Biomarker Characteristics in Asthma Subpopulations and Their Role in Pharmacological Studies

BIOMARKER CHARACTERISTICS IN ASTHMA SUBPOPULATIONS AND THEIR ROLE IN PHARMACOLOGICAL STUDIES

A thesis submitted to the University of Manchester for the degree of Doctor of Medicine in the Faculty of Biology, Medicine and Health

2018

Jethin Rafique

School of Medical Sciences

Table of Contents DECLARATION...... 5 PREFACE ...... 6 ABOUT THE AUTHOR ...... 7 ACKNOWLEDGEMENTS ...... 7 List of Tables ...... 8 List of Figures ...... 9 List of Abbreviations ...... 12 CHAPTER 1: INTRODUCTION – ASTHMA OVERVIEW ...... 15 Disease Pathobiology ...... 16 1.1 Theories of origin…………………………………………………………………………………………………...... 16 1.2 Asthma Immunology and Pathobiology………………………………………………………….……… ...... 17 1.2.1 The Innate and Adaptive Immune Response ...... 17 1.2.2 Antigen detection and recognition ...... 20 1.2.3 T2 High and T2 Low (non-T2) response ...... 22 1.2.4 Epithelial Derived Cytokines in Asthma (Alarmins) ...... 26 1.2.5 Key cells involved the asthmatic response ...... 31 1.3 Phenotypes and Endotypes…………………………………………………………………………………… ...... 35 1.4 CORTICOSTEROID NAÏVE ASTHMA………………………………………………………………………...... 43 1.4.1 Reproducibility ...... 45 1.5 NEUTROPHILIC ASTHMA…………………………………………………………………………………..………. 47 1.5.1 Neutrophil Biology ...... 47 1.5.2 Mediators of Neutrophil Inflammation ...... 49 1.5.3 Airway Microbiome and Neutrophilic Asthma ...... 52 1.5.4 Do neutrophils play a role in asthma disease processes? ...... 52 1.5.5 Pharmacotherapy for Neutrophil Asthma ...... 55 1.6 THE ANTICHOLINERGIC RESPONSE IN ASTHMA AND IDENTIFYING THE “RESPONDERS”…………………………………………………………………………………………….……… ...... 57 1.6.1 Physiology of bronchoconstriction and bronchodilation ...... 57 1.6.2 The mechanism of bronchoconstriction ...... 58 1.6.3 The mechanism of bronchodilation ...... 59 1.6.4 Use of anticholinergic agents in asthma ...... 60 1.7 FUTURE OF ASTHMA MANAGEMENT AND SCOPE OF THIS THESIS…………………..…… ...... 62 CHAPTER 2 - AIMS AND HYPOTHESES ...... 65 2.1 Corticosteroid Naïve Asthma………………………………………………………………………………… ...... 65 2.2 Neutrophils in Asthma…………………………………………………………………………………………...... 66 2.3 Anticholinergic response in asthma……………………………………………………………….……… ...... 67 CHAPTER 3 - METHODS ...... 68 3.1 Subjects………………………………………………………………………………………………………..……… ...... 68 3.2 Study Design………………………………………………………………………………………………..………...... 69 3.3 Study Procedures/Measurements……………………………………………………………….………… ...... 70 3.3.1 Asthma Control Questionnaire - 7 ...... 70 3.3.2 Asthma Control Test ...... 71 3.3.3 Fraction of Exhaled Nitric Oxide (FeNO) ...... 71 3.3.4 Lung Clearance Index ...... 72 3.3.5 Impulse Oscillometry ...... 73 3.3.6 Body Plethysmography ...... 75 3.3.7 Spirometry and Bronchodilator Reversibility ...... 76 3.3.8 Methacholine Challenge (Bronchial Hyperreactivity –BHR) ...... 77

2 3.3.9 Sputum Induction...... 79 3.3.10 Sputum Processing and Cytospin Differential Cell Count ...... 79 3.3.11 Peripheral Blood Sampling ...... 80 CHAPTER 4 – CHARACTERISTICS AND BIOMARKER REPRODUCIBILITY IN CORTICOSTEROID NAÏVE ASTHMA ...... 81 4.1 Introduction………………………………………………………………………………………………..………...... 81 4.2 Methods………………………………………………………………………………………………………………...... 82 4.2.1 Subjects and Study design ...... 82 4.2.2 Statistical analysis ...... 84 4.3 Results…………………………………………………………………………………………………………..……...... 84 4.4 Discussion…………………………………………………………………………………………………..………...... 96 CHAPTER 5 – EXPLORING THE CHARACTERISTICS AND LONG TERM REPRODUCIBILITY OF INCREASED SPUTUM NEUTROPHILS IN ASTHMA .. 102 5.1 Introduction……………………………………………………………………………………………..…………...... 102 5.2 Methods………………………………………………………………………………………………………………...... 104 5.2.1 Study subjects and study design ...... 104 5.2.2 Statistical analysis ...... 105 5.3 Results………………………………………………………………………………………………………..………...... 106 5.4 Discussion……………………………………………………………………………………………………..……...... 109 CHAPTER 6 – THE ROLE OF ANTICHOLINERGIC THERAPEUTIC AGENTS IN ASTHMA AND EXPLORING THE CHARACTERISTICS OF THE “RESPONDERS” ...... 114 6.1 Introduction…………………………………………………………………………………………………………. .... 114 6.2 Methods………………………………………………………………………………………………………………...... 117 6.2.1 Study subjects and study design ...... 117 6.2.2 Statistical analysis ...... 119 6.3 Results………………………………………………………………………………………………..………………...... 119 6.3 Discussion…………………………………………………………………………………………..………………...... 123 CHAPTER 7 – KEY FINDINGS AND OVERARCHING CONCLUSIONS FOR THE FUTURE ...... 128 7.1 Study 1 - Characteristics and biomarker reproducibility in corticosteroid naïve asthma………………………………………………………………………………………………………..………...... 129 7.1.1 Key findings: ...... 129 7.2 Study 2 - Assessing the long term reproducibility of raised sputum neutrophils in asthma and exploring their characteristics……………………………………………………….…… ..... 131 7.2.1 Key findings: ...... 132 7.3 Study 3 - The role of anticholinergic therapeutic agents in asthma and exploring the characteristics of the “responders”…………………………………………………………….………………...... 133 7.3.1 Key findings: ...... 133 7.5 Overarching conclusions – putting it all together for the future………………………….…...... 134 REFERENCES: ...... 138 Appendix 1 – Publication ...... 156 Appendix 2 – ACQ- 7 Questionnaire ...... 157 Appendix 3 – ACT Questionnaire ...... 158 Appendix 4 – Sputum processing worksheet ...... 159

ABSTRACT

A thesis submitted by Jethin Rafique for the degree of Doctor of Medicine in the Faculty of Medical and Human Sciences (University of Manchester)

BIOMARKER CHARACTERISTICS IN ASTHMA SUBPOPULATIONS AND THEIR ROLE IN PHARMACOLOGICAL STUDIES (Submitted: July 2018)

INTRODUCTION: Asthma is a very heterogeneous disease characterised by chronic airway inflammation and bronchial hyper-responsiveness. As the knowledge of the characteristics and inflammatory pathways of different subpopulations within asthma increase, biomarkers which are reliable, stable and reproducible are needed to identify target populations for “personalised treatments”, track drug effect in clinical drug trials and monitor disease activity over a period of time. With new emerging targeted therapeutic agents being developed, they are initially tested in early small clinical trial in patients with mild disease (usually in the corticosteroid naïve asthma subpopulation). Biomarkers for asthma related to neutrophil inflammation (so-called neutrophilic phenotype) and for subgroup of patients who respond to anticholinergic agents need to be studied.

AIMS: (1) To study the reproducibility of physiological measurements, sputum/blood eosinophil and neutrophil cell counts and characterise the corticosteroid naïve asthma population. (2) To study the characteristics and long term reproducibility of sputum neutrophils in patients with asthma who have raised/high sputum neutrophils count. (3) To assess whether a short acting β2 agonist (salbutamol) is more effective than a short acting anticholinergic (ipratropium) and identify similar characteristics/biomarkers of those who are “responders” to an anticholinergic agent (ipratropium).

METHODS: 30 patients who were corticosteroid naïve were screened. Their symptom scores, airway physiology, FeNO, lung clearance index (LCI), bronchial hyper-responsiveness and sputum/blood differential counts were all measured. A reproducibility visit took place within one month. 19 patients with a historic sputum neutrophil% count of ≥ 50% were recruited. Lung physiology including plethysmography and impulse oscillometry, FeNO, LCI and sputum differential counts were measured. Lastly 38 patients with asthma of varying severities were screened. Their physiological measurements and sputum cell counts were assessed. Reversibility testing to 400μg of salbutamol was done. Within on week, patients came back for measuring reversibility to 80μg of ipratropium.

RESULTS AND CONCLUSIONS: (1) Symptom scores, most physiological measurements, FeNO and sputum eosinophils show excellent reproducibility in corticosteroid naïve asthma. Measurements could be used as potential biomarkers or endpoints in clinical trials. (2) Long term reproducibility of sputum neutrophil is poor and raises the question as to whether sputum neutrophils can be used as a stable long term marker of disease activity. (3) Salbutamol is more effective than ipratropium as a bronchodilator in asthma. Increased symptoms (more severe disease) and raised sputum eosinophils may be a marker for those who are anticholinergic “responders” and warrants further study in the future.

4 DECLARATION

No portion of the work referred to in the thesis has been submitted in support of an application for another degree or qualification of this or any other university or other institute of learning.

(i) The author of this thesis (including any appendices and/or schedules to this thesis) owns certain copyright or related rights in it (the “Copyright”) and he has given The University of Manchester certain rights to use such Copyright, including for administrative purposes.

(ii) Copies of this thesis, either in full or in extracts and whether in hard or electronic copy, may be made only in accordance with the Copyright, Designs and Patents Act 1988 (as amended) and regulations issued under it or, where appropriate, in accordance with licensing agreements which the University has from time to time. This page must form part of any such copies made.

(iii) The ownership of certain Copyright, patents, designs, trade marks and other intellectual property (the “Intellectual Property”) and any reproductions of copyright works in the thesis, for example graphs and tables (“Reproductions”), which may be described in this thesis, may not be owned by the author and may be owned by third parties. Such Intellectual Property and Reproductions cannot and must not be made available for use without the prior written permission of the owner(s) of the relevant Intellectual Property and/or Reproductions.

(iv) Further information on the conditions under which disclosure, publication and commercialisation of this thesis, the Copyright and any Intellectual Property and/or Reproductions described in it may take place is available in the University IP Policy (see http://documents.manchester.ac.uk/DocuInfo.aspx?DocID=24420), in any relevant Thesis restriction declarations deposited in the University Library, The University Library’s regulations (see http://www.library.manchester.ac.uk/about/regulations/) and in The University’s policy on presentation of Theses.

5 PREFACE

The experiments in this thesis were developed by me, under the supervision of Professor Singh. To recruit the patients for these studies, a search was performed on the Medicines Evaluation Unit volunteer database to identify asthma patients that could potentially be used in the study. The patients were then contacted by phone or post to explain about the studies. I screened the majority of the patients involved in these studies which included performing lung function measurements and the collection and processing of all biological (sputum and blood) samples. However, I did receive help from my colleagues at the Medicines Evaluation Unit in collecting a small proportion of this data. Finally, I was fully responsible for the statistical analysis and the interpretation of all the data from the experimental chapters.

ABOUT THE AUTHOR

Dr. Jethin Rafique is currently a Consultant Respiratory Physician at the Royal Bolton Hospital in the Greater Manchester region of the United Kingdom. The research work that was undertaken and presented in this thesis was done when he was in the latter years of specialist training in Respiratory Medicine.

ACKNOWLEDGEMENTS

Without the help and support of the following people, this thesis would not have been possible. I would like to thank:

Professor Dave Singh (supervisor) for giving me the encouragement, teaching and patience in completing this thesis.

Dr. Thomas Southworth (co-supervisor) and Dr. Alex Horsley (advisor) for their knowledge and timely advice whenever I needed it.

My colleagues at the Medicines Evaluation Unit. In particular, I would like to say sincere thanks to Naimat Khan, Arjun Ravi, Pradeep Karur, Litza Mackenzie and Fred Reid.

The Academic Team and in particular to Alan Bell, Natalie Jackson, Sophie Wolosianka, Phil Lawrence, Paul Hitchen , Umme Kolsum and Kate Ahern.

Phil Foden, statistician, University of Manchester.

My patients and study subjects without whom none of this work would have happened.

To my mother and father who have always encouraged me to persevere, work hard and strive towards excellence.

And finally, to Amal, my wife and my two little children, Eshan and Hannah who have unwaveringly supported me and put up with my long hours away from the family.

7 List of Tables

Chapter 1

Table 1.1 Effects of epithelial derived alarmin blockade…………………………………..29

Table 1.2 Effects of eosinophils on other leukocytes……………………………………....34

Table 1.3 Examples of phenotypes based on different classifications……………………..37

Table 1.4 Studies looking at sputum eosinophil and neutrophil reproducibility…...……...40

Table 1.5 Studies assessing the link between IL-17 and neutrophils……………………...51

Table 1.6 The bronchoconstrictor mediators………………………………………………58

Table 1.7 The bronchodilator mediators……………………………...…………….……..58

Table 1.8 Studies looking at evaluating the effect of anticholinergics in asthma in the non- acute setting………………………………………………………...…………..62

Chapter 3 Table 3.1 Generic inclusion criteria for the 3 studies in this thesis……………………….68

Chapter 4 Table 4.1 Baseline characteristics of asthmatic patients who were corticosteroid naïve..85

Table 4.2 Reproducibility of measurements in corticosteroid naïve asthma…………….86

Table 4.3 Differences between symptom controlled group (ACQ-7 <1) and suboptimal control group (ACQ -7 ≥1) …………………………………..……………..….95

Table 4.4 Differences between “high eosinophil” group (sputum eosinophil% ≥ 3%) and “low eosinophil” group (sputum eosinophil% < 3%)………..………….……96

Chapter 5

Table 5.1 Baseline characteristics of study subjects……………………………………106

Table 5.2 Mean difference, within subject standard deviation and ICC for sputum reproducibility between historical visit and current study visit………………108

8 Table 5.3 Association of symptom scores & airway physiology with sputum neutrophil%.108

Chapter 6

Table 6.1 Baseline Characteristics…………………………………………………………120

Table 6.2 Reversibility to Salbutamol and Ipratropium in all subjects and in subgroups....120

Table 6.3 Anticholinergic “responder” vs. “non-responder”…………...…………………123

Chapter 7

Table 7.1 New drug deliveries in specialties……………..………………………………..136

List of Figures

Chapter 1

Fig. 1.1 Interactions between pathogen, innate and adaptive immune systems……..18

Fig. 1.2 Two arms of adaptive immunity…………………………………………….19

Fig. 1.3 Detection of PAMP by TLR and downstream signaling process resulting in the release of inflammatory cytokines and chemokines………………………….21

Fig. 1.4 Inflammatory pathways in allergic eosinophilic, non-allergic eosinophilic and noneosinophilic asthma………………………………………………………..…..30

Fig. 1.5 Sputum Eosinophilia and Sputum Neutrophilia……………………………...39

Fig. 1.6 Paucigranulocytic sputum and mixed cellular sputum…………….…………39

Fig. 1.7 Traditional phenotyping according to clinical features and inflammatory patterns overlap and the evolution towards mechanistic mapping (endotyping)…..…..41

Fig. 1.8 Effect of corticosteroids in the lung and airways…………………………..…44

Fig. 1.9 Structure of Neutrophil…………………………………………………..……49

Fig. 1.10 Airway smooth muscle responses to stimulation from airway epithelium…....57

9 Fig. 1.11 Novel therapeutic agents and their sites of action…………………………….63

Chapter 3

Fig. 3.1 Patient recruitment overview………………………………………………..70

Fig. 3.2 Colleague demonstrating the use of Niox Vero at a flow rate of 50mls/sec ..……………………………………………………………………………….72

Fig. 3.3 LCI Apparatus………………………………………………………………..73

Fig. 3.4 Colleague demonstrating the use of impulse oscillometry…………………...74

Fig. 3.5 Colleague demonstrating the use of body plethysmography…………………76

Fig. 3.6 DeVilbiss Nebuliser Pot…………………………………………………...….76

Chapter 4

Fig. 4.1 Consort diagram demonstrating the steps of the study……………………….83

Fig 4.2 Study design………………………………………………………………..…83

Fig. 4.3 Induced sputum cell distribution at baseline screening visit………………….85

Fig. 4.4 Bland-Altman Plot of the agreement between visits of ACQ-7 and ACT. ………..…...87 Fig. 4.5 Bland-Altman Plot of the agreement between visits of FEV1% and Reversibility% ….…………………………………………………………..…88

Fig. 4.6 Bland-Altman Plot of the agreement between visits of LCI and FeNO …….89

Fig. 4.7 Bland-Altman Plot of the agreement between visits of Sputum Neutrophil (106/g) and Sputum Neutrophil % …………………………………………………..…90

Fig. 4.8 Bland-Altman Plot of the agreement between visits of Sputum Eosinophil (106/g) and Sputum Eosinophil % ……...………………………………………………91

Fig. 4.9 Bland-Altman Plot of the agreement between visits of FEV1% and Reversibility% …………………………………….……………………...……92

Fig. 4.10 Sputum and blood eosinophil correlations………………………….…………93

Fig. 4.11 ACQ correlations………………………………………………………...…....94

10 Fig. 4.12 LCI correlations with airway physiology …………………….…….………...94

Chapter 5

Fig. 5.1 Study design………………………………………………………..………..105

Fig. 5.2 Bland-Altman Plot of the agreement between visits……………………...…107

Chapter 6

Fig. 6.1 Study consort diagram………………………………………………………..118

Fig. 6.2 Study design……………………………………………………………….….119

Fig. 6.3 Reversibility in all study subjects…………………………………………..…121

Fig. 6.4 Reversibility in corticosteroid naïve asthma and in subjects taking inhaled corticosteroids +/- long acting β2 agonist (ICS +/-LABA……………….……122

11 List of Abbreviations

A Ach Acetylcholine ACQ Asthma Control Questionnaire ACT Asthma Control Test APC Antigen Presenting Cell AQLQ Asthma Quality of Life Questionnaire ASM Airway smooth muscle ATS American Thoracic Society

BEC Bronchial epithelial cell BHR Bronchial hyper-reactivity

CLCA 1 Calcium activated chloride channel 1 CLC Charcot Leydon crystal

DTT Dithiothreitol

ECP Eosinophil cationic protein EDN Eosinophil derived neurotoxin ENFUMOSA European Network for Understanding Mechanisms of Asthma EPO Eosinophil peroxidase ERS European Respiratory Society

FeNO Fraction of exhaled nitric oxide FEV1 Forced Expiratory Volume in 1 second FRC Functional residual capacity

GINA Global Initiative for Asthma

IgM Immunoglobulin M IFN Interferon

12 ILC Innate lymphoid cell IOS Impulse Oscillometry IP3 Inositol Triphosphate IRF Interferon releasing factor

LCI Lung clearance index LPS Lipopolysaccharide

MAC Membrane Attack Complex MBP Major basic protein MBW Multiple breath washout MEU Medicines Evaluation Unit MHC Major histocompatibility complex MPO Myeloperoxidase MMP Metalloproteinase

NF-κB Nuclear Factor Kappa Light Chain Enhancer NOD Nucleotide-binding Oligmerisation Domain

PBS Phospate buffered solution PAMP Pathogen associated molecular pattern PRR Pathogen Recognition Receptor

Raw Airway resistance REC Respiratory Epithelial Cell ROR γ T Retinoic acid related orphan receptor RV Residual volume

SARP Severe Asthma Research Programme SD Standard deviation

TGF Tumor growth factor TH2 T Helper 2 Cell TIM -1 T-cell immunoglobulin and mucin TNF Tumor necrosis factor

13 TLC Total lung capacity TLR Toll like receptor TSLP Thymic stromal lymphopoetin

VC Vital Capacity VCAM Vascular adhesion molecule

CHAPTER 1: INTRODUCTION – ASTHMA OVERVIEW

Asthma is a heterogenic chronic inflammatory disorder of the airways with variable airflow obstruction and bronchial hyper responsiveness affecting children and adults [1, 2]. It is now an accepted cause of significant morbidity, mortality and preventable deaths [3]. The symptoms of cough, breathlessness and wheeze as a result of reversible airway obstruction lead to considerable healthcare burden. In the United Kingdom, at a cost of £ 1 billion annually, approximately 5.4 million adults suffer from asthma with an average of three patients dying every 24 hours [4] from a severe attack. On a global scale, asthma affects over

300 million individuals of all ages and places a huge drain on health economics and national productivity [5]. There have been great advances over the last few decades in scientific knowledge and in depth understanding of the mechanistic pathways that underpin the disease process in asthma. One of the major advances was the recognition of the presence of distinct subpopulations or phenotypes within asthmatics which can be characterised by common clinical or biomarker related features [6]. Further understanding of underlying molecular pathways [7] have resulted in the categorising patients suffering with asthma into subgroups based on their molecular biology called endotypes [8] which has also allowed the identification of new therapeutic targets and novel drugs [9] currently being tested in clinical drug trials. This thesis will focus on studying some of these subpopulations of asthmatics, their characteristics and relationships with common biomarkers which in the future could be incorporated into asthma related clinical drug trials and drug development.

15 1. Disease Pathobiology

1.1 Theories of origin

It is thought that the origin of the asthma lies in interactions between genetic factors and environmental stimuli [10]. The incidence of asthma has been increasing in the developed world and is postulated to be due to urbanisation resulting in less exposure to allergens and pathogens in children [11]. Ege et al. [12-14] have demonstrated children growing on farms and leading an anthroposophic lifestyle had a lower prevalence of asthma. Further more, other epidemiological studies [15] have shown that populations who are exposed to higher bacterial loads have substantially lower cases of asthma and atopy. The “Hygiene

Hypothesis” [16] proposes that inadequate microbial exposure in childhood results in delayed immune maturity and leads to an “allergic march” which corresponds to paediatric allergy driven disorders including eczema, food and environmental allergies and of more relevance – allergy-associated asthma. Over the last 25 years, this theory has evolved and epidemiological and translational research work by many teams including Gereda et al. [17],

Gehring et al. [18] as well as others [19-22] have increased the knowledge and strengthened the evidence around this concept. Work by Eder et al. [23] has shown exposure to the bacterial antigen lipopolysaccharide (LPS) in children with in the first six months of life correlates with a reduced incidence of asthma.

Other theories surrounding the origins of asthma (but less well understood) include genetic polymorphisms related to cytokine dysregulation and allergen induced impaired macrophage function resulting in the loss of the suppressive effects it normally has on lymphocytes [10].

Other genetic susceptibilities have been identified. The chromosomal region containing the

Adam33 gene [24-29], expressed in bronchial smooth muscle cells and codes for the proteins

16 disintegrin and metalloprotease, has been associated with the development of intrinsic airway hyper-responsiveness and increased IgE titres which is the key mediator is allergic responses.

Furthermore, another asthma susceptibility gene TIM-1 (T-cell immunoglobulin and mucin domain) [30-34] which encodes membrane proteins in CD4 T cells has been shown to have a role in responses that regulate the development of allergy driven diseases including asthma.

1.2 Asthma Immunology and Pathobiology

1.2.1 The Innate and Adaptive Immune Response

The biology of asthma involves responses from both the innate and adaptive immune (Fig.

1.1) systems [35]. The innate immune system is complex but is the primal host defense against microbial infection and other external pathogens [36]. It provides an immediate response to stimulation by an antigen and unlike the adaptive system, deficiencies in the innate shield can be catastrophic. The key feature of components of the innate system is the presence of fundamental evolutionary receptors on cell surface which recognise external pathogenic proteins. These receptors include pathogen recognition receptors (PRR) and toll- like receptors (TLR) [37-39] as described in later sections. The main cells involved include different leukocytes including macrophages, dendritic cells, natural killer cells, eosinophils, basophils, neutrophils and mast cells [36]. The complement system, consisting of more than

30 blood and tissue proteins, is also a significant component of innate immunity. Through a network system of opsonisation, chemotaxis, activation of leukocytes and direct cell lysis

[40], it provides an instant response to foreign antigen invasion. Following exposure to a trigger, a cascade of complement protein activation (C3 – C5b) occurs which results in phagocytosis or the formation of a membrane attack complex (MAC) which leads to cell destruction and lysis [40].

Fig. 1.1 showing the interactions between pathogen, innate and adaptive immune systems. In asthma, the clinical symptoms are due to exaggerated response to both mechanisms working together.

The adaptive immune response involving the T cell and B cell lymphocytes is the second line of defense seen in vertebrates in addition to the basic first line innate defense mechanisms

[41]. It provides long term memory of pathogens and thereby, continuous protection. The adaptive response commences when a pathogen is exposed to an antigen presenting cell

(APC) (eg. dendritic cell). These “activated” dendritic cells play a key role in initiating both the innate and adaptive systems [42]. However, the innate immune response is depended on germ-line encoded receptors to identify pathogens which do not evolve or develop over time.

Organisms such as encapsulated bacteria and viruses who either mask their surface proteins or do not have such protein matrixes are rarely identified by APCs. While they can still be ingested through macropinocytosis [43], the ability to efficiently clear the large amounts of pathogens of different varieties is constrained. Using a two pronged approach (Fig. 1.2), the adaptive system allows for the T cell differentiation for specific functions. These include cell destruction as well as the release of targeted cytokines and chemokines as well as clonal expansion of B cells which carry receptors for selective antigens as described in the

18 MacFarlane Burnet theory [44]. This theory, along with James Gowan’s [45] finding that removal of lymphocytes lead to the loss of adaptive immunity lead to the understanding that any antibody can be selectively produced against practically any antigen. Once sensitised and subsequent antibodies produced in large quantities during first exposure, the adaptive immunity provides “memory” against that particular antigen.

