UBC Theses and Dissertations

UBC Theses Logo

UBC Theses and Dissertations

Molecular profiling of the peripheral blood response to allergen inhalation challenge in asthmatics Kam, Sarah Hui Ying 2012

Your browser doesn't seem to have a PDF viewer, please download the PDF to view this item.

Item Metadata

Download

Media
24-ubc_2012_spring_kam_sarah.pdf [ 3.49MB ]
Metadata
JSON: 24-1.0103454.json
JSON-LD: 24-1.0103454-ld.json
RDF/XML (Pretty): 24-1.0103454-rdf.xml
RDF/JSON: 24-1.0103454-rdf.json
Turtle: 24-1.0103454-turtle.txt
N-Triples: 24-1.0103454-rdf-ntriples.txt
Original Record: 24-1.0103454-source.json
Full Text
24-1.0103454-fulltext.txt
Citation
24-1.0103454.ris

Full Text

MOLECULAR PROFILING OF THE PERIPHERAL BLOOD RESPONSE TO ALLERGEN INHALATION CHALLENGE IN ASTHMATICS  by  Sarah Hui Ying Kam B.M.L.Sc., The University of British Columbia, 2008  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUREMENTS FOR THE DEGREE OF MASTER OF SCIENCE  in  The Faculty of Graduate Studies (Experimental Medicine)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  April 2012  © Sarah Hui Ying Kam, 2012  ABSTRACT Allergen inhalation challenge (AIC) triggers biphasic responses in allergic asthmatic individuals. Airway narrowing represents the early phase response, which typically occurs within 30 minutes of allergen inhalation. In 50-60% of allergic asthmatic adults, the early response is followed by the late phase response, usually starting around 3 hours after AIC, and characterized by cellular inflammation of the airway, increased lung tissue permeability, and mucus secretion. The pathways leading to the late response are not completely understood. The purpose of this thesis is to investigate the mechanisms behind the allergic asthmatic response profiles using peripheral blood samples obtained from asthmatics prior to and 2 hours following AIC. Subjects exhibited either an isolated early response of ≥20% fall in FEV1 (isolated early responder – ER), or an early response followed by a late phase response of ≥15% fall in FEV1 (dual responder – DR). Genome-wide transcriptional profiling using microarrays indicated significant perturbations in the Nrf2 (NF-E2-related factor 2)-mediated oxidative stress response pathway following allergen inhalation. Notably, the ABCC1 (ATP-binding cassette, sub-family C (CFTR/MRP), member 1) gene within the pathway showed a decreased expression post-challenge, as validated through RT-qPCR. Furthermore, a significant decrease in the level of plasma chemokine (C-C motif) ligand 2 (CCL2) was evident, which was replicated using immunoassays in additional cohorts of allergic rhinitis and individuals with occupational asthma. However, this may be attributable to inherent fluctuations, based on similar results from control subjects. The comparison of transcriptomic response profiles between ERs and DRs undergoing cat allergen inhalation challenge revealed linoleic acid metabolism as the most significant ii  pathway. Separation of whole-blood gene expression profiles into cell-specific signals using the csSAM algorithm suggested that key transcriptomic differences lie in eosinophils and lymphocytes when comparing between ERs and DRs at the postchallenge time point. These findings are in support of the current model of asthma pathophysiology and provide valuable insights into molecular changes occurring as early as 2 hours after allergen inhalation. Further study into the underlying mechanisms leading to the different response patterns may expose new therapeutic targets effective in minimizing the late response, which is associated with chronic asthma.  iii  PREFACE Subject recruitment, allergen challenges, and peripheral blood samples collection were performed by the following collaborators:   Dr. GM Gauvreau and Dr. PM O’Byrne – McMaster University    Dr. JM FitzGerald – University of British Columbia    Dr. L-P Boulet – Université Laval    Dr. A Ellis – Queen’s University    Dr. C Carlsten – University of British Columbia  I was responsible for conducting the experiments and analyses using the collected samples and clinical information. The assessment of oxidative and inflammatory molecules in Chapter 2 and the multiplex cytokine assay described in Chapter 3 were conducted by Dr. D Radzioch and G Wojewodka, collaborators at McGill University. I was responsible for data analysis and all subsequent interpretations of results. A portion of Chapter 2 has been modified and published. Kam SHY, Singh A, He J-Q, Ruan J, Gauvreau GM, O’Byrne PM, FitzGerald JM, Tebbutt SJ. Peripheral blood gene expression changes during allergen inhalation challenge in atopic asthmatic individuals. The Journal of Asthma. 2012 Feb 9;(5):219–26. I participated in data analysis, conducted interpretations of results, and wrote most of the manuscript. This study has been approved by the Research Ethics Board of Providence Health Care Research Institute, UBC, with the ethics approval number of H09-02114. iv  TABLE OF CONTENTS Abstract.......................................................................................................................... ii Preface .......................................................................................................................... iv Table of Contents .......................................................................................................... v List of Tables ................................................................................................................ ix List of Figures ............................................................................................................... x Acknowledgements...................................................................................................... xi Dedication .................................................................................................................... xii 1 Introduction ................................................................................................................ 1 1.1 ASTHMA OVERVIEW AND PATHOGENESIS ..................................................... 1 1.2 ALLERGEN INHALATION CHALLENGE MODEL ................................................ 4 1.3 MOLECULAR MECHANISMS OF THE EARLY AND LATE RESPONSES .......... 8 1.3.1 Early Asthmatic Response............................................................................... 8 1.3.2 Late Asthmatic Response ................................................................................ 9 1.4 TRANSCRIPTIONAL PROFILING OF PERIPHERAL BLOOD ........................... 13 1.5 OVERVIEW OF EXPERIMENTAL GOALS AND RESEARCH FOCUS .............. 14 2 Pre versus Post Allergen Inhalation Challenge ..................................................... 16 2.1 INTRODUCTION ................................................................................................. 16 2.2 METHODS .......................................................................................................... 17 2.2.1 Subjects and Allergen Inhalation Challenge .................................................. 17 2.2.2 Blood Sample Collection and RNA Extraction ............................................... 19 2.2.3 Microarray Analysis ....................................................................................... 20 2.2.4 RT-qPCR Validation ...................................................................................... 20 2.2.5 Oxidative and Inflammatory Molecules Analysis............................................ 21 2.2.6 Statistical Analysis ......................................................................................... 22 2.3 RESULTS............................................................................................................ 23 2.3.1 Cohort Characteristics ................................................................................... 23 2.3.2 RNA Quality ................................................................................................... 23 v  2.3.3 Differentially Expressed Probe Sets .............................................................. 24 2.3.4 Gene Set Enrichment and Pathway Analysis ................................................ 24 2.3.5 Validation of Selected Genes ........................................................................ 28 2.3.6 Oxidative and Inflammatory Molecules .......................................................... 30 2.4 DISCUSSION ...................................................................................................... 30 2.4.1 Gene Sets...................................................................................................... 30 2.4.2 Nrf2-Mediated Oxidative Stress Response Pathway ..................................... 31 2.4.3 ABCC1 Gene ................................................................................................. 32 2.4.4 Oxidative and Inflammatory Molecules Support ............................................ 34 2.5 SUMMARY .......................................................................................................... 35 3 Chemokine (C-C Motif) Ligand 2 ............................................................................. 36 3.1 INTRODUCTION ................................................................................................. 36 3.2 METHODS .......................................................................................................... 38 3.2.1 Cohorts .......................................................................................................... 38 3.2.2 Allergen Challenges and Sample Processing ................................................ 41 3.2.3 Multiplex Cytokine Assay ............................................................................... 42 3.2.4 MSD Immunoassay Validation....................................................................... 43 3.2.5 Statistical Analysis ......................................................................................... 43 3.3 RESULTS............................................................................................................ 44 3.3.1 Cohort Characteristics ................................................................................... 44 3.3.2 Multiplex Cytokine Assay Analysis ................................................................ 45 3.3.3 CCL2 Validations ........................................................................................... 45 3.3.4 Baseline Level Correlations ........................................................................... 50 3.4 DISCUSSION ...................................................................................................... 54 3.4.1 CCL2 and CCL5 in Allergic Diseases ............................................................ 54 3.4.2 Normal CCL2 Fluctuation .............................................................................. 56 3.4.3 Baseline CCL2 Associations.......................................................................... 57 3.5 SUMMARY .......................................................................................................... 58 4 Isolated Early Response versus Dual Response................................................... 60 4.1 INTRODUCTION ................................................................................................. 60 4.2 METHODS .......................................................................................................... 61 4.2.1 Subjects, Allergen Inhalation Challenge, and Microarray Analysis ................ 61  vi  4.2.2 Statistical Analysis ......................................................................................... 64 4.3 RESULTS............................................................................................................ 66 4.3.1 Cohort Characteristics ................................................................................... 66 4.3.2 Complete Blood Cell Count and Differential Analysis .................................... 69 4.3.3 RNA Quality ................................................................................................... 69 4.3.4 Differentially Expressed Probe Sets .............................................................. 70 4.3.5 Pathway Analysis .......................................................................................... 70 4.3.6 Cell-Specific Significance Analysis of Microarrays ........................................ 73 4.3.7 Pathway Analysis of csSAM Results ............................................................. 77 4.4 DISCUSSION ...................................................................................................... 77 4.4.1 Interaction of Response and Time ................................................................. 77 4.4.2 Linoleic Acid Metabolism ............................................................................... 78 4.4.3 CsSAM for ER versus DR at Post-Challenge ................................................ 81 4.5 SUMMARY .......................................................................................................... 83 5 Conclusions and Future Directions ........................................................................ 84 5.1 OVERALL SUMMARY ........................................................................................ 84 5.2 LIMITATIONS AND FUTURE DIRECTIONS ....................................................... 85 5.3 RELEVANCE OF RESEARCH ............................................................................ 87 References ................................................................................................................... 89 Appendices ................................................................................................................ 100 Appendix 1 Sequences of Probes and Primers used in RT-qPCR......................... 100 Appendix 2 Differentially Expressed Probe Sets, Post- versus Pre-Allergen Inhalation Challenge (p≤0.01 and fold change≥1.1) ............................ 102 Appendix 3 Down-Regulated Gene Sets (FDR≤0.25) ............................................ 121 Appendix 4 Up-Regulated Gene Sets (FDR≤0.25) ................................................ 123 Appendix 5 Cytokine Level Changes after Allergen Inhalation Challenge ............. 125 Appendix 6 Differentially Expressed Probe Sets Identified by Interaction Analysis (FDR≤0.30) ......................................................................................... 131 Appendix 7 Lymphocyte-Correlated Probe Sets Significantly Lower-Expressed in DR than ER, Post-Allergen Inhalation Challenge (FDR≤0.30) .................. 144  vii  Appendix 8 Eosinophil-Correlated Probe Sets Significantly Higher-Expressed in DR than ER, Post-Allergen Inhalation Challenge (FDR≤0.30) .................. 148  viii  LIST OF TABLES Table 2.1  Subject Demographics (Pre versus Post) ................................................ 18  Table 2.2  Nine Differentially Expressed Genes in Nrf2-Mediated Oxidative Stress Response Pathway .................................................................................. 27  Table 3.1  Subject Demographics (CCL2) ................................................................ 40  Table 4.1  Subject Demographics (ER versus DR) ................................................... 63  Table 4.2  Biological Functions Identified by Interaction Analysis ............................. 71  ix  LIST OF FIGURES Figure 1.1  Asthma Pathophysiology ........................................................................... 3  Figure 1.2  Typical Response Profiles after Allergen Inhalation Challenge .................. 7  Figure 1.3  Mechanisms of the Early and Late Response.......................................... 12  Figure 2.1  Canonical Pathways Identified by Ingenuity Pathway Analysis ................ 26  Figure 2.2  Quantitative Expression of ABCC1 Pre- and Post-Allergen Inhalation Challenge by RT-qPCR ........................................................................... 29  Figure 3.1  Plasma CCL2 Levels at Pre- and Post-Allergen Challenge ..................... 47  Figure 3.2  Baseline CCL2 Level and Age Association .............................................. 52  Figure 3.3  Baseline CCL2 Level with Age in Allergen Cohorts ................................. 53  Figure 4.1  Lung Function Profiles for ER and DR ..................................................... 68  Figure 4.2  Canonical Pathways Identified by Interaction Analysis ............................ 72  Figure 4.3  SAM and csSAM Results for the Analysis of ER versus DR at PostAllergen Challenge .................................................................................. 75  Figure 4.4  Linoleic Acid Metabolism ......................................................................... 80  x  ACKNOWLEDGEMENTS I owe my deepest gratitude to my supervisor, Dr. Scott Tebbutt, who provided invaluable support and mentorship throughout my research and studies. His undeniable passion and commitment to the project greatly motivated me. It was an honor to conduct research under his direction. I would also like to thank my supervisory committee members, Dr. Andrew Sandford and Dr. Bob Schellenberg, for their advice and guidance in my research. Without their input and expertise in the fields of asthma genetics and allergy, this thesis would not have been possible. I wish to extend my gratitude to my colleagues at the laboratory. In particular, I would like to thank Jian Ruan for his technical help and encouragement, Amrit Singh for his assistance with statistical analyses, and Masatsugu Yamamoto for his clinical expertise. I definitely benefited by learning from these individuals. I wish to acknowledge the participants of this research, as well as the many technicians who assisted with subject recruitment, allergen challenge, and sample collection. I also thank the staff at CTAG (BC Cancer Agency, Vancouver, BC, Canada) for their help with the microarray experiments. I am grateful for the friendships and support of the James Hogg Research Centre. I also wish to acknowledge the funding provided by CIHR and AllerGen NCE. Finally, I wish to express my love and gratitude to God, my family, and friends for their love, understanding, and encouragement, throughout the duration of my studies. xi  DEDICATION  To my family and friends, who have always believed in me.  xii  CHAPTER 1: INTRODUCTION 1.1 Asthma Overview and Pathogenesis Asthma is a chronic inflammatory airway disorder characterized by airway hyperresponsiveness and reversible airflow obstruction, which manifests clinically as shortness of breath, chest tightness, wheezing, and coughing (1,2). Asthma affects up to 300 million people of all ages world-wide, with approximately 250,000 dying of the disease each year (1). In parallel with allergy, the prevalence of asthma is high in urbanized countries such as Canada. While the related mortality rate is low in North America, the direct medical costs (e.g., pharmaceuticals) and indirect medical costs (e.g., time lost from work) can be substantial (1). As a complex disease, asthma is believed to be caused by a combination of genetic and environmental factors. Various asthma susceptibility genes have been identified through genome-wide association studies (GWAS), linkage studies, and candidate gene approaches. An important locus lies on chromosome 17q21, where genes such as ORMDL3 have been identified and successfully validated to be associated with asthma (3,4). The exact roles of many of these genes remain under active investigation. Environmental exposures are also crucial in the onset of asthma. Multiple studies have suggested that maternal tobacco smoking, air pollution, and high ozone levels may lead to an increased risk of developing the disease (5). Past the stage of initial sensitization, environmental factors continue to play a role in provoking asthmatic responses, also known as asthma exacerbations or asthma attacks. Indeed, airborne 1  allergens inhaled by sensitized allergic asthmatic individuals act as the main trigger for an asthmatic response. Some of these stimulants include pollen of plants, house dust mites, and animal dander (6). Hence, people diagnosed with allergic asthma may be affected seasonally or year-round, depending on their allergen of sensitization. Because environmental factors are so important in evoking asthma, avoidance of such stimulants (if and when possible) is fundamental to reducing asthmatic responses (6). Airflow obstruction experienced during an asthmatic response can be attributed to three main biological events (7) (Figure 1.1). First, there is bronchoconstriction, referring to contractions of the airway smooth muscles. Second, excessive mucus production results in the formation of mucus “plugs”, leading to airway congestion. Third, the airways are thickened due to inflammation and swelling, decreasing the overall lumen size. Chronic inflammation can further lead to airway remodeling, a process describing the alteration of normal airway structure, as often observed in patients with chronic severe asthma (8).  