcomplex unknown, 1, 6kDa NADH dehydrogenase (ubiquinone) Fe-S protein 7, 20kDa (NADH-coenzyme Q NDUFS7 reductase) NDUFV3 NADH dehydrogenase (ubiquinone) flavoprotein 3, 10kDa NIPSNAP1 nipsnap homolog 1 (C. elegans) NIT2 nitrilase family, member 2 NOP14 NOP14 nucleolar protein homolog (yeast) nuclear receptor subfamily 1, group D, member 1 /// thyroid hormone receptor, alpha NR1D1 /// THRA (erythroblastic leukemia viral (v-erb-a) oncogene homolog, avian) NUDT19 nudix (nucleoside diphosphate linked moiety X)-type motif 19 NUDT9 nudix (nucleoside diphosphate linked moiety X)-type motif 9 PITRM1 pitrilysin metallopeptidase 1 POLG2 polymerase (DNA directed), gamma 2, accessory subunit PPOX protoporphyrinogen oxidase PRDX1 peroxiredoxin 1 QTRTD1 queuine tRNA-ribosyltransferase domain containing 1 RARS arginyl-tRNA synthetase REXO2 REX2, RNA exonuclease 2 homolog (S. cerevisiae) SFXN4 Sideroflexin 4 SLC22A4 solute carrier family 22 (organic cation/ergothioneine transporter), member 4 SLC25A15 solute carrier family 25 (mitochondrial carrier; ornithine transporter), member 15 SLC25A19 solute carrier family 25 (mitochondrial thiamine pyrophosphate carrier), member 19 SMCR7L Smith-Magenis syndrome chromosome region, candidate 7-like SUPV3L1 suppressor of var1, 3-like 1 (S. cerevisiae)

dsRNA-induced Gene Expression of Airway Epithelium 193 Table S6. (continued) Gene alias Gene name/description TFB1M transcription factor B1, mitochondrial TFB2M transcription factor B2, mitochondrial TIMM44 translocase of inner mitochondrial membrane 44 homolog (yeast) TK2 thymidine kinase 2, mitochondrial TMEM160 transmembrane protein 160 TMLHE trimethyllysine hydroxylase, epsilon TOMM70A translocase of outer mitochondrial membrane 70 homolog A (S. cerevisiae) TXNDC12 thioredoxin domain containing 12 (endoplasmic reticulum) UQCRB ubiquinol-cytochrome c reductase binding protein UQCRQ ubiquinol-cytochrome c reductase, complex III subunit VII, 9.5kDa VARS valyl-tRNA synthetase YME1L1 YME1-like 1 (S. cerevisiae) tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation protein, epsilon YWHAE polypeptide

Figure S1. Correlation plot of real-time PCR data and microarray results.

194 Chapter 4 References

(1) Wagener AH, Zwinderman AH, Luiten S, Fok- kens WJ, Bel EH, Sterk PJ, et al. The impact of allergic rhinitis and asthma on human nasal and bronchial epithelial gene expression. PLoS One 2013;8(11):e80257.

dsRNA-induced Gene Expression of Airway Epithelium 195

CHAPTER 5

External validation of blood eosinophils, FENO and serum periostin as surrogates for sputum eosinophils in asthma

Ariane H. Wagener, Selma B. de Nijs, Rene Lutter, Ana R. Sousa, Els J.M. Weersink, Elisabeth H. Bel, Peter J. Sterk

Thorax 2015;70(2):115-20 Abstract

Background Monitoring sputum eosinophils in asthma predicts exacerbations and improves man-

agement of asthma. Thus far blood eosinophils and FENO show contradictory results in predicting eosinophilic airway inflammation. More recently, serum periostin was proposed as a novel biomarker for eosinophilic inflammation.

Objectives: Quantifying the mutual relationships of blood eosinophils, FENO and serum periostin with sputum eosinophils by external validation in two independent cohorts across various severities of asthma.

Methods The first cohort consisted of 110 patients with mild to moderate asthma (external validation cohort). The replication cohort consisted of 37 patients with moderate to severe asthma. Both cohorts were evaluated cross-sectionally. Sputum was induced for the assessment of eosinophils. In parallel, blood eosinophil counts, serum periostin concen-

trations and FENO were assessed. The diagnostic accuracy of these markers to identify eosinophilic asthma (sputum eosinophils ≥3%) was calculated using receiver operating characteristics area under the curve (ROC AUC).

Results In the external validation cohort, ROC AUC for blood eosinophils was 89% (p<0.001) and

for FENO level 78% (p<0.001) to detect sputum eosinophilia ≥3%. Serum periostin was not able to distinguish eosinophilic from non-eosinophilic airway inflammation (ROC AUC=55%, p=0.44). When combining these three variables no improvement was seen. The diagnostic value of blood eosinophils was confirmed in the replication cohort (ROC AUC 85%, p<0.001).

Conclusions In patients with mild to moderate asthma as well as patients with more severe asthma blood eosinophils had the highest accuracy in the identification of sputum eosinophilia in asthma. The use of blood eosinophils can facilitate individualised treatment and management of asthma.

198 Chapter 5 Introduction

Asthma is a heterogeneous condition which includes several clinical phenotypes that differ in severity, natural history and responses to therapy (1). There is recent evidence from prospective clinical studies that inflammatory (sub)phenotyping of patients can help to optimise therapy and disease outcome (2). This suggests that biomarkers of inflammation should be considered in identifying patients and monitoring of asthma in clinical practice, such as the titration of steroid treatment. Sputum eosinophilia has been demonstrated to be a key marker in predicting asthma outcome (3). Whereas eosinophilic asthma responds well to anti-inflammatory treatment with steroids, non-eosinophilic asthma shows little or no response (4). Addition- ally, studies in which corticosteroids were withdrawn have consistently shown that a raised sputum eosinophil count is predictive of inducing an exacerbation (5;6). The strong evidence that monitoring sputum eosinophils improves outcome has come from randomised trials showing that normalising sputum eosinophil counts can lead to 60% reduction in asthma exacerbations (2;7;8). Sputum induction by hypertonic saline is generally considered a reliable non-invasive method to assess and monitor eosinophilia (9). However, the use of sputum analysis is hindered by the requirement of lab facilities and the duration of the analyses. Fur- thermore, in patients with severe and uncontrolled asthma, induction of sputum can be problematic, because of hypertonic saline-induced airway narrowing and/or failure to produce an adequate sputum sample in about a quarter of the patients (10). There is, therefore, a need for adequate surrogate markers of eosinophilic inflammation in asthma. The measurement of FENO has been considered a surrogate marker for eosinophilic airway inflammation. However, the correlation between FENO and sputum eosinophils appears to be only modest (11), particularly in patients with steroid-dependent asthma (12). This is in line with a Cochrane meta-analysis demonstrating insufficient benefit of monitoring steroid therapy by FENO (2), even though this was challenged by a recent positive result in primary care (13). Alternatively, blood eosinophil counts exhibit moderate to good correlation with sputum eosinophils in asthma (14), being associated with disease severity and asthma phenotypes (15;16). Blood eosinophils may, therefore, predict and direct anti-inflammatory therapy, for which there is preliminary evidence in asthma and COPD (17-20). Nevertheless, a very recent study demonstrated poor correlations of FENO and blood eosinophils with sputum eosinophils, both separately and combined (21), thereby raising controversy. Finally, serum periostin was proposed as a systemic biomarker of eosinophilic airway inflammation in asthma, by showing a significant correlation with sputum eosinophils and prediction of steroid responsiveness in asthma (22;23).

Biomarkers of Disease 199 Based on international guidelines on STAndars for the Reporting of Diagnostic accuracy studies, it is mandatory to perform external validation when assessing diagnostic or phenotypical accuracy of disease markers (24). This has not been done for sputum

eosinophils with the triad of FENO, blood eosinophils and serum periostin. Therefore,

we aimed to quantify the mutual relationships of FENO, blood eosinophils and serum periostin with sputum eosinophils in an external validation cohort of patients with mild to moderate asthma and to replicate findings in a population with more severe asthma.

Methods

Subjects For the external validation cohort, we recruited 200 patients with mild to moderate asthma in the outpatient clinic of the Academic Medical Center (AMC) in Amsterdam and two non-academic pulmonary second-line referral outpatient clinics. For the replication cohort, we recruited 40 patients with moderate to severe asthma in the outpatient clinic of the AMC. For both cohorts, the diagnosis of asthma was defined by a physician’s

diagnosis of asthma with reversibility in FEV1≥12% of the predicted value and/or airway

hyperresponsiveness (PC20 methacholine <8 mg/mL). In the external validation cohort, smokers or ex-smokers with a smoking history >10

pack-years were excluded if they did not show an improvement in FEV1 of at least 12% after inhalation of 400µg salbutamol with a normal diffusion capacity at the time of inclusion. In the replication cohort, all smokers or ex-smokers with a smoking history >10 pack-years were excluded. At the time of the study visit, no patients had any symptoms of respiratory infection for at least 4 weeks. Both studies were approved by the hospital medical ethics committee, and all patients gave their written informed consent. The external validation cohort was registered in The Netherlands trial register (www.trialregister.nl) under NTR1846 and the replication cohort under NTR2364.

Design The studies had similar cross-sectional designs and included one hospital visit for all measurements. During this visit, inclusion and exclusion criteria were examined, lung function was performed and sputum was induced by hypertonic saline. Inflammatory status in the external validation cohort was also measured by the assessment of blood

eosinophils, FENO and serum periostin. In the replication cohort, blood eosinophils and serum periostin were measured in order to replicate findings in a population with more severe asthma.

200 Chapter 5 Measurements

Lung function and allergy testing Lung function was performed according to the European Respiratory Society (ERS) recommendations (25). Atopic status was assessed by total and specific immunoglobulin E (IgE) to a panel of common aeroallergens. Patients were considered atopic if there was at least one serum-specific IgE>0.34 kU/L.

Markers of inflammation Sputum was induced by inhalation of hypertonic saline three times at intervals of 5 min, according to the ERS recommendations (26). Before induction of sputum, patients inhaled 400 µg salbutamol. For the external validation cohort, the volume of the whole sputum sample was assessed and an equal volume of dithiotreitol (10 mM DTT in 135 mN Tris buffer, pH 8.0) was added. For the replication cohort, selected plugs were processed with 0.1% DTT. The processing of the sputum and cell counts was done by experienced laboratory analysts blinded to other results. Differential cell counts were expressed as the percentage of non-squamous cells, based on 500 non-squamous cells. Those with significant squamous contamination (>80%) were excluded from analysis. According to previous studies, we used a sputum eosinophil count of 3% as the threshold for determining eosinophilic or non-eosinophilic airway inflammation (7). Peripheral blood eosinophil counts were obtained from standard complete blood counts done at the same centre, and FENO was measured using an online device at a constant flow of 50 mL/s (Niox Mino; Aerocrine AB, Solna, Sweden) (27). Serum was obtained by centrifugation of blood that coagulated for 30 min at room temperature, after which serum periostin levels were measured in an ELISA with the DuoSet Human Periostin/ OSF-2 (R&D Systems) (see the Methods section of the Supporting Information File). This in-house ELISA for periostin was validated for measurement of periostin in serum by serial dilutions (10×, 20×, 40× and 80× diluted; ±15.5% variation) and spike recovery (77.75%±11.69%; (mean±SD)). The intra-assay and interassay coefficients of variability were 12.3% (9.08%±3.91%; (mean±SD)) and 17.4% (12.69%±4.08%), respectively. West- ern blots were performed to determine which periostin isoforms were recognised by the antibody were performed (see the Methods and the Results sections of the Supporting Information File). Furthermore, all blinded serum samples were analysed by a second and independent periostin assay (Elecsys Periostin, for use on the COBAS e601), under development by Roche Professional Diagnostics, Penzberg, Germany, using the same antibodies as previously described (22).

Biomarkers of Disease 201 Statistical analysis SPSS (V.18.0) was used for data analysis. The results for continuous variables were expressed as mean±SD; skewed distributions were presented as medians with IQRs. Non-normally distributed variables were transformed to log or square root values. The relationship between sputum eosinophils and the surrogate markers were analysed using Pearson’s correlation coefficient. For the external validation cohort, receiver operating characteristic (ROC) curve analysis was performed for each variable individually or in combination, to determine the marker that best identified a sputum eosinophil count ≥3%. To analyse whether the area under the curve (AUC) of different ROC curves differ significantly, comparisons of AUCs were performed using R (V.2.15) and the pROC package (28). The optimum cut-points were considered for each variable and sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated. Additionally, sensitivity and specificity were calculated for alternative cut-points that were previously published: blood 9 9 eosinophils ≥0.25×10 /L and ≥0.22×10 /L; FENO levels >50, <24 and >20 ppb; serum periostin levels using the median of the biomarker as cut-off (16;22;29-31). The diagnostic accuracy of the best predictive marker for sputum eosinophils in the external validation cohort was subsequently verified in the replication cohort using ROC curve analysis.