In asthma, dysfunction and over expression of the innate and adaptive immune responses [35,

46-48] have been closely linked with the development of the disease and its clinical manifestations of bronchial hyper-reactivity, excessive mucous production and smooth muscle remodeling.

Fig. 1.2 Two arms of adaptive immunity – This figure demonstrates the two limbs of the adaptive immune response resulting in antigen/pathogen specific “memory antibodies” from B lymphocytes on one arm and the direct (cytotoxic) and indirect ( on various effector cells via cytokines and chemokines) of T lymphocytes.

1.2.2 Antigen detection and recognition

The asthmatic response begins with exposure of pathogens or inflammatory particles (i.e. antigens) on the surface of the respiratory airway epithelial cell. As described earlier, the presence of pathogens in the airway are detected by respiratory antigen presenting cells

(APCs), the most relevant one in contact with the airway surface being dendritic cells [49].

However, they can also be present in the lung interstitium, pleura, pulmonary vasculature and bronchial lymph nodes [46]. Microbial pathogens contain evolutionary conserved proteins within their cell walls which allow recognition by dendritic cells. These components of the microbial cell wall are called pathogen associated molecular patterns (PAMPs) [50] and were first described in 1989 [42]. PAMPs are detected by limited germ line origin pathogen recognition receptors (PRRs) [35, 50] present on the cell surface of epithelial and dendritic cells. The most common PRRs are toll like receptors (TLRs). Others include nucleotide- binding oligmerisation domain (NOD) proteins, Dectin, CD 14, RIG-I, MDA-5 and

Collectins [38, 51].

TLRs are integral in triggering signaling pathways of the innate immune system [42]. TLRs can be present on the outer cell membranes themselves or on intracellular organs such as the surface of endosomes. In all, 9 TLRs have been identified of which TLRs 1,2,4,5 and 6 are present on the outer cell membrane while TLRs 3,7,8 and 9 are found on the endosomal membranes internally [48]. TLRs 1 and 2 as well as 2 and 6 work as heterodimers and have specific microbial ligands which they sense. Endosomal TLRs are primarily concerned with recognition of viral DNA and RNA. The respiratory epithelial cell (REC) surface, in addition to APCs, express multiple TLRs [39]. Once a PAMP is recognised, TLRs initiate signaling cascades resulting in the transcription and production of various inflammatory cytokines

20 through adaptor proteins including MyD88, Mal/Tirap, Trif/Ticam-1 and MyD88-5 [51].

TLRs 1,2,6 and 9 are considered to signal through MyD88 and MAL/Tirap while TLR 4 signals through MyD88 and Trif [48, 52, 53]. There is considerable over lap of these pathways which ultimately results in the activation of NF- κB (nuclear factor kappa-light- chain-enhancer of B cells) and release of IRF-3 (interferon releasing factor 3) and IFN-β [54,

55] all of which are key in initiating downstream responses such as release of various inflammatory cytokines.

Fig.1.3 Detection of PAMP by TLR and downstream signaling process resulting in the release of inflammatory cytokines and chemokines. PAMP = Pathogen associated molecular pattern, TLR = Toll-like receptor APC= Antigen presenting cell (e.g. Dendritic cell), ssRNA – single strand RNA, dsRNA = double strand RNA, CpG DNA = cytidine-phosphate-guanosine DNA

Another pathogen recognition receptor similar to TLRs are nucleotide binding oligmerisation domain (NOD) proteins [48]. There are two that have been identified in humans- NOD 1 and

NOD2 and are mainly associated with detecting PAMPs originating from gram positive and

21 gram negative bacteria. Mutations in NOD 1 has been strongly linked to the development of asthma [48, 56-60].

1.2.3 T2 High and T2 Low (non-T2) response

In addition to releasing inflammatory cytokines, activated dendritic cells take up the antigen and break it down to basic polypeptides and prepare it to be presented to naïve T lymphocytes via major histocompatibility complexes (MHC class 1 and class 2) [35]. This is also aided by the presence of co-stimulatory molecules such as CD80 and CD86 along with chemokines CCL17 and CCL22 [46]. These naïve T lymphocytes migrate to local and regional lymph nodes where they differentiate into CD4+ Helper Type 2 T cells (TH2), CD4+

Helper Type 1 T cells (TH1), T regulatory cells (TReg) [61] among less common others.

Predominant type seen in asthma is the TH2 T cells which leads to allergic eosinophilic asthma which is seen in most children and about 50% of adults with asthma [47]. The degree of polarisation and differentiation is largely mediated via genetic and environmental influences [62, 63]. There is increasing evidence that in disease, there is an imbalance between the two inflammatory processes (TH1 and TH2) and their regulation (TReg) due to over expression or under expression of corresponding transcription factors. In asthma, there is an overexpression of GATA-3 (coding for TH2 cells) and under expression of T-bet and

Foxp3 (coding for TH1 and TReg respectively) [61]. TH2 T lymphocytes produce IL-4, IL-5,

IL-9 and IL-13 [35, 46, 47, 64, 65]. IL-4 and IL-13 are considered the canonical TH2 cytokines which play a cardinal role in the allergic asthmatic response [66]. IL-4 promotes B lymphocytes to switch to producing IgE isotypes [66], increases mucous production and increases the expression of adhesion molecules like VCAM-1 and thus promote cellular migration (mainly eosinophil) across the respiratory endothelium. IL-5 has effects purely on

22 eosinophils and basophils as the IL-5 receptor is solely found on the surface of these cells.

IL-5 facilitates the maturation, growth and release of eosinophils from the bone marrow. It is closely linked with eosinophil activation and transport.

In addition to TH2 mediated allergic eosinophilic response, there are other mechanisms which have been identified which facilitate a non-allergic eosinophilic inflammatory response[65].

As described in the earlier section, bronchial epithelial cells, as a result of direct injury, exposure to irritants or stimulation by microbial antigens release cytokines IL-33, IL-25 and thymic stromal lymphopoetic proteins (TSLP). These cytokines facilitate the activation and migration of type 2 innate lymphoid cells (ILC2) [47] which are a more recently discovered class of innate immune cells of lymphopoetic origin. Similar to TH2 T cells, ILC2s depend on the transcription factor GATA-3 for their development from common lymphoid progenitors

[47]. ILC2 cells induce lung eosinophilia and bronchial hyper-responsiveness as a result of releasing some of the classical TH2 related cytokines including IL-5 and IL-13[67-70]. As a result of IL-5 and IL-13 production, a non-allergic but still eosinophil driven asthma occurs.

Given that downstream signaling via ILC2s can evoke a response similar to TH2 cell activation, more recently, nomenclature in defining the inflammatory pathways have changed to a more appropriate T2 high (indicating the presence of IL-4, IL-5 and IL-13 driven characteristics/biomarkers) and T2 low (or non T2) inflammation. The current biomarkers used to identify T2 high asthma are fraction of exhaled nitric oxide (FeNO), serum IgE, sputum/blood eosinophilia and serum periostin [71]. Periostin, CLCA1 and SERPINB2 expression from bronchial epithelial cells are upregulated by IL-13 [72, 73]. Furthermore, clinically, T2 high asthma is characterised by increased bronchial hyperresponsiveness and responsiveness to glucocorticosteroids [71].

1.2.3.1 T2 low inflammation

Over the past 15 years, it has emerged, in a considerable subpopulation of patients with asthma, inflammation is not characterised by T2 cytokines (either from TH2 cells or ILCs) or eosinophilia. The proportion of this population can be as high as 30-50% [72]. While this group represents a significant proportion of the asthma population, not much is known about the pathobiology that underpins this disease process. While there is considerable debate as the whether this “T2 low” group truly exists or whether the characteristics seen are a result of treated (or partially treated) asthma, bronchial biopsies have shown in addition to predominant eosinophilia, there are subgroups of asthmatics who can demonstrate patterns of inflammation that are neutrophilic, mixed cellularity and paucigranulocytic [74].

Furthermore, large cohort studies involving severe asthma patients such as

ENFUMOSA/BIOAIR [75], TENOR [76], SARP [77], Belgium Severe Asthma study [78] and U-BIOPRED [79] have also demonstrated the presence of “noneosinophilic” inflammation. The main difficulty is that there is no widely accepted definition for this group of patients with asthma. There are no recognised parameters/cut-offs for what constitutes neutrophilia or pauci-granulocytosis. In most situations, T2 low asthma is defined by the

“absence of markers of T2 inflammation”[80] rather than having a distinct identity of its own.

The presence of T2 low asthma presents a clinical conundrum that needs addressing. No clear pathways for this type of inflammation have been identified yet. However, it is often related to stimuli such as occupational exposures, smoking and viral infections [81-83]. These patients do not respond well to corticosteroids and would not be eligible for current targeted biological agents [84]. Furthermore, specific biomarkers (apart from sputum cell counts) for

24 T2 low asthma are not readily available yet. But several have been studied and give promise for the future. IL-8 (also called CXCL8) induces neutrophil chemotaxis and respiratory burst

[85]. Gibson et al. [86] demonstrated IL-8 in sputum were maximal in patients with supposedly T2 low asthma. Additionally, in severe asthmatics who were resistant to treatment, a positive correlation was seen between sputum IL-8 and specific potentially pathogenic micro-organisms and neutrophilic airway inflammation [87]. Other chemokines such as CXCL1 and CXCL5, also neutrophil chemoattractants, act via binding to receptors

CXCR1 and CXCR2 [88]. Patients with neutrophilic asthma have shown increased expression of these receptors in their sputum [89, 90]. Other potential biomarkers that could be used include sputum myeloperoxidase (MPO) and neutrophil elastase [90, 91]. Lastly, IL-

17, activated by TH17 signaling positively correlates with IL-8 and neutrophils in severe asthmatics [92-94]. Naïve T lymphocytes, in the presence of transcription factor retinoic acid-related orphan receptor-γt (RORγt) [95] can polarise into TH17 T cells. These cells secrete IL-17 which orchestrates neutrophil recruitment into the lung interstitium and the airways directly using the chemokine CXCL8. They also indirectly facilitate the production of IL-8 from bronchial epithelial cells [92, 96]. In addition to TH17 cells, the innate lymphoid cells (ILCs), especially ILC type 2 (ILC2) and ILC type 3 (ILC3) are also able to produce IL-

17 and subsequent neutrophil driven asthma [96].

Managing T2 low asthma is a challenge and difficult to treat. Corticosteroid resistance is the prime issue. However, simple, basic measures such as smoking cessation (for atleast 6 weeks) has shown to improve neutrophilic inflammation, steroid sensitivity and lung physiology [97]. Trials with potential inhibitors/antagonists of neutrophilic airway inflammation have not shown a clinical benefit (discussed in later chapters). Other drugs, such as macrolides, statins and vitamin D3 have been investigated in the context noneosinophilic inflammation [98-100]. Of particular note, Brusselle et al. have demonstrated a

25 significant improvement in exacerbations in non-eosinophilic patients who were administered azithromycin (AZISAST study) [99]. Lastly, bronchial thermoplasty, which utilises heat to reduce airway smooth muscle has also shown to reduce exacerbation frequency and improve symptom control in patients with severe disease and associated chronic airflow obstruction

[101, 102].

1.2.4 Epithelial Derived Cytokines in Asthma (Alarmins)

The airway epithelium plays a key integral role in the initial physiochemical protection and

“immune surveillance” [103] between the external environment and the lungs. Constant contact with the outside environment results in exposure to microbial agents, allergens and particulate matter. The bronchial epithelial cells and local milieu release various inflammatory mediators, cytokines and metabolites [104] which have been implicated in initiating and regulating complex downstream inflammatory signals and processes [103, 105,

106]. Of the cytokines released by the airway epithelial cells, the triad of IL-25, IL-33 and

TSLP, collectively known as epithelial derived alarmins, are released rapidly after cell injury/death [104]. A significant feature of epithelial derived alarmins is they can activate and promote both innate and adaptive immune responses [107]. Studies have shown these three cytokines are implicated in allergic diseases and the development of T2 high asthma in particular (see below) [108, 109].

1.2.4.1 IL- 25 in asthma

IL-25 (also known as IL-17E) is related to the IL-17 cytokine family. The bronchial mucosa, epithelial cells, eosinophils and mast cells all express IL-25 [110]. Natural killer cells and group -2 innate lymphoid cells (ILCs) also express IL-25 [109]. IL-25 targets various cells

26 and primarily increases the recruitment of T helper 2 (TH2) lymphocytes, eosinophils and stimulates the release of IL-4, IL-5 and IL-13 (in lungs) and IgE, IgA and IgG in blood [109].

Increased levels of IL-25 are seen in patients with asthma when compared to healthy individuals [111-113]. Administration of recombinant IL-25 has shown to result in allergic responses, T2 related cytokine expression and increased production of IgE [112]. High expression of IL-25 was also associated with greater bronchial hyperresponsiveness and more responsive to inhaled corticosteroids [113]. Cheng et al. [113] conducted a study comparing sputum, BAL and airway brushings in steroid naïve asthmatics against a healthy control group. Based on IL-25 mRNA levels in airway brushings, the asthma group was divided into

IL-25 high and IL-25 low groups. The IL-25 high subgroup was atopic with high serum IgE levels and was characterised by a T2 high cytokine signature.

1.2.4.2 IL-33 in asthma

IL-33 was first identified in 2005 and is a member of the IL-1 cytokine family [114]. IL-33 is expressed in many parts of the body, but in the airways, it is expressed by epithelial cells,

Type 2 pneumocytes and activated Clara cells [109]. Other immune cells including macrophages, dendritic cells and monocytes also express IL-33, but at much lower levels compared to epithelial cells [115, 116]. IL-33 is seen in the nuclei of producing cells and therefore is considered an intracellular alarmin [117]. The IL-33 receptor, ST2 and is highly expressed in mast cells, TH2 cells, macrophages, natural killer cells, eosinophils , basophils,

ILC2 cells and fibroblasts [118-121]. Similar to IL-25, IL-33 induces the production of Type

2 cytokines and the activation of ILC2 cells. ILC2 cells produce 10 times the volume of IL-5 and IL-13 as compared to TH2 cells [104].

27 1.2.4.3 TSLP in asthma

Thymic stromal lymphopoetin (TSLP) is part of the IL-2 cytokine family and is also expressed by epithelial cells in the lungs, gut and skin. Other immune cells including dendritic cells, basophils, mast cells and ILC2 cells also express TSLP [122, 123]. Similar to the other alarmins, TSLP has also been implicated in asthma. Ying et al. has shown TSLP is elevated in bronchial mucosa in asthmatics [124]. The release of TSLP can be accelerated by rhinovirus and respiratory syncytial virus proteins [125]. Similar to IL-25 and IL-33, TSLP also promotes a Type 2 immune response. Clinically, TSLP expression correlates with asthma severity and inversely correlates with FEV1 [109]. There is also evidence TSLP improves the survival of ILC2 which is an action independent of IL-25 and IL-33 [109].

1.2.4.4 Anti-alarmin treatment approach

Given the impact epithelial derived cytokines have on the early inflammatory disease pathways in asthma, several therapeutic agents which target alarmins are in development.

Blocking IL-25 in murine models has been shown to reduce airway hyperresponsiveness as well as levels of IL-5, IL-13 and eosinophils in bronchoalveolar lavage (BAL) samples [109].

Similar results were seen with blocking IL-33 directly or its receptor (ST2) [126, 127]. At present, multiple anti IL-25 and IL-33 monoclonal antibodies are in development. To date, the only clinical data available in terms of human studies is that of Tezepelumab

(AMG157/MEDI9929) which is a humanized monoclonal antibody to TSLP and acts through competitive blocking/binding of TSLP receptors. This therapeutic agent was tested in a double-blinded, placebo-controlled study involving patients with mild allergic asthma. This antibody brought sputum and blood eosinophil counts and FeNO down to normal levels.

Allergen induced airway responses were also almost completely blocked [128]. Tezepelumab has also been shown to improve lung function, and exacerbation frequency in patients with

28 uncontrolled asthma irrespective of blood eosinophil levels [129]. A summary of data available regarding the effect of alarmin blockade is tabulated in Table 1.1.

Alarmin Model Therapeutic Challenge Outcome/Findings target/intervention

Murine [130] IL-25 blocking Mab Rhinovirus Reduced AHR, ILC2 levels, IL-13 levels and mucous secretion Murine [131] IL-25(R) blocking Rhinovirus Reduced BAL Mab eosinophils and IL -25 mucous secetion Murine [132] IL-25 blocking Mab Ovalbumin Reduced BAL eosinophils and BAL IL-5, IL-13 and IL- 25 Murine [133] IL-33 blocking Mab Ovalbumin Reduced AHR and BAL eosinophils Murine [134] IL-33 blocking Mab Ovalbumin Reduced BAL eosinophils, IL-5, IL- 13 and reduced airway remodeling, goblet cells hyperplasia and IL-33 smooth muscle hypertrophy Murine [135] ST2 blocking Mab Ovalbumin Reduced airway hypersensitivity and reduced BAL eosinophils, IL-4, IL- 5, IL-13, IL-25, IL- 33 and TSLP Murine [136] ST2 blocking Mab Rhinovirus Reduced BAL eosinophils, IL-13 and IL-17A. Human [128] TSLP blocking Mab Environmental Reduced AHR. [129] allergens Reduced FeNO and blood/sputum eosinophils. Reduced TH2:TH1 circulating cell ratio. Reduced exacerbation and improved FEV1 Murine [137] TSLP(R) knock out Ovalbumin Reduced AHR. TSLP Reduced BAL IL-4, IL-5, IL-10 and IL- 13. Reduced serum IgE. Murine [138] TSLP (R) blocking Ovalbumin Reduced BAL TSLP, MAB IL-4, IL-5 and IFN- γ. Reduced BAL eosinophils. Table 1.1 Data available with regards to the effect of blocking the action of epithelial derived cytokines (alarmins) in predominantly murine models. To date, only blockade of TSLP has clinical trial data.

Fig.1.4 Inflammatory pathways in allergic eosinophilic, non-allergic eosinophilic and non-eosinophilic asthma. IL = interleukin, ILC = innate lymphoid cell, MHC = major histocompatibility complex, IgE = immunoglobulin E TSLP = thymic stromal lymphopoetic protein This figure demonstrates the most predominant mechanistic pathways which lead to the development of asthma symptoms including bronchoconstriction (airway smooth muscle contraction), mucous production (goblet cell hyperplasia) and allergy symptoms (IgE mediated histamine release from mast cells).

1.2.5 Key cells involved the asthmatic response

Bronchial Epithelial Cells (BEC)

Bronchial epithelial cells are the first line of defense within the airways. While the physical defense barrier protects against foreign invasion, these cells have been shown to play an early role in innate immunity. Similar to other antigen presenting cells (APC), they also express major histocompatibility class (MHC) 2 antigens [139] and therefore are in a position to behave as secondary APCs. This is also facilitated by the fact they also express TLRs 1-6 and

9 [48]. In addition, as in Fig.1.4 and described earlier the epithelial cells have a major role in secreting upstream cytokines IL-25, IL-33 and TSLP [140] which are key mediators in the development of the asthmatic response [140]. To a lesser extent, epithelial cells also synthesize and release interferon γ [141], IL-1β, IL-6, IL-11 [142] and tumour necrosis factor α (TNF α) which are all pro-inflammatory and have pleotropic effects on multiple different effector cells.

Dendritic Cells

These cells, as described earlier, are classed as the major antigen presenting cells and serve as an important link between the innate and adaptive immune systems. They are derived from

CD34+ progenitor bone marrow cells and CD14+ monocytes [48]. The immature forms are of three types – Langerhan’s cells, myeloid dendritic cells and plasmacytoid dendritic cells

[48]. Maturation of these cells are promoted granulocyte-macrophage colony-stimulating factor (GM-CSF) which is abundant around the bronchial epithelial cells [143]. Studies have shown that production of myeloid dendritic cells and their maturation is critical to the development of TH2 driven asthma [144]. Furthermore, there is a substantial body of

31 evidence to suggest airway dendritic cells are increased in asthma and animal studies have demonstrated removal of these cells attenuates the antigen response [145].

T-Lymphocytes

T lymphocytes play a central role in the innate and adaptive immune arms of the asthma disease process. In asthma pathobiology, the common types involved are naïve T cells, TH1 cells, TH2 cells, TH17 cells, regulatory T cells (TReg) and a few other less understood subtypes [35, 143, 146]. There is a general natural skew towards differentiation to the TH2 subsets in but there is evidence to suggest this natural skew is more pronounced in allergic asthma and persists through childhood [147]. TH2 lymphocytes and their hallmark cytokines

(IL-4, IL-5, IL-13) have been discussed in earlier sections. TH1 cell differentiation, mediated in the presence of IL-10 and transforming growth factor β (TGF β) [35] is associated with increased interferon γ production which results in protection against intracellular pathogens and promotion of local tissue injury [148]. TH17 cells are integral to the development and regulation of neutrophil and macrophage related inflammation [35, 149]. Neutrophil activation and chemotaxis is promoted by the TH17 release of IL-17. A new subset of T lymphocytes, classified as TH9 population has been more recently described [35]. While it not entirely clear whether this is a variant of the TH2 variety, the sequence of events leading to TH9 cell differentiation is becoming more defined [150]. TH9 cells are associated with the release of IL-9 which has been implicated mucus production [151] as well as airway remodeling and sub-epithelial fibrosis [152].

32 Innate Lymphoid Cells (ILCs)

Knowledge around innate lymphoid cells is relatively new and ILCs are emerging as key players in asthma pathogenesis. They have been previously named as nuocytes [153]. These cells, present mainly in the lung interstitium, are found three forms – ILC1, ILC2 and ILC3

[149]. Each subset exhibits and releases cytokines similar to their corresponding CD4+ T cell

(i.e. ILC1 – IFNγ similar to TH1, ILC2 – IL-5, IL-13 similar to TH2 and ILC3 – IL-17 similar to TH17)[154-156]. ILC2s are stimulated primarily by epithelial cytokines IL-25, IL-33 and

TSLP. As described earlier, ILC2s have been related to the non-allergic eosinophilic asthma population and corticosteroid resistance [157].

Eosinophils

Eosinophil driven asthma is currently one of the most well-defined asthma subpopulations and is associated with chronic (and more often) severe disease [158]. First described in 1879, eosinophils are derived from bone marrow multi-potent progenitor cells [159]. They mature, develop and transport mainly under the influence of the powerful cytokine IL-5 [160]. The cell structure consists of a bi-lobed nucleus and cytoplasm with multiple granules [159].

These granules are composed of a core made up of 2 proteins – major basic protein 1 and 2

(MBP 1 and MBP2) and a surrounding matrix composed of eosinophil cationic protein (ECP), eosinophil-derived neurotoxin (EDN) and eosinophil peroxidase (EPO) [161]. ECP has cytotoxic and helminthotoxic and antiviral activity in addition to other roles including suppression of T cell growth, suppression of immunoglobulin synthesis and stimulation of airway mucus secretion [159]. EPO facilitates the production of highly reactive oxygen species with subsequent cell death by apoptosis and necrosis [159]. EDN has been shown to promote the maturation and transport of dendritic cells. There is also some evidence EDN promoted adaptive immunity via enhancing TH2 cell activity and cytokine release [162].

MBP1 and MBP2 have also been shown to destructive to the airways and is associated with

33 tissue damage to the bronchial mucosa[163-165]. A summary of the effects eosinophils have on other leukocytes is listed in Table 1.2.

Mediator Target effects T lymphocyte Surface MHC class 2 Increased proliferation proteins and co- and cytokine stimulatory molecules production TH2 cell CC17, CCL22 Increased recruitment Neutrophil MBP Increase IL-8 and superoxide secretion Macrophage IL-4, IL-13 Activation Mast cell MBP, ECP Increased survival, histamine release Dendritic cell EDN Increased maturation B Lymphocyte via priming Increased IgM production

Table 1.2 – Effects of eosinophils on other leukocytes[166] CC = chemokine, MBP = major basic protein, ECP = eosinophil cationic protein, EDN = eosinophil derived neurotoxin, MHC = major histocompatibility complex, IgM = immunoglobulin M

Neutrophils

The role of neutrophils in asthma is unclear and controversial. IL-17 (a TH17) cytokine up regulates the production of IL-8 which is a very potent neutrophils chemo-attractant [167].

Other recruiters of neutrophils into the airway include CXCL5, CCL3, LTB4 and GM-CSF

[168]. As an innate immune cell, the primary function of neutrophils is phagocytosis of foreign invading agents and release of free oxygen radicals (oxidative burst) [169] that result in tissue damage. Neutrophils release elastase which causes mucus gland hyperplasia and proliferation of airway smooth muscles [168]. Some human studies have questioned whether neutrophils in the lung actually have a role in asthma pathobiology or whether they are simple present and do not contribute to active disease pathogenesis [170, 171].

34 Mast Cells

Mast cells are leukocytes primarily which rest with in the bronchial smooth muscle, airway mucous glands and bronchial epithelium [172] and release histamine from granules within the cytoplasm. Histamine is a very potent smooth muscle constrictor and therefore, bronchoconstriction. In addition to histamine, mast cells also secrete prostaglandin D2 and leukotriene C4 which are also bronchoconstrictors as well. They also induce mucus secretion and mucosal oedema [172]. They are recruited to the smooth muscles using chemotactic factors IL-8, fractalkine, TFG-β, CXCL9, RANTES (CCL5) and eotaxin (CCL11) [173].

