Newborn DNA-Methylation, Childhood Lung Function, and the Risks of Asthma and COPD Across the Life Course

ERJ Express. Published on February 14, 2019 as doi: 10.1183/13993003.01795-2018

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Original article

Newborn DNA-methylation, childhood lung function, and the risks of asthma and COPD across the life course

Herman T. den Dekker, Kimberley Burrows, Janine F. Felix, Lucas A. Salas, Ivana Nedeljkovic, Jin Yao, Sheryl L. Rifas-Shiman, Carlos Ruiz-Arenas, N. Amin, Mariona Bustamante, Dawn L. DeMeo, A. John Henderson, Caitlin G. Howe, Marie-France Hivert, M. Arfan Ikram, Johan C. de Jongste, Lies Lahousse, Pooja R. Mandaviya, Joyce B. van Meurs, Mariona Pinart, Gemma C. Sharp, Lisette Stolk, André G. Uitterlinden, Josep M. Anto, Augusto A. Litonjua, Carrie V. Breton, Guy G. Brusselle, Jordi Sunyer, George Davey Smith, Caroline L. Relton, Vincent W.V. Jaddoe, Liesbeth Duijts

Please cite this article as: den Dekker HT, Burrows K, Felix JF, et al. Newborn DNA- methylation, childhood lung function, and the risks of asthma and COPD across the life course. Eur Respir J 2019; in press (https://doi.org/10.1183/13993003.01795-2018).

This manuscript has recently been accepted for publication in the European Respiratory Journal. It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online.

Original article

Newborn DNA-methylation, childhood lung function, and the risks of asthma and

COPD across the life course

Running head: DNA-methylation and respiratory disease

Herman T. den Dekker, M.D.1,2,3,*, Kimberley Burrows, Ph.D4,*, Janine F. Felix, M.D.,

Ph.D.1,3,5,*, Lucas A. Salas, M.D., Ph.D.6-9, Ivana Nedeljkovic, M.D., M.Sc.3, Jin Yao,

Ph.D.10, Sheryl L. Rifas-Shiman, M.P.H.11, Carlos Ruiz-Arenas, M.Sc.6,8,9, N. Amin, Ph.D.3,

Mariona Bustamante, Ph.D. 6,8,9,12, Dawn L. DeMeo, M.D., M.P.H.13, A. John Henderson,

M.D.4, Caitlin G. Howe, Ph.D.10, Marie-France Hivert, M.D., M.Sc.11, M. Arfan Ikram, M.D.,

Ph.D.3, Johan C. de Jongste, M .D., Ph.D.2, Lies Lahousse, Pharm.D., Ph.D.3,14, Pooja R.

Mandaviya, M.D.15,16, Joyce B. van Meurs, M.D., Ph.D.16, Mariona Pinart, Ph.D. 6,8,9,17,

Gemma C. Sharp, Ph.D. 4, Lisette Stolk, Ph.D.16,18, André G. Uitterlinden, Ph.D.3,16,18,

Josep M. Anto, M.D., Ph.D.6,8,9,17, Augusto A. Litonjua, M.D., M.P.H.13, Carrie V. Breton,

Sc.D.10, Guy G. Brusselle, M.D., Ph.D.3,10,19, Jordi Sunyer, M.D., Ph.D. 6,8,9,17, George

Davey Smith, M.D., Ph.D.4, Caroline L. Relton, Ph.D.4,†, Vincent W.V. Jaddoe, M.D.,

Ph.D.1,3,5,†, Liesbeth Duijts, M.D., Ph.D.2,20,†

*These authors contributed equally

†These authors contributed equally

1The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam,

Rotterdam, the Netherlands

2Department of Pediatrics, Division of Respiratory Medicine and Allergology, Erasmus

MC, University Medical Center Rotterdam, Rotterdam, the Netherlands

3Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam,

Rotterdam, the Netherlands

4MRC Integrative Epidemiology Unit, University of Bristol, UK School of Social and

Community Medicine, University of Bristol, UK

5Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam,

Rotterdam, the Netherlands

6ISGLobal, Centre for Research in Environmental Epidemiology (CREAL), Barcelona,

Spain

7Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH,

USA

8Universitat Pompeu Fabra (UPF), Barcelona, Spain

9CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain

10 Department of Preventive Medicine, University of Southern California, Los Angeles, CA

90089

11Obesity Prevention Program, Department of Population Medicine, Harvard Medical

School and Harvard Pilgrim Health Care Institute, Boston, MA 02115, USA

12 Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and

Technology, Barcelona, Spain

13Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA

02115, USA

14 Department of Respiratory Medicine, Ghent University Hospital, B-9000 Ghent,

Belgium;

15Department of Clinical Chemistry, Erasmus MC, University Medical Center Rotterdam,

The Netherlands

16Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, the Netherlands

17IMIM (Hospital del Mar Medical Research Institute)

18Netherlands Consortium for Healthy Ageing (NCHA), Erasmus MC, University Medical

Center Rotterdam, The Netherlands

19Department of Respiratory Medicine, Erasmus MC, University Medical Center

Rotterdam, Netherlands

20Department of Pediatrics, Division of Neonatology, Erasmus MC, University Medical

Center Rotterdam, Rotterdam, the Netherlands

Key words: Lung function, asthma, COPD, epigenetics, cohort study, meta-analysis

Acknowledgements

A full description of acknowledgements and funding is provided in the Supplementary

Appendix. The sponsors of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report. HD, KB, JF, CR, VJ, and LD contributed to the study design, data analysis plan, data collection, data and meta- analysis, data interpretation, writing, reviewing the manuscript critically and gave consent for submission. All other authors contributed equally to study design, data analysis plan, cohort specific data collection and analysis, reviewing the manuscript critically and gave consent for submission.

Corresponding author

Liesbeth Duijts, MD, PhD, Erasmus MC, University Medical Center Rotterdam, Sp-3435;

PO Box 2060, 3000 CB, Rotterdam, The Netherlands.

Tel: *31 10 7036263, Fax: *31 10 7036811, E-mail: [email protected]

Abbreviations

DMR Differentially Methylated Region

COPD Chronic Obstructive Pulmonary Disease

FEV1 Forced Expiratory Volume in 1 second

FEV1/FVC Forced Expiratory Volume in 1 second / Forced Vital Capacity

FEF75 Forced Expiratory Flow at 75% of Forced Vital Capacity

Summary text

Den Dekker et al. identified 59 differentially methylated regions in cord blood associated with childhood lung function, of which up to 30% was associated with later life asthma and

COPD. The newborns epigenetic status might affect life-course respiratory health.

ABSTRACT

Rationale We aimed to identify differentially methylated regions (DMRs) in cord blood DNA associated with childhood lung function, asthma and chronic obstructive pulmonary disease (COPD) across the life course.

Methods We meta-analyzed epigenome-wide data of 1688 children from five cohorts to identify cord blood DMRs and their annotated genes, in relation to Forced Expiratory Volume in 1 second (FEV1),

FEV1/Forced Vital Capacity (FVC), and Forced Expiratory Flow at 75% of FVC (FEF75) at ages 7 to

13 years. Identified DMRs were explored for associations with childhood asthma, adult lung function and COPD, gene expression and involvement in biological processes.

Results We identified 59 DMRs associated with childhood lung function, of which 18 were associated with childhood asthma and 9 with COPD in adulthood. Genes annotated to the top ten identified

DMRs were HOXA5, PAOX, LINC00602, ABCA7, PER3, CLCA1, VENTX, NUDT12, PTPRN2 and

TCL1A. Differential gene expression in blood was observed for 32 DMRs in childhood and 18 in adulthood. Genes related with 16 identified DMRs were associated with respiratory developmental or pathogenic pathways.

Interpretation Our findings suggest that the epigenetic status of the newborn affects respiratory health and disease across the life course.

INTRODUCTION

Asthma and chronic obstructive pulmonary disease (COPD) have become major global health problems in the last decades (1). Both diseases are characterized by airway obstruction, as indicated by a reduced Forced Expiratory Volume in 1 second (FEV1), FEV1 to Forced Vital Capacity (FVC) ratio, and Forced Expiratory Flow at 75% of FVC (FEF75) (2). Childhood lung function predicts lung function and risks of asthma and COPD in later life (3). An accumulating body of evidence suggests that asthma and COPD have at least part of their origins in fetal life (4, 5). Genetics alone fail to explain the quickly altering prevalence of allergies and chronic respiratory diseases in the past decades, because any mutation would require multiple generations to occur on a population level

(6). Furthermore, adverse fetal exposures, such as maternal smoking and suboptimal diet, increase the risk of asthma and COPD (5). The pathways linking genetic predisposition and environmental exposures in fetal life with life course respiratory disease may include epigenetic changes, including

DNA-methylation (5). Epigenetic changes are influenced by environmental exposures and could exert population effects much more rapidly than genetic mutations(6). DNA-methylation is currently the best understood epigenetic mechanism, and techniques have been developed to assess epigenome-wide

DNA-methylation patterns in large population- based studies. Fetal development is characterized by high rates of DNA-methylation changes and rapid organ development (5). DNA-methylation may affect fetal development through effects on gene transcription and expression (7). Recent studies assessing the associations between DNA-methylation and childhood respiratory health are mainly limited to candidate genes and small sample sizes (3, 8). We focused on identification of differential

DNA-methylated regions (DMRs) because regional methylation of CpGs controls cell-type-specific transcription. Also, the use of DMRs increases statistical power and minimizes the effects of genetic variants in the methylation analyses (9). Identification of genomic regions with altered DNA- methylation levels related to lung function and respiratory diseases across the life course is important to understand mechanisms underlying associations of environmental and genetic factors with the development of lower lung function and risk of chronic respiratory diseases. We hypothesized that fetal differential DNA-methylation reflected in cord blood DNA of newborns affect gene expression and subsequent respiratory tract development, and predispose individuals for obstructive airway diseases in later life (10, 11).

We meta-analyzed five epigenome-wide association studies using data from 1,688 children participating in prospective cohort studies to identify differential DNA-methylated regions (DMRs) of newborns associated with childhood FEV1, FEV1/FVC and FEF75. Identified top DMRs were subsequently explored for their associations with childhood asthma, lung function in adolescence and adulthood, and COPD in adulthood, and explored for association with gene expression and involvement in biological processes.

METHODS

Study Design and Data Sources

We included population-based cohort studies participating in PACE consortium with data on epigenome-wide DNA-methylation at birth and lung function in childhood (12). We used data from

1,688 Caucasian children aged 7 to 13 years participating in the Avon Longitudinal Study of Parents and Children (ALSPAC) (United Kingdom), Generation R (Netherlands), INfancia y Medio Ambiente

Study (INMA) (Spain), Children’s Health Study (CHS) and Project Viva (both from the U.S.A.). These data were used for the primary discovery epigenome-wide meta-analysis to identify DMRs of newborns related to childhood lung function. We aimed to identify DMRs instead of single CpGs while differences at any individual CpG may be small, and the use of DMRS might minimize the effects of genetic variants in the methylation analysis (13, 14).

We used several resources for the secondary analyses. For clinical outcomes, we used childhood asthma data (Generation R, mean age 6 years), lung function data from adolescents (ALSPAC, mean age 15 years) and adults (Rotterdam Study, mean age 66 years, The Netherlands), and COPD data in adults (Rotterdam Study) (Figure 1). For gene expression, we used blood samples from children

(INMA, at birth and mean age 4 years) and adults (Rotterdam Study). Last, we used publicly available resources to relate identified DMRs with biological processes (15-17). Parents, legal representatives or participants provided informed consent in accordance with local ethics policies. Detailed information about the study design and cohorts is provided in the Supplementary Appendix.

DNA-methylation

All cohorts extracted DNA from blood samples and used the EZ-96 DNA Methylation kit (Zymo

Research Corporation, Irvine, USA) for bisulfite conversion. Samples were processed with the

Infinium HumanMethylation450 BeadChip (Illumina Inc., San Diego, USA) followed by cohort-specific quality control, probe exclusion and data normalization. Detailed information on cohort-specific data acquisition and quality control is provided in the Supplementary Appendix.

Respiratory Outcome Assessment

Lung function measures comprised pre-bronchodilator FEV1, FEV1/FVC and FEF75, which were converted into sex-, age-, height- and ethnicity-adjusted z-scores (18). Physician-diagnosed asthma was obtained by questions adapted from the International Study on Asthma and Allergy in Childhood

(19). COPD was defined as pre-bronchodilator FEV1/FVC <0.70 in the absence of asthma, or a doctor diagnosis (20).

Statistical Analyses

Primary Meta-analysis on Childhood Lung Function A detailed description of applied methods is presented in the Supplementary Appendix. Individual cohorts used robust linear regression models to examine the associations of DNA-methylation levels of CpGs with childhood FEV1, FEV1/FVC and

FEF75. Analyses were adjusted for maternal age, socio-economic status, smoking during pregnancy, parity, asthma or atopy, technical covariates and estimated cell counts (21). Results were combined using inverse variance-weighted fixed-effect meta-analyses. Results from unadjusted models were similar to fully adjusted models (Supplementary Appendix Table 1). Using p-values obtained from the meta-analyses, we identified DMRs using the software-tool Comb-p, which is the most robust tool to identify DMRs with small effect sizes (9, 22). Regions were defined as a minimum of 2 probes within a window size of 500 bases with an FDR-threshold <0.05 (9). Comb-p uses unadjusted p- values for each probe as input, and calculates adjusted p-values for each probe that account for the correlation with nearby CpGs (23). Next, the SLK p-values were adjusted for multiple testing and adjusted into q-values. Comb-p finds DMRs based on these q-values and calculates p-values for these DMRs based on the original p-values. Finally, the DMR p-values were adjusted for multiple testing using the Šidák-correction based on the size of the region and number of possible regions of

that size. A sliding window identifies a DMR without any predefined regional borders, and therefore

(theoretically) does not have a maximum number of windows and DMRs. A more extensive description of the identification of DMRS is provided in the Supplementary Material. Annotation of the genes located nearest to the DMRs was performed using Peak Annotation and Visualization (PAVIS)

(24). We limited annotation to a region of 500kb (250kb upstream, 250kb downstream of the beginning and end of the region, respectively). All annotations were based on human GRCh37/hg19 assembly. Because genetic variants in Infinium probes could result in spurious methylation measurements, we performed a sensitivity analysis in a subset of high-quality probes (n=294,834) without SNPs, insertions or deletions, repeats, polymorphic probes and bisulfite induced reduced genomic complexity (25).

Secondary Analyses on Later Life Lung Function and Respiratory Diseases We used linear and logistic regression models to examine the associations of CpGs within identified DMRs with asthma in childhood, FEV1, FEV1/FVC and FEF75 in adolescence and adulthood, and COPD in adulthood.

Single CpG p-values were used to reconstruct the identified DMRs with Comb-p, applying identical parameter settings as in the discovery meta-analyses including false discovery rate (FDR)-correction

(9, 26). We did not apply Šidák-correction because analyses were limited to the identified DMRs.

Gene Expression Analyses We assessed the associations of CpGs within identified DMRs with gene expression in a region of ±250kb in blood samples from children and adults. P-values of CpGs associated with gene expression were combined for each DMR using a modified generalized Fisher method and FDR-correction (26, 27). Additionally, we explored whether the annotated and differentially expressed genes were expressed in human lung specimens of the Genotype-Tissue

Expression (GTEx) database (15).

Exploration biological processes The Gene Ontology database implemented in DAVID and

Genemania was used to examine gene function in biological processes (16, 17). We examined pathways for all genes annotated to the DMRs and for genes with differential expression in association with the identified DMRs. We used the Kyoto Encyclopedia of Genes and Genomes

(KEGG) database in DAVID and Genemania, the OMIM database and the Universal Protein

Resource (UniProt) to explore whether annotated or expressed genes have been related to respiratory development or diseases (28). We used the Ensemble Genome browser to visualize the genomic structure of the identified DMRs.

RESULTS

Meta-analysis of Epigenome-wide Association Studies on Childhood Lung Function

Characteristics of the participating cohorts are given in Table 1 and Supplementary Appendix Table

We identified 22, 15 and 22 DMRs associated with FEV1, FEV1/FVC and FEF75, respectively (Figure

2, Supplementary Appendix Tables 3 and 4). A higher mean methylation of CpGs located within 37

(63%) of the identified DMRs was associated with higher lung function measures, and within 22 (37%) of identified DMRs with lower lung function measures. We observed a high homogeneity across the

2 included studies (CpGs with I <50: FEV1 140/163 (86%), FEV1/FVC 82/89 (92%) and FEF75 139/148

(87%)) (Supplemental Tables 4a-c).

Of the top ten significant DMRs associated with childhood lung function, the 5 DMRs and their annotated genes for FEV1 were located at chr7:27,183,133-27,184,854 (HOXA5), chr10:135,202,522-

135,203,201 (PAOX), chr6:166,418,799-166,419,139 (LINC00602), chr19:1,063,624-1,064,219

(ABCA7) and chr1:7,887,199-7,887,561 (PER3). Three DMRs and their annotated genes for

FEV1/FVC were located at chr1:86,968,087-86,968,544 (CLCA1), chr10:135,051,149-135,051,582

(VENTX), and chr5:102,898,223-102,898,734 (NUDT12). Two DMRs for FEF75 and their annotated genes were located at chr7:158,045,980-158,046,359 (PTPRN2) and chr14:96,180,406-96,181,045

(TCL1A). After exclusion of potentially problematic probes containing genomic variants, 41 of the 59 previously identified DMRs still contained ≥2 CpGs (supplementary appendix Table 4). Of these 41

41 DMRs, 54% (n=22) remained to be associated with childhood lung function (Supplementary appendix Table 5).

Identified DMRs and Lung Function and Respiratory Diseases Across the Life Course

Of all 59 identified DMRs related with childhood lung function, 18 (31%) were associated with childhood asthma (Figure 3, Supplementary appendix Table 6). Furthermore, 11 (19%) and 9

(15%) DMRs were associated with lung function in adolescence and adulthood, respectively, and 9

(15%) were associated with COPD. The DMRs annotated to HOXA5 and PAOX were associated with childhood and adolescence FEV1 and COPD, but not with childhood asthma or adult lung function.

The DMRs annotated to PER3 and VENTX were associated with childhood and adolescence FEV1

and FEV1/FVC, respectively. The DMR annotated to NUDT12 was associated with childhood

FEV1/FVC and COPD. The DMRs annotated to PTPRN2 and TCL1A were associated with childhood

FEF75 and asthma. The DMRs annotated to LINC00602, ABCA7 and CLCA1 were associated with childhood lung function but not with other outcomes.

Identified DMRs and Gene Expression

Of the 59 identified DMRs, 32 (54%) DMRs at birth were associated with gene expression at age 4 years, and 18 (31%) DMRs with gene expression in adulthood (Supplementary Appendix Table 7).

The DMR annotated to HOXA5 was associated with differential expression of several genes of the

HOX-family (Table 2). The DMRs annotated to PER3, VENTX , NUDT12 and TCL1A were associated with differential expression of their respective genes. The DMRs annotated to PAOX, LINC00602,

ABCA7, CLCA1 and PTPRN2 were not associated with expression of their corresponding genes.

Genes annotated to 28 (47%) of all identified DMRs were expressed in adult lung tissue, including the top significant DMRs annotated to PAOX, ABCA7, CLCA1, VENTX and NUDT12 (Supplementary

Appendix Table 8).

Identified DMRs and related biological processes

Of all 59 identified DMRs, 43 were annotated to genes not previously associated with lung function or respiratory morbidity (Supplementary Appendix Table 7). Of the genes annotated to the top ten significant DMRs, HOXA5, CLCA1, TCL1A and NUDT12 were previously associated with respiratory development including alveogenesis, respiratory diseases and cellular immunity (Table 2). Integrative pathway analysis showed that the majority of genes annotated to DMRs associated with childhood lung function were in co-expression and are known for physical and genetic interactions

(Supplementary Figures 1a-c). Genes related to the identified DMRs, including HOXA5, PER3,

CLCA1, NUDT12 and PTPRN2, were located in pathways related to regionalization, DNA- and RNA- regulation and embryonic development (Supplementary Appendix Tables 9). The genes HLA-DRB4 and HLA-DRB5 were enriched in processes including asthma. These genes were associated with the

DMR located at chr6:32,305,068-32,305,146, which was related with childhood and adulthood

FEV1/FVC and COPD.

Of the top ten significant DMRs, the DMRs annotated to HOXA5, CLCA1 and TCL1A contained

CTCF-binding sites (Supplementary Figure 2). The DMRs annotated to HOXA5, PAOX, PER3 and

NUDT12 were located in promotor regions of their respective genes. The DMR annotated to ABCA7 was located in a CpG-island.

DISCUSSION

We identified 59 DMRs in neonatal cord blood associated with childhood lung function. Eighteen

(31%) of all identified DMRs were also associated with childhood asthma, 11 (19%) and 9 (15%) with adolescent and adult lung function, respectively, and 9 (15%) with COPD. Differential gene expression was observed for 32 (54%) DMRs in childhood and 18 (31%) DMRs in adulthood. Multiple genes related to the identified DMRs have previously been associated with respiratory development and morbidity, and many identified DMRs were located within known regulatory elements for gene expression.

Reduced lung function in childhood is associated with reduced lung function and increased risks of asthma and COPD many decades later (10, 29). Pathways of environmental exposures in early life that affect lung development might be modified by genetic susceptibility. Vice versa, genetic susceptibility could partly explain the difference in adverse effects of early environmental exposures on the risk of chronic obstructive respiratory diseases. Identified genetic variants associated with childhood asthma in large-scale GWA studies only account for up to 7.5% of the explained variance

(30). Epigenetic mechanisms could link environmental exposures with the unexplained heritability for childhood asthma (31, 32). Studies that examined associations of DNA-methylation with lung function, asthma or COPD are scarce, limited to candidate genes or high-risk population and lack replication.

An epigenome-wide study among 97 asthmatics and 97 healthy children aged 6-12 years identified 81

DMRs associated with asthma, of which 16 DMRs were also associated with FEV1 (8). Of these 81

DMRs, 19 were located within 500kb of our identified DMRs and may affect the same genes. Another epigenome-wide study in 1,454 adults identified 349 CpGs associated with COPD (33). Four annotated genes in this adult study (CBFA2T3, PADI4, LST1, KCNQ1) were replicated in our study of children. Multiple genes associated with the identified DMRs have previously been related with asthma and COPD in genome-wide association studies. Nine (15%) of the 59 DMRs we identified were associated with adult lung function, and annotated to, or associated with differential expression

of 11 genes. Nine of these genes were previously linked with pulmonary structures, immunity, asthma, COPD and smoking behavior in COPD (28). This suggests that genes associated with respiratory diseases could be influenced by differential DNA-methylation from early life onwards.

We explored the biological processes of the top significant DMRs for development of respiratory morbidity (28). The DMR annotated to HOXA5 was associated with childhood and adolescent FEV1,

COPD and differential expression of HOXA1, HOXA4 and HOXA7. One DMR associated with childhood FEV1/FVC was annotated to VENTX, which is a member of the HOX-gene family. The DMR annotated to LINC00602 (Long Intergenic Non-Protein Coding RNA (lncRNA) 602) was linked to childhood FEV1. LncRNAs influence gene-specific epigenetic regulation and interact amongst others with the transcription of HOX-genes. HOX-genes are critical for segmental fetal development, and especially HOXA5 is required for embryonic respiratory tract morphogenesis (35, 36). The DMR annotated to PAOX was linked to childhood and adolescence FEV1 and COPD. PAOX is involved in the regulation of intracellular polyamine, which is essential for protein synthesis. The DMR linked to

ABCA7 was associated with FEV1 in childhood and adolescence. ABCA7 is involved in the lipid homeostasis in the cellular immune system and is essential for phagocytosis of apoptotic cells by alveolar macrophages (37). PER3, annotated to a DMR associated with FEV1 in children and adolescents, is a key element in the endogenous circadian rhythm. The DMR linked to CLCA1 was associated with childhood FEV1/FVC and FEF75, and expressed in adult lung tissue. CLCA1 affects

IL-13 driven mucus production in human airway epithelial cells and is associated with asthma and

COPD (38-40). NUDT12, annotated to a DMR associated with childhood FEV1/FVC and COPD, is involved in intracellular biochemical reactions. NUDT12 is associated with smoking behavior in COPD

(41).

PTPRN2, annotated to a DMR associated with childhood FEF75 and asthma is member of a gene family regulating cell growth and differentiation, and is involved in vesicle-mediated secretory processes. DNA-methylation of PTPRN2 differentiates between lung cancer, pulmonary fibrosis and

COPD (42). TCL1A, annotated to a DMR associated with childhood FEV1/FVC, FEF75 and asthma, is specific to developing lymphocytes when expressed and is associated with asthma (34). Thus, many of the genes annotated to the top significant DMRs are involved in respiratory development, cellular immunity and respiratory morbidity. Furthermore, genes associated with 29 of the identified DMRs, including HOXA5, PAOX, VENTX, PTPRN2 and TCL1A, have been reported to be differentially

methylated in relation with maternal smoking during pregnancy (12). Genes related with four identified

DMRs associated with childhood lung function were differentially methylated in association with maternal folate levels during pregnancy (43)

This is the largest study to date evaluating the associations of newborn epigenome-wide DNA- methylation with lung function and respiratory disease in children and adults, and it provides new insights into the epigenetic changes in fetal life that increase the risk of life-time respiratory morbidity.

We aimed to strengthen our results using public databases on gene expression and biological pathways. Ideally, the presence of identified DMRs would be replicated in lung cells. However, in cohort studies, this is ethically not done. It is unknown whether nasal cells, which are easier to acquire, have a high enough correlation in DNA-methylation with lung tissue. Therefore, further studies should aim to examine whether DNA-methylation in nasal cells is a good proxy for lung tissue and data on DNA-methylation and phenotypes should be shared in consortia to increase statistical power. These results cannot currently be used as predictors of disease in individuals, but are important from an etiological perspective. Further experimental or Mendelian randomization studies on the identified DMRs and associated genes might inform strategies in early life to improve lung function and lower the lifetime risk of obstructive respiratory diseases.

Some limitations should be discussed. We measured DNA-methylation in blood because it is easily accessible in large cohort studies. Blood DNA-methylation does not necessarily reflect lung epithelial

DNA-methylation. However, asthma and COPD have systemic manifestations, characterized by increased inflammatory blood markers (44, 45). Although the analyses were adjusted for estimated cell counts, we cannot rule out residual confounding due to alterations in cell type distribution.

Recently, two new reference sets for cell type adjustment in cord blood samples were published (46,

47). These reference sets are currently being validated, and future studies will shed light on the differences between reference panels. In our secondary analyses, we assessed whether the identified

DMRs were associated with lung function measured in adolescence and adulthood. DNA methylation patterns and expression of genes vary depending on the developmental stage, and these changes could be non-linear (48). We were not able to assess the stability of DNA methylation in the identified

DMRs in the same individuals from birth to adulthood. In a recent study addressing DNA methylation changes in early life, significantly reduced or increased methylation of single CpGs between ages 0 to

4 years and 4 to 8 years occurred in <4% of all CpGs, suggesting only a minor change in genome-

wide DNA methylation in childhood (49). Longitudinal changes in DNA methylation in the same individuals from early life until adulthood in relation to respiratory morbidity have not been studied yet.

We presented our primary results including all probes, and provided results of analyses excluding potentially problematic probes. In our stringent sensitivity analyses, we observed similar size and direction of the effect estimates in 54% of the identified DMRs associated with childhood lung function. However, the true exact impact of potentially problematic probes on the measurement of

DNA methylation remains unknown (25, 50). Discarding probes a priori may discard information.

Therefore, we present all results of the main and sensitivity analysis.

Genetic variation might be influencing the DMRs associated with respiratory health. A recent study in two ethnic diverse adult cohorts in 557 subjects showed that DNA methylation of airway epithelium plays a central role in mediating the effects of SNPs and gene expression on asthma risk and its clinical course (51). Another study in 115 adults reported a potential mediating effect of DNA methylation of single CpGs on the associations between SNPs located at chromosomal locus 17q21 and asthma (52). The study identified 6 CpGs associated with gene expression of ORMDL3 and

GSDMB. The authors did not assess the associations of DNA methylation with asthma or lung function. We did not identify any DMR located near the 17q21 locus. This could be explained by the young age of our study subjects or differences in main respiratory outcomes measurements.

Several identified DMRs were associated with gene expression other than the nearest and therefore annotated gene, which limits the potential biological effect of the annotated genes. The genomic inflation factor for the primary analyses ranged from 1.07 to 1.21 (Supplementary Figure 3).

Recently, it was shown that the genomic inflation factor provides an invalid estimate of test-statistic inflation when the outcome of interest is associated with many, small genetic effects (53).

Furthermore, estimating the inflation factor using the genomic inflation factor results both in an overestimation of the actual inflation and in imprecise estimates contributing to the previously unexplained, high variability across studies. This might explain the genomic inflation in our analyses.

The statistical steps in Comb-P limit the final number of DMRs identified, and genomic inflation in the identification of DMRs could not be tested. Further studies are needed to develop statistical tools dealing with genomic inflation in epigenome-wide studies.

There were no cohort studies available for replication or validation analyses. We included all available cohorts in the meta-analysis to obtain the largest possible power to detect new associations. A

previously published study has shown that in (epi)genome-wide association analyses a meta-analysis of all participating cohorts rather than a split sample analysis with a properly selected level of

(epi)genome-wide significance is the most powerful approach to identify new associations (54). The high between-study homogeneity observed for the vast majority of CpGs in our meta-analysis

(Supplementary Tables 4a-c) also provides support for the stability of the reported associations.

Nevertheless, confirmatory studies are needed and presented results are limited by lack of independent cohorts for validation.

In conclusion, we identified 59 DMRs in cord blood that were associated with childhood lung function.

Multiple DMRs were additionally related with childhood asthma, adolescent and adult lung function, or adult COPD. Also, multiple DMRs were associated with differential gene expression of genes involved in embryonic and respiratory tract development, or were located in regulatory elements for gene expression. These findings suggest that epigenetic changes during fetal life might modify the risk of respiratory diseases across the life course.

REFERENCES

1. Chronic obstructive pulmonary disease (COPD): World Health Organisation; 2015 [Available from: http://www.who.int/mediacentre/factsheets/fs315/en/.

2. McDonough JE, Yuan R, Suzuki M, Seyednejad N, Elliott WM, Sanchez PG, et al. Small- airway obstruction and emphysema in chronic obstructive pulmonary disease. N Engl J Med.

2011;365(17):1567-75.

3. McGeachie MJ, Yates KP, Zhou X, Guo F, Sternberg AL, Van Natta ML, et al. Patterns of

Growth and Decline in Lung Function in Persistent Childhood Asthma. New Engl J Med.

2016;374(19):1842-52.

4. Martinez FD. Early-Life Origins of Chronic Obstructive Pulmonary Disease. N Engl J Med.

2016;375(9):871-8.

5. Duijts L, Reiss IK, Brusselle G, de Jongste JC. Early origins of chronic obstructive lung diseases across the life course. Eur J Epidemiol. 2014;29(12):871-85.

6. Begin P, Nadeau KC. Epigenetic regulation of asthma and allergic disease. Allergy Asthma

Clin Immunol. 2014;10(1):27.

7. Krauss-Etschmann S, Meyer KF, Dehmel S, Hylkema MN. Inter- and transgenerational epigenetic inheritance: evidence in asthma and COPD? Clin Epigenetics. 2015;7:53.

8. Yang IV, Pedersen BS, Liu A, O'Connor GT, Teach SJ, Kattan M, et al. DNA methylation and childhood asthma in the inner city. J Allergy Clin Immunol. 2015;136(1):69-80.

9. Pedersen BS, Schwartz DA, Yang IV, Kechris KJ. Comb-p: software for combining, analyzing, grouping and correcting spatially correlated P-values. Bioinformatics. 2012;28(22):2986-8.

10. Postma DS, Rabe KF. The Asthma-COPD Overlap Syndrome. N Engl J Med.

2015;373(13):1241-9.

11. Fu JJ, McDonald VM, Baines KJ, Gibson PG. Airway IL-1 beta and Systemic Inflammation as

Predictors of Future Exacerbation Risk in Asthma and COPD. Chest. 2015;148(3):618-29.

12. Joubert BR, Felix JF, Yousefi P, Bakulski KM, Just AC, Breton C, et al. DNA Methylation in

Newborns and Maternal Smoking in Pregnancy: Genome-wide Consortium Meta-analysis. Am J Hum

Genet. 2016;98(4):680-96.

13. Lister R, Pelizzola M, Dowen RH, Hawkins RD, Hon G, Tonti-Filippini J, et al. Human DNA methylomes at base resolution show widespread epigenomic differences. Nature.

2009;462(7271):315-22.

14. Bock C. Analysing and interpreting DNA methylation data. Nat Rev Genet. 2012;13(10):705-

19.

15. Carithers LJ, Ardlie K, Barcus M, Branton PA, Britton A, Buia SA, et al. A Novel Approach to

High-Quality Postmortem Tissue Procurement: The GTEx Project. Biopreserv Biobank.

2015;13(5):311-9.

16. Huang da W, Sherman BT, Lempicki RA. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic acids research. 2009;37(1):1-13.

17. Warde-Farley D, Donaldson SL, Comes O, Zuberi K, Badrawi R, Chao P, et al. The

GeneMANIA prediction server: biological network integration for gene prioritization and predicting gene function. Nucleic acids research. 2010;38(Web Server issue):W214-20.

18. Quanjer PH, Stanojevic S, Cole TJ, Baur X, Hall GL, Culver BH, et al. Multi-ethnic reference values for spirometry for the 3-95-yr age range: the global lung function 2012 equations. Eur Respir J.

2012;40(6):1324-43.

19. Asher MI, Keil U, Anderson HR, Beasley R, Crane J, Martinez F, et al. International Study of

Asthma and Allergies in Childhood (ISAAC): rationale and methods. Eur Respir J. 1995;8(3):483-91.

20. Terzikhan N, Verhamme KM, Hofman A, Stricker BH, Brusselle GG, Lahousse L. Prevalence and incidence of COPD in smokers and non-smokers: the Rotterdam Study. Eur J Epidemiol. 2016.

21. Houseman EA, Accomando WP, Koestler DC, Christensen BC, Marsit CJ, Nelson HH, et al.

DNA methylation arrays as surrogate measures of cell mixture distribution. BMC bioinformatics.

2012;13:86.

22. Peters TJ, Buckley MJ, Statham AL, Pidsley R, Samaras K, Lord RV, et al. De novo identification of differentially methylated regions in the human genome. Epigenet Chromatin. 2015;8.