2  Figure 1.1 — Asthma Pathophysiology.  During an asthmatic response, the airways of a sensitized individual display three distinct characteristics: the tightening of airway smooth muscles, the production of excessive mucus, and the swelling and thickening of the airways. All of these contribute to the outcome of decreased airflow in the airways. Source: National Heart, Lung, and Blood Institute; National Institutes of Health; U.S. Department of Health and Human Services. http://www.nhlbi.nih.gov/health/health-topics/topics/asthma/  3  1.2 Allergen Inhalation Challenge Model One method of studying the asthmatic response is by using the allergen inhalation challenge (AIC) model. As the name implies, this involves “challenging” subjects with aerosolized allergens, administered through the route of inhalation. The overall goal is to elicit a response in allergic asthmatic individuals, thereby providing a platform on which to carry out clinical and research investigations. Some of these inquiries include the determination of allergic status, exploration into disease mechanisms, and testing of therapy efficacies (9). Although there are other biological models available for asthma research (such as the use of cell lines and animal models), AIC provides a unique human-based approach. This way, the findings are directly applicable to the human population, bypassing the need to demonstrate a human relevance, as is often required for in vitro and animal studies. As a well-established model, AIC has been employed since the 1970s (10) and continues to be an important tool in asthma research today. However, as with any asthmatic responses, AIC-induced allergic response can be dangerous, potentially resulting in anaphylaxis and severe bronchoconstriction (9). Therefore, the administration of allergen must be well controlled in order to avoid overdosage. One way of determining a safe starting allergen concentration is to rely on data obtained from a prior methacholine inhalation challenge and skin prick test. Methacholine inhalation challenge allows for the direct assessment of bronchial hyperresponsiveness, which can be represented by methacholine PC20 (defined as the provocative concentration of methacholine required to cause a 20% fall in lung function, as measured by forced expiratory volume in one second – FEV1). Using the 4  methacholine PC20 value, along with the lowest allergen concentration needed to cause a 2 mm wheal during the skin prick test, the concentration of allergen extract to be used in AIC can be calculated with the Cockcroft formula (11). The resulting asthmatic response is measured using spirometry. In AIC, the goal is to stimulate a 20% decrease in FEV1 as compared to baseline (pre-challenge) lung function. Beginning with an initial concentration of allergen extract as calculated above, the concentrations are gradually doubled until the 20% drop is reached, typically within 3 doubling concentrations (12). The lung function of the subject is then monitored for 7 hours post-allergen challenge. Due to the many variabilities involved in human studies, the asthmatic responses observed during AIC can be heterogeneous. However, all response profiles of mild atopic asthmatics generally follow one of three patterns (Figure 1.2). Within ten minutes of allergen inhalation, bronchoconstriction is initiated and reaches a maximum within thirty minutes, finally resolving within 3 hours (13). This early asthmatic response (EAR) is detected as a drop in FEV1, with a minimum decrease of 20% as compared to baseline. Individuals with this single response profile are accordingly known as isolated early responders (ERs). In 50-60% of allergic asthmatic adults, however, the early response is followed by a late asthmatic response (LAR) (13). These individuals are termed dual responders (DRs). The late response starts around 3 to 4 hours after allergen inhalation and is measured as a secondary FEV1 drop of at least 15%. Compared to the EAR, the LAR is more sustained, lasting from a few hours to a few days (13). In addition to these two response profiles, which account for >90% of  5  asthmatic responses, <10% of asthmatic adults display an isolated late phase response (LR). The asthmatic response pattern of either an isolated early or a dual response is generally reproducible in a given individual. Even so, studies have shown that the concentration of allergen administered during AIC may be influential to some extent. In individuals normally displaying an isolated early response profile, an increased allergen dosage appears to be effective in inducing the development of a LAR (14,15). A possible explanation is that when the concentration of allergen exceeds a threshold, additional immune cells (such as dendritic cells and T lymphocytes) are activated, leading to the downstream event of the late response (9). In addition to allergen dosage, the type of allergen used has also been shown to affect the response outcome. Hatzivlassiou et al. demonstrated that asthmatics sensitized to both grass pollen and house dust mite (HDM) displayed an isolated early response during grass pollen challenge, but a dual response to HDM challenge (16). This suggests that different allergens may trigger varying response pathways in the body.  6  Figure 1.2 — Typical Response Profiles after Allergen Inhalation Challenge.  Figure 1. Common patterns of response following allergen inhalation challenge. (a) Isolated early asthmatic response (EAR); (b) isolated late After AIC, subjects typically display one of three lung function profiles, as assessed by asthmatic response (LAR); (c) dual FEV1 response. measurements. (a) & AnLemanske, isolated early response, (b) an isolated late response, and (From Varner (c) a dual 2000.)response.  © Varner AE, Lemanske Jr RF: The early and late asthmatic response to allergen. In: Asthma & Rhinitis. Edited by Busse WW, Holgate ST, vol. 2, 2 ed. Oxford: Blackwell Science; 2000: Chapter 75: 1172-1185, by permission  7  1.3 Molecular Mechanisms of Early and Late Responses 1.3.1 Early Asthmatic Response Despite decades of research, the exact mechanisms of the early and late asthmatic responses have not been fully elucidated. Nevertheless, a sequence of events has been proposed to explain the biology behind these responses (Figure 1.3). An asthmatic individual with prior sensitization to an allergen carries circulating IgE antibodies against that specific allergen. Upon re-exposure (during AIC, for example), the epitopes of the inhaled allergen molecules are recognized by IgE antibodies bound to mast cells and basophils. Multiple interactions between allergens and antibodies result in cross-linking of the FcεRI, the high affinity IgE receptor on cell surfaces (9). This leads to activation of downstream events, mainly cellular degranulation and the release of preformed molecules, including histamine, proteolytic enzymes, and proteoglycans (17). Furthermore, newly-synthesized mediators such as leukotrienes, prostaglandins, cytokines, and chemokines are also discharged. Histamine is a potent mediator of acute inflammation, acting directly on airway smooth muscle cells and the endothelium to cause bronchoconstriction, vasodilation, mucus secretion, and edema (18). Because all of these events contribute to the immediate symptoms observed after allergen inhalation, histamine is considered to be a key player in the onset of the EAR. In addition to histamine, cysteinyl leukotrienes (LTC4, LTD4, and LTE4) released by mast cells and basophils are thought to be responsible for the majority of bronchoconstriction occurring immediately after allergen challenge (19). Indeed, cysteinyl leukotrienes receptor antagonists are commonly  8  prescribed by physicians for relief of asthmatic symptoms. Even without any medication, however, the early phase response typically resolves within 2 hours. 1.3.2 Late Asthmatic Response While the EAR is predominantly a result of bronchoconstriction, the LAR is characterized by cellular inflammation of the airways, increased bronchovascular permeability, and heavy mucus secretion. Being a downstream event triggered by allergen inhalation, the biological mechanisms leading to the LAR are still unclear. Morphologically, the airways are infiltrated by a mixture of leukocytes, consisting of eosinophils, T lymphocytes, neutrophils, basophils, and mast cells (20–23). The attraction and activation of these inflammatory cells have been attributed to various mediators released by local mast cells, basophils, and airway epithelial cells (24). Each of the infiltrating cell types mentioned above plays a role in the inflammatory state of the late phase response. Dente et al. demonstrated that sputum eosinophilia was directly related to the severity of the LAR (25). Activated eosinophils release cytotoxic products, such as eosinophil cationic protein (ECP), which damages bronchial walls, adding to its hypersensitivity and worsening the response outcome (26). The action of eosinophils is further propagated by T lymphocytes, which have been shown to expand clonally (with allergen specificity) in response to allergen challenge (22). In the airways, activated CD4+ T cells with a T helper 2 (Th2) phenotype release pro-inflammatory cytokines such as IL-4 and IL-5, inducing B-cell class switching to IgE and recruiting additional eosinophils (19). Neutrophils have also been suggested to contribute to the inflammatory process, through release of mediators including IL-8 and  9  reactive oxygen species (27). Finally, mast cells and basophils have both been shown to be increased during the late phase response and may correlate with LAR severity (21). Their involvement in the inflammatory state of the airways includes the release of histamine, cysteinyl leukotrienes, and various cytokines which help stimulate other immune cells (9). The cellular infiltrate is believed to originate from a heightened production of progenitor cells from the bone marrow (28). Previous studies have demonstrated an increase in the numbers of eosinophil/basophil colony-forming units in the bone marrow and in circulation at 24 hours post-allergen inhalation in DR but not ER subjects (29,30). Furthermore, when bone marrow cells were assessed for cytokine responsiveness through analysis of their receptors, IL-3-responsive progenitors were identified as early as 5 hours post-allergen inhalation, and IL-5-responsive progenitors were identified starting at 12 hours after AIC (29,31). IL-3 is a cytokine that promotes the differentiation of hematopoietic stem cells to the myeloid lineage and stimulates the proliferation of myeloid cells, whilst IL-5 is a key mediator in eosinophil activation and survival (32). Both cytokines may be secreted by activated T lymphocytes that are either resident in or trafficked to the bone marrow upon stimulation by allergen challenge (33). Indeed, Wood et al. have demonstrated an increased production of IL-5 by such T lymphocytes (33). Taken together, and considering that these observations were exclusive to DR individuals only, it appears that eosinophilic late phase response may be partially due to T lymphocytes in the bone marrow releasing cytokines to stimulate progenitor cell development.  10  The development of the LAR is associated with the hallmarks of chronic asthma, featuring bronchial hyperresponsiveness, constant inflammation of the airways, and long-lasting bronchoconstriction which is difficult to reverse. This is in contrast to the EAR, which is easily reversible with bronchodilators and involves minimal inflammation. In chronic asthma, cellular inflammation can further lead to tissue remodeling, causing permanent damage to the airways (8). Therefore, ongoing efforts have been made to identify the critical pathways leading to the LAR, in order to find ways to effectively inhibit it and prevent the worsening progression to chronic asthma.  11  Figure 1.3 — Mechanisms of the Early and Late Response.  Early Phase  Late Phase  Other inflammatory cells  Bronchoconstriction  The early phase response is initiated when allergen molecules bind to IgE antibodies on mast cells, causing the receptors (FceRI) to cross-link. This triggers degranulation and the release of mediators such as histamine, which causes acute bronchoconstriction. Other mediators are believed to cause subsequent progression to the late phase response, during which leukocytes such as eosinophils and T cells are recruited. The cellular inflammation leads to increased airway reactivity and damage. © Adapted by permission from Macmillan Publishers Ltd: Nature Reviews Immunology. Lukacs NW. Role of chemokines in the pathogenesis of asthma. Nature Reviews. Immunology. 2001 Nov;1(2):108–16. Copyright 2001. http://www.nature.com/nri/journal/v1/n2/fig_tab/nri1101-108a_F1.html  12  1.4 Transcriptional Profiling of Peripheral Blood Traditionally, quantification of a single mRNA molecule is performed using northern blots and reverse transcription quantitative polymerase chain reaction (RTqPCR). With advancement in technology, and a desire to study multiple genes simultaneously, genome-wide expression profiling (transcriptomics) was developed. This technique allows for the assessment of every gene in the human genome, all measured on a single microarray chip. The result is an overview of cellular functions and biological processes, as observed from the samples studied. Nowadays, genomewide transcriptional profiling has become one of the more powerful approaches to explore disease mechanisms, to assist diagnosis and to determine better treatment strategies. Indeed, there are over 17,000 articles related to microarray analysis listed in PubMed between 1995 to 2005 (34), testifying to the effectiveness of this technique. Even though analysis of microarray data can be difficult due to the problem of multiple hypothesis testing, genome-wide gene expression profiling remains a useful tool for initial investigations, the results of which can then be validated by other techniques, such as RT-qPCR. Target tissues and cells are the ideal biological materials for gene expression studies, but they are usually difficult to obtain. In recent years, peripheral blood mononuclear cells (PBMCs) have been widely used for gene expression studies in biomedical research as well as in clinical services. Since isolation of blood cell-type fractions is time-consuming, expensive, and likely to introduce additional technical variation, peripheral whole-blood material, which includes granulocytes, has become increasingly popular among researchers conducting gene expression analyses. There 13  are several advantages to using peripheral whole-blood cells in genome-wide expression profile analysis. To start, they are very easy to obtain and are the most commonly used biological material in the clinical setting. In addition, peripheral wholeblood contains various cell types, many of which participate in the immune response and transport systems that contribute heavily to various biochemical conditions and disorders. Indeed, many of these cells play a role in the inflammation of the airways during the LAR, as discussed previously. Accumulating evidence has documented the usefulness of whole-blood material over PBMCs in gene expression profile research in large-scale studies (35,36).  1.5 Overview of Experimental Goals and Research Focus Driven by the incomplete understanding of the biology behind the asthmatic response patterns, and the need for an effective treatment option to minimize the LAR, my research aimed to explore the underlying mechanisms behind why some allergic asthmatic individuals develop an isolated early response, while others develop a dual response. This was achieved through the use of the allergen inhalation challenge model in order to stimulate an asthmatic response in a controlled environment. Peripheral blood samples, collected prior to and after allergen inhalation, acted as the biological source of investigation. The longitudinal design allowed for direct comparisons between each individual’s pre- and post-status, enabling a more accurate investigation into the exact changes occurring during an asthmatic response. This project was carried out with three main objectives, as described in more details in the following chapters. The first step was a pilot study to determine whether  14  the chosen time point of 2 hours post-allergen challenge was sufficient and reasonable to detect genome-wide transcriptomic differences in the peripheral blood, as compared to pre-challenge levels. The plasma content of oxidative and inflammatory molecules was also assessed for additional support. Next, the focus was shifted to investigate pre- versus post-challenge changes in plasma cytokine levels. Through this study, chemokine (C-C motif) ligand 2 (CCL2) was identified and further examined with regards to any possible associations with subject demographics. The cohort was also expanded to include normal controls, as well as subjects with occupational asthma and allergic rhinitis. Finally, the differences in genome-wide transcriptomic profiles between ERs and DRs were explored, taking into account both the pre-challenge and postchallenge data. A concluding chapter summarizes the overall findings, future directions, and implications of the results.  15  CHAPTER 2: PRE VERSUS POST ALLERGEN INHALATION CHALLENGE 2.1 Introduction The interlude between the early and the late phase response, as measured by FEV1 in dual responders, typically occurs around 2 to 3 hours after an asthmatic individual undergoes AIC. Therefore, this may be a reasonable time to assess any deviations in pathway activation patterns between the isolated early response and the dual response. Previous studies of asthmatic AIC have concentrated on uncovering the disease mechanisms by obtaining and testing blood samples around 24 hours after the inhalation of allergen (37,38). However, reports on the possible biological changes that may occur as early as 2 hours after allergen challenge have been limited. Given the importance of this time frame and the key role of the peripheral blood in relaying biological signals, it is of great interest to test the hypothesis that changes in the peripheral blood of asthmatic individuals can be detected within 2 to 3 hours after AIC. The determination of a valid time point to observe changes is a crucial first step before attempts to differentiate pathways between the isolated early and the dual responses can be taken. Furthermore, if molecular alterations are detectable within such a short time span, this may be helpful in identifying novel targets for early therapeutic interventions. This chapter aims to assess the molecular changes in the peripheral blood 2 hours after AIC. This will be accomplished mainly through genome-wide transcriptional  16  profiling using microarrays. Also, perturbations in the levels of inflammatory and oxidative lipid molecules in the peripheral blood will be examined for additional support.  