These cells are activated when IgE bound to high affinity receptors on mast cells are cross- linked by allergens and result in degranulation.

1.3 Phenotypes and Endotypes

Phenotypes

For over a decade, it has been clear asthma is not a single entity and that heterogeneity is prevalent across all spectrums of the disease [174]. The concept of phenotyping emerged when it was noticed certain population groups demonstrated common clinical features and disease profiles. A phenotype is defined as “ the visible characteristics of an organism resulting from the interaction between its genetic makeup and the environment” [158].

Historically, asthma phenotyping has been based on clinical or physiological characteristics.

Wenzel’s [158, 175] reviews of asthma phenotyping describe studies where discrepancies between guideline based asthma management and the true pathobiology and symptom control are quite evident. This resulted in a move away from a simple step based approach and towards categorising populations into groups based on an understanding of underlying disease driving features.

35 Much work has been done in trying to characterise these different groups and develop

biomarkers that can potentially identify each phenotype. Examples of phenotypes are listed

the table below. The Severe Asthma Research Program [176] (SARP) used a cluster analysis

of asthmatics with varying severity of asthma and identified 5 groups or “clusters” of

asthmatics that share similar characteristics. These ranged from those with mild early onset

atopic asthma with normal lung function to those with severe airflow limitation. Other

parameters used in cluster phenotyping included age of onset, duration of disease, sex,

symptoms, medication use and healthcare utilisation.

PHENOTYPE FEATURES  Earliest phenotype to be described based on symptom control and physiology. Severity defined  Implicated biomarkers include TGF-β, IL-11, TNF-α and IL-8  40% of patients. Exacerbation  Associated with airflow obstruction, prone  Reduced spirometry and raised airway eosinophilia  Allergic symptoms. Clinical  Symptoms can vary in severity Early onset  Cytokine IL-4, IL-5, IL-13 predominance (i.e. TH2) allergic  Thickened subepithelial membrane  Usually steroid responsive  Adult onset. Usually severe Late onset  Raised IL-5 with eosinophilia  Can be steroid resistant but respond to anti IL-5 therapy  Adult onset. Female predominance Obesity related  Pathobiology generally unclear and lack of biomarkers.  Responds to weight loss  Wide spectrum of disease Environment  TH2 cytokine signature predominance  Generally associated with better lung function but increased exacerbation rates allergens  Can account for up to 15% of asthmatics

 Usually IgE driven to low molecular weight triggers.

Occupational  A non-immunologic form has been identified which is rapid onset secondary

allergens to high exposure of irritant.  Can persist after removal of causative agent

36 Trigger related  Not very well characterized.  May or may not be associated with asthma. Exercise  Mechanism appears to be “cold air” triggered related acute inflammatory response with mast cell degranulation. Exact pathogenesis is not clear.

 Pathogenesis poorly understood. Aspirin/NSAID  Seen in severe asthma population Induced  Increased airway leukotrienes and eosinophils  Association with nasal polyps and rhino sinusitis  Worse disease control  Increased risk of exacerbations  Increased air flow obstruction, hyper-responsiveness, sub epithelial basement Eosinophilic membrane thickening Pattern of sputum  Raised levels of cytokine IL-5 and chemokine eotaxin inflammation  Associated with more severe asthma. Especially during exacerbations

Neutrophilic  Significantly reduced post bronchodilator FEV1 [177]  Older age of onset  Weak association with obesity and smoking  Smoking related asthma (likely due to neutrophilia and oxidative stress) can be considered as a separate phenotype with an overlap with COPD.

Paucigranulocytic Clinical features not specifically described. See description below.

Mixed Clinical features not specifically described. See description below.

Table. 1.3 – Examples of phenotypes based on different classifications

Phenotyping based on patterns of sputum inflammatory cells

Phenotyping asthmatic patients according to their predominant sputum cell pattern is of

significant importance from a therapeutics point of view. New therapies and pharmacological

agents have been (and are currently being) developed targeting individual cell driven

pathways. In early phase clinical drug trials and in identifying appropriate target populations,

analysis of sputum cell distributions is vital. As described in Table 1.3, four distinct sputum

cell patterns have been identified in asthmatics – eosinophilic, neutrophilic, mixed cellular

and paucigranulocytic. The characteristics classically associated with these phenotypes are

also listed in the table. Around 50% of asthmatics have an eosinophilic pattern [74]. While

37 debate still continues regarding “cut off” levels in sputum, two large, long term studies [178,

179] have shown targeting treatment aiming to keep sputum eosinophil counts ≤ 3% reduces rate of exacerbations and time to exacerbations compared to following generic “guideline” based treatment [158]. There is also evidence increased sputum eosinophils is associated with better response to corticosteroids [180]. Neutrophilic sputum and related clinical features is less clear and defined. The evidence so far is discussed in a later section dedicated to neutrophilic asthma. In this thesis, one study (Chapter 5) explores characteristics of neutrophilic asthma in further detail. Other cell patterns do not follow the classical dichotomy of eosinophilia vs neutrophilia. In some situations, both eosinophil and neutrophil counts are low (paucigranulocytic) or both may be present in large numbers (mixed cellularity). While by definition, paucigranulocytic refers to a lack of inflammatory cells in the sputum, evidence suggests symptoms of asthma +/- airway inflammation can exist without a clear influx of these cells [181]. It is postulated inflammation in these conditions may not be in conventional forms but originate from other local cells including mast cells, bronchial epithelial cells and smooth muscle cells [158].

1. 2.

Fig. 1.5 – Sputum Eosinophilia (1) with eosinophil granules seen taking up the eosin (pink) stain. Sputum Neutrophilia (2) seen with multiple lobed nuclei. The granules of neutrophils stain weakly or neutral (hence –called neutrophils). These photos were taken of slides prepared for this thesis.

1. 2.

Fig. 1.6 Paucigranulocytic sputum (1) showing very little granulocytic cells. Mixed cellular sputum (2) showing abundant neutrophils and eosinophils. These photos were taken of slides prepared for this thesis.

Endotyping

The concept of endotyping [182] rather than phenotyping asthma has increasingly become more relevant. Endotyping refers to classifying populations based on specific pathobiology and molecular mechanisms rather than physiological/clinical presentations and has been defined as “a subtype of a condition, which is defined by a distinct functional or pathophysiological mechanism” [182]. The debates and discussions surrounding the possibility of different mechanistic pathways among asthmatics who share similar clinical features came about following the realization heterogeneity within subpopulations was extensive and not all patients deemed similar responded similarly to therapeutic agents in clinical drug trials [183]. The predominant endotype described so far is the T2 inflammatory pattern (50%) which has been discussed earlier.

Other endotypes including TH1, TH17 and TH9 have been described but less understood.

The drive towards characterising endotypes stems from the fact that better understanding of underlying mechanistic pathways have the potential to identify future therapeutic targets [7].

Positive and encouraging data from clinical trials of antagonists of T2 cytokines seem to support this. Studies looking at cytokine blockade with monoclonal antibodies have shown good physiological responses and improvement in symptom control.

Fig. 1.7 – Demonstrates how traditional phenotyping according to clinical features and inflammatory patterns overlap and the evolution towards mechanistic mapping (endotyping).

In 2011, Lotvall et al. [182] proposed a “7 parameter” approach to defining endotypes on the basis that phenotypes and endotypes overlap with each other. Different phenotypes may be driven by a particular endotype and many different endotypes can produce similar clinical characteristics that result in particular phenotype. Lotvall used clinical characteristics, biomarkers, lung physiology, genetics, histopathology, epidemiology and response to treatment as parameters that were to be incorporated in defining an entire endotype. This would assure an attempt to explain the underlying pathobiology of the group.

More recent literature exploring contemporary has focused primarily dividing endotypes into two main broad categories [184] – T2 driven (mainly eosinophilic) and non-T2 (or T2 low) driven

(mainly neutrophilic + poorly defined others). Studying gene expression profiles from bronchial biopsy of epithelial cells and induced sputum samples have given rise to new discoveries of associated activated genes (and transcribed proteins) which drive disease. The most described is that of the triad of CLCA1, periostin and serpin B2 which forms the basis of T2 inflammation and are being described as potential measurable biomarkers for this endotype in the future. Other studies by Cheng et al. [113] explored expression of upstream bronchial epithelial cytokines (IL-

25, IL-33, thymic stromal lymphopoetin (TSLP) and found an IL-25 driven endotype associated with raised bronchial hyper-reactivity, IgE and sub-epithelial thickening (i.e. overlap with T2 related features). Similarly Traister et al. [185] demonstrated T2 patterns with the expression of

IL-33. A “whole genome differential expression analysis” was reported by Baines et al. [89] which studied the expression of 277 genes in 47 asthmatics. Six genes were identified which could be used to differentiate between T2 asthma and non-T2 asthma. Genes expressing the proteins Charcot-Leydon Crystal (CLC), carboxypeptidase A3 (CPA3) and deoxyribonuclease I- like 3 (DNASE IL3) were related to eosinophilic asthma while IL 1β, alkaline phosphatase

(ALPL) and chemokine receptor 2 (CXCR2) together described an endotype associated with neutrophilic driven asthma. Therefore, as current literature demonstrates, endotyping of asthma and understanding the underlying root cause/driver leads to the recognition of multiple coexisting pathways all or some of which could develop as future potential therapeutic targets in clinical drug trials or biomarkers for disease activity.

42 1.4 CORTICOSTEROID NAÏVE ASTHMA

Generally, patients with “mild” intermittent symptoms of asthma are treated with a short acting bronchodilator such as salbutamol on an as and when required basis. These patients are not prescribe anti-inflammatory agents such as corticosteroids and are usually cared for in a primary care setting. However, as Shahidi and Fitzgerald [186] point out, mild asthmatics by far constitute the largest number of asthma patients. A recent study of the socio-economic impact of asthma in

150,000 patients revealed 67.1% were classified as “mild” and constituted 60% of health care costs [187]. Despite this, the focus of research and drug development over time has been in severe asthma.

In developing new pharmacological agents in asthma, once laboratory and pre clinical testing is done, early phase clinical drug trials (Phase 1 and Phase 2) are usually done in healthy individuals and in those with mild symptoms. The purpose of these early phase trials is primarily to determine safety, drug effect and appropriate dosage [188]. In trials related to asthma, a considerable number are done in the relatively mild corticosteroid naïve population. This is the case, not only for safety reasons, but to eliminate steroid effect. Corticosteroid naïve asthma represents the “true inflammation” and is not confounded by the use of steroids. At a molecular level, corticosteroids reduce the number of inflammatory cells in the airway and inhibit or suppress the production of various inflammatory cytokines, chemokines and adhesion molecules [189]. Therefore, when trialing new pharmacological agents which may be designed to target these inflammatory pathways, using a target population that is steroid naïve is ideal. The characteristics of this population (i.e. symptom control, lung/airway physiology, sputum inflammatory patterns, prominent cytokines and their effectors cells, blood cell counts) can be used as dynamic markers of drug effect and as primary and secondary end points in clinical trials.

43 While there has been considerable characterisation of the more severe asthma population, our knowledge of the characteristics, underlying pathobiological pathways and potential biomarkers that represent corticosteroid naïve asthmatics is poor.

Fig. 1.8 – Effect of corticosteroids in the lung and airways

This for example, is of particular significance in clinical trials and when developing challenge models such as allergen, viral or lipolysaccharide challenges. The sputum characteristics and general physiology has been scarcely studied. Lee et al [190] assessed sputum characteristics in solely steroid naïve asthmatics looking purely at sputum differential cell counts. They demonstrating widespread eosinophilia (70.6%) (taken as >3%) and therefore, described eosinophilic inflammation (and by extension – probable T2 pattern) as a driver in the milder asthmatics. It has to be noted that no other associated biomarkers or cytokine assays were done to

44 substantiate this. Furthermore, the arbitrary cut off for neutrophilia was considerably high (>65%) rendering the chances of missing out on a potential neutrophilic or mixed cellular population.

It follows that knowledge of the stability of these characteristics and their reproducibility on repeated measurements is vital for them to validated as biomarkers. Although evidence in corticosteroid naïve asthma is limited, available evidence for sputum differential cell count in reproducibility in varying severities of asthma is described in the next section.

1.4.1 Reproducibility

The predominant sputum studies (tabulated in Table 1.4) below assess sputum differential cell count reproducibility of across the asthma severity spectrum.

Study Asthma Sample Size Findings Severity Bacci et al.[191] Mild to 17 ICS/LABA Reproducibility (ICC Ri ) within 1 week: Moderate on ICS 12 Eosinophil% - 0.87 Steroid Naive Neutrophil% – 0.80 Fahy et al.[192] Moderate to 53 Reproducibility (ICC Ri) within 2 days: severe ICS +/-LABA Eosinophil% – 0.74 26 Does not comment on other cells Steroid Naive Pizzichini et Moderate 13 Reproducibility (ICC Ri) within 6 days: al.[193] ICS Eosinophil% – 0.94 6 Neutrophil % - 0.81 Steroid Naive Veen et al.[194] Mild + 9 Reproducibility (ICC Ri) within 2 days: Moderate-Severe ICS +/- LABA Eosinophil% - 0.85 12 Neutrophil% - 0.57 Steroid Naive Rossall et al. Moderate to 19 Reproducibility (ICC Ri) within 1 month: [195] severe ICS/LABA Eosinophil (x 106/g) – 0.56 Eosinophil % - 0.28 Neutrophil (x 106/g) – 0.11 Neutrophil % - 0.61 Spanevello et al. “Stable asthma” 17 Reproducibility (ICC Ri) within 2 weeks: [196] ICS Eosinophil % - 0.84 36 Neutrophil% - 0.75

45 Steroid Naive

Gibson et al. “Asthma with 8 Reproducibility (ICC Ri) within 2 days [197] increased ICS Eosinophil (x106/g) - >0.7 daily sputum Neutrophil (x106/g) - >0.7 production” Mixed severity. 15 Reproducibility (ICC Ri) within 2 days Pin et al. [198] 5 – “good ICS/LABA Eosinophil% - 0.80 control” 2 Neutrophil% - 0.70 12 – “increased Oral Steroids (Polymorphonuclear cells) symptoms”

Table 1.4: Studies looking at sputum eosinophil and neutrophil reproducibility. ICC = intraclass correlation coefficient In this thesis I have focused on sputum eosinophils and neutrophils as they are the predominant cells associated with asthma. Hence, only eosinophil and neutrophil reproducibility is tabulated.

The studies tabulated in Table 1.4 demonstrate good to excellent reproducibility for sputum eosinophils and neutrophils across the spectrum of mild to moderate to severe asthma. However, none of the studies have either focused purely on corticosteroid naïve asthma or subanalysed their data to differentiate between the different severities of the disease.

The reproducibility of other biomarkers such as peripheral blood eosinophils, airway physiology

(FEV1, reversibility, lung clearance index) and FeNO needs further study in this group. FeNO in patients with mild steroid naïve asthma has been examined earlier [199, 200]. Kharitonov et al.

[200] demonstrated excellent reproducibility (ICC Ri coefficient = 0.90) of FeNO in steroid naïve asthmatics when checked 24 hours apart. However, sample size was small (n=10) and therefore will need corroborating with larger numbers. Purokivi et al. [201] described similar reproducibility with FeNO (ICC Ri coefficient = 0.97) measurements in healthy individuals when checked 48 hours apart.

46 1.5 NEUTROPHILIC ASTHMA

1.5.1 Neutrophil Biology

Neutrophils comprise the largest population of white blood cells and their primary role is phagocytosis of pathogens and microbes as a part of innate immunity. They have a half life of 6 to

8 hours and therefore, the bone marrow must generate more than 5-10 x 105 neutrophils on a daily basis [202]. Production is facilitated in the presence of transcription factors EgR1, HoxB7 and

STAT3 [203] from progenitor cells. While under normal homeostatic conditions, G-CSF regulates neutrophil release from bone marrow, under demand, stromal cell-derived factor 1-α and the chemokine CXCR4 play significant role in neutrophil release [202].

Neutrophil Migration

Circulating neutrophils migrate to the lungs mediated via leukotriene B4, IL-8 (via chemokines

CXCR1 and CXCR2) and IL-17. IL-8 has been shown to correlates significantly with the presence of a predominant neutrophilic inflammation [204]. In the lung parenchyma, neutrophils leave the peripheral circulation at the capillary level using a “rolling-tethering” mechanism [202].

In this situation, neutrophils interact with glycoprotein ligands, β2-integrins which lead to neutrophils “rolling” towards the endothelial membrane and cell adhesion/arrest [202]. Adhesion molecules facilitate the migration of neutrophils across the endothelium and basement membrane.

More recent evidence has shown that in addition to this mechanism, neutrophils can migrate across by an active process where they are engulfed by endothelial cells and transported across

[205]. In the presence of a pathogen, the neutrophil prepares for degranulation and respiratory burst. This however is preceded by a two step process – priming followed by activation [206].

47 Neutrophil Priming, activation and respiratory burst

Priming of neutrophils involves the mobilisation of secretory vesicles towards the cell membrane and is considered a vital regulatory step prior to full activation. It has been argued that priming

(and de-priming if necessary) can prevent unregulated neutrophil activity [202]. Once activated, neutrophils engulf the microbe (through phagocytosis) and form a phagosome with in the cytoplasm. The destruction of the phagosome is occurs through two processes – degranulation and respiratory burst [206]. Neutrophils posses 4 major granules – secretory, tertiary, specific and azurophilic. Azurophilic granules are present in the early stages of life of the neutrophil and contains myeloperoxidase (MPO), defensins, elastase, cathepsin and proteinase – 3 [206].

Neutrophil elastase being a prominent component. However, more recent evidence has shown that only 2% of elastase ( usually stored in azurophilic granules) are released during degranulation

[202]. The vast majority of elastase is released during neutrophil apoptosis and death. The specific granules contain lactoferrin (binds iron and copper), transcobalamin 2, flavocytochrome and almost two thirds of the neutrophil lysozyme content [207]. Tertiary granules contain gelatinase

[207]. The activated neutrophil also generates superoxide anions (respiratory burst) through a nicotinamide adenine dinucleotide phosphate (NADPH) oxidase complex, which causes potent destruction of bacteria and fungi.

A fairly new advance in the understanding surrounding the biology of neutrophils is the finding that they generate and release granule proteins mixed with chromatin which forms a “web of protein” can neutrophil extracellular traps (NETs) . These can trap bacteria and fungi and facilitate phagocytosis.

Unfortunately, in addition to protection against microbial invasion, mediators released by neutrophils can also cause tissue damage. Elastase and other proteases can cause serious host tissue destruction. They can digest and destroy extra cellular matrix. Elastase also promotes bronchial epithelial cells to release inflammatory cytokines. In addition, specific and tertiary

48 granules release matrix metalloproteinase (MMP-2 and MMMP-9) which can also cause considerable damage [206].

Fig. 1.9 Structure of Neutrophil A = multi-lobed nucleus, B = glycogen stores, C = Tertiary granule, D = Secondary granule E = primary azurophilic granule, F = mitochondria, G = Vacuoles * Adapted from www.biosiva.com

1.5.2 Mediators of Neutrophil Inflammation

Quite a few soluble mediators have been shown to play key roles in activating, processing and regulating neutrophil recruitment into the lungs and airways. IL-8 (CXCL80 is a chemokine is the most potent neutrophil chemoattractant [208]. While many types of cells including bronchial epithelial cells, T cells and macrophages can express IL-8, neutrophils have been shown to have the ability to do so as well, indicating a feed-forward loop cycle that augments neutrophil presence in the airway [86]. IL-8 is also induced by IL-17 which a key cytokine secreted by TH17 lymphocytes.

Cytokine IL-17 is closely related to neutrophilic asthma [209] playing significant roles in recruitment and activation. In severe asthma, it has been observed to upregulate the production of

IL-8 which is a very potent neutrophil chemoattactant [167]. IL-17 is a 20-30 kDa cytokine secreted primarily by TH17 lymphocytes [210]. This subset of CD4+ T lymphocytes appear a result of the differentiation of naïve T cells in a cytokine environment consisting predominantly of

TGFβ, IL-1β and IL-23 [211]. There are 6 types of IL-17 including IL-17A (simply known as IL-

17), IL-17B, IL-17C, IL-17D, IL-17E (usually known as IL-25) and IL-17F [212]. IL-17 and IL-

17F are the most biologically active while much less is known about the roles and significance of the other subtypes. IL-17 mediates its actions via IL-17R receptors found primarily in stromal/structural cells in the human airway. These include epithelial and endothelial cells as well as fibroblasts. Recent in vitro studies have shown IL17 can up regulate the release of cytokines

IL-6, IL-8, IL-10, IL-12 and TNFα [210].

Given the clinical significance and effects on lung physiology as a result of airway neutrophilia as well as the pivotal role IL-8 [213] and IL-6 [214] play in neutrophil trafficking; the relationship between raised IL-17 levels and airway neutrophils (with IL-17 being a potential soluble biomarker and therapeutic target for neutrophilia) have raised scientific and pharmacological interest. A review of IL-17 signaling in asthma by Linden [215] concluded there was significant evidence suggesting IL-17 and IL-17F involvement in the pathobiology of asthma. But, most previous studies were done in mixed phenotypes and therefore, a definitive target population for future interventional studies were not clearly identified. The link between IL-17 and neutrophils has a been subject to various studies before and are summarized below:

Study (Year) Sample size, asthma severity Conclusions IL-17 positive cells (IHC) in BAL and bronchial biopsies were seen more in Molet et al. (2001) [216] n = 7 Mild to moderate asthma asthmatics compared to controls. In vitro stimulation of bronchial fibroblasts with IL-17 increased levels of IL-6 and IL-8 among other inflammatory cytokines. IL-17A and IL-8 mRNA in sputum significantly elevated in asthmatics. n = 39 (asthma) Significant correlation between IL-17 and Bullens et al. (2006) [94] n = 15 (healthy control) IL-8 levels and raised neutrophils in varying GINA categories sputum DCC but no correlation in FeNO or airway hyper-responsiveness Significantly elevated sputum IL-17 and n = 16 mild, n = 14 moderate IL-8 in severe asthmatics with positive Sun et al. (2005) [217] n = 18 severe, n = 15 healthy correlation with sputum neutrophilia. Nasal and Bronchial washings IL-17A and IL-17F significantly elevated and positive Sobello et al. (2015) n = 14 severe, n = 14 mild, correlation with bronchial neutrophilia in n = 7 healthy severe asthmatics. Table 1.5: Studies assessing the link between IL-17 and neutrophils

Other studies have shown neutrophils secrete chemokine CXCL10 which facilitate the induction

and recruitment of TH1 lymphocytes. The main cytokine produced by TH1 lymphocytes is IFN-γ.

IFN-γ has been associated with neutrophil chemotaxis [218]. This again suggests a feed forward

loop and “cross talk” between neutrophils themselves and TH1 and TH17 lymphocytes.

51 1.5.3 Airway Microbiome and Neutrophilic Asthma

Contrary to previous concepts, it is now widely accepted the smaller airway environment is not sterile and certain organisms are associated with airway inflammation. Fungi, viruses and bacteria have been implicated in neutrophilic steroid resistant severe asthma [219]. There is increasing evidence that several bacterial species such as Chlamydia pneumonia, Streptococcus pneumonia,

Mycoplasma, Haemophilus Influenzae, Moraxella Catarrahlis and Staphylococcus aureus all play a role in stable severe asthmatics with neutrophilic airway inflammation [87] [220]. More recent data have shown that neutrophilic asthma is associated with “reduced diversity of the lung microbiota” [221] and suggests a bacterial imbalance or dysbiosis being a feature of this type of inflammation. Lipotechoic acid and lipopolysaccharide which are components of Gram positive and Gram negative bacteria respectively combine with TLRs on immune cell surfaces and promote the expression of IL-8, IL-1 and TNF-α as well as the transformation of TH1 lymphocytes to TH17 type. This vastly leads to neutrophil aggregation and activation [222]. Lastly, there is an emerging concept that pathogens may promote neutrophil survival as pathogen recognition receptors expressed on neutrophil cell surfaces, when activated can delay neutrophil apoptosis via specific downstream signaling though NF-κB and mitogen activated protein kinases (MAPKs)

[223].

1.5.4 Do neutrophils play a role in asthma disease processes?

For a while now, it has been hypothesised that a distinct population of asthmatics with more severe disease is associated with increased airway neutrophilia. Reviews by Wenzel [158], Fahy

[177], King [224] and Brightling [225] all point towards a relationship between lung neutrophilia and more severe airflow obstruction (reduced pre-bronchodilator FEV1), more severe exacerbation episodes, gas trapping, thicker airway walls and corticosteroid resistance [226]. A post hoc study of the SARP clusters revealed the highest magnitude of sputum neutrophilia was

52 seen in individuals with adult onset asthma with severe obstruction [175]. However, unlike the eosinophilic phenotype, bronchial hyper-reactivity was not affected and no association with PC20

[227] has been seen. It appears the role of neutrophils seems limited to severe disease and during acute exacerbations. Ennis et al. [228] compared absolute neutrophil counts in sputum, BAL and bronchial biopsies in those with mild asthma in the basal state against healthy controls. No statistically significant differences between the two groups were seen. When re-assessed post inhaled allergen challenge, neutrophils were significantly raised compared to controls in bronchial washes [228]. Furthermore the European Network for Understanding the Mechanisms of Severe

Asthma (ENFUMOSA) [75] study also showed increased neutrophils in sputum in severe asthmatics compared to those with well controlled disease. Finally, some weak association with smoking, obesity and female gender has also been described. Wood et al. [90] identified a correlation between sputum neutrophilia and systemic inflammation (raised serum CRP and IL-6).