23. Eckhardt F, Lewin J, Cortese R, Rakyan VK, Attwood J, Burger M, et al. DNA methylation profiling of human chromosomes 6, 20 and 22. Nat Genet. 2006;38(12):1378-85.

24. Huang W, Loganantharaj R, Schroeder B, Fargo D, Li L. PAVIS: a tool for Peak Annotation and Visualization. Bioinformatics. 2013;29(23):3097-9.

25. Naeem H, Wong NC, Chatterton Z, Hong MK, Pedersen JS, Corcoran NM, et al. Reducing the risk of false discovery enabling identification of biologically significant genome-wide methylation status using the HumanMethylation450 array. BMC Genomics. 2014;15:51.

26. Benjamini Y, Hochberg Y. Controlling for False Discovery Rate: a Practical and Powerful

Approach to Multiple Testing. Journal of the Royal Statistical Society, Series B. 1995;57:289-300.

27. Dai H, Leeder JS, Cui Y. A modified generalized Fisher method for combining probabilities from dependent tests. Front Genet. 2014;5:32.

28. UniProt C. UniProt: a hub for protein information. Nucleic acids research. 2015;43(Database issue):D204-12.

29. McGeachie MJ, Yates KP, Zhou X, Guo F, Sternberg AL, Van Natta ML, et al. Patterns of

Growth and Decline in Lung Function in Persistent Childhood Asthma. N Engl J Med.

2016;374(19):1842-52.

30. Soler Artigas M, Loth DW, Wain LV, Gharib SA, Obeidat M, Tang W, et al. Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function. Nat Genet.

2011;43(11):1082-90.

31. Cookson W, Moffatt M, Strachan DP. Genetic risks and childhood-onset asthma. J Allergy

Clin Immunol. 2011;128(2):266-70; quiz 71-2.

32. English S, Pen I, Shea N, Uller T. The information value of non-genetic inheritance in plants and animals. PLoS One. 2015;10(1):e0116996.

33. Qiu W, Baccarelli A, Carey VJ, Boutaoui N, Bacherman H, Klanderman B, et al. Variable DNA methylation is associated with chronic obstructive pulmonary disease and lung function. Am J Respir

Crit Care Med. 2012;185(4):373-81.

34. George BJ, Reif DM, Gallagher JE, Williams-DeVane CR, Heidenfelder BL, Hudgens EE, et al. Data-driven asthma endotypes defined from blood biomarker and gene expression data. PLoS

One. 2015;10(2):e0117445.

35. Golpon HA, Geraci MW, Moore MD, Miller HL, Miller GJ, Tuder RM, et al. HOX genes in human lung: altered expression in primary pulmonary hypertension and emphysema. Am J Pathol.

2001;158(3):955-66.

36. Mandeville I, Aubin J, LeBlanc M, Lalancette-Hebert M, Janelle MF, Tremblay GM, et al.

Impact of the loss of Hoxa5 function on lung alveogenesis. American Journal of Pathology.

2006;169(4):1312-27.

37. Jehle AW, Gardai SJ, Li S, Linsel-Nitschke P, Morimoto K, Janssen WJ, et al. ATP-binding cassette transporter A7 enhances phagocytosis of apoptotic cells and associated ERK signaling in macrophages. J Cell Biol. 2006;174(4):547-56.

38. Poole A, Urbanek C, Eng C, Schageman J, Jacobson S, O'Connor BP, et al. Dissecting childhood asthma with nasal transcriptomics distinguishes subphenotypes of disease. J Allergy Clin

Immunol. 2014;133(3):670-8 e12.

39. Hegab AE, Sakamoto T, Uchida Y, Nomura A, Ishii Y, Morishima Y, et al. CLCA1 gene polymorphisms in chronic obstructive pulmonary disease. J Med Genet. 2004;41(3):e27.

40. Alevy YG, Patel AC, Romero AG, Patel DA, Tucker J, Roswit WT, et al. IL-13-induced airway mucus production is attenuated by MAPK13 inhibition. J Clin Invest. 2012;122(12):4555-68.

41. Siedlinski M, Cho MH, Bakke P, Gulsvik A, Lomas DA, Anderson W, et al. Genome-wide association study of smoking behaviours in patients with COPD. Thorax. 2011;66(10):894-902.

42. Wielscher M, Vierlinger K, Kegler U, Ziesche R, Gsur A, Weinhausel A. Diagnostic

Performance of Plasma DNA Methylation Profiles in Lung Cancer, Pulmonary Fibrosis and COPD.

EBioMedicine. 2015;2(8):929-36.

43. Joubert BR, den Dekker HT, Felix JF, Bohlin J, Ligthart S, Beckett E, et al. Maternal plasma folate impacts differential DNA methylation in an epigenome-wide meta-analysis of newborns. Nat

Commun. 2016;7:10577.

44. Barnes PJ. Inflammatory mechanisms in patients with chronic obstructive pulmonary disease.

J Allergy Clin Immunol. 2016;138(1):16-27.

45. Nadif R, Siroux V, Boudier A, le Moual N, Just J, Gormand F, et al. Blood granulocyte patterns as predictors of asthma phenotypes in adults from the EGEA study. Eur Respir J. 2016.

46. Bakulski KM, Feinberg JI, Andrews SV, Yang J, Brown S, S LM, et al. DNA methylation of cord blood cell types: Applications for mixed cell birth studies. Epigenetics. 2016;11(5):354-62.

47. Gervin K, Page CM, Aass HC, Jansen MA, Fjeldstad HE, Andreassen BK, et al. Cell type specific DNA methylation in cord blood: a 450K-reference data set and cell count-based validation of estimated cell type composition. Epigenetics. 2016:0.

48. Feng L, Wang J, Cao B, Zhang Y, Wu B, Di X, et al. Gene expression profiling in human lung development: an abundant resource for lung adenocarcinoma prognosis. PLoS One.

2014;9(8):e105639.

49. Xu CJ, Bonder MJ, Soderhall C, Bustamante M, Baiz N, Gehring U, et al. The emerging landscape of dynamic DNA methylation in early childhood. BMC Genomics. 2017;18(1):25.

50. Lehne B, Drong AW, Loh M, Zhang WH, Scott WR, Tan ST, et al. A coherent approach for analysis of the Illumina HumanMethylation450 BeadChip improves data quality and performance in epigenome-wide association studies (vol 16, 37, 2015). Genome Biol. 2016;17.

51. Kothari PH, Qiu W, Croteau-Chonka DC, Martinez FD, Liu AH, Lemanske RF, Jr., et al. Role of local CpG DNA methylation in mediating the 17q21 asthma susceptibility gasdermin B

(GSDMB)/ORMDL sphingolipid biosynthesis regulator 3 (ORMDL3) expression quantitative trait locus.

J Allergy Clin Immunol. 2018;141(6):2282-6 e6.

52. Nicodemus-Johnson J, Myers RA, Sakabe NJ, Sobreira DR, Hogarth DK, Naureckas ET, et al. DNA methylation in lung cells is associated with asthma endotypes and genetic risk. JCI Insight.

2016;1(20):e90151.

53. van Iterson M, van Zwet EW, Consortium B, Heijmans BT. Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution. Genome

Biol. 2017;18(1):19.

54. Skol AD, Scott LJ, Abecasis GR, Boehnke M. Joint analysis is more efficient than replication- based analysis for two-stage genome-wide association studies. Nat Genet. 2006;38(2):209-13.

Table 1. Characteristics of Cohorts and Their Participants.

No. of Type of No. of No. of Age at Asthma COPD

partici blood availa subjects lung

pants sample ble with functio

for DNA- CpGs expressio n

methylati n data measur

on ement

Years Ca Contr Ca Contr

(SD) ses ols ses ols

Primary analyses

ALSPAC (UK) 654 Cord 471,1 n.a. 8·6 (0·2) n.a n.a. n.a n.a. . . blood 93

Generation R 643 Cord 436,0 n.a. 9·8 (0·3) 47 663 n.a n.a. . (NL) blood 13

INMA (Spain) 140 Cord 439,3 107 6·9 (0·3) n.a n.a. n.a n.a.

blood 06 . .

CHS (USA) 75 Cord 383,8 n.a. 13·3 n.a n.a. n.a n.a.

blood 57 (0·6) . .

Project Viva 176 Cord 470,8 n.a. 7·9 (0·7) n.a n.a. n.a n.a.

(USA) blood 70 . .

Secondary analyses

ALSPAC (UK) 542 Cord n.a. n.a. 15·4 n.a n.a. n.a n.a.

blood (0·2) . .

Rotterdam 488 Peripheral n.a. 488 64·0 n.a n.a. 63 425

Study – I (NL) blood (6·3) .

Rotterdam 703 Peripheral n.a. 703 67·5 n.a n.a. 92 611

Study – II (NL) blood (5·9) .

Lung function was obtained by spirometry and sex-, age-, height- and ethnicity-adjusted Z-scores were calculated. FEV1: Forced Expiratory Volume in 1 second; FVC: Forced Vital Capacity; FEF75:

Forced Expiratory Flow at 75% of FVC; n.a.: not applicable. UK: United Kingdom. NL: the

Netherlands. USA: United States of America.

Table 2. Associations of the Top Ten Significant Identified Differentially Methylated Regions with

Gene Expression and Related Respiratory Outcomes.

Molecular Lung Anno Expressed gene† Gene Gene Previously location of the funct tated expre expr associated with differentially ion gene ssion essio lung development methylated * in n in or respiratory region childr adult morbidity‖

(Chromosome: en‡ s§ start – end) chr1: 7,887,199 - FEV1 PER PER3, RP3-467l1.4, ↓ -

7,887,561 3 RNA5SP23, RP4-

726F1.1

RP11-431K24.1 - ↑ chr1: 86,968,087 FEV1 CLC no expression - - Lung

– 86,968,544 /FVC A1 development,

asthma, COPD chr5: 102,898,223 FEV1 NUD NUDT12 ↓ - Smoking

- 102,898,734 /FVC T12 behavior in

COPD

CMBL ↓ - chr6: 166,418,799 FEV1 LINC no expression - -

– 166,419,139 0060

2 chr7: 27,183,133 - FEV1 HOX HOXA1, HOTTIP ↓ ↓ Lung

27,184,854 A5 development,

FEV1, FEV1/FVC

EVX1, HOXA4, HOXA7 ↓ - Lung

development,

asthma, COPD chr7: 158,045,980 FEF7 PTP no expression - -

– 158,046,359 5 RN2 chr10: FEV1 PAO no expression - -

135,202,522 – X

135,203,201 chr10: FEV1 VEN TUBGCP2, RP11- ↓ -

135,051,149 – /FVC TX 122K13.12

135,051,582

VENTX, ECHS1 ↑ -

SPRN ↑ ↓

ZNF511 - ↑ chr14: 96,180,406 FEF7 TCL1 TCL1A, CCDC85C ↓ - Asthma

– 96,181,045 5 A chr19: 1,063,624 FEV1 ABC no expression - -

– 1,064,219 A7

Results present identified differentially methylated regions (DMRs) from association-analyses of DNA- methylation at birth with childhood Forced Expiratory Volume in 1 second (FEV1), FEV1/ Forced Vital

Capacity (FVC) and Forced Expiratory Flow at 75% of FVC (FEF75). *DMRs were annotated to their nearest gene. †: Identified DMRs at birth were associated with gene expression in: ‡: childhood

(INMA; mean age 4 years) and §: adulthood (the Rotterdam Study, mean age 66 years). Gene expressions levels were assessed limited to 250kb up- and downstream of the outer border of the

DMR. Directions of associations are marked ↓ if a higher methylation of the DMR was associated with a decreased expression of the specific gene, ↑ if a higher methylation of the DMR was associated with an increased expression of the specific gene, and - if no direction of associations were observed.

‖: Associations of expressed genes with lung development and respiratory morbidity were explored in previous published studies the OMIM database and UniProt.

Figure 1. Overall Study Design.

Epigenome-wide meta-analyses were performed to identify methylated CpGs associated with lung function in children using data from 1,689 children participating in ALSPAC, Generation R, INMA,

CHS and Project Viva. Identified differentially methylated regions (DMRs) were annotated to their nearest gene using PAVIS. Next, we examined if identified DMRs were associated with asthma in children participating in Generation R, lung function in adolescents and adults participating in the

ALSPAC or Rotterdam Study, or COPD in adults participating in Rotterdam Study, and with gene expression levels in children participating in INMA, adults in Rotterdam Study, and the GTEx- database. We further explored biological processes and associations with lung development and respiratory morbidity using publicly available resources (DAVID, GeneMania, OMIM and UniProt). N = x: number of participants included for the analysis. N = x/x: number of cases / total number of participants included in the analysis.

Figure 2. Manhattan Plots of Associations of CpGs located in Differentially Methylated Regions with

Childhood Lung Function Outcomes.

Green dots represent p-values from associations of CpGs located in differentially methylated regions

(DMRs) at birth with childhood Forced Expiratory Volume in 1 second (FEV1), FEV1/ Forced Vital

Capacity (FVC) and Forced Expiratory Flow at 75% of FVC (FEF75). P-values of DMRs ranged from

3·05E-14 to 0·031, and details are provided in Supplementary Appendix Table 3. Nearest annotated genes of DMRs are provided. The genes annotated to the top ten significant DMRs associated with childhood lung function are written in red. Single CpGs are presented as red and blue dots, corrected for correlations with neigboring CpGs.

Figure 3. Identified Differentially Methylated Regions and Their Location, and Direction of

Associations with Childhood Lung Function, Childhood Asthma, Adolescent Lung Function, and Adult

Lung Function and COPD.

Capacity (FVC) and Forced Expiratory Flow at 75% of FVC (FEF75), their location, and their direction of association with childhood lung function, childhood asthma, adolescent lung function, and adult lung function and COPD. Molecular locations of the top ten significant DMRs are presented in bold.

Identified DMRs associated with childhood lung function and other respiratory outcomes are marked in grey, and if not associated with respiratory outcomes in white. Directions of associations are marked ↓ if a higher mean methylation of the DMRs was associated with a lower z-score for lung function or lower risk of asthma or COPD, and marked ↑ if a higher mean methylation of the DMRs was associated with a higher z-score of lung function or higher risk of asthma or COPD. Red colored arrows represent disadvantageous effect estimates (lower lung function, increased risk of asthma or

COPD), and green colored arrows beneficial effect estimates (higher lung function, lower risk of asthma or COPD).

Supplementary Appendix

CONTENTS

Individual Cohort and Method Description

Statistical Analyses

Acknowledgements and Funding

Supplementary Tables 1 - 9

Supplementary Figures 1 - 2

References

Individual Cohort and Method Description

ALSPAC

The Avon Longitudinal Study of Parents and Children (ALSPAC) is a large, prospective cohort study based in the South West of England. In total, 14,541 pregnant women resident in Avon, UK with expected delivery dates between 1st April 1991 and 31st December 1992 were initially enrolled; 13,988 children were alive at 1 year.1,2 The study has been approved by the ALSPAC Ethics & Law

Committee (ALEC) and written consent was obtained from participating parents of their children.

Please note that the study website contains details of all the data that are available through a fully searchable data dictionary (http://www.bris.ac.uk/alspac/researchers/data-access/data-dictionary/).

For the current study, data on DNA methylation and lung function measures at age 10 years was available for 654 mothers and their children.

DNA-methylation Cord blood (whole blood or buffy coats) was collected according to standard procedures, spun and frozen at -80˚C. DNA-methylation data pre-processing was conducted as part of the Accessible Resource for Integrated Epigenomic Studies (ARIES) project

[ariesepigenomics.org.uk] at the University of Bristol.3 Briefly, DNA was bisulfite converted using

Zymo EZ DNA MethylationTM kit (Zymo, Irvine, CA). The Illumina Infinium® HumanMethylation450k

BeadChip assay was used to measure genome-wide methylation status. Assay arrays were scanned using the Illumina iScan and initial quality review was assessed using GenomeStudio (version

2011.1). Samples were distributed across slides using a semi-random approach. Samples with >20% probes with a detection p-value ≥0·01 failed quality control and were repeated. Genotype probes on the array were compared between samples of the same individuals and against genome wide SNP chip data to assess and remove any sample mismatches. The methylation data was pre-processed using the WateRmelon package in R (version 3.0.1) according to the subset quantile normalization approach as described by Touleimat and Tost.4 After assaying, repeat assays, pre-processing QC and normalization, 485,577 probes were available. Probes with a detection p-value of >0·05 for >5% of samples (N=3,033), probes residing on the X and Y chromosome and SNPs (N=11,713) were removed. This resulted in 471,193 probes for association analysis. Cell type proportions were estimated using the estimateCellCounts function in the minfi R package.5 This estimated the proportion of B-cells, CD8 T-cells, CD4 T-cells, granulocytes, NK-cells, monocytes and eosinophils in

each sample. Previous ALSPAC analysis with methylation data has shown that running models adjusted for bisulfite conversion batch caused non-singular fit errors (due to small batches). Batch was therefore included in all analyses by adding several surrogate variables generated using the sva() function in the SVA R package. Surrogate variables (SVs) were generated separately for every model and for each exposure. Ten SVs were generated and only those that were not associated with the lung function measure were included as covariates within each model. SVs are used to remove unwanted and unmeasured sources of bias. By including SV generation of all exposures, the SVs should capture unknown sources of variation and bias whilst maintaining the contribution of variation by the measured covariates and cell types. For this reason cell types was included in the SV analysis irrespective of whether the cell proportions are added as a covariate in that particular model in order to still observe the effect of cell proportions in the relevant models.

Respiratory Outcomes and Covariates Lung function was measured using spirometry at the Focus on Children clinic at the child’s ages of 8·6 (SD 0·2) and 15·4 (SD 0·2) years. We used the data of the children aged 15 years to replicate the DMRs identified in the discovery analyses. The correlations between the spirometric measures at age 8·6 and 15·4 years were weak to moderate (Pearson correlation for FEV1: 0·44, for FEV1/FVC: 0·44, for FEF75: 0·49). Lung function was measured using the Vitalograph 2120 hand-held spirometer connected to a computer-based pulmonary function package (spirotrac IV, Vitalograph, UK). The American Thoracic Society (1995) criteria were used as the basis to select lung function measurements that were acceptable for analysis.6 Maternal age at delivery was derived from the mother’s report of her own and child’s dates of birth. Maternal social class was recorded and derived from self-report questionnaire data of occupation according to the

Registrar General’s Social Classes based upon SOC 2000 codes. Data was collapsed to low

(classifications IV & V), middle (classifications of III (non-manual) & III (manual)) and high

(classifications of I & II). Maternal smoking status was derived from self-report questionnaire data completed by the mother. Smoking status was recorded at 18 weeks and 32 weeks gestation. Parity was extracted from medical records. Finally, maternal asthma or atopy was reported by questionnaire completed by the mothers at 12 weeks gestation. This variable was derived from questionnaire indicators of ―had asthma‖, ―had eczema‖ and ―had allergy‖. Ethical approval for the study was obtained from the ALSPAC Ethics and Law Committee and the Local Research Ethics Committees.

Generation R

The Generation R Study is a population-based prospective cohort study from fetal life onwards in

Rotterdam, the Netherlands.7 Assessments in pregnant women and children consisted of physical examinations, fetal ultrasounds, biological samples, and questionnaires. All children were born between April 2002 and January 2006. The study has been approved by the Medical Ethical

Committee of the Erasmus University Medical Center and written consent was obtained from participating parents of their children. For the current study, data was available for 643 Caucasian mothers and their children.

DNA-methylation DNA was extracted from cord blood samples of 979 Caucasian children. Using the

EZ-96 DNA-methylation kit (Shallow-well) (Zymo Research Corporation, Irvine, USA), 500 ng DNA per sample underwent bisulfite conversion. Samples were transferred onto 96-well plates in a random order. Samples were processed with Illumina’s Infinium HumanMethylation450 BeadChip (Illumina

Inc., San Diego, USA). Quality control of analyzed samples was performed using standardized criteria. Samples were excluded due to sample call rate <99% (n=7) or poor bisulfite conversion

(n=1). In addition, 2 samples were excluded because of a gender mismatch and 1 sample because of a retracted informed consent, leaving a total of 969 samples in the statistical analysis. Probes with a single nucleotide polymorphism in the single base extension site with a frequency of >1% in the

GoNLv4 reference panel were excluded, as were probes with non-optimal binding (non-mapping or mapping multiple times to either the normal or the bisulphite-converted genome), resulting in the exclusion of 49,564 probes, leaving a total of 436,013 probes in the analysis. Data were normalized with DASES normalization using a pipeline adapted from that developed by Touleimat and Tost.4

DASES normalization includes background adjustment, between-array normalization applied to type I and type II probes separately, and dye bias correction applied to type I and type II probes separately.

DASES is based on the DASEN method, but adds the dye bias correction, which is not included in

DASEN.8 Beta-values were calculated for all CpG sites.

Respiratory Outcomes and Covariates Spirometry according to the criteria of the American

Thoracic Society/ European Respiratory Society guidelines was performed at age 9·8 years (SD 3·0) to measure lung function. Physician-diagnosed ever asthma (no; yes) was assessed using questions adapted from the International Study on Asthma and Allergy in Childhood (ISAAC) at age 6 years.9

Information on maternal age, educational level as measure for socio-economic status, smoking during pregnancy, parity, and asthma and atopy was collected by questionnaires at enrollment. Maternal educational level was categorized as lower (none, primary or secondary education) or higher (more than secondary education). Information on maternal smoking at enrolment was combined with information on maternal smoking thereafter obtained by multiple questionnaires during pregnancy, and combined (no; yes). Parity was categorized as nulliparity or multiparity.

INMA

The INMA—INfancia y Medio Ambiente—(Environment and Childhood) Project is a network of birth cohorts in Spain that aim to study the role of environmental pollutants in air, water and diet during pregnancy and early childhood in relation to child growth and development

(http://www.proyectoinma.org/).10 The study has been approved by Ethical Committee of each participating center and written consent was obtained from participating parents. Data for this study comes from 140 children participating in the INMA Sabadell subcohort.

DNA-methylation Cord blood at birth was obtained in EDTA tubes and extracted using the Chemagic

DNA Blood Kits (Perkin Elmer) in a Chemagen Magnetic Separation Module 1 station at the Spanish

National Genotyping Center (CEGEN, http://www.usc.es/cegen/). DNA concentration was determined by NanoDrop Spectrophotometer (Thermo Scientific) measurement and Quant-iT PicoGreen dsDNA

Assay Kit (Life Technologies) quantification. Some of the samples underwent a precipitation-based concentration and purification using GlycoBlue (Ambion) to uniform the concentration and purity. After normalization of the concentration, the samples were randomized to reduce batch effects. Standard male and female DNA samples were included in this step as internal controls. Samples were processed with the Infinium HumanMethylation450 BeadChip at the Genome Analysis Facility of the

University Medical Center Groningen (UMCG) in Holland as part of the MeDALL project (Mechanisms of the Development of ALLergy). 500 ng of DNA of each sample were bisulfite- converted using the

EZ 96-DNA-methylation kit following the manufacturer’s standard protocol. After verification of the bisulfite conversion using Sanger Sequencing, the DNA-methylation was measured using the Illumina

Infinium HumanMethylation450 BeadChip. IDAT files were preprocessed imported using minfi.11 The preprocessing steps were:1) sample filtering to remove bad quality and mixed up samples, 2) 65

SNPs probes, the probes on sex chromosomes, potential cross reactive probes, and probes

containing SNPs at the target CpG sites with a MAF>10% (polymorphic) were excluded (cross reactive and polymorphic probes).12 A total of 439,306 CpG probes were retained for downstream analyses, 3) Signal correction and normalization was performed using ―DASEN‖, 4) batch correction was attained including the significant (permutation p-value < 10-4) principal components derived from the 613 negative control probes presented in 450K arrays.8 Twelve samples were excluded because they were outliers defined as more than 3 SD from the mean for PC1 or PC2 or there were sex discrepancies. The final sample size was 107. After 10,000 permutations five PCs were retained.

The beta-values were batch corrected incorporating these five PCs and calculating the residuals of the linear model. These residuals were used to test their association with lung function.

Respiratory Outcomes and Covariates Spirometry according to the criteria of the American

Thoracic Society/ European Respiratory Society guidelines was performed at age 6·9 (SD 0·3) years to measure lung function.6 Information on maternal age, socio-economic status, smoking during pregnancy, parity, and asthma or atopy was collected by questionnaire at enrollment (week 12 of pregnancy). Maternal education was based on maternal occupation at pregnancy and categorized into three levels: low (levels V/VI semi-skilled/unskilled occupations), medium (levels III/IV skilled manual/non-manual) or high (managers/technicians). Pregnant women were asked whether they were current smokers (at week 32 of pregnancy) and if so, how much. They were also asked if they had stopped smoking due to pregnancy and when (before pregnancy or at what month of pregnancy). Any smoking was defined as smoking any number of cigarettes at any time during pregnancy. Parity was categorized into 0 or ≥1.

Gene Expression Gene expression data was collected at 4 years of age. Whole blood was collected in PAXGene tubes and extracted using the kit recommended by the company. All samples had a RNA

Integrity Number (RIN) higher than 7. Gene expression data was obtained using Affymetrix HTA 2.0 at the European Institute for Systems Biology and Medicine in Lyon as part of the MeDALL project.

Gene expression was normalized with the RMA algorithm using the Expression Console Software from Affymetrix and probes were clustered to the transcript level. Expression transcripts were annotated using version 35 of Affymetrix annotation. The final sample size was 107.

For the DNA-methylation vs gene expression analysis, only the list of CpGs considered significant from the meta-analysis in newborns were tested. To control for technical variation in the

DNA-methylation dataset, a principal component analysis of 600 negative control probes using 10,000 permutations was performed, and the residuals of a linear regression model using the first five PCs were estimated. Next, the effect of sex and Houseman cell proportions estimates were controlled out in a second stage linear regression model. Only transcripts inside a 500 kb window of a selected

CpG sites (250 kb downstream and 250 kb upstream) were considered in the analysis (N=5,568 transcripts). Two models were applied to control for technical and unwanted biological variation when estimating gene expression residuals. In the first one, sex and six cell estimates obtained from the methylation values using the Houseman algorithm were regressed out.5 In the second one, 14 surrogate variables were detected and added to a second model including sex and six cell estimates.

Surrogate variables were estimated using the SVA R package. Finally, linear models of residuals of gene expression vs residuals of methylation were performed. The following associations were tested: methylation 0 years vs expression 4 years; and methylation 4 years vs expression 4 years. All the analyses were performed with R.

Children’s Health Study

The Children’s Health Study (CHS) has enrolled over 11,000 children in a series of cohorts investigating the health effects of air pollution. The study protocol was approved by the institutional review board for human studies at the University of Southern California, and written informed consent was provided by a parent or legal guardian for all study participants. The current analysis includes a cohort established in 2002–2003 when participants were 5–7 years of age, containing 75 children with available data on DNA-methylation in cord blood and childhood lung function.13

DNA-methylation Laboratory personnel performing DNA-methylation analysis were blinded to study subject information. DNA was extracted from cord bloodspots using the QiaAmp DNA blood kit

(Qiagen Inc, Valencia, CA) and stored at -80 degrees Celcius. 700 ng to 1 µg of genomic DNA from each sample was treated with bisulfite using the EZ-96 DNA-methylationKit™ (Zymo Research, Irvine,

CA, USA), according to the manufacturer’s recommended protocol and eluted in 18 µl. The results of the Infinium HumanMethylation450 BeadChip (HM450) were compiled for each locus using the methylumi package in R as previously described and were reported as beta values. 14 CpG loci on the

HM450 array were removed from analyses if they were on the X and Y chromosomes, or if they contained SNPs, deletions, repeats, or if they have more than 10% missing values, leaving 383,857

probes for analysis. A normal exponential background correction was first applied to the raw intensities at the array level to reduce background noise followed by dye bias correction.15 We then normalized each sample’s methylation values to have the same quantiles to address sample to sample variability.16

Respiratory Outcomes and Covariates At study visits at age 13·3 (SD 0·6), trained technicians measured lung function, weight, and height, and collected information about recent acute respiratory illness. Using pressure-transducer-based spirometers (Screenstar Spirometers, Morgan Scientific,

Haverhill, MA), we identified lung function measures from a series of seven efforts from each child, as described previously.17,18 Questionnaires completed by parents or guardians at study enrollment provided information on participants’ health, socio-demographic and other exposures, which was updated yearly. Information included maternal age, education, smoking during pregnancy parity and asthma or atopy. Maternal educational level was categorized as lower (none, primary or secondary education) or higher (more than secondary education) education.

Project Viva

Project Viva is a longitudinal pre-birth cohort of mother-offspring pairs. Study participants were enrolled between April 1999 and July 2002 from Atrius Harvard Vanguard Medical Associates, a multi- site group medical practice in eastern Massachusetts. All mothers in the study signed informed consents, and the study protocols were approved by the institutional review board of Harvard Pilgrim

Health Care. Details on recruitment and data collection have been published elsewhere.19 Exclusion criteria included non-singleton pregnancy, planning to relocate before delivery, unable to answer questions in English, and gestational age >22 completed weeks at initial prenatal visit. A total of 176 children with available data on DNA-methylation in cord blood and lung function in childhood were included for the current study. A total of 470,870 CpGs were available for analysis.

DNA-methylation DNA samples extracted from cord blood were arranged using a stratified randomization to ensure balance of cohort characteristics across sample plates/batches. Samples were bisulfite converted using the EZ-96 DNA-methylation kit (Zymo Research Corporation, Irvine,

USA). The Illumina Infinium HumanMethylation450 BeadChip (Illumina Inc., San Diego, USA) was run at Illumina FastTrack Microarray Services (San Diego, CA). Failing samples were rerun and passing arrays were defined as having >99% of probes with a detection p value 0·05 was set to NA (but

included no more than 5 samples per probe by the failure criteria described). Pre-processing for the secondary model included four additional steps: 1. background subtraction using the out-of-band probes (noob) as implemented in methylumi; 2. dye bias adjustment using the methylumi default; 3. within array type II probe adjustment using BMIQ as implemented in wateRmelon; and 4. conversion to M-values, adjustment for analytic plate using ComBat (plate was the largest batch effect seen in

PCA), and subsequent transformation back to the beta scale.

Respiratory Outcomes and Covariates Mothers and children attended in-person visits at 6 months after delivery and in mid-childhood (mean age 7·9 (SD 0·7) years). At the mid-childhood visit, trained research assistants measured child height and lung function. We obtained lung function measurements, including the forced expiratory volume in 1 second (FEV1), forced vital capacity

(FVC), and forced expiratory flow at 75% (FEF75) using the EasyOne Spirometer (NDD Medical

Technologies, Andover, MA). We obtained questionnaire and interview data, including maternal and household demographics, tobacco exposure, parity and asthma or atopy from the mother at study enrollment during the first prenatal visit and at the mid-childhood visit.

Rotterdam Study

The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The

Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, otolaryngological, locomotor, and respiratory diseases. As of 2008,

14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort.20 Data in the Rotterdam

Study was derived from two independent subsets. The first subset consisted participants of cohort III, first visit (III-1), and the second subset consisted participants from cohort I, fifth visit (I-5), cohort II, third visit (II-3), and cohort III, second visit (III-2).20 These two subsets are independent of each other.

The Rotterdam Study has been approved by the Medical Ethics Committee of the Erasmus University

Medical Center and by the Ministry of Health, Welfare and Sport of the Netherlands , implementing the Wet Bevolkingsonderzoek: ERGO (Population Studies Act: Rotterdam Study). All participants provided written informed consent to participate in the study and to obtain information from their treating physicians.

DNA-methylation In Rotterdam study, DNA-methylation and gene expression datasets were produced at the Genetic Laboratory (Department of Internal Medicine, Erasmus University Medical

Center, Rotterdam, the Netherlands). DNA was extracted from whole peripheral blood by standardized salting out methods. This was followed by a bisulfide conversion using the Zymo EZ-96

DNA-methylation kit (Zymo Research, Irvine, CA, USA). The genome for each sample was then amplified, fragmented and hybridized to the Infinium Illumina Human Methylation 450K arrays according to the manufacturer’s protocol. The quality control for samples was performed using the

Methylation Module of the GenomeStudio software. Data was extracted into beta values from raw

IDAT files. We excluded samples based on the detection p-value criteria >99%, poor bisulfite conversion based on control dashboard check and failed chromosome X & Y clustering. Data preprocessing was performed using an R programming pipeline based on the pipeline developed by Tost

& Touleimat, which includes additional parameters and options to pre-process and normalize methylation data directly from idat files. The beta values were extracted using methylumi. We excluded probes which had a detection p-value >0·01 in >95% of samples. We used DNA-methylation data generated for a subset of 731 individuals of RS-III. Second independent subset was comprising of the individuals at their fifth, third and second visits of RS-I, RS-II and RS-III respectively, between

2009-2013. Those individuals were not included in the first subset, and are part of the Biobanking and

Biomolecular Resources Research Infrastructure for The Netherlands (BBMRI-NL), BIOS (Biobank- based Integrative Omics Studies) project (http://www.bbmri.nl/?p=259). After filtering we ended up with 731 samples and 463,456 probes in the first dataset, and 767 samples and 419,937 probes in the second dataset. The raw beta values were then background corrected and normalized using the

DASEN option of the WateRmelon R-package. Linear regression models for epigenome-wide association analyses, based on subjects with spirometry data, were restricted to 488 individuals in the first and 702 individuals in the second dataset.

Respiratory Outcomes and Covariates In Rotterdam Study, spirometry was performed by trained paramedical personnel, according to the guidelines of the American Thoracic Society/European

Respiratory Society, using the Master Screen® PFT Pro (CareFusion, San Diego, CA). The diagnosis of COPD was based on an obstructive spirometry examination according to the modified Global

Initiative for Chronic Obstructive Lung Disease criteria (proportion of the FEV1/FVC <0·7). Participants with a spirometry report suggestive of restrictive respiratory disease (FEV1/FVC ≥0·7 and FVC or

FEV1 < 80% predicted) and patients with asthma were excluded. No reversibility tests were conducted. When spirometry measures were absent, medical information was reviewed, including

files from specialists and general practitioners, to label a diagnosis of COPD. Data on participants current age, sex, social class (low, middle, high) and smoking status (never, ever) was collected by questionnaires.

Gene Expression mRNA gene expression and 450K methylation data, both from whole-blood samples from 730 adults over 45 years of age in the Rotterdam Study, was collected (PAXGene

Tubes – Becton Dickinson) and total RNA was isolated (PAXGene Blood RNA kits - Qiagen). To ensure a constant high quality of the RNA preparations, all RNA samples were analyzed using the

Labchip GX (Calliper) according to the manufacturer’s instructions. Samples with an RNA Quality

Score more than 7 were amplified and labeled (Ambion TotalPrep RNA), and hybridized to the

Illumina HumanHT12v4 Expression Beadchips as described by the manufacturer’s protocol.