2.2 Methods 2.2.1 Subjects and Allergen Inhalation Challenge Sixteen adult subjects (age 20-60) with stable, mild atopic asthma were recruited from McMaster University (10 subjects) and Vancouver General Hospital (VGH) - UBC (6 subjects), following informed consent. Diagnosis of asthma was based on the Global Initiative for Asthma (GINA) criteria. All subjects were non-smokers, free of other lung diseases, and not pregnant. All had a baseline forced expiratory volume in one second (FEV1) ≥70% of predicted, and the provocative concentration of methacholine required to produce a 20% decrease in FEV1 (PC20) was ≤16 mg/ml in all except for one individual (39). Subject demographics are listed in Table 2.1. A skin prick test and a methacholine inhalation challenge, as described by Cockcroft (40,41), were performed on each subject. Based on these procedures, the concentration of allergen required to achieve a 20% decrease in FEV1 was predicted using the Cockcroft formula (11). One day after methacholine challenge, all participants underwent allergen inhalation challenges as described by O’Byrne et al. (42), using extracts of house dust mite (HDM; Dermatophagoides pteronyssinus), cat dander, or ragweed and grass (Timothy or Orchard) pollen, as indicated by the skin prick test. The FEV1 lung function of subjects was monitored for 7 hours post-challenge. All subjects developed an EAR of ≥20% drop in FEV1 from baseline between 0 and 3 hours.  17  Table 2.1 — Subject Demographics (Pre versus Post).  Subject  Site  Age (yr)  Sex  Mch PC20a (mg/ml)  1  VGH  36  M  3.2  2  VGH  35  F  0.64  3  VGH  47  M  0.28  4  McM  21  F  EDTA (5 Subjects)  5 6 7 8 9  McM McM McM McM McM  20 27 23 60 22  PAXgene Validation (7 Subjects)  10 11 11Rc 12 13 14 15 16  VGH VGH VGH VGH McM McM McM McM  1  Cohort  PAXgene (4 Subjects)  Lipids and Oxidative Molecules (8 Subjects)  Allergenb  % Fall in FEV1 (EAR)  % Fall in FEV1 (LAR)  -61  -38  -27  -5  -23  -17  1.09  Timothy Grass Timothy Grass Orchard Grass HDMDP  -32.1  -12.5  F F M F M  9.62 1.45 10.9 2.19 4.28  Cat HDMDP Cat Cat HDMDP  -37.7 -43.3 -31.4 -25.5 -22.7  -17.3 -16.7 -15.1 -6.7 -19.9  42 41 41 52 21 33 18 21  M M M F F M F F  0.13 1 0.69 N/A 6.96 3.17 27.86 4.72  Cat Grass Mix Grass Mix Cat Ragweed HDMDP HDMDP Cat  -23 -21 -42 -33 -26.9 -29.5 -46.4 -20  -9 -7 -31 -27 0 -19.7 -25.9 -20  VGH  36  M  3.2  -61  -38  2  VGH  35  F  0.64  -27  -5  3  VGH  47  M  0.28  -23  -17  10 13 14 15 16  VGH McM McM McM McM  42 21 33 18 21  M F M F F  0.13 6.96 3.17 27.86 4.72  -23 -26.9 -29.5 -46.4 -20  -9 0 -19.7 -25.9 -20  Timothy Grass Timothy Grass Orchard Grass Cat Ragweed HDMDP HDMDP Cat  a  Methacholine PC20. HDMDP=House dust mite (Dermatophagoides pteronyssinus). c Subject 11 received a repeated allergen inhalation challenge one month later. b  18  2.2.2 Blood Sample Collection and RNA Extraction Peripheral venous blood samples were drawn at two time points, immediately prior to AIC and at 2 hours after the last inhaled allergen dose. The blood samples from 11 subjects were collected into PAXgene Blood RNA tubes (PreAnalytiX – Qiagen / BD, Valencia, CA, USA), with one subject (subject 11 in Table 2.1) undergoing a repeated AIC one month later, to make a total of 12 sets of PAXgene blood samples. For each of these PAXgene samples, a corresponding blood sample was drawn using standard EDTA tubes. Peripheral blood was also collected from 5 additional subjects into EDTA tubes only, without the use of PAXgene tubes. All of the samples collected pre- and post-allergen challenge were frozen and transported to the laboratory on dry ice, where they were stored at –80°C until RNA extraction. From thawed PAXgene tube samples, intracellular RNA (excluding small RNA) was purified from 2.5 ml of whole blood according to manufacturer protocols using the PAXgene Blood RNA Kit (Qiagen, Chatsworth, CA, USA). RNA (excluding small RNA) was isolated from EDTA tube samples (3.0 ml of whole-blood) following a modified TRIzol-based extraction method that uses a combination of the TRIzol® LS Reagent (Invitrogen, Carlsbad, CA, USA) and the RNeasy mini kit (Qiagen, Chatsworth, CA, USA). The yield and quality of RNA were assessed by NanoDrop 8000 Spectrophotometer (Thermo Scientific, Wilmington, DE, USA) and Agilent 2100 Bioanalyzer following the RNA 6000 Nano Kit protocol (Agilent Technologies, Santa Clara, CA, USA).  19  2.2.3 Microarray Analysis Microarray analysis was performed on a cohort of 4 PAXgene blood sample pairs and 5 EDTA blood sample pairs (different subjects). Genome-wide RNA labeling and array hybridization were carried out by the staff at the Centre for Translational and Applied Genomics at the BC Cancer Agency (Vancouver, BC), an Affymetrix-certified service provider. Affymetrix Human Gene 1.0 ST arrays were used (Affymetrix, Santa Clara, CA, USA). The pre- and post-challenge RNA samples from each subject were processed at the same time to avoid possible confounding batch effects. 2.2.4 RT-qPCR Validation RT-qPCR of 9 selected genes was performed on an additional 8 PAXgene blood sample pairs. RNA was converted into cDNA using SuperScript RNase H- Reverse Transcriptase (Invitrogen, Carlsbad, CA, USA) according to the manufacturer's instructions. Quantitative PCR was carried out in duplicate. 20 ng cDNA was reacted with 2× Agilent Brilliant qPCR master mix with high ROX (internal reference dye), in a 12 μl reaction including appropriate forward and reverse primers (10 μM) and qPCR probe (5 μM) (Integrated DNA Technologies, Coralville, IA, USA). The sequences of primers and probes are provided in Appendix 1. Thermal cycling was carried out using an ABI 7900 Sequence Detection System (Applied Biosystems, Carlsbad, CA, USA) with the following profile: 95 °C for 10 min, 92 °C for 15 s and 60 °C for 1 min for 45 cycles. Three housekeeping genes, β-Glucuronidase (GUSB), Glyceraldehyde-3phosphate dehydrogenase (GAPDH) and Phosphoglycerokinase (PGK1), were selected based on their low coefficient of variation (CV) values across all samples in the  20  microarray data. Efficiency standard curves were generated by plotting a serial dilution of the cDNA amount (derived from a pooled RNA sample) against the threshold cycle (Ct) value for each gene. The relative quantitative value of each sample was normalized using a factor calculated from the expression levels of the three housekeeping genes using the geNorm algorithm (43). 2.2.5 Oxidative and Inflammatory Molecules Analysis Peripheral blood samples collected with EDTA-coated tubes were centrifuged at 500g for 10 minutes at room temperature to separate the layers of plasma, buffy coat, and erythrocytes. The plasma was isolated and sent to collaborators at McGill University, where several markers of oxidative stress response and inflammation were analyzed. In detail, plasma was first suspended in 1 mM butylated hydroxyanisole (BHA) in chloroform and methanol (2:1 vol) in order to protect the integrity of the samples. Following a previously described method (44), lipids were extracted from these plasma samples using chloroform/methanol (2:1). Thin layer chromatography was performed to identify the phospholipids present. Finally, the fatty acids were esterified using diazomethane and the esters were quantified using gas chromatography/mass spectrometry (Hewlett Packard5880A, WCOT capillary column (Supelco-10, 35 m×0.5 mm, 1 μm thick)) using commercial standards (Sigma-Aldrich, Oakville, ON, Canada). Arachidonic acid (AA) and docosahexaenoic acid (DHA) were extracted and analyzed as previously described (45). The AA/DHA ratio was calculated by dividing the concentration of AA by the concentration of DHA for individual samples. Initially, analysis was performed for a subset of 8 subjects (Table 2.1). This was  21  subsequently expanded to include another 21 individuals who were not previously analyzed (demographics not shown). 2.2.6 Statistical Analysis CEL files containing the probe intensity data from the Affymetrix microarray analysis were imported into Partek Genomics Suite 6.5 (Partek Inc, St Louis, MO, USA). Background correction, quantile normalization and probe summarization were performed using robust multi-chip average (RMA) (46). Repeated measures ANOVA (paired analysis) and paired t-tests were used to detect differentially expressed probe sets (DEPs) or differentially expressed genes (DEGs) post- versus pre-allergen challenge. DEPs or DEGs were declared significant for initial discovery purposes at the p≤0.01 level (without multiple testing corrections) with a fold change ≥1.1 (based on log2 intensity values). Gene set enrichment analysis (GSEA) was performed, using the gene sets databases c2.all.v2.5.symbols.gmt [Curated] and c5.all.v2.5.symbols.gmt [Gene ontology] (47,48). Sample pairing was achieved by baselining the raw intensity values (pre- subtracted from each corresponding post-value) prior to data input. The number of permutations was set to 1000 and the gene sets were considered significant at a false discovery rate (FDR) ≤0.25. Pathway analyses were carried out using Ingenuity Pathway Analysis (IPA – Ingenuity Systems, Redwood City, CA, USA). IPA organizes differentially expressed genes into related pathways and reports a p value that is representative of the probability that a specific set of genes has a significant number of members in a pathway. Analyses were restricted to consider genes related to immune  22  cells and lungs only. One-tailed paired t-tests were used to analyze the genes that were selected for validation using RT-qPCR (based on the hypothesis test that the direction of change would replicate). Significance was declared at the p≤0.05 level when comparing post- versus pre-allergen challenge samples. For lipids analysis, twotailed paired t-tests were used, with the significance set at p≤0.05.  2.3 Results 2.3.1 Cohort Characteristics The mean age of the 16 participants (7 males and 9 females) in the study was 32.4 ± 3.2 years (Table 2.1). The geometric mean for methacholine PC20 was 2.28 mg/ml, far below the guidelines of ≤16 mg/ml that is indicative of airway hyperresponsiveness (49). The type of allergens used were evenly distributed among the challenges, 5 of which were administered using HDM extracts, 6 with cat allergen, and 6 with either grass or ragweed pollen extracts. All subjects exhibited an EAR, with the mean drop in FEV1 being 32.1 ± 2.7% between 0 and 3 hours. Of the 17 allergen inhalation challenges, 11 also produced a LAR of ≥15% FEV1 drop. 2.3.2 RNA Quality RNA samples to be analyzed using microarrays were first assessed for quality. An initial cohort of 4 PAXgene whole-blood sample pairs was of excellent quality with a mean RNA integrity number (RIN) of 8.68 ± 0.24, while RNA from EDTA whole-blood (5 sample pairs) was of moderate quality with a mean RIN of 6.21 ± 0.34. NanoDrop analysis showed that for PAXgene sample, the 260/280 ratio was 2.12 ± 0.01, while for  23  EDTA samples, it was 1.99 ± 0.02. The above values are expressed as mean ± standard error. 2.3.3 Differentially Expressed Probe Sets Analyzing an initial 4 pairs of PAXgene samples using an ANOVA model, 524 significant probe sets (unadjusted p≤0.01 and fold change ≥1.1) were found to be differentially expressed between pre- and post-AIC (Appendix 2). Although the selection of a fold change threshold ≥1.1 seems lenient compared to other microarray-based studies that often use a 1.5 fold change threshold, it is important to take into account both the nature of the whole-blood material used for RNA extraction, and the small time interval (2 hours) between pre- and post-sampling. Considering the minimal effects of the fold change cut-off, it can be regarded that the p value alone was used to determine significance. 2.3.4 Gene Set Enrichment and Pathway Analysis The complete dataset of normalized intensity values was entered into GSEA in order to explore the biological context of the perturbed genes. At the default cut-off of FDR≤0.25, 51 gene sets were found to be significantly down-regulated post-challenge, with the most significant gene set identified to be the Nakajima eosinophil gene set at FDR=3.82E-2 (Appendix 3). Using the same significance cut-off, 53 gene sets were found to be up-regulated post-challenge (Appendix 4). Pathway analysis was performed based on the top ~100 probe sets using Ingenuity Pathway Analysis (IPA). This was done in order to reduce the false positive findings that are often associated with single gene level analysis. Of the 94 probe sets 24  initially entered into the pathway analysis, 82 met the criteria for inclusion. The biological functions identified failed to reach statistical significance after multiple testing corrections. For canonical pathways, the Nrf2 (NF-E2-related factor 2)-mediated oxidative stress response pathway was the sole significant canonical pathway at adjusted p=5.31E-3 (Figure 2.1). Nine genes were identified to be differentially expressed in this pathway: CUL3, DNAJA2, DNAJC1, DNAJC19, DNAJC21, KRAS, SOD1, and PTPLAD1 were found to have an increased expression level post-challenge, while ABCC1 displayed a decreased level of expression (Table 2.2).  25  Figure 2.1 — Canonical Pathways Identified by Ingenuity Pathway Analysis.  The top 10 canonical pathways and their significance values are presented. The horizontal threshold line (meeting the left y-axis at 1.30) denotes statistical significance at p≤0.05 after Benjamini and Hochberg multiple testing corrections. The square points represent the ratio, which was calculated as the number of genes in a given pathway that meet significance, divided by the total number of genes that make up that pathway. Nrf2-mediated oxidative stress response was the only canonical pathway to reach significance.  26  Table 2.2 — Nine Differentially Expressed Genes in Nrf2-Mediated Oxidative Stress Response Pathway.  Probe Set ID  a  Gene Symbol  4 PAXgene Sample Pairs (Microarray)  5 EDTA Sample Pairs (Microarray)  4 PAXgene Sample Pairs (RT-qPCR)  8 Independent Sample Pairs (RT-qPCR)  P Valuea (2-Tailed)  Fold Change  P Valuea (1-Tailed)  Fold Change  P Value (1-Tailed)  Fold Change  P Value (1-Tailed)  Fold Change  7993478  ABCC1  5.00E-04  -1.17  3.30E-03  -1.11  2.10E-02  -1.09  3.90E-02  -1.16  8059393  CUL3  4.72E-02  1.26  1.60E-03  1.11  8.90E-02  1.80  1.72E-01  2.78  8001185  DNAJA2  3.20E-03  1.17  2.82E-02  1.10  6.30E-02  1.07  2.02E-01  1.06  7932512  DNAJC1  9.00E-04  1.15  1.91E-02  1.11  1.88E-01  1.03  2.42E-01  -1.06  8092314  DNAJC19  2.89E-02  1.29  1.24E-02  1.10  1.38E-01  1.35  1.48E-01  -1.09  8104838  DNAJC21  5.40E-03  1.14  4.86E-02  1.11  3.50E-02  1.11  1.72E-01  -1.15  7961865  KRAS  8.40E-02  1.16  1.10E-03  1.16  3.12E-01  -1.02  1.99E-01  1.05  8068168  SOD1  7.60E-03  1.15  9.90E-03  1.09  9.10E-02  5.86  4.56E-01  1.04  7984263  PTPLAD1  3.62E-02  1.15  5.10E-03  1.15  2.80E-02  2.88  3.32E-01  -1.60  P values were not corrected for multiple testing.  27  2.3.5 Validation of Selected Genes Using microarray analysis, the 9 DEGs within the Nrf2-mediated oxidative stress response pathway were tested in a new cohort consisting of 5 independent subjects whose blood samples were collected into EDTA tubes. All of the 9 DEGs reached significant levels of differential expression post-allergen challenge with a one-tailed p value cut-off of 0.05 (Table 2.2). In order to technically validate the 9 DEGs identified from the microarray results, RT-qPCR was performed on the RNA obtained from the same samples that were used for the initial microarray analysis (4 subjects). Three genes (ABCC1, DNAJC21 and PTPLAD1) were replicated with a one-tailed p value cut-off of 0.05 (Table 2.2). Subsequently, RT-qPCR was carried out using 8 new sets of PAXgene tube samples as hypothesis-testing of the 9 genes. ABCC1 was the only gene that replicated with a onetailed p value cut-off of 0.05 (Table 2.2). Pre- and post-challenge ABCC1 gene expression levels as detected by RT-qPCR are shown in Figure 2.2.  28  Figure 2.2 — Quantitative Expression of ABCC1 Pre- and Post-Allergen Inhalation Challenge by RT-qPCR.  Relative mRNA levels of ABCC1, as detected in PAXgene peripheral blood samples, were determined using RT-qPCR on a) the 4 original sample pairs with the microarray data, and b) 8 additional sample pairs. Samples were run in triplicates. Values were normalized with a normalized factor calculated using three housekeeping genes: GUSB, PGK1 and GAPDH. P values are based on a one-tailed paired t-test.  29  2.3.6 Oxidative and Inflammatory Molecules Additional support for a perturbed oxidative stress response as implicated by the gene expression results was evident when examining plasma levels of oxidative and inflammatory molecules as assessed by collaborators at McGill University. The preand post-allergen challenge samples from a subset of 8 out of the 16 individuals (Table 2.1) were tested initially. The levels of free docosahexaenoic acid (DHA) and arachidonic acid (AA) phospholipid in the plasma were found to be significantly decreased following AIC (p=6.1E-3 and p=1.8E-2, respectively). The AA/DHA ratio was also significantly decreased post-challenge at p=3.3E-2. When an additional 21 subjects were included to form a cohort of 29 individuals with paired samples, the analysis showed an up-regulation of nitrotyrosine (p=5.5E-3) and a down-regulation of ceramide (p=3.0E-2) after challenge.  2.4 Discussion 2.4.1 Gene Sets In this study, the levels of 9 gene transcripts in the Nrf2 pathway were found to be significantly higher (CUL3, DNAJA2, DNAJC1, DNAJC19, DNAJC21, KRAS, SOD1, and PTPLAD1) or lower (ABCC1) post-AIC. Three validation studies were conducted, including microarray analysis using a cohort of 5 independent subjects, RT-qPCR on the original PAXgene samples used to generate the initial data, and RT-qPCR on 8 new pairs of samples. ABCC1 was the only gene displaying a consistently significant result, with lowered expression levels post-challenge in all sets of data.  30  Coupled with previous studies showing that 2 hours post-exposure to diesel could cause lung function decline with increased biomarkers of neutrophilic inflammation in sputum (50), and that peripheral blood can be used to decipher gene expression patterns in asthmatics (51), the data indicates that 2 hours post-AIC is a reasonable time point to observe changes in the peripheral blood gene expression profiles, even when using a small sample size. GSEA identified the Nakajima eosinophil gene set (renamed from NAKAJIMA_MCSMBP_EOS) (52) as the most significantly down-regulated gene set post-challenge using an initial cohort of 4 pairs of PAXgene blood samples (Appendix 3). Because of the role of eosinophils in allergic diseases (26), a significant change post-challenge in this gene set is of particular interest in our study of asthmatics undergoing allergen inhalation challenge. Specifically, the discovery of perturbations in eosinophil-specific transcripts may lead to a better understanding of the biological processes occurring in eosinophils during an asthmatic response. A limitation in this study, however, was that the frequencies of the various cell types in the peripheral whole blood were not measured for all of the samples. Therefore, possible confounding effects of dynamic changes in cell type numbers on gene expression measurements could not be taken into account. 2.4.2 Nrf2-Mediated Oxidative Stress Response Pathway The Nrf2-mediated oxidative stress response pathway was the only differentially expressed canonical pathway following AIC in asthmatics. To reduce the possibility that this was a false positive finding, the hypothesis was tested in an independent cohort  31  consisting of 5 subjects whose pre- and post-allergen challenge blood samples were collected into EDTA tubes. (These subjects were recruited and challenged prior to implementing the use of PAXgene tubes.) Additionally, the results were tested through RT-qPCR on 9 selected genes in the Nrf2-mediated oxidative stress response pathway. This was performed on the original 4 subjects previously used for the microarray analysis, as well as on 8 new sample pairs from additional subjects. ABCC1 was the only gene showing a consistently lowered expression level post-challenge (p≤0.05). Oxidative stress plays an important role in allergic reactions, as triggered by allergen challenges (53,54). In oxidative stress, Nrf2 detaches from its inhibitor Keap1 in the cytoplasm and translocates to the nucleus, leading to transcription of genes encoding a group of stress-induced proteins by binding to the antioxidant response elements (AREs) in the promoter regions (55–57). Thus, Nrf2 activates cellular rescue pathways against oxidative injury and inflammation/immunity (58). The present study has demonstrated that peripheral blood cell transcripts from a gene identified to be in the Nrf2 pathway – ABCC1 – was expressed at a significantly lowered level in asthmatic subjects 2 hours post-AIC, as compared to pre-challenge. 