Despite these clinical associations and prevalence in severe asthma and exacerbations, the actual immunopathological pathways involving airway neutrophils are still not clearly described. Apart from direct phagocytosis of foreign organisms, neutrophils also release metalloproteinases (e.g.

MMP 9, MPO, collagenase, elastase etc.,) as well as pro-inflammatory cytokines such as TNF α,

IL-1, IL-6, IL-8 and leukotriene B4. The up regulation these (especially TNF α) have been implicated, but not substantiated. The mechanistic pathways through which neutrophils exert their effects are a gap in knowledge and needs further study. Furthermore, literature on the extent of correlation between the clinical features and neutrophilia itself remains largely unclear and inconsistent [225].

What is currently being debated and is still not clear is the question whether the presence of large numbers of neutrophils in the airways is a true primary disease/inflammatory process or whether their occurrence is a mere consequence of the secondary effects of other factors or treatment.

53 While there is an increasing body of evidence pointing to an alternate T2 low inflammatory process, of which neutrophilic asthma is a significant component, there are a considerable other confounding factors that can result in the persistence of neutrophils in the airways. Patients with asthma who smoke seemingly have large numbers of neutrophils as it is known cigarette smoke promotes neutrophilia [229]. In females, an association has been observed between obesity and airway neutrophilia and similarly, in males serum saturated fatty acid levels correlated with the same [230, 231]. The SARP [232] and UBIOPRED [233] cohorts have also identified gastroesophageal reflux disease being a common feature in severe asthmatics. In one of these cohorts, acid reflux disease was associated with sputum neutrophilia [234]. The use of corticosteroids is a very significant confounding factor. Suppressing airway inflammation with oral and inhaled corticosteroids is the “cornerstone” asthma management [219] and severe asthmatics who are usually maintained on a sustained high level of steroids often demonstrate increased neutrophil counts in sputum [219]. These steroids, while facilitating the apoptosis of eosinophils, also concurrently promote the survival of neutrophils [235, 236]. Adenosine triphosphate (ATP), released by damaged and dying cells can also encourage neutrophil survival

[237]. Similarly, Leukotriene B4 (LBT4) has also been implicated in improving neutrophil persistence and in fact, Lee et al. [238] have shown that this can be reversed if LBT4 receptors are blocked. Furthermore, targeted therapies against neutrophil inflammatory pathways (discussed in the next section) have shown promise, but have not been conclusive.

While the debate continues, the volume of knowledge and evidence around the pathological and physiological effects activated neutrophils in lungs and airways can bring about is increasing

(albeit still limited), there can be no argument that addressing this cohort of patients is of paramount importance in treatment resistant severe asthmatics. Regardless of whether neutrophilia is due to a primary inflammatory process and is an endotype in its own right or

54 whether it is secondary to steroids, infection or other covariates, identifying biomarkers and therapeutic targets for this group must continue as a prime focus for research.

1.5.5 Pharmacotherapy for Neutrophil Asthma

Insensitivity to corticosteroids , severity of symptoms and exacerbation frequency have made addressing neutrophilic asthma and urgent unmet need. As a primary problem, there is no defined clear value as to what can be considered as a neutrophilic sputum. In the different studies discussed earlier there is an inconsistency when it comes to deciding how high sputum/BAL neutrophil counts should be before being defined as neutrophilic. Till now there is no agreement on the cut off . Different authors have used cut offs ranging from 40% - 65% [239-242] without a clear rationale as to how these values were chosen. This clearly poses a problem for drug development, especially when identifying the target population, exploring potential biomarkers for disease activity/drug effect and deciding on primary/secondary end points when designing clinical drug trials.

Having said that, at this point, there have been no phase 3 trials for “anti-neutrophil” therapies.

Several potential molecules have been developed and are in evolution. CXCR2 antagonists [243,

244], 5-lipoxygenase-activating protein (FLAP) inhibitors [245], anti- IL-17 [246] and anti-

TNF α [247] are such examples. Although showing promise in experimental models, the results in clinical studies have been disappointing.

A phase 1 clinical trial of a CXCR2 antagonist (AZD5069) in severe uncontrolled asthmatics demonstrated a dose-dependent reduction in blood neutrophils counts [244] but did not improve clinical outcomes. FLAP inhibitors prevent the formation of leukotriene B4 (LTB4) which promotes neutrophil survival [238]. Despite reductions in LTB4 levels, the FLAP inhibitor

55 GSK2190915 had no short term effects on sputum cell counts or clinical endpoints in non- smokers and smokers with asthma associated with elevated sputum neutrophils [245].

Brodalumab is a human monoclonal antibody again IL-17 receptors and blocks the activity of IL-

17 and IL-25. A randomized controlled trial of brodalumab in moderate to severe asthma (but not selected for neutrophilic inflammation alone) reported no improvement in symptoms (asthma control questionnaire) or lung function [246]. A further trial of an IL-17A monoclonal antibody, secukinumab (AIN457) in uncontrolled asthma was terminated early due lack of proof of efficacy

[98]. TNF α blocker, etanercept, had shown promise in early small clinical studies in severe asthma but larger studies around etanercept and another TNF α blocker, golimumab [247], did not confirm a sustained clinical benefit. Furthermore, worryingly, there were concerns over increased risk of infection and malignancies with TNF α blockers [247].

1.5.6 Reproducibility and stability (Short and long term) of sputum neutrophils

As discussed earlier, drug development and subsequent clinical trials of novel therapeutic agents involves measurements of various clinical endpoints (for drug effect) and biomarkers (for drug effect and monitoring). The reproducibility of these measurements is of paramount importance in order to achieve conclusive outcomes. Studies exploring sputum cell counts including the reproducibility of sputum neutrophils have been tabulated in Table 1.4. Most studies have demonstrated good to excellent short term (within one month) reproducibility. Future new, targeted “anti-neutrophil” therapies that reach larger Phase 3 clinical trials will rely on the long term reproducibility of sputum neutrophil measurements as it is very likely sputum counts will be used as biomarkers or trial endpoints. In latter phase larger trials, the duration of studies is much longer (months – years) and therefore, knowledge of the reproducibility and stability of

56 neutrophils as a long-term marker important. This feature has not been explored and data regarding this is not available at present.

1.6 THE ANTICHOLINERGIC RESPONSE IN ASTHMA AND IDENTIFYING THE “RESPONDERS”

1.6.1 Physiology of bronchoconstriction and bronchodilation

Hyper-reactivity and subsequent intermittent contraction of the airway smooth muscle (ASM) resulting in bronchoconstriction forms the hallmark of asthma. The ASM itself is exposed to various direct and indirect mediators that facilitate; depending on which surface receptor is activated; bronchoconstriction or bronchodilation. These mediators are usually released from activated inflammatory cells in and around the airway.

Similar effects on the ASM can occur by the activation or blocking of certain neurotransmitters at the neuromuscular junction.

Fig. 1.10 Airway smooth muscle responses to stimulation from airway epithelium

The “bronchoconstrictors”

Mediators Receptors Neurotransmitters Receptors Histamine H1 Acetylcholine M3 Leukotrienes Cys LT1 Substance P NK2 Thromboxane TP Calitonin gene – CGRP1 related peptide (CGRP) Prostaglandin D2 TP Neuropeptide Y Y2 Isoprostanes TP Cholecystokinin CCKA Platelet Activating PAF Factor Bradykinin B2

The “bronchodilators” Mediators Receptor Epinephrine β2 adrenergic Vasoactive peptide PVR1 Prostacycline EP Atrial natriuretic peptide cGMP (ANP) Nitric oxide cGMP Table 1.6 and 1.7 The bronchoconstrictor and bronchodilator mediators * Both tables adapted from: [248]

1.6.2 The mechanism of bronchoconstriction

The human respiratory tract normally has a degree of resting muscle tone that is maintained by the parasympathetic system via the neurotransmitter acetylcholine (Ach). This, in addition to the thickness of the mucosa determines the caliber of the airway lumen. As described in the tables above, there are various receptors on the muscle cell surface that respond to direct stimuli (e.g. histamine, methacholine, leukotriene) and indirectly (e.g. Allergens, adenosine, exercise) via mediators and neuropeptides released at the neuro-muscular junction. In terms of neural

58 bronchoconstriction, the cholinergic nerves, Ach and muscarinic receptors form the major mechanistic pathway for smooth muscle contraction.

A vast majority of the bronchoconstrictor receptors listed above bring about changes through intracellular signaling via G-protein coupling related to phosphatidyl-inositol hydrolysis[248].

Once activated by a specific mediator, these cell surface receptors are coupled to phospholipase C

(PLC) that in turn converts phosphinositide (4,5) biphosphate to inositol (1,4,5) triphosphate (IP3) or diacyl glycerol (DAC). Intracellularly, IP3 binds to the endoplasmic reticulum, which results in the rapid release of calcium. Calcium activates calcium/calmodulin-sensitive myosin light chain kinase (MLCK), which phosphorylates myosin, which in turn activates ATPase and brings about cross bridging and interlinking of the actin and myosin muscle fibers. This results in shortening of the myocyte and thereby muscle contraction and subsequent bronchoconstriction. IP3 is phosphorylated to IP4 [249] which opens the Ca channels and thus replenishes the intracellular

Ca stores.

1.6.3 The mechanism of bronchodilation

Bronchodilation takes place due to the relaxation of the airway smooth muscles. This can happen via direct action of potent endogenous bronchodilators such as nitric oxide (NO) and prostaglandin E2 (PGE2) as well as via soluble mediators. The most extensively studied receptor in bronchodilation is the β receptor. β receptors are present through out airway including the very small caliber airways. Activated β2 receptors and other bronchodilator protein receptors

(prostaglandin E2, vasoactive interstitial peptide (VIP) and atrial natriuretic peptide (ANP) get coupled (via G protein coupling) to membrane-bound adenylyl cyclase or guanylyl cyclase which increases cAMP and cGMP respectively. This activates protein kinase A (PKA) that phosphorylates serine and threonine residues and results in the opening of K+ channels leading to

59 a K+ efflux. The efflux of K+ out of the cell causes hyperpolarisation and subsequent relaxation of the monocyte and therefore, bronchodilation.

1.6.4 Use of anticholinergic agents in asthma

Traditionally, symptoms of asthma, namely wheeze, chest tightness and cough have been managed by a stepwise drug therapy strategy starting from the occasional short acting inhaled β2 agonist (e.g. salbutamol) to varying doses of combinations of inhaled corticosteroids (ICS) and long acting β2 agonists (LABA) (e.g. formoterol, salmeterol etc.) as well other add on therapeutic agents including recently developed monoclonal antibodies [5, 250]. The use of β2 receptor agonists has been a widely used, evidence based, practice [251]. Anticholinergic agents (e.g. ipratropium, glycopyronium, tiotropium etc.) have been used as bronchodilators in the management of COPD [252, 253] and have proven quite effective in the acute setting as well as long-term disease control. There has been growing interest regarding the role of anticholinergic agents in asthma. In the acute setting, β2 agonists (in the inhaled and nebulised) form have been preferentially used. However, given the biology of the airway smooth muscle as described earlier, the reasons why anticholinergic blockade is not as effective as β2 receptor agonism in asthma is not clear. Again, in an acute setting, whether there is a role for anticholinergics to be preferentially used in a select group of patients has not been studied. More recently, in patients who do not respond to conventional treatment (i.e. ICS +/- LABA), an interest has developed into the role of anticholinergic antagonism as a longer term strategy. An early Cochrane review of anticholinergic agents for chronic asthma in adults in 2004 [254] reported 13 studies comparing anticholinergics versus placebo and 9 studies comparing anticholinergics versus β2 agonists. The overall conclusion in 2004 was there was only a modest improvement in lung function compared to placebo and no significant superiority to β2 agonists. Therefore, at the time, their use in chronic asthma could not be justified, but the reviewer did question the quality of the studies. Since 2004,

60 a few more studies evaluating the role of anticholinergics in chronic asthma (in addition to

standard treatment) have been re-visited. They are summarized below:

Study (Year) Sample size, asthma severity Conclusions n = 107 Tiotropium + ICS/LABA vs. Placebo + ICS/LABA for Kerstjens et al. >GINA 2 Asthma 8 weeks. (2011)[255] Finding:

Trough and peak FEV1 higher in tiotropium group by 139 – 170 mls. n = 912 Two replicate trials: Tiotropium Respimat 5mcg +/- >GINA 2 Asthma ICS/LABA vs. placebo +/- ICS/LABA Kerstjens et al. 24 week treatment period (2012)[256] Finding:

Peak FEV1 higher in Tiotropium group and increased time to first exacerbation (21% risk reduction). n = 210 Data analysed from the TALC trial (Tiotropium as an >GINA 2 Asthma alternative to increased ICS in patients inadequately controlled on a lower dose of ICS) to assess predictors Peters et al. of response to Tiotropium. (2013)[257] Finding: Increased cholinergic tone, positive response to short acting β2 agonists and increased airflow obstruction predicted better response to Tiotropium. Ethnicity, sex, atopy, IgE level, FeNO, BMI and sputum eosinophil counts were not predictors. n = 174 Three- way cross over trial – Tiotropium + ICS vs. > GINA 2 Asthma double dose ICS and vs. ICS + Salmeterol. Peters et al. 14 week treatment period. (2010) [258] Finding: Increased peak flow rate (25.8 L/min) Reduced asthma symptoms

Increased post BD FEV1 n = 10 Double blind, 5 way, cross over study (3 doses of

61 GINA 1 Asthma glycopyrrolate, Ipratropium, placebo) to assess Hansel et al. protection against constrictor effects of Methacholine. (2005) [259] Finding: Prolonged bronchodilator response and protection against Methacholine induced bronchospasm with glycopyrrolate.

Table 1.8: Studies looking at evaluating the effect of anticholinergics in asthma in the non-acute setting.

Given these findings, the current management of asthma changed to include inhaled

anticholinergic agents in Step 4 or Step 5 [260]. Never the less, whether they are truly less

effective than β2 agonists needs to be confirmed. In this context, there exists the possibility that

there may be sub groups of patients with asthma who respond equally or better to anticholinergics.

The characteristics of these “responder” groups constitute a gap in knowledge and need to be

identified.

1.7 FUTURE OF ASTHMA MANAGEMENT AND SCOPE OF THIS THESIS

Realising the sheer extent of heterogeneity in asthma has completely revolutionised the

approaches evolving towards managing all spectrums of asthma. The “one size fits all” and “step

ladder” approach have may have had its role earlier, but with increasing knowledge of asthma

endotypes, identifying new biomarkers for disease activity, and developing novel therapeutic

agents targeting specific inflammatory pathways have all lead from a generic approach to more of

precision medicine. As not all patients respond identically to different treatments, correct patient

selection for specific treatments using clinical features, radiological images, physiological tests

and various blood, sputum, exhaled breath volatile organic compounds (future) biomarkers [261]

are becoming routine practice. Identifying responder groups to alternate therapies such as anti

62 muscarinic agents, leukotriene receptor antagonists, macrolide therapy, bronchial thermoplasty etc. still needs considerable development.

TSLP specific Mab: IL-13 specific Mabs: Tezepelumab Lebrikizumab Tralokinumab Anrukinzumab IL-17 specific Mabs:

Broadlumab Secukinumab IL-5 specific Mabs:

Mepolizumab Reslizumab Benralizumab

IL-4 specific Mabs:

Pascolizumab Pitrakinra Altrakincept Toll Like Receptor 7/9 Dupilumab therapies:

QbG10 Imiquimod IgE specific Mab: Resquimod

Omalizumab

Fig 1.11 – Novel drugs and their associated pathways in study. Omalizumab and Mepolizumab have already been licensed for use. Mab = monoclonal antibody

Novel potential therapeutic agents are constantly being trialed in early phase clinical trials and beyond. New molecules including bronchodilators, anti-inflammatories and monoclonal antibodies that target various inflammatory cells and pathways are currently being studied with

63 many more in pre clinical phases showing future promise. Appropriate patient selection, assessing drug effect and identifying stable reproducible biomarkers is integral to an effective clinical trial.

This thesis is all about developing more reliable information/knowledge that can help enhance, improve and facilitate clinical drug trials and thereby, contribute to the rapidly developing concept of future precision medicine in asthma. I will study the most commonly used study subject group in early phase clinical trials, the corticosteroid naïve population. I will explore their characteristics, sputum and physiological profile and the reproducibility of these measurements.

Increasing and/or verifying current knowledge in this domain will help in identifying select groups for targeted therapies and provide information about useful measurements that can be used as pharmacodynamic biomarkers. I will study patients with asthma associated with raised sputum neutrophils. I will assess observed characteristics of this population and relate them to existing limited knowledge. More importantly, with “anti-neutrophil” therapies in currently pre-clinical phases, the need to evaluate sputum neutrophil count reproducibility in the long term (of particular importance in larger latter phase trials) is vital to establish true drug effect. Finally, new inhaled bronchodilators +/- new devices are also continually being developed and evaluated in clinical trials. Selection of the right study target population is of paramount importance in order to attain the right outcomes. The “responder” population is often identified using certain common characteristics and biomarkers. I study the characteristics of the responders to anti-cholinergic agents and try to increase the volume of knowledge that can be used to identify the anticholinergic “responders” which can be useful both in future clinical trials involving these therapeutic agents and in clinical practice.

CHAPTER 2 - AIMS AND HYPOTHESES

2.1 Corticosteroid Naïve Asthma

The corticosteroid naïve asthma population is integral and core to providing the platform to study true airway inflammation. Various biomarker, proof of concept studies and clinical trials in asthma are based around this group.

Hypotheses:

 Symptom scores, airway physiological measurements and sputum/blood eosinophil and

neutrophil cell counts are reproducible in corticosteroid naïve asthma.

 Subgroups exist within the corticosteroid naïve asthma population which can be identified

on the basis of their physiological and sputum/blood characteristics.

 Lung clearance index (LCI) is a reproducible tool for the assessment of airway

dysfunction in patients with asthma.

Primary aim:

 To assess the reproducibility of symptom scores (ACQ-7, ACT), physiological

measurements (spirometry, reversibility, lung clearance index), FeNO, sputum

eosinophil/neutrophil cell counts and blood eosinophil counts.

Secondary aims:

 To characterise the corticosteroid naïve asthma population in terms of symptom control,

lung physiology and sputum inflammatory patterns.

 To examine/explore the possibility of the presence of subgroups within this population.

2.2 Neutrophils in Asthma

Neutrophilic asthma is classically associated with a more severe disease. There is a potential for new therapeutic agents to be developed against neutrophils or its mediators in the future. These novel therapeutic agents will need to undergo rigorous clinical trials. Sputum neutrophil counts could be used as a biomarker to measure disease activity and drug effect.

Hypotheses:

 Sputum neutrophil cell count has long term reproducibility and can be potentially used as a

stable/reliable biomarker in larger/longer studies/clinical trials.

Primary aim:

 To assess the long term reproducibility of sputum neutrophils in patients with neutrophilic

asthma.

Secondary aim:

 To explore the characteristics (symptom scores, atopic status, FeNO, spirometry,

reversibility, lung clearance index, impulse oscillometry and body plethysmography) of

patients (asthma) with raised sputum neutrophils and consider whether findings are in

keeping with current existing evidence.

2.3 Anticholinergic response in asthma

Short acting β2 agonists have been conventionally used as rescue medication in patients with symptomatic asthma. Short acting anticholinergic antagonists have been conventionally used as rescue medications in COPD. There is a widespread notion that β2 agonists are more effective than anticholinergics in asthma.

Hypotheses:

 In line with historical evidence, short acting β2 agonists are more effective than short

acting anticholinergic agents in asthma as rescue medication.

 There is a sub population of anticholinergic “responders” in asthma whose characteristics

can be identified.

Primary aim:

 To confirm or dispel the belief that short acting β2 agonists are more effective that short

acting anticholinergic agents.

Secondary aim:

 To identify the anticholinergic “responders” and assess their characteristics as compared to

the “non responders”.

CHAPTER 3 - METHODS

3.1 Subjects

All subjects for the 3 studies were recruited from the internal database of the Medicines

Evaluation Unit (MEU), University of South Manchester NHS Foundation Trust site, Manchester,

United Kingdom. The generic criteria for inclusion as listed in Table 3.1.

Generic Asthma Inclusion Criteria 1. Previous clinician proven asthma 2. Smoking history of <1 pack year 3. Not smoked in the last 12 months 4. No history of clinically diagnosed respiratory disorders except for asthma 5. No history of non respiratory inflammatory disorders 6. No use of antibiotics within 6 weeks of screening 7. No history of respiratory illness within 6 weeks of screening Table 3.1 Generic inclusion criteria for the 3 studies in this thesis.

All subjects with asthma on the database had a diagnosis of asthma based on the Global Initiative for Asthma (GINA 2015 guidelines) [260] which include a combination of classical symptoms of asthma (wheeze, shortness of breath, chest tightness, cough) and evidence of variable expiratory flow limitation (post bronchodilator reversibility or diurnal peak flow rate variation). Subjects recruited had current or historical data (within one year) showing bronchodilator reversibility of

200mls and/or 12% or a positive methacholine challenge with a PC20 cut off of ≤ 8 mg/ml.

Patients with any other co-existing respiratory conditions were excluded. Patients who had a history of unstable/brittle asthma were excluded. Written consent was obtained from each patient using protocols approved by the Greater Manchester Ethics Committees and was conducted in

68 accordance with the International Conference on Harmonization of Good Clinical Practice

Guideline and the Declaration of Helsinki.

For the 3 individual studies in this thesis (Chapter 4, 5 and 6), additional specific inclusion/exclusion criteria were used based on the aims and objective of the study.

Individual criteria include:

 Study 1 (Characteristics and Biomarker Reproducibility in Corticosteroid Naïve Asthma) . No history of previous use of any form of corticosteroids (inhaled, oral or parenteral).

 Study 2 (Exploring the Long-Term Reproducibility and Role of Neutrophils in Asthma)

. Previous documented historical evidence of a sputum differential cell count with sputum neutrophil percentage ≥ 50%.

 Study 3 (Role of Anticholinergic Therapeutic Agents in Asthma and Exploring the Characteristics of the “Responders”)

. No specific criteria apart from the generic criteria in Table 3.1.

3.2 Study Design

Patients adhered to the following restrictions prior to each visit of the study:

1) Withhold short acting bronchodilators (SABA) for ≥ 6 hours.

2) Withhold long acting bronchodilators (LABA) for ≥ 12 hours.

3) Withhold alcohol and certain foods ≥ 24 hours (lettuce, spinach, carrots, cured meats and

carbonated drinks.

4) Withhold caffeine for ≥ 2 hours.

Safety for all patients was assessed at each visit through physical examination, measurement of pulse-oximetry, heart rate and blood pressure. Occurrence of any adverse events (AEs) was monitored through out the studies.

69 Individual study designs are described in their respective chapters. An overview of patient recruitment is shown in Fig. 3.1.

Study 1 Characteristics and Biomarker Total Patient Reproducibility Recruitment in Corticosteroid Naïve Asthma

n = 30 n = 87*

Study 2 Exploring the Long-Term Reproducibility and Role of Neutrophils in Asthma

n = 19

Study 3 Role of Anticholinergic Therapeutic Agents in Asthma and Exploring the Characteristics of the “Responders”

n = 38

Fig 3.1 Patient recruitment overview * 2 subjects were very borderline with PC20 of 8.8mg/ml. These subjects were included based on work by Crapo et al. [262] who cited ROC curve analysis data showing the best PC20 cut off to separate asthma vs. not asthma is a range between 8mg/ml – 16mg/ml and work by Cockroft et al. [263] who concluded values up to 16mg/ml are “consistent but not diagnostic” of asthma while any value above 16mg/ml “rules out” the presence of the disease.

3.3 Study Procedures/Measurements

3.3.1 Asthma Control Questionnaire - 7

The Asthma Control Questionnaire -7 (ACQ-7) is a multidimensional questionnaire which allows the subjective measure of the severity of asthma symptoms. First developed in 1999, it has been shown to be a discriminative and reproducible measure of asthma control [264]. The ACQ-7 has 6 questions relying on the individual patient’s recall of the severity of his/her symptoms and use of rescue medications as well as a measure of pre-bronchodilator airflow limitation (FEV1) within the last one week. It has been validated against the Asthma Quality of Life Questionnaire (AQLQ) and the Medical Outcomes Survey Form -36 (SF-36) [264]. Patients were given the questionnaire

70 to read and mark the answers by themselves to avoid any bias. A score of ≥ 1.0 was taken as cut off for uncontrolled symptoms with a change of 0.5 indicating significant change in quality of symptoms [265].

3.3.2 Asthma Control Test

The asthma control test (ACT) is a similar patient self-administered tool used to identify those with uncontrolled asthma symptoms. It has 5 questions and requires a 4 – week recall of symptoms and daily functioning. Unlike the ACQ-7, there is no objective measure of airflow limitation. Since spirometry is not involved in the scoring system, it is more patient friendly.

Previous studies have shown good concordance with ACQ-7 [266]. A score < 20 indicates uncontrolled symptoms [267].

3.3.3 Fraction of Exhaled Nitric Oxide (FeNO)

Nitric oxide in the exhaled breath was measure using the NIOX Vero (Aerocrine, Solna, Sweden) at a flow rate of 50ml/sec and expressed as fractional exhaled nitric oxide at 50ml/sec (i.e.

FeNO50). Patients were required to withhold certain foods ≥ 24 hours (lettuce, spinach, carrots, cured meats and carbonated drinks) as these may affect readings and give false positive measurements. Patients were instructed to breathe out fully and then to inhale deeply after forming a tight seal around the mouthpiece. Without pausing, they exhaled at a steady flow rate until the measurement was completed. The mean of three acceptable manoeuvres within 10% of each other was recorded.