Processing of the Rotterdam Study RNA samples was performed at the Genetic Laboratory of Internal

Medicine, Erasmus University Medical Center Rotterdam. Illumina gene expression data was quantile- normalized to the median distribution and subsequently log2-transformed. The probe and sample means were centered to zero. Genes were declared significantly expressed when the detection p values calculated by GenomeStudio were less than 0·05 in more than 10% of all discovery samples, which added to a total number of 21,238 probes. Quality control was done using the eQTL-mapping pipeline. We only analyzed probes that uniquely mapped to the human genome build 37. Gene expression was assessed within a region of 250-kb upstream or downstream of the CpG (total region

500 kb).

Statistical Analyses

Primary Meta-analysis on Childhood Lung Function All cohorts performed spirometry according to the American Thoracic Society / European Respiratory Society recommendations.6 The cohort- specific statistical models were run independently. For each cohort, robust linear regression models were used to evaluate the associations of cord blood DNA-methylation for each CpG-site with FEV1,

th FEV1/FVC and FEF75. All cohorts excluded DNA-methylation data outside the range ([25 percentile –

3* interquartile range) and (75th percentile + 3* interquartile range]). For the meta-analyses, we excluded probes that were missing in ≥3 cohorts (n=12,960), probes that mapped to X- or Y- chromosomes (n=11,448) and control probes (n = 65). A total of 457,748 CpGs were used for meta- analyses. First, models were adjusted for batch effects only. Second, models were additionally adjusted for maternal age, socio-economic status, smoking during pregnancy, parity, and asthma or atopy, and estimated cell type proportions using the Houseman method.5 Results did not materially differ without adjustment for estimated cell type proportions. Inverse variance-weighted fixed-effects meta-analysis was completed using METAL.21 The median I2 value for all CpGs located in differentially methylated regions (DMRs) associated with FEV1 was 4·9, with FEV1/FVC 0.0, and with

FEF75 2·4, indicating a strong homogeneity of the results across the cohorts. The genomic inflation factors (λ) for the associations with childhood FEV1, FEV1/FVC and FEF75 were 1·21, 1·07 and 1·11, respectively (Supplementary Figures 1a-c).

The rationale to identify associations of DMRs instead of single CpGs is threefold. First, the vast majority of DMRs reported in the literature fall within a size range of a few hundred to a few thousand bases. This range coincides with typical sizes of gene-regulatory regions, and it is widely believed that DMRs can control cell-type-specific transcription of an associated gene. Second, while differences at any individual site may be small, if they are consistent across a region, statistical power to detect them may be greater. Third, the use of DMRs instead of single CpGs minimizes the effects of genetic variants in the methylation analysis. This is driven by the applied Stouffer-Liptak-Kechris

(SLK)-correction, in which each p-value is adjusted according to adjacent p-values as weighted according to the correlation with neighboring CpGs. A given p-value will be pulled down if its neighbors also have low p-values (and little auto-correlation) and likely remain insignificant if the neighboring p-values are also high.

Using p-values obtained from the meta-analyses we identified DMRs with the software-tool

Comb-p, using a window size of 500 bases and FDR-threshold <0·05 with a minimum of 2 probes to start a region.22 The window size of 500 bases was based on the strong correlation of CpGs within this distance, whereas at distances larger than 1,000 bases no correlation between CpG methylation and spatial distance is detectable.23 Comb-p uses unadjusted p-values for each probe as input, and calculates adjusted p-values for each probe that accounts for the correlation with nearby CpGs (SLK- correction).23 Next, the SLK p-values are adjusted for multiple testing and adjusted into q-values using the false-discovery rate (FDR) procedure of Benjamini-Hochberg. Comb-p finds DMRs based on the q-values and calculates p-values for these DMRs based on Stouffer-Liptak correction of the original p- values. Finally, the DMR p-values are adjusted for multiple testing using the Šidák-correction based on the size of the region and number of possible regions of that size. For a given region, the number of possible tests in the Šidák-correction is the total bases covered by all input probes divided by the size of the given region, such that larger regions undergo less stringent correction because there are fewer possible large regions.

Annotation of the genes located nearest to the DMRs was performed using Peak Annotation and Visualization (PAVIS).24 We limited annotation to a region of 500 kb (250kb upstream, 250kb downstream). All annotations were based on human GRCh37/hg19 assembly. Because genetic variants in Infinium probes could result in spurious methylation measurements, we performed a sensitivity analysis in a subset of high-quality probes (n=294,834) without SNPs, insertions or deletions, repeats and bisulfite induced reduced genomic complexity.25

Secondary Analyses on Later Life Lung Function and Respiratory Diseases The associations of all CpGs present in the DMRs with lung function were replicated at older age in ALSPAC (DNA- methylation in cord blood) and the Rotterdam Study (DNA-methylation in peripheral blood samples).

The statistical models in ALSPAC were adjusted for similar confounders used in the discovery analyses. The statistical models in the Rotterdam Study were adjusted for participants current age, sex, social class (low, middle, high), smoking status (never, ever), technical covariates and estimated cell counts.5 We combined the p-values of the individual associations into the previous identified

DMRs using Comb-p, applying correlation-correction based on the discovery meta-analysis using identical parameter settings. We considered SL p-values <0·05 significant. We used logistic

regression models to examine the associations of CpGs within identified DMRs with ever physician- diagnosed asthma in childhood. The statistical model was adjusted for maternal age, smoking during pregnancy, maternal asthma or atopy, gender, batch effects and estimated cell counts.5 We did not additionally adjust for the correlation between asthma and lung function in children in Generation R, because most school-aged children have an FEV1 >80% predicted, independent of their asthma

26 severity when defined on the basis of symptoms. In childhood, FEV1 may not be sensitive and may have a different physiological meaning as compared with older ages.27 We used linear regression models to examine the associations of CpGs within identified DMRs with FEV1, FEV1/FVC and FEF75 in adolescence. Statistical models were adjusted for maternal age, socio-economic status, smoking during pregnancy, parity, asthma or atopy, batch effects and estimated cell counts. Last, we used linear and logistic regression models to examine the associations of CpGs within identified DMRs with

FEV1, FEV1/FVC and FEF75 and COPD in adulthood. The statistical models were adjusted for participants age, sex, social class (low, middle, high), smoking status (never, ever), technical covariates and estimated cell counts.5

Gene Expression Analyses We examined the associations of methylation of individual CpGs with quantitative levels of gene expression for all significant CpGs located in the DMRs. We used 450K

DNA-methylation data in cord blood and at age 4 years, and gene expression data at age 4 years obtained from whole blood from 107 individuals in INMA. Furthermore, we used gene expression and

450K methylation data both from white blood cells from 730 adults aged >45 years in the Rotterdam

Study. Individual associations of CpGs with expression levels of all genes within a distance of 250 kb upstream and downstream (total region 500 kb) were assessed. Since correlations between CpGs for gene expression might differ from the correlations between CpGs for lung function parameters, we could not use Comb-p to reconstruct DMRs. Therefore, we combined the p-values of the individual associations between CpGs and gene expression into DMRs using a modified generalized Fisher method with Lancaster procedure, after which we applied multiple testing correction using the

Benjamini-Hochberg procedure.28 Last, we assessed whether expressed genes were also expressed in 278 human adult lung tissue specimen using the Genotype-Tissue Expression (GTEx) Version 6 database.29

Acknowledgements and Funding

ALSPAC

We are extremely grateful to all the families who took part in the ALSPAC study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The UK Medical Research Council and the Wellcome Trust (Grant ref: 102215/2/13/2) and the

University of Bristol provide core support for ALSPAC. The Accessible Resource for Integrated

Epigenomics Studies (ARIES) was funded by the UK Biotechnology and Biological Sciences

Research Council (BB/I025751/1 and BB/I025263/1). This work was supported by the Medical

Research Council Integrative Epidemiology Unit and the University of Bristol (MC_UU_12013_2). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Generation R

The Generation R Study is conducted by the Erasmus University Medical Center in close collaboration with the School of Law and Faculty of Social Sciences of the Erasmus University

Rotterdam, the Municipal Health Service Rotterdam area, Rotterdam, the Rotterdam Homecare

Foundation, Rotterdam and the Stichting Trombosedienst & Artsenlaboratorium Rijnmond (STAR-

MDC), Rotterdam. We gratefully acknowledge the contribution of children and parents, general practitioners, hospitals, midwives and pharmacies in Rotterdam. The study protocol was approved by the Medical Ethical Committee of the Erasmus University Medical Center, Rotterdam. Written informed consent was obtained for all participants. The generation and management of the Illumina

450K methylation array data for Generation R was executed by the Human Genotyping Facility of the

Genetic Laboratory of the Department of Internal Medicine, Erasmus University Medical Center, the

Netherlands. The EWAS data was funded by a grant to Vincent W.V. Jaddoe from the Netherlands

Genomics Initiative (NGI)/Netherlands Organization for Scientific Research (NWO), Netherlands

Consortium for Healthy Aging (NCHA; project nr. 050-060-810), and by funds from the Genetic

Laboratory of the Department of Internal Medicine, Erasmus University Medical Center. We thank

Michael Verbiest, Mila Jhamai, Sarah Higgins, Marijn Verkerk and Lisette Stolk for their help in

creating the EWAS database. Generation R is made possible by financial support from the Erasmus

University Medical Center, Rotterdam, the Erasmus University Rotterdam and the Netherlands

Organization for Health Research and Development. Vincent W.V. Jaddoe received funding from the

Netherlands Organization for Health Research and Development (VIDI 016.136.361) and a

Consolidator Grant from the European Research Council (ERC-2014-CoG-64916). Liesbeth Duijts received funding from the Netherlands Organization for Health Research and Development

(ALPHABET 529051014) and the Lung Foundation Netherlands (no 3.2.12.089; 2012). Janine F.Felix received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 633595 (DynaHEALTH). Vincent W.V. Jaddoe, Liesbeth Duijts and Janine F.

Felix received funding from the European Union’s Horizon 2020 research and innovation programme

(733206, LIFECYCLE). The researchers are independent from the funders. The study sponsors had no role in the study design, data analysis, interpretation of data, or writing of this report.

INMA

INMA researchers would like to thank all the participants for their generous collaboration. INMA researchers are grateful to Silvia Fochs, Nuria Pey, and Muriel Ferrer for their assistance in contacting the families and administering the questionnaires. A full roster of the INMA Project Investigators can be found at http://www.proyectoinma.org/presentacion-inma/listado-investigadores/en_listado- investigadores.html. INMA was funded by grants from Instituto de Salud Carlos III (Red INMA

G03/176, CB06/02/0041), Spanish Ministry of Health (FIS-PI041436, FIS-PI081151), Generalitat de

Catalunya-CIRIT 1999SGR 00241, Generalitat de Catalunya-AGAUR 2009 SGR, Fundació La marató de TV3 (090430), CIBERESP, EU Commission (261357-MeDALL: Mechanisms of the Development of ALLergy). LAS was supported through a Colciencias PhD Scholarship, Colombia (Grant:

529/2011). CR-A was supported by a FI fellowship from Catalan Government (#016FI_B 00272).

Children’s Health Study

We would like to express our sincere gratitude to Martin Kharrazi, Steve Graham and Robin Cooley at the California Biobank Program and Genetic Disease Screening Program within the California

Department of Public Health for their assistance and advice regarding newborn bloodspots. We are

indebted to the school principals, teachers, students and parents in each of the study communities for their cooperation and especially to the members of the health testing field team for their efforts. This work was supported by the following NIH grants: 5K01ES017801, 1R01ES022216, 5P30ES007048,

P01ES011627, R01ES014447, R01HL061768, R01HL087680.

Project Viva

The authors thank the mothers and children of Project Viva. The Project Viva cohort is funded by NIH grants R01HL111108, R01NR013945, and R01HD034568.

Rotterdam Study

The Rotterdam Study is funded by Erasmus University Medical Center and Erasmus University,

Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the

Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam. The authors are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. The generation and management of the

Illumina 450K methylation array data was executed by the Human Genotyping Facility of the Genetic

Laboratory of the Department of Internal Medicine, Erasmus University Medical Center, the

Netherlands. The EWAS data was funded by the Genetic Laboratory of the Department of Internal

Medicine, Erasmus University Medical Center, and by the Netherlands Organization for Scientific

Research (NWO; project number 184021007) and made available as a Rainbow Project (RP3; BIOS) of the Biobanking and Biomolecular Research Infrastructure Netherlands (BBMRI-NL). The authors thank Michael Verbiest, Mila Jhamai, Ms. Sarah Higgins, Marijn Verkerk and Lisette Stolk for their help in creating the methylation database. The generation and management of RNA-expression array data was executed and funded by the Human Genotyping Facility of the Genetic Laboratory of the

Department of Internal Medicine, Erasmus University Medical Center, the Netherlands. The authors thank Mila Jhamai, Sarah Higgins, Marjolein Peters, Marijn Verkerk and Jeroen van Rooij for their help in creating the RNA array expression database. Najaf Amin is supported by grant number

4.1.13.007 of the Longfonds COPD consortium. Lies Lahousse is a Postdoctoral Fellow of the

Research Foundation-Flanders (FWO).

Supplementary Table 1. Unadjusted and Fully Adjusted Associations of Differentially Methylated

Regions with Childhood Lung Function Outcomes.

Unadjusted model Full model Chr Start End No. of P-value No. of P-value probes probes FEV1 1 1,957,385 1,957,806 2 1 4 0·016 1 7,887,199 7,887,561 4 0·121 5 7·27E- 05 1 17,222,405 17,222,716 - - 2 0·019 1 38,461,540 38,461,897 - - 4 0·029 1 45,452,166 45,452,606 7 3·01E-04 7 6·89E- 04 1 47,915,553 47,915,952 6 6·61E-03 6 5·50E- 03 3 195,489,708 195,490,31 8 1·71E-04 8 7·46E- 0 05 5 88,179,235 88,179,540 2 1 6 9·96E- 03 6 114,181,482 114,181,79 3 0·013 3 3·59E- 9 03 6 166,418,799 166,419,13 4 2·24E-05 4 4·55E- 9 06 7 27,183,133 27,184,854 49 3·48E-21 47 3·05E- 14 7 76,828,885 76,829,169 - - 2 0·031 7 130,131,480 130,132,16 - - 18 1·34E- 2 03 10 135,202,522 135,203,20 7 2·19E-06 7 6·65E- 1 09 11 843,897 844,285 - - 6 0·016 12 120,763,487 120,763,87 5 1·81E-03 5 1·23E- 0 03 15 64,995,133 64,995,502 3 1 5 0·025 16 22,018,727 22,019,308 3 7·19E-03 4 1·42E- 04 16 88,803,803 88,804,052 4 7·25E-03 4 4·36E- 03 17 9,550,137 9,550,546 - - 5 0·015 17 59,940,709 59,941,133 2 0·072 8 2·09E- 03 19 1,063,624 1,064,219 2 6·21E-03 3 3·83E- 05

FEV1/FV 1 1,564,422 1,564,921 2 1·17E-03 4 8·51E- C 05 1 86,968,087 86,968,544 3 4·02E-03 4 3·59E- 06 2 121,223,534 121,223,96 - - 6 1·28E- 5 04 5 102,898,223 102,898,73 6 2·56E-05 6 6·95E- 4 05 6 32,305,068 32,305,146 - - 3 2·21E-

03 6 168,533,375 168,533,69 1 1 4 0·017 0 10 135,051,149 135,051,58 3 0·99 11 4·28E- 2 05 11 64,064,947 64,065,372 3 4·23E-03 3 7·71E- 03 11 67,417,958 67,418,406 - - 13 9·21E- 03 13 20,805,380 20,805,896 9 1·02E-05 9 1·22E- 04 14 96,180,406 96,181,045 - - 10 1·49E- 03 16 89,023,389 89,023,634 - - 3 1·45E- 03 17 19,314,299 19,314,619 - - 6 3·39E- 04 17 79,485,529 79,485,710 - - 2 0·029 21 40,759,534 40,759,695 5 2·29E-04 5 1·66E- 04 FEF75 1 1,957,073 1,957,712 5 0·012 5 7·53E- 03 1 2,383,438 2,383,688 - - 4 0·013 1 17,634,543 17,634,717 4 3·24E-03 4 0·016 1 86,968,087 86,968,256 3 0·075 3 0·015 2 14,774,786 14,774,903 - - 3 0·013 2 54,086,854 54,087,553 6 0·010 14 4·08E- 03 3 62,860,103 62,860,225 2 3·12E-03 2 0·013 5 125,931,001 125,931,36 8 7·26E-04 7 7·83E- 3 03 5 135,416,029 135,416,61 4 1 11 1·34E- 4 03 5 138,725,400 138,725,83 5 8·21E-03 5 6·06E- 1 04 6 31,650,735 31,651,159 21 3·61E-05 16 3·45E- 03 6 31,690,998 31,691,540 - - 10 0·020 6 132,271,361 132,271,58 - - 3 5·89E- 9 04 7 158,045,980 158,046,35 6 3·29E-06 6 1·14E- 9 06 8 142,377,303 142,377,49 6 3·06E-03 5 4·31E- 0 03 11 2,721,207 2,721,633 19 1·98E-05 14 0·029 11 67,417,958 67,418,406 - - 13 7·07E- 03 12 114,843,919 114,844,26 7 3·63E-04 3 0·025 6 14 96,180,406 96,181,045 10 8·50E-07 10 2·20E- 06 16 89,023,389 89,023,634 3 3·00E-03 3 1·55E- 03

17 44,897,431 44,897,513 1 1 2 3·95E- 04 21 40,759,534 40,759,695 - - 5 0·024 Results present identified differentially methylated regions (DMRs) from association-analyses of DNA- methylation at birth with childhood Forced Expiratory Volume in 1 second (FEV1), FEV1/ Forced Vital

Capacity (FVC) and Forced Expiratory Flow at 75% of FVC (FEF75). Crude model: adjusted for batch effect. Full model: adjusted model, additionally adjusted for estimated cell counts. Start: Genetic location of the start of the DMR. End: Genetic location of the end of the DMR. No.: total number of

CpGs located in the DMR. P-value: Šidák-corrected p-values.

Supplementary Table 2. Characteristics of the Covariates of Cohorts.

Maternal Maternal socio-economic status % (n) Maternal Ever Maternal Maternal age in years smoking smoking nulliparity % asthma or mean (SD) during (n) atopy % (n) % (n) Low Middle High pregnancy % (n)

Childhood ALSPAC (UK) 30·3 (4·2) 8·3 (54) 43·6 (285) 48·2 (315) 11·8 (77) n.a. 48·9 (320) 58·7 (384)

Generation R (NL) 31·6 (4·2) 12·4 (71) 49·2 (282) 38·4 (220) 19·4 (111) n.a. 63·7 (365) 38·7 (222)

INMA (Spain) 32·1 (4·1) 21·4 (30) 30·7 (43) 47·9 (67) 24·3 (34) n.a. 51·4 (72) 32·1 (45)

Children’s Health Study 30·7 (5·4) 16·0 (12) 37·3 (28) 46·7 (35) 8·0 (6) n.a. 41·3 (31) 53·3 (40) (CHS) (USA)

Project Viva (USA) 33·4 (4·5) 20·5 (36)# n.a.# 79·5 (140)# 6·3 (11) n.a. 47·2 (83) 39·8 (70)

Adolescents / adults ALSPAC (UK) n.a. 30·2 (4·2) 8·9 (48) 43·5 (236) 47·6 (258) 11·8 (64) 50·4 (269) 57·2 (310)

Rotterdam Study – I (NL)* n.a. 7·6 (37) 59·5 (290) 32·9 (323) n.a. 66·2 (323) n.a. n.a.

Rotterdam Study – II n.a. 16·2 (114) 58·7 (412) 25·1 (176) n.a. 67·7 (475) n.a. n.a. (NL)*

#Project Viva: Maternal socio-economic status was defined as college graduate (no: lower educated; yes: higher educated). n.a.: not applicable.

Supplementary Table 3. Associations of Differentially Methylated Regions (DMRs) with Childhood

Lung Function Outcomes, Location of DMRs, and Direction of Association of DMRs with Childhood

Lung Function Outcomes.

Distance Directi to on of Chr No. Seque nearest associ omo of P- Neares Loca nce Start End transcrip ation som pro value t gene tion locatio tion e bes n start site (bases) FEV1 1 1,957,38 1,957,80 4 0·016 GABR S- 6,828 Intron ↓ 5 6 D Shor e 1 7,887,19 7,887,56 5 7·27 PER3 Islan 42,618 Exon ↓ 9 1 E-05 d 1 17,222,4 17,222,7 2 0·019 CROC Islan -25,884 Upstrea ↑ 05 16 C d m 1 38,461,5 38,461,8 4 0·029 FHL3 Islan 9,469 Downst ↓ 40 97 d ream 1 45,452,1 45,452,6 7 6·89 EIF2B3 Islan 8 5'UTR ↑ 66 06 E-04 d 1 47,915,5 47,915,9 6 5·50 FOXD2 Islan 14,064 Downst ↑ 53 52 E-03 d ream 3 195,489, 195,490, 8 7·46 MUC4 Islan 48,835 Intron ↓ 708 310 E-05 d 5 88,179,2 88,179,5 5 9·96 Islan ↑ MEF2C 20,535 Intron 35 40 E-03 d 6 114,181, 114,181, 3 3·59 MARC Islan 3,114 Exon ↓ 482 799 E-03 KS d 6 166,418, 166,419, 4 4·55 LINC00 N- 17,931 Downst ↑ 799 139 E-06 602 Shelf ream 7 27,183,1 27,184,8 47 3·05 HOXA5 Islan -706 Intron ↓ 33 54 E-14 d 7 76,828,8 76,829,1 2 0·031 CCDC1 Open 77,094 Intron ↓ 85 69 46 sea 7 130,131, 130,132, 18 1·34 MEST Open -808 Upstrea ↓ 480 162 E-03 sea m 10 135,202, 135,203, 7 6·65 PAOX Open 10,121 Intron ↑ 522 201 E-09 sea 11 843,897 844,285 6 0·016 TSPAN S- 1,268 Intron ↑ 4 Shor e 12 120,763, 120,763, 5 1·23 PLA2G Islan 1,914 Exon ↑ 487 870 E-03 1B d 15 64,995,1 64,995,5 5 0·025 OAZ2 Islan 145 5'UTR ↑ 33 02 d 16 22,018,7 22,019,3 4 1·42 C16orf Islan -423 Upstrea ↑ 27 08 E-04 52 d m 16 88,803,8 88,804,0 4 4·36 PIEZO Islan 47,445 Intron ↓ 03 52 E-03 1 d 17 9,550,13 9,550,54 5 0·015 USP43 N- 1,488 Upstrea ↑ 7 6 Shor m

e 17 59,940,7 59,941,1 8 2·09 BRIP1 Islan -1 Upstrea ↑ 09 33 E-03 d m 19 1,063,62 1,064,21 3 3·83 ABCA7 Islan 23,820 Intron ↓ 4 9 E-05 d

FEV1/ 1 1,564,42 1,564,92 4 8·51 MIB2 Islan 13,877 Exon ↓ FVC 2 1 E-05 d 1 86,968,0 86,968,5 4 3·59 CLCA1 Open 33,790 Downst ↓ 87 44 E-06 sea ream 2 121,223, 121,223, 6 1·28 LOC84 Open 176 3’UTR ↑ 534 965 E-04 931 sea 5 102,898, 102,898, 6 6·95 NUDT1 Open 12 5’UTR ↑ 223 734 E-05 2 sea 6 32,305,0 32,305,1 3 2·21 C6orf1 Open 34,549 Intron ↓ 68 46 E-03 0 sea 6 168,533, 168,533, 4 0·017 FRMD1 S- -53,693 Upstrea ↑ 375 690 Shelf m 10 135,051, 135,051, 11 4·28 VENTX Islan -42 Upstrea ↑ 149 582 E-05 d m 11 64,064,9 64,065,3 3 7·71 KCNK4 N- 6,367 Intron ↑ 47 72 E-03 Shor e 11 67,417,9 67,418,4 13 9·21 ACY3 Open -52 Upstrea ↓ 58 06 E-03 sea m 13 20,805,3 20,805,8 9 1·22 GJB6 N- 896 Intron ↑ 80 96 E-04 Shor e 14 96,180,4 96,181,0 10 1·49 TCL1A Islan -192 Upstrea ↑ 06 45 E-03 d m 16 89,023,3 89,023,6 3 1·45 CBFA2 Open 19,993 Intron ↓ 89 34 E-03 T3 sea 17 19,314,2 19,314,6 6 3·39 RNF11 Open -31 Upstrea ↑ 99 19 E-04 2 sea m 17 79,485,5 79,485,7 2 0·029 ACTG1 Islan -5,727 Upstrea ↑ 29 10 d / N- m Shor e 21 40,759,5 40,759,6 5 1·66 WRB N- 7,402 Intron ↑ 34 95 E-04 Shor e FEF75 1 1,957,07 1,957,71 5 7·53 GABR Islan 6,625 Intron ↓ 3 2 E-03 D d 1 2,383,43 2,383,68 4 0·013 PLCH2 N- -24,190 Upstrea ↑ 8 8 Shelf m 1 17,634,5 17,634,7 4 0·016 PADI4 Open -59 Upstrea ↑ 43 17 sea m 1 86,968,0 86,968,2 3 0·015 CLCA1 Open 33,646 Downst ↓ 87 56 sea ream 2 14,774,7 14,774,9 3 0·013 FAM84 Islan 2,035 Exon ↑ 86 03 A d 2 54,086,8 54,087,5 14 4·08 GPR75 Islan -33 Upstrea ↓ 54 53 E-03 d m 3 62,860,1 62,860,2 2 0·013 CADPS Islan 900 Intron ↑ 03 25 d 5 125,931, 125,931, 7 7·83 ALDH7 S- -100 Upstrea ↑ 001 363 E-03 A1 Shor m e

5 135,416, 135,416, 11 1·34 VTRNA Islan -35 Upstrea ↑ 029 614 E-03 2-1 d m 5 138,725, 138,725, 5 6·06 MZB1 N- -10 Upstrea ↑ 400 831 E-04 Shor m e 6 31,650,7 31,651,1 16 3·45 LY6G5 Islan -2,797 Upstrea ↑ 35 59 E-03 C d m 6 31,690,9 31,691,5 10 0·020 C6orf2 Islan 149 Intron ↑ 98 40 5 d 6 132,271, 132,271, 3 5·89 CTGF Islan 1,043 Exon ↑ 361 589 E-04 d 7 158,045, 158,046, 6 1·14 PTPRN Open 334,313 Intron ↑ 980 359 E-06 2 sea 8 142,377, 142,377, 5 4·31 GPR20 Open -31 Upstrea ↑ 303 490 E-03 sea m 11 2,721,20 2,721,63 14 0·029 KCNQ1 Islan -192 Upstrea ↓ 7 3 OT1 d m 11 67,417,9 67,418,4 13 7·07 ACY3 Open -52 Upstrea ↓ 58 06 E-03 sea m 12 114,843, 114,844, 3 0·025 TBX5 N- 2,155 Intron ↑ 919 266 Shor e 14 96,180,4 96,181,0 10 2·20 TCL1A Islan -192 Upstrea ↑ 06 45 E-06 d m 16 89,023,3 89,023,6 3 1·55 CBFA2 Open 19,993 Intron ↓ 89 34 E-03 T3 sea 17 44,897,4 44,897,5 2 3·95 WNT3 S- -1,346 Upstrea ↑ 31 13 E-04 Shor m e 21 40,759,5 40,759,6 5 0·024 WRB N- 7,402 Intron ↑ 34 95 Shor e Results present identified differentially methylated regions (DMRs) from association-analyses of DNA- methylation at birth with Forced Expiratory Volume in 1 second (FEV1), FEV1/ Forced Vital Capacity

(FVC) and Forced Expiratory Flow at 75% of FVC (FEF75) observed in the discovery meta-analyses and shown in numeric order. Start: Genetic location of the start of the DMR. End: Genetic location of the end of the DMR. No. of probes: total number of CpGs located in the DMR. P-value: Šidák- corrected p-values. Nearest gene: gene located nearest to the DMR. Location: location of the DMR in the epigenome. N-shelf: North shelf. N-Shore: North shore. S-Shore: South shore. Direction of association: mean direction of beta-coefficient of associations of identified DMRs with lung function, marked ↓ if a higher mean methylation of the DMRs was associated with a lower z-score for lung function and ↑ if a higher mean methylation of the DMRs was associated with a higher z-score of lung function.

Supplementary Table 4a. Associations of CpGs located in Differentially Methylated Regions with

Childhood FEV1.

Chro mo- som P- ProbeI Effe Std P.val Direc HetI HetPV e Start End value D ct Err ue tion Sq al - 1,957,8 cg0484 0·87 0·60 1 1,957,385 06 0·016 7273* 5 5 0·148 +--?- 56·7 0·07 cg0565 2·34 0·54 +++? 4059* 2 9 0·020 - 0 0·57 - cg1083 1·46 0·78 7110* 0 4 0·063 ---?- 6·4 0·36 - cg2410 1·71 0·76 5782 1 7 0·026 ---+- 31·7 0·21 - 7,887,5 7·27E- cg0472 0·81 0·37 1 7,887,199 61 05 5166* 8 2 0·028 -+-+- 30·2 0·22 - cg0892 0·54 0·22 6642* 8 8 0·016 -+--+ 41·2 0·14 - cg0916 0·76 0·22 8·37 8692* 1 8 E-04 ---+- 0 0·66 - cg1732 0·38 0·15 8665 7 5 0·013 -+--+ 32·1 0·20 - cg1772 0·85 0·27 1·57 4687* 2 0 E-03 -+--+ 55·8 0·05 17,222,40 17,222, cg1107 6·49 2·02 1·36 ++++ 1 5 716 0·019 9989* 6 9 E-03 + 1·6 0·39 - cg2582 31·6 9·79 1·22 2552* 85 4 E-03 -??-- 50·1 0·13 - 38,461,54 38,461, cg0467 1·20 0·54 1 0 897 0·029 3462 6 7 0·028 ----- 0 0·70 - cg0984 0·94 0·32 3·15 7153 6 0 E-03 ---?- 0 0·83 - cg1707 0·65 0·29 7180 6 3 0·025 ---+- 0 0·88 - cg1845 0·36 0·17 1016 2 0 0·033 ---+- 16·4 0·31 45,452,16 45,452, 6·90E- cg0258 7·64 1·92 6·87 +++? 1 6 606 04 6249* 8 1 E-03 + 0 0·86 - cg0322 12·1 5·12 9887 82 0 0·017 --+-- 66·3 0·01 cg0565 0·57 0·98 ++- 4404* 8 2 0·556 ++ 2·4 0·39 cg1204 2·50 1·55 0·108 +++? 14·2 0·32

4615* 1 6 + - cg1395 13·6 6·61 0210 63 7 0·039 ---+- 0 0·88 cg1461 1·37 0·59 ++++ 1683* 1 6 0·021 + 4·1 0·38 cg1660 1·53 0·50 2·26 - 4218 6 3 E-03 ++++ 55·2 0·06 47,915,55 47,915, 5·50E- cg0025 3·61 1·65 ++++ 1 3 952 03 6155* 6 4 0·029 - 0 0·70 cg0311 2·26 0·69 1·20 +++? 9043 3 8 E-03 + 0 0·90 cg0490 3·18 2·32 8380* 9 9 0·171 +-+-- 0 0·74 cg0787 2·82 1·06 7·83 ++++ 0914 9 4 E-03 + 0 0·55 cg1801 2·22 0·66 8·74 ++++ 7482 0 7 E-04 + 18 0·30 cg2260 1·60 2·22 6303 8 4 0·470 -++-- 0 0·69 - 195,489,7 195,49 7·46E- cg0131 0·24 0·13 3 08 0,310 05 0397* 0 7 0·081 ---?- 0 0·44 - cg0734 0·41 0·16 1007 7 4 0·011 --+-- 0 0·78 - cg1375 0·21 0·10 2114 2 4 0·042 ----- 0 0·99 - cg1603 0·35 0·16 4541* 9 9 0·034 ----- 0 0·75 - cg1635 0·48 0·22 8155* 7 0 0·027 --++- 0 0·82 - cg1871 0·23 0·11 3687 7 1 0·032 --+-- 0 0·86 - cg1891 0·31 0·11 6·79 8831 3 6 E-03 ----- 0 0·85 - cg2317 0·50 0·20 0091 0 0 0·012 --+?- 0 0·75 88,179,23 88,179, 9·96E - cg0276 3·04 1·17 9·46 ++++ 5 5 540 03 1345 5 3 E-03 - 26·6 0·24 cg0774 3·32 1·57 2134 1 5 0·035 -+++- 0 0·95 cg0822 2·98 1·03 4·02 3748 3 7 E-03 -++-- 47·4 0·10 cg1519 1·78 0·89 +++- 0401 6 9 0·047 + 0 0·81 cg1849 0·85 0·58 +++- 8987* 4 4 0·144 + 0 0·96 cg2242 5·29 2·52 6944* 4 0 0·036 +++-- 0 0·98 6 114,181,4 114,18 3·60E- cg0200 - 0·40 5·78 ---++ 19·6 0·28

82 1,799 03 4337* 1·10 1 E-03 8 - cg1047 0·32 0·12 8·54 4881 8 5 E-03 ---+- 33 0·20 - cg1920 0·67 0·20 7·24 3457* 9 1 E-04 ---++ 0 0·56 166,418,7 166,41 4·55E- cg0879 2·22 0·64 5·97 +++- 6 99 9,139 06 5949* 2 7 E-04 + 0 0·52 cg1925 0·75 0·27 4·97 ++++ 1564 8 0 E-03 + 69·9 0·00 cg2076 2·22 0·59 1·79 ++++ 9926 0 2 E-04 + 9·2 0·35 cg2174 0·59 0·20 4·24 ++++ 9424* 5 8 E-03 + 43·2 0·13 - 27,183,13 27,184, 3·05E- cg0096 0·44 0·24 7 3 854 14 9405 7 7 0·071 ---+- 48·2 0·10 - cg0132 0·44 0·18 3381 3 3 0·015 ---+- 25·5 0·25 - cg0137 0·70 0·34 0449 2 1 0·040 ---+- 0 0·53 - cg0174 0·86 0·45 8892 4 4 0·057 ---+- 0 0·66 - cg0200 0·77 0·30 5600 0 1 0·010 --++- 36·1 0·18 - cg0210 1·56 0·78 6682 0 7 0·047 ---+- 0 0·81 - cg0224 0·52 0·21 8486 0 8 0·017 --++- 3·1 0·38 - cg0264 1·07 0·40 6423 9 4 0·008 +--+- 52·4 0·07 - cg0291 0·93 0·39 6332 5 3 0·017 ---+- 5·7 0·37 - cg0320 1·21 0·51 7666 1 8 0·019 ---+- 0 0·68 - cg0336 0·77 0·35 8099 2 0 0·028 ---+- 30·1 0·22 - cg0374 1·49 0·78 4763 8 4 0·056 ---+- 0 0·48 - cg0486 0·30 0·14 3892 0 7 0·041 --++- 14·6 0·32 - cg0557 0·72 0·29 9037 7 6 0·014 ---++ 46·5 0·11 cg0577 - 0·22 0·360 ---+- 22·4 0·27