Results

In the external validation cohort (recruitment: June 2009−June 2011) 110 out of 200 patients and in the replication cohort (recruitment: October 2010−June 2011) 37 out of 40 patients were able to produce adequate sputum samples. The patient characteristics of both cohorts are described in Table 1, and characteristics stratified by sputum eosinophil counts of ≤3% or ≥3% are presented in Table E1 of the Supporting Information File.

External validity of blood eosinophils, FENO and serum periostin

Blood eosinophils and FENO correlated with sputum eosinophil percentages (r=0.59, p<0.001 and r=0.52, p<0.001, respectively). Using the in-house periostin ELISA, there was no significant correlation between serum periostin and sputum eosinophil percentages (r=0.09, p=0.4). Using the Elecsys Periostin assay, there was a weak but significant correlation between serum periostin and sputum eosinophil percentages (r=0.32, p=0.001). The diagnostic accuracy of blood eosinophils, described as ROC AUC, was 89% (p<0.001, 95% CI 0.81 to 0.96) (Figure 1). Using ≥0.27×109/L blood eosinophils as a cut-point, eosinophilic and non-eosinophilic inflammation was well differentiated with a sensitivity of 78% and a specificity of 91% (Table 2).

202 Chapter 5 Table 1. Patient characteristics External validation cohort Replication cohort Number of patients 110 37 Age (years) 49±13.8 53±11.4 Gender (% female) 51 51 BMI 28±5.2 30±7.5 Smoking history (py)* 4 (0−18) 0 (0−5.5) Oral corticosteroids (%) 0 19 Inhaled corticosteroids (%) 85 100 Dose ICS (µg/day)*† 500 (250−500) 500 (500−1000) Atopy (% positive RAST) 43 57 Total IgE (Ku/L)* 62 (26−235) 153 (42−288) pb FEV1 (% predicted) 100±17.1 90±18.1 pb FEV1/FVC (% predicted) 95±11.0 86±16 Sputum eosinophils, %* 0.6 (0.1−3.6) 2.1 (0.2−8.8) Blood eosinophils, 109/L* 0.17 (0.11−0.29) 0.18 (0.09−0.32)

* FENO level, ppb 20 (13−40) NA Periostin (in-house), ng/mL* 25.5 (19.9−32.6) 36.3 (28.7−54.2) Periostin (Elecsys), ng/mL* 47.7 (40.2−56.3) 50.8 (45.7−60.4) Data expressed as mean±SD; *Median (IQR). †Fluticasone equivalent. BMI, Body Mass Index; ICS, inhaled corticosteroids; IgE, immunoglobulin E; NA, not available; pb, postbronchodilator; py, pack-years; RAST, radioallergosorbent test.

Figure 1. ROC curve analyses Receiver operating characteristics curve analyses of the sensitivity and the specificity of blood eosino-

phils (eos), FENO and serum periostin (in-house) for the diagnosis of eosinophilic inflammation. AUC, area under the curve.

Biomarkers of Disease 203 The overall accuracy of FENO levels to differentiate eosinophilic and non-eosinophilic inflammation, described as ROC AUC, was 78% (p<0.001, 95% CI 0.66 to 0.89) (Figure 1). This ROC AUC was not significantly different from the ROC AUC of blood eosinophils

(p=0.09). A FENO level of ≥42 ppb provided a sensitivity of 63% and a specificity of 92% (Table 2). Serum periostin measured by the in-house ELISA was not able to distinguish eosinophilic from non-eosinophilic inflammation (ROC AUC=55%, p=0.44, 95% CI 0.43 to 0.67) (Figure 1). Serum periostin analyses using the Elecsys Periostin assay showed similar results (see the Results section of the Supporting Information File). When combining these three variables in the prediction of eosinophilic inflammation, no improvement was seen, resulting in an ROC AUC of 88% (p<0.001, 95% CI 0.79 to 0.97). Next, sensitivity, specificity, PPV and NPV for different criteria used in previous studies are presented in Table 2. Since others have reported 2% sputum eosinophils as an alternative criterion for the diagnosis of eosinophilic or non-eosinophilic asthma (8), additional ROC curve analyses were performed using 2% sputum eosinophils as threshold. The results were similar to those using 3% sputum eosinophils, with an ROC AUC of 88% (p<0.001) for blood eo-

sinophils, an ROC AUC of 79% (p<0.001) for FENO and no significant diagnostic accuracy for serum periostin (see Table E2 of the Supporting Information File).

Replication In the replication cohort as well, there was a significant correlation between blood eosinophils and sputum eosinophil percentages (r=0.80, p<0.001). Blood eosinophil levels were effective in assessing eosinophilic inflammation, with an ROC AUC of 85% (p<0.001, 95% CI 0.72 to 0.98) (Figure 2). Using ≥0.27×109/L blood eosinophils as reported in the external validation cohort as best threshold, the sensitivity was 60% and specificity

Table 2. Sensitivity, specificity, PPV and NPV of different surrogate markers using alternative cut-points to diagnose eosinophilic airway inflammation (less than, more than or equal to 3% sputum eosinophils) Threshold Sensitivity Specificity PPV NPV Blood eosinophils >0.22×109/L 86 79 60 93 Blood eosinophils ≥0.25×109/L 79 84 64 91 Blood eosinophils ≥0.27×109/L 78 91 79 91

FENO level >20 ppb 74 57 40 87

FENO level ≥24 ppb 74 63 42 87

FENO level ≥42 ppb 63 92 74 89

FENO level >50 ppb 56 92 67 84 Serum periostin (in-house) >26 ng/mL 54 57 29 77 NPV, negative predictive value; PPV, positive predictive value.

204 Chapter 5 90% (see Table E3 of the Supporting Information File). In line with the results of the external validation cohort, no correlation was found between serum periostin (using the in-house ELISA) and sputum eosinophils in the replication cohort (r=0.13, p=0.46), nor was periostin able to distinguish eosinophilic inflammation from non-eosinophilic inflammation (ROC AUC 54%, p=0.79, 95% CI 0.34 to 0.74) (Figure 2). Independent analysis using the Elecsys Periostin assay provided similar results (see the Results section of the Supporting Information File).

Figure 2. Replication ROC curve analyses Replication of findings: receiver operating characteristics curve analyses of the sensitivity and the specificity of blood eosinophils (eos) and serum periostin (in- house) for the diagnosis of eosinophilic inflammation in a second cohort with more severe asthma. AUC, area under the curve.

Discussion

This study shows that in patients with mild to moderate asthma blood eosinophils is an accurate surrogate marker for sputum eosinophils. Next, we were able to replicate blood eosinophils as highly effective surrogate markers in a second independent cohort of patients with more severe asthma. FENO was second best, while serum periostin showed the lowest accuracy for eosinophilic asthma in both cohorts. These findings suggest that blood eosinophil count can be used in mild, moderate and severe asthma as an easy-to- measure biomarker for sputum eosinophil percentage, which can have great practical advantages for guiding current or novel anti-inflammatory therapies. Periostin might provide different information than sputum eosinophils, which may be complementary in asthma phenotyping.

Biomarkers of Disease 205 Interestingly, blood eosinophils and sputum eosinophils were highly correlated in both our cohorts and exhibited the highest diagnostic accuracy which validates previous data (31;32), and to a lesser extent a recent report (21). We were not able to show a role for periostin as diagnostic marker for sputum eosinophils in both populations. The present data are not in line with the single previous study investigating the relationship between airway eosinophilia and all three markers, which demonstrated the highest ROC AUC for serum periostin (22). However, the latter study used a combination of both high sputum and high tissue eosinophils as definition of eosinophilic airway inflammation. Furthermore, they included patients with uncontrolled severe asthma only, whereas the present study included a larger cohort of mild to moderate patients and a somewhat smaller cohort of severe patients.

In our study, FENO appeared to be the second-best predictor for eosinophilic inflammation with an ROC AUC 0.78, which is nearly similar to previous studies (21;22;31), although, surprisingly, the best combination of sensitivity and specificity was achieved at a rather high cut-point of 42 ppb in our cohort of patients with mild to moderate

disease. Even though FENO was significantly associated with sputum eosinophils, when

combining the three markers in the ROC analysis, neither FENO nor periostin had any additive value. Our data confirms a recent paper in which a weak correlation was found

between blood eosinophils and FENO (33), suggesting that blood eosinophils and FENO relate to two different inflammatory pathways. This supports our main result that blood eosinophil count alone is the strongest independent predictor for eosinophilic airway inflammation. To the best of our knowledge, this is the first study to externally validate serum periostin as surrogate marker for sputum eosinophils in a population with mild to moderate asthma, including replication in a second cohort with more severe disease. We believe that the strength of this study is that we have two independent well-characterised cohorts of varying asthma severity and treatment, though with similar stringent criteria for the diagnosis of asthma. Another strength is the size of the external validation cohort, which reassures the confidence of the analysis. However, the size of the replication cohort of patients with severe asthma was limited, which may require further analysis in large severe asthma cohorts, such as U-BIOPRED (Unbiased BIOmarkers in PREDic- tion of respiratory disease outcome). The predictive accuracy of blood eosinophils is unlikely to be affected by treatment in our cohorts, since we recruited widely varying levels of therapy in mild, moderate and severe patients, including 19% of the severe patients using oral corticosteroids. Next, the sputum from both cohorts was processed in different standardised ways (whole sample vs selected plug). Nevertheless, the correlation with blood eosinophils was consistent, which may be due to careful quality control procedures. We used 3% sputum eosinophils as the threshold for eosinophilic or non-eosinophilic airway inflammation according to the literature. Because others

206 Chapter 5 have used 2% as the cut-point, we reanalysed the data with 2% blood eosinophils as threshold showing similar results. Finally, we used two independent periostin assays, thereby contributing to the validity of our data. One of the potential weaknesses of our study is that we could not obtain adequate sputum in all patients. However, no significant differences were found in blood eosinophil counts and FENO level between the patients who successfully produced sputum and those who did not (data not shown). Therefore, we do not believe that the results of our study are biased by this limitation. Furthermore, the smoking status between the cohorts differed, as ex-smokers were included in the validation cohort and excluded in the replication cohort. In the validation cohort, patients with a smoking history, as compared with never-smokers, had borderline significantly higher sputum eosinophils (p=0.05), whereas no differences were found for blood or sputum neutrophils, blood eosinophils, FENO and periostin (p=0.26, p=0.09, p=0.46, p=0.25, p=0.31, respectively). As a result, smoking status does not seem to have affected our results. Finally, we used a different assay to measure serum periostin as compared with previous studies. Our in-house ELISA for periostin was validated as described in the Supporting Information File. It has been argued that some antiperiostin antibodies may not recognise all four isoforms of periostin in serum (22;34). Since it is unknown which isoforms are present in serum, we have extensively, but unsuccessfully attempted to determine which isoforms of periostin were present in (up to 10-fold concentrated) serum using western blotting with a goat polyclonal antibody (R&D; AF3548) affinity-purified on periostin (Asn22-Gln836; data not shown). Given that the amounts of periostin in serum reported here were similar to those reported by others (22;30), we consider it highly unlikely that our in-house ELISA failed to recognise the most abundant splice variants of periostin in serum. Moreover, the additional analyses by the Elecsys Periostin assay with antibodies aimed to recognise all known splice variants that showed similar results. The correlation between blood and sputum eosinophils in asthma may not be biologi- cally surprising. Eosinophils are produced in the bone marrow, and in case of inflammation, the formation is amplified and the eosinophils traffic into inflammatory sites, all under influence of a number of cytokines, such as interleukin (IL)-5 (35). Blood eosinophils of patients with asthma have a distinct phenotype, especially in relation to their adhesive properties (36), which is involved in the transmigration across endothelium and epithelium. Increased eosinophils were observed in both the blood and sputum after allergen challenge (37). Furthermore, several studies have demonstrated that the infusion of anti-IL-5 intravenously dramatically lowers eosinophil levels in both the blood and sputum or in bronchoalveolar lavage fluid (18-20;38-41). Hence, although the transport of eosinophils from the blood into the lung is a complex active process, in a chronic inflammatory disease such as asthma, the levels of eosinophils in the blood and sputum appear to be closely related.