2.4.3 ABCC1 Gene ABCC1/MRP1 (ATP-binding cassette, sub-family C (CFTR/MRP), member 1) was the single gene that retained significance through both the microarray and the RTqPCR analyses. This gene codes for a protein belonging to the family of ATP-binding cassette transporters, which transports various molecules across cellular membranes, both intra-cellularly and extra-cellularly. Specifically, the protein product of ABCC1  32  mediates the ATP-dependent transport of various organic anions, using molecules such as oxidized glutathione and cysteinyl leukotrienes as substrates (59,60). Interestingly, oxidized glutathione forms a link back to the topic of oxidative stress; firstly because the molecule is generated by the activity of antioxidant enzymes (61). Secondly, an increase in the ratio of oxidized glutathione to its naturally reduced form is indicative of oxidative stress (62). Further relevance for the clinical presentation of asthma lies within cysteinyl leukotrienes, a type of fatty signaling molecule that can cause bronchial smooth muscle contraction and stimulate pro-inflammatory activities, including the recruitment of eosinophils to the asthmatic airways (63,64). Finally, a previous pharmacogenetics study has identified a single-nucleotide polymorphism (SNP) in the ABCC1 gene that was associated with an increase in % predicted FEV1 in asthma patients who had undergone treatment with the leukotriene receptor antagonist montelukast (65). In the current study, the gene expression of ABCC1 was shown to have decreased 2 hours post-AIC. This finding suggests that there may also be a corresponding reduction in the activity of the membrane transport system as facilitated by the gene product of ABCC1. However, such a conclusion, along with its biological implications, cannot be so readily drawn, given that peripheral blood samples rather than lung tissues were used as the source of mRNA. Peripheral blood contains a heterogeneous mixture of immune cells, all of which could contribute to the gene expression signals. Hence, it is difficult to decipher between the various cell types to understand the biological mechanisms, which also may not be reflective of the processes occurring directly in the lungs. 33  2.4.4 Oxidative and Inflammatory Molecules Support Building on the finding of a differentially expressed oxidative stress response pathway, additional support was provided through the work of collaborators, who assessed molecular indicators of oxidative stress in the plasma. Using a subset of samples consisting of 8 pre- and post-challenge pairs, and a subsequent expanded cohort, the data indicated changes in the signals of oxidative stress and inflammation, through perturbed levels of DHA, AA, nitrotyrosine, and ceramide following AIC. DHA, an omega-3 (ω-3) fatty acid, and AA, an omega-6 (ω-6) fatty acid, are both essential fatty acids in the human body involved in the inflammatory response. In the biological pathway, these two families of fatty acids are in close interactions, competing with each other for the same enzymes. However, the health benefits of these lipids are vastly different. DHA has been shown by numerous studies to be anti-inflammatory (66,67), lowering inflammatory markers and cytokines. AA, on the other hand, has been shown to contain pro-inflammatory properties and increase the risk of various diseases, especially when the levels of ω-6 fatty acids greatly exceed the levels of ω-3 (68–71) Hence, the ratio of AA/DHA is essential to assess the overall degree of inflammation. In the present data, a significant decrease post-allergen challenge was noted in the levels of DHA, AA, and AA/DHA ratio, indicating a perturbed state of inflammation in the peripheral blood after challenge. Nitrotyrosine, which was found to be up-regulated, is a molecule that is indicative of the presence of reactive nitrogen species (RNS) (72). Because RNS are often associated with reactive oxygen species (ROS) in causing oxidative/nitrosative stress  34  resulting in cellular damage, this molecule was worth assessing within the context of a perturbed oxidative stress response, as already shown in my data. Ceramide is a lipid that can act as a signaling molecule to regulate a wide range of cellular processes, including differentiation, proliferation, and apoptosis (73). Previous studies have suggested that oxidative stress and ceramide are closely linked, especially in the context of cell death induction (74). Evidence for this includes common apoptotic triggers for the production of ROS and ceramide, and extensive cross-talk between the two signaling pathways that are mutually influential to each other (74). Hence, a significant decrease in plasma ceramide level post-allergen challenge may be a reflection of an altered oxidative stress response, as was suggested through the microarray analysis.  2.5 Summary This preliminary study has demonstrated that significant changes can be detected in the peripheral blood genomic profile at 2 hours after asthmatic individuals undergo allergen inhalation challenge. The Nrf2-mediated oxidative stress response pathway was identified as a perturbed pathway, and the ABCC1 gene was validated by both microarray analysis and RT-qPCR to be expressing at a significantly lower level post-challenge. These findings were further supported by collaborators’ work, which showed corresponding changes in the levels of various oxidative and inflammatory molecules in the plasma. All of these results are valuable contributions to an initial step in exploring the biology behind the asthmatic response at 2 hours post-allergen inhalation challenge.  35  CHAPTER 3: CHEMOKINE (C-C MOTIF) LIGAND 2 3.1 Introduction In asthmatics undergoing AIC, cell signaling plays a vital role in determining the final outcome and severity of response. Cytokines represent one such means of intercellular communication that is extensively used, especially by cells in the immune system. Numerous studies have established their importance in the pathogenesis of asthma, demonstrating their effects on inflammation and airway remodeling (75,76). In particular, cytokines produced by T helper (Th) 2 cells are believed to be major contributors in mild asthma through stimulation of immune cell differentiation, and have been studied as potential therapeutic targets (77–80). On the other hand, cytokines with anti-inflammatory effects have also been suggested to have a role in helping to contain excessive allergic inflammation (81). Given this and the ability of cytokines to travel through the blood stream to exert effects on distant cells, it is hypothesized that changes in cytokine levels can be detected in the peripheral blood 2 hours after AIC, as compared to pre-challenge levels. A positive finding would help reinforce the current model of asthma pathophysiology, in which the secretion of cytokines shortly after allergen inhalation is believed to be a major factor leading to the inflammatory state of the airways in the LAR. If shown to be true, this would also provide strong additional support for the results of the previous chapter – that molecular changes are indeed present in the peripheral blood at 2 hours post-challenge.  36  Furthermore, it is worthwhile to investigate any differences in cytokine profiles that may be distinguishable between the isolated early responders and the dual responders, especially at the time point of 2 hours post-challenge when these two response profiles start to diverge. Based on the proposed mechanism that the recruitment of additional inflammatory cells to the lungs is the main driving force for the LAR, it would be of great interest to observe a corresponding cytokine profile in DRs that is absent from ERs. Such discoveries can easily translate into potential therapeutic targets, by way of cytokines and their receptors, to minimize the late phase response. The aim of this chapter is to explore the cytokine profiles as found in the peripheral blood plasma, pre- and 2 hours post-allergen inhalation challenge. This will be performed by testing the samples against a panel of cytokines/chemokines, with follow-up validation studies using plasma from various other cohorts, including control subjects. One major finding, and the focus of a large portion of the chapter, is chemokine (C-C motif) ligand 2 (CCL2), also called monocyte chemotactic protein-1 (MCP-1). This cytokine is secreted by various cells, including monocytes, macrophages, lymphocytes, fibroblasts, and keratinocytes (7,82). It binds to the cell surface receptors CCR2 and CCR4 (83). As its name implies, this cytokine displays chemotactic abilities, attracting monocytes, basophils, and lymphocytes but not neutrophils or eosinophils (7,82,84). Accordingly, CCL2 has been implicated in many disorders involving monocyte infiltration, such as psoriasis, rheumatoid arthritis, and atherosclerosis (85). This cytokine also activates macrophages, stimulates histamine release from basophils, and promotes Th2 immunity (7). Because of its involvement in immune processes and its 37  chemotactic properties, it is suspected that CCL2 may have a role in the recruitment and differentiation of inflammatory cells in the airways of asthmatic individuals after AIC. This will be discussed in more detail later on in the chapter.  3.2 Methods 3.2.1 Cohorts Four cohorts of adult subjects (age 18-60), as summarized in Table 3.1, were examined for the cytokine study. The groups represent individuals with atopic asthma (n=39), occupational asthma (n=7), allergic rhinitis (n=32), as well as control subjects (n=6), to form a total of 84 subjects. The atopic asthmatic cohort consists of individuals recruited from Université Laval (24 subjects), McMaster University (9 subjects) and Vancouver General Hospital UBC (6 subjects). Informed consents were obtained prior to the study. The inclusion and exclusion criteria were as described in section 2.2.1. Within this group, an initial discovery cohort was assembled using 32 subjects of mixed allergen sensitivity. Subgroups were also formed based on allergen sensitivity (cat dander - 12 subjects, grass pollen - 10 subjects, and house dust mite - 6 subjects). All participants within these subgroups were part of the initial cohort, with the exception of 7 new individuals within the grass pollen-sensitized group. Seven individuals with occupational asthma who were sensitized to Western red cedar (WRC), or plicatic acid found within WRC dust, were also included in this study. A diagnosis of WRCA is based on both an occupational history and objective evidence that inhalation challenge test using extracts of plicatic acid results in acute respiratory 38  symptoms and lung function changes. All subjects were recruited from Vancouver General Hospital – UBC. In addition, 39 individuals exhibiting seasonal allergic rhinitis symptoms to short ragweed pollen were also studied. They were recruited from Queen’s University, with informed consent. Allergic rhinitis was determined by medical history, physician diagnosis and a positive response to skin prick test using short ragweed pollen. Finally, six non-asthmatic healthy control subjects from St. Paul’s Hospital were included in the investigation to enable comparison of data between allergic and nonallergic individuals. These three males and three females were age-matched as closely as possible with the subjects in the atopic asthmatic cohort.  39  Table 3.1 — Subject Demographics (CCL2).  Cohort  Subgroups  # # Subjects Challenges  Site (# Challenges)  Mean Age  Sex (M:F)  Allergen (# Challenges)  Responsese (# Challenges)  Discovery  32  35a  Laval (26), VGH (7), McM (2)  33.3 ± 1.8  13:19  Cat (19), Grass (7), HDMb (8), Other (1)  ER (13), DR (18), Undetermined (4)  Cat Allergen  12  12  Laval (12)  30.8 ± 2.2  3:9  Cat (12)  ER (7), DR (5)  Grass Allergen  10  11  Laval (2), VGH (1), McM (8)  26.1 ± 2.7  7:3  Grassc (11)  ER (5), DR (6)  HDM Allergen  6  6  Laval (6)  31.2 ± 4.6  2:4  D. pteronyssinus (3), D. farinae (3)  ER (1), DR (5)  Occupational Asthma  7  8  VGH (8)  43.3 ± 5.4  7:0  Methacholine & Plicatic acid (8)  DR (3), LR (2), NR (3)  Allergic Rhinitis  32  32  Queens (32)  34.3 ± 1.6  15:17  Short Ragweed (32)  ER (9), DR (6), PER (17)  Control  6  6d  St. Paul's (6)  33.7 ± 4.3  3:3  N/A  N/A  Atopic Asthma (n=39)  a  The number of challenges are different from the number of subjects because some subjects received a repeated allergen challenge. b HDM=House dust mite (Dermatophagoides pteronyssinus and Dermatophagoides farina). c Grass allergen includes pollen from Timothy grass, Orchard grass, Grass mix, and Ragweed. d Although control subjects did not undergo allergen challenge, 6 pre/post samples pairs were still collected. e ER=Early responder, DR=Dual responder, LR=Late responder, NR=Non-responder, PER=Protracted early responder.  40  3.2.2 Allergen Challenges and Sample Processing Allergen inhalation challenge was administered to atopic asthmatic individuals as described in the previous chapter. Peripheral venous blood samples were collected prior to allergen challenge and 2 hours after the last inhaled allergen dose using EDTA tubes. Four of the 39 individuals were given a second AIC, bringing the total pre/post sample pairs to 43. The FEV1 lung function was monitored for 7 hours post-challenge and the response was categorized as either an isolated early response (FEV1 drop ≥20% from baseline between 0 and 2 hours) or a dual response (FEV1 drop ≥15% between 3 and 7 hours, in addition to the early response). For individuals with occupational asthma, the allergen challenge procedure was similar to the above, with the exception that all subjects were challenged with plicatic acid extracts. In addition to the blood samples collected pre- and 2 hours post-AIC, peripheral blood was also drawn before and 2 hours after methacholine inhalation challenge on the previous day. Out of the 7 subjects, one individual received a second methacholine and allergen challenge. Subjects were categorized as ER, DR, LR (late response, defined by a single FEV1 drop ≥15% between 3 and 7 hours), or NR (nonresponder). Allergic rhinitis subjects were given a skin prick test of ragweed pollen and 13 other allergens in order to confirm history of seasonal allergic rhinitis as part of the screening process. Eligible individuals returned for the allergen challenge in the Environmental Exposure Unit (EEU), where ragweed pollen was circulated at a controlled and consistent level, enabling all subjects to simultaneously receive an equal  41  amount of pollen exposure. Participants were required to record their rhinoconjunctivitis symptoms on score cards at 30 minute intervals throughout the 3 hour pollen exposure, and every hour from 6 to 12 hours after the start of the allergen challenge. Peripheral blood samples were collected into EDTA tubes immediately prior to and after the 3 hour ragweed pollen exposure in the EEU. Upon compilation of the score cards, subjects were categorized into either early responders (marked symptom scores increase, then drop ≥50% by 7 hours), dual responders (early response plus an increase in symptom scores after 2 hours of decreased scores), or protracted early responders (an initial increase in symptom scores, then decrease by <50% by 7 hours). The 6 non-asthmatic control subjects did not undergo allergen challenge. However, venous blood samples were still drawn into EDTA tubes at two time points – 9 am and 12 noon – to parallel the blood sampling of the asthmatic subjects occurring pre- and 2 hours post- the last inhaled dose of allergen. All of the samples collected pre- and post-allergen challenge were immediately centrifuged at 500 x g for 10 minutes at room temperature to separate the layers of plasma, buffy coat, and erythrocytes. These three blood fractions were isolated and aliquoted into microcentrifuge tubes, and were frozen and transported to the laboratory on dry ice to be stored at –80°C. 3.2.3 Multiplex Cytokine Assay From the initial discovery cohort of atopic asthmatic challenge subjects, 35 pre/post pairs of thawed plasma samples were analyzed on a panel of 42 cytokines at our collaborator’s laboratory at McGill University. For this procedure, the MILLIPLEX 42  MAP Human Cytokine/Chemokine Premixed 42-Plex Panel assay (Millipore, Billerica, MA, USA) was used, following the manufacturer’s protocol. The signals were detected with the Luminex 100 system (Luminex, Austin, TX, USA), using xMAP technology, which allows for rapid and precise detection of fluorescent intensities in multiplexed assays. 3.2.4 MSD Immunoassay Validation Follow-up study of a selected cytokine, CCL2/MCP-1, was performed using the Human MCP-1 Ultra-Sensitive Kit from MULTI-ARRAY Assay System (Meso Scale Discovery, Gaithersburg, MD, USA). This single-plex assay employs a sandwich immunoassay format in conjunction with an electrochemiluminescent label. Signals are generated and read when voltage is applied to the plate electrodes in the MSD SECTOR Imager 6000 instrument (Meso Scale Discovery, Gaithersburg, MD, USA). The cytokine concentrations in the samples were calculated based on a standard curve generated by plotting a known serial dilution of CCL2 (included in the kit) against the signal output. CCL2 validation studies by MSD technology was carried out on all of the allergen-specific subgroups (cat, grass, and HDM allergens) within the atopic asthma cohort, as well as on the occupational asthma cohort, the allergic rhinitis cohort, and the control subjects. Samples were run in duplicates and triplicates with high reproducibility of results (median CV=1.87%). 3.2.5 Statistical Analysis For the initial discovery cohort of 35 sample pairs that were analyzed on the MILLIPLEX 42 cytokines panel, pre- versus post-allergen challenge results were 43  evaluated using two-tailed paired t-tests and declared significant at p≤0.05. Subsequent studies of the CCL2 cytokine using MSD technology employed the onetailed t-test, assuming that the directionality of change would replicate. Significance cutoff remained at p≤0.05. Baseline CCL2 levels were evaluated with respect to allergen, age, and sex using a multiple linear regression model as performed in R (statistical computing program) version 2.12.0 (86). Significance was set at p≤0.05.  3.3 Results 3.3.1 Cohort Characteristics A total of 84 subjects were recruited across the different cohorts for this study (Table 3.1). Among these participants, 97 pre/post sample pairs were collected from 83 allergen challenges, 8 methacholine challenges, and 6 healthy controls without challenge. The overall mean age was 33.86 ± 1.1, with the youngest cohort being the grass allergic asthma group (26.1 ± 2.7), and the oldest cohort being the plicatic acid occupational asthma group (43.3 ± 5.4). An equal number of males and females were enrolled, with exactly 42 individuals in each group. However, within cohorts and subgroups, the breakdown of the sexes was not so evenly distributed. Of particular note is the Western red cedar/plicatic acid occupational asthma cohort, which is comprised entirely of male participants. Since different models of allergen challenges were used for the different allergic diseases, a universal indicator of positive response was not feasible. Nonetheless, in all subjects within the atopic asthma and the allergic rhinitis cohorts, a positive early phase response was detected within 3 hours, either by a FEV1 drop ≥20% from 44  baseline, or by a marked increase in total nasal/non-nasal rhinitis symptom score. The late phase response was observed in 23 asthmatic challenges and 6 allergic rhinitis challenges. The remaining 17 allergic rhinitis subjects were categorized as protracted early responders (Table 3.1). In occupational asthma subjects undergoing plicatic acid challenge, none of the participants displayed an isolated early response. However, FEV1 profiles of an isolated late responder and a non-responder were detected in two and three of the allergen challenges, respectively. Methacholine challenge of the same individuals resulted in an isolated early phase response in all subjects. 