4699 0·20 8 9 - cg0583 0·36 0·16 5726 9 2 0·022 --++- 53·4 0·07 - cg0704 0·30 0·47 9592 7 3 0·516 +-++- 43·2 0·13 - cg0807 1·35 0·39 5·13 0327* 5 0 E-04 ---+- 53·7 0·07 - cg0954 0·55 0·31 9073 7 4 0·076 +--+- 23 0·26 - cg0988 1·10 0·50 0291 8 7 0·029 --++- 72 0·00 - cg1201 0·35 0·51 5737 7 0 0·483 --+++ 62·1 0·03 - cg1212 0·58 0·24 8839 0 9 0·020 +--+- 19·9 0·28 - cg1351 0·83 0·28 3·42 2268 2 4 E-03 ---+- 72·8 0·00 - cg1369 0·60 0·40 4927 1 2 0·135 --+-- 13·5 0·32 - cg1401 0·59 0·43 3695* 9 2 0·167 ---+- 0 0·48 - cg1401 0·57 0·30 4955 4 7 0·061 --++- 58·7 0·04 - cg1405 1·21 0·54 8329* 8 7 0·026 --++- 47·8 0·10 - cg1465 0·39 0·16 8493* 2 9 0·021 --++- 58·4 0·04 - cg1488 0·85 0·39 2265 4 7 0·031 ---+- 0 0·45 - cg1699 0·25 0·21 7642 8 1 0·220 ---++ 41·3 0·14 - cg1743 0·70 0·37 2857 1 4 0·061 ---+- 0 0·48 - cg1756 0·98 0·33 3·33 9124 4 5 E-03 ---+- 0 0·44 - cg1919 0·46 0·51 6335 6 2 0·362 --++- 46·9 0·11 - cg1964 0·17 0·19 3053* 6 9 0·375 ---+- 42·5 0·13 cg1975 - 0·24 8·15 ---+- 0 0·57

9481 0·65 7 E-03 3 - cg2051 0·94 0·36 7050 0 6 0·010 ---+- 0 0·54 - cg2081 0·22 0·18 7131* 8 3 0·215 ---+- 62·2 0·03 - cg2320 0·37 0·19 4968* 5 1 0·051 ---+- 40·6 0·15 - cg2345 0·08 0·17 4797 7 0 0·610 +--+- 50·7 0·08 - cg2393 0·61 0·25 6031* 0 8 0·018 --++- 40·1 0·15 - cg2438 0·83 0·52 9585 6 5 0·111 ----- 22·7 0·27 - cg2530 0·53 0·21 7665* 6 5 0·013 --++- 54·7 0·06 - cg2539 0·39 0·19 0165 2 6 0·046 ---+- 25·2 0·25 - cg2550 0·05 0·19 6432 1 5 0·796 ---+- 0 0·99 - cg2586 0·30 0·19 6143 2 5 0·122 ---+- 25·5 0·25 - cg2602 11·1 0·50 3912* 9 2 0·026 ---+- 14 0·32 - cg2715 13·9 0·63 1303 4 5 0·028 ---+- 0 0·45 - 76,828,88 76,829, cg0131 5·72 2·23 7 5 169 0·031 0473 1 9 0·011 ----- 0 0·95 cg1475 6·64 1·77 1·81 ++++ 2838* 6 5 E-04 + 0 0·99 - 130,131,4 130,13 1·34E- cg0028 3·16 1·10 3·98 7 80 2,162 03 6878 8 0 E-04 +--+- 23·6 0·26 - cg0434 3·16 1·16 6·73 4875 3 7 E-03 +--+- 32·7 0·20 - cg0478 1·46 0·54 7·36 6207 4 6 E-03 ----- 0 0·47 - cg0555 0·27 0·64 6276* 3 1 0·670 +--+- 17·2 0·30 - cg0621 0·88 0·70 2135 4 2 0·208 +--+- 50·7 0·08 cg0731 - 0·37 5·22 5018* 1·03 0 E-03 ---?- 31·6 0·22

4 - cg0908 0·49 0·39 0913 3 8 0·215 ---+- 0 0·52 - cg1024 0·30 0·33 9538 8 5 0·358 ---+- 10·6 0·34 - cg1234 1·11 0·49 7392 5 2 0·024 ----- 48·8 0·09 - cg1310 0·44 0·38 4298 3 4 0·248 ---+- 11·5 0·34 - cg1682 0·78 0·37 3958 4 2 0·035 ---+- 65·1 0·02 - cg1707 2·01 1·33 9325 1 8 0·133 ---+- 0 0·84 - cg1938 0·43 0·30 6484* 1 6 0·160 +--+- 61·3 0·03 - cg2005 1·30 1·07 0761 3 4 0·225 -?+-- 0 0·93 - cg2162 1·03 0·45 9528* 3 3 0·023 -+-?+ 0 0·60 - cg2270 0·39 0·68 5386 5 3 0·563 ++-+- 53·7 0·07 - cg2670 3·24 1·17 5·52 8559 8 0 E-03 ----- 0 0·94 - cg2733 0·52 0·42 8480 0 5 0·221 ---+- 11·8 0·33 135,202,5 135,20 6·65E- cg0331 2·20 0·66 9·45 +++- 10 22 3,201 09 9315 1 6 E-04 + 0 0·87 cg0608 0·51 0·21 +++? 0948* 7 9 0·018 + 0 0·58 cg1090 1·67 0·46 3·55 +++- 2549 0 8 E-04 + 15·2 0·31 cg1714 1·19 0·57 ++++ 3376* 8 4 0·037 + 0 0·64 cg1856 1·37 0·43 1·38 +++- 3886 5 0 E-03 + 6 0·37 cg2464 0·81 0·28 4·08 +++- 4436* 0 2 E-03 + 0 0·68 cg2707 1·58 0·53 2·87 +++- 2025 0 0 E-03 + 0 0·75 844,28 cg0617 0·65 0·24 7·49 +++- 11 843,897 5 0·016 9011* 4 5 E-03 + 29·2 0·22 cg0726 1·14 0·48 +++- 9682 0 6 0·019 + 42 0·14 cg1310 0·69 0·38 4938 2 4 0·071 +++-- 43·8 0·12

cg1930 1·81 0·57 1·55 3748 2 2 E-03 ++--+ 51·6 0·08 cg1938 1·20 0·75 6379 5 5 0·110 +++-- 60·3 0·03 cg2607 0·65 0·51 1135 2 2 0·203 +++-- 0 0·48 120,763,4 120,76 1·23E- cg0728 1·69 0·74 ++++ 12 87 3,870 03 0387 1 9 0·024 - 0 0·88 cg1561 1·04 0·50 - 1176 1 9 0·041 ++++ 2·8 0·39 cg2031 3·15 0·88 3·61 +++- 3400 8 5 E-04 + 0 0·44 cg2233 2·59 1·42 ++++ 5246 3 0 0·068 + 0 0·73 cg2687 1·02 0·37 6·31 +- 2792 4 5 E-03 +++ 0 0·45 64,995,13 64,995, cg0133 2·21 1·72 ++++ 15 3 502 0·025 7439 5 9 0·200 - 0 0·84 - cg1448 3·67 1·44 8391 8 4 0·011 +---- 31·7 0·21 cg1490 9·83 4·43 ++++ 9603 4 5 0·027 - 43·5 0·13 cg1895 6·49 5·99 +++- 8966* 6 0 0·278 + 0 0·85 - cg1979 6·22 1·54 7659 6 9 0·059 ----- 0 0·59 22,018,72 22,019, 1·40E- cg0041 12·9 3·41 1·46 ++++ 16 7 338 04 9692 72 5 E-04 - 27·6 0·23 cg0541 1·56 1·12 8150* 0 7 0·166 -+-?- 0 0·44 - cg1005 3·10 0·93 8·96 6854 3 4 E-04 ----- 0 0·83 cg2724 4·10 1·39 3·33 +++? 7832* 1 7 E-03 - 0 0·47 - 88,803,80 88,804, 4·36E- cg0097 3·47 2·06 16 3 052 03 3732* 4 5 0·092 ----- 0 0·60 - cg0306 0·70 0·20 6·92 2760* 5 8 E-04 ---?+ 37·6 0·18 - cg0698 0·92 0·38 8897 1 6 0·017 ----+ 4·9 0·37 - cg2674 0·60 0·19 1·92 8794* 8 6 E-03 ----+ 0 0·60 9,550,5 cg0236 0·85 0·34 17 9,550,137 46 0·015 2978* 8 4 0·013 ++--+ 0 0·42 cg1213 2·24 0·62 3·48 ++++ 0768* 4 7 E-04 + 0 0·72 cg1528 0·69 0·56 3852 6 5 0·218 ++--+ 0 0·95 cg2269 0·32 0·30 7684 2 1 0·285 ++--- 0 0·62

cg2337 1·46 0·47 2·13 +++- 8165 5 7 E-03 + 34·8 0·18 59,940,70 59,941, 2·09E- cg0051 2·64 3·29 17 9 133 03 5161 7 7 0·422 +-++- 0 0·45 cg0086 7·0· 3·28 ++++ 9632 17 1 0·032 - 0 0·97 cg0537 9·11 3·18 4·19 7417 1 2 E-03 +++-- 36·2 0·18 cg0598 3·49 1·52 6149 1 3 0·021 +-++- 0 0·65 cg0625 3·42 1·41 7227 4 2 0·015 -+++- 0 0·64 - cg1121 2·17 1·73 2038 4 8 0·211 ---?+ 10·6 0·34 cg1152 3·43 1·08 1·59 9614 5 7 E-03 +-++- 0 0·57 cg1243 1·99 1·04 5611 8 7 0·056 +-++- 34 0·19 - 1,064,2 3·83E- cg0537 2·01 0·54 2·22 19 1,063,624 19 05 2495* 8 7 E-04 ---+- 0 0·81 - cg1208 0·83 0·26 1·50 2025* 5 3 E-03 ---+- 0 0·62 - cg2199 1·89 0·61 2·01 5147* 5 3 E-03 ---+- 35·6 0·18 All CpGs located in differentially methylated regions (DMRs) associated with Forced Expiratory

Volume in 1 second (FEV1) observed in the discovery meta-analyses are shown, ordered by significance of the association. Chr: chromosome. Start: Genetic location of the start of the DMR. End:

Genetic location of the end of the DMR. P-value: Šidák-corrected p-values. Effect: beta of the association between methylation of the specified CpG and FEV1. StdErr: Standard Error of the beta of the association between methylation of the specified CpG and FEV1. P.value: original p-value of the association between methylation of the specified CpG and FEV1. Direction: direction of the effect of the association between methylation of the specified CpG and FEV1 for ALSPAC, Generation R,

INMA, CHS and Project Viva, respectively. +: positive effect estimate in the respective cohort, -: negative effect estimate in the respective cohort, ?: CpG not available for the respective cohort.

HetIsq: I2-statistic for heterogeneity between cohorts for the association between methylation of the specified CpG and FEV1. HetPVal: p-value for the heterogeneity between cohorts for the association between methylation of the specified CpG and FEV1. * CpG in which array probes contain SNPs, insertions, deletions, repeats or bisulfite induced reduced genomic complexity.25

Supplementary Table 4b. Associations of CpGs located in Differentially Methylated Regions

Associated with Childhood FEV1/FVC.

Chro mo- Het som Pvalu Effe Std P.val Direc HetIS PVa e Start End e ProbeID ct Err ue tion q l - 1,564,9 8·51E- cg00078 1·22 0·59 1 1,564,422 21 05 456 7 2 0·038 ----+ 55·7 0·06 - cg05642 1·38 0·37 2·39 789 8 8 E-04 ----- 18·6 0·29 - cg17122 0·85 0·26 1·44 213 8 9 E-03 ----- 0 0·73 - cg18852 1·78 0·66 7·01 096 9 4 E-03 ----+ 34·2 0·19 - 86,968,08 86,968, 3·59E- cg04896 0·51 0·18 4·32 1 7 544 06 168 5 1 E-03 ---+- 18·8 0·29 - cg10760 0·65 0·21 1·84 651 8 1 E-03 -??-- 0 0·44 - cg19807 0·94 0·25 2·04 991* 6 5 E-04 -??-- 0 0·60 - cg26829 1·17 0·39 2·66 098* 4 1 E-03 -??+- 0 0·48 121,223,5 121,22 1·28E- cg07412 0·49 0·22 +++- 2 34 3,965 04 254 3 0 0·025 + 26·3 0·24 cg11455 0·44 0·20 ++++ 444 8 5 0·029 + 6·5 0·36 cg17204 1·30 0·65 +++- 557 2 9 0·048 + 0 0·43 cg21406 0·61 0·20 2·78 ++++ 402 5 5 E-03 + 0 0·54 cg23006 0·77 0·23 9·71 ++++ 519 8 6 E-04 + 0 0·54 cg23689 0·53 0·25 ++++ 428 9 1 0·032 + 1 0·40 102,898,2 102,89 6·95E- cg02976 1·40 0·44 1·44 ++++ 5 23 8,734 05 617 6 1 E-03 + 0 0·44 cg07655 0·86 0·31 5·65 ++++ 627 8 4 E-03 + 0 0·69 cg07666 1·93 1·00 - 882 2 5 0·054 ++++ 0 0·61 cg09166 1·41 0·43 1·17 ++++ 085 4 6 E-03 + 0 0·50 cg13665 1·20 0·38 1·74 ++++ 998 5 5 E-03 + 0 0·47 cg15206 0·40 0·45 834 3 2 0·373 ++-+- 0 0·86 6 32,305,06 32,305, 2·21E- cg14704 - 0·22 1·06 ----- 0 0·95

8 146 03 780* 0·73 3 E-03 0 - cg20636 0·49 0·17 6·36 526* 0 9 E-03 ----- 0 0·98 - cg24640 1·53 0·43 4·94 182* 1 9 E-04 ----- 0 0·99 168,533,3 168,53 cg05422 0·53 0·21 +++- 6 75 3,690 0·017 022 0 8 0·015 + 0 0·70 cg09214 1·05 0·31 8·82 ++++ 616* 1 6 E-04 + 0 0·55 cg17172 0·72 0·36 - 308* 0 0 0·045 ++++ 0 0·50 cg20992 0·63 0·31 +++- 785* 7 6 0·044 + 8·5 0·35 135,051,1 135,05 4·28E- cg02207 0·62 0·53 ++- 10 49 1,582 05 686* 8 6 0·241 ++ 0 0·69 cg02645 1·73 0·79 ++++ 368 4 7 0·030 + 0 0·88 cg04347 1·72 0·54 1·39 ++++ 264 9 1 E-03 + 12·1 0·33 cg04665 1·85 0·82 ++++ 423 3 2 0·024 + 0 0·59 cg09827 2·05 0·84 ++++ 249 2 0 0·015 + 0 0·81 cg12554 1·47 0·55 8·10 +?++ 483* 3 6 E-03 + 0 0·67 cg12666 1·56 0·69 +?++ 165* 9 5 0·024 + 8·6 0·35 cg14539 3·04 1·63 +++? 179* 2 7 0·063 + 0 0·68 cg20472 3·70 2·06 +??+ 189 3 0 0·072 + 63·1 0·06 cg22165 1·16 0·80 ++- 685 9 7 0·147 ++ 0 0·52 cg23845 1·18 0·63 ++++ 574 9 4 0·061 + 4 0·38 64,064,94 64,065, 7·71E- cg04939 3·45 1·62 11 7 372 03 630 4 4 0·034 +++-- 0 0·68 cg14437 3·87 1·28 2·59 ++++ 534 5 6 E-03 + 52·9 0·07 cg19846 2·97 0·93 1·38 ++++ 387* 9 1 E-03 + 0 0·76 67,417,95 67,418, 9·21E- cg00350 0·06 0·62 11 8 406 03 199* 7 3 0·914 +-+-- 26·2 0·24 - cg01240 0·47 0·41 599 2 2 0·252 ----- 0 0·95 - cg04565 0·62 0·53 008 5 6 0·244 --+-- 0 0·93 - cg04986 0·67 0·33 336 9 6 0·043 +---- 12·2 0·33

- cg06148 0·81 0·31 9·61 175 8 6 E-03 --+-- 0 0·58 - cg09296 0·42 0·21 957 9 3 0·044 --+?- 0 0·40 - cg11096 0·40 0·26 993* 5 6 0·128 --+-- 0 0·93 - cg12355 0·43 0·27 172* 8 1 0·106 --+?- 26·9 0·25 - cg12894 0·80 0·58 325 9 7 0·170 --+-- 0 0·77 - cg23130 0·89 0·39 0·024 075 9 9 03 ----- 0 0·71 - cg25835 0·42 0·22 0·052 179 6 0 55 --+-- 34·6 0·19 - cg26288 1·4· 0·44 1·48 806 07 3 E-03 ----- 0 0·63 - cg27022 1·08 0·55 933 4 0 0·049 --+-- 0 0·50 20,805,38 20,805, 1·22E- cg00012 2·77 1·25 +++- 13 0 896 04 692* 5 7 0·027 + 0 0·89 cg01446 1·86 0·56 1·05 ++++ 515 0 8 E-03 - 56·8 0·05 cg01700 0·94 0·40 ++++ 504* 7 4 0·019 + 0 0·83 cg03473 3·94 2·01 518 1 6 0·051 -++-+ 0 0·51 cg07610 0·72 0·42 ++++ 777 5 9 0·091 + 0 0·98 cg10395 3·90 1·55 448 8 1 0·012 -++-- 63·1 0·02 cg18363 0·61 0·43 ++++ 035 4 1 0·154 - 0 0·54 cg20972 0·93 0·45 ++++ 453* 7 2 0·038 + 0 0·94 cg22377 3·12 1·67 389 1 2 0·062 -++-+ 41·5 0·14 96,180,40 96,181, 1·49E- cg04313 1·33 0·52 1·00 ++++ 14 6 045 03 756* 8 0 E-04 + 0 0·64 cg07445 1·05 0·61 246* 0 4 0·087 -++-+ 0 0·48 cg08092 0·53 0·38 +++- 680 2 3 0·164 + 29·9 0·22 cg13282 1·19 0·65 +++- 837 2 5 0·069 + 0 0·49 cg16696 1·05 0·58 ++++ 317* 9 2 0·069 - 0 0·75 cg17717 1·28 0·71 ++++ 124* 3 8 0·074 + 0 0·90

cg19992 1·28 0·84 +++- 633 6 6 0·128 + 0 0·95 cg23114 2·36 0·87 7·02 ++++ 311 8 9 E-03 + 0 0·86 cg24996 2·22 1·04 +++- 565 1 1 0·033 + 0 0·93 cg27089 2·81 1·74 ++++ 768 3 1 0·106 + 0 0·55 - 89,023,38 89,023, 1·45E- cg02431 0·75 0·28 8·64 16 9 634 03 972 7 8 E-03 ----- 39·3 0·15 - cg05953 0·96 0·38 373 9 6 0·012 -+--- 52·2 0·07 - cg08732 1·59 0·39 950* 6 5 0·055 ----- 18·4 0·29 19,314,29 19,314, 3·39E- cg04279 1·02 0·43 ++++ 17 9 619 04 801 4 7 0·019 + 0 0·89 cg09482 2·11 0·75 5·34 ++++ 093* 4 9 E-03 + 0 0·74 cg13305 0·58 0·33 951 4 7 0·083 +++-- 0 0·47 cg16674 1·00 0·49 ++++ 433 3 1 0·041 + 0 0·96 cg21158 1·10 0·42 9·50 +++? 317 8 7 E03 - 0 0·76 cg26939 1·45 0·45 1·43 ++++ 946 6 6 E-03 + 0 0·85 79,485,52 79,485, cg14316 1·15 0·39 3·29 ++++ 17 9 710 0·029 944* 2 2 E-03 - 0 0·51 cg24718 2·24 0·64 4·52 ++++ 197* 6 0 E-04 + 0 0·52 40,759,53 40,759, 1·66E- cg15977 0·84 0·32 +++? 21 4 695 04 137* 4 8 0·010 + 0 0·96 cg19684 0·79 0·27 4·20 ++++ 207* 8 9 E-03 + 0 0·97 cg19761 1·16 0·40 4·15 ++++ 502 5 6 E-03 + 0 0·95 cg21736 1·91 0·75 ++++ 411* 1 5 0·011 + 0 0·75 cg27119 0·63 0·22 4·16 ++++ 318 3 1 E-03 + 0 0·93 All CpGs located in differentially methylated regions (DMRs) associated with Forced Expiratory

Volume in 1 second / Forced Vital Capacity (FEV1/FVC) observed in the discovery meta-analyses are shown, ordered by significance of the association. Chr: chromosome. Start: Genetic location of the start of the DMR. End: Genetic location of the end of the DMR. P-value: Šidák-corrected p-values.

Effect: beta of the association between methylation of the specified CpG and FEV1/FVC. StdErr:

Standard Error of the beta of the association between methylation of the specified CpG and

FEV1/FVC. P.value: original p-value of the association between methylation of the specified CpG and

FEV1/FVC. Direction: direction of the effects of the association between methylation of the specified

CpG and FEV1/FVC for ALSPAC, Generation R, INMA, CHS and Project Viva, respectively. +: positive effect estimate in the respective cohort, -: negative effect estimate in the respective cohort, ?:

CpG not available for the respective cohort. HetIsq: I2-statistic for heterogeneity between cohorts for the association between methylation of the specified CpG and FEV1/FVC. HetPVal: p-value for the heterogeneity between cohorts for the association between methylation of the specified CpG and

FEV1/FVC. * CpG in which array probes contain SNPs, insertions, deletions, repeats or bisulfite induced reduced genomic complexity.25

Supplementary Table 4c. Associations of CpGs located in Differentially Methylated Regions

Associated with Childhood FEF75.

H et Chro P mo- P- Effec Std P.val Direc HetIS Va some Start End value ProbeID t Err ue tion q l 1,957,07 1,957,7 7·53E- cg048472 - 0·6 ++- 0· 1 3 12 03 73* 0·572 05 0·345 ?+ 0 42 cg108371 - 0·7 0· 10* 1·757 80 0·024 +--?- 0 64 cg158251 - 0·8 0· 27* 1·506 09 0·063 ----- 0 97 cg232887 - 0·8 1·67 0· 55 3·246 62 E-04 ---+- 32·5 20 cg241057 - 0·7 0· 82 1·926 67 0·012 ----- 0 96 2,383,43 2,383,6 cg001571 0·8 0· 1 8 88 0·013 79* 1·062 58 0·216 +-+-+ 36·2 18 cg062154 0·4 5·10 ++++ 0· 16* 1·666 80 E-04 + 0 74 cg127280 0·7 ++++ 0· 61* 1·801 31 0·014 + 0 60 cg133849 0·8 3·18 ++++ 0· 49 2·492 45 E-03 + 0 87 17,634,5 17,634, cg160919 0·9 +- 0· 1 43 717 0·016 81 1·986 99 0·048 +++ 0 58 cg183336 0·9 7·78 ++++ 0· 90 2·571 66 E-03 + 60·3 03 cg212958 0·8 6·18 ++++ 0· 38 2·331 51 E-03 + 53·4 07 cg269187 1·0 6·76 ++++ 0· 54* 2·941 86 E-03 + 0 42 86,968,0 86,968, cg107606 - 0·2 8·16 0· 1 87 256 0·015 51 0·574 17 E-03 ?-?+- 52·7 12 cg198079 - 0·2 6·37 0· 91* 0·862 52 E-04 ?-?+- 27·9 24 cg268290 - 0·4 0· 98* 1·068 41 0·016 ?-?+- 46·5 15 14,774,7 14,774, cg110077 2·3 ++++ 0· 2 86 903 0·013 59 5·572 12 0·016 - 0 56 cg130218 1·1 3·40 ++++ 0· 41 4·202 72 E-04 + 17 30 cg257651 1·6 6·79 ++++ 0· 30 4·523 71 E-03 + 0 66 54,086,8 54,087, 4·08E- cg007019 - 0·4 1·72 0· 2 54 553 03 46 1·299 15 E-03 ----- 14·7 32 cg014004 - 0·9 0· 68* 1·105 55 0·247 ---?- 0 59 cg018763 - 0·1 0· 38 0·011 52 0·942 -+--- 79·2 00 cg054149 - 0·6 6·96 0· 08 1·649 11 E-03 ---+- 31·2 21 cg086118 - 0·5 0· 10 1·163 95 0·051 ---+- 16·9 30 cg101248 - 1·0 0· 12 1·222 42 0·241 ---+- 27·8 23 cg119398 - 0·8 0·738 -+--+ 0 0·

25 0·278 30 49 cg124515 - 0·4 0· 30 0·781 06 0·055 ---+- 46·6 11 cg133562 - 0·7 2·28 0· 53 2·276 46 E-03 ----- 26·6 24 cg148329 - 0·1 0· 04 0·194 50 0·195 ---+- 67·8 01 cg195922 - 1·3 0· 77 2·121 06 0·104 ----- 45·2 12 cg196649 - 0·2 0· 45 0·256 06 0·214 ----- 45·1 12 cg198786 0·6 7·10 0· 27 -1·68 24 E-03 ---+- 14·6 32 cg199615 - 0·3 0· 45 0·893 68 0·015 ----- 36·9 17 62,860,1 62,860, cg135142 2·9 1·21 ++?+ 0· 3 03 225 0·013 30 9·496 34 E-03 - 0 48 cg159144 1·3 3·51 ++++ 0· 63 4·758 31 E-04 + 48 10 125,931, 125,93 7·83E- cg042000 - 0·2 2·69 0· 5 001 1,363 03 10* 0·882 94 E-03 +--?- 0 50 cg087024 0·4 4·89 +++? 0· 13* 1·286 57 E-03 - 27·2 24 cg167389 1·7 ++++ 0· 71 3·179 02 0·062 - 0 88 cg176533 0·9 0· 68* 0·564 90 0·569 +-+?- 0 83 cg186703 1·2 +++? 0· 73* 2·723 15 0·025 - 0 40 cg195512 3·9 0· 32* 6·481 06 0·097 ++--- 13 33 cg263277 2·3 0· 32 5·999 50 0·011 +++-- 52 08 135,416, 135,41 1·34E- cg001249 0·2 3·50 ++++ 0· 5 029 6,614 03 93 0·586 01 E-03 + 51·7 08 cg044819 0·1 ++++ 0· 23 0·332 79 0·062 + 16·7 30 cg064788 0·3 ++- 0· 86 0·659 84 0·086 ++ 56·6 05 cg065366 0·3 ++++ 0· 14* 0·639 10 0·039 + 53·6 07 cg087459 0·2 - 0· 65* 0·425 03 0·036 ++++ 21·2 27 cg166153 0·1 - 0· 57 0·282 63 0·084 ++++ 21·1 28 cg186786 0·1 - 0· 45 0·380 99 0·056 ++++ 30·7 21 cg187976 0·2 ++- 0· 53 0·344 28 0·132 ++ 27·6 23 cg253406 0·3 ++- 0· 88 0·389 01 0·196 ++ 23·2 26 cg263286 0·2 0·092 ++- 0· 33 0·492 92 5 ++ 49·9 09 cg268969 0·2 ++++ 0· 46 0·526 91 0·071 + 0 48 138,725, 138,72 6·06E- cg087366 1·1 3·82 0· 5 400 5,831 04 80 3·213 10 E-03 +-+-- 44 12 cg116233 - 0·9 0· 39 0·930 39 0·322 +--+- 51·9 08 cg135008 - 0·3 0·012 +-+-- 0 0·

19 0·890 55 60 cg147109 1·0 0· 84 2·782 91 0·011 +-++- 0 53 cg241134 1·0 2·07 ++++ 0· 96 3·717 02 E-04 - 34·2 19 31,650,7 31,651, 3·45E- cg000229 0·1 ++++ 0· 6 35 159 03 97* 0·271 68 0·107 - 0 60 cg012976 0·4 ++++ 0· 70* 0·621 12 0·132 - 0 61 cg021697 0·3 ++++ 0· 13* 0·558 29 0·090 - 0 52 cg023045 0·2 0· 84* 0·405 03 0·046 -+++- 0 44 cg023890 0·1 ++++ 0· 40* 0·332 79 0·063 - 0 70 cg043864 0·1 ++++ 0· 00* 0·460 99 0·021 - 0 88 cg058579 0·1 ++++ 0· 99* 0·245 48 0·098 - 0 81 cg064605 0·2 ++++ 0· 87* 0·329 23 0·140 - 0 64 cg074557 0·1 ++++ 0· 90* 0·256 46 0·081 - 0 88 cg086246 0·1 0· 48* 0·181 55 0·243 -+++- 0 55 cg182644 0·1 ++++ 0· 86* 0·233 59 0·143 - 0 48 cg185769 0·1 0· 57* 0·273 59 0·085 -+++- 0 66 cg204355 0·2 ++++ 0· 35* 0·357 01 0·076 - 0 51 cg223185 0·2 0· 14* 0·097 02 0·632 -+++- 24·5 25 cg254176 0·2 ++++ 0· 75* 0·724 81 0·010 - 0 51 cg264507 0·2 0· 17* 0·385 34 0·099 -+++- 0 47 31,690,9 31,691, cg005780 0·6 ++++ 0· 6 98 540 0·020 39* 1·391 13 0·023 - 0 75 cg013396 1·0 1·22 +- 0· 48* 3·453 68 E-03 +++ 0 61 cg069287 0·5 1·79 +++- 0· 41* 1·712 48 E-03 + 42·6 13 cg144379 10· 0· 86* 1·250 387 0·229 +-++- 0 63 cg145229 0·4 0· 90* 0·984 87 0·043 -++-- 18·4 29 cg159730 0·8 8·50 ++++ 0· 98* 2·348 92 E-03 - 0 50 cg160635 1·3 0· 87* 1·481 59 0·276 ++-+- 0 50 cg187186 1·2 6·84 ++++ 0· 47* 3·425 66 E-03 - 0 72 cg201917 0·5 ++- 0· 40* 1·110 30 0·036 ++ 0 63 cg215065 0·4 +++- 0· 65* 0·836 31 0·053 + 0 49 132,271, 132,27 5·89E- cg146239 0·7 4·51 ++++ 0· 6 361 1,589 04 17 2·086 35 E-03 + 0 67 cg228436 2·077 0·6 2·54 ++++ 0 0·

13 88 E-03 + 83 cg246841 0·9 2·79 ++++ 0· 68 3·494 62 E-04 + 0 64 158,045, 158,04 1·14E- cg027700 0·1 ++++ 0· 7 980 6,359 06 61 0·242 42 0·088 + 18·6 29 cg064001 0·1 ++++ 0· 19* 0·432 93 0·025 + 0 42 cg067151 0·1 6·71 ++++ 0· 36* 0·468 73 E-03 + 37·2 17 cg104733 0·3 1·32 +++- 0· 11 1·282 36 E-04 + 6·6 36 cg165716 0·3 4·96 ++++ 0· 42* 0·911 24 E-03 + 6·9 36 cg272008 0·5 3·15 ++?+ 0· 69* 1·897 27 E-04 + 29·1 23 142,377, 142,37 4·31E- cg031448 1·1 2·11 ++++ 0· 8 303 7,490 03 48 4·239 44 E-04 + 0 42 cg035927 1·0 1·74 ++++ 0· 63* 3·319 60 E-03 - 53·5 07 cg041370 1·1 +++? 0· 03* 1·924 16 0·085 - 29·2 23 cg071902 1·4 2·98 0· 29 4·209 17 E-03 +-+-+ 0 77 cg131959 - 1·7 0· 54 1·522 93 0·396 -+--+ 0 59 2,721,20 2,721,6 cg018733 - 0·8 7·26 0· 11 7 33 0·029 34 2·952 73 E-04 ---+- 37·8 16 cg022193 - 0·3 0· 60* 0·266 71 0·474 ---++ 36 18 cg034017 - 1·0 0· 26 0·621 22 0·543 +--+- 0 40 cg075952 - 0·5 0· 03 1·361 79 0·019 ---+- 45·3 12 cg083591 - 0·8 0· 67* 1·082 85 0·222 ---+- 41·7 14 cg084462 - 0·3 0· 15* 0·456 90 0·243 ---+- 61·7 03 cg095187 - 0·5 0· 20* 0·386 36 0·472 --++- 0 89 cg143927 - 0·8 0· 46 1·444 00 0·071 ---+- 19·4 29 cg149584 - 1·0 0· 41 2·550 68 0·017 ---+- 36·7 17 cg167396 - 0·4 0· 86 0·544 05 0·179 ---+- 0 50 cg206997 - 0·4 9·42 0· 37* 1·185 57 E-03 ---+- 41·5 14 cg261047 - 0·4 0· 81 0·631 01 0·116 ---+- 66·6 01 cg265477 - 0·6 0· 19* 1·498 20 0·016 ---+- 48·3 10 cg273230 - 1·0 0· 91 1·685 32 0·103 ---+- 44 12 67,417,9 67,418, 7·07E- cg003501 - 0·6 0· 11 58 406 03 99* 0·369 17 0·550 -+--- 60·2 03 cg012405 - 0·4 0· 99 0·295 07 0·468 -+--- 26·8 24 cg045650 - 0·5 0· 08 0·782 36 0·144 ----- 14·7 32 cg049863 - 0·3 0·022 -+--- 55·3 0·

36 0·739 24 06 cg061481 - 0·3 0· 75 0·769 06 0·012 --+-- 24·7 25 cg092969 - 0·2 0· 57 0·299 02 0·141 ---?- 68·7 02 cg110969 - 0·2 0·198 0· 93* 0·325 53 3 --+-- 0 89 cg123551 - 0·2 0· 72* 0·328 58 0·204 -+-?- 67·6 02 cg128943 - 0·6 0· 25 1·338 11 0·029 ----- 0 93 cg231300 - 0·3 0· 75 0·753 84 0·050 ----- 46·3 11 cg258351 - 0·2 0· 79 0·201 10 0·337 -+--- 61·7 03 cg262888 - 0·4 2·98 0· 06 1·314 42 E-03 ----- 0 71 cg270229 - 0·5 2·98 0· 33 1·668 62 E-03 ----- 0 76 114,843, 114,84 cg088070 2·2 2·83 ++++ 0· 12 919 4,266 0·025 97 6·712 48 E-03 - 0 85 cg204265 1·4 0· 71 3·270 04 0·020 +++-- 0 53 cg233208 1·4 3·82 +++- 0· 62 4·216 57 E-03 + 0 76 96,180,4 96,181, 2·20E- cg043137 0·4 2·35 ++++ 0· 14 06 045 06 56* 1·516 98 E-03 + 0 50 cg074452 0·5 0· 46* 1·409 81 0·015 -++-+ 0 58 cg080926 0·3 +++- 0· 80 0·758 64 0·037 + 63·8 02 cg132828 0·6 +++- 0· 37 1·519 87 0·027 + 24·2 25 cg166963 0·5 0· 17* 0·916 71 0·109 -+++- 31·5 21 cg177171 0·7 - 0· 24* 1·487 25 0·040 ++++ 0 61 cg199926 0·7 0· 33 1·209 90 0·126 -++-+ 0 81 cg231143 0·8 3·62 +++- 0· 11 2·614 98 E-03 + 0 73 cg249965 1·0 1·66 +++- 0· 65 3·773 02 E-04 + 0 73 cg270897 1·6 ++++ 0· 68 2·152 70 0·197 + 1·2 39 89,023,3 89,023, 1·55E- cg024319 - 0·2 9·95 0· 16 89 634 03 72 0·709 75 E-03 --+-- 44·1 12 cg059533 - 0·3 3·83 0· 73 1·058 66 E-03 --++- 52·3 07 cg087329 - 0·3 2·74 0· 50* 1·376 78 E-04 ----- 3·6 38 44,897,4 44,897, 3·95E- cg008175 1·5 ++++ 0· 17 31 513 04 98* 6·423 23 0·025 - 0 74 cg241145 15·32 4·1 2·50 0· 56* 8 85 E-04 +++-- 32·4 20 40,759,5 40,759, cg159771 0·3 +++? 0· 21 34 695 0·024 37* 0·756 16 0·017 - 0 43 cg196842 0·2 0· 07* 0·601 70 0·026 +++-- 0 65 cg197615 0·860 0·3 0·027 +++- 0 0·

02 89 + 74 cg217364 0·7 ++++ 0· 11* 1·717 23 0·018 - 0 41 cg271193 0·2 ++++ 0· 18 0·500 16 0·020 - 0 52 All CpGs located in differentially methylated regions (DMRs) associated with Forced Expiratory Flow at 75% of Forced Vital Capacity (FEF75) observed in the discovery meta-analyses are shown, ordered by significance of the association. Chr: chromosome. Start: Genetic location of the start of the DMR.