Biomarkers of Disease 207 What are the clinical implications of our study? Since the measurement of blood eosinophils is easy and quick in comparison with sputum eosinophils, our data support the opportunity to assess the presence or absence of eosinophilic airway inflammation and monitor treatment in asthma. This is supported by two very recent trials using anti- IL-5 (mepolizumab), resulting in a significant reduction in the daily requirement of oral glucocorticoid therapy, reducing exacerbations and improving asthma symptoms of patients with severe eosinophilic asthma, identified by a blood eosinophil count of ≥300 cells/µL during the year before screening or ≥150 cells/µL before randomisation (18;19). Additionally, in a large study using anti-IL-5 to target eosinophilic airway inflammation in patients with severe asthma, blood eosinophil count at baseline was predictive for the efficacy of reducing exacerbations (20). A follow-up analysis of this study showed that blood eosinophil count in the placebo cohort was stable over time (42). Furthermore, several studies showed that anti-IL-5 treatment results in a significant decrease in both

sputum and blood eosinophil counts, but not in FENO (20;39), confirming the relevance of blood eosinophils in stratification studies for anti-IL-5. With regard to anti-IL-13 therapy, blood eosinophils were not successful in the stratification of patients responsive to treatment (43). However, the latter study used a much lower cut-point for blood eosinophils (≥0.14×109/L) as compared with our study, and used a combination of serum IgE and blood eosinophil counts to identify an IL-13 signature surrogate. A more recent study on anti-IL-4/IL-13, using a higher cut-point for blood eosinophils for the stratification of patients (≥0.30×109/L), did show significant improvements after treatment, thereby supporting blood eosinophil count as biomarker (44). Obviously, this needs replication. Regarding periostin, this study shows that this biomarker is not associated with sputum eosinophilia. This does not exclude complementary information to sputum eosinophils by periostin as a biomarker in asthma. Indeed, it is likely that periostin can play a meaningful role in the identification of specific phenotypes based on a Th2-high cytokine profile, since serum periostin was demonstrated to be a successful biomarker for predicting effectiveness of anti-IL-13 therapy (43), and was associated with airway eosinophilia in patients with uncontrolled severe asthma (22). In our study, the diagnostic accuracy of blood eosinophils to distinguish eosinophilic from non-eosinophilic asthma in the replication cohort was equal to the validation cohort. However, the best cut-point was different in both cohorts with a lower cut-point in the replication cohort (see Table 2 and Table E3 of the Supporting Information File). This may be explained by the difference in disease severity between the cohorts. Therefore, when using blood eosinophil count as biomarker for eosinophilic airway inflammation, the optimum cut-point may differ per population and per study question (24). In conclusion, we showed a meaningful relationship between blood eosinophils and

sputum eosinophils in two independent cohorts with varying asthma severity. FENO

was a second-best predictor for eosinophilic airway inflammation, though FENO did not

208 Chapter 5 demonstrate additive value to blood eosinophils. Serum periostin was not related to sputum eosinophils in mild to moderate asthma, and this finding was replicated in the population with more severe disease. This suggests that periostin might capture other asthma phenotypes than those represented by sputum eosinophils per se. Our data indicate that blood eosinophils represent an accurate biomarker for sputum eosinophils in asthma, which can facilitate effective guidance of individualised asthma treatment.

Biomarkers of Disease 209 References

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212 Chapter 5 CHAPTER 5 Supporting Information File

External validation of blood eosinophils, FENO and serum periostin as surrogates for sputum eosinophils in asthma

Methods

In-house periostin assay set up and quality Serum periostin was measured by ELISA (duoset DY3548: R&D systems) using poly-HRP (Sanquin, Amsterdam, the Netherlands) for amplification. In short, capture antibody (100 μl/well; 1 μg/mL) was incubated overnight in a NUNC 96-well ELISA plate at room temperature. After three washes with phosphate-buffered saline (PBS) pH 7.4 and 0.2% Tween-20 (PBST), remaining binding sites were blocked using 0.5% non-fat milk in PBS (150 μl/well) for 30 min. After three washes with PBST, standard curve (10,000 pg/mL till 39 pg/mL; 1 to 1 dilutions), samples (1 in 40 and 1 in 80 dilution) and internal controls were added (100 μl/well) and incubated for 2h, followed by three washes with PBST. Subsequently, detecting antibody (100 μl; 2 μg/mL) was added and left for 1h. After another three washes with PBST, 100 μl of a 1 in 10,000 dilution of poly-HRP (Sanquin, the Netherlands) in PBS with 0.5% non-fat milk in PBS was added and incubated for 30 min. After four washes with PBST the plates were developed using tetra-methyl benzidine and stopped with sulphuric acid. Incubations were at 500 rpm, at room temperature and in the dark, unless indicated otherwise. This in-house ELISA for periostin was validated for measurement of periostin in serum by serial dilutions (10×, 20×, 40× and 80× diluted; ± 15.5% variation) and spike recovery (77.75%±11.69%; (mean±SD)). The intra-assay and interassay coefficients of variability were 12.3% (9.08%±3.91%; (mean±SD)) and 17.4% (12.69%±4.08%), respectively.

Western blot of periostin isoforms Serum samples with high and low periostin were run on 10% polyacrylamide gels under reducing conditions with SDS. In some experiments serum proteins were concentrated by precipitation using 15 (w/v) TCA and carefully solubilized in Laemmli sample buffer before layering. After separation proteins were transferred to PVDF membranes, blocked with milk powder in PBS tween-20 buffer and developed using a goat polyclonal periostin purified detecting antibody followed by an anti-goat secondary antibody (1:15000; LI-COR Biosciences). Membranes were scanned and quantified using the Odyssey Infra- red Imaging system (LI-COR Biosciences).

Results

Western blot of periostin isoforms No isoforms of periostin were detected in (up to 10-fold concentrated) serum using Western blotting with a goat polyclonal antibody (R&D; AF3548) affinity-purified on periostin (Asn22-Gln836).

Biomarkers of Disease 215 Serum periostin analyses by Elecsys Periostin In conjunction with our data, serum periostin analyses using the Elecsys Periostin assay showed similar results. In the external validation cohort there was a weak but significant correlation between serum periostin and sputum eosinophil percentages (r=0.32, p=0.001), whereas in the replication cohort there was no significant correlation (r=0.28, p=0.1). The diagnostic accuracy of serum periostin to differentiate eosinophilic from non- eosinophilic airway inflammation using 3% sputum eosinophils as threshold, described as ROC AUC, was 62% (p=0.09, 95% CI 0.48 to 0.75) in the external validation cohort and 55% (p=0.6, 95% CI 0.35 to 0.75) in the replication cohort (Figure E1).

Table E1. Patient characteristics stratified by sputum eosinophil percentages External validation cohort Replication cohort Mild to moderate asthma Moderate to severe asthma EO ≥3% EO <3% EO ≥3% EO <3% n=30 n=80 n=16 n=21 Age (years) 52±14.0 49±13.6 55±9.1 52±12.9 Gender (% female) 43 54 56 48 BMI 28±5.3 28±5.2 31±9.3 29±6.0 Smoking history (py)# 6 (0−17) 4 (0−19) 0 (0−7.5) 0 (0−5) Dose ICS (µg/day)#1 500 (250−500) 250 (250−500) 500 (500−1000) 625 (500−1000) % positive RAST 60* 37* 50 62 Serum IgE (Ku/L)# 164 (34−262)* 54 (20−190)* 226 (35−383) 153 (44−267)

pb FEV1, % pred 101±18.5 100±16.6 86±21.4 94±14.7

pb FEV1/FVC, % pred 92±9.5 96±11.4 82±15.3 88±16.5 Blood eos, ×109/l# 0.38 (0.29−0.61)** 0.14 (.09−0.20)** 0.32 (0.23−0.48)** 0.13 (.06−0.20)**

# ** ** FENO level, ppb 55 (17−86) 18 (13−32) NA NA Periostin (in-house), ng/mL# 27 (21.2−32.9) 25 (19.0−32.8) 42 (27.1−59.3) 36 (29.1−49.4) Periostin (Genentech), ng/mL# 49.7 (42.4−62) 45.3 (39.4−54.6) 56.8 (45.5−61.2) 49.1 (45.6−58) Data expressed as mean±SD; # Median (IQR). *t-test p<0.05; **t-test p<0.001. BMI, Body Mass Index; Dose ICS, fluticason equivalent; ICS, inhaled corticosteroids; IgE, immunoglobulin E; NA, not available; pb, postbronchodilator; py, pack-years; RAST, radioallergosorbent test.

216 Chapter 5 Table E2. Sensitivity, specificity, PPV and NPV of different surrogate markers using alternative cut-points to diagnose eosinophilic airway inflammation (less than, more than or equal to 2% sputum eosinophils) Threshold Sensitivity Specificity PPV NPV Blood eosinophils >0.22×109/L 83 82 70 90 Blood eosinophils ≥0.25×109/L 74 86 72 88 Blood eosinophils ≥0.27×109/L 69 92 80 86

FENO level >20 ppb 76 60 49 85

FENO level ≥24 ppb 76 67 52 85

FENO level ≥42 ppb 58 94 83 84

FENO level >50 ppb 48 94 80 80 Periostin (in-house) >26 ng/mL 56 57 37 73 PPV, positive predictive value; NPV, negative predictive value.

Table E3. Replication cohort: sensitivity, specificity, PPV and NPV of different surrogate markers using alternative cut-points to diagnose eosinophilic airway inflammation (less than, more than or equal to 3% sputum eosinophils) Threshold Sensitivity Specificity PPV NPV Blood eosinophils >0.22×109/L 80 80 75 84 Blood eosinophils ≥0.25×109/L 67 85 77 77 Blood eosinophils ≥0.27×109/L 60 90 83 78 Periostin (in-house) >36 ng/mL 56 67 50 65 PPV, positive predictive value; NPV, negative predictive value.

Elecsys Periostin assay 1.0 0.8 0.6 Sensitivity 0.4 0.2 AUC Validation cohort=0.62 AUC Replication cohort=0.55 0.0

0.0 0.2 0.4 0.6 0.8 1.0

1 − Specificity Figure E1. ROC curve analyses Receiver operating characteristics curve analyses of the sensitivity and the specificity of serum periostin, using the Elecsys Periostin assay, for the diagnosis of eosinophilic inflammation. AUC, area under the curve.

Biomarkers of Disease 217

CHAPTER 6 Predicting eosinophilic airway in ammation in asthma using exhaled breath pro ling

Ariane H. Wagener, Paul Brinkman, Aeilko H. Zwinderman, Aruna T. Bansal, Arnaldo D’Amico, Giorgio Pennazza, Marco Santonico, Paolo Montuschi, Ratko Djukanovic, Rene Lutter, Stephen J. Fowler, Peter J. Sterk

Planned submission Q1 2016 Abstract

Background Management of asthma based on inflammatory profiling improves clinical outcomes. However, there is a need for surrogate markers of airway eosinophilia for daily practice. Exhaled air metabolomics by gas-chromatography and mass-spectrometry enables identification of eosinophilic inflammation. The electronic nose (eNose) offers a low- cost, rapid, point of care alternative for breath profiling. Objectives: To validate breathprints obtained by a composite eNose platform in the prediction of sputum eosinophilia in asthma.

Methods This multicenter study included 104 patient visits (58 baseline visits and 46 longitudinal visits) of the U-BIOPRED project. Induced sputum and blood eosinophils were measured. Breath samples were collected locally and analysed centrally by 84 eNose sensors in parallel (based on four different technologies). Discriminant accuracy of eNose sensors and blood eosinophil counts for sputum eosinophilia was obtained by receiver operating characteristics (ROC) analysis in the baseline cohort and validated in the longitudinal cohort.

Results Models derived from eNose sensors classified patients based on sputum eosinophilia ≥3% with an area under the ROC curve (AUC) of 73%. Validation in the longitudinal cohort, 57% of whom had not provided breath samples at baseline resulted in an AUC of 78%. Discriminant analysis using blood eosinophil counts produced an AUC of 69%.

Conclusions ENose breathprints discriminate eosinophilic from non-eosinophilic airway inflammation in asthma, which was validated at a second study visit in a largely independent cohort of patients. Blood eosinophil counts showed similar accuracies. This suggests that eNoses have potential to capture eosinophilic airway inflammation in a quick way, thereby facilitating personalized asthma management.