3.3.2 Multiplex Cytokine Assay Analysis At McGill University, plasma samples from an initial discovery cohort of 32 atopic asthmatics undergoing 35 allergen challenges were analyzed against a panel of 42 cytokines. The results for pre- versus post-challenge analysis are presented in Appendix 5. Out of these cytokines, CCL2 (also known as MCP-1) and CCL5 (also known as RANTES – Regulated upon Activation, Normal T-cell Expressed, and Secreted) were the only cytokines identified by paired t-tests to have been significantly perturbed post-challenge, at p=5.7E-4 and p=2.2E-2, respectively. CCL2 showed a significant decrease while CCL5 showed a significant increase after AIC. 3.3.3 CCL2 Validations Focusing on the most significant finding of a decreased level of CCL2 after AIC, hypothesis-testing experiments using MSD’s electrochemiluminescence technology were performed. The results are summarized in Figure 3.1. Using the same samples that were analyzed in the initial discovery phase of the study, significance was 45  replicated when examining samples from a subgroup of 12 cat allergen-sensitized individuals (p=5.5E-4, using a one-tailed t-test). However, testing samples from a cohort of 6 HDM-sensitized subjects who were also part of the initial cohort failed to yield statistically significant results. When evaluating the subgroup of allergic asthmatics sensitized to grass allergen, in which 7 new individuals were included, the findings were once again significant (p=2.4E-4). The investigation of perturbed plasma CCL2 levels post-challenge was extended to a cohort of subjects with occupational asthma. Although analysis of the samples taken before and after methacholine challenge were insignificant, pre- versus postplicatic acid challenge examinations revealed significant results (p=6.8E-3). Broadening the study to include a cohort of allergic rhinitis subjects, the levels of CCL2 was still significantly decreased after ragweed pollen allergen exposure (p=2.2E-10). Finally, the samples from 6 control subjects who had no history of asthma or allergic rhinitis and who did not undergo allergen challenge were tested. When analyzed with a 2-tailed paired t-test, the CCL2 levels were found to be significantly decreased (p=1.3E-2). In addition to evaluating changes in CCL2 levels between pre- and postchallenge, attempts were also made to examine any differential patterns of CCL2 perturbations between isolated early and dual responders. However, there did not appear to be any differences between the two response types, based on the analyses of data from either the atopic asthmatic or the allergic rhinitis cohorts (results not shown).  46  Figure 3.1 — Plasma CCL2 Levels at Pre- and Post-Allergen Challenge. a) Dot Plot Representations  Cat Allergen*  Grass Allergen*  HDM Allergen  Methacholine  47  Plicatic Acid*  Ragweed Allergen*  Controls*  9 AM  12 Noon  48  b) Histogram Representation  CCL2  CCL2  Pre- and post- plasma CCL2 levels (measured by MSD) are presented for each cohort of subjects grouped by allergens. Asterisks denote statistically significant results (p≤0.05) when comparing between pre- and post-challenge samples, as calculated by a one-tailed paired t-test. In the case of the control cohort, consisting of subjects who were not exposed to allergens, a two-tailed paired t-test was used. In dot plot representations (a), ER=Early responder, DR=Dual responder, PER=Protracted early responder, NR=Non-responder, LR=Late responder. In histogram representation (b), the mean and SEM are shown.  49  3.3.4 Baseline Level Correlations Pre-allergen challenge CCL2 levels were examined in conjunction with subject demographical and clinical data in order to explore whether baseline CCL2 levels may be influenced by any of these factors. Considering the disease categories of atopic asthma, occupational asthma, allergic rhinitis, and normal controls, the only significant difference was found between the occupational asthma group and the atopic asthma group. Specifically, baseline CCL2 levels were higher in subjects with occupational asthmatic as opposed to subjects with atopic asthma. CCL2 levels were not found to be different between control subjects and allergic subjects as a whole. When the groups were further broken down according to specific allergens, pre-challenge CCL2 levels were revealed to be different only on two occasions: 1) between the HDM-sensitized group (within the atopic asthmatic cohort) and the plicatic acid-sensitized group (occupational asthma cohort), and 2) between the HDM-sensitized group and the ragweed pollen-sensitized group (allergic rhinitis cohort). In both cases, lower CCL2 levels were noted in the HDM-sensitized individuals. Subject demographics, specifically the age and sex of participants, were analyzed in conjunction with baseline levels of CCL2 using a linear model. CCL2 was found to be positively correlated with age in a simple regression analysis (p=7.3E-6, r2=0.2114). This relationship is illustrated in Figure 3.2. When sex and the interaction between age and sex were added to the model, however, the results failed to reach significance. Next, the data were separated and plotted based on cohorts (Figure 3.3). This revealed a sampling bias in which atopic asthmatic subjects clustered in the younger age range, while participants in the occupational asthma cohort clustered in the 50  older age range. In order to minimize possible confounding effects related to allergen sensitivity and age, the previously described analysis was repeated using only the cohort of the most even age distribution – the allergic rhinitis group. The findings remained supportive of an increase in CCL2 with age, in both the single-covariate analysis (age only, p=4.0E-3), and the multi-covariate analysis (age and sex, p=6.1E-3). The results from the sex-based analysis did not reach significance. In addition to the age and sex of subjects, several clinical parameters were also assessed for possible associations with baseline CCL2 levels. The % FEV1 drops in the EAR and the LAR, as measured during allergen challenges in the atopic asthma cohort, were analyzed and found to have no relationship with baseline CCL2. Similarly, no significant association was observed when the cytokine level was tested against the response phenotype (ER or DR) in either the atopic asthmatic cohort or the allergic rhinitis cohort. Peripheral blood monocyte counts were also assessed because of their role as the main target cell type of CCL2. The analysis of the monocyte counts (both absolute and relative counts) and CCL2 data (obtained from the allergic rhinitis cohort and the cat allergen cohort) did not reveal any significant associations between the baseline cytokine level and either the baseline monocyte level or the change in monocyte counts after allergen challenge.  51  Baseline CCL2 (pg/mL)  Figure 3.2 — Baseline CCL2 Level and Age Association.  Age  Subject age was correlated with baseline levels of CCL2. Older age is associated with an increase in baseline CCL2 level (p=7.3E-6, r2=0.2114).  52  Baseline CCL2 (pg/mL)  Figure 3.3 — Baseline CCL2 Level with Age in Allergen Cohorts.  Age  Baseline CCL2 data was separated according to allergen cohorts. This revealed a sampling bias towards younger participants in the atopic asthmatic groups (cat, grass, HDM), but older participants in the occupational asthma group (plicatic acid). The only cohort to show an even distribution of age was the allergic rhinitis group (ragweed).  53  3.4 Discussion 3.4.1 CCL2 and CCL5 in Allergic Diseases In this study of plasma cytokine profiles associated with AIC, CCL2 and CCL5 were identified to be cytokines of interest, displaying a significant decrease and a significant increase, respectively, 2 hours post-AIC. This was observed from a cohort of atopic asthmatic subjects with mixed allergen sensitivity, through the use of a multiplex assay on a cytokine panel. Subsequently, the CCL2 results were replicated in cohorts of various allergic diseases, using a more sensitive single-plex CCL2 immunoassay. CCL5/RANTES is a chemokine that is produced by various cells including T lymphocytes, endothelial cells, fibroblasts, and eosinophils (87). It has the ability to attract Th cells, eosinophils, and basophils to the airways during an asthmatic response (88). Many studies have inquired into possible associations between CCL5 polymorphisms and asthma; however, results have been mixed (89–91). On the protein level, an increase in the cytokine has been demonstrated in the BAL fluid and serum of asthmatics, with a positive correlation to disease severity (87,92). Following neutralization of CCL5, decreased eosinophil recruitment to the allergic airways has also been observed in a mouse model, providing further support for a mechanistic role of the cytokine in asthma (93). In the present study, CCL5 was found to be increased in the plasma after AIC. This is in direct agreement with the work of Chihara et al., who showed that plasma CCL5 levels were significantly higher in subjects undergoing an asthmatic response, as compared to the same subjects during the asymptomatic state, or to control subjects (94). The elevated level of CCL5 post-AIC suggests that it may  54  play an important role in asthma pathophysiology, perhaps through eosinophil recruitment and activation (95). The involvement of the chemokine CCL2/MCP-1 in allergic diseases has previously been explored. Starting at the genetic level, there have been reports of polymorphisms found to be associated with increased asthma risk (96,97). For the protein, numerous studies have shown a significant increase in CCL2 levels in asthmatic BAL fluid and serum at baseline and after allergen challenge (92,98,99), a pattern that was also observed from subjects with allergic rhinitis (100). Additionally, many in vitro and in vivo studies have investigated further into the cytokine’s possible roles in allergic asthma (101). As mentioned in the introduction of this chapter, CCL2 has the ability to attract inflammatory cells, such as monocytes and lymphocytes, to the airways (102,103). These cells can in turn release cytokines and attract additional immune cells, thereby amplifying the inflammatory response in an asthmatic reaction (101). Moreover, there is evidence that CCL2 may induce histamine and leukotriene release, which would exert a direct effect on bronchial hyperreactivity (104). Finally, CCL2 has been suggested to enhance Th2 activity, perhaps by encouraging the polarization of CD4 cells to the Th2 phenotype (105,106). Since Th2 cytokines are important in the development of asthma and allergic rhinitis, this provides additional support that CCL2 may play a pivotal role in allergic diseases (107). Contradictory to the reports discussed above, the level of plasma CCL2 was observed to have decreased following allergen challenge in the current study. This may be explained by variations in experimental design, such as differences in the specimens tested and the nature of the allergen challenges. The sampling time point represents 55  another factor of consideration. In the present study, post-challenge samples were taken at 2 hours after allergen inhalation; whereas previously, the time point was set as 4 hours or more. Because the infiltration of inflammatory cells is a hallmark of the late phase response (which also occurs in allergic rhinitis subjects) and CCL2 can contribute to this event through binding to its receptor CCR2 on target cells (101), it is possible that the reduction in plasma CCL2 shortly after allergen inhalation challenge represents the uptake of the cytokine in such a process. Indeed, Maus et al. have demonstrated that an increase in monocyte accumulation is accompanied by a consumption of CCL2 (108). Although their in vitro study differs from the current investigation, it nonetheless offers a possible explanation for the decrease in CCL2 levels post-challenge. 3.4.2 Normal CCL2 Fluctuation Despite all this, however, it is unlikely that the drop in plasma CCL2 is a result of biological processes triggered by allergen inhalation. The reason is that even in nonatopic control subjects who have not undergone allergen challenge, a significant decrease in plasma CCL2 levels remained evident when comparing between samples drawn at 9am and at noon. This suggests that there may be a physiological, and perhaps diurnal, fluctuation of CCL2 levels in the peripheral blood in all individuals, whether challenged or not. To date, there have been no reports describing a CCL2 fluctuation in healthy individuals. Some studies have investigated the effects of stress, in the form of exercise, on circulating CCL2 levels in normal individuals. For instance, Fatouros et al. reported that serum CCL2 decreased after 30 minutes of exercise (109). However,  56  results have been conflicting, as other studies have found an increase in the cytokine level at 1 hour and 6 hours after exercise (110,111). Despite these potential explanations, direct support of an inherent decrease in circulating CCL2 levels is still lacking from existing literature. Therefore, future timecourse studies involving additional healthy subjects should be carried out in order to confirm the current findings. If shown to be true, this would have implications for other studies involving CCL2. For example, in the area of cardiovascular diseases, there have been reports of a decrease in serum CCL2 levels immediately after primary percutaneous coronary intervention as compared to prior to treatment (112). GarciaAlonso et al. also described a lowered circulating CCL2 level at various time points (within 24 hours) after a morning ingestion of anthocyanin, a substance believed to be protective against coronary heart disease (113). Interestingly, the decrease was significant only at the 3 hour time point. Since the timing of the experimental procedure was similar to that of the AIC (in terms of morning initiation and ~3-hour post sampling), the CCL2 decrease reported by Garcia-Alonso et al. may possibly reflect a physiological fluctuation, as opposed to a biological outcome of anthocyanin ingestion. Hence, caution should be taken when interpreting such results. 3.4.3 Baseline CCL2 Associations Baseline plasma CCL2 levels were analyzed in the context of subject demographics. Results indicated that age was a major factor influencing the cytokine level, with older subjects having higher baseline CCL2. Numerous studies have reported a positive relationship between aging and increasing CCL2 levels. Three  57  studies have investigated the level of circulating CCL2 in healthy subjects of various ages; the findings were unanimously in support of the current results (114–116). Using animal models, elevated CCL2 levels were also evident in different tissues of aging mice. Examples of these include heart tissue and vascular smooth muscle cells, attesting to the higher risk of cardiovascular diseases (as well as other inflammatory diseases) with age (117,118). Different reasons have been proposed to explain this association. First, the increase in CCL2 has been suggested to be a reflection of the development of atherosclerosis, perhaps sub-clinically (114). This stems from many human and animal studies demonstrating a link between CCL2 and atherosclerosis (119). Another explanation is that the increase in CCL2 may be indicative of a shift towards the Th2 phenotype as the immune system ages (115). While this idea is supported by some studies (120,121), others have provided evidence for the opposing argument of an enhanced TH1 response with aging (122,123). In the current investigation, potential reasons for the correlation between CCL2 and age cannot be easily speculated upon without further work assessing subject history and other molecular signals of the immune system.  3.5 Summary In this chapter, CCL2/MCP-1 was identified to be a cytokine that is significantly decreased in plasma post-allergen inhalation challenge. This finding was replicated in various cohorts of allergic diseases, including asthma and allergic rhinitis. A downregulation was also observed in healthy control subjects, indicating that the decrease in  58  CCL2 level may reflect a physiological fluctuation of the cytokine, as opposed to an outcome of allergen inhalation. Finally, baseline CCL2 levels were found to be associated with age, with higher cytokine levels observed in older subjects.  59  CHAPTER 4: ISOLATED EARLY RESPONSE VERSUS DUAL RESPONSE 4.1 Introduction Having shown in Chapters 2 and 3 that it is possible to observe peripheral blood molecular perturbations, especially transcriptomic changes, at 2 hours after AIC, the next step was to compare and contrast the isolated early and the dual responses. As discussed previously, these two response patterns are hypothesized to be the result of varying immunological processes, with the LAR believed to involve the infiltration of inflammatory cells to the airways, leading to a more detrimental clinical outcome as compared to the isolated early response (9). In order to address this experimental aim, the focus was on a cohort of allergic asthmatic adults challenged with cat allergens. The study was performed through the analysis of transcriptomic changes between preand post-AIC, as assessed by microarrays. By attempting to distinguish between these two response phenotypes through the study of genome-wide gene expression changes, it was anticipated that the biological mechanisms underlying these response patterns could be further unraveled. In turn, this may aid in the phenotyping of asthma. Currently, ER and DR are separated based on FEV1 profiles, which employ strict FEV1 cut-off values for response categorization. Due to the heterogeneity of the asthmatic response, this method may easily lead to the miscategorization of subjects, especially those who are approaching the set FEV1 cut-off. Therefore, the identification of crucial pathways unique to the development of a late phase response may give rise to better markers for the LAR. In 60  addition, a better understanding of disease mechanisms may lead to the identification of potential therapeutic targets to minimize the LAR.  4.2 Methods 4.2.1 Subjects, Allergen Inhalation Challenge, and Microarray Analysis Subjects with mild allergic asthma who were sensitized to cat allergens were recruited for this study. The choice of allergen was based on a preliminary analysis demonstrating an even distribution of ERs and DRs following cat AIC (data not shown). In contrast, HDM allergen challenges produced mostly DRs, which was consistent with previous findings (16). Grass allergen was not chosen due to limited number of sensitized individuals. The inclusion and exclusion criteria were as described in Chapter 2. Fourteen participants were included in total, which consisted of the 12 who were in the cat allergen group within the CCL2 study (as mentioned in Chapter 3, Table 3.1), and an additional 2 new subjects. The 12 participants were recruited from Université Laval, while the 2 new individuals were recruited from Vancouver General Hospital (VGH) – UBC. Subject demographics are summarized in Table 4.1. Following the administration of a skin prick test and methacholine PC20 test, AIC using extracts of cat dander was performed as previously described. Methacholine inhalation challenge was also administered a day later to most subjects, in order to assess the airway hyperresponsiveness post-challenge. All participants were required to exhibit an FEV1 drop ≥20% during the EAR, and DRs were required to demonstrate a LAR of ≥15% drop in FEV1. For individuals who experienced a LAR FEV1 drop that was 61  approaching the 15% cut-off, a determination of a dual response could be made if the methacholine PC20 value measured 24 hours post-AIC was decreased by at least half as compared to the original value recorded prior to allergen challenge (21), or if the subject had historically demonstrated a consistent dual response. Following previous procedures, peripheral blood samples were collected in PAXgene Blood RNA tubes and EDTA tubes prior to and 2 hours after allergen challenge. A complete blood cell count with differential was taken from each EDTA blood sample using the Cell-Dyn® System (Abbott Diagnostics Division, Abbott Laboratories, Abbott Park, IL, USA). Total RNA was extracted from PAXgene blood samples and analyzed on the Affymetrix Human Gene 1.0 ST microarrays as detailed in Chapter 2.  