End: Genetic location of the end of the DMR. P-value: Šidák-corrected p-values. Effect: beta of the association between methylation of the specified CpG and FEF75. StdErr: Standard Error of the beta of the association between methylation of the specified CpG and FEF75. P.value: original p-value of the association between methylation of the specified CpG and FEF75. Direction: direction of the effect of the association between methylation of the specified CpG and FEF75 for ALSPAC, Generation R,

INMA, CHS and Project Viva, respectively. +: positive effect estimate in the respective cohort, -: negative effect estimate in the respective cohort, ?: CpG not available for the respective cohort.

HetIsq: I2-statistic for heterogeneity between cohorts for the association between methylation of the specified CpG and FEF75. HetPVal: p-value for the heterogeneity between cohorts for the association between methylation of the specified CpG and FEF75. * CpG in which array probes contain SNPs, insertions, deletions, repeats or bisulfite induced reduced genomic complexity.25

Supplementary Table 5. Associations of Differentially Methylated Regions Associated with Childhood

Lung Function Outcomes in Quality Probes Only.

Chromo- Start End No. of P-value some probes FEV1 1 38,461,540 38,461,897 4 0·018 1 47,915,553 47,915,952 4 9·90E-03 3 195,489,708 195,490,095 5 2·44E-03 5 88,179,235 88,179,497 4 0·023 6 166,418,922 166,419,013 2 0·030 7 27,183,196 27,184,854 36 3·73E-11 7 130,131,826 130,131,932 8 0·014 10 135,202,522 135,203,201 4 5·30E-07 11 843,943 844,086 3 1·62E-03 12 120,763,487 120,763,870 5 7·72E-04 15 64,995,133 64,995,502 5 6·49E-03 16 22,019,138 22,019,338 2 1·67E-03 17 59,940,709 59,941,133 8 1·37E-03

FEV1/FVC 5 102,898,223 102,898,730 5 2·14E-06

FEF75 2 54,086,854 54,087,553 12 3·14E-03 3 62,860,103 62,860,225 2 7·71E-03 5 135,416,205 135,416,399 4 5·28E-03 5 138,725,400 138,725,831 5 3·83E-04 6 132,271,361 132,271,589 3 3·92E-04 11 2,721,480 2,721,867 7 7·56E-06 11 67,418,045 67,418,406 10 1·71E-03 14 96,505,869 96,505,875 2 3·32E-04 Results present differentially methylated regions (DMRs) at birth associated with childhood Forced

Expiratory Volume in 1 second (FEV1), FEV1/ Forced Vital Capacity (FVC) and Forced Expiratory

Flow at 75% of FVC (FEF75), excluding all probes potentially containing genomic variant. Start:

Genetic location of the start of the differentially methylated region (DMRs). End: Genetic location of the end of the DMR. No. of probes: total number of CpGs located in the DMR. P-value: Šidák- corrected p-values.

Supplementary Table 6. Associations of CpGs Located in Identified Differentially Methylated

Regions Related with Childhood Asthma, Adolescent and Adult Lung Function, and Adult COPD. This

table is provided as a separate Microsoft Excel file.

Generation R ALSPAC Rotterdam Study Rotterdam Study Lung Lung Asthma function function COPD Lung C P.v D Eff P.v Ef P.v Ef P.v Effe Std Std DM Std DM Std DM functi H alu M ec alu fe alu fe alu ct Err Err R Err R Err R on R Start End CpG e R t e ct e ct e 5, - 1,957,3 1,957,8 cg0484 1,93 4,27 0,65 57 1, 0, 1 85 06 7273 9 4 0 E- 0,7 1,32 0,55 0,05 64 0,70 0,02 0,06 44 2,15 0,83 N.R FEV1 03 84 0 3 2 6 7 0 0 0 3 8 . - cg0565 6,15 6,79 0,36 0, 0,

4059 0 5 5 2,7 0,85 0,00 38 1,82 0,83 59 5,96 0,92 44 9 1 1 8 5 0 3 1 - cg1083 9,67 8,43 0,25 - 2, 4,

7110 7 7 1 0,9 1,40 0,49 15 0,99 0,03 05 2,99 0,17 64 5 3 4 0 0 9 8 6 - 0, 0, cg2410 5,49 0,94 0,37 2,3 1,94 0,22 99 0,65 0,13 00 2,00 0,99 5782 6 6 4 47 9 9 8 9 0 8 6 7 - - 7,887,1 7,887,5 cg0472 2,74 0,32 N. - 1,64 4,91 0, 0, 1 2,71 99 61 5166 0 1 R. 3,3 0,87 E- E- 30 0,45 0,50 0,08 78 1,43 0,58 N.R 7 12 2 04 06 2 1 4 2 5 8 5 . - - - cg0892 1,76 0,10 - 0, 0, 2,83 6642 7 9 0,8 0,46 0,06 11 0,35 0,74 16 1,12 0,88 3 70 4 1 6 7 5 8 5 1 - - 0, 0, cg0916 3,27 0,28 3,48 1,0 0,36 0,00 05 0,51 0,90 09 1,61 0,95 8692 1 7 1 54 0 4 9 0 7 2 0 4 - - - cg1732 2,38 0,14 - 0, 0, 3,47 8665 9 6 0,4 0,23 0,04 21 0,37 0,56 11 1,12 0,91 2 81 4 0 6 3 2 4 7 9 - - cg1772 2,22 0,04 - 0, 0, 4,44 4687 0 5 1,2 0,49 0,01 15 0,45 0,73 04 1,39 0,97 3 42 0 2 1 2 8 2 9 6 - - 17,222, 17,222, cg1107 6,81 17,4 0,69 N. 13, 10,0 6, 5,63 7, 1 405 716 9989 7 00 5 R. 02 97 0,19 0,03 69 3,30 0,04 E- 20 9,91 0,46 N.R 4 8 7 9 4 3 03 5 0 7 . - - cg2582 40, 31 62 - - - 2552 56 20,2 0,04 ,2 13,9 0,02 ,6 47,5 0,18 0 81 6 31 29 5 04 18 8 - - 38,461, 38,461, cg0467 2,90 0,63 N. 0, 1, 1 1,38 540 897 3462 2 2 R. 0,4 1,67 0,78 N.R 52 0,56 0,35 0,23 31 1,76 0,45 N.R 9 56 6 6 . 4 6 5 0 4 6 7 . - - cg0984 1,59 0,42 0, 0, 1,26 7153 5 8 0,3 1,12 0,78 31 0,34 0,36 56 1,07 0,60 4 08 0 3 2 7 8 3 5 0 - - cg1707 1,75 0,49 - 0, 1, 1,19 7180 5 5 0,4 0,59 0,46 37 0,43 0,39 29 1,32 0,32 9 39 5 1 0 9 9 8 4 7 - - cg1845 1,09 0,78 0, 0, 0,29 1016 8 8 0,1 0,33 0,74 39 0,29 0,17 47 0,90 0,59 6 08 6 8 6 0 1 7 8 9 - - 45,452, 45,452, cg0258 15,7 0,00 N. 1,97 0, 5, 1 42,5 166 606 6249 53 7 R. 5,6 4,06 0,16 E- 19 1,30 0,87 0,79 30 3,91 0,17 N.R 85 48 3 5 05 8 3 9 0 2 4 6 . - - - cg0322 28,7 0,19 24, 0, 3, 37,0 9887 95 8 77 13,7 0,07 19 1,92 0,91 92 6,01 0,51 94 7 65 2 6 6 9 1 3 4 - - cg0565 6,79 0,71 3,68 2, 5, 2,49 4404 3 4 7,1 2,00 E- 43 2,59 0,34 46 8,29 0,51 1 93 6 04 7 8 8 7 9 0 - - cg1204 10,6 0,06 13, 0, 7, 19,5 4615 85 8 09 7,47 0,08 66 2,06 0,74 90 6,34 0,21 13 0 0 0 9 6 6 9 4 3 - cg1395 30,1 27,7 0,27 11, 1, 1,

0210 77 29 6 65 16,8 0,48 05 3,00 0,72 20 7,97 0,88 5 30 9 2 3 6 4 7 0

0, 0, cg1461 1,10 4,89 0,82 0,9 1,56 0,53 47 0,64 0,46 67 1,96 0,73 1683 4 8 2 64 5 8 7 7 1 2 8 3 - - 0, 0, cg1660 3,69 0,86 0,64 2,9 1,39 0,03 45 0,55 0,41 96 1,70 0,57 4218 6 2 1 52 9 5 1 4 6 7 2 0 - - 47,915, 47,915, cg0025 15,2 0,27 N. 1, 4, 1 16,5 553 952 6155 48 6 R. 7,2 4,32 0,09 0,05 60 0,95 0,09 0,04 94 2,81 0,07 N.R 98 59 8 4 8 7 9 4 0 4 4 9 . - - cg0311 1,79 4,70 0,70 0, 0,

9043 4 7 3 0,7 3,09 0,80 65 0,62 0,30 67 1,94 0,72 51 9 9 0 8 1 2 0 9 - - cg0490 14,3 0,40 - 2, 5, 11,8 8380 85 9 2,0 5,51 0,70 48 1,07 0,02 16 3,21 0,10 86 89 9 5 7 2 0 6 9 9 - cg0787 7,71 6,22 0,21 10, 1, 2,

0914 3 7 5 17 4,66 0,03 23 0,86 0,15 44 2,53 0,33 2 8 0 1 6 5 0 0 5 - - cg1801 5,29 0,92 1, 3, 0,50 7482 6 3 5,3 3,99 0,18 55 0,79 0,05 44 2,53 0,17 9 53 4 1 4 2 0 4 1 4 - - - cg2260 20,3 0,32 11, 1, 2, 19,9 6303 31 7 63 6,97 0,09 61 2,94 0,58 29 9,57 0,81 10 5 5 6 3 4 4 4 5 1 - 195,48 195,49 cg0131 1,35 1,47 0,36 N. 0, 0, 3 9,708 0,310 0397 0 9 1 R. 0,1 0,22 0,55 N.R 50 0,36 0,16 0,01 18 1,08 0,86 N.R 34 6 2 . 9 4 3 5 6 4 4 . - cg0734 1,07 1,35 0,42 - 0, 0,

1007 5 6 8 0,2 0,33 0,39 44 0,31 0,16 10 0,95 0,91 87 6 4 0 8 6 0 4 7 - cg1375 0,51 0,75 0,49 - 0, 0,

2114 3 2 5 0,0 0,21 0,92 36 0,22 0,10 24 0,68 0,72 20 3 4 9 4 0 3 0 1 - - cg1603 1,07 1,22 0,38 - 0, 0,

4541 3 2 0 0,4 0,42 0,30 02 0,22 0,92 18 0,67 0,78 40 6 2 2 6 4 3 8 7 - - cg1635 1,23 1,64 0,45 - 0, 0,

8155 4 3 3 0,0 0,44 0,86 42 0,40 0,29 18 1,21 0,88 76 9 6 6 9 8 0 0 2 - cg1871 0,86 1,23 0,48 - 0, 0,

3687 8 5 2 0,0 0,17 0,57 32 0,29 0,27 22 0,87 0,79 99 8 7 0 5 8 9 3 3 - cg1891 0,73 0,95 0,44 - 0, 0,

8831 6 9 3 0,1 0,22 0,49 27 0,20 0,17 19 0,59 0,73 52 0 2 3 1 4 9 8 9 - cg2317 0,75 2,44 0,75 0, 0,

0091 7 3 7 0,0 0,31 0,85 46 0,45 0,30 41 1,37 0,76 59 4 1 9 4 2 4 3 3 - 88,179, 88,179, cg0276 7,91 25,2 0,75 N. 2, 4, 5 235 540 1345 1 11 4 R. 5,6 18,5 0,76 N.R 96 3,27 0,36 0,01 24 10,6 0,69 N.R 02 72 3 . 8 8 5 7 3 24 0 . - - - cg0774 13,7 0,45 14, 7, 5, 10,2 2134 01 4 86 15,7 0,34 61 3,44 0,02 09 10,7 0,63 59 6 72 6 0 9 7 3 02 4 - - cg0822 16,4 0,08 7, 7, 27,9 3748 24 9 8,0 8,65 0,35 45 2,54 0,00 54 7,91 0,34 49 69 7 2 7 4 3 8 1 0 - - cg1519 17,7 0,33 - 4, 4, 17,2 0401 95 2 2,8 7,49 0,70 55 2,46 0,06 75 8,20 0,56 57 32 6 6 5 1 4 5 9 2 - 0, 1, cg1849 2,05 4,82 0,67 0,8 1,38 0,54 46 0,62 0,45 31 1,87 0,48 8987 2 3 1 38 9 6 5 1 3 3 1 3 - - cg2242 35,9 0,24 - 2, 7, 42,2 6944 39 0 1,1 11,1 0,91 40 1,69 0,15 58 5,09 0,13 56 41 93 9 4 2 5 8 9 7 - 114,18 114,18 cg0200 0,66 3,07 0,83 N. 0, 2, 1,79 6 1,482 1,799 4337 1 6 0 R. 0,9 0,88 0,27 N.R 95 0,70 0,17 0,02 38 2,17 0,27 E- 68 0 2 . 2 6 7 5 1 2 3 03 - - cg1047 1,46 0,68 - 0, 3, 0,60 4881 2 1 0,3 0,19 0,09 70 0,34 0,04 74 1,10 0,00 1 20 1 4 4 4 1 6 4 1 - - cg1920 1,83 0,36 - 0, 4, 1,67 3457 6 1 0,1 0,32 0,71 87 0,51 0,09 17 1,63 0,01 6 17 5 9 4 7 1 9 2 0 - 166,41 166,41 cg0879 2,47 4,68 0,59 N. 0, 2, 6 8,799 9,139 5949 2 7 8 R. 4,4 4,11 0,27 N.R 32 0,71 0,64 0,51 99 2,21 0,17 N.R 63 0 8 . 6 5 8 0 9 0 5 .

- - cg1925 3,01 0,89 - 0, 0, 0,40 1564 4 3 0,0 0,42 0,82 61 0,47 0,19 94 1,54 0,54 4 96 7 2 2 4 7 2 1 1 - cg2076 5,52 3,79 0,14 - 0, 1,

9926 5 7 6 0,6 1,71 0,69 11 0,65 0,85 93 2,00 0,33 74 8 5 8 8 7 6 9 5 - cg2174 5,06 2,05 0,01 - 0, 0,

9424 9 0 3 0,1 0,36 0,60 39 0,38 0,30 44 1,24 0,72 86 1 6 7 9 8 1 9 4 - - 27,183, 27,184, cg0096 0,27 2,19 0,89 N. 7,51 0, 1, 5,27 7 133 854 9405 9 4 9 R. 0,4 0,43 0,31 E- 08 0,43 0,84 N.R 57 1,31 0,23 E- 39 5 4 03 8 9 2 . 0 7 3 03 - - cg0132 2,54 2,80 0,36 - 0, 0,

3381 1 5 5 0,1 0,27 0,70 25 0,50 0,61 36 1,50 0,80 05 8 5 3 0 3 4 6 9 - - cg0137 1,05 2,14 0,62 0, 0,

0449 1 2 4 1,7 0,98 0,07 26 0,37 0,47 93 1,15 0,41 31 0 8 9 8 6 6 1 6 - cg0174 7,74 4,21 0,06 0, 5,

8892 1 1 6 1,4 0,78 0,05 39 0,85 0,64 52 2,60 0,03 94 4 7 4 4 5 1 6 4 - - cg0200 1,07 1,99 0,59 0, 1,

5600 3 8 1 0,8 0,80 0,29 12 0,37 0,73 09 1,14 0,33 49 6 2 7 0 2 9 1 5 - cg0210 2,51 5,37 0,63 0, 2,

6682 5 0 9 0,7 2,71 0,77 05 0,69 0,94 99 2,19 0,17 83 6 3 1 0 1 1 3 3 - - - cg0224 1,66 0,99 0, 0, 0,00 8486 8 9 0,2 0,39 0,50 26 0,30 0,39 73 0,96 0,44 3 65 7 5 2 7 3 7 0 3 - - cg0264 2,94 2,78 0,29 0, 0,

6423 3 6 1 2,2 1,50 0,14 06 0,44 0,89 60 1,36 0,65 08 6 3 1 1 0 9 5 6 - - cg0291 0,66 2,60 0,79 0, 1,

6332 9 3 7 1,6 1,19 0,17 19 0,41 0,64 67 1,32 0,20 44 7 0 1 9 9 9 9 6 - cg0320 8,83 7,56 0,24 - 0, 0,

7666 8 7 3 0,1 0,84 0,83 08 0,61 0,88 50 1,79 0,77 73 4 8 9 6 6 6 0 8 - - cg0336 2,94 0,89 0, 3, 0,37 8099 5 8 1,5 0,64 0,01 07 0,54 0,88 34 1,80 0,06 6 86 9 5 6 7 9 3 4 4 - cg0374 9,25 4,96 0,06 0, 7,

4763 0 0 2 2,4 2,71 0,37 19 0,77 0,80 65 2,44 0,00 16 3 4 6 5 0 3 3 2 - - cg0486 1,10 1,73 0,52 0, 0,

3892 8 9 4 0,2 0,22 0,28 04 0,27 0,86 72 0,84 0,39 44 8 5 6 3 5 9 9 1 - cg0557 1,08 2,88 0,70 - 0, 0,

9037 4 1 7 0,3 0,57 0,54 80 0,50 0,11 24 1,49 0,86 47 7 8 8 9 3 8 3 8 - cg0577 3,46 3,71 0,35 - 0, 3,

4699 5 2 0 0,3 0,34 0,31 16 0,94 0,86 13 2,90 0,28 47 5 5 5 6 1 2 2 0 cg0583 1,78 1,89 0,34 0,0 0,25 0,87 5726 7 6 6 42 6 0 ------cg0704 1,65 4,39 0,70 0, 2,

9592 4 1 6 0,4 0,85 0,62 42 0,88 0,62 39 2,72 0,37 18 6 5 8 1 7 4 3 9 - - cg0807 1,44 5,29 0,78 - 0, 0,

0327 3 3 5 0,4 0,61 0,45 69 0,49 0,15 31 1,50 0,83 64 4 0 1 0 9 2 9 6 - - cg0954 0,97 2,29 0,66 0, 1,

9073 8 0 9 1,1 0,81 0,16 03 0,37 0,93 52 1,21 0,20 47 4 0 3 7 0 9 2 7 - - cg0988 6,83 0,69 - 0, 1, 2,65 0291 8 8 0,9 0,77 0,23 84 0,58 0,14 12 1,76 0,52 6 28 2 0 7 7 9 8 8 4 - - cg1201 0,03 7,38 0,99 - 0, 8,

5737 5 2 6 0,2 0,83 0,72 34 1,10 0,75 73 3,32 0,00 94 6 5 9 6 2 2 2 9 - - cg1212 0,86 1,64 0,59 0, 1,

8839 2 1 9 2,8 1,02 0,00 05 0,27 0,84 29 0,88 0,14 44 0 5 4 3 2 5 1 1 cg1351 - 4,25 0,64 - 0,46 0,62 - 0,45 0,65 - 1,32 0,10 2268 1,98 8 1 0,2 8 7 0, 7 4 2, 0 3

4 28 20 15 4 0 - cg1369 1,12 5,08 0,82 0, 5,

4927 5 8 5 1,3 0,59 0,03 54 0,73 0,46 38 2,26 0,01 01 8 0 0 6 3 5 9 8 - - cg1401 3,64 0,98 0, 3, 0,05 3695 6 9 0,6 0,74 0,35 52 0,81 0,52 25 2,51 0,19 0 92 7 4 3 4 1 1 6 6 - - cg1401 1,50 2,52 0,55 0, 0,

4955 5 4 1 0,3 0,58 0,54 00 0,32 0,99 98 0,95 0,30 54 6 7 3 5 3 7 5 1 - cg1405 0,93 4,85 0,84 - 0, 2,

8329 7 7 7 0,7 1,07 0,50 09 0,80 0,90 97 2,48 0,23 21 8 4 7 6 4 5 8 2 - cg1465 0,60 3,09 0,84 0, 0,

8493 0 6 6 0,0 0,23 0,67 11 0,37 0,75 97 1,09 0,37 99 5 4 7 6 6 0 2 5 - - cg1488 0,60 2,84 0,83 0, 2,

2265 6 8 2 0,5 0,92 0,58 12 0,48 0,80 35 1,53 0,12 03 4 6 2 9 3 4 7 6 - - cg1699 6,72 0,71 - 0, 2, 2,48 7642 3 2 0,0 0,30 0,91 27 0,74 0,71 49 2,10 0,23 4 34 5 2 3 9 5 7 0 5 - - cg1743 2,10 2,34 0,37 - 0, 1,

2857 4 6 0 0,3 1,08 0,76 20 0,42 0,63 83 1,29 0,15 29 5 2 1 5 5 1 1 6 - - cg1756 1,70 2,24 0,44 0, 0,

9124 6 5 7 0,5 1,21 0,63 22 0,33 0,50 80 1,05 0,44 80 9 4 2 5 8 6 5 5 - cg1919 1,78 7,03 0,79 - 0, 2,

6335 9 3 9 0,3 0,77 0,66 55 0,83 0,50 47 2,37 0,29 31 2 8 8 9 6 1 4 8 - cg1964 1,48 6,27 0,81 0, 0,

3053 8 8 3 0,0 0,28 0,75 51 0,66 0,44 75 1,94 0,69 89 9 8 2 5 2 9 4 6 - - cg1975 0,92 1,55 0,55 0, 0,

9481 4 2 2 0,5 0,72 0,45 07 0,26 0,79 52 0,82 0,52 44 9 6 0 7 3 8 5 2 - cg2051 1,76 2,46 0,47 0, 1,

7050 9 3 2 0,2 1,08 0,82 18 0,33 0,57 20 1,03 0,24 36 7 9 5 2 7 2 6 6 - - - cg2081 2,56 0,83 - 0, 0, 0,53 7131 6 5 0,1 0,27 0,66 19 0,33 0,56 47 0,99 0,63 5 19 7 8 5 8 5 3 4 4 - - cg2320 1,56 3,10 0,61 0, 0,

4968 3 6 5 0,0 0,28 0,94 39 0,36 0,28 66 1,11 0,55 18 3 8 3 7 3 0 8 5 - - cg2345 0,99 3,09 0,74 0, 0,

4797 4 2 8 0,2 0,25 0,24 01 0,43 0,97 34 1,30 0,78 97 7 9 4 5 4 9 6 9 - - cg2393 0,39 2,04 0,84 0, 1,

6031 5 5 7 0,7 0,50 0,12 24 0,38 0,52 10 1,21 0,36 93 9 0 1 0 6 4 1 2 - cg2438 1,36 7,08 0,84 - 1, 1,

9585 8 5 7 0,3 0,78 0,65 22 0,88 0,16 62 2,44 0,50 48 2 7 7 9 7 0 8 8 - - cg2530 1,00 1,77 0,57 0, 1,

7665 9 4 0 0,5 0,43 0,22 09 0,33 0,78 05 1,06 0,32 29 3 3 1 7 7 0 0 2 - cg2539 1,20 3,23 0,71 0, 2,

0165 0 6 1 0,0 0,30 0,98 22 0,69 0,74 93 2,11 0,16 06 0 5 3 0 6 0 5 6 - - cg2550 0,43 2,64 0,87 0, 0,

6432 0 3 1 0,0 0,29 0,90 19 0,43 0,64 55 1,34 0,68 36 7 3 7 4 9 3 3 0 - - - cg2586 2,32 0,72 0, 1, 0,82 6143 2 2 0,3 0,30 0,29 34 0,42 0,41 61 1,33 0,22 5 20 4 4 7 4 3 5 0 5 - - cg2602 2,22 3,15 0,48 0, 1,

3912 1 7 2 1,4 1,52 0,33 33 0,52 0,52 82 1,66 0,27 63 8 9 6 4 1 6 2 2 - cg2715 3,56 4,01 0,37 0, 4,

1303 6 8 5 1,9 2,40 0,41 13 0,56 0,81 44 1,80 0,01 68 7 4 0 7 9 3 3 4 76,828, 76,829, cg0131 - 12,9 0,78 N. 7 - 12,2 0,73 N.R - 2,71 0,74 0,28 5, 8,84 0,52 N.R 885 169 0473 3,54 23 4 R. 4,0 28 8 . 0, 8 9 0 57 8 8 .

3 97 87 9 0 - - cg1475 13,7 0,91 1, 4, 1,42 2838 49 7 3,7 4,19 0,36 63 0,86 0,05 36 2,50 0,08 9 79 6 8 0 2 9 5 8 2 - 130,13 130,13 cg0028 13,2 8,25 0,10 N. 1, 4, 7 1,480 2,162 6878 40 7 9 R. 0,5 4,14 0,89 N.R 40 1,78 0,43 0,23 54 5,30 0,39 N.R 67 8 1 . 0 6 3 0 1 9 2 . - cg0434 10,0 9,78 0,30 - 1, 10

4875 52 1 4 0,6 3,25 0,84 31 2,30 0,56 ,2 7,29 0,16 34 9 6 5 8 9 15 0 1 - cg0478 3,79 3,18 0,23 1, 3,

6207 5 9 4 0,8 2,09 0,67 46 0,99 0,14 41 2,96 0,24 73 9 8 1 1 1 7 3 9 - cg0555 8,64 11,4 0,44 - 0, 2,

6276 2 26 9 0,1 0,93 0,89 45 1,81 0,80 57 5,56 0,64 20 8 9 2 4 3 1 0 4 - cg0621 12,8 5,55 0,02 0, 6,

2135 36 4 1 2,1 1,76 0,23 86 1,22 0,48 56 3,74 0,08 23 7 0 8 7 0 7 9 0 - - cg0731 12,2 8,77 0,16 0, 0,

5018 91 7 1 0,8 0,56 0,14 53 0,45 0,24 01 1,50 0,99 13 1 8 1 8 7 6 0 1 - cg0908 10,8 9,99 0,27 2, 6,

0913 39 7 8 0,3 0,58 0,50 19 1,76 0,21 59 5,40 0,22 86 1 7 2 1 3 0 0 2 - cg1024 6,66 4,93 0,17 1, 2,

9538 8 3 6 0,6 0,53 0,21 48 1,30 0,25 49 4,12 0,54 69 3 0 7 0 3 6 7 5 - - - cg1234 2,79 0,91 1, 1, 0,31 7392 8 0 2,5 2,40 0,28 01 0,80 0,20 08 2,66 0,68 7 63 7 8 6 3 6 5 8 4 - cg1310 10,4 7,70 0,17 1, 8,

4298 70 3 4 0,4 0,56 0,44 98 1,65 0,23 56 5,17 0,09 30 6 8 5 7 1 3 4 8 - cg1682 8,63 8,92 0,33 1, 7,

3958 9 9 3 0,0 0,54 0,94 70 1,79 0,34 43 5,50 0,17 35 6 9 2 0 2 3 5 7 - cg1707 7,29 10,9 0,50 - 2, 4,

9325 5 32 5 4,9 3,93 0,20 69 2,53 0,28 01 8,30 0,62 66 3 7 0 3 8 9 9 9 - - cg1938 2,22 0,63 2, 4, 1,05 6484 1 6 0,5 0,59 0,39 50 1,17 0,03 87 3,81 0,20 2 03 4 7 2 7 4 5 1 1 - cg2005 1, 17 - - - 0761 1,5 1,58 0,34 71 3,09 0,58 ,2 9,34 0,06 00 1 3 2 2 0 37 3 5 - - cg2162 13,0 9,64 0,17 0, 0,

9528 24 2 7 0,7 0,68 0,27 61 0,64 0,34 48 2,05 0,81 42 3 8 7 8 1 6 8 3 - cg2270 1,94 4,74 0,68 0, 7,

5386 3 9 2 2,5 1,89 0,17 51 1,19 0,66 04 3,67 0,05 51 5 9 8 7 5 4 6 5 - cg2670 13,6 10,0 0,17 1, 10

8559 30 45 5 8,5 5,42 0,11 68 1,91 0,38 ,1 5,93 0,08 90 9 4 2 7 0 09 6 9 - cg2733 14,9 9,81 0,12 2, 6,

8480 45 3 8 0,2 0,61 0,70 65 2,02 0,19 03 6,49 0,35 35 1 0 4 9 1 7 2 2 - 0, 5, 2,69 135,20 135,20 cg0331 3,96 0,06 N. 10 7,26 4,6 4,32 0,28 0,04 60 0,78 0,44 0,40 43 2,47 0,02 E- 2,522 3,201 9315 9 7 R. 2 41 1 3 9 3 8 4 0 6 3 8 03 - 0, 1, cg0608 1,37 0,17 1,88 0,5 0,53 0,27 20 0,34 0,55 91 1,06 0,07 0948 8 2 1 79 0 5 3 4 5 7 2 1 - 0, 2, cg1090 3,01 0,10 4,83 5,3 2,11 0,01 37 0,45 0,41 39 1,44 0,09 2549 1 8 8 26 6 2 1 9 8 0 2 8 - 0, 1, cg1714 3,67 0,35 3,40 0,6 1,59 0,67 58 0,48 0,22 66 1,47 0,25 3376 6 5 1 77 6 2 7 2 4 9 3 7 - 0, 4, cg1856 2,67 0,00 6,97 3,6 2,68 0,17 57 0,64 0,37 91 1,98 0,01 3886 2 9 9 49 3 4 2 4 4 8 8 3 - 0, 2, cg2464 2,13 0,10 3,43 0,7 0,64 0,22 36 0,44 0,41 04 1,34 0,12 4436 8 8 6 93 8 1 6 6 1 2 4 9 - 0, 2, cg2707 3,33 0,38 2,90 2,9 2,12 0,16 15 0,46 0,73 82 1,53 0,06 2025 6 3 9 77 8 2 4 0 7 1 2 6

- 1, 2, 843,89 844,28 cg0617 2,03 0,07 N. 11 3,61 1,1 0,56 0,04 0.01 04 0,68 0,12 0,35 03 2,19 0,35 N.R 7 5 9011 6 6 R. 7 69 7 0 0 2 2 7 0 1 4 5 . - - cg0726 3,60 0,10 0, 5, 5,83 9682 3 6 2,9 1,89 0,12 87 1,77 0,62 40 5,12 0,29 0 41 9 2 4 2 2 5 5 2 - - cg1310 3,36 0,18 0, 2, 4,40 4938 6 7 0,9 0,81 0,26 12 0,98 0,89 89 2,94 0,32 5 05 6 8 6 4 8 8 1 4 - - cg1930 4,93 0,01 1, 0, 11,6 3748 4 8 3,4 1,18 0,00 34 1,34 0,31 52 4,27 0,90 64 17 9 4 5 6 8 6 7 2 - - - cg1938 5,88 0,05 2, 16 3,03 11,3 6379 2 5 4,4 3,23 0,16 05 1,36 0,13 ,9 4,69 E- 03 74 6 7 2 9 4 59 4 04 - - - cg2607 4,02 0,05 - 0, 6, 7,78 1135 3 3 0,2 2,05 0,88 84 1,01 0,40 17 3,18 0,05 9 99 5 4 0 8 9 2 8 3 - 120,76 120,76 cg0728 34,9 17,1 0,04 N. 10, 1, 0, 12 3,487 3,870 0387 16 12 1 R. 70 13,8 0,44 N.R 21 2,81 0,66 0,61 68 8,97 0,93 N.R 8 93 1 . 2 9 7 0 9 0 9 . - cg1561 0,66 3,49 0,84 0, 2,