220 Chapter 6 Introduction

Classification of asthma phenotypes based on sputum differential cell counts character- ises patients with eosinophilic and/or neutrophilic airway inflammation (1). Inflammatory phenotyping of asthma has been shown to be of clinical importance, since eosinophilic asthma responds well to corticosteroid treatment, whereas non-eosinophilic asthma responds poorly (2;3). By selecting patients based on sputum eosinophil count specific antibodies against IL5 and IL4/IL13 have been shown to be effective (4-6). Several studies have consistently demonstrated that targeting sputum eosinophils by tailoring inhaled steroid therapy reduces asthma exacerbations by 60% (7-9). Alternatively, azithromycin is suggested to reduce asthma exacerbations in patients with non-eosinophilic asthma (10). These studies show that personalizing therapy by identification of asthma inflammatory subtypes lead to a better disease outcome then indiscriminate treatment (9). Sputum induction by hypertonic saline is considered a safe and non-invasive method to identify airway inflammation in patients with asthma (11). However, processing of sputum is technically demanding and time-consuming. Notably, about 25% of patients fail to produce an adequate sputum sample, and in patients with uncontrolled asthma induction can cause significant airway narrowing (12). Therefore, there is a need for adequate surrogate markers of airway inflammation in asthma. Blood differential cell counts and fractional exhaled nitric oxide (FENO) have been considered as alternative biomarkers to diagnose asthma inflammatory subtypes. Recently, we have shown that blood eosinophils represent an accurate biomarker for sputum eosinophils in two independent cohorts of patients with mild to severe asthma (13), even though a recent meta-analysis was still inconclusive (14). Notably, FENO and sputum eosinophils are only weakly to moderately correlated (15-17). Therefore, it may not be surprising that guiding steroid therapy based on FENO is not effective on asthma outcomes (9), although using an improved algorithm did show reduced exacerbations by FENO-guided therapy (18) and a recent study in primary care demonstrated a positive result (19). Exhaled air contains volatile organic compounds (VOCs) that may qualify as non-invasive biomarkers of disease (20). Assessment of the profile of these volatiles by gas-chromatography and mass-spectrometry (GC-MS) and sensors of various types of electronic noses (eNoses) allows capturing disease-related molecular patterns (21;22). The latter approach combines the non-invasiveness of measuring exhaled breath with real-time analysis of a metabolomic fingerprint (breathprint) (23;24). It has been shown that electronic noses are able to discriminate exhaled breath between well-characterized subjects with asthma, COPD and controls (25;26). Interestingly, recent studies demonstrated that GC-MS of exhaled air can identify eosinophilic and neutrophilic inflammation in asthma (27) and COPD (28;29). Furthermore, the eNose was successfully used in predicting steroid responsiveness in a small cohort of patients with asthma (30) and

Exhaled Breath Profiling in Asthma 221 very recently exhaled molecular profiles have shown potential in asthma clustering (31). This raises the question whether exhaled molecular profiling by eNoses can recognize inflammatory phenotypes in asthma since this could provide a low-cost, rapid, point of care alternative for breath profiling. In this study, we hypothesized that breathprints analysed by eNoses can be used as surrogate markers of eosinophilic airway inflammation in asthma. We aimed to test this hypothesis by examining the relationship of breathprints analysed by a composite eNose platform with eosinophil counts in induced sputum in a wide spectrum of patients with mild to severe asthma and to validate this relationship in a second cohort. Subsequently, we aimed to compare the resulting accuracies by the eNose with those by blood eosinophil counts.

Methods

Subjects We included patients with mild to severe asthma (aged ≥18y), recruited by six clinical centres in Europe (Amsterdam, Netherlands; Budapest, Hungary; Catania, Italy; Man- chester, United Kingdom; Rome, Italy; Southampton, United Kingdom). These patients were amongst those recruited for the Unbiased BIOmarkers for the Prediction of RE- spiratory Disease Outcomes (U-BIOPRED)-study within the framework of the Innovative Medicines Initiative (IMI). The first cohort included patients as part of the baseline visit (baseline cohort). A second cohort to validate discriminant models included patients as part of the longitudinal visit (longitudinal cohort). The diagnosis of asthma was defined by a physician’s diagnosis of asthma, including a

history of wheeze, together with reversibility in FEV1 of at least 12% and 200mL and/or

airway hyperresponsiveness (PC20 methacholine < 8 mg/mL) and/or diurnal variation in

peak flow and/or a decrease in FEV1 of at least 12% and 200 mL within four weeks after tapering of treatment. Patients with mild-moderate asthma were on low to moderate dose of inhaled corticosteroids (ICS) (≤500mcg fluticasone propionate (FP) or equivalent) and were controlled or partly controlled according to GINA guidelines (32). Patients with severe asthma were diagnosed according to the IMI-criteria (33): patients used high dose ICS (≥1000mcg FP or equivalent) plus at least one other controller medication and were uncontrolled according to GINA guidelines (32) and/or had frequent severe exacerbations (≥2 per year) and/or required prescription of daily or alternate day oral corticosteroids (OCS) to achieve asthma control. Patients were excluded if they had had a severe asthma exacerbation in the previous month prior to the study visits. Fur- thermore, smokers or ex-smokers with a smoking history ≥5 pack years were excluded

222 Chapter 6 among the patients with mild asthma only. The clinical methods and entire adult cohort of the U-BIOPRED study have recently been published (34). The study was approved at all local Medical Ethics Committees and all patients gave their written informed consent. The study was registered on ClinicalTrials.gov, Identifier: NCT01982162.

Design During this multicenter study, all patients visited the hospital for a screening visit and a baseline study visit. First, inclusion and exclusion criteria were examined. Next, exhaled breath was collected for eNose analysis, lung function was performed, peripheral blood was collected and sputum was induced by hypertonic saline. The longitudinal visit was planned 12-18 months after the baseline visit and included identical procedures as the baseline visit.

Measurements

Lung function and blood eosinophil counts Spirometry was performed according to ATS/ERS recommendations (35). Peripheral blood eosinophil counts were obtained from standard complete blood counts done at each centre locally.

Exhaled breath collection Exhaled breath was collected locally at each site as previously described (25;36). In short, patients breathed normally for five minutes through a mouthpiece connected to a three-way non re-breathing valve and an inspiratory VOC-filter (A2, North Safety, NL). Next, the patient exhaled one vital capacity volume into a 10 L Tedlar bag (SKC Inc, Eighty Four, PA, USA). The content of the Tedlar bag was drawn through stainless steel desorption tubes packed with Tenax (Tenax GR SS 6mm x 7” (Gerstel), SS compression cap (Swagelok)) by a peristaltic pump. Tubes were sent to Amsterdam for desorption of VOCs using a thermal desorption oven (Gerstel TDS 3) and transferred into a Tedlar bag with nitrogen as carrier gas. Subsequent analysis by a composite eNose platform was carried out. Storage of VOCs has been shown to preserve the eNose signal (37). The eNose platform consists of five eNoses from four different brands, using distinct measurement technologies (38): 1) two Cyranoses C320 (Smiths Detection Inc., Pasadena, CA, USA) using carbon-polymer sensors (39), 2) one Tor Vergata TEN (University of Tor Vergata, Rome, Italy) using quartz microbalance metalloporphyrins sensors (40), 3) one Common Invent eNose (Common Invent B.V., Delft, The Netherlands) using metal oxide semiconductor sensors (41), and 4) one Lonestar (Owlstone Nanotech Ltd., Cambridge, UK) based on field asymmetric

Exhaled Breath Profiling in Asthma 223 ion mobility spectrometry (42). Preliminary within-sample repeatability data showed a relative percentage difference in sensor deflection of 6.21% (43).

Inflammatory status Induced sputum was collected according to a standardized protocol (44). Selected plugs were processed with 0.1% DTT and differential cell counts were expressed as percentage of non-squamous cells. Cells were counted centrally (AMC, Amsterdam, The Netherlands) by the same certified technician, and 10% of the cell counts were validated by a second independent technician. According to previous literature, we used a sputum eosinophil count of 3% as cut-point to define eosinophilic or non-eosinophilic airway inflammation for our primary analysis (7). Since others have reported different cut-points, additional discriminate analysis was done using a sputum eosinophil count of 2% as cut-off (8).

Statistical analysis SPSS (V.22.0; IBM Corp, Armonk, NY, USA) and R (V.3.01; R Foundation for Statistical Com- puting, Vienna, Austria) (45) were used for data analysis. One of the Cyranoses had missing values from three subjects because of technical problems. Since the eNose platform includes two Cyranoses, we decided to exclude data from the Cyranose with missing values. Owlstone Lonestar sensors were included if more than 10% of the subjects had ion currents three times the noise level, which is considered 0.02. Batch effects were adjusted for using empirical Bayes methods (46). The eNose sensor data was normalized to the same scale with a mean of 0 and standard deviation of 1. Data were transformed in case of non-normal distribution. The relationship between sputum eosinophil percentages and blood eosinophil counts were analysed using Pearson’s correlation coefficient. Subsequently, a t-test was used to test for significant relationships between sensors and eosinophilic or non-eosinophilic airway inflammation. The significantly associated sensors (unadjusted p-value<0.05) were further analysed for variable selection and model fitting using sparse partial least squares regression of which tuning parameters were chosen by 10-fold cross-validation (47). The discrimination performance of the retrieved model was determined by receiver operating characteristic (ROC) curve analysis and externally validated in the longitudinal cohort (48). Furthermore, similar analysis was done for blood eosinophil counts and for the combination of eNose and blood eosinophil counts.

Results

Complete data were available for 104 study visits. This included 58 patients in the baseline cohort, and 46 in the longitudinal validation cohort, of which 20 patients were

224 Chapter 6 included in both cohorts. Baseline characteristics are presented in Table 1. Patients featuring the presence or absence of eosinophilic airway inflammation from the baseline cohort did not differ with regard to clinical characteristics, except for oral steroid usage (see Table 1).

Table 1. Baseline characteristics Baseline Cohort Longitudinal Cohort EO ≥3% EO <3% EO ≥3% EO <3% N=58 N=46 N=32 N=26 N=19 N=27 Age (years)# 54 (13.8) 56.1 (13.3) 51.4 (14.2) 58.6 (10.9) 59.2 (8.8) 58.1 (12.2) Male gender (%) 39.7 31.3 50.0 47.8 36.8 55.6 OCS use (%) 31.0 43.8* 15.4* 60.9 63.2 59.3 Severe asthma (%) 85 88 81 100 100 100

# Pb predicted FEV1 (%) 80.3 (21.1) 79.7 (21) 81.0 (21.6) 70.1 (21.1) 68.9 (15.8) 70.9 (24.5)

# Pb FEV1/FVC 79.7 (13.6) 76.8 (13.5) 83.2 (13.2) 73.3 (15.1) 71.1 (13.4) 74.8 (16.3)

† FENO (ppb) 29.0 37.5 20.0 29 39.0 20.0 (14.0−53.5) (27.5−76.5)* (10.5−29.3)* (17.8−52.1) (25.0−76.0)* (13.5−34.0)* Blood eosinophils 0.30 0.41 0.19 0.30 0.43 0.25 (×109/L)† (0.13−0.52) (0.23−0.57)* (0.10−0.38)* (0.11−0.47) (0.24−0.58)* (0.06−0.41)* Sputum eosinophils 5.0 15.7 1.13 2.1 17.7 0.74 (%)† (1.2−20.2) (9.1−28.6)** (0.34−2.25)** (0.56−12.9) (6.2−41.8)** (0.19−1.66)** # Mean (SD); † Median (IQR). *t-test p<0.05; **t-test p<0.001. EO, sputum eosinophils; Pb, post-bronchodi- lator; OCS, oral corticosteroids

Prediction of eosinophilic airway inflammation using the eNose platform Using 3% sputum eosinophils as criterion for the diagnosis of eosinophilic and non-eosinophilic asthma, the t-test identified 13 out of 84 eNose sensors as potential biomarker predictors that were analysed for model fitting. Subsequently, the diagnostic accuracy of this model described as area under the receiver operating characteristic curve (AUC), was 73% (95% CI 0.60 to 0.87) in the baseline cohort, (see Figure 1). Validation of this model in the longitudinal cohort produced an AUC of 78% (95% CI 0.64 to 0.92) (see Figure 1). Additionally, using 2% sputum eosinophils as criterion, 14 eNose sensors were identified as potential predictors, producing an AUC of 73% (95% CI 0.58 to 0.88). External validation of this model in the longitudinal cohort resulted in an AUC of 68% (95% CI 0.52 to 0.84) (see Figure 1). The sensitivity, specificity, positive predictive values and negative predictive values using the eNose to predict eosinophilic airway inflammation are presented in Table 2. Overall, there were nine identical eNose sensors included as predictors in both models.

Exhaled Breath Profiling in Asthma 225 Threshold = 3% sputum eosinophils Threshold = 2% sputum eosinophils 100 100 Sensitivity (% ) Sensitivity (% )

Baseline AUC=73.4% Baseline AUC=72.7% Validation AUC=77.8% Validation AUC=68.2% 0 2 0 4 0 6 00 8 0 2 0 4 0 6 0 8 0

100 80 60 40 20 0 100 80 60 40 20 0 Specificity (%) Specificity (%)

Figure 1A. ROC curve analyses Figure 1B. ROC curve analyses ROC curve analyses of eNose sensors for the as- ROC curve analyses of eNose sensors for the assess- sessment of eosinophilic airway inflammation in ment of eosinophilic airway inflammation in spu- sputum, using 3% sputum eosinophils as thresh- tum, using 2% sputum eosinophils as threshold, as old, as obtained in the baseline cohort and validat- obtained in the baseline cohort and validated in the ed in the longitudinal cohort. AUC, area under the longitudinal cohort. AUC, area under the receiver op- receiver operating curve. erating curve.

Prediction of eosinophilic airway inflammation using blood eosinophil counts Sputum eosinophil differential cell counts were positively associated with blood eosinophil counts (r=0.54, p<0.001). The accuracies of blood eosinophil counts to differentiate sputum eosinophilia in the baseline and longitudinal cohorts at 3% and 2% sputum eosinophils exhibited similar ranges as those observed for eNose (Table 2). The best combination of sensitivity, specificity, positive predictive values and negative predictive values using a blood eosinophil count cut-off of 0.22×109 cells/L are also shown in Table 2.