Fig. 3.2 Colleague demonstrating the use of Niox Vero at a flow rate of 50mls/sec for the measurement of FeNO

3.3.4 Lung Clearance Index

Lung clearance index (LCI) was measured straight after FeNO measurements and prior to any spirometry. LCI measurements using MBWN2 technique (multiple breath nitrogen washout) were performed as previously described by Jensen et al.[268] using an open circuit (Exhalyzer DH,

EcoMedics AG, Switzerland) and its associated software (SpirowareH 3.1, EcoMedics AG). The device uses an ultrasonic flow sensor (Spiroson1, Medical Technologies, Zurich, Switzerland) which contains two ultrasonic transducers mounted on opposite sides of the flow tube that emit ultrasonic pulses through inspired and expired air. The affected transit time of the ultrasound allows the measurement of flow and volume. Nitrogen is measure indirectly using Dalton’s law of partial pressures. Carbon dioxide and oxygen are measure using an infrared CO2 sensor

(CapnostatH 5, Respironics Novametrix, Wallingford CT, USA) and O2 analyser (Oxigraf Inc.

Mountain View CA, USA). The MBWN2 method does not require a wash in period and the switch from room air to pure O2 circuit is automatic. Subjects breath at steady tidal volume wearing a nose clip in sitting position. Once stable on the system, a switch from room air to a pure oxygen circuit was done automatically and the subject continued to the same breathing pattern

72 until the concentration of nitrogen reached at least 1/40th of the original concentration for a minimum of 3 consecutive breaths. A test was rejected if nitrogen spikes occurred due to cough or leak. The subjects were allowed to re-equilibrate in room air between tests with a rest time of 1.5 times the duration of the previous washout. The reproducibility of LCI required 3 separate tests that did not vary ≥ 10% with each other.

Dalton’s Law of Partial Pressures: Ptotal = PA + PB + PC

d b a c

Fig. 3.3 LCI Apparatus a = mouth piece, b = filter, c = ultrasonic transducers with CO2 and O2 flow meters, d = sidestream gas sampling line *Adapted from Horsley et al.[269]

Lung Clearance Index = Cumulative Expired Air / Functional Residual Capacity

3.3.5 Impulse Oscillometry

The impedance within the airway system (Z) was measured using impulse oscillometry

(Masterscreen impulse oscillometer; Erich Jaeger, Hoechenberg, Germany). The instrument was calibrated every morning prior to use with corrections made for temperature, barometric pressure

73 and humidity. Multiple frequency waveforms to the airway using a loudspeaker allow air flow to be generated from different pressure oscillations. The subjects were sat erect with a nose clip and hands supporting the cheeks to minimize upper airway shunting due to bulging out of the cheeks.

Impulses were applied at 0.2 second intervals during tidal breathing for 30 seconds. An impulse frequency range of 5 to 35Hz was used to determine resistance (R) and reactance (X) which are the two components of impedance (Z). Reactance is the energy stored as elastic recoil of surrounding lung tissue [270]. Wave propagation is dependent on the physiological size and compliance of the airways. Slower frequencies are transmitted much further along while higher frequencies are limited to the more proximal airways. It follows that resistance measured at 5 Hz

(R5) reflects total airway resistance and at 20 Hz, measurements reflect resistance in the proximal larger airways. The difference in measurements between the two (R5-R20) is used as a surrogate marker of peripheral small airway resistance. The difference inspiratory and expiratory reactance at 5 Hz (ΔX5) is used as a surrogate marker for expiratory flow limitation [271]. The mean value of 3 measurements were reported provided each of the 3 measurements did not vary greater than

10% from the mean value.

Fig.3.4 Colleague demonstrating the use of impulse oscillometry

3.3.6 Body Plethysmography

Body plethysmography uses the principles of Boyle’s Law to determine lung volumes and resistance to air flow. A constant volume whole body plethysmography was used (Autobox 6200

DL, Sensormedics, Yorba Linda CA, USA). It was calibrated and corrections made for temperature, barometric pressure and humidity. Application of Boyle’s law allows the measurement of airway resistance (Raw), specific conductance (sGAW), functional residual volume

(FRCpleth), vital capacity (VC), residual volume (RV), inspiratory capacity (IC) and total lung capacity (TLC).

Subjects sat inside the plethysmography (body box) with nose clip on and a seal around the mouth piece while supporting their cheeks. Measurement started with breathing at tidal volume until the baseline FRC is calculated. Subjects were asked to “pant” at a rate of approximately one breath per second to determine Raw. Once measured, the shutter closed to calculate thoracic gas volume

(VTG). The subjects then returned to tidal breathing followed by maximal inhalation to measure

IC, VC and calculation of TLC. A minimum of 3 manoeuvres were performed to determine at least 3 reproducible FRCpleth measurements with a mean value reported as per ATS/ERS guidelines [272]. A reproducibility criterion of +/- 5% from the mean value for FRC and TLC were applied.

Relevant plethysmography formulae:

1. Boyle’s Law

P1 x V1 = P2 x V2 where P1 = box pressure, V1 = Box volume, P2 = alveolar pressure and V2 = lung volume

2. TLC = FRC + highest IC

3. RV = TLC – highest VC

Fig. 3.5 Colleague demonstrating the use of body plethysmography

3.3.7 Spirometry and Bronchodilator Reversibility

Spirometry provides information regarding obstruction/restriction to air flow. Spirometry was measured using the Carefusion Micro Lab® spirometer. After daily calibration with a 3-litre syringe, subjects performed the procedure in a seated position with nose peg and forming a tight seal around the mouth piece. They were then instructed to inhale maximally and forcefully exhale until lungs were completely emptied. A minimum of three technically acceptable maneuvers (out of a maximum of 8 attempts) were required. The 2 highest FEV1’s and 2 highest FVC’s should be

≤ 150mls apart as per American Thoracic Society/ European Respiratory Society (ATS/ERS) guidelines [273]. Reversibility was assessed following administration of 400mcg of Salbutamol

(Ventolin Inhaler, Baker Norton, London UK) via a volumatic spacer. Post bronchodilator measurements of FEV1 and FVC were obtained 15 minutes post Salbutamol administration.

76 Reversibility with Ipratropium Bromide (Atrovent®) was tested in Study 3 (Chapter 6). Initial baseline spirometry was done using Carefusion MicroLab® spirometer. Reversibility was assessed following administration of 80mcg of Ipratropium Bromide (Atrovent®) via a spacer.

Post bronchodilator measurements of FEV1 and FVC were obtained 15 minutes after drug administration.

3.3.8 Methacholine Challenge (Bronchial Hyperreactivity –BHR)

Methacholine challenge was performed using pre-prepared Methacholine Chloride (Mch) sourced from Stockport Pharmaceuticals (Stepping Hill Hospital, Poplar Grove, Stockport, Cheshire).

Concentrations used were 0.03125, 0.06250, 0.125, 0.5, 1.0, 2.0, 4.0, 8.0, 16.0 and 32.0 mg/ml.

Contraindications to BHR testing included severe airflow obstruction (FEV1 < 50%), known aortic aneurysm and myocardial infarction/CVA within last 3 months.

A DeVilbiss 646 nebuliser pot was calibrated using an air source to an output of 0.13ml/min.

Baseline FEV1 measurements (best of 3) were taken. Subjects first undertook a “diluent” challenge, inhaling 0.9% saline for 2 minutes with a nose clip. FEV1 was then measured at 30 seconds and 90 seconds post inhalation. The best FEV1 measurement between the two was used to calculate the target FEV1 (i.e. a 20% drop). This step also served as a safety step to ensure subjects did not bronchoconstrict more than 10% of baseline. Subjects were then administered increasing concentrations of methacholine (see above) via the nebuliser pot using tidal breathing with nose clip for 2 minutes for each concentration. FEV1 was measured at 30 seconds and 90 seconds post inhalation. The highest FEV1 was used to calculate % change. Increasing concentrations of Methacholine was administered until FEV1 fell by 20% or more below the highest post-saline (diluent) value. Once this stage was achieved, no further methacholine was given and 4 puffs of 100mcg Salbutamol was administered via volumatic spacer. FEV1 was re-

77 checked 15 minutes later to ensure recovery to within 90% of baseline FEV1. If not, a further 400 mcg of Salbutamol was given and FEV1 checked again after 10 minutes.

PC20 calculation:

PC20 = antilog10 x [log10C1 + (log10C2 – log10C1) (20 – R1)] (R2 – R1)

C1 = the second to last concentration administered (< 20% fall in FEV1) C2 = the final concentration administered (inducing a ≥ 20% fall in FEV1) R1 = the % fall in FEV1 observed following C1 R2 = the % fall in FEV1 observed following C2

Fig 3.6 DeVilbiss 646 T Piece Style Nebuliser

For the purpose of my studies, a cut-off PC20 of 8mg/ml was used to confirm asthma and bronchial hyperreactivity. Two subjects were just above the cut off (PC20 8.8 mg/ml) but were included based on literature (see Fig. 3.1).

3.3.9 Sputum Induction

Sputum induction took place straight after post bronchodilator spirometry. Subjects inhaled 3 escalating concentrations of saline (3%, 4% and 5%). Saline was delivered by the EASY Neb II ultrasonic nebuliser (Flaem Nuova, Bresicia – Italy) at the maximum flow rate for the device (i.e.

0.55ml/min). Subjects inhaled the nebulised saline for 5 minutes at tidal breathing. They were instructed to blow their nose and rinse their mouths with water following which they attempted to expectorate. Safety spirometry (FEV1) was performed after each session. If the FEV1 had fallen ≤ post bronchodilator values, inhalation would proceed with the next incremental concentration of saline. If the FEV1 had fallen between ≥ 10% but ≤ 20%, inhalation would continue using the same concentration of saline. The procedure would be terminated if the FEV1 had fallen by ≥ 20% at any stage.

3.3.10 Sputum Processing and Cytospin Differential Cell Count

Samples were processed within 2 hours of expectoration. Sputum plugs were isolated manually and transferred to a pre-weighed 15mls Falcon Tube (BD Biosciences, Oxford, UK). The weight of the sputum plugs was calculated and 8 times volume of phosphate buffered solution (PBS)

(Sigma Aldrich, Poole, UK) were then added to the sample. This was vortexed for 15 seconds and then placed on a rocker for 15 minutes. The sample was then centrifuged at 790G for 10 minutes at 4oC. 4 volumes of PBS supernatant were then removed and micro centrifuged at 13000G for 10 minutes. The PBS supernatant was then aliquoted and stored frozen at -80oC. 4 volumes of 0.2%

Dithiothreitol (DTT) was then added to the sample. This was then rocked again for 15 minutes.

The sample was filtered through a 48μm nylon gauze (SEFAR, Heiden- Switzerland) to remove mucus and the filtrate collected in a pre-weight Falcon tube. Total cell count and %viability were determined using a Neubauer Haemocytometer and Trypan Blue stain (cells that had taken up the

79 blue stain were deemed non-viable). The filtrate was centrifuged at 790G for 10 minutes at 4oC.

The DTT supernatant was then removed and stored frozen at -80oC. The remaining cell pellet was re-suspended in an adjusted volume of PBS to yield a cell count of 0.5 x 106/ml. Cytoslides were made using a Cytospin 4® Cytocentrifuge (Thermo Shandon, Runcorn – UK).

The cytoslides were air dried, fixed in methanol for 30 minutes and then stained with Rapi-Diff®

(GCC Diagnostics, Sandyhurst, UK) to obtain differential cell counts. The DCC was performed by counting a total of 400 cells per cytospin. Total numbers of neutrophils, macrophages, eosinophils, lymphocytes and squamous cells were recorded and calculated as a percentage of total cells. For the purpose of this thesis, only the neutrophil and eosinophil counts were taken into account when analyzing data. For quality assurance, as per the Medicines Evaluation Unit standard operating procedure, every slide was counted by an independent second observer prior to reporting the differential cell count result. A variation of <5 % between the two observers was considered acceptable.

3.3.11 Peripheral Blood Sampling

24mls of blood was taken from each patient via ante-cubital fossa venipuncture using sterile technique. Blood was collected in tubes anticoagulated with EDTA and serum tubes. Both tubes were centrifuged at 1500G for 15 minutes at 4oC. The supernatants were collected from this and aliquots stored frozen at -80oC.

80 CHAPTER 4 – CHARACTERISTICS AND BIOMARKER REPRODUCIBILITY IN CORTICOSTEROID NAÏVE ASTHMA

4.1 Introduction

It has been long understood asthma is a heterogeneous disease resulting in various clinical and pathobiological phenotypes [158, 175, 274]. This heterogeneity has given rise to the need for developing targeted, personalised therapies [275], which offer better control of the disease. In more recent years, the development of novel pharmacological treatments for asthma has focused on patients who remain poorly controlled despite inhaled corticosteroid/long acting beta agonist

(ICS/LABA) treatment. These novel treatments are tested through robust clinical trials which measure asthma endpoints such as symptom control, spirometry and bronchial hyper-reactivity.

Drug effect can also be determined by the indirect measurement of airway inflammation through the use of biomarkers [143, 276]. Common biomarkers of inflammation and disease activity in asthma are FeNO [277] and blood/sputum cellular counts [177, 278] as well as basic lung physiology. It follows that the stability and reproducibility of these prognostic biomarkers is integral when it comes to target population selection and assessing true drug effect in the context of clinical drug trials.

Early phase asthma clinical trials (i.e. phase 1 and phase 2) often enroll individuals who are not using inhaled corticosteroids (and therefore – steroid naïve). These clinical trials enroll the steroid naïve (SN) asthma population as this group represents “true inflammation” which is not affected or confounded by steroid use. In this study I aim to characterise and gain a better understanding of the SN asthma population and explore relationships with validated clinical endpoints and biomarkers. More significantly, I aim to gain an understanding of the reproducibility of the clinical and laboratory characteristics of this group, which in the framework of drug development and clinical trials is of paramount importance. I specifically studied corticosteroid naïve asthma as

81 providing data and information could be used to design future early phase clinical drug trials and the reproducibility data could be used for power calculations (using the measurements as pharmacodynamics biomarkers). Finally I also analysed data and report on the possibility of distinct subgroups/phenotypes within the SN asthmatic population itself. Knowledge of the presence of subgroups and their common features would be useful in identifying biomarkers directed at specific target subpopulations which could be enrolled in drug trials.

4.2 Methods

4.2.1 Subjects and Study design

Thirty adult patients (mean age 40.33 years; SD 11.51 years) with a diagnosis of asthma and no previous exposure to corticosteroids (oral, inhaled or parenteral) were recruited. Patients were required to have <1 pack year smoking history and stable disease with not respiratory tract infections in the last 4 weeks prior to all study visits. All patients provided written informed consent and the study was approved by the local ethics committee.

Procedure for each measurement is described in detail in Chapter 3 (METHODS). At Visit 1, demographic data was collected and patients performed ACQ -7 score and ACT score to assess symptom control. Physiological assessments including spirometry, reversibility to 400μg

Salbutamol, FeNO and lung clearance index (LCI) using multiple breath nitrogen washout technique were carried out. Peripheral blood sampling was done for blood white cell differential counts. Induced sputum was processed for cytospin preparation and creation. Four hundred non- squamous cells were counted; absolute and differential cell counts were obtained.

At Visit 2, patients underwent a methacholine challenge to assess bronchial hyper-reactivity. A reproducibility visit (Visit 3) was conducted within one month of Visit 1 and all physiological, blood and sputum measurements were repeated. The one month (4 week) time point to assess reproducibility was chosen as a considerable number of early phase (Phase 1) clinical trials

82 designed to assess safety and gather early data on efficacy run for a period of one month and therefore, reproducibility data at this time point would be beneficial in this context.

Fig. 4.1 Consort diagram demonstrating the steps of the study

Fig 4.2 shows the steps and measurements taken at each visit. Visit 2 occurred within one week of visit 1 and visit 3 occurred within one month of visit 1. ACQ = Asthma control questionnaire, ACT = Asthma control test, LCI = lung clearance index, PC20 = provocative concentration required for a force expiratory volume (1st second) to fall by 20%, FeNO = fraction of exhaled nitric oxide

83 4.2.2 Statistical analysis

Normality was determined by using Kolmogorov Smirnov tests. Data was presented as mean

(standard deviation) or geometric mean (95% confidence intervals). Reproducibility between

Visits 1 and 3 were analysed using the Bland Altman method with bias (mean difference) and

95% limits of agreement (Graphpad Prism version 6.0). Intraclass correlation coefficients (ICC) were analysed using SPSS (version 22.0). A Ri value of ≥ 0.40 indicates good agreement, while

> 0.75 indicates excellent agreement [279]. ICC analysis requires data to be parametric, so log transformations were performed where appropriate. A p value ≤ 0.05 was deemed significant.

Correlations were performed using Spearmann Rank tests. Mann Whitney U tests were used to compare non-parametric data when analyzing subgroups.

4.3 Results

Subject characteristics:

Thirty steroid naïve asthmatics were studied for characterisation purposes. Twenty-three produced sputum at Visit 1. Twenty-two patients completed the repeatability visit. Twelve patients produced sputum on both visits. Demographic, physiologic, blood and sputum characteristics are outlined in Table 4.1. Overall sputum cell distribution showed no predominant cell line (Fig. 4.3).

Of these, the majority of samples were paucigranulocytic (70%), while 17% was eosinophilic (cell count ≥ 3%), 9% neutrophilic (cell count ≥ 60%) and 4% of mixed cellularity.

Fig. 4.3 Induced sputum cell distribution at baseline screening visit.

Reproducibility of measurements:

Excellent reproducibility was seen (in terms of Bland Altman mean difference and intraclass correlation coefficients (Ri)) with symptom control (ACQ-7 Ri =0.74, ACT Ri = 0.89), airway physiology (FEV1% Ri = 0.92, Reversibility% Ri = 0.43, lung clearance index Ri = 0.94), FeNO

(Ri = 0.94), blood eosinophil Ri = 0.84 and sputum eosinophil counts (sputum percentage Ri =

0.71, absolute count Ri = 0.77). Sputum neutrophil counts do not demonstrate acceptable reproducibility (Table 4.2) (Figs.4.4 – 4.9).

Table 4.2 Reproducibility of measurements in corticosteroid naïve asthma. 1 ICC ≥ 0.4 considered good reproducibility. Values ≥ 0.75 considered excellent. * On a natural logarithm scale The differences between variables between visits 1 and 3 were either normally distributed or approximately normally distributed. Therefore, Bland-Altman analysis was performed on un transformed variables.

86 Graphical representation of reproducibility data using Bland-Altman plots:

A B

ACQ-7 Reproducibility ACQ - 7 Reproducibility

t n 3 e Bias: -0.007 (SD 0.42) m 1.5

s a 1.0 2

0.5 c

A 1 o 0.0

w t 0.5 1.0 1.5 2.0 2.5

-0.5

c 0 n 1 3 e -1.0 r it it e is is f V V

f i Mean of two ACQ-7 measurements

D C D

ACT Reproducibility ACT Reproducibility

n 30 e Bias: 0.44 (SD 1.55) m 6

a 4 20

2 c

A 10 o 0

t 10 20 30

-2

c 0

e 1 3 r -4 Mean of two ACT measurements it it e is is

f V V

Fig. 4.4 Bland-Altman Plot of the agreement between visits of ACQ-7 (A) and ACT (C). The central dotted line represents the mean difference (bias), and upper and lower dotted lines represent the limits of agreement (mean difference +/- 2 SD). Figures (B) and (D) represent the true graphical representation of the measurements at each visit.

A B

FEV1% Reproducibility FEV1% Reproducibility

t 150

e Bias: 0.20 (SD 5.31)

e 15

s 100

a 10 %

5 E

F 1 50

E 0

80 100 120 140 o -5

f 0

-10 1 3 e it it c is is n -15 V V

e r Mean of two FEV % measurements

e 1

C D

Reversibility (%) Reproducibility Reversibility (%) Reproducibility

Bias: -1.36 (SD 6.02)

% 30

t 20

i s 10

n 20

e 0 i

o 5 10 15 20 25

s -10

o 10

m c -20

f f -30 Mean of two Reversibility % i 0

D measurements 1 3 IT IT IS IS V V

Fig. 4.5 Bland-Altman Plot of the agreement between visits of FEV1% (A) and Reversibility% (C). The central dotted line represents the mean difference (bias), and upper and lower dotted lines represent the limits of agreement (mean difference +/- 2 SD). Figures (B) and (D) represent the true graphical representation of the measurements at each visit.

A B LCI Reproducibility LCI Reproducibility 15 s Bias: - 0.09 (SD 0.37)

m 1.0

r u 10

s a 0.5

L 0.0 5 o 5 10 15

o -0.5

n 0

e r -1.0 1 3 e t t f i i f s s i i i V V D Mean of two LCI measurements C D

FeNO Reproducibility

s FeNO Reproducibility

n Bias: -1.36 (SD 7.41) e 150

e 20

10 b 100

e 0 N

50 100 150 F 50

f -10

c 0

e -20 1 3

r it it e s s f i i f V V i Means of two FeNO measurements

Fig. 4.6 Bland-Altman Plot of the agreement between visits of LCI (A) and FeNO (C). The central dotted line represents the mean difference (bias), and upper and lower dotted lines represent the limits of agreement (mean difference +/- 2 SD). Figures (B) and (D) represent the true graphical representation of the measurements at each visit.

A B

Sputum Neutrophil (x106/g) Reproducibility Sputum Neutrophil (x106/g) Reproducibility

n u Bias: 9.17 (SD 65.49)

)

l 250

6 h 150

1 o 200

(

100

50 p 150

m t

u 0 e 100

s 50 100 150 200 250

o -50

u 50

-100 p

S 0

e c -150 1 3 n IT IT

e r Mean of two sputum neutrophil count IS IS e V V

i measurements

C D

Sputum Neutrophil % Reproducibility Sputum Neutrophil % Reproducibility

l i Bias: 3.74 (SD 17.53) 80

p 40

t l

h 60

t 20

t e 40

p r 0

s 20 40 60

t a 20

m -20

c 0 n 1 3 e -40 Mean of two sputum neutrophil % r IT IT e S S f measurements I I f V V

Fig. 4.7 Bland-Altman Plot of the agreement between visits of Sputum Neutrophil (106/g) (A) and Sputum Neutrophil % (C). The central dotted line represents the mean difference (bias), and upper and lower dotted lines represent the limits of agreement (mean difference +/- 2 SD). Figures (B) and (D) represent the true graphical representation of the measurements at each visit.

A B

Sputum Eosinophil (x106/g) Sputum Eosinophil (x106/g) Repeatability

)

g Reproducibility / N = 11

1 200

(

Bias: 1.5 (SD 8.06)

i 20 )

o 150

1 i 10

(

0 h 100

e u 50 100 150 200

p -10

a s 50

t -20

f Mean of two sputum

t 6 0

u e -30 eosinophil (x10 /g)

p c 1 3

n measurements S IT IT

e S S

r I I V V

C D

Sputum Eosinophil % Reproducibility Sputum Eosinophil % Reproducibility

Bias: 0.40 (SD 1.96) 50

i o 4 40

o 2 o

n t 30

o t 0

p 10 20 30 40 r 20

o -2

m 10

o -4

n Mean of two sputum eosinophil % 0 e -6

e measurements 1 3 f

f i IT IT

D IS IS V V

Fig.4.8 Bland-Altman Plot of the agreement between visits of Sputum Eosinophil (106/g) (A) and Sputum Eosinophil % (C). The central dotted line represents the mean difference (bias), and upper and lower dotted lines represent the limits of agreement (mean difference +/- 2 SD). Figures (B) and (D) represent the true graphical representation of the measurements at each visit.

A B

Bland-Altman of Blood Neutrophil Count Repeatability Blood Neutrophil (x109/L) Repeatability Bias: 0.23 (SD 0.61) N = 16 3 10

8 2

L 6

1 0

f x 4

D 0 2 4 6 8 2

-1 0 Average 1 2 IT IT IS IS V V C D

Bland-Altman of Blood Eosinophil Count Repeatability Blood Eosinophil (x109/L) Repeatability N = 16 Bias: - 0.02(SD 0.10) 0.8 0.3 0.6 0.2

e 0.1 9

c 0 0.4

r 0.0

f 0.2 0.4 0.6 0.8 i 0.2

D -0.1

-0.2 0.0 1 2 -0.3 Average IT IT IS IS V V

Fig. 4.9 Bland-Altman Plot of the agreement between visits of FEV1% (A) and Reversibility% (C). The central dotted represents the mean difference (bias), and upper and lower dotted lines represent the limits of agreement (mean difference +/- 2 SD). Figures (B) and (D) represent the true graphical representation of the measurements at each visit.

92 Measurement correlations

Significant correlations were seen between blood eosinophil count and FeNO (r = 0.42, p = 0.03), sputum eosinophil count and FeNO (r = 0.51, p = 0.02) and between sputum eosinophil and blood eosinophil counts (r = 0.57, p = 0.007) (Fig.4.9). In terms of symptom control, significant correlations were seen between ACQ-7 and FEV1% (r = -0.44, p = 0.02) and between ACQ-7 and

Reversibility (%) (r = 0.43, p = 0.02). There was also a clear correlation between the two symptom questionnaires (ACQ-7, ACT: r = -0.75, p <0.001) (Fig.4.10). No correlations were seen between ACQ and FeNO or sputum eosinophil count. Lastly, there were significant correlations between lung clearance index and FEV1% (r = -0.60, p = 0.002) and reversibility% (r

= 0.46, p = 0.02) (Fig.4.11).