1176 5 2 9 1,8 5,93 0,75 54 1,18 0,64 38 3,45 0,49 20 1 9 2 2 6 7 5 0 - - cg2031 9,39 0,69 2, 0, 3,73 3400 4 1 1,3 9,96 0,89 06 2,23 0,35 75 6,52 0,90 1 29 4 4 5 7 6 2 2 8 - cg2233 5,47 12,3 0,65 - 1, 11

5246 3 59 8 5,9 9,28 0,51 04 3,00 0,72 ,1 9,05 0,22 97 7 9 9 9 7 10 9 0 - - cg2687 10,2 0,42 0, 2, 8,14 2792 75 8 2,0 6,28 0,74 50 0,61 0,41 20 1,76 0,21 2 67 6 2 3 4 3 0 5 3 - - 64,995, 64,995, cg0133 8,24 0,11 N. 25, 1, 0, 15 13,0 133 502 7439 7 3 R. 26 13,0 0,05 N.R 57 2,63 0,54 0,43 74 8,05 0,92 N.R 85 3 50 3 . 5 0 9 0 3 6 7 . - cg1448 7,67 9,28 0,40 - 3, 11

8391 9 5 8 4,8 7,95 0,54 53 2,17 0,10 ,4 7,13 0,10 28 5 4 3 7 5 43 4 9 - cg1490 52,7 26,8 0,04 10, 3, 4,

9603 29 09 9 24 11,0 0,35 54 2,34 0,13 09 6,85 0,55 0 46 4 7 4 0 6 6 0 - - cg1895 24,3 35,0 0,48 11, 0, 0,

8966 51 06 7 68 15,7 0,45 45 2,21 0,83 17 6,48 0,97 0 04 7 9 1 5 0 8 9 - cg1979 13,5 9,03 0,13 - 1, 6,

7659 36 9 4 3,2 8,44 0,70 59 2,83 0,57 12 8,87 0,49 02 9 5 7 8 4 0 0 0 - - 22,018, 22,019, cg0041 20,2 0,55 N. 2, 28 16 12,0 727 338 9692 93 3 R. 0,7 1,36 0,58 N.R 82 4,50 0,53 0,89 ,5 14,2 0,04 N.R 30 46 9 6 . 9 2 0 0 52 85 6 . - - cg0541 6,99 0,16 - 0, 3, 9,62 8150 5 9 1,9 6,25 0,75 61 1,22 0,61 10 3,88 0,42 1 78 1 2 2 1 6 8 1 3 - cg1005 0,43 8,18 0,95 0, 6,

6854 1 0 8 0,4 1,94 0,82 23 1,69 0,88 00 5,34 0,26 37 3 2 6 4 9 9 3 1 - - cg2724 8,71 0,01 20, 0, 6, 21,4 7832 1 4 13 7,40 0,00 13 1,46 0,92 80 4,60 0,13 64 6 2 7 7 6 5 9 4 9 - - - 88,803, 88,804, cg0097 15,8 0,46 N. 12, 1,78 1, 0, 16 11,5 803 052 3732 56 5 R. 37 5,43 0,02 E- 28 1,03 0,21 0,06 22 3,22 0,94 N.R 81 9 1 3 04 2 5 5 0 8 9 4 . - - cg0306 1,57 0,74 - 0, 0, 0,51 2760 6 4 0,7 0,45 0,09 39 0,37 0,29 70 1,14 0,53 5 63 1 1 5 5 2 5 0 6 - - cg0698 2,45 0,32 - 0, 1, 2,43 8897 7 1 3,5 2,15 0,09 86 0,50 0,08 02 1,56 0,51 8 73 9 9 3 1 5 8 6 1 - - cg2674 1,39 0,66 - 0, 0, 0,60 8794 6 5 0,6 0,41 0,09 43 0,25 0,08 84 0,77 0,27 4 98 2 1 5 0 1 4 0 3 0, 0, 9,550,1 9,550,5 cg0236 3,94 4,19 0,34 N. 17 0,7 0,58 0,17 N.R 17 0,66 0,79 0,73 29 2,13 0,89 N.R 37 46 2978 7 4 7 R. 93 6 6 . 7 7 0 0 2 2 1 . - 0, - cg1213 4,60 0,81 1,07 1,4 1,83 0,42 66 0,69 0,34 2, 2,14 0,19 0768 3 6 0 62 3 5 5 7 0 76 6 8

- - cg1528 4,82 0,13 - 0, 3, 7,27 3852 8 2 0,0 1,21 0,95 35 0,63 0,58 47 2,07 0,09 6 77 8 0 0 8 4 5 5 4 - cg2269 3,62 4,32 0,40 - 0, 3,

7684 2 3 2 0,0 0,45 0,89 34 0,56 0,54 51 1,65 0,03 58 2 8 4 2 1 8 0 3 - - cg2337 4,79 0,92 0, 1, 0,43 8165 0 8 2,3 0,92 0,01 10 0,69 0,87 69 2,12 0,42 1 09 2 3 5 1 9 0 5 6 - 59,940, 59,941, cg0051 18,1 25,6 0,47 N. 19, 0, 10 17 709 133 5161 99 57 8 R. 14 11,3 0,09 0,01 92 1,45 0,52 0,57 ,0 4,31 0,01 N.R 6 53 2 4 8 2 3 0 77 2 9 . - - - - cg0086 24,0 0,93 10, 2, 2, 1,89 9632 28 7 01 14,0 0,47 63 4,86 0,58 97 14,5 0,83 8 1 61 7 1 8 9 6 15 8 - cg0537 47,5 25,5 0,06 18, 0, 3,

7417 26 87 3 26 9,76 0,06 89 1,55 0,56 23 4,52 0,47 8 5 2 7 3 4 6 7 5 - - - cg0598 16,0 0,27 11, 1, 6, 17,5 6149 94 4 24 6,49 0,08 89 3,90 0,62 49 11,4 0,57 97 8 0 4 9 7 7 4 66 1 - - cg0625 1,00 15,7 0,94 1, 18

7227 1 45 9 3,7 6,24 0,54 56 3,32 0,63 ,1 10,6 0,08 68 2 6 4 6 8 67 62 8 - - - cg1121 10,9 0,04 - 2, 0, 21,5 2038 13 8 3,3 7,60 0,65 52 1,62 0,11 13 5,26 0,98 69 56 9 9 4 1 9 4 0 0 - cg1152 23,0 20,3 0,25 11, 0, 9,

9614 89 51 7 66 6,30 0,06 40 3,68 0,91 09 10,8 0,40 5 5 5 9 6 2 0 17 1 - cg1243 3,48 14,9 0,81 11, 3, 9,

5611 2 20 5 14 6,70 0,09 27 3,21 0,30 38 9,59 0,32 5 3 7 7 4 8 0 2 8 - - - 1,063,6 1,064,2 cg0537 4,17 0,40 N. - 0, 0, 19 3,47 24 19 2495 8 6 R. 1,2 1,19 0,31 0,07 65 1,60 0,68 0,24 78 5,33 0,88 N.R 4 12 7 2 4 9 1 1 0 2 0 3 . - - cg1208 2,37 0,61 - 1, 0, 1,18 2025 3 9 0,7 0,46 0,11 14 0,96 0,23 32 2,85 0,91 1 40 2 0 6 3 4 5 9 0 - - cg2199 5,47 0,87 - 2, 6, 0,85 5147 6 6 1,3 1,05 0,20 22 1,48 0,13 82 5,47 0,21 3 49 8 3 1 3 4 6 1 2 - - 1,564,4 1,564,9 cg0007 4,12 0,47 N. - 0, 0, 1 2,93 FEV / 22 21 8456 2 6 R. 1,4 2,42 0,55 N.R 07 0,46 0,87 0,97 98 1,57 0,53 N.R 1 9 FVC 27 2 6 . 3 4 5 0 0 7 4 . - - 0, 2, cg0564 3,26 0,23 3,84 0,0 0,75 0,97 07 0,38 0,84 66 6,36 0,67 2789 7 9 3 23 8 6 5 0 4 1 2 6 - - cg1712 1,96 0,08 - 0, 0, 3,42 2213 2 1 0,1 0,54 0,79 17 0,35 0,63 84 1,24 0,49 2 44 1 0 0 2 0 8 5 6 - - cg1885 4,64 0,73 0, 0, 1,60 2096 3 0 0,6 3,04 0,84 03 0,43 0,92 12 1,49 0,93 3 02 2 3 9 2 7 5 6 3 - - 86,968, 86,968, cg0489 1,36 0,33 N. - 0, 0, 1 1,31 087 544 6168 7 5 R. 0,6 0,34 0,05 N.R 01 0,22 0,94 0,75 42 0,80 0,60 N.R 9 48 2 9 . 6 3 4 0 1 3 0 . - cg1076 - 0, 1, - - - 0651 0,3 0,32 0,32 19 0,53 0,72 62 1,93 0,40 24 6 1 2 7 1 0 3 2 - cg1980 - 0, 1, - - - 7991 0,6 0,36 0,08 44 0,59 0,44 63 2,15 0,44 42 9 3 8 0 8 8 6 7 - cg2682 - 0, 2, - - - 9098 1,0 0,81 0,21 64 0,68 0,34 73 2,52 0,27 07 5 7 5 5 7 6 9 9 - - 121,22 121,22 cg0741 2,27 0,78 N. - 0, 1, 2 0,61 3,534 3,965 2254 2 5 R. 0,0 0,35 0,81 N.R 38 0,56 0,49 0,78 23 1,95 0,52 N.R 9 83 2 4 . 6 6 6 0 1 6 9 . - - 0, 0, cg1145 2,49 0,85 0,45 0,3 0,32 0,22 14 0,46 0,75 72 1,61 0,65 5444 4 7 0 93 4 6 2 1 8 2 3 4 - - cg1720 6,55 0,04 - 0, 2, 13,0 4557 9 6 1,3 1,01 0,19 64 0,99 0,51 32 3,51 0,50 89 32 7 1 6 4 6 7 1 7

- - cg2140 1,67 0,76 - 0, 1, 0,49 6402 2 7 0,0 0,41 0,89 12 0,37 0,73 55 1,33 0,24 5 54 7 8 7 2 2 5 3 3 - - cg2300 2,10 0,83 - 0, 1, 0,43 6519 5 5 0,1 0,42 0,78 01 0,41 0,96 84 1,50 0,22 9 16 2 3 8 6 6 8 5 0 - - cg2368 2,49 0,65 0, 0, 1,10 9428 6 8 0,0 0,46 0,92 41 0,52 0,43 71 1,83 0,69 6 42 6 8 1 7 5 5 8 7 - 102,89 102,89 cg0297 1,90 2,18 0,38 N. 1, 3,20 3, 5 8,223 8,734 6617 5 4 3 R. 4,8 3,81 0,20 N.R 14 0,45 0,01 E- 19 1,65 0,05 0,04 50 6 4 . 4 2 1 03 1 8 4 7 - cg0765 0,93 2,31 0,68 1, 2,

5627 6 9 6 6,1 2,92 0,03 13 0,43 0,00 26 1,57 0,15 76 1 5 4 3 9 4 9 2 - cg0766 3,88 5,96 0,51 - 0, 1,

6882 1 6 5 1,2 2,87 0,67 68 0,48 0,15 57 1,70 0,35 23 9 1 8 5 7 4 5 6 - cg0916 1,46 2,63 0,57 1, 2,

6085 0 3 9 4,8 3,43 0,15 39 0,51 0,00 83 1,88 0,13 76 0 6 9 6 7 5 9 3 - cg1366 1,09 2,16 0,61 1, 2,

5998 7 5 2 1,5 3,60 0,67 00 0,41 0,01 45 1,49 0,10 15 8 5 1 2 5 8 4 0 - - cg1520 2,87 0,36 1, 1, 2,62 6834 3 1 2,9 1,79 0,10 13 0,48 0,02 15 1,69 0,49 3 45 8 2 1 5 0 3 4 6 - - 32,305, 32,305, cg1470 2,19 0,51 N. 0, 1,60 2, 6 1,43 068 146 4780 9 3 R. 0,0 0,36 0,83 N.R 75 0,26 0,00 E- 23 0,94 0,01 0,01 9 78 3 1 . 8 2 4 03 6 5 8 0 - - cg2063 1,68 0,31 - 1, 2, 1,71 6526 7 0 0,0 0,30 0,94 00 0,41 0,01 47 1,40 0,08 2 20 0 6 5 0 4 0 9 0 - - cg2464 3,85 0,40 1, 3, 3,18 0182 5 8 0,3 0,75 0,66 41 0,58 0,01 48 2,01 0,08 7 30 8 4 1 0 5 9 9 4 0, 8,60 168,53 168,53 cg0542 0,13 1,40 0,92 N. 6 0,9 0,48 0,05 N.R 35 0,31 0,25 0,22 E- 3,375 3,690 2022 4 7 4 R. 22 3 7 . 7 1 0 0 - - - 03 - cg0921 1,53 2,33 0,51 0, 3,

4616 2 6 2 0,7 0,65 0,22 39 0,36 0,27 19 1,26 0,01 99 2 1 5 1 4 3 2 1 - 0, cg1717 2,49 0,67 1,04 0,7 0,91 0,40 29 0,22 0,18 2308 3 4 9 56 3 8 6 4 6 - - - - cg2099 2,08 2,23 0,35 0, 2,

2785 6 0 0 0,2 0,71 0,68 25 0,34 0,45 28 1,22 0,06 90 6 5 6 0 1 1 2 2 - 135,05 135,05 cg0220 3,99 3,15 0,20 N. 1,27 0, 0, 10 1,149 1,582 7686 1 0 5 R. 2,2 1,46 0,12 E- 27 0,45 0,55 0,66 77 1,57 0,62 N.R 39 6 7 03 1 9 5 0 7 5 2 . - cg0264 3,70 4,63 0,42 0, 1,

5368 0 4 5 6,7 4,59 0,14 14 0,69 0,83 29 2,41 0,59 38 0 3 7 2 2 0 2 3 - - cg0434 2,85 3,92 0,46 0, 1,

7264 0 8 8 3,0 2,74 0,26 03 0,62 0,96 63 2,14 0,44 72 4 3 0 4 1 8 7 5 - cg0466 7,90 5,57 0,15 0, 0,

5423 8 1 6 5,4 4,47 0,22 47 0,76 0,53 48 2,65 0,85 79 6 1 8 4 1 7 5 5 - 0, 0, cg0982 4,46 0,70 1,70 5,6 4,61 0,22 22 0,76 0,77 26 2,65 0,92 7249 5 3 5 68 3 0 0 4 4 3 5 1 - cg1255 0, 3, - - - 4483 1,7 1,01 0,09 88 0,75 0,24 15 2,74 0,25 19 1 0 6 8 2 0 4 1 - cg1266 1, 2, - - - 6165 2,1 1,78 0,22 04 0,96 0,27 96 3,32 0,37 78 0 1 3 0 7 0 8 4 - 0, 0, cg1453 12,1 0,38 10,6 3,0 4,10 0,45 12 0,42 0,77 65 1,47 0,65 9179 43 2 08 73 4 4 3 7 3 9 4 5 - cg2047 3, 11 - - - 2189 6,4 4,98 0,19 76 2,95 0,20 ,4 10,0 0,25 64 1 5 1 6 3 44 42 4 - - cg2216 5,05 0,67 0, 1, 2,15 5685 1 0 4,7 3,83 0,21 31 0,73 0,66 53 2,59 0,55 0 98 6 2 9 6 4 5 0 3

- cg2384 0,34 4,03 0,93 0, 2,

5574 8 1 1 0,1 3,90 0,97 39 0,70 0,57 17 2,44 0,37 05 0 9 2 4 8 2 6 5 - - 64,064, 64,065, cg0493 11,4 0,01 N. 1, 0, 11 27,9 947 372 9630 93 5 R. 3,0 7,44 0,68 N.R 49 1,56 0,34 0,23 52 5,30 0,92 N.R 39 72 7 0 . 1 6 1 0 8 9 1 . - - cg1443 7,01 0,45 1, 13 5,24 7534 5 4 7,6 7,02 0,27 72 1,38 0,21 ,3 6,11 0,02 9 82 3 5 4 8 4 98 9 9 - - cg1984 4,62 0,90 12, 0, 4, 0,52 6387 2 9 05 5,55 0,03 80 0,77 0,29 57 3,03 0,13 6 9 0 0 4 2 8 4 1 1 - 0, 0, 67,417, 67,418, cg0035 5,76 4,20 0,17 N. 11 1,2 1,38 0,35 N.R 08 0,47 0,86 0,92 49 1,59 0,75 N.R 958 406 0199 1 3 0 R. 84 2 3 . 1 1 4 0 8 9 6 . - 0, 0, cg0124 4,79 3,52 0,17 0,0 0,69 0,94 15 0,42 0,71 23 1,40 0,86 0599 2 5 4 51 5 2 6 0 0 3 1 8 - 0, 1, cg0456 8,27 5,09 0,10 0,3 0,95 0,67 03 0,49 0,94 31 1,67 0,43 5008 6 9 5 99 5 7 1 1 9 7 0 0 - cg0498 1,22 2,58 0,63 - 0, 0,

6336 2 1 6 0,9 0,65 0,13 15 0,44 0,73 86 1,54 0,57 68 0 7 1 1 3 5 8 6 - cg0614 5,92 4,73 0,21 - 0, 1,

8175 6 5 1 0,6 0,44 0,17 12 0,44 0,77 63 1,49 0,27 01 5 7 4 3 9 1 9 7 - 0, 0, cg0929 1,17 2,53 0,64 0,2 0,29 0,43 04 0,36 0,90 48 1,26 0,69 6957 0 1 4 33 7 2 3 8 7 8 0 9 - 0, 0, cg1109 6,66 3,66 0,06 0,4 0,37 0,22 10 0,42 0,80 62 1,42 0,66 6993 8 9 9 51 3 7 7 4 0 0 1 3 - 0, 0, cg1235 1,35 2,37 0,56 0,2 0,40 0,47 06 0,33 0,85 00 1,14 0,99 5172 6 8 9 88 6 8 1 3 6 9 1 4 - cg1289 0,62 3,42 0,85 - 2,11 0, 0,

4325 6 2 5 7,7 2,08 E- 23 0,48 0,62 46 1,63 0,77 99 9 04 8 6 3 9 0 4 - 0, 0, cg2313 1,60 4,48 0,72 1,1 0,59 0,04 03 0,40 0,93 81 1,39 0,55 0075 6 7 0 88 0 5 5 9 3 7 2 7 - cg2583 1,64 2,25 0,46 - 0, 0,

5179 3 5 6 0,3 0,31 0,26 11 0,35 0,75 93 1,19 0,43 50 5 7 0 5 7 6 6 4 - - cg2628 2,79 0,80 - 0, 0, 0,68 8806 7 6 0,6 1,84 0,73 07 0,74 0,92 30 2,68 0,91 8 26 0 4 3 8 2 1 7 1 - cg2702 0,98 3,79 0,79 0, 0,

2933 5 4 5 0,1 1,48 0,93 22 0,44 0,61 81 1,51 0,59 19 0 6 3 2 4 1 0 1 - - - 20,805, 20,805, cg0001 8,72 0,62 N. 2,77 0, 6, 13 4,27 380 896 2692 7 4 R. 6,0 3,25 0,06 E- 44 1,38 0,74 0,37 80 4,97 0,17 N.R 5 08 3 5 04 3 4 9 0 9 6 1 . - cg0144 6,05 3,83 0,11 0, 4,

6515 4 5 4 5,6 3,77 0,13 10 0,77 0,88 83 2,88 0,09 46 3 5 8 4 9 5 0 3 - - cg0170 1,31 3,10 0,67 0, 2,

0504 2 3 2 2,0 0,94 0,02 28 0,67 0,67 52 2,36 0,28 93 7 7 4 9 6 4 7 6 - cg0347 5,51 14,8 0,71 - 1, 2,

3518 5 82 1 3,0 6,90 0,66 87 1,81 0,30 66 6,36 0,67 01 9 4 2 0 1 1 2 6 - cg0761 0,48 3,31 0,88 0, 1,

0777 5 9 4 3,0 1,54 0,04 83 0,62 0,18 37 2,19 0,53 53 7 9 6 9 4 4 8 2 - - cg1039 7,81 15,0 0,60 1, 15

5448 7 07 2 8,0 8,47 0,34 00 1,81 0,58 ,8 7,07 0,02 57 8 2 1 0 0 22 5 5 - cg1836 1,28 2,98 0,66 0, 0,

3035 2 7 8 5,5 1,81 0,00 77 0,72 0,28 15 2,66 0,95 48 2 2 7 4 3 8 6 3 - cg2097 4,16 2,63 0,11 0, 6,

2453 4 1 4 1,8 0,94 0,05 70 0,77 0,36 88 2,78 0,01 33 9 4 0 8 8 8 6 3 - - cg2237 15,3 0,82 - 4, 4, 3,32 7389 58 9 6,0 7,10 0,39 62 1,70 0,00 86 5,81 0,40 1 51 6 5 0 7 7 9 4 2 9, - 96,180, 96,181, cg0431 0,57 4,01 0,88 37 0, 0, 14 406 045 3756 5 9 6 E- 0,7 0,98 0,41 N.R 00 0,54 0,99 N.R 62 1,87 0,74 N.R 06 97 3 7 . 5 6 3 . 1 0 0 .

- cg0744 3,91 3,15 0,21 - 1, 1,

5246 8 9 5 1,3 1,36 0,31 04 0,96 0,27 51 1,69 0,37 67 3 6 3 0 7 9 3 0 - cg0809 5,08 5,59 0,36 - 0, 0,

2680 0 5 4 0,7 0,55 0,18 02 0,42 0,96 30 1,42 0,83 33 2 5 0 5 3 0 0 3 - cg1328 0,07 4,01 0,98 0, 1,

2837 4 0 5 8,7 3,72 0,01 38 0,66 0,56 48 2,22 0,50 58 3 9 2 0 3 9 8 4 - cg1669 4,89 5,17 0,34 0, 3,

6317 8 4 4 2,0 1,10 0,06 07 0,54 0,89 89 1,90 0,04 39 3 5 2 1 4 0 7 1 - cg1771 1,74 4,35 0,68 0, 0,

7124 6 1 8 1,0 4,08 0,80 30 0,63 0,63 79 2,18 0,71 02 0 6 1 4 5 1 3 7 - cg1999 0,91 4,80 0,85 0, 2,

2633 1 2 0 0,2 2,06 0,91 40 0,52 0,43 89 1,89 0,12 14 7 8 5 0 7 9 5 6 - cg2311 8,93 6,09 0,14 0, 2,

4311 1 5 3 3,1 3,34 0,35 96 0,53 0,07 99 1,88 0,11 09 4 3 3 6 2 0 1 2 - cg2499 0,42 6,29 0,94 0, 0,

6565 9 4 6 3,6 2,60 0,16 22 0,67 0,74 56 2,24 0,80 22 3 5 3 9 3 8 3 0 - cg2708 4,89 10,5 0,64 0, 2,

9768 0 87 4 1,4 1,39 0,28 30 0,65 0,63 13 2,29 0,35 95 5 4 7 6 9 2 6 3 - - 89,023, 89,023, cg0243 3,30 0,71 0, - 0, 1, 16 1,20 389 634 1972 8 7 02 0,1 0,40 0,65 N.R 46 0,61 0,45 0,50 30 2,14 0,54 N.R 1 7 81 9 9 . 6 9 2 0 9 7 2 . - - cg0595 3,76 0,83 - 0, 2, 0,79 3373 2 2 0,1 0,54 0,77 39 0,36 0,27 66 2,33 0,25 8 55 9 8 5 1 4 2 3 4 - - - cg0873 5,63 0,94 - 0, 0, 0,37 2950 3 7 0,3 0,56 0,48 70 0,96 0,46 35 3,30 0,91 3 97 3 2 0 7 9 5 1 4 - 19,314, 19,314, cg0427 1,49 7,88 0,85 N. 1, 5, 17 299 619 9801 3 8 0 R. 0,7 0,64 0,25 N.R 30 0,87 0,13 0,11 73 3,16 0,07 0,03 41 8 3 . 7 8 6 0 8 9 0 7 - cg0948 2,11 5,85 0,71 1, 4,

2093 0 8 9 2,3 1,50 0,11 32 0,72 0,06 54 2,51 0,07 51 1 8 6 2 6 5 5 1 - cg1330 0,61 4,97 0,90 1, 4,

5951 8 6 1 0,5 0,46 0,25 01 0,58 0,07 79 2,07 0,02 37 7 1 8 0 9 3 7 1 - - cg1667 4,57 0,26 0, 2, 5,06 4433 0 8 1,0 0,87 0,22 41 0,70 0,55 49 2,51 0,32 3 52 1 8 9 8 4 5 0 0 - cg2115 3,55 8,07 0,66 1, 4,

8317 8 9 0 0,6 0,59 0,27 52 0,99 0,12 12 3,48 0,23 50 5 5 2 5 6 2 8 7 - - cg2693 3,56 0,56 0, 1, 2,08 9946 7 0 1,1 0,74 0,12 48 0,49 0,32 49 1,71 0,38 0 41 0 4 5 5 7 2 5 5 - - 79,485, 79,485, cg1431 2,54 0,03 N. - 1, 10 17 5,43 529 710 6944 3 3 R. 0,1 0,74 0,80 N.R 21 1,22 0,32 0,09 ,5 4,31 0,01 N.R 4 88 6 2 . 4 1 0 0 31 5 5 . - - 1, cg2471 4,78 0,05 9,16 0,3 1,30 0,79 96 0,98 0,04 8197 8 6 0 45 0 1 8 1 5 - - - 1, - - 40,759, 40,759, cg1597 2,33 0,41 75 0, 1, 21 1,88 534 695 7137 6 9 E- 0,0 0,72 0,92 N.R 48 0,49 0,32 0,66 54 1,33 0,24 N.R 9 03 72 3 0 . 5 5 7 0 2 8 9 . - - 0, 1, cg1968 2,05 0,40 1,69 0,1 0,61 0,81 11 0,31 0,71 62 1,18 0,16 4207 9 9 8 47 2 1 6 8 5 1 0 9 - - 0, 1, cg1976 3,14 0,28 3,33 0,6 1,13 0,56 15 0,43 0,71 70 1,57 0,28 1502 3 8 7 56 9 5 9 2 2 2 8 1 - - 0, 0, cg2173 6,01 0,17 8,24 0,9 2,15 0,64 37 0,48 0,44 61 1,76 0,72 6411 6 0 9 86 3 7 6 7 1 4 3 7 - - 0, 1, cg2711 1,55 0,17 2,08 0,1 0,51 0,83 13 0,26 0,60 01 0,97 0,29 9318 2 9 8 07 1 4 7 1 0 5 7 9 5, 1,957,0 1,957,7 cg0484 1,93 4,27 0,65 57 0, 1 73 12 7273 9 4 0 E- 0,9 1,06 0,37 N.R 52 0,46 0,25 0,42 N.R FEF75 03 55 6 1 . 4 5 9 0 - - - .

- cg1083 9,67 8,43 0,25 - 0, 4,

7110 7 7 1 0,2 1,14 0,82 44 0,49 0,37 05 2,99 0,17 58 0 1 0 5 4 9 8 6 - 0, 0, cg1582 0,34 6,80 0,96 1,9 1,30 0,13 53 0,63 0,40 05 2,81 0,98 5127 0 6 0 31 0 8 2 5 2 1 6 6 - cg2328 2,57 7,02 0,71 0, 0,

8755 7 0 4 2,9 2,04 0,14 04 0,58 0,93 12 2,68 0,96 78 0 5 8 3 4 1 9 4 - 0, 0, cg2410 5,49 0,94 0,37 0,6 1,56 0,67 22 0,43 0,60 00 2,00 0,99 5782 6 6 4 49 2 8 4 3 5 8 6 7 - - - 2,383,4 2,383,6 cg0015 7,49 0,76 N. - 0, 0, 1 2,21 38 88 7179 0 7 R. 3,8 1,49 0,01 N.R 59 0,51 0,25 0,41 33 2,39 0,89 N.R 5 34 0 0 . 2 5 1 0 0 8 0 . - cg0621 3,51 5,67 0,53 0, 1,

5416 6 6 6 1,3 0,66 0,04 39 0,42 0,34 25 2,08 0,54 24 4 7 8 0 3 4 2 7 - - cg1272 3,39 5,76 0,55 - 0, 0,

8061 5 6 6 0,4 1,63 0,78 29 0,39 0,45 09 1,86 0,96 46 5 5 2 5 9 3 3 0 - - cg1338 4,31 5,12 0,40 0, 1,

4949 7 9 0 0,8 2,57 0,74 13 0,42 0,74 45 2,06 0,48 48 5 2 8 8 7 0 6 3 - - 17,634, 17,634, cg1609 6,96 0,71 N. 0, 2, 1 2,51 543 717 1981 4 8 R. 3,2 4,93 0,51 N.R 66 1,11 0,55 0,47 81 5,27 0,59 N.R 4 36 1 2 . 6 3 0 0 9 1 3 . - 0, cg1833 6,00 0,22 7,27 0,9 2,90 0,73 04 0,22 0,83 3690 5 6 3 84 8 5 8 7 3 - - - - cg2129 1,10 4,95 0,82 0, 5,

5838 1 3 4 0,7 3,57 0,84 87 0,83 0,29 63 3,98 0,15 13 0 2 8 4 3 1 4 8 - - cg2691 5,68 0,75 0, 1, 1,81 8754 9 0 6,5 4,25 0,12 47 0,95 0,61 48 4,41 0,73 1 80 7 3 6 7 9 6 8 7 - 86,968, 86,968, cg1076 N. 0, 1, 1 - - - 087 256 0651 R. 8,5 4,32 0,05 N.R 61 0,41 0,13 0,03 62 1,93 0,40 N.R 18 8 0 . 5 4 7 7 0 3 2 . - cg1980 - 0, 1, - - - 7991 0,5 0,32 0,06 59 0,45 0,19 63 2,15 0,44 91 1 6 2 6 4 8 6 7 - cg2682 - 0, 2, - - - 9098 0,7 0,70 0,31 86 0,52 0,10 73 2,52 0,27 15 5 1 2 9 3 6 9 9 - 14,774, 14,774, cg1100 18,6 13,3 0,16 0, 0, 1, 2 786 903 7759 43 16 1 01 5,5 4,05 0,17 N.R 58 0,68 0,39 0,28 00 3,28 0,76 N.R 1 40 0 2 . 1 6 6 0 3 2 0 . - cg1302 3,06 7,32 0,67 1, 4,

1841 4 2 6 5,1 4,80 0,28 23 0,68 0,06 55 3,18 0,15 84 3 1 9 2 9 3 3 3 - 0, 6, cg2576 8,37 0,49 5,72 5,4 8,20 0,51 58 1,56 0,70 89 7,25 0,34 5130 9 4 5 03 9 1 6 4 8 8 4 2 - - - 54,086, 54,087, cg0070 2,88 0,58 N. 0, 0, 2 1,58 854 553 1946 0 2 R. 0,4 0,70 0,56 N.R 31 0,35 0,37 N.R 95 1,64 0,56 N.R 4 12 9 2 . 7 7 6 . 0 9 5 . - cg0140 27,3 16,0 0,08 - 0, 7,

0468 15 46 9 0,2 1,27 0,84 34 0,72 0,63 84 3,57 0,02 52 0 3 3 4 5 2 5 8 - - - cg0187 2,69 0,65 0, 0, 1,22 6338 7 1 0,1 0,18 0,46 46 0,34 0,18 26 1,63 0,87 0 36 6 6 9 9 0 3 9 2 - - - cg0541 4,01 0,32 0, 1, 3,98 4908 2 1 1,0 1,03 0,30 19 0,48 0,68 43 2,20 0,51 2 72 4 0 3 3 9 4 6 6 - - - cg0861 3,53 0,43 0, 2, 2,74 1810 0 7 1,4 1,02 0,15 06 0,53 0,90 68 2,43 0,27 1 43 1 8 2 2 8 0 0 0 - - cg1012 4,28 11,8 0,71 0, 1,

4812 2 36 8 0,2 1,36 0,84 55 1,26 0,66 39 6,72 0,83 72 4 2 3 3 1 1 3 6 - - cg1193 5,13 9,05 0,57 0, 0,

9825 1 8 1 0,8 0,93 0,37 68 0,53 0,20 33 2,38 0,89 31 5 4 9 8 1 0 8 0 - - - cg1245 2,41 0,78 0, 0, 0,67 1530 4 1 0,9 0,71 0,20 21 0,42 0,61 98 1,91 0,60 0 04 1 4 1 2 7 5 8 7

- - - cg1335 4,43 0,35 0, 0, 4,08 6253 3 6 0,4 1,28 0,71 28 0,62 0,64 76 2,92 0,79 9 71 3 4 9 7 4 1 3 5 - - - cg1483 2,59 0,33 - 0, 0, 2,49 2904 5 6 0,0 0,18 0,58 36 0,36 0,32 46 1,68 0,78 5 98 1 7 1 4 1 2 9 4 - - - cg1959 12,3 0,59 - 0, 4, 6,53 2277 55 7 0,6 1,78 0,72 14 0,79 0,85 28 4,01 0,28 0 28 9 6 1 9 9 7 8 6 - - cg1966 2,25 0,63 0, 0, 1,06 4945 7 7 0,2 0,26 0,35 40 0,32 0,21 56 1,44 0,69 5 46 5 3 4 4 2 4 6 7 - - - cg1987 3,87 0,56 0, 1, 2,21 8627 1 6 1,1 1,09 0,28 19 0,47 0,67 02 2,18 0,63 9 86 6 0 8 9 9 7 7 9 - - - cg1996 2,94 0,83 - 0, 0, 0,59 1545 2 9 0,0 0,57 0,86 35 0,35 0,31 24 1,60 0,87 6 99 1 3 2 1 7 5 8 9 - 62,860, 62,860, cg1351 N. - 1, 4, 3 - - - 103 225 4230 R. 0,2 6,44 0,96 N.R 15 1,69 0,49 0,74 14 7,21 0,56 N.R 64 7 7 . 4 4 6 0 7 5 5 . - - - cg1591 7,36 0,68 - 0, 0, 2,95 4463 6 9 2,4 7,34 0,73 19 1,08 0,85 47 4,88 0,92 1 74 8 6 3 2 8 7 4 2 7, - 125,93 125,93 cg0420 2,15 4,06 0,59 93 0, 0, 5 1,001 1,363 0010 8 9 6 E- 0,0 0,36 0,89 N.R 14 0,31 0,64 0,03 78 1,43 0,58 N.R 05 46 3 9 . 7 6 1 2 9 7 3 . - cg0870 1,25 2,47 0,61 0, 0,