Combining eNose and blood eosinophils When eNose and blood eosinophils were combined in the same model using the baseline cohort, the prediction of sputum eosinophilia slightly improved towards an AUC of 83% (95% CI 0.71 to 0.94) and 81% (95% CI 0.69 to 0.94) for sputum eosinophil counts of 3% and 2%, respectively (Figure 2).

226 Chapter 6 Table 2. ROC parameters eNose platform Blood eosinophil cut-off: 0.22×109 cells/L Threshold sputum eosinophils 3% 2% 3% 2%

Baseline AUC 73 73 69 72 Baseline sensitivity 88 82 81 80 Baseline specificity 58 63 56 67 Baseline PPV 72 82 70 84 Baseline NPV 79 63 70 60 Longitudinal AUC 78 68 75 86 Longitudinal sensitivity 74 60 76 83 Longitudinal specificity 70 71 54 70 Longitudinal PPV 64 71 52 76 Longitudinal NPV 79 60 78 78 PPV, positive predictive value; NPV, negative predictive value

eNose & blood eosinophils 100

Figure 2. ROC curve analyses ROC curve analyses of the combination of eNose sensors and blood eosinophil count for the assessment of eosinophilic airway inflammation in spu- Sensitivity (% ) tum as obtained in the baseline cohort. Sputum eos, sputum eosinophils.

Threshold=3% sputum eos Threshold=2% sputum eos 0 2 0 4 0 6 0 8 0

100 80 60 40 20 0 Specificity (%)

Discussion

The results of this study show that VOCs analysed by eNoses have diagnostic potential for detecting eosinophilic airway inflammation in asthma. The eNose platform was able to discriminate between eosinophilic and non-eosinophilic asthma which was validated at the second study visit one year after. These findings suggest that eNoses could be used for the non-invasive assessment of the eosinophilic profile of asthma, which can improve and facilitate the guidance of individualized asthma treatment.

Exhaled Breath Profiling in Asthma 227 To our knowledge, this is the first multicentre study analysing breathprints by different types of eNoses to find surrogate markers for sputum eosinophils in patients with asthma. Our results support and extend recent studies that were able to identify eosinophilic inflammation by GC-MS breath analysis in asthma (27) and COPD (28;29). Even though these GC-MS results merit subsequent validation in other larger cohorts, they can be regarded as independent confirmation that exhaled VOCs capture eosinophilic airway inflammation. The eNose appeared to have similar accuracies as blood eosinophil cell counts in the prediction of sputum eosinophil percentages varying between 68- 78% depending on the threshold of sputum eosinophils. This confirms previous data showing modest to high diagnostic accuracies of blood eosinophils to predict sputum eosinophil percentages (2;13;14;17;49;50). Notably, the accuracies slightly improved when combining eNose and blood eosinophils in the same model. This suggests that eNose and blood eosinophils represent partly complementary information with regard to the presence or absence of sputum eosinophilia. We believe the strength of this study is that we validated our results by using two visits separated by 12-18 months and by partially including different patients. Therefore, these two study visits were regarded as being sufficiently distinct, in order to pursue independent validation. Moreover, reanalysing our data using only unique samples (n=26) for a true external validation resulted in an AUC of 78% (95% CI 0.59 to 0.97) and 65% (95% CI 0.41 to 0.89) using sputum eosinophil counts of 3% and 2%, respectively. Another potential strength is the inclusion of patients with a wide range of asthma severity in six different centres from four different countries, thereby reducing potentially confounding effects of geographical locations on VOCs (51). Furthermore, the eNose platform enabled centralised analysis of breathprints by multiple sensor systems in parallel (from 4 different types of eNoses), which took the benefit of combining distinct sensor technologies. This maximized the differential sensor distribution of exhaled VOCs and thereby the potential of successful pattern recognition. In addition, all centres were trained to carry out sputum induction, sputum processing, and the collection and transport of exhaled air in the same way in order to minimize external influences on the sputum and breathprints. Finally, sputum differential cells were counted and reproduced centrally by the same experienced analysts. A total of 13 and 14 amongst 84 eNose sensors were significantly different between patients with high and low sputum eosinophils depending on the sputum eosinophils cut- off values. The fact that nine identical eNose sensors were significantly different using both cut-offs and that external validation reproduced similar accuracies substantiates our findings. The most discriminative sensors comprised metal oxide semiconductor sensors and the field asymmetric ion mobility spectrometer. This indicates that various technologies may still be required to obtain discriminative eNose data in the clinical setting. In order to optimize eNose performance it is warranted to tailor the various sensors

228 Chapter 6 towards the VOCs of interest, in this case those VOCs that are associated with eosinophilic airways inflammation. Based on an earlier GC-MS study in asthma this comprises for instance alkanes (27). Specific sensor development for such individual components is challenging, but not unrealistic (52). The predictive accuracy for sputum eosinophilia by the eNose platform showed moderate results with areas under the ROC curve of 68-78%. These values are definitely suboptimal, however they serve as impetus for further studies of increased sample size.

Furthermore, these accuracies are similar to those obtained by FENO in asthma (15-17), which has led to the usage of FENO as surrogate marker of sputum eosinophils in recent studies with novel targeted treatments in asthma (53). Similarly, blood eosinophils are increasingly used for the phenotyping of patients in clinical trials (53;54) based on comparable levels of accuracy for sputum eosinophilia (14). The present data show that the combination of eNose and blood eosinophil data leads to somewhat improved predictive accuracy. This suggests that easily available biomarkers such as exhaled air and peripheral blood together provide adequate information for replacing sputum induction in the phenotyping of eosinophilic asthma. Notably, in the present study we have reported the best combination of sensitivity, specificity, positive predictive values and negative predictive values. However, the model could be tailored to a clinical application where a higher positive predictive value is preferable, for example in a study design for novel therapies (49). Although previous studies on the diagnostic accuracy of eNoses for asthma and COPD were unlikely to be largely influenced by the use of inhaled corticosteroids or long- acting bronchodilators (25;55), it cannot be excluded that such treatment may have affected the exhaled profiles of patients. In the present study, significantly more patients with eosinophilic asthma used daily or alternate day oral corticosteroids as compared to non-eosinophilic asthma (see Table 1). Nevertheless, 56% of patients with high sputum eosinophilia did not require oral steroids. Therefore, it is unlikely that the diagnostic accuracy of the eNose sensors to differentiate eosinophilic and non-eosinophilic inflammation was driven by oral steroids usage. The present results suggest that the exhaled breath of patients with asthma contain metabolites that are directly related to, or are a product of eosinophilic airway inflammation. The presence of sputum eosinophils in asthma reflects underlying airway pathology, and it predicts treatment response and exacerbation rate (2-9;56). Therefore, it is likely that different inflammatory processes in the airways of patients with varying subtypes of asthma generate partially distinct volatile metabolites. The individual VOCs found previously by GC-MS to be associated with sputum eosinophilia differed between asthma and COPD (27;28), thereby suggesting that eosinophil-related VOCs are disease- specific as well. Apparently, the eNose platform sensors are capturing these biomarkers, but they are principally unable to identify the individual VOC. The latter is not required

Exhaled Breath Profiling in Asthma 229 for medical decision making per se, but is certainly needed when investigating the underlying pathophysiological mechanisms. Specific analysis by GC-MS will then be necessary in order to unravel the identity of the combination of VOCs that are driving the prediction of eosinophilic inflammation. The discriminant accuracies of VOCs to assess eosinophilic airway inflammation can have diagnostic implications. The analysis of exhaled air by eNoses is a relatively easy, non-invasive technique with prompt results in comparison with sputum induction and processing. Thus, it could provide a surrogate for sputum eosinophils in the phenotyping and monitoring of asthma patients (9), particularly with regard to excluding sputum eosinophilia of 3% or more, since the sensitivity of the eNose for this was 88%. Inter- estingly, a recent proof of concept trial indicated that eNose breathprints can indeed predict clinical efficacy by oral steroids in asthma, being even more accurate than sputum eosinophils or exhaled nitric oxide in patients (30). In addition, exhaled molecular profiles have shown potential in the clustering of asthma phenotypes (31). This suggests that composite biomarker fingerprints will become a powerful alternative to single cell or single molecule approaches in the management of asthma. In conclusion, we demonstrated that VOCs measured by eNoses can discriminate eosinophilic from non-eosinophilic airway inflammation, which was validated in an independent data set. These data warrant further development of tailored eNose sensors and validation in larger cohorts in order to substantiate the accuracy of eNoses in establishing the eosinophilic phenotype amongst patients with asthma. Taken together, our data suggest that eNose breathprints have potential to provide a quick and simple alternative to the assessment of sputum eosinophilia in asthma, thereby facilitating phenotyping and personalized asthma treatment.

230 Chapter 6 References

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234 Chapter 6 CHAPTER 7 Summary and General Discussion

Summary

Background Asthma is considered a complex respiratory disease of which various asthma phenotypes are being discovered. Clinical biomarkers have shown to be successful in the management of asthma phenotypes. However, to increase the understanding of this complex disease and discover new biomarkers, will require knowledge of the molecular mechanisms involved. High-throughput omics technologies are now available, such as transcriptomics, proteomics, lipidomics, and breathomics. Using these methods will allow further understanding of complex diseases such as asthma, and will potentially offer biomarker discovery (1). In this thesis, I have reviewed the strengths and limitations of both transcriptomics analysis and breathomics analysis, and I have applied both technologies to increase understanding and discover surrogate biomarkers. Furthermore I have validated previously examined biomarkers.

Conclusions of the studies

Towards composite molecular signatures in the phenotyping of asthma In chapter 2 I discussed the strengths and limitations of transcriptomics by microarrays and next-generation RNA sequencing. Next, I reviewed metabolomics in exhaled air (breathomics) as a non-invasive tool for the clinic.

Main conclusions: • For signature discovery, transcriptomics analysis using microarrays is at present the- state-of-the-art method, because of available data for comparisons and validation, and its maturity of experimental design and analysis. • When experience has increased and costs have decreased, RNA sequencing will become preferable since it allows an unbiased analysis and enables higher dynamic detection ranges. • Breathomics has diagnostic potential as a non-invasive method, though sampling methods and devices still need to be standardised to enable validation.

Implications: Composite molecular fingerprints have the best prospect as biomarkers in the phenotyping of patients with complex respiratory diseases such as asthma.

Summary and Discussion 237 The impact of allergic rhinitis and asthma on human nasal and bronchial epithelial gene expression In chapter 3 I studied the link between the upper and lower airways by analysing gene expression profiles of upper and lower airway epithelial cells in healthy individuals and examining the impact of allergic rhinitis and asthma on these expression profiles.

Main conclusions: • There were substantial differences in gene expression between the upper and lower airway epithelium of healthy individuals but many of these differences disappeared in patients with allergic rhinitis with or without asthma. • Genes that were influenced by allergic rhinitis and asthma were related to lung development, remodelling, regulation of peptidases and normal epithelial barrier function. • Our unbiased approach identified genes, such as UDP-glucuronosyltransferase genes and RUNX2 that have not been previously described in relation to allergy, rhinitis or asthma. • Allergic rhinitis affected the epithelial gene expression in both the upper and lower airway epithelium.

Implications: Differences in epithelial gene expression between upper and lower airway epithelial cells of healthy individuals largely disappeared in patients with allergic rhinitis with or without asthma, with a main impact of allergic rhinitis. Several new genes and pathways were identified that might be potential targets for future drug development.

dsRNA-induced changes in gene expression profiles of primary nasal and bronchial epithelial cells from patients with asthma, rhinitis and controls In chapter 4 I examined the responses of airway epithelium to double-stranded RNA (dsRNA) as a model of viral induced exacerbations. This was done by comparing dsRNA- induced gene expression profiles of primary nasal and bronchial epithelial cells and observing modulation of these expression profiles by the presence of allergic rhinitis and asthma.

Main conclusions: • The dsRNA-induced transcriptional response was characterized by a strong induction of genes involved in the response to virus, apoptotic processes and antigen presentation.

238 Chapter 7 • The airway epithelium of patients with asthma demonstrated significantly fewer induced genes, in particular with regard to impaired interferon expression and reduced down-regulation of mitochondrial genes. • Several disease-specific genes were identified that are induced in patients with allergic rhinitis with or without asthma but not in healthy controls.

Implications: The viral-induced differences in gene expression between upper and lower airways improved the understanding of mechanistic pathways of the mutual interaction between asthma and rhinitis. Furthermore, potential targets for drug-discovery studies were identified, related to mitochondrial dysfunction and interferon signalling.

External validation of blood eosinophils, FENO and serum periostin as surrogates for sputum eosinophils in asthma In chapter 5 the mutual relationship between blood eosinophils, exhaled nitric oxide

(FENO) and serum periostin with sputum eosinophils was quantified by external validation in two independent cohorts of patients with mild to severe asthma.