Blood Eosinophil - FeNO Sputum Eosinophil - FeNO 1.0 r = 0.42 150 r = 0.51

6 p = 0.03 0 p = 0.02

1 0.8

h 100

p p 0.6

o 0.4

o 0.2

B 0.0 0 0 50 100 150 200 250 0 0.01 0.1 1 10 100 FeNO ppb Sputum Eosinophils (%)

Sputum Eosinophil - Blood Eosinophil 0.8 r = 0.57

0 p = 0.007

0.6

i 0.4

d 0.2

B 0.0 0 0.01 0.1 1 10 100 Sputum Eosinophil (%)

Fig. 4.10 Sputum and blood eosinophil correlations

93 A ACQ- ACT Correlation B ACQ - Reversibilty correlation 30 r = -0.75 r = 0.43 p < 0.001 p = 0.02 25 30

)

(

C 20 t 20

15 e 10

R 10 0 0.0 0.5 1.0 1.5 2.0 2.5 0.5 1.0 1.5 2.0 2.5 ACQ ACQ -10

Fig. 4.11– ACQ correlations

LCI - Reversibility correlation

LCI - FEV1 correlation A B r = 0.46 p=0.02 140 r = -0.60 30 p= 0.002

)

120 %

(

) 20

(

100 i

v 10

80 e

60 0 0 5 10 15 0 5 10 15 LCI LCI

LCI -BMI correlation Fig. 4.12 – LCI correlations withC airway physiology r = 0.50 p= 0.01 40

M 20 B

0 0 5 10 15 Subgroup analysis LCI

In this study, I hypothesised that within the corticosteroid naïve asthmatic population, there may exist subgroups or subphenotypes. In many clinical drug trials, symptom control is a common endpoint that is used as a marker of drug effect. Furthermore, in those trials where pharmacological agents targeting the TH2 endotype are used, sputum eosinophil counts are used as

94 the primary endpoint as a measure of drug effect. Pharmacodynamic and physiological biomarkers may aid in identifying these target groups and would useful during patient selection and recruitment. In this study, the study population was divided into two groups based on symptom control (good control: ACQ-7 < 1, suboptimal control: ACQ-7 ≥ 1) [265] and sputum eosinophil counts (high eosinophil group: eosinophil% ≥ 3%, low eosinophil group: eosinophil%

< 3%). Several selected measurements were analysed to explore where there were any significant differences between the groups. These results are tabulated in Tables. 4.3 and 4.4.

Table 4.3 – Differences between symptom controlled group (ACQ-7 <1) and suboptimal control group (ACQ -7 ≥1) * Parametric data presented as mean (SD) and analysed using unpaired student’s t test. a Non parametric data presented as median (interquartile range) and analysed using Mann Whitney U test.

Table 4.4 – Differences between “high eosinophil” group (sputum eosinophil% ≥ 3%) and “low eosinophil” group (sputum eosinophil% < 3%) All data were nonparametric and presented as median (interquartile range) and were analysed using Mann Whitney U test.

4.4 Discussion

This study focuses on adding to the limited knowledge of the characteristics of steroid naïve asthma which is a common target population in early phase clinical trials. Particular emphasis was given to studying the reproducibility of measurements and evaluating lung clearance index which is emerging as a future tool for measuring early airway dysfunction and as a potential pharmacodynamic biomarker to be used in clinical trials.

On the whole, the study population demonstrates adequate symptom control (mean ACQ 0.65, mean ACT 21.29) and good airway physiology (mean FEV1 90.43%). This is consistent with the notion these are “mild asthmatics”. While there is a paucity of previous studies exploring the characteristics of corticosteroid naïve asthma, Lee et al. [190] explored the sputum characteristics.

96 They described an eosinophilic pattern in 70.6% of their study population. In my study population, 16 out of 23 (70%) asthmatics had a paucigranulocytic pattern of inflammation while

17% were eosinophilic. I believe these results represent a more true characterisation of the sputum cell distribution in these mild asthmatics. While my study participants came from entirely varied and different environments, Lee’s study population were confined and limited a small island city in Brazil whose characteristics may be influenced by local surroundings. Furthermore, we have gone on to substantiate our results with clinical parameters. Our mean ACQ-7 (0.65 – showing good symptom control) and FeNO (34.30 ppb) both do not point towards a predominant eosinophilic pattern of disease. While the American Thoracic Society (ATS) clinical practice guidelines [277] sets a cut off of “high FeNO” as >50ppb, Schleich et al. have demonstrated a threshold as low as 42ppb as a significant cut off level to discriminate between eosinophilic and non-eosinophilic asthma. This is still higher than the measured mean value in my study. However, that being understood, it must be not overlooked that just under 20% of this study participants had a sputum eosinophil level ≥ 3% which does suggest the presence of a subgroup which follows a

T2 pattern of inflammation. Furthermore, despite mild symptoms and normal spirometry, a significantly low PC20 (mean 1.05) [263] indicates considerable airway hyper-responsiveness.

Mean lung clearance index (7.63) is above the accepted normal range of 7-7.3 in healthy controls in previous studies [280, 281]. On a backdrop of a normal mean FEV1 in these so-called “mild asthmatics”, this finding is of significant relevance and adds to the body of knowledge that, by measuring ventilation inhomogeneity in small airways, LCI is a more reliable marker of early dysfunction in the “silent phase” [282] between the onset of disease and detection of this with standard spirometry.

A key objective of this study was to determine the reproducibility of physiological and sputum/blood characteristics of steroid naïve asthmatics. The Asthma Control Questionnaire and

Asthma Control Test have been tested previously for validity and responsiveness [266, 283, 284].

97 The data in this study shows evidence of good reproducibility of the ACQ-7 and ACT in steroid naïve asthmatics. This is of particular importance as these questionnaires are often used as benchmarks in measuring symptom control in clinical drug trials. While FeNO has been used as a marker of eosinophilic inflammation [277], in a broader sense, it is a marker of T2 inflammation as nitric oxide synthase is predominantly induced by IL-13. My results concur with that of

Purokivi [201] and Kharitnov [200] both of whom demonstrated that FeNO as a measurement was reproducible. However, in these studies, reproducibility was checked 24 and 48 hours later respectively. My study provides evidence FeNO has excellent reproducibility when checked even one month apart.

The study data suggests, in steroid naïve asthmatics, the reproducibility of sputum eosinophil counts is reproducible with higher levels of agreement. This is consistent with many previous asthma studies which explored sputum cell count reproducibility [191-194, 196]. However, most studies enrolled patients with varying levels of disease severity and inhaled corticosteroid use.

Furthermore, reproducibility visits were within days or few weeks from the initial visit in these studies. My study focuses purely on the steroid naïve population and tests reproducibility at one month. Clinical trials of novel anti-eosinophilic therapies often need prolonged duration of at least one month to assess drug efficacy and these results indicating little or reasonable variation in sputum eosinophil count is therefore significant.

My results, however, show a large variation in sputum neutrophil counts and little reproducibility.

Reviews on neutrophilic inflammation [168, 175, 177, 224, 225] in asthma all point towards a relationship between neutrophilia and more severe airflow obstruction, gas trapping and corticosteroid resistance. Therefore, interest in developing biomarkers for neutrophil driven inflammation and anti-neutrophil therapies is evolving. Previous sputum reproducibility studies

[191, 193-196] have shown moderate to good agreement and intraclass correlation for neutrophils.

98 In fact, Pizzichini [193] and Bacci [191] have reported Ri = 0.81 and Ri = 0.85 respectively. This is in stark contrast to our values (absolute neutrophil count Ri = 0.14, neutrophil % Ri = 0.006). I believe this gross difference is probably directly due to the characteristics of our study population.

While previous studies incorporated an eclectic mix of mild to moderate to severe asthmatics on and off inhaled corticosteroids, my group comprised exclusively of steroid naïve patients with the milder spectrum of disease. As neutrophilic activity is associated with more severe disease, neutrophil levels are likely to be more consistent in those leaning towards the severe end.

Furthermore, the influence of inhaled steroids locally may affect sputum neutrophil transport and recruitment. In my steroid naïve population, this steroid effect is not a factor.

Lung clearance index (LCI) is a novel investigative method that has been developed over the last few years to assess early airway disease working on the premise airway inflammation and subsequent disease in peripheral airways in a ventilation homogeneity [285] which can be used as a surrogate marker of early airway dysfunction. While reviews by Horsley [282], Kent [286] and

Rowan [287] have identified a relationship between LCI and cystic fibrosis and CF related bronchiectasis, its role is asthma is not entirely clear. Data on the usefulness of LCI as a measure of airway dysfunction in asthma is very limited. Zwitserloot et al. [281] demonstrated increased

LCI compared to controls in paediatric asthma and Gustafsson et al. [288] showed abnormal LCI in post bronchodilator measurements in a similar population. My reproducibility measurements virtually mirror Rowan’s work [287] with both our intraclass correlation coefficients measured at

0.94. While Rowan measured LCI in patients with stable bronchiectasis in a two week interval, this study provides evidence of similar reproducibility in steroid naïve asthmatics when measured a month apart. This is promising for future research work related to asthma and indicates LCI has the potential to be used as a surrogate outcome measure in clinical drug trials.

99 I have shown a number of significant associations in relation to symptom control, lung physiology and laboratory parameters. Using the ACQ-7 as a marker of symptom control, I have shown a negative correlation with FEV1% (r = -0.44, p = 0.22) and a positive one with reversibility (%)

(r = 0.43, p = 0.02) respectively. Jia et al. [289] conducted a meta-analyses of diagnostic accuracy studies of ACQ and ACT which concluded both questionnaires perform well in distinguishing between controlled and uncontrolled disease in mild to moderate asthmatics and less so towards the more severe spectrum when cut-off values are predetermined. The relationships between

ACQ-7 and FEV1% as well as reversibility % in our results are consistent with this. Data from this study goes on to demonstrate concordance with ACQ-7 and ACT (r = -0.75, p <0.001). This again is in line with previous studies [266, 290]. Although the ACT is more clinician friendly, we chose the ACQ-7 as a benchmark for asthma control as it is most often used in clinical trials and pharmacological studies (of which steroid naive asthmatics are a common target) to measure drug effect. The relationship between eosinophilia and FeNO has historically been a contentious one

[291]. While various studies in asthmatic children and adults have shown significant correlation between FeNO versus peripheral blood and sputum eosinophils[292-295] others have not been as encouraging [296-298]. Our study results add to the volume of evidence suggesting an association between exhaled nitric oxide and eosinophil counts (r = 0.51, p = 0.02).

Of particular importance is the significant correlation between LCI and airway physiology (LCI vs. FEV1% r = -0.60, p =0.02). My result here is in concordance with previous studies exploring the LCI in CF and non-CF bronchiectasis[286] re-enforcing the fact that LCI is a valid measurement of airway dysfunction and in many cases, more sensitive than FEV1 [299-302] as described earlier.

Further analysis of our data was done to explore whether subgroups exist within the study population. We chose symptom control (ACQ-7 ≥ 1 = sub optimally controlled asthma; ACQ-7 <

100 1 = controlled asthma) and sputum inflammamometry represented by eosinophil counts (≥ 3% vs.

< 3%) as potential sub groups to study. These were chosen as often these endpoints and biomarkers are used as measurements of drug effects in asthma related clinical drug trials. In terms of symptom control, I demonstrate (Table 4.3) a trend where sub optimally controlled asthmatics have an earlier age of onset of symptoms, poorer spirometry, more reversibility and bronchial hyper-responsiveness as well as increased blood and sputum eosinophils as compared to those with better controlled asthma. Similarly, in terms of sputum eosinophils, I show (Table 4.4) a trend where, those with increased sputum eosinophils tend to develop symptoms earlier, have poorer symptom control, have increased bronchial hyper-responsiveness and higher FeNO, lung clearance indices and peripheral blood eosinophils. I recognise statistical significance has not been achieved with most of these parameters, but this is likely due to the relatively small study population and subsequent n numbers in individual groups. Some measurements are bordering statistical significance and a larger study may prove more conclusive, However, I present early data which suggests these sub populations may exist and the relevant measurements could be utilised as biomarkers for each group but clearly needs larger studies to draw definite conclusions.

101 CHAPTER 5 – EXPLORING THE CHARACTERISTICS AND LONG TERM REPRODUCIBILITY OF INCREASED SPUTUM NEUTROPHILS IN ASTHMA

5.1 Introduction

As discussed in earlier sections of this thesis, the role of neutrophils in the orchestra that is asthma pathobiology is contentious, unclear and not thoroughly studied. The essential conundrum is the debate as to whether the presence of neutrophils in lung tissue and airways actively contributes to the disease process or whether their presence is the result of secondary consequences of the inflammatory process. Kamath et al. [303] point out, as the knowledge of the heterogenic nature of asthma develops; it becomes increasing evident that eosinophils cannot be the sole key effector cell in asthma. There are many reasons for this: (a) eosinophilic driven inflammation is seen in half of the asthmatic population [304] and raises the question as to what could be the driving mechanism(s) for the other half , (b) Brightling et al. [225] have shown even in severe eosinophil lead inflammation as in eosinophilic bronchitis, the definite symptoms of asthma do not always occur, (c) a significant proportion of asthma related exacerbations occur with out an increase in tissue eosinophils [303] and more recently and importantly, (d) direct anti-eosinophil therapies and clinical trials have improvement in physiology and symptom control, but only in very selective severe patients [305-307]. These issues have resulted in a renewed interest in neutrophil biology related to asthma.

Although described in further detail in Chapter 1, a strong association has be now been established between neutrophilic inflammation and more severe asthma [75, 167] along with evidence pointing towards more significant airflow limitation, more severe exacerbations and corticosteroid resistance [158, 177, 224, 226]. These effects are mediated through various key chemical mediators released by activated neutrophils. IL-8 is a powerful cytokine associated with

102 neutrophil chemoattraction. Shannon et al.[308] and Pepe et al. [309] have shown IL-8 is significantly elevated (and upregulated) in severe asthma. Furthermore, neutrophil generated proteases including matrix metalloproteinaise (MMP-9) and elastase, lipid mediators such as leukotriene B4 and platelet-activating factor (PAF), oncostatin, tumour necrosis factor α (TNF α)

- and superoxide anions (O2 ) all have been shown to play a role significant role in bronchial hyper- responsiveness, airway remodeling and interestingly, increased transmembrane migration of eosinophils [168, 310, 311]. IL-17, generated predominantly by TH17 lymphocytes also plays an integral role as it has been shown to induce neutrophilic inflammation. Barczyk et al. [312] and

Al-Ramli et al. [93] have both shown IL-17 sputum concentration and expression in the airways is increased and correlates with severe asthma.

Given the increasing evidence for the role neutrophils may be actively involved in airway inflammation, the impetus to identify biomarkers for neutrophilic activity, identify therapeutic targets and develop pharmacological agents to combat this is also increasing. Nakano et al. [313,

314] have shown dopamine released by dendritic cells is involved in and promotes TH17 cell differentiation. A generic dopamine receptor antagonist (D1 like-R antagonist), labeled as

SCH23390, has shown to suppress neutrophil airway inflammation in T cell receptor-transgenic mice [315]. Theophylline is a commonly used methylxanthine and phosphodiesterase inhibitor. It allows for bronchial smooth muscle relaxation and therefore, combats bronchoconstriction. Kraft et al. [316] have demonstrated, in BAL fluid from patients with nocturnal asthma, theophylline suppresses eosinophil and neutrophil levels in vivo. It is postulated the mechanism may be the attenuation of neutrophil dependent eosinophil migration as discussed earlier [317]. While these studies are promising, a further understanding of the physiological impact and reproducibility of neutrophils in the airway is still needed in the hope this knowledge may, in the future, give rise to new biomarkers or measurements which can be used as endpoints in clinical trials of anti- neutrophil therapeutic agents.

103 In this study, the aims were:

Primary aim:

1. To assess long-term reproducibility of sputum neutrophilia.

Secondary aim:

2. To explore symptom control and lung physiology of asthmatic patients with a previous

documented history of raised sputum neutrophils (≥ 50%).

5.2 Methods

5.2.1 Study subjects and study design

Nineteen asthmatics with a previous sputum differential cell count of neutrophils ≥ 50% on the

Medicines Evaluation Unit database were recruited. Given the ambiguity, uncertainty and inconsistency surrounding what constitutes “sputum neutrophilia”, the cut off of ≥ 50% was chosen as a realistic value based on available literature. While Belda et al. [240] demonstrated sputum in healthy non-smokers had neutrophil levels varying from 37% to 39% and Moore et al.

[241] indicated a cut off of 40% was used the Severe Asthma Research Programme (SARP) cluster analyses, other studies used cut offs >60% as a standard for neutrophilia [239, 278, 318].

During the study visit, demographics, symptom control (using the ACQ-7 and ACT questionnaires), spirometry including body plethysmography, post bronchodilator reversibility, lung clearance index, FeNO and impulse oscillometry (IO) measurements were taken. Induced sputum was then processed and cytospin slides for differential cell count were made. The slides were stained (Rapi-Diff®) and 400 cells per cytospin were counted. The methods used are described in detail in Chapter 3.

104 Inclusion Criteria: Study Visit * Demographics 1. Diagnosis of asthma. * Symptom Control 2. Previous historical  ACQ – 7 sputum neutrophil count  ACT of ≥ 50%. * Airway Physiology 3. No change in  Spirometry medications since  Body Plethysmography historical count was done  Reversibility 4. Smoking history ≤ 10  LCI pack year history.  Impulse Oscillosmetry 5. No history of * FeNO respiratory infection or * Sputum induction/processing/ exacerbation of airways cytospin staining and differential disease with last 4 weeks. cell counts

Fig. 5.1 – Study design

5.2.2 Statistical analysis

Normality was determined by using Kolmogorov Smirnov tests. Data was presented as mean

(standard deviation) or geometric mean (95% confidence intervals). Reproducibility between previous historical neutrophil counts and the current study counts were analysed using the Bland

Altman method with bias (mean difference) and 95% limits of agreement (Graphpad Prism version 6.0). Intraclass correlation coefficients (ICC) were analysed using SPSS (version 22.0). A

Ri value of ≥ 0.40 indicates good agreement, while > 0.75 indicates excellent agreement [279]. A p value ≤ 0.05 was deemed significant. Correlations were performed using Spearmann Rank tests.

Student t tests were used to compare non-parametric data when analysing groups based on different cut off levels.

105 5.3 Results

Subject Characteristics

Nineteen asthmatic patients with a previous historical documentation of sputum neutrophil count

≥ 50% were recalled/recruited. Mean age was 51 (SD 12) and the male to female ratio was 4:1.

Thirteen patients were on inhaled corticosteroids and six were corticosteroid naïve. Mean interval between historical sputum neutrophil cell count and current study visit was 45 months (range 9.5

– 72.5). Mean ACQ-7 and ACT scores were 1.3 (SD 0.83) and 20 (3.2) respectively with cut off scores ≥ 1.0 and ≥ 19 taken as indication of sub-optimal symptom control for ACQ-7 and ACT respectively. Other physiological characteristics in terms of air flow limitation, reversibility, small airways resistance, expiratory flow limitation, ventilation inhomogeneity, gas trapping, FeNO and sputum cell characteristics are tabulated in Table 5.1.

Table 5.1- Baseline characteristics of study subjects Data presented as mean (SD) or ageometric mean (95% confidence interval). ACQ = Asthma control questionnaire, ACT = Asthma control test, FEV1 = forced expiratory volume in first second, FeNO = fraction of exhaled nitric oxide, LCI = lung clearance index, RV = residual volume, RV/TLC = Residual volume/total lung capacity, R5-R20 = difference between airway resistance measure a 5Hz and 20Hz, delta X5 = difference between inspiratory and expiratory reactance measured by impulse oscillometry

106 Long term reproducibility of sputum neutrophils

As described earlier, mean interval between historical sputum neutrophil cell count and current study visit cell count was 45 months (range 9.5 – 72.5). Mean difference for sputum neutrophil count (x106/g) and neutrophil percentage were 49.26 and 12.8 respectively. This is graphically shown in a Bland-Altman plots (Fig.5.2 and Table 5.2). Reproducibility in terms of intraclass correlation coefficients (ICC) for sputum neutrophil count (x106/g) and neutrophil percentage were 0.07 and 0.06 respectively.

A B Sputum Neutrophil (x 106/g) Reproducibility Sputum Neutrophil (x 106/g) Reproducibility

i Bias 49.26 (SD 79.26)

h ) 400

r 300

t ( 300

200 i

r u 100 200

m 100

t 100 200 300 400

o t

e -100

S n 0

e r -200 it it e s s

f i i

f V V i l 6/ a y D Mean of two sputum neutrophil count (10 g) c d ri tu measurements to S is H

C D

Sputum Neutrophil % Reproducibility Sputum Neutrophil % Reproducibility

i Bias 12.8 (SD 19.94)

p 100

o 80

e 60 i 80

40 o

t 60

20 e

a 40 w 0

m 20 40 60 80 100

-20 u e 20

n S

e -40

f 0

i Mean of two sputum neutrophil % it it D measurements is is V V l a y c d ri tu to S is H Fig.5.2 Bland-Altman Plot of the agreement between visits. The central dotted represents the mean difference (bias), and upper and lower dotted lines represent the limits of agreement (mean difference +/- 2 SD). Figures (B) and (D) represent the true graphical representation of the measurements at each visit.

107

Table 5.2 Mean difference, within subject standard deviation and ICC for sputum reproducibility between historical visit and current study visit. 1 ICC ≥ 0.4 considered good reproducibility. Values ≥ 0.75 considered excellent.

Measurement associations:

Table 5.3 Association of symptom scores and airway physiology with sputum neutrophil%. ACQ = Asthma control questionnaire, ACT = Asthma control test, FEV1 = forced expiratory volume in first second, LCI = lung clearance index, RV = residual volume, RV/TLC = Residual volume/total lung capacity, R5-R20 = difference between airway resistance measure a 5Hz and 20Hz, ΔX5 = difference between inspiratory and expiratory reactance measured by impulse oscillometry.

108

5.4 Discussion

Long term Reproducibility

With increasing knowledge of the “neutrophilic phenotype”, its characteristics and inflammatory pathways, developing new therapeutic agents against neutrophils or its mediators and designing clinical trials to test them will potentially be a reality in the future. In order to determine true drug effect and be able to draw conclusive evidence in these trials, it is important to be able to determine the short and long term reproducibility (and therefore, stability) of airway neutrophils.

The short-term reproducibility of sputum neutrophils has been demonstrated in previous studies.

Bacci et al. [191], Fahy et al. [192], Pizzichini et al. [193] and others [194-196] have all shown good to excellent reproducibility with a few days to a month apart. While early phase clinical drug trials (Phase 1) span often a month or less, an understanding of short-term reproducibility in this context is suitable. Larger and more latter phases of clinical trials (Phase 2-4) can run from a few months to a few years. In these situations, an understanding of long-term reproducibility is useful.

Reproducibility in these time scales in sputum neutrophils have not been reported before. My data suggests such reproducibility is poor. There may be a few reasons for this. The mean time interval in my study is 45 months (range 9.5 – 72.5 months) between initial cell count and the second one.

Patients were randomly chosen from our database of historical cell counts (those with sputum neutrophil ≥ 50%). It is mere chance that the mean time interval became 45 months. During these

45 months, the pathobiology of the disease may have changed. While 63% remained

“neutrophilic”, the sputum inflammatory patterns of the other 37% changed. This transition of inflammatory patterns over time has been reported before [242, 319, 320]. Shin et al.[242] demonstrated a change in the sputum inflammatory pattern in 40% of stable asthmatics over a mean 29.6 months. This is supported by similar findings by Majewski et al. [319] and Al-Samri et al. [321]. In the latter study, the authors describe a transformation from neutrophilic to non-

109 neutrophil by 12% of the subjects over the course of 1 year. Fleming et al. describes such pattern change in children as well [320]. This is similar to what occurred in my study subjects although I present data over a longer period of time.

Another point which may have affected reproducibility in my study is the severity of disease in the study population. Most short term reproducibility studies recruited patients with moderate to severe disease. While the mean ACQ-7 score in my study 1.3 suggesting sub-optimal asthma control, it may not reflect the more severe spectrum of the disease. Rossall et al.[195] who showed good reproducibility (albeit short term) for sputum neutrophil% had patients with a mean

ACQ-7 of 2.04 suggesting possibly more severe symptoms results in more consistent inflammatory phenotype. For the purpose of designing long term clinical trials/studies, my data concurs with limited evidence indicating sputum inflammatory pictures can evolve over a longer period of time, the monitoring of which will have to be incorporated into study design and data interpretation.

Characteristics with sputum neutrophilia

Exploring the characteristics of my study population with raised neutrophils was a secondary aim with the purpose of seeing whether their physiological characteristics concur with existing evidence and literature surrounding neutrophilic asthma. There was no control group in this study and therefore findings mentioned here are purely observational only.

Increased neutrophils in the airway and sputum have been associated with a distinct phenotype of physiological and clinical characteristics. The evidence gap for this phenotype has been narrowing as more knowledge and research data have been generated. The common themes that emerge through available literature suggest increased neutrophils in asthmatics are associated with more

110 severe disease, airflow limitation, more frequent and intense exacerbations and fatal asthma[158,

177, 322]. It follows that the interest in characterising this inflammatory phenotype, which is considered a key player in the group of “non-TH2 endotypes”, has gained considerable popularity.