62  Table 4.1 — Subject Demographics (ER versus DR).  Response  Isolated Early Responders (n=8)  Subject  Site  Age (yr)  Sex  Pre Mch PC20a,b (mg/ml)  Post Mch PC20a,b (mg/ml)  Allergen  % Fall in FEV1 (EAR)  % Fall in FEV1 (LAR)  1  VGH  42  M  0.13  N/A  Cat  -23  -9  2  Laval  28  F  12.8  N/A  Cat  -20.3  -4.8  3  Laval  29  F  0.35  N/A  Cat  -44.3  0  4  Laval  34  F  2.69  6.11  Cat  -21  -1.5  5  Laval  27  M  4.54  1.76  Cat  -34.4  0  6  Laval  42  F  5.34  8.6  Cat  -42.1  -11.1  7  Laval  31  M  11.75  16  Cat  -24.2  -7.5  8  Laval  28  F  9.39  16  Cat  -27.1  -7.1  32.6 ± 2.2  3:5  2.82  7.50  29.6 ± 3.4  5.1 ± 1.5  Mean ± SEM  Dual Responders (n=6)  Mean ± SEM a b  9  VGH  52  F  N/A  N/A  Cat  -33  -27  10  Laval  23  F  0.3  0.18  Cat  -38.9  -31.8  11  Laval  26  F  5.13  1.53  Cat  -31.4  -14.9  12  Laval  49  F  3.61  0.99  Cat  -25.3  -12.6  13  Laval  26  M  0.93  1.02  Cat  -31.5  -15.6  14  Laval  27  F  0.63  0.12  Cat  -48.3  -25.8  33.8 ± 5.3  1:5  1.27  0.51  34.7 ± 3.2  21.3 ± 3.2  Methacholine PC20 was taken one day pre- and one day post-allergen inhalation challenge. Geometric means were calculated separately for the ER and the DR groups.  63  4.2.2 Statistical Analysis Subject demographics and clinical FEV1 measurements were compared between the ER and DR groups using 2-tailed t-tests, assuming unequal variances. Analysis of complete blood cell count and differential (comparing pre- versus post-AIC) were conducted using the 2-tailed paired t-test on each cell type. To investigate whether the cell count changes deviate between the two response types, the data was first baselined (pre- subtracted from each corresponding post-value), and the results were analyzed by comparing between ER and DR using the 2-tailed t-test, assuming unequal variances. For all of the above, significance cut-off was set at p≤0.05. The raw probe intensity data from the microarray procedure, summarized in CEL files, were analyzed using an algorithm called significance analysis of microarrays (SAM), performed within the R-package (86). SAM employs a moderated t-test approach that uses permutations in order to estimate the variance of the genes and the resulting false discovery rate (124); thus it does not rely on the assumption of a parametric genes distribution. Data processing begins with RMA normalization, followed by the removal of non-annotated genes, and finally the application of the SAM algorithm. During the analysis, genes are ranked by a score that is assigned based on the change in gene expression relative to the standard deviation. The analysis was conducted using an interaction model, which is intended for situations where two factors exert a combined, but not additive, effect on an outcome. Briefly, when there is interaction, the result of one variable is dependent on the level of the other. In the current study, the two main factors of interest were the status of the  64  challenge (pre and post) and the response type (ER and DR). Hence, the DEPs identified using the SAM interaction analysis were those that significantly increase postchallenge for ER but decrease for DR, and vice versa. In context of the SAM algorithm, the interaction analysis was carried out by comparing the pre-to-post change (achieved by baselining the data through subtracting pre-values from post-values) of ER versus DR. The significance threshold was set at FDR≤0.30, following previous report of a similar method (125). A derivative of the SAM algorithm called cell-specific significance analysis of microarrays (csSAM) was employed for further data analysis. This method was developed to address the concern that the overall gene expression measured from a sample is a combination of the individual signals from multiple cell types; thus, the total gene expression may overlook many differentially expressed genes within each cell type (125). In response, csSAM statistically deconvolutes the total signal into cell typespecific gene expression profiles, using the SAM algorithm in conjunction with the measured relative cell type frequencies. This enables the identification of genes previously not found to be significant in the analysis of the whole sample gene expression. CsSAM, conducted using the R-package, was employed for four analyses: a) pre- versus post-challenge for ERs only, b) pre- versus post-challenge for DRs only, c) ER versus DR at pre-challenge, and d) ER versus DR at post-challenge. The whole blood gene expression profile was separated based on the five types of peripheral blood leukocytes – neutrophils, lymphocytes, monocytes, eosinophils, and basophils – a process achieved through inclusion of the relative counts of each cell type into csSAM. 65  The analyses were performed using an unpaired approach, following the original statistical design of the algorithm (125). Although a paired analysis is likely to be more powerful in detecting differentially expressed genes, especially when comparing preand post-allergen challenge data, this was not carried out due to the lack of a validated csSAM pairing method. Correspondingly, unpaired SAM analyses were performed in order to generate reference data to which the results of the csSAM analyses could be compared. Genes were considered significant at FDR≤0.30, following the methods outlined in the original manuscript (125). Pathway analyses were performed using IPA, as described in Chapter 2. Analyses were restricted to consider genes related to immune cells, lungs, and the nervous system, based on a study reporting sensory nerves as having a role in the LAR (126). Gene lists created using the SAM interaction analysis and csSAM analyses were used. Although a lenient significance cut-off of FDR≤0.30 was employed, pathway analyses helps to reduce the possible false positive errors associated with single-gene level analyses, by taking into account multiple genes in order to provide relevant biological information through networks and pathways (127).  4.3 Results 4.3.1 Cohort Characteristics The study cohort was comprised of 8 ERs and 6 DRs (Table 4.1). The mean ages of the ER group and the DR group were not statistically different, at 32.6 ± 2.2 and 33.8 ± 5.3 respectively. There was an equal number of female participants within the two cohorts (5 each), but the ER group contained 2 additional male subjects as 66  compared to the DR group. The presence of a hyperresponsive airway was evident in both cohorts, as indicated by a pre-allergen challenge methacholine PC20 <16 mg/ml (39). The geometric means for pre-allergen challenge methacholine PC20 were 2.82 mg/ml and 1.57 mg/ml for the ER and DR groups, respectively. Post-allergen challenge, the methacholine PC20 values were significantly different between the two cohorts, with the geometric means being 7.50 mg/ml (ER) and 0.51 mg/ml (DR). Hence, a more hyperresponsive airway was detected for dual responders following AIC, which was consistent with literature findings (21). All 14 subjects underwent AIC using extracts of cat dander. An EAR was detected in all participants, as shown by a drop in FEV1 ≥20% between 0 and 3 hours. The mean FEV1 drop for the ER group was 29.6 ± 3.4% and that for the DR group was 34.7 ± 3.2%; these values were not statistically different. Conversely, the two groups were found to be significantly different (p=2.5E-3) for the LAR, with the mean FEV1 drop being 5.1 ± 1.5% for ER and 21.3 ± 3.2% for DR. Figure 4.1 presents the lung function profiles of isolated early responders and dual responders, through measurements of the FEV1 drop from baseline after AIC. Comparing between the two responses at each data collection time point, the % drop in FEV1 was not significantly different at any stage from the start of the allergen challenge until, and inclusive of, 2 hours into the challenge. Starting at 3 hours after allergen inhalation, however, the difference in % FEV1 drop between ERs and DRs became increasingly significant with each passing hour. The only exception to this was at 6 hours after AIC, at which point the significance was decreased as compared to the two previous measurements taken at 4 and 5 hours (Figure 4.1). 67  Figure 4.1 — Lung Function Profiles for ER and DR.  Lung function profiles for the ER group and the DR group after allergen inhalation challenge were measured by spirometry and presented as % drop in FEV 1 from baseline. The data points represent the mean and the error bars represent the SEM for each response cohort. Comparing between the two response types at each measurement time point, the profiles significantly diverge starting at 3 hours after the challenge, with p values of 0.041, 0.023, 0.011, 0.029, and 0.004 for each point from 3 hours to 7 hours.  68  4.3.2 Complete Blood Cell Count and Differential Analysis Complete blood cell count and differential in peripheral blood were measured from all 14 subjects using EDTA tube samples drawn prior to and following AIC. Comparing between pre- versus post-challenge (while disregarding ER and DR), total leukocyte counts in absolute terms were found to be significantly increased after allergen inhalation (p=6.1E-3). From the analysis of specific cell types, neutrophils and eosinophils were identified to be increased (p=1.2E-3) and decreased (p=4.1E-2), respectively post-challenge. The other leukocytes (lymphocytes, monocytes, and basophils) were not significantly changed with regards to cell counts. Next, the ER and DR data were compared to assess whether each cell type was affected in a similar manner between the two responses. The results indicated no significant differences for any of the cell types, suggesting that differential cell count perturbations occurred (or did not occur) regardless of response. Another analysis was performed to compare the pre-allergen challenge cell counts of ER samples against those of DR samples. The baseline leukocyte counts for the different cell types were not found to be significantly different between ERs and DRs. 4.3.3 RNA Quality To ensure that the RNA samples to be used for microarray analysis were not degraded, the quality of all 14 pre/post sample pairs was assessed. Electropherograms showed very distinct 18s and 28s peaks for all samples. Similar to the PAXgene blood samples collected for the experiments described in Chapter 2, the RIN indicated  69  excellent quality (range of 8.3 – 8.9). NanoDrop analysis provided further support for the purity of these samples, demonstrating the 260/280 ratio to be 2.09 ± 4.5E-3. 4.3.4 Differentially Expressed Probe Sets The SAM interaction analysis, which takes into account both the response type and the pre/post time points of the samples as covariates, identified 501 DEPs as being perturbed differently between ER and DR (FDR≤0.30). All demonstrated an increase in gene expression post-allergen challenge for ER, but a decreased expression for DR. Out of this list, 251 probe sets remained significant at FDR≤0.25. The list of genes can be found in Appendix 6. Among the top genes of significance included a few with potential relevance to asthma, such as the genes for Interleukin 10 (IL10) and Kallikrein1 (KLK1), both at FDR=0.14. 4.3.5 Pathway Analysis The list of DEPs (FDR≤0.30) identified in the interaction analysis was entered into IPA for pathway analysis. Of the 501 probe sets initially inputted, 328 met the criteria for inclusion. The significant biological functions are listed in Table 4.2, with the highest-ranked functions being cell-to-cell signaling and interaction, hematological system development and function, immune cell trafficking, and inflammatory response. The only canonical pathway perturbed differently between ER and DR was identified to be linoleic acid metabolism (adjusted p=1.96E-2). Other pathways such as arachidonic acid metabolism and the role of cytokines in mediating communication between immune cells were significant at unadjusted p values (Figure 4.2).  70  Table 4.2 — Biological Functions Identified by Interaction Analysis.  Rank  Biological Function  P Valuea  1  Cell-To-Cell Signaling and Interaction  2.27E-02 – 1.62E-01  2  Hematological System Development and Function  2.27E-02 – 1.62E-01  3  Immune Cell Trafficking  2.27E-02 – 1.62E-01  4  Inflammatory Response  2.27E-02 – 1.62E-01  5  Cellular Growth and Proliferation  3.31E-02 – 1.42E-01  6  Cell-mediated Immune Response  3.31E-02 – 1.42E-01  7  Cellular Function and Maintenance  3.31E-02 – 1.52E-01  8  Hematopoiesis  3.31E-02 – 1.53E-01  9  Cellular Development  3.31E-02 – 1.53E-01  10  Cellular Movement  3.31E-02 – 1.61E-01  11  Tissue Development  3.31E-02 – 1.61E-01  a  The p value represents how likely the association between a set of genes in the dataset and a related function is due to random chance. The range is based on the individual p values of the subcategories within that biological function. The results have been adjusted based on Benjamini and Hochberg multiple testing corrections.  71  Figure 4.2 — Canonical Pathways Identified by Interaction Analysis.  The top 10 canonical pathways and their significance values are presented. The horizontal threshold line (meeting the left y-axis at 1.30) denotes statistical significance at p≤0.05 after Benjamini and Hochberg multiple testing corrections. The square points represent the ratio, which was calculated as the number of genes in a given pathway that meet significance, divided by the total number of genes that make up that pathway. Linoleic acid metabolism was the only canonical pathway to reach significance.  72  4.3.6 Cell-Specific Significance Analysis of Microarrays To further explore the gene expression profiles of isolated early and dual responders, the csSAM algorithm was applied in conjunction with the complete blood cell count and differentials, with the purpose of separating the whole blood gene expression signals into their respective peripheral blood leukocyte sources. As additional support for this method, the results generated using csSAM were compared against those created using parallel SAM algorithms. It is hypothesized that csSAM would be able to identify differential genes that may have been missed by the SAM analysis. Alternatively, csSAM may generate an adjusted FDR value for DEPs found in the whole blood analysis, such that confounding effects due to differences in complete blood cell count and differentials would decrease the number of DEPs. The analyses of pre- versus post-allergen challenge in both the ER cohort and the DR cohort did not reveal any significant genes (FDR≤0.30) within the five cell types. However, when comparing ER and DR gene expression at the pre-allergen challenge (baseline) level, 10 genes correlating to basophils were found to exhibit significantly lower expression levels in DR as compared to ER. Similarly, two genes correlating to lymphocytes reached statistical significance as being expressed at a lower level in DR than in ER subjects. These results generated by csSAM were in contrast to those produced using the corresponding SAM algorithms (whole blood analyses), in which all of the genes demonstrated an FDR≥0.90. The final analysis of ER versus DR at the post-allergen challenge time point yielded the most significant results (Figure 4.3). Whole blood SAM analysis initially identified the overall significance to be around FDR=0.45 for the top genes in the list. 73  Separating by directionality, genes that showed a lower expression for DR as compared to ER (“down”) were found to reach a significance level as low as FDR=0.25, while genes showing a higher expression for DR (“up”) barely reached FDR=0.50. CsSAM deconvolution revealed that lymphocytes and eosinophils were the main cell types of interest with regards to differential gene expression between ER and DR. Specifically, 140 genes correlating to lymphocytes were observed to be significantly (FDR≤0.30) lower expressed in DR than in ER (Appendix 7), and 262 genes correlating to eosinophils were detected to be expressed at a higher level in DR as compared to ER (Appendix 8). Overall, the largest gene expression discrepancies between ER and DR at 2 hours after allergen challenge seem to be associated with eosinophils.  74  Figure 4.3 — SAM and csSAM Results for the Analysis of ER versus DR at PostAllergen Challenge.  0.8 0.4 0.0  0.8 0.4 0.0  0.8 0.4 0.0  0.8 0.4 0.0  0.8 0.4 0.0  0.8 0.4 0.0  75  Each of these graphs depicts the number of genes identified (x-axis, on a log scale) against the FDR significance values (y-axis). The “up” column displays the genes that were found to be higher expressed in DR than ER, while the “down” column shows genes that were lower expressed in DR than ER. The top row presents the whole blood results obtained using the unpaired SAM statistical approach. Applying the csSAM algorithm, additional significance of genes were detectable in association with specific cell types, mainly lymphocytes and eosinophils.  76  4.3.7 Pathway Analysis of csSAM Results The two gene lists as identified to be associated with eosinophils and lymphocytes by the csSAM algorithm were entered into pathway analyses in IPA. Of the 262 genes found to be increased in expression in association with DR eosinophils, 58 were eligible to be included into the analysis. For the lymphocyte gene list, 39 out of 140 genes met the inclusion criteria. The biological functions identified by both lists failed to reach statistical significance after multiple testing corrections. For canonical pathways, mitotic roles of polo-like kinase was significant for both eosinophils and lymphocytes, at adjusted p=6.6E-5 and p=3.8E-2, respectively. Cell cycle: G2/M DNA damage checkpoint regulation was also significant for eosinophils (adjusted p=6.6E-5). Correspondingly, the protein products of the top genes found to be associated with both cell types included many that were known to be involved in DNA replication, spindle formation, and mitosis (data not shown).  4.4 Discussion 4.4.1 Interaction of Response and Time In this chapter, the differences in gene expression profiles between asthmatic isolated early and dual responders were explored. This was performed through an interaction analysis, which incorporates both the response type and the time points into a single model. Doing so enables the comparison between ER and DR on the basis of the change in gene expression from pre- to post-AIC. The biological functions identified by IPA revealed many that are in agreement with the current pathophysiological model of the early and the late response. For instance, a major feature of the late asthmatic  77  response is the recruitment and influx of inflammatory cells to the airways. The top three biological functions listed in Table 4.2 are in direct support of this: “cell-to-cell signaling and interaction” are necessary to initiate the inflammatory cell recruitment process, “hematological system development and function” lead to the production and release of additional leukocytes from the bone marrow, and “immune cell trafficking” governs the overall movement of immune cells from the site of production, through the peripheral blood, and into the airways. Because these processes may be more subdued in isolated early responders, it is not surprising that results as such were found to be significantly different between ER and DR using the interaction model. 