Main conclusions: • Blood eosinophil count was an accurate surrogate marker for sputum eosinophils in patients with mild to moderate asthma and this relationship was replicated in patients with severe asthma. • Serum periostin was not able to differentiate between eosinophilic and non-eosinophilic airway inflammation.

• When combining the three markers, neither FENO nor periostin showed any improvement to the diagnostic value of blood eosinophils.

Implications: Blood eosinophil cell count represented an accurate biomarker for eosinophilic airway inflammation which can facilitate guidance of current and novel individualised asthma treatment.

Predicting eosinophilic airway inflammation in asthma using exhaled breath profiling In chapter 6 the relationship of breathprints analysed by a composite electronic nose (eNose) platform with sputum eosinophils was validated in patients with mild to severe asthma.

Summary and Discussion 239 Main conclusions: • The eNose platform was able to differentiate between eosinophilic and non-eosinophilic airway inflammation in asthma, which is validated at a second visit. • Blood eosinophil cell counts showed similar discriminant accuracies.

Implications: ENoses have potential to assess eosinophilic airway inflammation in patients with asthma in a quick and non-invasive way, thereby potentially facilitating personalized asthma management.

General Discussion

Transcriptomics

Transcriptomics analysis using microarrays In chapters 3 and 4 I used transcriptomics analysis by microarrays to explore gene expression in airway epithelial cells with an unbiased approach. Unlike gene sequencing though, microarrays are limited to known RNA transcripts and therefore these analyses are not completely unbiased (2), as is discussed in chapter 2. Still, expression of more than 33,000 well-characterized RNA probes can be analysed by microarrays, which was shown to be promising in the biomarker discovery in pulmonary diseases.

Transcriptomics analysis in asthma Recently, distinct phenotypes defined by Th2-high or Th2-low inflammation were identified by gene expression profiling of bronchial epithelial cells from patients with mild to moderate asthma using microarrays (3). Following these results, patients with severe asthma appeared to benefit from anti-interleukin-13 treatment if serum periostin levels were high, which corresponds to the Th2-high phenotype (4). Subsequently, anti-interleukin-4 receptor treatment seemed successful in patients with moderate to severe asthma with increased sputum or blood eosinophils (5), which appeared to identify patients with Th2-high asthma (6). Furthermore, induced sputum gene expression profiles identified three phenotypes related to both clinical asthma status and airway inflammation (7). This showed the potential of this technology to have additive value in clinical phenotyping. Additionally, analysing gene expression improved our understanding of disease mechanisms underlying the associations between airway inflammation and systemic inflammation. Gene profiling of induced sputum from asthmatics with systemic inflammation showed upregulation of signalling pathways involved in particularly neutrophilic inflammation (8). Also, mechanisms of treatment resistance in

240 Chapter 7 asthma were studied by gene profiling bronchoalveolar lavage cells of patients with corticosteroid-resistant asthma and corticosteroid-sensitive asthma. This revealed involvement of endotoxin (LPS) and classical macrophage activation in corticosteroid resistance (9). Taken together, transcriptomics analysis in pulmonary disease was shown to be promising in biomarker discovery and in improving our understanding of asthma.

Sample method In chapters 3 and 4 I explored gene expression profiles of both upper and lower airway epithelial cells from subjects with allergic asthma, allergic rhinitis, and healthy controls. I chose to isolate and culture epithelial cells only, without the influences of other cell types. Of course, extracted and cultured cells will not exactly represent the same conditions in tissue. Alternative procedures to obtain epithelial cells such as direct measurement after isolation or laser capture might mitigate these effects of cell culturing, but could introduce new biases introduced by contamination by other cell types or the isolation procedure itself. Air-liquid interface induces differentiation into a pseudostrati- fied mucociliary epithelium resembling thein vivo appearance of the airway epithelium. Nevertheless, this still cannot ensure that the in vivo expression profile is fully preserved after differentiation ex vivo. Other studies used whole biopsies to study airway gene expression. However, by using entire biopsies it is not clear how the different cell types contribute to the gene expression since every biopsy contains different types and numbers of cells. Hence, every method has its strengths and limitations, and there is no consensus on the most desirable sample method. Standardisation of these method procedures would improve the ability to compare and validate results.

Transcriptomics analysis in this thesis In both studies the unbiased analysis identified several new genes that were influenced by allergic rhinitis and asthma, and also confirmed the role of previously described genes. Since microarrays produce such large datasets I used different techniques in both studies to enable interpretation. In chapter 3 I used K-means clustering to reduce the data into subgroups and to be able to differentiate patters of gene expression between the different cohorts. In this way we were able to see the impact of allergic disease, in particular of allergic rhinitis, on the gene expression differences between upper and lower airways. Furthermore, I made use of overrepresentation of gene ontology groups. A regulation interaction network discovery was performed to study the function and relationships between differential expressed genes. In chapter 4 I mainly focused on the overrepresentation of gene ontology groups because of so many differentially expressed genes after dsRNA-stimulation. In chapter 3 one of the conclusions was that in a healthy state considerable differences exist in gene expression between nose and bronchus. However, in case of allergic rhinitis

Summary and Discussion 241 many of these differences seemed to disappear, especially in case of allergic asthma with concomitant rhinitis. Using K-means clustering I demonstrated that gene expression in the lower airways of patients with allergic rhinitis was altered as well, which suggested a major impact of allergic disease. This also suggested interaction between the upper and lower airways in patients with allergic asthma and/or allergic rhinitis (10). Previ- ously, gene expression of allergic nasal epithelial cells in response to house dust mite showed smaller changes as compared to healthy epithelial cells, which was explained by an activated state of allergic nasal epithelium before stimulation (11). Therefore, the diminished differences between gene expression of upper and lower airway epithelium in allergic disease could be explained by this activated state of genes in both upper and lower airways, and thereby reducing differences. In chapter 4 a considerable loss in dsRNA-induced down-regulation of mitochondrial genes was observed in both upper and lower airways of patients with allergic asthma with concomitant rhinitis. However, I did not see this effect in patients with allergic rhinitis, suggesting changed host characteristics of the upper airways in patients with allergic rhinitis plus asthma as compared to those with allergic rhinitis alone. Again, this supported mutual interaction between upper and lower airways of patients with asthma and rhinitis. Furthermore, a considerable proportion of the most highly up-regulated genes in all three groups were interferon-related genes. Nevertheless, interferon-β1 and interferon-λ3 were induced in all subjects except for patients with asthma. This is in line with previous studies reporting reduced interferon-β and interferon-λ in primary bronchial epithelial cells from those patients with asthma following rhinovirus-infection (12;13). However, in a very recent report the same group failed to find any evidence for deficient type I or III interferon induction in rhinovirus-infected primary bronchial epithelial cells from patients with asthma (14). They speculated on the relation with asthma severity that these patients were too mild for a difference to be detected. However, in our study patients with asthma had even milder disease when comparing medication usage. The reason for this contrast in data is unknown. Recently, a study showed impaired interferon induction by bronchial epithelial cells following rhinovirus infection if these cells were pretreated with interleukin-4 (IL-4) and interleukin-13 (IL-13) prior to infection, suggesting that enhanced Th2 inflammation can dampen the antiviral response (15). This shows the need for further studies to validate and improve the understanding of the complex interactions in these signalling pathways.

Biased surrogate markers for sputum eosinophils Asthma phenotyping started a long time ago using a biased approach, identifying allergic and nonallergic asthma (16). Subsequently, based on sputum differential cell counts, inflammatory subtypes were identified (17) with clinical consequences (18). Since sputum eosinophil count is considered an important clinical biomarker, many

242 Chapter 7 studies have tried to find surrogate markers because sputum analysis is hindered by the duration of the analysis and the possible failure of producing an adequate sample. Furthermore, in patients with severe and uncontrolled asthma, who are exactly those of which the inflammatory profile is of interest for treatment adjustments, the procedure can cause unwanted hypertonic saline-induced airway narrowing (19). Several surrogate markers have been considered, such as FENO, blood eosinophils, and serum periostin. However, blood eosinophils and FENO have shown varying correlations with sputum eosinophils (20-24). FENO demonstrated insufficient capacity to monitor steroid therapy (18), although this was challenged by a recent positive study in primary care and a different study using an improved algorithm to successfully reduce exacerbations by FENO-guided therapy (25;26). In chapter 5 I concluded that blood eosinophil count is an adequate surrogate marker for sputum eosinophils in mild to moderate asthma, and these findings were replicated in a cohort with more severe asthma. However, a very recent meta-analysis concluded that blood eosinophil count has only moderate diagnostic accuracy as a single surrogate marker for airway eosinophilia (27). But perhaps more importantly, two recent trials using anti-IL-5 (mepolizumab) to target eosinophilic airway inflammation in patients with severe asthma, defined by blood eosinophils, resulted in a significant reduction in the daily requirement of oral glucocorticoids, reduced exacerbations and improved asthma symptoms (28;29). In a different large study using anti-IL-5, blood eosinophil count predicted the efficacy of reducing exacerbations in patients with severe eosinophilic asthma (30). These trials support the potential role of blood eosinophil count as a non-invasive marker to predict responsiveness to novel personalised therapies. Obviously, finding the best biomarkers to identify individual patients most appropriate for a targeted therapy is the ultimate goal, instead of determining the best surrogate marker for sputum eosinophilia. In other words, a moderate surrogate marker for sputum eosinophils might perform better as biomarker itself to predict treatment responsiveness. Finally, serum periostin has showed high diagnostic accuracy to identify sputum eosinophils (31) but these results had not been replicated yet. Therefore, chapter 5 was the first to validate serum periostin as biomarker for eosinophilic airway inflammation, a relationship that we did not find in the mild to moderate cohort nor in the more severe patients with asthma. Periostin might be more related to IL-13 instead of sputum eosinophils, because the protein is partly regulated by IL-13 (32) and was shown to be predictive in the treatment response to anti-IL13 medication (4). As IL-13 is a Th2 cytokine, it is not surprising that periostin will correlate with sputum eosinophils in some patients. Taken together, it seems that variation exist within patients with a Th2-phenotype or high sputum eosinophils regarding levels of IL-13 and periostin. Therefore it seems that periostin may have complementary information to sputum or blood eosinophils in identifying patients with specific profiles based on a Th2-high cytokine profile.

Summary and Discussion 243 Breathomics

Breathomics analysis using eNoses In chapter 6 I have used eNoses to measure metabolites in the exhaled air that are potential non-invasive biomarkers of disease. These metabolites or volatile organic compounds (VOCs) originate from both local and systemic metabolic processes. The gold-standard for exhaled breath analysis is gas chromatography-mass spectrometry (GC-MS), which identifies individual molecular compounds by determining the composition and the concentration of the component (33). Unlike GC-MS, eNoses analyse VOCs using pattern recognition by arrays of nanosensors that capture various combinations of VOCs (34). Before implementation of eNoses in clinical practice can be accomplished, the pattern recognition algorithms require training and staged validation. There are different types of VOC-sensors, such as organic polymers, quartz crystals, metaloxide, and ion mobility spectrometry. The choice of sensors will influence the suitability of the eNose in the phenotyping or diagnosis of a specific disease. However, it is still unknown what type or combination of sensors is best in detecting which disease. Therefore, a composite eNose platform, used in chapter 6, was developed for the U-BIOPRED study group that integrates different types of eNose sensors to measure breathprints in parallel. Metal oxide semiconductor sensors and the field asymmetric ion mobility spectrometer were the most discriminative sensors to assess eosinophilic airway inflammation. To improve the discrimination performance of the eNose, a tailor made eNose should be developed to detect those VOCs that are specifically associated with eosinophilic airway inflammation, or eventually with treatment responsiveness. The eNose has already showed potential in predicting corticosteroid responsiveness in a small cohort of patients with asthma (35).

Breathomics analysis in asthma Breathomics research in pulmonary diseases is rapidly expanding, especially concerning lung cancer, infectious and airway diseases (36). ENose studies in asthma have shown that eNoses can discriminate patients with asthma from healthy controls (37), and from those with COPD (38). Moreover, a subsequent external validation study showed that patients with fixed asthma and COPD can be discriminated using exhaled breath pattern recognition based on the previous training set (39). These previous studies mainly focus on disease diagnosis, though the results of chapter 6 indicate additive value of the eNose in asthma phenotyping. This is supported by GC-MS studies that were able to identify eosinophilic inflammation in asthma (40) and COPD (41;42), whilst a recent study showed potential in asthma clustering (43). The eNose platform was able to discriminate eosinophilic from non-eosinophilic asthma with an ROC area under the curve (AUC) of 73%, and validation of the model in the longitudinal cohort resulted in an

244 Chapter 7 AUC of 78%. Blood eosinophils showed nearly similar discriminant values. Interestingly, when adding blood eosinophils to the predictive model of the eNose the AUC increased slightly to 83%. This difference in AUC is probably not significantly different but may suggest that VOCs, small molecules, and systemic markers all reflect different aspects of eosinophilic inflammatory pathways. This is in line with a recent study in which FENO and blood eosinophils were independently associated with wheeze and asthma events (44). Therefore, composite marker signatures might perform better than single biomarkers in the phenotyping of asthma. A recent study identified the eNose as predictor for steroid responsiveness in asthma, being more accurate than sputum eosinophils or FENO (35). Unfortunately these authors did not show the results of adding sputum eosinophils or

FENO to the predictive model of the eNose, which could have improved the predictive value. On the other hand, the eNose data themselves represent a composite molecular signature which supports the concept that composite biomarker fingerprints are more powerful than single biomarkers.