The ENFUMOSA study [75], a cross sectional study exploring the characteristics of severe asthma as compared to mild-moderate asthma, has shown increased sputum neutrophils in severe asthmatics and those with frequent exacerbations. Observational data in my study concurs with this (mean ACQ-7 = 1.3) and adds support to the evidence that increased neutrophils in the airways is associated with uncontrolled symptoms. While the use of corticosteroids has been suggested to increase levels of sputum neutrophils by delaying programmed apoptosis[235], there is growing evidence of occurrence of sputum neutrophilia in asthmatics independent of corticosteroids. Brinke et al. demonstrated no change in sputum neutrophil counts despite controlled use of intramuscular triamcinolone [323]. Green et al. [226] and myself (in Chapter 4) have shown a subgroup of asthmatics with raised sputum neutrophils in corticosteroid naïve asthma. Furthermore, in my current study, six out of nineteen patients (32%) recruited were steroid naïve. Therefore, the signal that neutrophilia is associated with more severe symptoms suggests a link to direct neutrophilic activity rather than their mere presence secondary to corticosteroid related delayed cell death.

Abnormal airway physiology associated with increased sputum neutrophils have been studied before. Neutrophils in the airway have been associated with airflow limitation. This has been shown to be due to chronic inflammation with subsequent release of tumor growth factor - β

(TGF-β) and neutrophil elastase, both of which result in airway remodeling [168, 324]. Various studies have shown an association with lower pre and post bronchodilator FEV1 with sputum neutrophilia. Little et al. [325] demonstrated an inverse relationship between FEV1 and neutrophil numbers in asthmatics. Shaw and colleagues [227] showed similar results with pre and post bronchodilator FEV1. In fact, they went on to calculate a 83ml reduction in pre-bronchodilator

111 FEV1 per 10-fold increase in sputum neutrophil per gram. Further similar findings were reported by Woodruff et al. [326]. My study results, however, do not concur with this. Mean FEV1% is with in normal limits at 80% and did not show a significant correlation with sputum neutrophil %

(r =0.06, p = 0.85). This discrepancy between my findings and other studies may be down to patient recruitment. Most studies mentioned earlier do not mention the severity of disease in terms of symptom control in their the study population. But patients were recruited from local clinical databases and were on significant doses on inhaled corticosteroids. A number of patients in Little et al.’s study were on maintenance oral corticosteroids. This suggests, disease severity was likely to be at the higher end with subsequent chronic inflammation and airway remodeling secondary to this. In my study, although patients were symptomatic and sub-optimally controlled, the mean

ACQ-7 score was 1.3 which is just marginally above the threshold for uncontrolled asthma (ACQ-

7 < 1.0 = controlled symptoms and ≥ 1.0 = uncontrolled symptoms [265]). It is possible the cohort of patients recruited in my study were in the earlier “silent phase” of disease where chronic inflammation and smooth muscle remodeling hadn’t yet taken place. Furthermore, an important factor that may have affected my results is the presence of confounding factors. Woodruff et al,

[326] have found that age, gender and ethnicity can confound the relationship between airway inflammation and measurements of airway function. When accounted for, they demonstrated an increased association with lower FEV1. My data analysis does not take into account these factors and it is likely this would have affected the results.

A worthwhile observation in my results is the indication of the presence of small airway disease

(SAD) in this cohort of patients with raised sputum neutrophils. Both, mean values for lung clearance index (LCI) and impulse oscillometry measurements (R5-R20), are above the relevant cut-offs compared to healthy controls (normal healthy cut offs for LCI – 7.0 and R5-R20 –

0.03kPA/L-1 [280, 327]). There is increasing evidence of small airway involvement in asthma.

112 Airways with an internal diameter < 2mm and extend beyond the eighth division of the bronchial tree have been classed as “small airways” [328].

Wagner et al.[329] demonstrated increased peripheral resistance up to seven fold in asthmatics compared to healthy controls. Autopsy [330-332] and surgical resection[333] studies of lung tissue in asthmatics have shown distal small airway inflammation. Radiological imaging with xenon ventilation computed tomography scans and hyperpolarized gas lung magnetic resonance ventilation imaging have also added weight to this evidence[334]. Ventilation inhomogeneity in the acinar region of the lung has been shown to correlate with FEV1. While the severity and extent of small airway disease may be to be due to contribution from both eosinophilic and neutrophilic activity, in my study, 12 out of 14 patients (86%) with a sputum neutrophil % ≥ 50% had a R5-R20

≥ 0.03kPA/L-1 and 13 out of 14 patients (93%) had an LCI ≥ 7.0. This seems to suggest a relationship with sputum neutrophilia and small airway dysfunction which concurs with existing knowledge and adds to the premise that neutrophils in the airway do indeed play a role in contributing to the inflammatory process. Normal mean residual volume % (RV%) and mean residual volume to total lung capacity ratios (RV/TLC) measure during body plethysmography do not point towards hyperinflation or significant gas trapping that is usually seen in COPD. A normal mean ΔX5 measured during impulse oscillometry does not suggest expiratory flow limitation either.

113 CHAPTER 6 – THE ROLE OF ANTICHOLINERGIC THERAPEUTIC AGENTS IN ASTHMA AND EXPLORING THE CHARACTERISTICS OF THE “RESPONDERS”

6.1 Introduction

Anticholinergic agents (also known as antimuscarinic agents) have been used as bronchodilators in airways diseases to improve airflow, gas trapping and symptoms. While the use of these agents have been widespread in COPD [335], their usefulness and role in asthma is less clear. In asthma, the use of inhaled β2 agonists such as salbutamol have been more common. There is a widely held view that β2 agonists are more effective than anticholinergic agents in the management of asthma

[336]. Van Schayck et al. [251] have shown better bronchodilator response to inhaled salbutamol

(400μg) in patients with mild to moderate asthma as compared to inhaled ipratropium (80μg).

This phenomenon appears to be reversed in those with chronic bronchitis. Thiessen and Pedersen

[337] also demonstrated superior response to salbutamol than with ipratropium in asthmatics but not in healthy subjects. More recent studies have concentrated on evaluating the benefit of adding an anticholinergic agent to standard therapy such as inhaled corticosteroids (with or without long acting β2 agonists) in more severe uncontrolled asthmatics over a longer period of time. Both

Kerstjens [255] and Peters [258] have shown improvements in lung physiology and symptoms with the addition of tiotropium to inhaled corticosteroid therapy over a four to eight week period.

Hansel et al. [259] showed similar prolonged bronchodilator response with glycopyrrolate.

Outcomes from these more recent trials have resulted in guidelines changing to include inhaled tiotropium as a Step 4 or Step 5 add on treatment in severe asthmatics as a long term management strategy [260]. Nevertheless, in an acute setting, inhaled salbutamol and/or ipratropium continue to be the most common therapeutic agents used.

114

Ipratropium Bromide – Pharmacodynamics and Dose Response

Ipratropium bromide is a quaternary ammonium derivative of atropine. It’s absorption in the lungs is generally poor, but can be delivered by inhalation at high doses with minimal side effects [338].

Unlike atropine, it does not cross the blood-brain barrier and therefore, exerts no central effects.

Several studies have been done to assess and understand how this therapeutic agent behaves once deliver to the lung. Allen et al. [339] studied the dose relationships of ipratropium bromide in patients with reversible airway obstruction. Doses of 40μg, 80μg and 120 μg were tested against baseline FEV1. Peak bronchodilation was seen with 80 μg and 120 μg as compared to 40 μg. The degree of improvement in bronchodilation was much more when stepped up from 40 μg to 80 μg as compared to the step up from 80 μg to 120 μg indicating a plateau in response at higher doses.

It was also noted peak effect of the drug was not achieved till 30-40 minutes post administration.

At higher doses, drug effect was more prolonged. Similar results were seen in studies by

Baigelman et al.[340], Ruffin et al.[341]. Loddenkemper et al. [342] and Meier et al. [343] demonstrated a similar effect while measuring total and expiratory airways resistance. Chervinsky

[344] took FEV1 measurements earlier and demonstrated inhaled ipratropium begins to show bronchodilator effect as early as 5- 15 minutes post administration with doses as low as 40 μg. A review by Mann KV [345] also concluded the onset of action of ipratropium to be in 15 minutes with a dose dependent duration of action.

Salbutamol – Pharmacodynamics and Dose Response

Salbutamol is a short acting selective β2 adrenoreceptor agonist and is widely used in the management of acute symptoms in asthma. It works via potentiating β2 receptors in the airway which are G protein coupled receptors and leads to airway smooth muscle relaxation and

115 bronchodilation via cAMP pathway (more details in introduction). Unlike ipratropium, studies have shown the onset of action of Salbutamol to be within minutes with peak bronchodilation

(PEFR and FEV1) occurring at about 15 minutes post inhalation [346] [347]. Lipworth et al. [348]

[349] have shown a direct log linear dose-response relationship in patients with asthma, but considerable amount of individual variation. There is evidence to suggest responsiveness to

Salbutamol is greater in asthmatics as the dose response plateaus were not attained even at higher doses whereas, in contrast, in healthy individuals, response curve plateaus occurred much earlier on with lower doses [348].

Attempts at identifying subgroups of asthmatics who are “better responders” to anticholinergic medications have not resulted in concrete conclusions. Younger asthmatics (age < 40) appear to respond better to β2 agonists, rather than anticholinergic agents, and this response appears to decline with advancing age [336]. Endoh et al. [350] demonstrated a significant correlation with anticholinergic (oxitropium) related bronchodilation and raised serum IgE. However, other studies exploring the relationship between atopy and anticholinergic response in asthma have indicated atopy results in a reduced response [351]. Work by others appears to suggest better anticholinergic response in nocturnal asthma and a relationship between cholinergic tone and circadian rhythm [352-354].

The aims of this study was to:

1. To explore the differences in bronchodilator response (inhaled ipratropium vs. inhaled

salbutamol) in different severities of asthma.

2. To explore the differences between “anticholinergic responders” and “anticholinergic non-

responders” to provide evidence of markers/measurements which may aid identifying the

subgroup of asthmatics who respond to anticholinergic agents.

116

6.2 Methods

6.2.1 Study subjects and study design

Thirty-eight subjects were recruited from the Medicines Evaluation Unit database. These subjects had a diagnosis of asthma and <10-pack year smoking history. They did not have any respiratory infections or flare up of asthma symptoms within four weeks of the study. Those who were on inhaled corticosteroids/long acting β2 agonist (LABA) inhaler therapies were instructed to withhold medications 12 hours prior to each visit. LABAs generally have an extended duration of action leading up to 12 hours after inhalation. However, pharmacokinetic studies show that by 12 hours post dose, the plasma concentration is < 5% of maximum concentration (Cmax) [355] and thus, with holding 12 hours prior to this study would mitigate their bronchodilator effect. While a

24 hour washout would have been ideal, the 12 hour mark was a compromise that allows the study subjects not to become excessively symptomatic due to LABA withhold and still tests reversibility with a low level of LABA activity on board.

At Visit 1, symptom control (ACQ-7 questionnaire score), spirometry (FEV1), small airway ventilation inhomogeneity in the form of lung clearance index (LCI) and FeNO measurements were carried out in addition to measuring airway reversibility to 400μg of inhaled salbutamol via volumatic spacer (patient blinded). FEV1 measurements were taken were measured at baseline and at 15 minutes post bronchodilator. Induced sputum was then processed and cytospin slides for differential cell count were made. The slides were stained (Rapi-Diff®) and 400 cells per cytospin were counted. The methods used are described in detail in Chapter 3.

Subjects were invited back within one week for Visit 2 during which spirometry (FEV1) at baseline and reversibility to 80μg of ipratropium bromide via volumatic spacer (patient blinded)

117 15 minutes post drug administration were measured. The decision to set post treatment measurement of bronchodilator effect at 15 minutes for both salbutamol and ipratropium was based on evidence [344] [345] showing ipratropium begins bronchodilating the airways as early as 5-15 minutes even at much lower doses (although not reaching peak levels till 30-40 mins) while salbutamol also responds in the same time frame and in fact, drug effect peaks at 15 mins.

Keeping the same time point for measurement would also help minimise bias and be more convenient for patients/volunteers. This will have drawbacks that are discussed later. The doses of both bronchodilators used are same as Van Schayck et al.’s study [251] where a similar study design (but with fewer measurements) was used. Millar et al. [356] used incremental doses of ipratropium (40μg, 80μg, and 200μg), but increased drug related side effects were noted while using 200μg. A “responder” was defined as those who had an improvement in FEV1 of ≥12% or

200mls from baseline spirometry fifteen minutes after the inhalation of ipratropium bromide. The criteria for establishing “significant” bronchodilator response in asthma have been controversial.

While many studies use American Thoracic Society (ATS) criterion of an FEV1 improvement of

12% and 200mls, Gjevre et al. [357] have shown that using the ATS criterion alone resulted in the under-diagnosis of asthma in more than 50% of patients. They suggest using these as guidelines only and not as gold standard. Therefore, we opted to broaden our definition of significant reversibility (and therefore definition of “responder”) to a post bronchodilator response of ≥12% or 200mls.

Fig 6.1 Study consort diagram

118

Fig 6.2 Study design

6.2.2 Statistical analysis

Normality was determined using Kolmogorov Smirnov tests. Data was presented as mean

(standard deviation) or median (interquartile range). Parametric data was compared using paired student t tests and non-parametric data compared using Mann Whitney U tests (Graphpad Prism version 6.0).

6.3 Results

38 patients in total were recruited. Mean age was 47.05 (SD 11.69) with 68% males and 32% females. 15 patients were already on inhaled corticosteroids + long acting β2 agonists

(ICS/LABA). 23 patients were corticosteroid naïve. 32 out of 38 patients produced sputum on

Visit 1. Median ACQ-7 was 0.71 (interquartile range 0.43-1.29). Other baseline characteristics are tabulated in Table 6.1.

119 Baseline Characteristics (N=38) Age 47.05 (11.69) ACQ – 7 0.71 (0.43-1.29) FEV1% 86.28 (17.33) Reversibility (mls)* 258.90 (180.80) Reversibility (%)* 10.80 (8.71) LCI 8.81 (2.16) FeNO 37.19 (26.9) Sputum Eosinophil % 1.00 (0.25-3.25) Sputum Neutrophil % 46.21 (17.55)

Table 6.1 Baseline Characteristics * Reversibility to 400μg of Salbutamol Parametric data presented as mean (SD) and non-parametric data presented as median (interquartile range)

Reversibility to both bronchodilators was assessed. Reversibility in subgroups (i.e. corticosteroid naïve group and ICS/LABA group) was also assessed.

Table 6.2 Reversibility to Salbutamol and Ipratropium in all subjects and in subgroups. SNA = steroid naïve asthma. ICS/LABA = Inhaled corticosteroid/long acting β2 agonist.

120

Reversibility (mls) - All Subjects Reversibility (%) - All subjects

p = 0.05 p = 0.02

500 20

)

) s 400

% 15

(

t 300

i b 10

r s 200

e 5 100 R

0 0 l l o m o m iu iu m p m p ta o ta o u tr u tr lb a lb a a r a r S Ip S Ip Bronchodilator Bronchodilator

Fig.6.3 Reversibility in all study subjects

121 A Reversibility (mls) Reversibility (%) Corticosteroid Naive Subgroup Corticosteroid Naive Subgroup

p = 0.003

500 20 p = 0.006

)

) s 400

% 15

(

i t 300

i b 10

r s 200

e 5 100 R

0 0 l l o m o m iu iu m p m p ta o ta o u tr u tr lb a lb a a r a r S Ip S Ip Bronchodilator Bronchodilator

B Reversibility (mls) Reversibility (%) ICS +/- LABA subgroup ICS +/- LABA subgroup

p = 0.71 p = 0.63 500 30

)

) s 400

(

t 300

r s 200

v 10

e 100 R

0 0 l l o m o m iu iu m p m p ta o ta o u tr u tr lb a lb a a r a r S Ip S Ip Bronchodilator Bronchodilator

Fig. 6.4 Reversibility in corticosteroid naïve asthma (A) and in subjects taking inhaled corticosteroids +/- long acting β2 agonist (ICS +/-LABA) (B)

122 “Responders” to ipratropium were identified and their characteristics were compared to “non- responders. (Table 6.3)

Table 6.3 Anticholinergic “responder” vs. “non-responder” 1 Responder defined as reversibility ≥12% or ≥200mls after inhalation of 80mcg Ipratropium bromide 2Parametric data presented as mean (SD) and analysed by unpaired t test 3Nonparametric data presented as median (interquartile range) and analysed by Mann Whitney test

6.3 Discussion

Bronchodilator response

My results concur with that of previous studies exploring the immediate and short-term bronchodilator response with anticholinergic agents compared to conventional β2 agonists

(salbutamol). The widespread notion β2 agonists provide better bronchodilator response in the short term appears to be valid [251, 337, 358-360]. Van Schayck et al. reported a 370ml improvement from baseline FEV1 with 400μg of inhaled salbutamol as compared to 260 ml improvement with 80μg ipratropium bromide [251]. Using the exact same drugs and doses, my

123 observations were similar (salbutamol – 258.9mls, ipratropium – 179.3mls). Van Schayck, however, measures response to salbutamol 15 minutes post drug administration and after 45 minutes with ipratropium. This is in contrast to my study where reversibility is measured 15 minutes post drug administration for both salbutamol and ipratropium. However, one significant limitation of my study is that measurement of bronchodilator effect of ipratropium was done before peak effect occurred. Furthermore, Van Schayck recruited patients with more moderate to severe disease while those in my study had mild symptoms (median ACQ-7 = 0.71). These factors may explain the relative differences in response.

Ullah et al. [358] again used similar pharmacological agent at the same doses. The only difference was total dosing was staggered at 30 minute intervals (i.e. 0, 30, 60, 90 min dosing with 100μg inhaled salbutamol at each interval) and FEV1 was measured up to 120 minutes post drug administration. Even at 30 minutes with only 100μg of salbutamol and 20μg of ipratropium, significant bronchodilation was achieved but again, akin to my results, salbutamol showing more effective bronchodilation. Therefore, including results from my study, it can be concluded anticholinergic agents can provide bronchodilation effects in asthma but the notion that has been long held that β2 agonists are more effective is true.

Another observation from my study results seems to suggest long term inhaled corticosteroids +

LABA appear to either improve response to ipratropium or reduce/blunt the response to salbutamol (see Table 6.2) and the gross difference between the two classes of drugs appear to be smaller and non significant. This is interesting and may be explained by two factors.

Corticosteroids have been known to increase prejunctional auto-inhibitory M2-receptor gene expression in airway smooth muscle [361] and subsequently reduce vagally mediated bronchoconstriction. In addition, Lipworth et al. [362, 363] have shown that concurrent use of

LABAs causes a subsensitivity of salbutamol (short acting β2 agonist – SABA) for protection against bronchoconstricor stimuli. This has been thought to be due to the down regulation of β2

124 adrenoreceptors. In vitro studies have shown a reduction of these receptors in the human lung following exposure to salmeterol and formoterol which are commonly used LABAs [364]. Two other studies have shown a down regulation of β2 adrenorecptors in peripheral blood lymphocytes following 4 weeks exposure to formoterol [365, 366]. Patients on my study, who were on long acting β2 agonists in addition to inhaled corticosteroids, where required to omit their last dose > 12 hours prior to the visit. While the immediate bronchodilator effects those class of drugs should have been minimal, the longer term influence on β2 adrenoreceptor activity may have had an impact resulting in the apparent “more effectiveness” of ipratropium.

Of further interest is the observation made by Kerstjens et al. [256] that the addition of tiotropium to standard therapy in poorly controlled asthma increases the time to first exacerbation and in combination with data from my study raises the question as to whether there may be a temporal relationship between the effects of corticosteroid and anticholinergic therapies. Further studies exploring this are needed as there may be scope to utilise anticholinergic pharmacotherapy earlier and at higher doses in those who appear to be steroid resistant through conventional antiinflammatory pathways.

Anticholinergic Responders

While it has been established anticholinergic agents do provide significant bronchodilation (and potentially more so in patients on corticosteroids) in both short term and long term[255, 256, 258], the need to identify the common characteristics (and biomarkers) for a subgroup of responders would be very useful in both clinical practice as well in recruiting patients for clinical drug trials studying anticholinergic pharmacotherapy. As discussed earlier, previous limited attempts at doing so have generally not been successful or reproducible. Endoh et al. [350] showed a correlation between raised IgE and anticholinergic bronchodilator response. This phenomenon

125 was thought to be secondary to an exaggerated vagal/cholinergic tone in airway smooth muscle related to IgE which appears to be a determinant of airway calibre [367, 368]. Retrospective analysis of the “responders” in my study show that 13 out of 16 (81%) patients with available historical (with in one year) skin prick test results were positive for atopy. However, more recent and longer term studies have not been able to replicate this observation. Peters et al. [257] report on the TALC study sub-analysis to identify predictors of response to Tiotropium. The TALC trial was a three way cross over trial studying ICS alone vs. ICS + LABA vs. ICS + Tiotropium. While confirming higher cholinergic tone/vagal was a predictor for response to tiotropium, other factors such as atopy, IgE, sputum eosinophil count, FeNO and body mass index were not. In my study, those with higher sputum eosinophil percentage and more symptoms appeared to respond better than the “non responders”. This is goes against the findings TALC trial sub-analysis. However, analysis of response to tiotropium was done in the ICS + tiotropium arm of the trial and the concurrent use of ICS over a 14-week period may have influenced sputum eosinophil counts. My study also had patients on ICS, but this was briefly withheld 12 hours prior to measurements.

Whether this short term withdrawal, although unlikely, makes a considerable difference needs further study. Ullah et al. [358] reports better bronchodilator response to β2 agonists in the younger asthmatic (age <40) and a more prominent role for anticholinergics with advancing age.

Data from my study did not find any significant correlation between age and reversibility with ipratropium. It is known in humans, vagal and cholinergic tone reduces with age [369]. Therefore, it follows that it would be expected response to an anticholinergic agent would reduce with age. It may be that the “prominent” response Ullah et al. had observed is relative to the decline in bronchodilator response to β2 adrenergic activity with increasing age. Over all, evidence for predictors of anticholinergic activity is very limited and is not consistent. While my study has provided further insight, there is an unmet need for larger studies in this arena.

126 Limitations:

A very significant limitation to my study is the measurement of FEV1 before peak bronchodilation was achieved with ipratropium. As described earlier, early dose response studies have shown peak drug effect with ipratropium occurs 30-40 minutes post inhalation. While bronchodilation would have begun, the true extent of it could have been missed. This, therefore, could have affected the analysis between responder vs. non responder groups. Some patients categorized as non responders may well have become a responder if FEV1 was measured at peak bronchodilation times. Furthermore, while unlikely, the degree of difference in bronchodilation between salbutamol and ipratropium may have become insignificant.

Another limitation or potential source of bias is that all 38 patients followed the exact format. Although patients were not told which therapeutic agent they were getting, they all received salbutamol in Visit 1 and ipratropium in Visit 2. Perhaps randomly switching the medications in Visit 1 and Visit 2 would reduce accidental bias.

127 CHAPTER 7 – KEY FINDINGS AND OVERARCHING CONCLUSIONS FOR THE FUTURE

With increasing knowledge and awareness of the heterogeneity of asthma as a disease process, the understanding that a “personalised approach” and tailored treatment plan for individual patients or a “phenotype” of patients has been gathering importance. These tailored treatments involve an understanding of the individual phenotypes and their underlying downstream molecular pathways

(endotypes). More recently, we have seen a rapid increase in the testing of new pharmacological agents including various new biological agents targeting specific inflammatory mediators, receptors or even the cells involved [370]. For these new drugs to be tested robustly, clinical drug trials have to be designed targeting specific populations with specific biomarkers and endpoints that can track and measure drug effect and its pharmacodynamic properties. A key factor is the reproducibility and reliability of these biomarkers. With new molecules being developed, be it anti inflammatory, bronchodilator or biological, the first step in clinical studies after laboratory and animal studies is to trial the investigational product in early proof of concept and Phase 1 trials in patients with mild disease. A group that is commonly used for this is the corticosteroid naïve asthmatic population.

In this thesis, I set out to study 3 different subpopulations of patients with asthma who feature regularly in clinical drug trials or have the potential to do so in the future with precision medicine advances ( (1) the corticosteroid naive, (2) those with raised sputum neutrophils and (3) those responders to the anticholinergic agent - ipratropium bromide). The overarching aim to explore and understand the different characteristics, potential physiological and pharmacodynamic biomarkers and their reliability in terms of stability and reproducibility in these subpopulations.

The intent was to increase/consolidate the knowledge about these groups to help facilitate more effective, robust and efficient clinical trials which are so needed for future drug development. The salient and key findings are summarised and discussed now.

128

7.1 Study 1 - Characteristics and biomarker reproducibility in corticosteroid naïve asthma

The primary aim in this study was to determine the reproducibility of physiological, sputum and blood measurements in the corticosteroid population that are frequently used as biomarkers and endpoints in early phase clinical trials. The secondary aims included exploring the associations around these measurements, and to further the scientific knowledge surrounding the usefulness of measuring lung clearance index (LCI) which is a novel and upcoming investigative tool.

7.1.1 Key findings:

 Symptom scores and physiological measurements such as ACQ-7, ACT, FEV1%, reversibility, FeNO and LCI have good to excellent reproducibility.  Sputum eosinophils have excellent reproducibility. This was not the case with sputum neutrophils. Reproducibility was poor.  I found significant associations between sputum and blood eosinophils, sputum eosinophil and FeNO and between blood eosinophils and FeNO.

 I also found significant association between LCI and FEV1% and reversibility.  While not statistically significant, exploratory subanalysis suggests the presence of subgroups within the total population (in this study I chose to divide between high and low sputum eosinophils and between symptom controlled and uncontrolled groups.).