4.4.2 Linoleic Acid Metabolism Linoleic acid (LA) metabolism was the single canonical pathway that reached statistical significance. Another related pathway, arachidonic acid (AA) metabolism, was also identified, but only at an unadjusted p value. These two polyunsaturated omega-6 fatty acids share a close relationship, as summarized in Figure 4.4 (128). Briefly, LA is an essential fatty acid that must be ingested (129). Through metabolism, it is converted to AA, from which many pro-inflammatory eicosanoids are produced, including prostaglandins, thromboxanes, and leukotrienes. Of special interest are the signaling molecules leukotrienes, which have been heavily implicated in the pathophysiology of asthma, particularly with respect to inflammation (130). Numerous reports have demonstrated their key roles in causing various asthmatic symptoms, including airway hyperresponsiveness, bronchoconstriction, inflammatory cell infiltration, mucus production, and airway remodeling (64,131–133), many of which are hallmarks of the LAR. Furthermore, several leukotriene receptor antagonists have been 78  successfully developed as a line of treatment for asthma (134), of which montelukast has shown promising results in significantly inhibiting the LAR (135). Additional evidence of LAR relevance is provided by studies that showed a suppression in the LAR due to the inhibition of AA-derived eicosanoid synthesis and release (136,137). In the present study, the eicosanoid signaling canonical pathway failed to reach statistical significance. This does not detract from the points mentioned above, however, considering the time frame of sampling. Two hours after allergen inhalation challenge is a brief time span for the body to fully react to allergens. Hence, it is possible that the observed perturbations in the LA (and AA) metabolism pathways are occurring in preparation for the synthesis of downstream eicosanoid metabolites. These molecules will subsequently contribute to the inflammatory state of the LAR as exhibited in DRs. Indeed, in Chapter 2, a significant decrease in the level of AA phospholipid in the plasma following allergen challenge was demonstrated, which may be explained by such a mechanism. There are also literature reports in support of the importance of these fatty acids at the upstream level of LA and AA, suggesting a connection between dietary LA intake and the prevalence of wheeze and asthma (138,139). However, not all studies were consistent in identifying such a positive association (140,141). Hence, further work is needed before a conclusion can be drawn regarding the relationships of LA, AA, and eicosanoids with the pathophysiology of asthma, especially with respect to the early and late response.  79  Figure 4.4 — Linoleic Acid Metabolism.  Linoleic acid is metabolized to form arachidonic acid through intermediates of gamma linolenic acid (GLA) and dihomo-gamma linolenic acid (DGLA). Prostaglandins (PG), prostacyclins (PGI), thromboxanes (TX), and leukotrienes (LT) – collectively known as eicosanoids – are subsequently produced. Those downstream of arachidonic acid, which accounts for the majority of eicosanoids, are pro-inflammatory. With respect to asthma, leukotrienes synthesized from arachidonic acid have been shown to play an active role in asthma pathophysiology.  80  4.4.3 CsSAM for ER versus DR at Post-Challenge Using the csSAM algorithm, many significant genes were uncovered in correlation with lymphocytes and eosinophils in the analysis of ER versus DR at postAIC. Both of these cell types have been suggested to be active contributors to the LAR (142), with eosinophils being a central effector cell (143) and Th2 lymphocytes producing cytokines to promote airway inflammation (144). In general, csSAM results indicated that eosinophils were associated with the largest gene expression discrepancies between ER and DR post-challenge (Figure 4.3). Considering the key role of eosinophils in the LAR, this finding provides support for the usefulness of the csSAM algorithm in uncovering cell-specific differentially expressed genes of true biological relevance. Cell cycle regulation appears to be a major theme that differs between ER and DR post-allergen challenge, as demonstrated by the canonical pathways and the top genes associated with both the lymphocytes and the eosinophils. In accordance with the proposed model of asthma pathogenesis, this suggests that eosinophils and lymphocytes may be undergoing active cellular growth and division, contributing to the rising number of inflammatory cells as seen in the late response. Indeed, previous reports have described the release of eosinophil haematopoietic progenitors from the bone marrow into the peripheral blood after allergen challenge, as well as an increase in post-challenge blood eosinophil counts in dual responders but not in isolated early responders (28,145,146). Based on this, it may be deduced that DR eosinophils are undergoing cellular differentiation in the peripheral blood, a process seemingly absent in  81  ER samples. Further studies are needed to elucidate the exact biological processes occurring in eosinophils post-allergen challenge. Research into lymphocytes during an asthmatic response has been more limited. Most of the work has focused on T lymphocytes (particularly Th2 cells), describing an increase in T cell activation post-challenge (147). However, reports have been conflicting with regards to T cell recruitment and an actual increase in the number of T cells in the airways (147–149). In the present study, csSAM has identified lymphocytes as expressing significantly different genes – with a cell cycle focus – between ER and DR samples at 2 hours post-challenge. A limitation in the study design, however, was that the lymphocyte sub-populations of natural killer cells, B cells, and various types of T cells were not distinguished. Such knowledge would have been useful in better understanding the disease mechanisms as relevant to each population of lymphocytes. For instance, CD4+ T cells have been found to have a Th2 phenotype, producing cytokines which promote a more severe asthmatic response (150). On the other hand, CD8+ T cells may help regulate these responses, as supported by the finding that an increase in these cells seems to suppress the development of the LAR (151). Without information on the composition of lymphocyte subsets, it is not feasible to attribute the csSAM findings, which showed a down-regulation of genes associated with DR lymphocytes, to certain cell types. Likewise, the identification of cell cycle regulation canonical pathways cannot be easily interpreted without further validation studies focusing on specific lymphocyte sub-populations.  82  4.5 Summary The results presented in this chapter demonstrate that changes in gene expression from pre- to post-allergen challenge follow different patterns between isolated early and dual asthmatic responders. In whole blood analysis, linoleic acid metabolism was identified as a significant canonical pathway, with implications for the development of the LAR. In addition, through the use of the csSAM algorithm, eosinophils and lymphocytes were identified to be associated with the largest discrepancies in gene expression profiles between ER and DR at the post-challenge time point. In particular, cell cycle regulation processes were noted, which is in support of the current model of asthma pathophysiology demonstrating a key role of these cell types in cellular inflammation.  83  CHAPTER 5: CONCLUSIONS AND FUTURE DIRECTIONS 5.1 Overall Summary The purpose of this research was to investigate the molecular profiles of the allergic asthmatic response, ultimately focusing on differences between isolated early responders and dual responders. To achieve this, peripheral blood samples drawn prior to and 2 hours after allergen inhalation challenge were examined. A preliminary study was undertaken in order to validate the usefulness of the chosen time point (2 hours) in detecting gene expression changes in the peripheral blood. Through genome-wide microarray analysis and pathway tools, it was demonstrated that the Nrf2-mediated oxidative stress response pathway was perturbed. A gene within this pathway, ABCC1, was further confirmed to be decreased in expression level post-allergen inhalation, as shown by RT-qPCR results on additional sample pairs. Differential levels of oxidative and inflammatory molecules in the plasma, such as DHA, AA, and nitrotyrosine, provided additional support for an altered oxidative stress response after AIC. Next, plasma samples were tested against a cytokine panel, which identified CCL2 as being reduced post-challenge. Extending the atopic asthmatic cohort to include subjects with allergic rhinitis and occupational asthma, comparable results were observed. Despite the highly significant findings and the known effects of CCL2 in allergic diseases (101), this decrease may be irrelevant of allergen exposure. This is because control subjects who did not undergo AIC were also shown to demonstrate a significant decrease in CCL2 levels, suggesting an inherent (perhaps diurnal) fluctuation in the cytokine. Additional analysis of baseline CCL2 revealed a positive association between aging and increasing CCL2 levels in plasma. Having shown that 2 hours after AIC is sufficient to 84  detect molecular changes in peripheral blood, samples from isolated early responders and dual responders were compared. Genome-wide transcriptomic profiles indicated that linoleic acid metabolism was perturbed differently between the two responses after cat allergen inhalation challenge. When the whole blood gene expression signals were deconvoluted in accordance with differential leukocyte numbers using the csSAM algorithm, eosinophils and lymphocytes were identified as the cell types associated with the most divergent transcriptomic profiles between ER and DR at the post-challenge time point.  5.2 Limitations and Future Directions Much of the findings reported here are based on data generated by microarrays and pathway analyses (e.g., GSEA, IPA). While these tools offer a useful means to conduct a general assessment of biological events, there are limitations. In addition to the errors associated with multiple hypothesis testing, a lack of a standard procedure for microarray data processing may lead to variations in significant findings (152). For pathway analysis software, which are driven by the current knowledge base, research trends and inaccurate or missing information may create a bias for certain pathways over others (153). Due to the exploratory nature of my study, limited follow-up analyses were conducted to confirm the microarray results and the pathways identified. Future directions include validation of ER and DR gene expression signals using RT-qPCR, as was performed for the preliminary analysis in Chapter 2. RT-qPCR is highly sensitive and specific, allowing for more accurate quantification of gene expression signals (154,155). In addition, the protein products of significant genes can be tested by enzyme-linked immunosorbent assays (ELISA) or other protein detection methods. 85  Because gene expression levels are not necessarily proportional to the level of proteins produced (due to variable rates of mRNA translation, for instance), it is important to assess whether changes in the transcriptome after AIC is reflected in protein output (152). The results produced by the csSAM algorithm will also require further validation. Because this gene expression deconvolution method is relatively new, it would be ideal to have additional evidence as support. One possible experiment is to isolate the leukocyte subsets prior to measuring their transcriptomes, and then compare these results with that of csSAM. It must be noted, however, that the separation process may introduce alterations in gene expression profiles. Therefore, perhaps the immediate usefulness of csSAM is to aid in hypothesis formulation, as suggested by the authors of the algorithm (125). Having identified a cell type of interest – in this case, the eosinophils and lymphocytes – a next step may be to carry out assays targeted toward those cell types in order to assess their importance in the real biological context. A future direction stemming from the cytokine study described in Chapter 3 is to follow up on CCL5, which was identified to be significantly increased after AIC. In the same way that CCL2 was validated, CCL5 immunoassays can be performed to test for a consistent pattern of perturbation in cytokine levels post-challenge, using different cohorts of allergic diseases and control subjects. Having observed a very high reproducibility of results using the MSD immunoassay system in the present study, it may be fitting to also assess CCL5 levels using this technology.  86  To further explore the mechanisms of the asthmatic response, additional molecular targets may be studied. For instance, microRNAs (miRNAs) are known to play important roles in regulating the mRNA translation process, through binding to complementary sections of mRNAs (156). Examining the miRNA profiles between preand post-AIC may reveal underlying factors contributing to altered gene expression, especially if complementary base pairs can be demonstrated between specific mRNAs and miRNAs. Metabolites can also be investigated. Through identification of molecules perturbed after AIC, the biological processes occurring during an asthmatic response can be better understood. Because the current research is based around the use of peripheral blood samples, it may not fully reflect the situation of the airways. Therefore, future investigations may include the use of airway tissues taken directly from the site of injury, although obtaining these samples may be difficult. In conjunction with ongoing subject recruitment, research into these various areas as discussed above can add valuable insight into the pathophysiology of asthma, especially if additional sampling time points are included.  5.3 Relevance of Research This study demonstrates the usefulness of the 2 hour time point in detecting molecular changes after allergen inhalation challenge, providing a model for future studies to also employ an early time point of investigation. Through transcriptome profiling, a list of new genes were suggested to be involved in the asthmatic responses, in both the isolated early responders and the dual responders. Follow-up of these  87  targets may confirm novel genes crucial to the disease, which can be further investigated in genetic studies. In addition, biomarkers may be revealed through these molecular analyses to enable new methods of disease detection and monitoring. If measurable at 2 hours after allergen inhalation, such biomarkers may also be useful in the prediction of the LAR before its clinical onset. Finally, this study enables a better insight into the mechanisms and pathways behind the asthmatic response. This may lead to possible pharmacologic targets to improve the treatment of asthma, especially with respect to minimizing the late phase response and the associated outcome of chronic asthma.  88  REFERENCES 1.  2. 3.  4. 5.  6.  7. 8. 9. 10. 11.  12.  13.  14. 15.  16. 17.  Bousquet J, Khaltaev N. Global surveillance, prevention and control of chronic respiratory diseases: a comprehensive approach. In: Global Alliance against Chronic Respiratory Diseases. World Health Organization; 2007. British Guideline on the Management of Asthma. British Thoracic Society; 2009. Moffatt MF, Kabesch M, Liang L, Dixon AL, Strachan D, Heath S, et al. Genetic variants regulating ORMDL3 expression contribute to the risk of childhood asthma. Nature. 2007 Jul 26;448(7152):470–3. Akhabir L, Sandford AJ. Genome-wide association studies for discovery of genes involved in asthma. Respirology. 2011 Apr;16(3):396–406. D’Amato G, Liccardi G, D’Amato M, Holgate S. Environmental risk factors and allergic bronchial asthma. Clinical and Experimental Allergy. 2005 Sep;35(9):1113–24. Baxi SN, Phipatanakul W. The role of allergen exposure and avoidance in asthma. Adolescent Medicine: State of the Art Reviews. 2010 Apr;21(1):57–71, viii-ix. Murphy K, Travers P, Walport M. Janeway’s Immunobiology. 7th ed. London: Garland; 2007. Halwani R, Al-Muhsen S, Hamid Q. Airway remodeling in asthma. Current Opinion in Pharmacology. 2010 Jun;10(3):236–45. Gauvreau GM, Evans MY. Allergen inhalation challenge: a human model of asthma exacerbation. Contributions to Microbiology. 2007 Jan;14:21–32. Haddad ZH. Current status of bronchial inhalation challenge in asthmatics. The Western Journal of Medicine. 1975 Jun;122(6):493. Cockcroft DW, Murdock KY, Kirby J, Hargreave F. Prediction of airway responsiveness to allergen from skin sensitivity to allergen and airway responsiveness to histamine. The American Review of Respiratory Disease. 1987 Jan;135(1):264–7. Cockcroft DW, Davis BE, Boulet L-P, Deschesnes F, Gauvreau GM, O’Byrne PM, et al. The links between allergen skin test sensitivity, airway responsiveness and airway response to allergen. Allergy. 2005 Jan;60(1):56–9. Robertson DG, Kerigan AT, Hargreave FE, Chalmers R, Dolovich J. Late asthmatic responses induced by ragweed pollen allergen. The Journal of Allergy and Clinical Immunology. 1974 Oct;54(4):244–54. Machado L, Stålenheim G. Factors influencing the occurrence of late bronchial reactions after allergen challenge. Allergy. 1990 May;45(4):268–74. Lai CK, Beasley R, Holgate ST. The effect of an increase in inhaled allergen dose after terfenadine on the occurrence and magnitude of the late asthmatic response. Clinical and Experimental Allergy. 1989 Mar;19(2):209–16. Hatzivlassiou M, Grainge C, Kehagia V, Lau L, Howarth PH. The allergen specificity of the late asthmatic reaction. Allergy. 2010 Mar;65(3):355–8. Warner JA, Kroegel C. Pulmonary immune cells in health and disease: mast cells and basophils. European Respiratory Journal. 1994 Jul 1;7(7):1326–41.  89  18. 19. 20.  21.  22.  23.  24. 25.  26. 27. 28.  29.  30.  31.  Dunford PJ, Holgate ST. The role of histamine in asthma. Advances in Experimental Medicine and Biology. 2010 Jan;709:53–66. Bisgaard H. Pathophysiology of the cysteinyl leukotrienes and effects of leukotriene receptor antagonists in asthma. Allergy. 2001 Jan;56 Suppl 6:7–11. Rossi GA, Crimi E, Lantero S, Gianiorio P, Oddera S, Crimi P, et al. Late-phase asthmatic reaction to inhaled allergen is associated with early recruitment of eosinophils in the airways. The American Review of Respiratory Disease. 1991 Aug;144(2):379–83. Gauvreau GM, Lee JM, Watson RM, Irani AM, Schwartz LB, O’Byrne PM. Increased numbers of both airway basophils and mast cells in sputum after allergen inhalation challenge of atopic asthmatics. American Journal of Respiratory and Critical Care Medicine. 2000 May;161(5):1473–8. Burastero SE, Crimi E, Balbo A, Vavassori M, Borgonovo B, Gaffi D, et al. Oligoclonality of lung T lymphocytes following exposure to allergen in asthma. Journal of Immunology. 1995 Dec 15;155(12):5836–46. Diaz P, Gonzalez MC, Galleguillos FR, Ancic P, Cromwell O, Shepherd D, et al. Leukocytes and mediators in bronchoalveolar lavage during allergen-induced latephase asthmatic reactions. The American Review of Respiratory Disease. 1989 Jun;139(6):1383–9. Weersink EJ, Postma DS, Aalbers R, de Monchy JG. Early and late asthmatic reaction after allergen challenge. Respiratory Medicine. 1994 Feb;88(2):103–14. Dente FL, Bacci E, Bartoli ML, Cianchetti S, Di Franco A, Costa F, et al. Magnitude of late asthmatic response to allergen in relation to baseline and allergen-induced sputum eosinophilia in mild asthmatic patients. Annals of Allergy, Asthma & Immunology. 2008 May;100(5):457–62. Kay AB. The role of eosinophils in the pathogenesis of asthma. Trends in Molecular Medicine. 2005 Apr;11(4):148–52. Monteseirín J. Neutrophils and Asthma. Journal of Investigational Allergology and Clinical Immunology. 2009;19(5):340–54. Gauvreau GM, Ellis AK, Denburg JA. Haemopoietic processes in allergic disease: eosinophil/basophil development. Clinical and Experimental Allergy. 2009 Sep;39(9):1297–306. Sehmi R, Wood LJ, Watson R, Foley R, Hamid Q, O’Byrne PM, et al. Allergeninduced increases in IL-5 receptor alpha-subunit expression on bone marrowderived CD34+ cells from asthmatic subjects. A novel marker of progenitor cell commitment towards eosinophilic differentiation. The Journal of Clinical Investigation. 1997 Nov 15;100(10):2466–75. Gibson PG, Manning PJ, O’Byrne PM, Girgis-Gabardo A, Dolovich J, Denburg JA, et al. Allergen-induced asthmatic responses. Relationship between increases in airway responsiveness and increases in circulating eosinophils, basophils, and their progenitors. The American Review of Respiratory Disease. 1991 Feb;143(2):331–5. Dorman SC, Sehmi R, Gauvreau GM, Watson RM, Foley R, Jones GL, et al. Kinetics of bone marrow eosinophilopoiesis and associated cytokines after allergen inhalation. American Journal of Respiratory and Critical Care Medicine. 2004 Mar 1;169(5):565–72. 90  32. 33.  34. 35.  36.  37.  38.  39.  40. 41.  42. 43.  44.  45.  