Validation Regardless of the technique chosen and whether the aim is to find a biomarker or composite marker signature to diagnose or phenotype disease, validation of tools and results is required based on international guidelines on STAndards for the Reporting of Diagnostic accuracy studies (STARD) (45) and the very recent published Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) (46). First of all, internal validity of a test or new application should be determined and possible introduction of bias should be considered, after which external validation is necessary. When we focus on the microarray analysis in chapter 3 and chapter 4, expression values can be validated using RT-qPCR. In this thesis, nine differentially expressed genes were identified for RT-qPCR validation in both chapters since these genes represented a complete range of fold change values. Since there were differences in sample sizes between the groups and in distribution of age and gender, I re-analysed the data randomly excluding one subject from each of the other groups and tested for associations with gender and age to exclude bias. Next, internationally accepted criteria were used for the diagnosis of allergic rhinitis and asthma. Unfortunately, further internal validation tests such as cross validation were impossible since the cohort was too small to split in training and validation sets. The ultimate test now will be external validation in large cohorts, such as U-BIOPRED (Unbiased BIOmarkers in PREDiction of respiratory disease outcomes) (www.ubiopred.eu). In chapters 5 and 6 I tested surrogate markers for sputum eosinophils. In order to evalu- ate diagnostic accuracy the selection of subjects in whom the markers are being tested is crucial. Current guidelines recommend using the golden standard to discriminate

Summary and Discussion 245 between patients with the targeted condition and those without it (45). Therefore the cohorts included in chapters 5 and 6 were well-characterised and stringent criteria for the diagnosis of asthma were used.

In chapter 5 blood eosinophils, FENO and serum periostin were externally validated in a large cohort of mild to moderate asthma and this was replicated in a smaller cohort

of severe asthma. Blood eosinophils and FENO were measured using devices that meet the recommended technical specifications for measurements according to the STARD guidelines, whereas serum periostin and sputum eosinophils were measured by assays that do not meet this standard. Such a technically recommended assay for sputum eosinophils does not exist, and the quality of processing is especially dependent on the experiences of the technician. The processing of sputum and cell counts for the two cohorts from chapter 5 was done by the same experienced technicians. Moreover the correlation between sputum eosinophils and blood eosinophils was consistent and the fact that we were able to reproduce our results in a second independent cohort represents a major validation. Since the size of the cohort of patients with severe asthma was limited, further analysis in large multicentre severe asthma cohorts is required. However, the pitfall of such multicentre studies is bias because of potential differences in qualities and experience levels of technicians between centres. Multicenter studies therefore demand adequate training in advance. Finally, to measure serum periostin we used two different assays that showed similar results, one of which was used in the single previous study that demonstrated the highest AUC for serum periostin to diagnose airway eosinophilia (31). The results presented in chapter 6 show the discriminative ability of the eNose platform to distinguish patients with eosinophilic airway inflammation from patients with non- eosinophilic airway inflammation. Previous studies using GC-MS breath analysis have already showed that exhaled VOCs can identify eosinophilic airway inflammation (40- 42) which could be regarded as internal validation. Next, a largely independent second cohort was used to externally validate the retrieved model. Taken together, I used several ways or techniques in order to improve the quality of results presented in this thesis and potential weaknesses were discussed in every chapter separately.

Future opportunities for research This thesis has addressed several omics technologies to allow further understanding asthma as a complex disease, and to potentially offer biomarker discovery. During the discussion of this thesis I addressed the requirement of future studies for external validation in larger multicentre cohorts. A recent user-friendly, open-access microarray repository was constructed relevant to allergic airway inflammation (47). This database includes the microarray results from chapters 3 and 4, which will increase the use of

246 Chapter 7 these large datasets and will allow validation of genes and further experiments. To increase the quality of transcriptomics analysis, we urged standardisation of techniques and further validation and development of next-generation RNA sequencing, as was discussed in chapter 2. Furthermore, I addressed the potential use of blood eosinophil count and composite molecular signatures to identify patients with asthma that are responsive to novel or existing therapies. First of all, large severe asthma cohorts, such as U-BIOPRED will be required to distinguish asthma profiles with targets per profile for novel treatments. Next, easy-to-measure biomarkers, such as blood eosinophil count and exhaled VOCs need to be discovered that rapidly identify every asthma profile that is sensitive to a certain therapy.

Summary and Discussion 247 References

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248 Chapter 7 (20) Berry MA, Shaw DE, Green RH, Brightling CE, CM, Keene ON, Yancey SW, et al. Oral Wardlaw AJ, Pavord ID. The use of exhaled glucocorticoid-sparing effect of mepolizumab nitric oxide concentration to identify eosino- in eosinophilic asthma. N Engl J Med 2014 Sep philic airway inflammation: an observational 25;371(13):1189‑97. study in adults with asthma. Clin Exp Allergy (29) Ortega HG, Liu MC, Pavord ID, Brusselle GG, 2005 Sep;35(9):1175‑9. FitzGerald JM, Chetta A, et al. Mepolizumab (21) Fleming L, Tsartsali L, Wilson N, Regamey N, treatment in patients with severe eosinophilic Bush A. Longitudinal relationship between asthma. N Engl J Med 2014 Sep 25;371(13): sputum eosinophils and exhaled nitric oxide 1198‑207. in children with asthma. Am J Respir Crit Care (30) Pavord ID, Korn S, Howarth P, Bleecker ER, Buhl Med 2013 Aug 1;188(3):400‑2. R, Keene ON, et al. Mepolizumab for severe (22) Hastie AT, Moore WC, Li H, Rector BM, Ortega eosinophilic asthma (DREAM): a multicentre, VE, Pascual RM, et al. Biomarker surrogates do double-blind, placebo-controlled trial. Lancet not accurately predict sputum eosinophil and 2012 Aug 18;380(9842): 651‑9. neutrophil percentages in asthmatic subjects. (31) Jia G, Erickson RW, Choy DF, Mosesova S, Wu J Allergy Clin Immunol 2013 Jul;132(1):72‑80. LC, Solberg OD, et al. Periostin is a systemic (23) Nair P, Kjarsgaard M, Armstrong S, Efthimiadis biomarker of eosinophilic airway inflamma- A, O’Byrne PM, Hargreave FE. Nitric oxide in tion in asthmatic patients. J Allergy Clin Im- exhaled breath is poorly correlated to sputum munol 2012 Sep;130(3):647‑54. eosinophils in patients with prednisone- (32) Woodruff PG, Boushey HA, Dolganov GM, dependent asthma. J Allergy Clin Immunol Barker CS, Yang YH, Donnelly S, et al. Genome- 2010 Aug;126(2): 404‑6. wide profiling identifies epithelial cell genes (24) Schleich FN, Manise M, Sele J, Henket M, Seidel associated with asthma and with treatment L, Louis R. Distribution of sputum cellular phe- response to corticosteroids. Proc Natl Acad Sci notype in a large asthma cohort: predicting U S A 2007 Oct 2;104(40):15858‑63. factors for eosinophilic vs neutrophilic inflam- (33) Phillips M. Method for the collection and assay mation. BMC Pulm Med 2013 Feb 26;13(1):11. of volatile organic compounds in breath. Anal (25) Honkoop PJ, Loijmans RJ, Termeer EH, Snoeck- Biochem 1997 May 1;247(2):272‑8. Stroband JB, van den Hout WB, Bakker MJ, et (34) Wilson AD, Baietto M. Advances in electronic- al. Symptom- and fraction of exhaled nitric nose technologies developed for biomedical oxide-driven strategies for asthma control: applications. Sensors (Basel) 2011;11(1): A cluster-randomized trial in primary care. J 1105‑76. Allergy Clin Immunol 2015 Mar;135(3):682‑8. (35) van der Schee MP, Palmay R, Cowan JO, Taylor (26) Powell H, Murphy VE, Taylor DR, Hensley MJ, DR. Predicting steroid responsiveness in McCaffery K, Giles W, et al. Management of patients with asthma using exhaled breath asthma in pregnancy guided by measurement profiling. Clin Exp Allergy 2013 Nov;43(11): of fraction of exhaled nitric oxide: a double- 1217‑25. blind, randomised controlled trial. Lancet (36) van de Kant KD, van der Sande LJ, Jobsis Q, 2011 Sep 10;378(9795):983‑90. van Schayck OC, Dompeling E. Clinical use of (27) Korevaar DA, Westerhof GA, Wang J, Cohen JF, exhaled volatile organic compounds in pul- Spijker R, Sterk PJ, et al. Diagnostic accuracy monary diseases: a systematic review. Respir of minimally invasive markers for detection Res 2012;13:117. of airway eosinophilia in asthma: a systematic (37) Dragonieri S, Schot R, Mertens BJ, Le CS, Gauw review and meta-analysis. Lancet Respir Med SA, Spanevello A, et al. An electronic nose in 2015 Apr;3(4):290 ‑300. the discrimination of patients with asthma (28) Bel EH, Wenzel SE, Thompson PJ, Prazma

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250 Chapter 7 CHAPTER 8 Nederlandse Samenvatting

Achtergrond Astma wordt beschouwd als een complexe luchtwegziekte waarvan inmiddels verschillende astma fenotypes zijn gedetecteerd. Klinische biomarkers zijn al succesvol gebleken bij de aanpak van verschillende astma fenotypes. Toch is er meer kennis nodig van betrokken moleculaire mechanismen om deze complexe ziekte beter te kunnen begrijpen en om nieuwe biomarkers te kunnen ontdekken. Inmiddels zijn er meerdere high-throughput omics technieken beschikbaar, zoals transcriptomics, proteomics en breathomics. Deze omics methoden zullen significant bijdragen aan het beter begrijpen van complexe ziektes zoals astma, met mogelijk nieuwe biomarkers tot gevolg. In dit proefschrift heb ik de sterke en zwakke aspecten van transcriptomics en breathomics besproken, en beide technieken gebruikt om kennis te vergroten en om nieuwe biomarkers te ontdekken. Verder heb ik reeds bekende biomarkers gevalideerd.

Conclusies

Towards composite molecular signatures in the phenotyping of asthma In hoofdstuk 2 heb ik de sterke en zwakke kanten van transcriptomics op basis van microarrays en op basis van next-generation sequencing bediscussieerd. Tevens heb ik metabolomics in uitgeademde lucht (breathomics) besproken om als non-invasieve methode te gebruiken in de kliniek.

Bevindingen: • Transcriptomics op basis van microarrays is tot nu toe de state-of-the-art methode gebleken om moleculaire ‘signatures’ te ontdekken, omdat de techniek van deze methode al verder ontwikkeld door de mate van ervaring, en omdat er al veel data van gepubliceerd is om mee te kunnen vergelijken en valideren. • Als er eenmaal meer ervaring is met RNA sequencing en de kosten ervan verminderd zijn zal deze techniek de voorkeur krijgen door het ‘unbiased’ karakter van de analyse en omdat het een groter analyse-bereik heeft. • Breathomics heeft diagnostische potentie doordat het een non-invasieve methode is, maar deze techniek zal eerst gestandaardiseerd moeten worden om validatie mogelijk te maken.

Implicaties: Samengestelde moleculaire ‘fingerprints’ hebben de grootste potentie om als biomarker patiënten met complexe luchtwegziekten te kunnen fenotyperen, zoals patiënten met astma.

Nederlandse Samenvatting 253 The impact of allergic rhinitis and asthma on human nasal and bronchial epithelial gene expression In hoofdstuk 3 heb ik de link tussen de bovenste en onderste luchtweg onderzocht door het analyseren van genexpressie profielen van epitheelcellen uit de bovenste en onderste luchtweg van gezonde vrijwilligers en door de invloed van allergische rinitis en astma op deze expressie profielen te bestuderen.

Uitkomsten: • Er waren substantiële verschillen in genexpressie van epitheel afkomstig uit de bovenste en uit de onderste luchtweg van gezonde vrijwilligers, maar het merendeel van deze verschillen verdwenen bij patiënten met allergische rhinitis met of zonder bijkomend astma. • Genen onder invloed van allergische rhinitis en astma waren gerelateerd aan long- ontwikkeling, remodelling, regulatie van peptidases en aan een normale barrière functie van het epitheel. • Onze benadering heeft meerdere genen geïdentificeerd, zoals UDP-glucuronosyltransferase genen en RUNX2, die niet eerder beschreven zijn in relatie tot allergie, rinitis of astma • Allergische rinitis was van invloed op de genexpressie van epitheel van zowel de bovenste als onderste luchtweg.