2413 2 9 4 0,6 0,97 0,48 09 0,34 0,79 67 1,60 0,67 84 2 2 0 3 3 2 1 5 - cg1673 12,8 8,31 0,12 1, 6,

8971 92 6 1 2,1 4,35 0,61 81 0,96 0,05 34 4,41 0,15 86 5 6 9 5 9 3 9 1 - cg1765 5,10 6,19 0,41 1, 3,

3368 2 2 0 5,9 3,10 0,05 95 0,95 0,04 89 4,57 0,39 21 5 7 1 4 1 9 7 4 - cg1867 0,67 7,05 0,92 2, 9,

0373 1 2 4 8,0 5,13 0,11 22 1,08 0,04 22 5,26 0,08 59 3 7 3 6 1 8 4 0 - - cg1955 32,6 0,94 - 1, 3, 2,20 1232 21 6 1,8 8,07 0,82 59 0,92 0,08 15 4,07 0,43 3 03 6 3 8 0 3 6 5 9 - cg2632 10,7 15,7 0,49 2, 11

7732 47 10 4 7,3 7,64 0,33 34 1,32 0,07 ,3 5,94 0,05 44 3 7 4 0 6 21 3 7 9, - 135,41 135,41 cg0012 0,78 5,75 0,89 72 - 0, 0, 5 6,029 6,614 4993 6 0 1 E- 0,0 0,28 0,88 N.R 04 0,13 0,72 N.R 79 0,62 0,20 0,06 06 42 0 1 . 8 3 1 . 3 0 1 3 - - cg0448 1,15 0,48 - 0, 0, 0,81 1923 9 4 0,3 0,96 0,70 04 0,15 0,76 68 0,70 0,33 2 67 2 3 6 0 1 2 9 7 - - cg0647 3,31 0,34 0, 0, 3,14 8886 7 3 0,3 1,27 0,75 09 0,20 0,63 85 0,99 0,39 5 94 6 8 9 9 7 7 8 1 - cg0653 6,00 9,50 0,52 - 0, 0,

6614 9 4 7 0,2 0,65 0,65 05 0,13 0,68 82 0,61 0,18 99 9 0 3 1 6 5 8 2 - - cg0874 1,18 0,22 - 0, 0, 1,45 5965 7 1 0,3 0,67 0,63 05 0,16 0,75 86 0,77 0,25 1 17 2 7 1 3 4 9 0 9 - - cg1661 1,13 0,31 - 0, 1, 1,12 5357 0 9 0,1 0,35 0,58 12 0,16 0,47 13 0,79 0,15 7 96 4 0 0 9 9 9 3 1 - - cg1867 1,22 0,46 - 0, 1, 0,89 8645 0 5 0,4 1,13 0,70 09 0,16 0,58 05 0,77 0,17 1 29 9 6 1 5 2 6 7 4 - - cg1879 3,01 0,63 - 0, 0, 1,44 7653 6 2 0,3 0,40 0,41 08 0,15 0,60 94 0,74 0,20 3 31 5 5 3 8 0 4 5 5 - cg2534 7,57 10,6 0,47 0, 0,

0688 3 09 5 0,0 0,73 0,99 04 0,11 0,70 75 0,55 0,18 01 0 9 6 9 0 0 9 0 - cg2632 3,86 10,9 0,72 0, 0,

8633 9 24 3 0,0 0,74 0,96 04 0,11 0,70 77 0,55 0,15 31 8 7 5 8 6 9 4 9

- cg2689 6,97 9,33 0,45 0, 1,

6946 3 1 5 0,0 0,35 0,86 09 0,15 0,54 17 0,72 0,10 60 1 5 5 5 1 5 6 6 7, 138,72 138,72 cg0873 1,84 5,57 0,74 52 - 3, 1, 5 5,400 5,831 6680 1 1 1 E- 1,2 5,51 0,82 N.R 14 1,34 0,01 0,07 33 6,57 0,83 N.R 04 48 7 1 . 7 5 9 5 6 4 9 . - - cg1162 5,55 0,61 - 1, 8, 2,82 3339 2 1 3,7 2,89 0,19 52 1,12 0,17 31 5,32 0,11 2 62 3 4 8 9 6 2 7 9 - cg1350 5,67 4,44 0,20 - 0, 1,

0819 7 5 2 0,1 0,47 0,68 05 0,96 0,95 03 4,63 0,82 90 1 7 5 6 5 3 0 4 - - cg1471 5,82 0,70 1, 4, 2,23 0984 9 2 5,6 5,47 0,29 50 1,09 0,16 02 5,05 0,42 3 95 2 8 1 3 9 8 4 5 - - cg2411 6,35 0,16 - 2, 0, 8,82 3496 3 5 4,5 4,48 0,31 33 1,08 0,03 44 4,90 0,92 5 14 5 5 2 4 2 0 1 8 7. - - 31,650, 31,651, cg0002 1,15 0,70 61 1,56 0, 0, 6 0,44 735 159 2997 5 3 E- 0,7 0,30 0,02 E- 11 0,25 0,63 0,93 41 1,14 0,71 N.R 0 07 00 5 2 07 8 0 8 0 8 2 5 . - - cg0129 2,76 0,88 0, 1, 0,39 7670 4 7 3,2 1,36 0,01 25 0,37 0,50 79 1,74 0,30 2 09 4 9 2 4 1 4 3 3 - - cg0216 2,34 0,92 0, 1, 0,21 9713 8 6 1,3 0,73 0,06 23 0,37 0,54 26 1,74 0,46 7 44 3 7 0 6 1 6 5 8 - 0, 0, cg0230 1,26 0,31 1,27 1,3 0,65 0,04 03 0,24 0,89 01 1,14 0,98 4584 9 6 1 47 7 1 4 8 1 8 0 8 - - cg0238 1,22 0,59 0, 0, 0,65 9040 3 4 0,3 0,50 0,46 01 0,22 0,93 32 1,02 0,74 2 71 4 2 9 7 2 9 4 8 - - cg0438 1,30 0,27 0, 0, 1,42 6400 8 6 0,6 0,56 0,27 03 0,22 0,88 42 1,05 0,68 6 20 9 6 3 6 4 5 7 8 - - cg0585 1,12 0,82 0, 0, 0,24 7999 8 6 0,4 0,27 0,09 12 0,21 0,56 69 1,01 0,49 8 69 7 2 7 9 1 8 5 1 - - cg0646 2,00 0,28 0, 1, 2,13 0587 7 8 0,6 0,39 0,08 17 0,32 0,58 02 1,52 0,50 4 97 9 1 7 0 1 2 2 2 - - cg0745 1,13 0,45 0, 0, 0,85 5790 6 0 0,4 0,25 0,06 09 0,23 0,69 20 1,11 0,85 8 79 6 2 3 9 6 8 3 2 - - cg0862 1,11 0,33 0, 0, 1,06 4648 3 8 0,5 0,32 0,07 26 0,28 0,34 85 1,36 0,52 6 78 4 5 5 1 6 8 2 9 - - cg1826 1,30 0,22 0, 0, 1,58 4486 1 4 0,6 0,29 0,03 50 0,56 0,37 52 1,05 0,61 1 35 6 3 1 8 8 8 1 6 - - cg1857 1,12 0,43 0, 0, 0,88 6957 4 0 0,4 0,33 0,16 09 0,25 0,70 06 1,20 0,95 7 63 1 2 6 5 6 6 2 6 - - cg2043 1,27 0,35 - 0, 0, 1,18 5535 7 5 0,2 0,60 0,70 07 0,24 0,74 10 1,11 0,92 0 27 2 6 8 1 7 8 9 3 - - cg2231 2,07 0,21 0, 0, 2,57 8514 8 4 0,8 0,35 0,01 02 0,22 0,92 40 1,06 0,70 9 62 4 5 2 8 3 5 3 3 - - cg2541 2,15 0,56 0, 2, 1,25 7675 7 1 1,2 0,50 0,01 12 0,39 0,74 06 1,82 0,25 3 75 5 2 9 2 3 6 9 9 - - cg2645 1,92 0,41 0, 0, 1,56 0717 0 4 0,7 0,41 0,08 02 0,28 0,93 40 1,32 0,76 8 13 0 3 5 6 1 3 8 1 9, - - 31,690, 31,691, cg0057 6,26 0,35 09 0, 5, 6,74 6 5,76 998 540 8039 2 7 E- 0,5 0,92 0,52 N.R 85 0,69 0,21 0,39 39 3,24 0,09 E- 3 03 84 8 9 . 8 9 9 0 7 9 7 03 - - cg0133 6,14 0,62 - 1, 2, 3,01 9648 8 4 1,0 5,28 0,84 21 0,82 0,14 91 3,85 0,45 1 05 8 9 6 8 2 3 3 0 - - cg0692 4,45 0,92 0, 6, 0,40 8741 6 8 0,2 0,90 0,78 91 0,63 0,15 11 3,03 0,04 1 52 3 1 4 6 0 5 4 4

- - cg1443 7,02 0,24 0, 0, 8,21 7986 2 2 9,0 5,54 0,10 32 0,85 0,70 61 3,99 0,87 1 16 7 5 7 8 3 1 1 8 - - - cg1452 4,86 0,92 0, 2, 0,44 2990 3 8 1,1 0,76 0,12 16 0,59 0,78 82 2,75 0,30 1 82 9 5 0 2 7 9 2 4 - - cg1597 1,77 5,66 0,75 0, 1,

3098 3 3 4 0,9 4,30 0,83 55 0,65 0,39 52 2,91 0,60 22 6 0 8 6 5 8 9 1 - cg1606 3,68 10,6 0,72 0, 5,

3587 8 43 9 3,1 2,66 0,23 14 0,65 0,82 50 3,04 0,07 94 1 1 4 1 5 9 3 0 - - cg1871 7,57 0,78 0, 1, 2,02 8647 1 9 5,5 6,03 0,36 11 0,87 0,89 88 4,09 0,64 3 19 3 1 6 5 5 8 3 5 - - cg2019 4,50 5,82 0,43 0, 5,

1740 7 0 9 0,9 0,76 0,20 19 0,68 0,77 62 3,14 0,07 74 3 2 5 1 4 4 7 4 - cg2150 3,77 3,26 0,24 0, 4,

6565 7 6 8 0,0 0,74 0,94 62 0,34 0,07 27 1,57 0,00 48 2 9 4 5 1 3 7 7 1, - 132,27 132,27 cg1462 10,4 5,04 0,03 53 - 0, 1, 6 1,361 1,589 3917 29 3 9 E- 0,0 3,19 0,98 N.R 63 0,43 0,14 0,27 01 1,94 0,60 N.R 03 62 8 5 . 9 5 2 0 7 5 1 . - cg2284 9,06 4,71 0,05 0, 1,

3613 5 0 4 2,2 2,65 0,40 48 0,36 0,19 01 1,64 0,53 24 2 2 1 7 0 4 8 9 - cg2468 1,36 6,32 0,82 0, 2,

4168 4 5 9 5,7 3,68 0,12 16 0,65 0,80 33 3,07 0,44 14 3 1 6 6 0 4 4 8 3, - - 158,04 158,04 cg0277 1,28 0,53 81 0, 0, 7 0,80 5,980 6,359 0061 8 2 E- 0,0 0,20 0,68 N.R 13 0,13 0,33 0,94 72 0,61 0,23 N.R 6 04 83 7 8 . 5 9 3 0 9 8 8 . - - cg0640 1,32 0,92 0, 0, 0,12 0119 4 3 0,2 0,32 0,37 13 0,20 0,50 71 0,94 0,45 8 86 2 5 7 5 4 4 7 1 - - cg0671 1,21 0,57 0, 0, 0,69 5136 5 0 0,2 0,29 0,46 01 0,21 0,93 36 1,00 0,71 0 17 7 6 8 3 1 5 6 7 - 0, 0, cg1047 2,62 0,15 3,76 0,0 0,47 0,92 02 0,23 0,90 34 1,04 0,74 3311 4 1 7 43 7 8 9 8 2 1 9 5 - - - cg1657 1,93 0,42 0, 0, 1,54 1642 5 6 0,0 0,57 0,91 02 0,29 0,93 39 1,32 0,76 2 61 8 6 3 6 8 1 7 8 - cg2720 0, 2, - - - 0869 0,5 0,71 0,46 23 0,63 0,70 88 2,81 0,30 25 0 0 7 2 7 8 6 5 4, - - 142,37 142,37 cg0314 6,59 0,73 12 - 0, 7, 8 2,27 7,303 7,490 4848 7 1 E- 5,4 7,08 0,44 N.R 96 1,19 0,42 0,68 64 5,40 0,15 N.R 0 03 45 2 2 . 2 3 0 0 8 6 7 . - cg0359 1,39 6,49 0,83 11, 0, 6,

2763 7 1 0 31 5,60 0,04 48 0,87 0,57 43 4,03 0,11 8 0 4 8 9 9 1 2 1 - cg0413 17,8 7,74 0,02 - 0, 5,

7003 32 2 1 1,4 1,98 0,45 64 0,91 0,48 13 4,01 0,20 85 7 5 4 8 3 3 5 1 - - cg0719 8,31 0,30 - 0, 5, 8,48 0229 9 8 7,7 9,21 0,39 58 1,54 0,70 67 6,87 0,40 3 68 1 9 6 3 4 4 2 9 - - cg1319 11,9 0,35 - 0, 0, 10,9 5954 59 8 1,0 8,29 0,89 40 1,63 0,80 53 7,46 0,94 99 53 2 9 9 4 2 4 1 3 - 2,721,2 2,721,6 cg0187 15,8 7,78 0,04 N. - 1, 0, 11 07 33 3334 26 4 2 R. 1,7 1,36 0,21 N.R 17 1,35 0,38 0,51 79 6,50 0,90 N.R 07 1 0 . 2 7 8 0 6 0 3 . - - cg0221 0,63 5,73 0,91 - 0, 0,

9360 6 2 2 0,6 0,52 0,18 99 0,73 0,17 83 3,43 0,80 98 9 8 9 6 5 8 1 7 - 1, 1, cg0340 26,7 13,9 0,05 0,1 1,34 0,94 63 0,96 0,09 26 4,98 0,80 1726 41 43 5 01 1 0 3 9 2 1 9 0 0, 2, cg0759 4,49 7,29 0,53 0,7 0,81 0,38 67 1,03 0,51 25 4,89 0,64 5203 3 2 8 06 2 6 7 7 4 4 3 5 - cg0835 22,2 8,80 0,01 - 2, 4,

9167 12 4 2 0,3 1,18 0,77 17 1,19 0,06 34 5,30 0,41 33 1 8 3 2 8 5 3 3

- - cg0844 12,0 8,25 0,14 - 0, 2,

6215 83 7 3 0,9 0,51 0,05 08 0,99 0,93 37 4,69 0,61 86 6 7 6 3 1 5 7 3 - cg0951 5,84 4,47 0,19 - 0, 1,

8720 5 7 2 1,5 0,92 0,08 52 0,46 0,25 63 2,10 0,43 92 0 4 2 1 7 2 5 8 - 0, 2, cg1439 6,63 0,84 1,33 1,1 2,23 0,60 19 0,82 0,80 24 3,58 0,53 2746 5 1 4 57 1 4 8 0 9 1 1 2 - cg1495 11,2 13,2 0,39 - 0, 5,

8441 85 63 5 1,6 3,94 0,67 35 1,40 0,80 47 6,37 0,39 70 8 3 0 1 3 7 2 0 - cg1673 11,3 8,03 0,15 0, 5,

9686 52 4 8 0,0 0,52 1,00 83 0,80 0,29 42 4,40 0,21 00 9 0 5 0 7 3 6 8 0, 4, cg2069 0,50 7,71 0,94 0,2 0,61 0,73 18 0,91 0,84 11 4,32 0,34 9737 6 4 8 06 5 7 5 8 0 2 3 2 - 0, 0, cg2610 3,37 7,03 0,63 0,8 0,53 0,09 79 0,96 0,40 25 4,62 0,95 4781 4 6 2 89 6 8 8 0 6 3 3 6 - - cg2654 16,4 7,70 0,03 0, 1,

7719 17 0 3 0,5 0,85 0,55 32 0,98 0,74 90 5,47 0,72 05 9 7 6 6 1 1 8 9 - - cg2732 26,0 11,6 0,02 - 0, 6,

3091 14 44 5 0,1 1,46 0,89 62 1,41 0,65 07 6,68 0,36 90 2 7 8 1 7 3 4 4 - 67,417, 67,418, cg0035 5,76 4,20 0,17 N. - 0, 0, 11 958 406 0199 1 3 0 R. 0,9 1,20 0,45 N.R 26 0,35 0,46 0,66 49 1,59 0,75 N.R 00 7 6 . 0 3 2 0 8 9 6 . - cg0124 4,79 3,52 0,17 - 0, 0,

0599 2 5 4 0,1 0,60 0,79 07 0,31 0,81 23 1,40 0,86 55 8 9 3 4 7 3 1 8 - cg0456 8,27 5,09 0,10 - 0, 1,

5008 6 9 5 0,1 0,82 0,87 28 0,36 0,44 31 1,67 0,43 30 8 5 2 7 3 7 0 0 - cg0498 1,22 2,58 0,63 - 0, 0,

6336 2 1 6 0,2 0,56 0,68 19 0,33 0,55 86 1,54 0,57 30 7 5 5 0 4 5 8 6 - cg0614 5,92 4,73 0,21 - 0, 1,

8175 6 5 1 0,5 0,38 0,17 29 0,33 0,38 63 1,49 0,27 22 7 8 1 1 0 1 9 7 - cg0929 1,17 2,53 0,64 - 0, 0,

6957 0 1 4 0,1 0,25 0,66 15 0,27 0,57 48 1,26 0,69 13 8 2 4 5 5 8 0 9 - cg1109 6,66 3,66 0,06 - 0, 0,

6993 8 9 9 0,4 0,32 0,20 00 0,31 0,99 62 1,42 0,66 04 1 9 3 6 3 0 1 3 - cg1235 1,35 2,37 0,56 - 0, 0,

5172 6 8 9 0,0 0,35 0,84 09 0,24 0,69 00 1,14 0,99 68 4 8 9 9 1 9 1 4 - - cg1289 0,62 3,42 0,85 - 0, 0,

4325 6 2 5 5,0 1,83 0,00 23 0,36 0,51 46 1,63 0,77 10 5 7 6 4 7 9 0 4 - cg2313 1,60 4,48 0,72 - 0, 0,

0075 6 7 0 0,5 0,51 0,25 20 0,30 0,50 81 1,39 0,55 87 3 3 6 5 0 7 2 7 - cg2583 1,64 2,25 0,46 - 0, 0,

5179 3 5 6 0,3 0,27 0,24 16 0,26 0,52 93 1,19 0,43 19 5 6 7 4 8 6 6 4 - - cg2628 2,79 0,80 - 0, 0, 0,68 8806 7 6 0,8 1,59 0,59 97 0,55 0,08 30 2,68 0,91 8 57 2 0 2 9 2 1 7 1 - - cg2702 0,98 3,79 0,79 0, 0,

2933 5 4 5 1,3 1,28 0,28 21 0,33 0,51 81 1,51 0,59 62 0 8 4 1 9 1 0 1 - - 114,84 114,84 cg0880 13,8 0,95 0, - 2, 13 12 0,84 3,919 4,266 7097 44 2 02 8,9 8,54 0,29 N.R 16 1,52 0,15 0,04 ,6 7,98 0,08 N.R 2 5 29 0 6 . 8 7 6 9 48 7 7 . - - cg2042 7,85 0,77 - 3, 18 2,24 6571 9 6 6,0 7,15 0,39 43 1,52 0,02 ,7 8,77 0,03 0 87 3 5 9 5 4 74 0 2 - - cg2332 9,12 0,89 15, 1, 8, 1,25 0862 4 1 31 9,06 0,09 15 1,36 0,39 71 7,25 0,23 5 0 2 2 5 3 7 1 3 0 9, 96,180, 96,181, cg0431 0,57 4,01 0,88 37 0, 0, 14 406 045 3756 5 9 6 E- 1,1 0,83 0,17 N.R 02 0,40 0,95 0,87 62 1,87 0,74 N.R 06 21 2 8 . 3 6 5 0 1 0 0 .

- cg0744 3,91 3,15 0,21 - 0, 1,

5246 8 9 5 0,2 1,18 0,83 08 0,38 0,83 51 1,69 0,37 45 5 6 2 9 4 9 3 0 - cg0809 5,08 5,59 0,36 - 0, 0,

2680 0 5 4 0,7 0,47 0,13 11 0,32 0,71 30 1,42 0,83 16 7 4 8 4 7 0 0 3 - cg1328 0,07 4,01 0,98 0, 1,

2837 4 0 5 6,3 3,24 0,04 44 0,49 0,37 48 2,22 0,50 93 5 9 0 5 4 9 8 4 - - cg1669 4,89 5,17 0,34 0, 3,

6317 8 4 4 1,8 0,94 0,05 20 0,40 0,60 89 1,90 0,04 41 7 2 9 5 5 0 7 1 - cg1771 1,74 4,35 0,68 0, 0,

7124 6 1 8 0,3 3,53 0,91 05 0,47 0,91 79 2,18 0,71 74 4 6 3 2 0 1 3 7 - - cg1999 0,91 4,80 0,85 0, 2,

2633 1 2 0 0,8 1,79 0,65 04 0,39 0,90 89 1,89 0,12 09 0 2 9 4 2 9 5 6 - cg2311 8,93 6,09 0,14 0, 2,

4311 1 5 3 3,5 2,90 0,22 49 0,40 0,21 99 1,88 0,11 57 2 1 4 2 8 0 1 2 - cg2499 0,42 6,29 0,94 0, 0,

6565 9 4 6 2,9 2,25 0,19 39 0,51 0,43 56 2,24 0,80 27 9 6 9 3 7 8 3 0 - - cg2708 4,89 10,5 0,64 0, 2,

9768 0 87 4 3,8 3,45 0,26 59 0,50 0,23 13 2,29 0,35 41 1 6 2 0 7 2 6 3 - - - 89,023, 89,023, cg0243 3,30 0,71 0, - 0, 1, 16 1,20 389 634 1972 8 7 02 0,1 0,35 0,76 N.R 03 0,46 0,94 0,89 30 2,14 0,54 N.R 1 7 04 1 7 . 2 4 6 0 9 7 2 . - - cg0595 3,76 0,83 - 0, 2, 0,79 3373 2 2 0,3 0,47 0,40 07 0,50 0,88 66 2,33 0,25 8 95 8 9 3 7 5 2 3 4 - - - cg0873 5,63 0,94 - 0, 0, 0,37 2950 3 7 0,1 0,49 0,79 67 0,72 0,35 35 3,30 0,91 3 27 2 7 9 6 0 5 1 4 - - 44,897, 44,897, cg0081 7,69 0,26 N. 1, 9, 17 8,54 431 513 7598 0 6 R. 9,9 8,08 0,21 N.R 47 1,28 0,24 0,55 02 6,41 0,16 N.R 6 66 6 8 . 7 1 9 0 6 7 0 . - - cg2411 3,10 29,7 0,91 25, 0, 1,

4556 1 58 7 35 9,00 0,00 22 0,87 0,80 64 4,14 0,69 6 0 5 1 9 2 8 2 1 1, - - 40,759, 40,759, cg1597 2,33 0,41 75 0, 1, 21 1,88 534 695 7137 6 9 E- 0,7 0,62 0,23 N.R 00 0,27 0,97 0,99 54 1,33 0,24 N.R 9 03 46 1 0 . 8 2 8 0 2 8 9 . - 0, 1, cg1968 2,05 0,40 1,69 0,5 0,52 0,29 01 0,23 0,96 62 1,18 0,16 4207 9 9 8 51 3 3 0 8 6 1 0 9 - - cg1976 3,14 0,28 0, 1, 3,33 1502 3 8 0,3 0,98 0,69 01 0,32 0,96 70 1,57 0,28 7 88 3 3 3 3 8 2 8 1 - - cg2173 6,01 0,17 - 0, 0, 8,24 6411 6 0 0,1 1,87 0,92 00 0,36 0,98 61 1,76 0,72 9 76 6 5 8 9 4 4 3 7 - 0, 1, cg2711 1,55 0,17 2,08 0,5 0,43 0,19 03 0,19 0,84 01 0,97 0,29 9318 2 9 8 69 5 2 8 5 6 5 7 9

Results present CpGs located in identified differentially methylated regions (DMRs) at birth associated with childhood asthma, adolescent and adult lung function, and adult COPD. Start: Genetic location of the start of the differentially methylated region (DMR). End: Genetic location of the end of the DMR. CpG: CpG probes located in the DMR. Effect: effect estimate of the association of differential DNA-methylation if the CpG with the corresponding outcome. StdErr: standard error of the effect estimate. P.value: Stouffer-Liptak p-value from associations of CpGs with childhood asthma, adolescent and adult lung function and adult COPD. DMR: q-value derived from the DMRs identified with Comb-p. The p-values of neighboring CpGs in the discovery meta-analyses were adjusted for local correlation and adjusted for multiple testing using the False-Discovery-Rate correction. N.R.: Not reconstructed; some DMRs could not be reconstructed as the regions did not meet the criteria for identification (2 or more probes within 500 bases).

CpG: CpG probes located in the DMR. Effect: effect estimate of the association of differential DNA- methylation if the CpG with the corresponding outcome. StdErr: standard error of the effect estimate.

P.value: Stouffer-Liptak p-value from associations of CpGs with childhood asthma, adolescent and adult lung function and adult COPD. DMR: q-value derived from the DMRs identified with Comb-p.

The p-values of neighboring CpGs in the discovery meta-analyses were adjusted for local correlation and adjusted for multiple testing using the False-Discovery-Rate correction. N.R.: Not reconstructed; some DMRs could not be reconstructed as the regions did not meet the criteria for identification (2 or more probes within 500 bases).

Supplementary Table 7. Associations of Identified Differentially Methylated Regions with Gene

Expression in Childhood and Adulthood.

Molecular Expressed gene DMRs DMRs DMR Previously location of the in cord in s in associated with lung differentially blood periph perip development or methylated region and eral heral respiratory morbidity* (Chromosome: gene blood bloo start – end) express and d ion gene and in expre gene children ssion expr in essio childr n in en adult s FEV1 chr7: 27,183,133- HOXA1*, HOTTIP ↓ ↓ ↓ *Fetal lung 27,184,854 development, FEV1, 30 FEV1/FVC EVX1*, HOXA4**, ↓ ↓ *COPD 31; **Lung HOXA7 development 32, asthma 33, COPD 32 EVX1-AS, RP1- ↑ 170O19.17 chr10: SPRN ↑ ↑ ↓ 135,202,522- 135,203,201 RP11-122K13.7 ↓ chr1: 7,887,199- PER3¶, RP3- ↓ ↓ 7,887,561 467l1.4, RNA5SP23, RP4- 726F1.1 RNU6-1102P ↑ RP11-431K24.1 ↑ chr3: 195,489,708- MUC20* ↓ ↓ *Ciliated epithelial lung 195,490,310 cells 34 NCI_CGAP_Lu24 ↓ MIR570, SDHAP1, ↑ ↑ *Lung development35 PPP1R2* chr12: SIRT4 ↓ 120,763,487- 120,763,870 LINC1089, ↓ *Lung mast cell TMEM142A* mediator release 36, bronchoconstriction 37 COQ5 ↑ chr16: 88,803,803- APRT ↓ ↓ 88,804,052 TRAPPC2L ↓ LOC100129697 ↑ chr1: 47,915,553- RP11-511I2.2 ↑ 4,7915,952 chr1: 1,957,385- MIR3120, RP5- ↓ ↓ * Asthma, COPD 38 1,957,806 1114G22.2, SNORA77, RP3- 329E20.2, GAS5*, RP11-95P13.2

CAMSAP2, RNU6- ↓ 778P, TPR, RPS6KC1, RNU6- 773P, RP3-467L1.4 LOC100506801, ↑ IPO9-AS1, PADI4, CHI3L1, TMEM52, CDA, PPP1R11P1, PRDX6, RP11- 15I11.2 RNU6-307P, ↑ *Fetal lung PM20D1*, RP11- development, 30 160H22.3, RP11- FEV1/FVC ; **asthma 108M9.4, 39,40 TNFSF4**, FMO3, LINC01036, LOC101929541 chr1: 38,461,540- MIR3659, INPP5B ↓ ↓ 38,461,897 YRDC ↑ chr11: 843,897– AP2A2* ↑ ↑ *COPD, chronic 844,285 bronchitis 41 FEV1/ chr10: RP11-122K13.12, ↓ FVC 135,051,149- TUBGCP2 135,051,582 TUBGCP2 ↓ SPRN ↑ ↓ VENTX¶, ECHS1 ↑ ECHS1 ↑ ZNF511 ↑ chr5: 102,898,223- NUDT12¶, CMBL ↓ 102,898,734 NUDT12 ↓ chr2: 121,223,534- AC012363.13 ↓ ↓ 121,223,965 INHBB, LINC01101, ↑ ↑ AC073257.2 chr21: 40,759,534- BRWD1-IT2, ↓ 40,759,695 SH3BGR BRWD1-IT2 ↓ BRWD1*, BRWD1- ↑ *Fetal lung 30 AS1, HMGN1, development, FEV1 BRWD1-IT1 BRWD1-AS1 ↑ chr17: 19,314,299- AC099684.1 ↓ 19,314,619 SNORD3A, ↑ SNORD3C chr14: 96,180,406- CCDC85C, TCL1A¶ ↓ 96,181,045 TCL1A¶ ↓ chr6: 32,305,068- HCG23*, XXbac- ↓ *Asthma 42, **adult 32,305,146 BPG154L12.4, asthma 43 C6orf10¶, LOC285768, OFCC1 RNF5* ↓ *Cystic fibrosis 44

HLA-DRB4*, HLA- ↑ *Fetal lung DRB5** development 30 30 ** FEV1/FVC HLA-DRB4 ↑ TNXA ↑ chr11: 67,417,958- NUDT8, CABP2*, ↓ *Asthma 45 67,418,406 CABP4, C11orf72, ACY3¶ NUDT8, CABP2 ↓ AIP, NDUFV1, ↑ FAM86C2P, LOC729196 AIP ↑ chr6: 168,533,375- KIF25-AS1, DACT2, ↑ 168,533,690 KIF25, FRMD1¶ KIF25-AS1, DACT2 ↑ chr17: 79,485,529- HGS ↓ 79,485,710 OXLD1 ↑ chr13: 20,805,380 CRYL1 ↓ – 20,805,896 MRPL57, MRP63 ↑ chr11: 64,064,947 PRDX5* ↓ *Lung development 46, 47 – 64,065,372 COPD , FEV1 and 30,48 FEV1/FVC chr1: 1,564,422 – LOC728661 ↑ 1,564,921 ¶ FEF75 chr14: 96,180,406- CCDC85C, TCL1A ↓ 96,181,045 TCL1A ↓ chr6: 132,271,361- RP11-69I8.2 ↑ ↑ 132,271,589 chr16: 89,023,389- APRT, TRAPPC2L ↑ ↑ 89,023,634 30 chr6: 31,650,735- NEU1*, SNORA38, ↓ ↓ *FEV1/FVC 31,651,159 VWA7, LST1* CSNK2B*, ↓ *FEV1 and FEV1/FVC 30 30 HSPA1L**, ; **FEV1/FVC ABHD16A*, ↑ ↑ *Steroid use in COPD 49 30 LSM2**, ; ** FEV1/FVC ; *** ¶ 30 50 LY6G5C ***, FEV1 ; ****asthma PRRC2A**** BAG6 ↓ TSTD3 ↑ C6orf25 ↑ chr2: 54,086,854- ASB3*, PSME4 ↓ *Childhood asthma 51 54,087,553 ACYP2, ASB3 ↑ ACYP2 ↑ chr8: 142,377,303- RP11-10J21.3 ↓ 142,377,490 chr11: 67,417,958- NUDT8, CABP2*, ↓ *Bronchopulmonary 67,418,406 CABP4*, C11orf72* dysplasia 52 CABP2, NUDT8 ↓ AIP*, NDUFV1*, ↑ Bronchopulmonary FAM86C2P, ACY3¶ dysplasia 52

AIP ↑ CORO1B*, ↑ *Lung injury 53; ** T-cell TMEM134, mediated immune TCIRG1** response 54 chr1: 1,957,385- MIR3120, RP5- ↓ * Asthma, COPD 38 1,957,806 1114G22.2, SNORA77, RP3- 329E20.2, GAS5*, RP11-95P13.2 MIR3120, ↓ SNORA77, CAMSAP2, IL19, RP11-95P13.2, TGFB2, NBPF3, TPR RNU6-307P, ↑ LOC100506801, PTP4A1P7, LYPLAL1-AS1, IPO9-AS1, RNU6- 773P, DDOST, RP11-15I11.2, ANGPTL1, C4BPA, CAPZB, CHI3L1, PPP1R11P1, PRDX6, CDA, CYB5R1, RNA5SP71 RNU6-307P, ↑ *Fetal lung PM20D1*, RP11- development, 30 160H22.3, RP11- FEV1/FVC ; **asthma 108M9.4, 39,40 TNFSF4**, FMO3, LINC01036, LOC101929541, 55 chr1: 2,383,438- GJC2, LGALS8- ↓ *FEV1/FVC 2,383,688 AS1, OR2T27, MIR3115, C1QB, GALE, LOC100288175, LYPLAL1-AS1, C1orf35, MORN1, HMGCL, PGBD2, IBA57, ADCK3, CHRM3*, LINC01341, LEFTY1, OR2M3, PEX10, GNG4, RNA5SP78, EPHA8, CAPN9, LOC100129534, LOC339529 GJC2, LGALS8- ↓ AS1, GALE, MIR3115, C1orf35, RP11-275O4.3, RP11-527D7.1, MIR4684, C1QB, ADCK3, CHRM3, MORN1,

RNA5SP78, MARC1, HMGCL, LEFTY1, OR2T27, OR2M3 MIR320B2, ↑ LINC01347, NVL, KDM1A, RP11- 488L18.8, OR6F1, OR2L8, ZNF593 RER1 ↓ 30 NVL, KDM1A, ↑ *FEV1 MIR320B2, LINC01347, CLIC4*, LOC100287497, OR2L8, MIR4742, LINC01061 chr1: 17,634,543- PTP4A1P7 ↑ 17,634,717 ANGPTL1*, ↓ *Lung development 56 RABGAP1L chr6: 31,690,998- TSTD3 ↑ 31,691,540 chr21: 40,759,534- BRWD1-IT2, ↓ 40,759,695 HMGN1, SH3BGR BRWD1-IT2 ↓ 30 BRWD1*, BRWD1- ↑ *FEV1 AS1, BRWD1-IT1 BRWD1-AS1 ↑ chr11: 2,721,207- KCNQ1DN ↑ ↑ ↑ 2,721,633 KIF18A ↑ NAP1L4 ↓ chr5: 125,931,001 RNUXA ↓ – 125,931,363 chr17: 44,897,431 ABI3 ↓ – 44,897,513 Results present identified differentially methylated regions (DMRs) at birth associated with gene expression. * Association of expressed genes with lung development and respiratory morbidity were explored in previous published studies the OMIM database and UniProt. Gene expressions levels were assessed using the Illumina HumanHT12v4 Expression Beadchip limited to 250kb up- and downstream of the outer border of the DMR. The direction of associations of identified DMRs are marked ↓ if a higher mean methylation of the DMRs was associated with a lower expression of the gene, and ↑ if a higher mean methylation of the DMRs was associated with a higher expression of the gene.