While reproducibility of sputum cell counts (mainly in moderate to severe asthmatics) have been reported before (see Chapter 1), the novel feature of my work is that I have shown similar findings in the so called “mild disease”. Further more, reproducibility of physiological measurements in solely corticosteroid naïve asthma has not been reported before. An important usefulness of this

129 data is that information about within subject standard deviations can be used for power calculations when designing clinical trials. My data on sputum neutrophil reproducibility is not consistent with previous studies (see Chapter 1 and Chapter 4). This may be due to the “mild nature” of the disease. Evidence for better neutrophil reproducibility is seen more in the moderate to severe asthmatics.

Another important novelty of my work in this study is the information and data we have gathered on lung clearance index (LCI). LCI has been emerging as a reliable and reproducible measure of ventilation inhomogeneity and small airways disease in cystic fibrosis and non-CF bronchiectasis

[269, 282, 371, 372]. However, I provide data on its reproducibility and associations with lung physiology in adult asthma. I envisage LCI becoming a valuable pharmacodynamic marker in clinical trials in the future.

In this study, I have also provided additional evidence with regards to associations between different measurements that are already known or is still contentious. The relationship between

FeNO and eosinophils (sputum and blood) is subject to ongoing debate. In this study, I have added weight to the argument for using FeNO as a biomarker for eosinophilic (and by extension –

TH2) activity. In addition, I have demonstrated the possibility of the presence of subpopulations

(e.g. high eosinophil ,vs low eosinophil) which could be screened for in early phase clinical trials.

The measurements and characteristics of that particular groups could be used for screening or as pharmacodynamic biomarkers . For example, Hodsman et al, [373] in a study evaluating the safety and effectiveness of a novel anti-IL 13 agent, used FeNO as a surrogate marker of IL-13 activity and drug response. Similarly, I provide knowledge of biomarkers that can represent particular target subpopulations in corticosteroid naïve asthma and would particularly be useful in screening for patients to recruit for clinical trials.

130 There are limitations in this study. The most significant limitation is the small sample size. While

I had planned for recruiting a larger study group, time constraints and relying on patients with

“mild disease” to come for study visits restricted my numbers. However, a sample size of at least n = 12 have been shown to provide enough statistical power to in previous induced sputum studies

[374, 375]. Furthermore, given the mild disease, not all subjects were able to produce adequate volumes of sputum at both visits which also limited the robustness of sputum analysis. An increased sample size would probably have allowed more significant discrimination between subgroups I examined and possibly achieve statistical significance between different measurements.

7.2 Study 2 - Assessing the long term reproducibility of raised sputum neutrophils in asthma and exploring their characteristics.

As discussed in Chapters 1 and 5, the lack of knowledge around the “neutrophilic phenotype” in asthmatics has been a source of increasing interest. The association of this phenotype with more severe disease and more intense exacerbations has raised the need for identifying new therapeutic targets and biomarkers that can track the activity of neutrophils in the short term and in the longer run. While previous studies have shown good reproducibility in the short term (up to 1 month), the reliability of sputum neutrophil counts for longer periods of time has not been tested. The primary aim in this study was to assess long term reproducibility of raised sputum neutrophils in asthmatics. The secondary aim was to explore their physiological characteristics to increase our understanding and re-enforce existing knowledge regarding this population.

131 7.2.1 Key findings:

 Long term reproducibility of sputum neutrophils (over years) is poor and not reliable. There is significant within subject variation over time. 37% of subjects were no longer “neutrophilic”.

 Exploratory findings (abnormal LCI and R5-R20) suggest ventilation inhomogeneity and small airways disease (SAD) are present in this group.

The main finding in this study is the poor reproducibility (over years) of sputum neutrophils which naturally raises the question as to whether sputum inflammometry using neutrophil count as a marker of disease activity (or drug effect in clinical trials) is reliable. My work is the first study to examine this and these findings could prove useful in future when longitudinal studies and more advanced clinical trials using therapeutic agents against neutrophils are designed. The change in sputum inflammatory pattern in over years in asthma is interesting although not a new concept. While neutrophilic inflammation has been associated with significant airflow limitation in previous literature, the suggestion there is a small airway component to neutrophilic disease is novel.

The primary limitation in this study again was the small sample size. Recruitment was challenging in this study and tracking down subjects who had a historical sputum differential count with raised neutrophils going back a few years was difficult. While a mean time difference of 45 months between historical cell count and this study’s is a considerable amount of time, attempting to recruit within a pre-set time limit would likely have reduced sample size even smaller. While exploring and measuring the physiological characteristics were not the primary aim, it became clear having a control group of “non-neutrophil asthmatics” would have been beneficial for comparisons and the study should have been designed in such a manner. Without the control group, my findings remain an “exploratory observation” which will need confirmation with a larger sample size and appropriate study design.

132

7.3 Study 3 - The role of anticholinergic therapeutic agents in asthma and exploring the characteristics of the “responders”

This study examined the usefulness of an anticholinergic (ipratropium bromide) in asthma. Earlier studies have shown better responses with salbutamol that ipratropium in asthmatics. More recent evidence demonstrated additional benefit by adding a longer acting anticholinergic agent such as tiotropium to standard asthma therapy. The primary aim of this study was to determine whether the widespread view that β2 agonists (salbutamol) were more effective that anticholinergics

(ipratropium) was valid. The secondary aim was to explore was to explore the differences between anticholinergic “responder” and “non responder” groups.

7.3.1 Key findings:

 The reversibility response to salbutamol is generally better in asthmatics. It is particularly better in corticosteroid naïve asthmatics.  Anticholinergic response showed an apparent improvement with more severe asthmatics on inhaled corticosteroids and long acting β2 agonists (ICS + LABA).  When “responders” to anticholinergics were studied, they were significantly more symptomatic and had higher sputum eosinophils as compared to the “non- responders”.

In this study, I have confirmed the long held view regarding the superiority of β2 agonists in asthma. However, the novel and interesting finding is improved response to anticholinergic agents

(ipratropium) in patients who are on ICS + LABA (and consequently likely to have more symptomatic disease). As discussed earlier, the reasons for this is likely to be two fold (see

Chapter 6). Corticosteroids have been shown to increase the expression of prejunctional M2 muscarinic receptors which are autoinhibitory and reduce vagally mediated bronchoconstriction.

In addition to this mechanism, Lipworth et al. [362, 363]and others have shown directly in in vitro

133 studies and indirectly that the concurrent use of a LABA results in the subsensitivity of a SABA

(e.g. salbutamol) protection against bronchoconstricor stimuli and down regulation of β2 receptors. My study findings are of clinical and pharmacological significance where I have shown objective evidence of higher effectiveness with β2 agonists in corticosteroid naïve asthma but, when broken data is broken down, a more substantial role for anticholinergic medications in those with probable more severe disease needing ICS and LABA. The other novelty in this study is the subanalysis of the characteristics of the ipratropium “responders”. In line with the earlier finding, I have shown those with higher symptom scores appear to respond better than those who have milder disease. In addition, elevated sputum eosinophils also appear to be more prominent in the “responder” group and is likely goes hand in hand with the higher symptom scores.

Nevertheless, these findings have to be corroborated with larger studies which, given the potential clinical impact, is warranted. I have used ipratropium in this study. Other studies need to be done using other anticholinergic agents to assess class effect. Another limitation in my study, although likely theoretical, is the potential for bias in my study design. Reversibility in all subjects were tested with salbutamol first followed by ipratropium in that order. Subjects were not blinded. It would have been better in the study design if I had blinded the subjects in terms of which bronchodilator was used and randomly mix the days in which salbutamol and ipratropium were used.

7.5 Overarching conclusions – putting it all together for the future

Asthma is a disease that has been held responsible for considerable morbidity, mortality and health-care burden around the world. While progress was made in reducing hospital admissions and mortality towards the latter part of the last century, very little development has occurred in the last 20 years. New drug discovery and development have progressed at a much lower rate (Table

7.1) than in other disease groups [376]. The first asthma guidelines were documented 27 years ago

134 [377] which associated asthma as a predominant inflammatory disease and resulted in the widespread use of inhaled corticosteroids. This undoubtedly benefitted many and resulted in the reduction of crude mortality worldwide since the mid 1980s as shown by Ebmeier et al. [378].

However, substantial development and improvement has since generally flat-lined and an important factor for this stagnation was the persistent adherence and over reliance on outdated disease labels, treatment frameworks and monitoring strategies [376]. This is aptly summarised by

Rosenthal who observed “therapy still comprises a blue and brown inhaler (the latter of which is usually left to gather dust in the bathroom cabinet) and looking menacingly at the pet cat” [379].

This over simplification and overgeneralisation of a complex heterogeneous disease resulted in distinct and pathologically important mechanisms being missed.

New, outside the box, thinking was needed and the discovery and development of simple, noninvasive methods to assess and monitor airway inflammation, lung physiology and drug pharmacodynamics have been a stimulus for change. Our increasing understanding of presence of phenotypes, endotypes and underlying downstream inflammatory pathways as well as being able to pool together data and identify responders to certain classes of therapeutic agents are now starting to result in a more targeted, biomarker directed approach to therapy and disease monitoring. These developments have also facilitated the design and conduct of more robust clinical trials with new treatments/drugs aimed at inhibiting very precise pathways.

135 Drugs (n) Market entry Cumulative market probability (%) entry probability HIV and AIDs 108 Phase 2 trials 75% 14% Phase 3 trials 39% Approved 39% Dermatology 122 Phase 2 trials 8% 11% Phase 3 trials 44% Approved 29% Haematology 163 Phase 2 trials 60% 9% Phase 3 trials 4% Approved 22% Neurology 192 Phase 2 trials 73% 8% Phase 3 trials 47% Approved 22% Cancer 68 Phase 2 trials 78% 7% Phase 3 trials 46% Approved 20% Cardiovascular 280 Phase 2 trials 69% 6% Phase 3 trials 4% Approved 22% Respiratory 165 Phase 2 trials 68% 3% Phase 3 trials 31% Approved 16% Table 7.1 New drug discoveries in different specialties [380]

A key concept that has evolved more recently is the idea that a reductionist approach should be the way forward [376]. This approach focuses on certain traits that are distinctly recognisable, reproducible and is associated with disease morbidity. First based on the ideas of Hargreave et al.

[381], these treatable traits include airflow limitation, airway inflammation, airway infection and impaired airway defenses. In a Lancet commission, Pavord et al. [376] conclude that clinical trial designs being too broad can be a source of for hindrance and should focus on key potential predictors of response primarily with the treatable traits in the framework.

By studying these 3 different groups of asthmatics, I have re-enforced knowledge that was already known and I have introduced novel ideas. The 3 studies in this thesis build around the concept of measurable, modifiable and treatable traits. The studies further knowledge around characteristics and measurements that define subpopulations and have the potential for incorporation into clinical trials. The reproducibility data in corticosteroid naïve and “neutrophilic” asthmatics can be used

136 in the design and power calculations of future clinical trials. It gives a perspective into which measurements or biomarkers can be confidently used as markers of drug effect. To date, most clinical trials have focused on moderate and severe asthma in large teaching hospital research facilities at the expense of the milder steroid naïve form who, in fact, do experience significant morbidity that has gone largely unrecognised. Therefore, in addition to providing data to be used in a clinical trial setting, my characterisation data will be useful in furthering subphenotyping this fairly untapped population. I would have ideally liked to study the sputum microbiomata in the 3 different groups to complete the triad of treatable traits, but was limited due to time constraints.

Lung clearance index as a measurement for early airway dysfunction is gaining popularity due to its degree of sensitivity and ease of use (incorporates tidal breathing and no forced manoeuvres). I have provided early data on the usefulness of LCI in adult asthma. This certainly needs to be taken forward with studies in larger numbers for it to be established as a biomarker and a validated endpoint in clinical trials. The use of anticholinergic agents in selected patients over β2 agonists has significant clinical implications; especially in the acute setting. While there has been early work exploring the role of anticholinergic medications in asthma, interest had tapered down.

More recently, with the advancement of tailored therapies that target specific patient groups, the interest in the use of anticholinergic agents, especially longer acting drugs such as tiotropium and glycopyrronium, has been resurrected. My work in identifying responder characteristics, although with limitations, adds to the limited knowledge in this area. The notion that patients who responded equally or better to ipratropium that salbutamol had significantly higher sputum eosinophils is no doubt very interesting and warrants further study of the relationship between eosinophilia (and by extension – T2 high asthma) and the anticholinergic/muscarinic pathways.

137

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155 Appendix 1 – Publication

So far part of this work has resulted this publication:

 Lung Clearance Index (LCI) Measurements Are Reproducible And Associated with Airway Physiological Changes in Steroid Naïve Asthmatic (SNA) Adults.

[POSTER]

J.Rafique, T. Southworth, A.Bell, U.Kolsum, D.Singh

European Respiratory Society (ERS) conference, Milan, Italy 2017

Lung Clearance Index (LCI) measurements are reproducible and associated with airway physiological changes in steroid naïve asthmatic adults J Rafique1, T Southworth1, A Bell1, U Kolsum1, D Singh1 Medicines Evaluation Unit, University Hospital of South Manchester NHS Foundation Trust, Manchester, United Kingdom1

Background Results Conclusion Lung Clearance Index (LCI) is a novel investigative method to DEMOGRAPHIC,CHARACTERISTICS, assess early airway dysfunction. ,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,, Early results show LCI has excellent It works on the premise inflammation in peripheral airways result reproducibility in adult asthma. in a ventilation inhomogeneity and abnormal gas mixing. It is calculated as the cumulative expired volume needed to wash out In asthmatics, there is significant correlation an inert gas (usually nitrogen or sulfur hexafluoride) divided by between LCI and markers of airway physiology. functional residual capacity (FRC).1 LCI measurements do not correlate with symptom LCI has been shown to be a sensitive and reproducible marker of early airway disease in cystic fibrosis and cystic fibrosis related control scores or sputum/blood eosinophil and bronchiectasis. It has also been used to measure drug effect in SPUTUM, neutrophil counts (data not shown). cystic fibrosis clinical trials.2,3,4,5,6,7,8 This preliminary data shows a role for LCI in the The role and usefulness of LCI in asthma is not clear. assessment of airway dysfunction in asthma is highly possible. It could potentially be used as an If proved as a sensitive and reproducible test in asthma, LCI will BLOOD, endpoint to assess drug effect in clinical trials. have a significant role as pharmacodynamic biomarker and clinical Larger studies involving different phenotypes and endpoint in asthma related clinical drug trials and research. Baseline characteristics of asthmatic patients who were corticosteroid naive Explanation of abbreviations: BMI = body mass index, ACQ = Asthma Control Questionnaire, ACT= Asthma levels of severity is needed. Control Test, FeNO = Fraction of exhaled Nitric Oxide, LCI = Lung Clearance Index, Data presented as mean (standard deviation) a Denotes geometric mean (95% confidence interval) Aim References LCI Reproducibility A B LCI Reproducibility C To determine the reproducibility of lung clearance index and explore 1) Gonem, S., et al., Lung clearance index in the associations with physiological measurements and sputum cell 15 Bland Altman Within subject SD Intraclass

s Bias: - 0.09 (SD 0.37) adults with non-cystic fibrosis bronchiectasis. t Mean Difference/ (calculated from correlation

n 1 counts in corticosteroid naïve adult asthma. e Bias difference of coefficient Respir Res, 2014. 15: p. 59. m 1.0 (95% limits of means)

r 2) Fuchs, S.I., et al., Feasibility and variability of

u agreement)

s 10 a 0.5 measuring the Lung Clearance Index in a

multi-center setting. Pediatr Pulmonol, 2012.

L 0.0 47(7): p. 649-57.

o Lung Clearance Index -0.09 (-0.81-0.63) 5 10 15 5 0.37 0.94* w 3) Owens, C.M., et al., Lung Clearance Index and

Methods

o -0.5 HRCT are complementary markers of lung

n abnormalities in young children with CF.

• All subjects gave written informed consent. The research was e r -1.0 0

f Thorax, 2011. 66(6): p. 481-8.

f approved by a local ethics committee. i 1 3 D Mean of two LCI measurements it it 4) Vanderhelst, E., et al., The Lung Clearance • Corticosteroid naïve asthmatics were recruited. is is • Those who had a smoking history of >10 pack years or a V V Index as a probe for the effectiveness of short-

respiratory infection within 4 weeks were not considered. Reproducibility of LCI measurements in corticosteroid naïve asthma term therapies in cystic fibrosis lung disease. J • Patients attended a further “reproducibility visit” to the (A) – Bland-Altman plot of LCI measurements taken at Visit 1 and Visit 3, central dotted line represents mean difference (bias) and upper and lower dotted lines represent limits of agreement ( mean difference Cyst Fibros, 2015. 14(2): p. 285-6. +/- 2 SD) (B) Line plot of actual LCI measurements at both visits (C) Intra-class correlation coefficient calculated from both measurements taken at Visit 1 and Visit 3 5) Horsley, A.R., et al., Lung clearance index is a research unit. • LCI was measured using multiple breath nitrogen washout 1 ICC ≥ 0.4 considered good reproducibility. Values ≥ 0.75 considered excellent reproducibility sensitive, repeatable and practical measure of technique (Exhalyzer ® DH, Ecomedics AG) * On a natural logarithm scale. airways disease in adults with cystic fibrosis. Note: The differences between visits for all variables were either normally distributed or approximately normally distributed so the Bland-Altman analysis was performed on untransformed variables. Thorax, 2008. 63(2): p. 135-40. LCI - Reversibility % 6) Davies, J.C., Sheridan H, Lee P-S, Song T, LCI - FEV1/FVC LCI - FEV1 Stone A, Ratjen F., Effect of Ivacaftor on lung r = -0.59 r = 0.46 140 r = -0.60 p = 0.003 p=0.02 function in subjects with CF who have G551D- p= 0.002 90 30 CFTR mutation and mild lung disease: a 120 80

)

( comparision of lung clearance index (LCI) vs.

(

F 20

1 100 t

i 1 70

E spirometry. J Cyst Fibros, 2012. 11 (Suppl. 1):

80 60 e

v 10 p. S15.

R 60 50 7) Amin, R., et al., Hypertonic saline improves the 0 5 10 15 0 5 10 15 0 LCI LCI 0 5 10 15 LCI in paediatric patients with CF with normal LCI LCI correlations with with measurements of airway physiology lung function. Thorax, 2010. 65(5): p. 379-83. All tests performed using Spearman Rank tests. 8) Amin, R., et al., The effect of dornase alfa on p<0.05 = statistical significance ventilation inhomogeneity in patients with cystic fibrosis. Eur Respir J, 2011. 37(4): p. 806-12.

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Appendix 2 – ACQ- 7 Questionnaire

Asthma Control Questionnaire

1 On average, during the past week, how often were you 0 Never woken by your asthma during the night? 1 Hardly ever 2 A few minutes 3 Several times 4 Many times 5 A great many times 6 Unable to sleep because of asthma 2 On average, during the past week, how bad were you 0 No symptoms asthma symptoms when you woke in the morning? 1 Very mild symptoms 2 Mild symptoms 3 Moderate symptoms 4 Quite severe symptoms 5 Severe symptoms 6 Very severe symptoms 3 In general, during the past week, how limited were you 0 Not limited at all in your activities because of your asthma? 1 Very slightly limited 2 Slightly limited 3 Moderately limited 4 Very limited 5 Extremely limited 6 Totally limited 4 In general, during the past week, how much shortness of 0 None breath did you experience because of your asthma? 1 A very little 2 A little 3 A moderate amount 4 Quite a lot 5 A great deal 6 A very great deal 5 In general, during the past week, how much of the time 0 Not at all did you wheeze? 1 Hardly any of the time 2 A little of the time 3 A moderate amount of the time 4 A lot of the time 5 Most of the time 6 All of the time 6 On average, during the past week, how many puffs of 0 None short-acting bronchodilator (e.g. Ventolin or Bricanyl) 1 1-2 puffs most days have you used each day? 2 3-4 puffs most days 3 5-8 puffs most days 4 9-12 puffs most days 5 13-16 puffs most days 6 More than 16 puffs most days 7 To be filled in by technician/physician: 0 >95% predicted 1 95-90% FEV1 pre-bronchodilator: …………………….. 2 89-80% 3 79-70% FEV1 predicted ………………………………... 4 69-60% 5 59-50% FEV1 % predicted …………………………….. 6 <50% predicted

157

TOTAL

Appendix 3 – ACT Questionnaire

Asthma Control Test™

This survey was designed to help you describe your asthma and how your asthma affects how you feel and what you are able to do. To complete it, please mark an in the one box that best describes your answer.

1. During the last 4 weeks, how much of the time has your asthma kept you from getting as much done at work, school or home? All of the time Most of the time Some of the time A little of the time None of the time

1 2 3 4 5

2. During the last 4 weeks, how often have you had shortness of breath?

More than 3 to 6 Once or twice

once a day Once a day times a week a week Not at all

1 2 3 4 5

3. During the last 4 weeks, how often have your asthma symptoms (wheezing, coughing, shortness of breath, chest tightness or pain) woken you up at night or earlier than usual in

the morning? 4 or more 2 to 3

nights a week nights a week Once a week Once or Twice Not at all

1 2 3 4 5

4. During the last 4 weeks, how often have you used your rescue inhaler or nebuliser medication (such as Salbutamol)? 3 or more Once or twice per 2 or 3 Once a week times per day day times per week or less Not at all

1 2 3 4 5

5. How would you rate your asthma control during the last 4 weeks?

Not Controlled Poorly Somewhat Well Completely at all Controlled Controlled Controlled Controlled 158 1 2 3 4 5 Appendix 4 – Sputum processing worksheet

Induced Sputum Collection

Time of final : (hh/mm) expectoration

Time of processing : (hh/mm)

Processed by (Name)

Colour Sputum Appearance White Grey Green Yellow Brown Red Mucoid Purulent MP (in between)

Other Comments :

Total Sample Weight

Weight of tube g Weight of tube and sputum g Total sputum plug weight: g

Glass Bead PBS Processing N/A

Weight of tube g Weight of tube and sputum g Collected sputum plug weight: (A) g

Volume of PBS added: 8 x (A) mL : Start time on roller hh/mm : End time on roller hh/mm Number of Vials Prepared: Volume in each vial:

Time to -20°C: : Stored: Staff Initials: ______Time to -80°C: : Stored: Staff Initials: ______

159

PBS Processing

Weight of tube g Weight of tube and sputum g Collected sputum plug weight: (A) g

Volume of PBS added: 8 x (A) mL : Start time on roller hh/mm : End time on roller hh/mm

Sputum PBS Supernatant Vials Prepared:

Time into centrifuge : hh/mm Time out of centrifuge : hh/mm Volume of PBS removed mL Time into micro-centrifuge : hh/mm Time out of micro-centrifuge : hh/mm Number of vials prepared: Volume in each vial:

Time to -20°C: : Stored: Staff Initials: ______Time to -80°C: : Stored: Staff Initials: ______

DTT Processing

Volume of 0.2% Sputolysin or 0.2% DTT added: 4 x (A) mL Start time on roller : hh/mm End time on roller : hh/mm Weight of tube g Weight of tube and filtrate g Weight of filtrate g

160

Sputum DTT Supernatant Vials Prepared

: Time into centrifuge hh/mm : Time out of centrifuge hh/mm Number of Vials Prepared: Volume in each vial:

Time to -20°C: : Stored: Staff Initials: ______Time to -80°C: : Stored: Staff Initials: ______

Haemocytometer counts:

Quadrant Non-Squamous Cells Total Non Squamous Cells Total Cells Squamous

Viable Dead Viable + Dead

Total

Mean XV= XD= XV+XD= XS= XV+XD+XS=

161

Volume of Filtrate or PBS added to cell pellet mL (B) Dilution Factor

Total non-squamous cell count Dilution Factor x (XV + XD) x ___.______x 106 cells/ml (C) 104

% viability of non-squamous cells [XV ÷ (XV + XD)] x 100 %

% Squamous cells [XS ÷ (XS + XV + XD)] x 100 %

Absolute number of retrieved cells C x B ___.______x 106 (D)

Volume of PBS required to make 0.5 x D / 0.5 ___.______mL 106/ml

Total non-squamous cell count/g D / A ___.______x 106 cells/g (E) sputum weight

Cytospin Sample Preparation:

ICC Sample Preparation:

Time into cytospin : hh/mm Time out of cytospin : hh/mm Number of differential cell slides produced: 50µl: 75µl: 100µl:

Time into cytospin : hh/mm Time out of cytospin : hh/mm Number of ICC slides produced: Volume used: µl Date slides wrapped in foil: Date placed at - 80°C:

Differential Cell Slide Staining Date slides fixed: ___ /___ /___

Date slides stained: ___ /___ /___

162 Differential Cell Count:

First Cytoslide Count:

Raw % Proportion Absolute Cell Type Counts cell count / total count Slide Information x 100 % value/100 x E

(%) (106/g) Neutrophil Slide counted (µl):

(106/g) Macrophage (%) 50µl

(106/g) Eosinophil (%) 75µl

(106/g) Lymphocyte (%) 100 µl

(106/g) Bronchial Epithelial (%) Quality: Total (%) E= ___.______x Acceptable (non-squamous) 106cells/g

Unacceptable Squamous

Second Cytoslide Count (only if the first is unacceptable):

Raw % Proportion Absolute Cell Type Counts cell count / total count Slide Information x 100 % value/100 x E

(%) (106/g) Neutrophil Slide counted (µl):

(106/g) Macrophage (%) 50µl

(106/g) Eosinophil (%) 75µl

(106/g) Lymphocyte (%) 100 µl

(106/g) Bronchial Epithelial (%) Quality: Total (%) E= ___.______x Acceptable (non-squamous) 106cells/g

Unacceptable Squamous

163

164