Implicaties: Verschillen in genexpressie van epitheelcellen van de bovenste en onderste luchtweg waren grotendeels verdwenen in patiënten met allergische rinitis met of zonder bijkomend astma, door voornamelijk het effect van allergische rinitis. Meerdere verrassende genen en netwerken van genen werden geïdentificeerd die mogelijk potentie hebben voor de ontwikkeling van nieuwe geneesmiddelen.

dsRNA-induced changes in gene expression profiles of primary nasal and bronchial epithelial cells from patients with asthma, rhinitis and controls In hoofdstuk 4 heb ik de reacties van luchtwegepitheel op dubbelstrengs RNA (dsRNA) onderzocht als model voor viraal-geïnduceerde exacerbaties. Hierbij hebben we de dsRNA-geïnduceerde genexpressie profielen van epitheelcellen afkomstig uit de neus en uit de bronchus vergeleken en hebben we het effect van allergische rinitis en astma op deze expressie profielen geanalyseerd.

254 Chapter 8 Uitkomsten: • De dsRNA-geïnduceerde transcriptionele reactie werd gekenmerkt door een sterke inductie van genen die betrokken zijn bij de reactie op virussen, apoptotische processen en antigeenpresentatie. • Het luchtwegepitheel van patiënten met astma induceerde significant minder genen, waaronder een verzwakte interferonexpressie en een verminderde downre- gulatie van mitochondriale genen. • We hebben meerdere ziekte-specifieke genen geïdentificeerd die wel geïnduceerd werden in patiënten met allergische rinitis met of zonder bijkomend astma maar niet in gezonde vrijwilligers.

Implicaties: De gevonden verschillen in viraal-geïnduceerde genexpressie tussen de bovenste en onderste luchtweg hebben bijgedragen aan het beter begrijpen van de onderliggende biochemische processen die betrokken zijn bij de interactie tussen astma en rinitis. Ver- der werden genen gerelateerd aan mitochondriale dysfunctie en interferon signalering geïdentificeerd die mogelijk gebruikt kunnen worden in nieuwe geneesmiddelenstu- dies.

External validation of blood eosinophils, FENO and serum periostin as surrogates for sputum eosinophils in asthma In hoofdstuk 5 heb ik de relatie onderzocht tussen sputum eosinofielen en het aantal eosinofielen in het bloed, het stikstofgehalte in de uitgeademde lucht (FENO) en de hoe- veelheid periostin in het serum door middel van externe validatie in twee onafhankelijke cohorten met patiënten met mild tot ernstig astma.

Uitkomsten: • Het aantal eosinofielen in het bloed bleek een accurate maat voor het gehalte sputum eosinofielen van patiënten met mild tot matig astma en deze relatie hebben we nogmaals laten zien in patiënten met ernstig astma. • Periostin gemeten in het serum kon niet differentiëren tussen eosinofiele en niet- eosinofiele luchtwegontsteking. • De diagnostische waarde van het aantal eosinofielen in het bloed verbeterde niet na

het toevoegen van FENO en/of periostin aan het diagnostische model.

Implicaties: Het aantal eosinofielen in het bloed was een accurate biomarker voor de mate van eosinofiele luchtwegontsteking wat huidige en nieuwe astma behandelingen significant kan ondersteunen.

Nederlandse Samenvatting 255 Predicting eosinophilic airway inflammation in asthma using exhaled breath profiling In hoofdstuk 6 heb ik de relatie gevalideerd tussen sputum eosinofielen en uitgeade- mede lucht van patiënten met mild tot ernstig astma geanalyseerd door een samenge- steld platform van elektronische neuzen (eNoses).

Uitkomsten: • Het platform van eNoses kon differentiëren tussen patiënten met astma met eosinofiele en niet-eosinofiele luchtwegontsteking, wat we gevalideerd hebben tijdens een tweede meting. • Het aantal eosinofielen in het bloed liet een vergelijkbaar onderscheidend vermo- gen zien.

Implicaties: ENoses kunnen snel en op een non-invasieve manier eosinofiele luchtwegontsteking bepalen waardoor eNoses de mogelijkheid hebben om geïndividualiseerde astma behandeling te vergemakkelijken.

256 Chapter 8 APPENDICES

Contributing authors

Academic Medical Center, University of Amsterdam, the Netherlands

Department of Respiratory Medicine Elisabeth H. Bel Paul Brinkman Niki Fens Selma B. de Nijs Marc P. van der Schee Peter J. Sterk Ching Yong Yick Els J.M Weersink

Department of Respiratory Medicine and Experimental Immunology Rene Lutter

Department of Clinical Epidemiology, Biostatistics & Bioinformatics Aeilko H. Zwinderman

Department of Otorhinolaryngology Cornelis M. van Drunen Wytske J. Fokkens Silvia Luiten

Respiratory Therapy Unit, GlaxoSmithKline, London, United Kingdom Ana R. Sousa

Acclarogen Ltd, St John’s Innovation Centre, Cambridge, United Kingdom Aruna T. Bansal

Electronic Engineering, University of Rome “Tor Vergata”, Rome, Italy Arnaldo D’Amico

Center for Integrated Research – CIR, Unit for Electronics for Sensor Systems, Campus Bio- Medico U, Rome, Italy Giorgio Pennazza Marco Santonico

Contributing authors 259 Department of Pharmacology, Faculty of Medicine, Catholic University of the Sacred Heart, Rome, Italy Paolo Montuschi

Clinical and Experimental Sciences, University of Southampton Faculty of Medicine and NIHR Southampton Respiratory Biomedical Research Unit, Southampton, United Kingdom Ratko Djukanovic

Centre for Respiratory Medicine and Allergy, The University of Manchester, Manchester Academic Health Science Centre, University Hospital of South Manchester NHS Foundation Trust, Manchester, United Kingdom; Airways Clinic, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, United Kingdom Stephen J. Fowler

Chapter 2: Conception and design: AH Wagener, CY Yick, PJ Sterk; Design of tables and figures: AH Wagener, CY Yick, P Brinkman, N Fens, PJ Sterk; Principal Investigator and final responsibility: PJ Sterk. AH Wagener, CY Yick, and PJ Sterk drafted and revised the paper. All authors revised the manuscript.

Chapter 3: Conception and design: AH Wagener, WJ Fokkens, EH Bel, PJ Sterk, CM van Drunen; Sub- ject recruitment: AH Wagener; Data collection: AH Wagener; S Luiten; Cell culture and RNA extraction: AH Wagener, S Luiten; Preparation of statistical analysis: AH Wagener, S Luiten, AH Zwinderman; Analysis and Interpretation: AH Wagener, AH Zwinderman, PJ Sterk, CM van Drunen; Principal Investigator and final responsibility: CM van Drunen. AH Wagener, PJ Sterk and CM van Drunen drafted and revised the paper. All authors revised the manuscript.

Chapter 4: Conception and design: AH Wagener, WJ Fokkens, EH Bel, PJ Sterk, CM van Drunen; Sub- ject recruitment: AH Wagener; Data collection: AH Wagener, S Luiten; Cell culture and RNA extraction: AH Wagener, S Luiten; Preparation of statistical analysis: AH Wagener, S Luiten, AH Zwinderman; Analysis and Interpretation: AH Wagener, AH Zwinderman, PJ Sterk, CM van Drunen; Principal Investigator and final responsibility: CM van Drunen. AH Wagener, PJ Sterk and CM van Drunen drafted and revised the paper. All authors revised the manuscript.

260 Appendices Chapter 5: Conception and design: AH Wagener, SB de Nijs, AR Sousa, EJM Weersink, EH Bel, PJ Sterk; Subject recruitment: AH Wagener, SB de Nijs; Data collection: AH Wagener, SB de Nijs, R Lutter; Preparation of statistical analysis: AH Wagener, SB de Nijs; Analysis and Interpretation: AH Wagener, SB de Nijs, R Lutter, PJ Sterk; Principal Investigator and final responsibility: PJ Sterk. AH Wagener, SB de Nijs and PJ Sterk drafted and revised the paper. All authors revised the manuscript.

Chapter 6: Conception and design: AH Wagener, P Brinkman, A D’Amico, G Pennazza, M Santonico, P Montuschi, R Djukanovic, SJ Fowler, PJ Sterk; Subject recruitment: U-BIOPRED Study Group; Data collection: AH Wagener, P Brinkman, R Lutter; Preparation of statistical analysis: AH Wagener, P Brinkman, AT Bansal, AH Zwinderman; Analysis and Interpreta- tion: AH Wagener, P Brinkman, AT Bansal, AH Zwinderman; Principal Investigator and final responsibility: PJ Sterk. AH Wagener and PJ Sterk drafted and revised the paper. All authors revised the manuscript.

Contributing authors 261

List of Publications

(1) Shaw DE, Sousa AR, Fowler SJ, Fleming LJ, Roberts G, Corfield J, Pandis I, Bansal AT, Bel EH, Auffray C, Compton CH, Bisgaard H, Bucchioni E, Caruso M, Chanez P, Dahlen B, Dahlen SE, Dyson K, Frey U, Geiser T, de Gerhardsson V, Gibeon D, Guo YK, Hashi- moto S, Hedlin G, Jeyasingham E, Hekking PW, Higenbottam T, Horvath I, Knox AJ, Krug N, Erpenbeck VJ, Larsson LX, Lazarinis N, Matthews JG, Middelveld R, Montuschi P, Musial J, Myles D, Pahus L, Sandstrom T, Seibold W, Singer F, Strandberg K, Vestbo J, Vissing N, von Garnier C, Adcock IM, Wagers S, Rowe A, Howarth P, Wagener AH, Djukanovic R, Sterk PJ, Chung KF. Clinical and inflammatory characteristics of the European U-BIOPRED adult severe asthma cohort. Eur Respir J 2015 Sep 10. Epub ahead of print. (2) Wagener AH, de Nijs SB, Lutter R, Sousa AR, Weersink EJ, Bel EH, Sterk PJ. External validation of blood eosinophils, FE(NO) and serum periostin as surrogates for sputum eosinophils in asthma. Thorax 2015 Feb;70(2):115-20. (3) Wagener AH, Zwinderman AH, Luiten S, Fokkens WJ, Bel EH, Sterk PJ, van Drunen CM. dsRNA-induced changes in gene expression profiles of primary nasal and bronchial epithelial cells from patients with asthma, rhinitis and controls. Respir Res 2014;15:9. (4) Wagener AH, Yick CY, Brinkman P, van der Schee MP, Fens N, Sterk PJ. Toward composite molecular signatures in the phenotyping of asthma. Ann Am Thorac Soc 2013 Dec;10 Suppl:S197-S205. (5) Wagener AH, Zwinderman AH, Luiten S, Fokkens WJ, Bel EH, Sterk PJ, van Drunen CM. The impact of allergic rhinitis and asthma on human nasal and bronchial epithelial gene expression. PLoS One 2013;8(11):e80257. (6) Bel EH, Sousa A, Fleming L, Bush A, Chung KF, Versnel J, Wagener AH, Wagers SS, Sterk PJ, Compton CH. Diagnosis and definition of severe refractory asthma: an international consensus statement from the Innovative Medicine Initiative (IMI). Thorax 2011 Oct;66(10):910-7. (7) Lazar Z, Fens N, van der Maten J, van der Schee MP, Wagener AH, de Nijs SB, Dijkers E, Sterk PJ. Electronic nose breathprints are independent of acute changes in airway caliber in asthma. Sensors (Basel) 2010;10(10):9127-38.

List of Publications 263

Dankwoord / Acknowledgements

Dit proefschrift is tot stand gekomen door de bijdragen van een groot aantal collega’s. Ik zou graag iedereen hier zeer hartelijk voor willen bedanken.

This thesis is the result of effort of many collegues. I would very much like to thank you all for your help and support.

In het bijzonder zou ik graag mijn promotoren en co-promotor willen noemen: Professor Peter Sterk, Professor Koos Zwinderman en Dr. Kees van Drunen.

Dankwoord / Acknowledgements 265

Curriculum Vitae

Ariane H. Wagener was born in Leiden on the 10th of July 1983. She received her certifi- cate VWO at the Willem de Zwijger College in 2001. After a year of attending courses of politics, philosophy and psychology in Oxford, and atteding a Spanish language course in Guatemala and Mexico, she started her medical training at the University of Gronin- gen and received her medical degree in March 2009. She completed her final clinical internship at the Department of Respiratory Medicine of the Academic Medical Center in Amsterdam, which resulted in her first job as a PhD student, under supervision of Pro- fessor Peter Sterk, Professor Koos Zwinderman and Dr. Kees van Drunen. In November 2013 she went back into clinical practice as a pediatric resident in Tergooi in Blaricum. In april 2015 she started her pediatric residency training in the VUmc in Amsterdam.

Curriculum Vitae 267

Biomarker discovery for discovery Biomarker asthma phenotyping asthma

from gene expression to the clinic ARIANE H. WAGENER H. ARIANE

ISBN: 978-94-6169-778-3