Supplementary Table 8. Expression of Genes Related to Identified Differentially Methylated Regions

in Adult Lung Tissue.

Molecular location of the Gene differentially methylated region (Chromosome: start – end)

FEV1 chr1: 1,957,385 - 1,957,806 PADI4, CHI3L1, CDA, PM20D1, RP11-108M9.4, FMO3 chr1:17,222,405-17,222,716 CROCC* chr1:38,461,540-38,461,897 FHL3 *, INPP5B, YRDC chr3:195,489,708-195,490,310 MUC4*, MUC20, MIR570, SDHAP1 chr7:76,828,885-76,829,169 CCDC146* chr10: 135,202,522 - PAOX* 135,203,201 chr11:843,897-844,285 TSPAN4* chr12: 120,763,487 - SIRT4, COQ5 120,763,870 chr15:64,995,133-64,995,502 OAZ2* chr16: 88,803,803 - APRT, TRAPPC2L 88,804,052 chr19:1,063,624-1,064,219 ABCA7* * FEV1/FVC chr1:86,968,087-86,968,544 CLCA1 chr5:102,898,223-102,898,734 NUDT12*, CMBL chr6: 32,305,068 - 32,305,146 HCG23, HLA-DRB5 chr6: 168,533,375 - KIF25-AS1, KIF25 168,533,690 chr10: 135,051,149 - VENTX*, RP11-122K13.12, ECHS1 135,051,582 chr11: 64,064,947 – PRDX5 64,065,372 chr11: 67,417,958 - NUDT8, NDUFV1 67,418,406 chr17: 79,485,529 - OXLD1 79,485,710 chr21:40,759,534-40,759,695 WRB*, SH3BGR

FEF75 chr1: 1,957,385 - 1,957,806 NBPF3, C4BPA, CAPZB, CHI3L1, CDA, PM20D1, RP11-108M9.4, FMO3 chr1: 2,383,438 - 2,383,688 PLCH2*, MORN1, IBA57, ADCK3, LEFTY1, CAPN9, NVL, ZNF593 chr1: 17,634,543 - 17,634,717 PADI4*, RABGAP1L chr2: 54,086,854 - 54,087,553 GPR75*, PSME4, ACYP2 chr5:125,931,001-125,931,363 ALDH7A1* chr6: 31,650,735 - 31,651,159 LY6G5C*, LY6G5C, PRRC2A, BAG6 chr17:44,897,431-44,897,513 WNT3* chr21: 40,759,534 - WRB*, SH3BGR 40,759,695 Results present the expression of genes related to identified differentially methylated regions (DMRs)

in adult lung tissue in the Genotype-Tissue Expression (GTEx) database. All annotated and

differentially expressed genes were assessed. Molecular locations are based on human

GRCh37/hg19 assembly. *Nearest gene to DMR.

Supplementary Table 9a. Biological Processes Enriched by Genes Related with Identified

Differentially Methylated Regions Associated with Childhood FEV1.

Fold Co enrich Fisher Category Term unt % Genes ment Exact GOTERM_B GO:0003002~regionaliza 12 HOXA1; HOXA4; EVX1; 3·90E- P_FAT tion 5 ·8 HOXA5; HOXA7 12·7 05 MEF2C; HOXA1; TNFSF4; HOXA4; EVX1; GO:0006355~regulation HOXA5; HOXA7; SIRT4; GOTERM_B of transcription; DNA- 30 PLA2G1B; BRIP1; 6·40E- P_FAT dependent 12 ·8 PER3; FOXD2 3·4 05 MEF2C; HOXA1; TNFSF4; HOXA4; EVX1; GO:0051252~regulation HOXA5; HOXA7; SIRT4; GOTERM_B of RNA metabolic 30 PLA2G1B; BRIP1; 8·00E- P_FAT process 12 ·8 PER3; FOXD2 3·3 05 GOTERM_B GO:0048562~embryonic 10 HOXA1; HOXA4; 1·30E- P_FAT organ morphogenesis 4 ·3 HOXA5; HOXA7 15·1 04 GO:0032583~regulation GOTERM_B of gene-specific 10 MEF2C; TNFSF4; EVX1; 1·40E- P_FAT transcription 4 ·3 PLA2G1B 15·0 04 MEF2C; HOXA1; GOTERM_ GO:0043565~sequence- 17 HOXA4; EVX1; HOXA5; 1·40E- MF_FAT specific DNA binding 7 ·9 HOXA7; FOXD2 5·8 04 GOTERM_B GO:0007389~pattern 12 HOXA1; HOXA4; EVX1; 1·60E- P_FAT specification process 5 ·8 HOXA5; HOXA7 9·4 04 GOTERM_B GO:0009952~anterior/po 10 HOXA1; HOXA4; 1·60E- P_FAT sterior pattern formation 4 ·3 HOXA5; HOXA7 14·3 04 GO:0048704~embryonic GOTERM_B skeletal system 7· HOXA4; HOXA5; 1·90E- P_FAT morphogenesis 3 7 HOXA7 26·4 04 GOTERM_B GO:0048568~embryonic 10 HOXA1; HOXA4; 3·50E- P_FAT organ development 4 ·3 HOXA5; HOXA7 11·7 04 GO:0048706~embryonic GOTERM_B skeletal system 7· HOXA4; HOXA5; 4·70E- P_FAT development 3 7 HOXA7 19·5 04 GO:0045944~positive regulation of transcription GOTERM_B from RNA polymerase II 12 MEF2C; HOXA1; EVX1; 7·40E- P_FAT promoter 5 ·8 HOXA7; PLA2G1B 6·8 04 GO:0010551~regulation of specific transcription GOTERM_B from RNA polymerase II 7· MEF2C; EVX1; 8·40E- P_FAT promoter 3 7 PLA2G1B 16·0 04 GOTERM_B GO:0048705~skeletal 7· HOXA4; HOXA5; 1·40E- P_FAT system morphogenesis 3 7 HOXA7 13·4 03 GO:0045893~positive regulation of GOTERM_B transcription; DNA- 12 MEF2C; HOXA1; EVX1; 2·30E- P_FAT dependent 5 ·8 HOXA7; PLA2G1B 5·3 03 GO:0051254~positive GOTERM_B regulation of RNA 12 MEF2C; HOXA1; EVX1; 2·30E- P_FAT metabolic process 5 ·8 HOXA7; PLA2G1B 5·2 03 MEF2C; HOXA1; TNFSF4; HOXA4; EVX1; HOXA5; HOXA7; SIRT4; GOTERM_B GO:0045449~regulation 30 PLA2G1B; BRIP1; 2·40E- P_FAT of transcription 12 ·8 PER3; FOXD2 2·3 03

MEF2C; HOXA1; GOTERM_ GO:0003700~transcriptio 17 HOXA4; EVX1; HOXA5; 2·40E- MF_FAT n factor activity 7 ·9 HOXA7; FOXD2 3·6 03 GO:0006357~regulation MEF2C; HOXA1; EVX1; GOTERM_B of transcription from RNA 15 HOXA7; PLA2G1B; 2·60E- P_FAT polymerase II promoter 6 ·4 BRIP1 4·1 03 GOTERM_B GO:0048598~embryonic 10 HOXA1; HOXA4; 3·00E- P_FAT morphogenesis 4 ·3 HOXA5; HOXA7 6·5 03 GO:0050714~positive GOTERM_B regulation of protein 5· 3·00E- P_FAT secretion 2 1 TNFSF4; PLA2G1B 24·4 03 GOTERM_B GO:0001816~cytokine 5· 3·80E- P_FAT production 2 1 TNFSF4; PLA2G1B 21·8 03 GO:0016763~transferase GOTERM_ activity; transferring 5· 3·80E- MF_FAT pentosyl groups 2 1 SIRT4; APRT 21·7 03 GO:0010558~negative regulation of GOTERM_B macromolecule 12 MEF2C; TNFSF4; 4·10E- P_FAT biosynthetic process 5 ·8 HOXA7; SIRT4; EIF2B3 4·6 03 GO:0009792~embryonic GOTERM_B development ending in 10 HOXA4; EVX1; HOXA5; 4·10E- P_FAT birth or egg hatching 4 ·3 HOXA7 6·0 03 GO:0032582~negative GOTERM_B regulation of gene- 5· 4·10E- P_FAT specific transcription 2 1 MEF2C; TNFSF4 20·9 03 GO:0031327~negative GOTERM_B regulation of cellular 12 MEF2C; TNFSF4; 4·60E- P_FAT biosynthetic process 5 ·8 HOXA7; SIRT4; EIF2B3 4·5 03 GOTERM_B GO:0045941~positive 12 MEF2C; HOXA1; EVX1; 4·70E- P_FAT regulation of transcription 5 ·8 HOXA7; PLA2G1B 4·4 03 GO:0009890~negative GOTERM_B regulation of biosynthetic 12 MEF2C; TNFSF4; 5·00E- P_FAT process 5 ·8 HOXA7; SIRT4; EIF2B3 4·4 03 GO:0045892~negative regulation of GOTERM_B transcription; DNA- 10 MEF2C; TNFSF4; 5·10E- P_FAT dependent 4 ·3 HOXA7; SIRT4 5·6 03 GO:0010628~positive GOTERM_B regulation of gene 12 MEF2C; HOXA1; EVX1; 5·30E- P_FAT expression 5 ·8 HOXA7; PLA2G1B 4·3 03 GO:0051253~negative GOTERM_B regulation of RNA 10 MEF2C; TNFSF4; 5·40E- P_FAT metabolic process 4 ·3 HOXA7; SIRT4 5·5 03 GO:0045935~positive regulation of nucleobase; nucleoside; nucleotide GOTERM_B and nucleic acid 12 MEF2C; HOXA1; EVX1; 7·10E- P_FAT metabolic process 5 ·8 HOXA7; PLA2G1B 4·0 03 GOTERM_B GO:0051046~regulation 7· TNFSF4; SIRT4; 7·40E- P_FAT of secretion 3 7 PLA2G1B 7·4 03 GO:0051173~positive regulation of nitrogen GOTERM_B compound metabolic 12 MEF2C; HOXA1; EVX1; 8·10E- P_FAT process 5 ·8 HOXA7; PLA2G1B 3·9 03 GO:0010557~positive regulation of GOTERM_B macromolecule 12 MEF2C; HOXA1; EVX1; 8·70E- P_FAT biosynthetic process 5 ·8 HOXA7; PLA2G1B 3·8 03 GOTERM_B GO:0031328~positive 5 12 MEF2C; HOXA1; EVX1; 3·7 1·00E-

P_FAT regulation of cellular ·8 HOXA7; PLA2G1B 02 biosynthetic process GO:0009891~positive GOTERM_B regulation of biosynthetic 12 MEF2C; HOXA1; EVX1; 1·10E- P_FAT process 5 ·8 HOXA7; PLA2G1B 3·6 02 GOTERM_B GO:0016481~negative 10 MEF2C; TNFSF4; 1·20E- P_FAT regulation of transcription 4 ·3 HOXA7; SIRT4 4·4 02 GOTERM_B GO:0060341~regulation 7· TNFSF4; SIRT4; 1·30E- P_FAT of cellular localization 3 7 PLA2G1B 6·1 02 GO:0010605~negative regulation of GOTERM_B macromolecule metabolic 12 MEF2C; TNFSF4; 1·40E- P_FAT process 5 ·8 HOXA7; SIRT4; EIF2B3 3·4 02 GO:0010629~negative GOTERM_B regulation of gene 10 MEF2C; TNFSF4; 1·70E- P_FAT expression 4 ·3 HOXA7; SIRT4 4·0 02 GO:0045934~negative regulation of nucleobase; nucleoside; nucleotide GOTERM_B and nucleic acid 10 MEF2C; TNFSF4; 1·80E- P_FAT metabolic process 4 ·3 HOXA7; SIRT4 3·9 02 GO:0051172~negative regulation of nitrogen GOTERM_B compound metabolic 10 MEF2C; TNFSF4; 1·90E- P_FAT process 4 ·3 HOXA7; SIRT4 3·9 02 GO:0010604~positive regulation of GOTERM_B macromolecule metabolic 12 MEF2C; HOXA1; EVX1; 2·50E- P_FAT process 5 ·8 HOXA7; PLA2G1B 2·9 02 MEF2C; HOXA1; GOTERM_ GO:0030528~transcriptio 17 HOXA4; EVX1; HOXA5; 2·60E- MF_FAT n regulator activity 7 ·9 HOXA7; FOXD2 2·3 02 Results present biological pathways enriched for the identified genes. Pathways are based on the Gene Ontology database implemented in DAVID and GeneMania. MF-FAT: molecular function, CC- FAT: Cellular Component, BP-FAT: Biological Process. Count: number of genes enriching the respective Gene Ontology term. %: the % of the identified genes for all genes known for the respective Gene Ontology term. Fold Enrichment: the x-fold enrichment of the respective Gene Ontology term by identified genes. Fisher Exact: p-value for the enrichment of Gene Ontology terms by the identified genes.

Supplementary Table 9b. Biological Processes Enriched by Genes Related with Identified

Differentially Methylated Regions Associated with Childhood FEV1/FVC.

Fold Co Fisher Category Term % Genes enrich unt Exact ment GO:0002504~antigen processing and GOTERM_B 5· 1·10E- presentation of peptide or 2 HLA-DRB4; HLA-DRB5 41·0 P_FAT 3 03 polysaccharide antigen via MHC class II GOTERM_C GO:0042613~MHC class 5· 1·60E- 2 HLA-DRB4; HLA-DRB5 33·9 C_FAT II protein complex 3 03 RNF112; CLCA1; NUDT12; CABP2; ACY3; GOTERM_ GO:0046872~metal ion 31 2·30E- 12 MIB2; NDUFV1; NUDT8; 1·7 MF_FAT binding ·6 02 HGS; CABP4; CBFA2T3; KCNK4 RNF112; CLCA1; NUDT12; CABP2; ACY3; GOTERM_ GO:0043169~cation 31 2·50E- 12 MIB2; NDUFV1; NUDT8; 1·7 MF_FAT binding ·6 02 HGS; CABP4; CBFA2T3; KCNK4 RNF112; CLCA1; NUDT12; CABP2; ACY3; GOTERM_ 31 2·80E- GO:0043167~ion binding 12 MIB2; NDUFV1; NUDT8; 1·7 MF_FAT ·6 02 HGS; CABP4; CBFA2T3; KCNK4 Results present biological pathways enriched for the identified genes. Pathways are based on the Gene Ontology database implemented in DAVID and GeneMania. MF-FAT: molecular function, CC- FAT: Cellular Component, BP-FAT: Biological Process. Count: number of genes enriching the respective Gene Ontology term. %: the % of the identified genes for all genes known for the respective Gene Ontology term. Fold Enrichment: the x-fold enrichment of the respective Gene Ontology term by identified genes. Fisher Exact: p-value for the enrichment of Gene Ontology terms by the identified genes.

Supplementary Table 9c. Associations of Genes Related with Identified Differentially Methylated

Regions Associated with Childhood FEV1/FVC with Human Diseases.

Fold Co Fisher Category Term % Genes enrichm unt Exact ent KEGG_PA hsa05416:Viral ACTG1; HLA-DRB4; 2·90E- 3 7·9 21·5 THWAY myocarditis HLA-DRB5 04 KEGG_PA 1·40E- hsa05310:Asthma 2 5·3 HLA-DRB4; HLA-DRB5 35·1 THWAY 03 KEGG_PA hsa05330:Allograft 2·10E- 2 5·3 HLA-DRB4; HLA-DRB5 28·3 THWAY rejection 03 KEGG_PA hsa05332:Graft-versus- 2·50E- 2 5·3 HLA-DRB4; HLA-DRB5 26·1 THWAY host disease 03 KEGG_PA hsa04940:Type I diabetes 2·90E- 2 5·3 HLA-DRB4; HLA-DRB5 24·2 THWAY mellitus 03 hsa04672:Intestinal KEGG_PA 3·90E- immune network for IgA 2 5·3 HLA-DRB4; HLA-DRB5 20·8 THWAY 03 production KEGG_PA hsa05320:Autoimmune 4·20E- 2 5·3 HLA-DRB4; HLA-DRB5 19·9 THWAY thyroid disease 03 Results present the enrichment of KEGG-defined human diseases by the identified genes. Disease terms are based on the KEGG database implemented in DAVID and GeneMania. Count: number of genes enriching the respective Gene Ontology term. %: the % of the identified genes for all genes known for the respective Gene Ontology term. Fold Enrichment: the x-fold enrichment of the respective Gene Ontology term by identified genes. Fisher Exact: p-value for the enrichment of Gene Ontology terms by the identified genes.

Supplementary Table 9d. Biological Processes Enriched by Genes Related with Identified

Differentially Methylated Regions Associated with Childhood FEF75.

Fold Co Fisher Category Term % Genes enrich unt Exact ment GOTERM_ GO:0050662~coenzyme KDM1A; NDUFV1; 5 7·4 8·2 3·50E-04 MF_FAT binding FMO3; GALE; HMGCL GOTERM_ GO:0048037~cofactor KDM1A; NDUFV1; 5 7·4 5·9 1·50E-03 MF_FAT binding FMO3; GALE; HMGCL GOTERM_ GO:0005254~chloride 3 4·4 GABRD; CLCA1; CLIC4 12·3 1·80E-03 MF_FAT channel activity GOTERM_ GO:0031404~chloride 3 4·4 GABRD; CLCA1; CLIC4 11·5 2·20E-03 MF_FAT ion binding GOTERM_ GO:0005253~anion 3 4·4 GABRD; CLCA1; CLIC4 11·3 2·30E-03 MF_FAT channel activity GO:0004435~phosphoin GOTERM_ ositide phospholipase C 2 2·9 CHRM3; PLCH2 23·6 3·20E-03 MF_FAT activity GOTERM_ GO:0043168~anion 3 4·4 GABRD; CLCA1; CLIC4 9·6 3·70E-03 MF_FAT binding GOTERM_ GO:0004629~phospholip 2 2·9 CHRM3; PLCH2 19·0 4·90E-03 MF_FAT ase C activity GO:0032583~regulation GOTERM_B of gene-specific 3 4·4 KDM1A; TNFSF4; TBX5 6·9 9·40E-03 P_FAT transcription OR2L8; WNT3; CHRM3; OR2T27; GO:0007166~cell surface GOTERM_B 17· EPHA8; CTGF; GPR75; receptor linked signal 12 2·0 1·30E-02 P_FAT 6 ANGPTL1; GPR20; transduction GNG4; OR2M3; LEFTY1 GO:0008509~anion GOTERM_ transmembrane 3 4·4 GABRD; CLCA1; CLIC4 6·0 1·30E-02 MF_FAT transporter activity GO:0007167~enzyme GOTERM_B EPHA8; CTGF; linked receptor protein 4 5·9 3·6 2·50E-02 P_FAT ANGPTL1; LEFTY1 signaling pathway GABRD; OR2L8; TNFSF4; CLCA1; CABP2; GPR75; ACY3; PTPRN2; C6ORF25; GOTERM_C GO:0005886~plasma 30· 21 GJC2; OR2M3; CADPS; 1·5 2·50E-02 C_FAT membrane 9 CHRM3; OR2T27; EPHA8; CTGF; CLIC4; PLCH2; NEU1; GNG4; GPR20 CADPS; CLCA1; GOTERM_ GO:0005509~calcium ion 10· 7 CABP2; PLCH2; 2·2 3·40E-02 MF_FAT binding 3 CAPN9; CABP4; PADI4 GABRD; TNFSF4; CLCA1; CABP2; ACY3; GOTERM_C GO:0044459~plasma 19· GPR75; PTPRN2; 13 1·6 5·90E-02 C_FAT membrane part 1 GJC2; CADPS; CHRM3; EPHA8; GPR20; GNG4 Results present biological pathways enriched for the identified genes. Pathways are based on the Gene Ontology database implemented in DAVID and GeneMania. MF-FAT: molecular function, CC- FAT: Cellular Component, BP-FAT: Biological Process. Count: number of genes enriching the

respective Gene Ontology term. %: the % of the identified genes for all genes known for the respective Gene Ontology term. Fold Enrichment: the x-fold enrichment of the respective Gene Ontology term by identified genes. Fisher Exact: p-value for the enrichment of Gene Ontology terms by the identified genes.

Supplementary Figure 1a. Integrative pathway analysis of all genes annotated to DMRs associated with childhood FEV1.

Integrative pathway analysis of all genes annotated to DMRs associated with FEV1. Interpretation of line colours: purple: co-expression; pink: physical interaction; blue: co-localisation.

Supplementary Figure 1b. Integrative pathway analysis of all genes annotated to DMRs associated

with childhood FEV1/FVC.

Integrative pathway analysis of all genes annotated to DMRs associated with FEV1/FVC. Interpretation of line colours: purple: co-expression.

Supplementary Figure 1c. Integrative pathway analysis of all genes annotated to DMRs associated with childhood FEF75.

Integrative pathway analysis of all genes annotated to DMRs associated with FEF75. Interpretation of line colours: purple: co-expression; pink: physical interaction; blue: co-localisation; green: genetic interaction.

Supplementary Figure 2. Visualization of the Underlying Genomic Structure of the Top 10 Identified Differentially Methylated Regions Associated With Childhood Lung Function Outcomes.

Data were visualized using the Encyclopedia of DNA Elements (ENCODE) Consortium embedded in the Ensembl Genome browser. Results present the underlying genomic structure of the top 10 identified differentially methylated regions (DMRs) with childhood lung function. –Log10-transformed p- values of the CpGs located within the DMR are visualized. The presence of CpG Islands is shown, if applicable. Nearest genes and genomic variants (SNPs, Indels) are visualized. Regulatory elements are shown as defined in the specific figure legends. The DNA-methylation of a reference dataset of embryonic tissue (H1ESC WGBS) is shown.

chr7:27,183,133-27,184,854 (HOXA5)

chr10:135,202,522-135,203,201 (PAOX)

chr6:166,418,799-166,419,139 (LINC00602)

chr19:1,063,624-1,064,219 (ABCA7)

chr1:7,887,199-7,887,561 (PER3)

chr1:86,968,087-86,968,544 (CLCA1)

chr10:135,051,149-135,051,582 (VENTX)

chr5:102,898,223-102,898,734 (NUDT12)

chr7:158,045,980-158,046,359 (PTPRN2)

chr14:96,180,406-96,181,045 (TCL1A)

Supplementary Figure 3a. QQ-plot of Associations of CpGs with Childhood FEV1.

λ = 1·21

QQ-plot of the associations of DNA-methylation of CpGs at birth with childhood FEV1, adjusted for covariates and estimated cell counts. The–log10(p-values) are plotted by expected –log10(p-values). ʎ indicates the genomic inflation factor (lambda) for the model.

Supplementary Figure 3b. QQ-plot of Associations of CpGs with Childhood FEV1/FVC.

λ = 1·07

QQ-plot of the associations of DNA-methylation of CpGs at birth with childhood FEV1/FVC, adjusted for covariates and estimated cell counts. The –log10(p-values) are plotted by expected –log10(p- values). ʎ indicates the genomic inflation factor (lambda) for the model.

Supplementary figure 3c. QQ-plot of Associations of CpGs with Childhood FEF75.

λ = 1·11

QQ-plot of the associations of DNA-methylation of CpGs at birth with childhood FEF75, adjusted for covariates and estimated cell counts. The –log10(p-values) are plotted by expected –log10(p-values). ʎ indicates the genomic inflation factor (lambda) for the model.

REFERENCES

1. Boyd A, Golding J, Macleod J, et al. Cohort Profile: The 'Children of the 90s'-the index offspring of the Avon Longitudinal Study of Parents and Children. Int J Epidemiol 2013;42:111-27.

2. Fraser A, Macdonald-Wallis C, Tilling K, et al. Cohort Profile: The Avon Longitudinal Study of

Parents and Children: ALSPAC mothers cohort. Int J Epidemiol 2013;42:97-110.

3. Relton CL, Gaunt T, McArdle W, et al. Data Resource Profile: Accessible Resource for

Integrated Epigenomic Studies (ARIES). Int J Epidemiol 2015;44:1181-90.

4. Touleimat N, Tost J. Complete pipeline for Infinium((R)) Human Methylation 450K BeadChip data processing using subset quantile normalization for accurate DNA methylation estimation.

Epigenomics 2012;4:325-41.

5. Houseman EA, Accomando WP, Koestler DC, et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC bioinformatics 2012;13:86.

6. Miller MR, Hankinson J, Brusasco V, et al. Standardisation of spirometry. Eur Respir J

2005;26:319-38.

7. Kruithof CJ, Kooijman MN, van Duijn CM, et al. The Generation R Study: Biobank update

2015. Eur J Epidemiol 2014;29:911-27.

8. Pidsley R, CC YW, Volta M, Lunnon K, Mill J, Schalkwyk LC. A data-driven approach to preprocessing Illumina 450K methylation array data. BMC Genomics 2013;14:293.

9. Asher MI, Keil U, Anderson HR, et al. International Study of Asthma and Allergies in

Childhood (ISAAC): rationale and methods. Eur Respir J 1995;8:483-91.

10. Guxens M, Ballester F, Espada M, et al. Cohort Profile: the INMA--INfancia y Medio

Ambiente--(Environment and Childhood) Project. Int J Epidemiol 2012;41:930-40.

11. Aryee MJ, Jaffe AE, Corrada-Bravo H, et al. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics 2014;30:1363-9.

12. Chen YA, Lemire M, Choufani S, et al. Discovery of cross-reactive probes and polymorphic

CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics 2013;8:203-9.

13. McConnell R, Berhane K, Yao L, et al. Traffic, susceptibility, and childhood asthma. Environ

Health Perspect 2006;114:766-72.

14. Hukkinen M, Kaprio J, Broms U, et al. Heritability of lung function: a twin study among never- smoking elderly women. Twin Res Hum Genet 2011;14:401-7.

15. Palmer LJ, Knuiman MW, Divitini ML, et al. Familial aggregation and heritability of adult lung function: results from the Busselton Health Study. Eur Respir J 2001;17:696-702.

16. Ingebrigtsen TS, Thomsen SF, van der Sluis S, et al. Genetic influences on pulmonary function: a large sample twin study. Lung 2011;189:323-30.

17. Urman R, McConnell R, Islam T, et al. Associations of children's lung function with ambient air pollution: joint effects of regional and near-roadway pollutants. Thorax 2014;69:540-7.

18. Peters JM, Avol E, Navidi W, et al. A study of twelve Southern California communities with differing levels and types of air pollution. I. Prevalence of respiratory morbidity. Am J Respir Crit Care

Med 1999;159:760-7.

19. Oken E, Baccarelli AA, Gold DR, et al. Cohort Profile: Project Viva. Int J Epidemiol

2015;44:37-48.

20. Hofman A, Brusselle GG, Darwish Murad S, et al. The Rotterdam Study: 2016 objectives and design update. Eur J Epidemiol 2015;30:661-708.

21. Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 2010;26:2190-1.

22. Pedersen BS, Schwartz DA, Yang IV, Kechris KJ. Comb-p: software for combining, analyzing, grouping and correcting spatially correlated P-values. Bioinformatics 2012;28:2986-8.

23. Eckhardt F, Lewin J, Cortese R, et al. DNA methylation profiling of human chromosomes 6,

20 and 22. Nat Genet 2006;38:1378-85.

24. Huang W, Loganantharaj R, Schroeder B, Fargo D, Li L. PAVIS: a tool for Peak Annotation and Visualization. Bioinformatics 2013;29:3097-9.

25. Naeem H, Wong NC, Chatterton Z, et al. Reducing the risk of false discovery enabling identification of biologically significant genome-wide methylation status using the

HumanMethylation450 array. BMC Genomics 2014;15:51.

26. Sears MR, Greene JM, Willan AR, et al. A longitudinal, population-based, cohort study of childhood asthma followed to adulthood. N Engl J Med 2003;349:1414-22.

27. Vonk JM, Postma DS, Boezen HM, et al. Childhood factors associated with asthma remission after 30 year follow up. Thorax 2004;59:925-9.

28. Dai H, Leeder JS, Cui Y. A modified generalized Fisher method for combining probabilities from dependent tests. Front Genet 2014;5:32.

29. Carithers LJ, Ardlie K, Barcus M, et al. A Novel Approach to High-Quality Postmortem Tissue

Procurement: The GTEx Project. Biopreserv Biobank 2015;13:311-9.

30. Obeidat M, Hao K, Bosse Y, et al. Molecular mechanisms underlying variations in lung function: a systems genetics analysis. Lancet Respir Med 2015;3:782-95.

31. Rabinovich RA, Drost E, Manning JR, et al. Genome-wide mRNA expression profiling in vastus lateralis of COPD patients with low and normal fat free mass index and healthy controls.

Respir Res 2015;16:1.

32. Golpon HA, Geraci MW, Moore MD, et al. HOX genes in human lung: altered expression in primary pulmonary hypertension and emphysema. Am J Pathol 2001;158:955-66.

33. Kim YJ, Park SW, Kim TH, et al. Genome-wide methylation profiling of the bronchial mucosa of asthmatics: relationship to atopy. BMC Med Genet 2013;14:39.

34. Kesimer M, Ehre C, Burns KA, Davis CW, Sheehan JK, Pickles RJ. Molecular organization of the mucins and glycocalyx underlying mucus transport over mucosal surfaces of the airways. Mucosal

Immunol 2013;6:379-92.

35. Otulakowski G, Duan W, O'Brodovich H. Global and gene-specific translational regulation in rat lung development. Am J Respir Cell Mol Biol 2009;40:555-67.

36. Duffy SM, Ashmole I, Smallwood DT, Leyland ML, Bradding P. Orai/CRACM1 and KCa3.1 ion channels interact in the human lung mast cell plasma membrane. Cell Commun Signal 2015;13:32.

37. Peel SE, Liu B, Hall IP. ORAI and store-operated calcium influx in human airway smooth muscle cells. Am J Respir Cell Mol Biol 2008;38:744-9.

38. Keenan CR, Schuliga MJ, Stewart AG. Pro-inflammatory mediators increase levels of the noncoding RNA GAS5 in airway smooth muscle and epithelial cells. Can J Physiol Pharmacol

2015;93:203-6.

39. Di C, Lin X, Zhang Y, et al. Basophil-associated OX40 ligand participates in the initiation of

Th2 responses during airway inflammation. J Biol Chem 2015;290:12523-36.

40. Siddiqui S, Mistry V, Doe C, Stinson S, Foster M, Brightling C. Airway wall expression of

OX40/OX40L and interleukin-4 in asthma. Chest 2010;137:797-804.

41. Lee JH, Cho MH, Hersh CP, et al. Genetic susceptibility for chronic bronchitis in chronic obstructive pulmonary disease. Respir Res 2014;15:113.

42. Ortiz RA, Barnes KC. Genetics of allergic diseases. Immunol Allergy Clin North Am

2015;35:19-44.

43. Hirota T, Takahashi A, Kubo M, et al. Genome-wide association study identifies three new susceptibility loci for adult asthma in the Japanese population. Nat Genet 2011;43:893-6.

44. Tomati V, Sondo E, Armirotti A, et al. Genetic Inhibition Of The Ubiquitin Ligase Rnf5

Attenuates Phenotypes Associated To F508del Cystic Fibrosis Mutation. Sci Rep 2015;5:12138.

45. Kamada F, Mashimo Y, Inoue H, et al. The GSTP1 gene is a susceptibility gene for childhood asthma and the GSTM1 gene is a modifier of the GSTP1 gene. Int Arch Allergy Immunol

2007;144:275-86.

46. Chen L, Wilson R, Bennett E, Zosky GR. Identification of vitamin D sensitive pathways during lung development. Respir Res 2016;17:47.

47. Pastor MD, Nogal A, Molina-Pinelo S, et al. Identification of proteomic signatures associated with lung cancer and COPD. J Proteomics 2013;89:227-37.

48. Bentley AR, Kritchevsky SB, Harris TB, et al. Genetic variation in antioxidant enzymes and lung function. Free Radic Biol Med 2012;52:1577-83.

49. Wan ES, Qiu W, Baccarelli A, et al. Systemic steroid exposure is associated with differential methylation in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2012;186:1248-55.

50. Migita O, Noguchi E, Koga M, et al. Haplotype analysis of a 100 kb region spanning TNF-LTA identifies a polymorphism in the LTA promoter region that is associated with atopic asthma susceptibility in Japan. Clin Exp Allergy 2005;35:790-6.

51. Israel E, Lasky-Su J, Markezich A, et al. Genome-wide association study of short-acting beta2-agonists. A novel genome-wide significant locus on chromosome 2 near ASB3. Am J Respir

Crit Care Med 2015;191:530-7.

52. Ahmad A, Bhattacharya S, Sridhar A, Iqbal AM, Mariani TJ. Recurrent copy number variants associated with bronchopulmonary dysplasia. Pediatr Res 2016.

53. Hu P, Wang X, Haitsma JJ, et al. Microarray meta-analysis identifies acute lung injury biomarkers in donor lungs that predict development of primary graft failure in recipients. PLoS One

2012;7:e45506.

54. Smirnova AS, Morgun A, Shulzhenko N, Silva ID, Gerbase-DeLima M. Identification of new alternative splice events in the TCIRG1 gene in different human tissues. Biochem Biophys Res

Commun 2005;330:943-9.

55. Wilk JB, Walter RE, Laramie JM, Gottlieb DJ, O'Connor GT. Framingham Heart Study genome-wide association: results for pulmonary function measures. BMC Med Genet 2007;8 Suppl

1:S8.

56. Lai DM, Tu YK, Hsieh YH, et al. Angiopoietin-like protein 1 expression is related to intermuscular connective tissue and cartilage development. Dev Dyn 2007;236:2643-52.