Takatsu K, Nakajima H. IL-5 and eosinophilia. Current Opinion in Immunology. 2008 Jun;20(3):288–94. Wood LJ, Sehmi R, Dorman S, Hamid Q, Tulic MK, Watson RM, et al. Allergeninduced increases in bone marrow T lymphocytes and interleukin-5 expression in subjects with asthma. American Journal of Respiratory and Critical Care Medicine. 2002 Sep 15;166(6):883–9. Kawasaki ES. The end of the microarray Tower of Babel: will universal standards lead the way? Journal of Biomolecular Techniques. 2006 Jul;17(3):200–6. Debey S, Zander T, Brors B, Popov A, Eils R, Schultze JL. A highly standardized, robust, and cost-effective method for genome-wide transcriptome analysis of peripheral blood applicable to large-scale clinical trials. Genomics. 2006 May;87(5):653–64. Wang Z, Neuburg D, Li C, Su L, Kim JY, Chen JC, et al. Global gene expression profiling in whole-blood samples from individuals exposed to metal fumes. Environmental Health Perspectives. 2005 Feb;113(2):233–41. Halldén G, Hellman C, Grönneberg R, Lundahl J. Increased levels of IL-5 positive peripheral blood eosinophils and lymphocytes in mild asthmatics after allergen inhalation provocation. Clinical and Experimental Allergy. 1999 May;29(5):595– 603. Matsumoto K, Gauvreau GM, Rerecich T, Watson RM, Wood LJ, O’Byrne PM. IL10 production in circulating T cells differs between allergen-induced isolated early and dual asthmatic responders. The Journal of Allergy and Clinical Immunology. 2002 Feb;109(2):281–6. Gauvreau GM, Hessel EM, Boulet L-P, Coffman RL, O’Byrne PM. Immunostimulatory sequences regulate interferon-inducible genes but not allergic airway responses. American Journal of Respiratory and Critical Care Medicine. 2006 Jul 1;174(1):15–20. Cockcroft DW, Killian DN, Mellon JJ, Hargreave FE. Bronchial reactivity to inhaled histamine: a method and clinical survey. Clinical Allergy. 1977 May;7(3):235–43. Cockcroft DW. Measure of airway responsiveness to inhaled histamine or methacholine; method of continuous aerosol generation and tidal breathing inhalation. In: Hargreave FE, Woolcock AJ, eds. Airway responsiveness: measurement and interpretation. Astra Pharmaceuticals, Mississauga, Canada, 1996; p. 22.: O’Byrne PM, Dolovich J, Hargreave FE. Late asthmatic responses. The American Review of Respiratory Disease. 1987 Sep;136(3):740–51. Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, et al. Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biology. 2002 Jun 18;3(7):RESEARCH0034. Van Handel E, Zilversmit DB. Micromethod for the direct determination of serum triglycerides. The Journal of Laboratory and Cinical Medicine. 1957 Jul;50(1):152– 7. Saeed Z, Guilbault C, De Sanctis JB, Henri J, Marion D, St-Arnaud R, et al. Fenretinide prevents the development of osteoporosis in Cftr-KO mice. Journal of Cystic Fibrosis. 2008 May;7(3):222–30. 91  46.  47.  48.  49.  50.  51.  52.  53.  54.  55.  56.  57.  Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, et al. Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics. 2003 Apr;4(2):249–64. Mootha VK, Lindgren CM, Eriksson K-F, Subramanian A, Sihag S, Lehar J, et al. PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nature Genetics. 2003 Jul;34(3):267–73. Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences of the United States of America. 2005 Oct 25;102(43):15545–50. Crapo RO, Casaburi R, Coates AL, Enright PL, Hankinson JL, Irvin CG, et al. Guidelines for methacholine and exercise challenge testing-1999. This official statement of the American Thoracic Society was adopted by the ATS Board of Directors, July 1999. American Journal of Respiratory and Critical Care Medicine. 2000 Jan;161(1):309–29. McCreanor J, Cullinan P, Nieuwenhuijsen MJ, Stewart-Evans J, Malliarou E, Jarup L, et al. Respiratory effects of exposure to diesel traffic in persons with asthma. The New England Journal of Medicine. 2007 Dec 6;357(23):2348–58. Brutsche M, Joos L, Carlen Brutsche IIE, Bissinger R, Tamm M, Custovic A, et al. Array-based diagnostic gene-expression score for atopy and asthma. Journal of Allergy and Clinical Immunology. 2002 Feb;109(2):271–3. Nakajima T. Gene expression screening of human mast cells and eosinophils using high-density oligonucleotide probe arrays: abundant expression of major basic protein in mast cells. Blood. 2001 Aug 15;98(4):1127–34. Boldogh I, Bacsi A, Choudhury BK, Dharajiya N, Alam R, Hazra TK, et al. ROS generated by pollen NADPH oxidase provide a signal that augments antigeninduced allergic airway inflammation. The Journal of Clinical Investigation. 2005 Aug;115(8):2169–79. Rangasamy T, Williams MA, Bauer S, Trush MA, Emo J, Georas SN, et al. Nuclear erythroid 2 p45-related factor 2 inhibits the maturation of murine dendritic cells by ragweed extract. American Journal of Respiratory Cell and Molecular Biology. 2010 Sep;43(3):276–85. Itoh K, Wakabayashi N, Katoh Y, Ishii T, Igarashi K, Engel JD, et al. Keap1 represses nuclear activation of antioxidant responsive elements by Nrf2 through binding to the amino-terminal Neh2 domain. Genes & Development. 1999 Jan 1;13(1):76–86. Kobayashi A, Kang M-I, Okawa H, Ohtsuji M, Zenke Y, Chiba T, et al. Oxidative stress sensor Keap1 functions as an adaptor for Cul3-based E3 ligase to regulate proteasomal degradation of Nrf2. Molecular and Cellular Bology. 2004 Aug;24(16):7130–9. Itoh K, Chiba T, Takahashi S, Ishii T, Igarashi K, Katoh Y, et al. An Nrf2/small Maf heterodimer mediates the induction of phase II detoxifying enzyme genes through antioxidant response elements. Biochemical and Biophysical Research Communications. 1997 Jul 18;236(2):313–22.  92  58. 59.  60.  61. 62.  63.  64.  65.  66.  67.  68. 69.  70.  71.  72.  Cho H-Y, Reddy SP, Kleeberger SR. Nrf2 defends the lung from oxidative stress. Antioxidants & Redox Signaling. 2006 Jan 17;8(1-2):76–87. Haimeur A, Conseil G, Deeley RG, Cole SPC. The MRP-related and BCRP/ABCG2 multidrug resistance proteins: biology, substrate specificity and regulation. Current Drug Metabolism. 2004 Feb;5(1):21–53. Leier I, Jedlitschky G, Buchholz U, Cole SP, Deeley RG, Keppler D. The MRP gene encodes an ATP-dependent export pump for leukotriene C4 and structurally related conjugates. The Journal of Biological Chemistry. 1994 Nov 11;269(45):27807–10. Meister A. Glutathione metabolism and its selective modification. The Journal of Biological Chemistry. 1988 Nov 25;263(33):17205–8. Serru V, Baudin B, Ziegler F, David JP, Cals MJ, Vaubourdolle M, et al. Quantification of reduced and oxidized glutathione in whole blood samples by capillary electrophoresis. Clinical Chemistry. 2001 Jan;47(7):1321–4. Weiss JW, Drazen JM, Coles N, McFadden ER, Weller PF, Corey EJ, et al. Bronchoconstrictor effects of leukotriene C in humans. Science. 1982 Apr 9;216(4542):196–8. Laitinen LA, Laitinen A, Haahtela T, Vilkka V, Spur BW, Lee TH. Leukotriene E4 and granulocytic infiltration into asthmatic airways. Lancet. 1993 Apr 17;341(8851):989–90. Lima JJ, Zhang S, Grant A, Shao L, Tantisira KG, Allayee H, et al. Influence of leukotriene pathway polymorphisms on response to montelukast in asthma. American Journal of Respiratory and Critical Care Medicine. 2006 Feb 15;173(4):379–85. Kelley DS, Siegel D, Fedor DM, Adkins Y, Mackey BE. DHA supplementation decreases serum C-reactive protein and other markers of inflammation in hypertriglyceridemic men. The Journal of Nutrition. 2009 Mar;139(3):495–501. Vedin I, Cederholm T, Freund Levi Y, Basun H, Garlind A, Faxen Irving G, et al. Effects of docosahexaenoic acid-rich n-3 fatty acid supplementation on cytokine release from blood mononuclear leukocytes: the OmegAD study. American Journal of Clinical Nutrition. 2008;87(6):1616–22. Calder PC. n-3 Polyunsaturated fatty acids, inflammation, and inflammatory diseases. American Journal of Clinical Nutrition. 2006;83(6):S1505–19. Lands WEM. Dietary fat and health: the evidence and the politics of prevention: careful use of dietary fats can improve life and prevent disease. Annals of the New York Academy of Sciences. 2005 Dec;1055:179–92. Hibbeln JR, Nieminen LR, Blasbalg TL, Riggs JA, Lands WE. Healthy intakes of n-3 and n-6 fatty acids: estimations considering worldwide diversity. American Journal of Clinical Nutrition. 2006;83(6):S1483–93. Okuyama H, Ichikawa Y, Sun Y, Hamazaki T, Lands WEM. Omega3 fatty acids effectively prevent coronary heart disease and other late-onset diseases--the excessive linoleic acid syndrome. World Review of Nutrition and Dietetics. 2007 Jan;96:83–103. van der Vliet A, Eiserich JP, Kaur H, Cross CE, Halliwell B. Nitrotyrosine as biomarker for reactive nitrogen species. Methods in Enzymology. 1996 Jan;269:175–84. 93  73.  74.  75. 76. 77. 78. 79. 80. 81.  82.  83. 84.  85. 86. 87.  88. 89.  90.  Geilen CC, Wieder T, Orfanos CE. Ceramide signalling: regulatory role in cell proliferation, differentiation and apoptosis in human epidermis. Archives of Dermatological Research. 1997 Sep;289(10):559–66. Andrieu-Abadie N, Gouazé V, Salvayre R, Levade T. Ceramide in apoptosis signaling: relationship with oxidative stress. Free Radical Biology & Medicine. 2001 Sep 15;31(6):717–28. Kips JC. Cytokines in asthma. European Respiratory Journal. 2001 Jul 2;18(1):24–33. Doherty T, Broide D. Cytokines and growth factors in airway remodeling in asthma. Current Opinion in Immunology. 2007 Dec;19(6):676–80. Kay AB. TH2-type cytokines in asthma. Annals of the New York Academy of Sciences. 1996 Oct 31;796:1–8. Barnes PJ. Th2 cytokines and asthma: an introduction. Respiratory Research. 2001 Jan;2(2):64–5. Renauld J-C. New insights into the role of cytokines in asthma. Journal of Clinical Pathology. 2001 Aug 1;54(8):577–89. O’Byrne PM. Cytokines or their antagonists for the treatment of asthma. Chest. 2006 Jul;130(1):244–50. Chung F. Anti-inflammatory cytokines in asthma and allergy: interleukin-10, interleukin-12, interferon-gamma. Mediators of Inflammation. 2001 Apr;10(2):51– 9. Leonard EJ, Skeel A, Yoshimura T. Biological aspects of monocyte chemoattractant protein-1 (MCP-1). Advances in Experimental Medicine and Biology. 1991 Jan;305:57–64. Craig MJ, Loberg RD. CCL2 (Monocyte Chemoattractant Protein-1) in cancer bone metastases. Cancer Metastasis Reviews. 2006 Dec;25(4):611–9. Rollins BJ, Yoshimura T, Leonard EJ, Pober JS. Cytokine-activated human endothelial cells synthesize and secrete a monocyte chemoattractant, MCP-1/JE. The American Journal of Pathology. 1990 Jun;136(6):1229–33. Xia M, Sui Z. Recent developments in CCR2 antagonists. Expert Opinion on Therapeutic Patents. 2009 Mar;19(3):295–303. Team RDC. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing. Vienna, Austria. 2006. Saad-El-Din Bessa S, Abo El-Magd GH, Mabrouk MM. Serum Chemokines RANTES and Monocyte Chemoattractant Protein-1 in Egyptian Patients with Atopic Asthma: Relationship to Disease Severity. Archives of Medical Research. 2012 Jan 30;:1–6. Romagnani S. Cytokines and chemoattractants in allergic inflammation. Molecular Immunology. 2002 May;38(12-13):881–5. Sohn MH, Kim S-H, Kim K-W, Jee HM, Park H-S, Kim K-E. RANTES gene promoter polymorphisms are associated with bronchial hyperresponsiveness in Korean children with asthma. Lung. 2008;186(1):37–43. Lachheb J, Chelbi H, Hamzaoui K, Hamzaoui A. Association between RANTES polymorphisms and asthma severity among Tunisian children. Human Immunology. 2007 Aug;68(8):675–80.  94  91.  92.  93.  94.  95.  96.  97.  98.  99.  100. 101. 102.  103.  Muro M, Marín L, Torio A, Pagan JA, Alvarez-López MR. CCL5/RANTES chemokine gene promoter polymorphisms are not associated with atopic and nonatopic asthma in a Spanish population. International Journal of Immunogenetics. 2008 Feb;35(1):19–23. Alam R, York J, Boyars M, Stafford S, Grant JA, Lee J, et al. Increased MCP-1, RANTES, and MIP-1alpha in bronchoalveolar lavage fluid of allergic asthmatic patients. American Journal of Respiratory and Critical Care Medicine. 1996 Apr;153(4 Pt 1):1398–404. Lukacs NW, Strieter RM, Warmington K, Lincoln P, Chensue SW, Kunkel SL. Differential recruitment of leukocyte populations and alteration of airway hyperreactivity by C-C family chemokines in allergic airway inflammation. Journal of Immunology. 1997 May 1;158(9):4398–404. Chihara J, Yasuba H, Tsuda A, Urayama O, Saito N, Honda K, et al. Elevation of the plasma level of RANTES during asthma attacks. The Journal of Allergy and Clinical Immunology. 1997 Dec;100(6 Pt 2):S52–5. Bisset LR, Schmid-Grendelmeier P. Chemokines and their receptors in the pathogenesis of allergic asthma: progress and perspective. Current Opinion in Pulmonary Medicine. 2005 Jan;11(1):35–42. Szalai C, Kozma GT, Nagy A, Bojszkó Á, Krikovszky D, Szabó T, et al. Polymorphism in the gene regulatory region of MCP-1 is associated with asthma susceptibility and severity. Journal of Allergy and Clinical Immunology. 2001 Sep;108(3):375–81. Chelbi H, Ghadiri A, Lacheb J, Ghandil P, Hamzaoui K, Hamzaoui A, et al. A polymorphism in the CCL2 chemokine gene is associated with asthma risk: a case-control and a family study in Tunisia. Genes and Immunity. 2008 Oct;9(7):575–81. Holgate ST, Bodey KS, Janezic A, Frew AJ, Kaplan AP, Teran LM. Release of RANTES, MIP-1 alpha, and MCP-1 into asthmatic airways following endobronchial allergen challenge. American Journal of Respiratory and Critical Care Medicine. 1997 Nov;156(5):1377–83. Chan C-K, Kuo M-L, Yeh K-W, Ou L-S, Chen L-C, Yao T-C, et al. Sequential evaluation of serum monocyte chemotactic protein 1 among asymptomatic state and acute exacerbation and remission of asthma in children. The Journal of Asthma. 2009 Apr;46(3):225–8. Kuna P, Lazarovich M, Kaplan AP. Chemokines in seasonal allergic rhinitis. The Journal of Allergy and Clinical Immunology. 1996 Jan;97(1 Pt 1):104–12. Rose CE, Sung S-SJ, Fu SM. Significant involvement of CCL2 (MCP-1) in inflammatory disorders of the lung. Microcirculation. 2003 Jun;10(3-4):273–88. Gunn MD, Nelken NA, Liao X, Williams LT. Monocyte chemoattractant protein-1 is sufficient for the chemotaxis of monocytes and lymphocytes in transgenic mice but requires an additional stimulus for inflammatory activation. Journal of Immunology. 1997 Jan 1;158(1):376–83. Gonzalo JA, Lloyd CM, Wen D, Albar JP, Wells TN, Proudfoot A, et al. The coordinated action of CC chemokines in the lung orchestrates allergic inflammation and airway hyperresponsiveness. The Journal of Experimental Medicine. 1998 Jul 6;188(1):157–67. 95  104. Campbell EM, Charo IF, Kunkel SL, Strieter RM, Boring L, Gosling J, et al. Monocyte chemoattractant protein-1 mediates cockroach allergen-induced bronchial hyperreactivity in normal but not CCR2-/- mice: the role of mast cells. Journal of Immunology. 1999 Aug 15;163(4):2160–7. 105. Lu B, Rutledge BJ, Gu L, Fiorillo J, Lukacs NW, Kunkel SL, et al. Abnormalities in monocyte recruitment and cytokine expression in monocyte chemoattractant protein 1-deficient mice. The Journal of Experimental Medicine. 1998 Feb 16;187(4):601–8. 106. Karpus WJ, Lukacs NW, Kennedy KJ, Smith WS, Hurst SD, Barrett TA. Differential CC chemokine-induced enhancement of T helper cell cytokine production. Journal of Immunology. 1997 May 1;158(9):4129–36. 107. Del Prete GF, De Carli M, D’Elios MM, Maestrelli P, Ricci M, Fabbri L, et al. Allergen exposure induces the activation of allergen-specific Th2 cells in the airway mucosa of patients with allergic respiratory disorders. European Journal of Immunology. 1993 Jul;23(7):1445–9. 108. Maus UA, Wellmann S, Hampl C, Kuziel WA, Srivastava M, Mack M, et al. CCR2positive monocytes recruited to inflamed lungs downregulate local CCL2 chemokine levels. American Journal of Physiology. Lung Cellular and Molecular Physiology. 2005 Feb;288(2):L350–8. 109. Fatouros I, Chatzinikolaou A, Paltoglou G, Petridou A, Avloniti A, Jamurtas A, et al. Acute resistance exercise results in catecholaminergic rather than hypothalamic-pituitary-adrenal axis stimulation during exercise in young men. Stress. 2010 Nov;13(6):461–8. 110. García JJ, Bote E, Hinchado MD, Ortega E. A single session of intense exercise improves the inflammatory response in healthy sedentary women. Journal of Physiology and Biochemistry. 2011 Mar;67(1):87–94. 111. Paulsen G, Benestad HB, Strøm-Gundersen I, Mørkrid L, Lappegård KT RT. Delayed Leukocytosis and Cytokine Response to High-Force Eccentric Exercise. Medicine & Science in Sports & Exercise. 2005 Nov;37(11):1877–83. 112. Korybalska K, Pyda M, Grajek S, Lanocha M, Breborowicz A, Witowski J. Serum profiles of monocyte chemoattractant protein-1 as a biomarker for patients recovering from myocardial infarction. Clinical Research in Cardiology. 2010 May;99(5):315–22. 113. Garcia-Alonso M, Minihane A-M, Rimbach G, Rivas-Gonzalo JC, de PascualTeresa S. Red wine anthocyanins are rapidly absorbed in humans and affect monocyte chemoattractant protein 1 levels and antioxidant capacity of plasma. The Journal of Nutritional Biochemistry. 2009 Jul;20(7):521–9. 114. Inadera H, Egashira K, Takemoto M, Ouchi Y, Matsushima K. Increase in circulating levels of monocyte chemoattractant protein-1 with aging. Journal of Interferon & Cytokine Research. 1999 Oct;19(10):1179–82. 115. Antonelli A, Rotondi M, Fallahi P, Ferrari SM, Paolicchi A, Romagnani P, et al. Increase of CXC chemokine CXCL10 and CC chemokine CCL2 serum levels in normal ageing. Cytokine. 2006 Apr;34(1-2):32–8. 116. Seidler S, Zimmermann HW, Bartneck M, Trautwein C, Tacke F. Age-dependent alterations of monocyte subsets and monocyte-related chemokine pathways in healthy adults. BMC Immunology. 2010 Jan;11:30. 96  117. Cieslik KA, Taffet GE, Carlson S, Hermosillo J, Trial J, Entman ML. Immuneinflammatory dysregulation modulates the incidence of progressive fibrosis and diastolic stiffness in the aging heart. Journal of Molecular and Cellular Cardiology. 2011 Jan;50(1):248–56. 118. Song Y, Shen H, Schenten D, Shan P, Lee PJ, Goldstein DR. Aging Enhances the Basal Production of IL-6 and CCL2 in Vascular Smooth Muscle Cells. Arteriosclerosis, Thrombosis, and Vascular Biology. 2011 Oct 27;:103–9. 119. Coll B, Alonso-Villaverde C, Joven J. Monocyte chemoattractant protein-1 and atherosclerosis: is there room for an additional biomarker? Clinica Chimica Acta. 2007 Aug;383(1-2):21–9. 120. Ginaldi L, De Martinis M, D’Ostilio A, Marini L, Loreto MF, Martorelli V, et al. The immune system in the elderly: II. Specific cellular immunity. Immunologic Research. 1999 Jan;20(2):109–15. 121. Shearer GM. Th1/Th2 changes in aging. Mechanisms of Ageing and Development. 1997 Mar;94(1-3):1–5. 122. Sakata-Kaneko S, Wakatsuki Y, Matsunaga Y, Usui T, Kita T. Altered Th1/Th2 commitment in human CD4+ T cells with ageing. Clinical and Experimental Immunology. 2000 May;120(2):267–73. 123. Ide K, Hayakawa H, Yagi T, Sato A, Koide Y, Yoshida A, et al. Decreased expression of Th2 type cytokine mRNA contributes to the lack of allergic bronchial inflammation in aged rats. Journal of Immunology. 1999 Jul 1;163(1):396–402. 124. Tusher VG, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proceedings of the National Academy of Sciences of the United States of America. 2001 Apr 24;98(9):5116–21. 125. Shen-Orr SS, Tibshirani R, Khatri P, Bodian DL, Staedtler F, Perry NM, et al. Cell type-specific gene expression differences in complex tissues. Nature Methods. 2010 Apr;7(4):287–9. 126. Raemdonck K, de Alba J, Birrell MA, Grace M, Maher SA, Irvin CG, et al. A role for sensory nerves in the late asthmatic response. Thorax. 2012 Jan;67(1):19–25. 127. Jiménez-Marín A, Collado-Romero M, Ramirez-Boo M, Arce C, Garrido JJ. Biological pathway analysis by ArrayUnlock and Ingenuity Pathway Analysis. BMC Proceedings. 2009 Jan;3 Suppl 4:S6. 128. Cheuvront SN. The Zone Diet phenomenon: a closer look at the science behind the claims. Journal of the American College of Nutrition. 2003 Feb;22(1):9–17. 129. Burr GO, Burr MM, Miller E. On the nature and role of the fatty acids essential in nutrition. The Journal of Biological Chemistry. 1930;86(587):1–9. 130. Ogawa Y, Calhoun WJ. The role of leukotrienes in airway inflammation. The Journal of Allergy and Clinical Immunology. 2006 Oct;118(4):789–98; quiz 799– 800. 131. Mehrotra AK, Henderson WR. The role of leukotrienes in airway remodeling. Current Molecular Medicine. 2009 Apr;9(3):383–91. 132. Arm JP, Lee TH. Sulphidopeptide leukotrienes in asthma. Clinical Science. 1993 May;84(5):501–10. 133. Hay DW, Torphy TJ, Undem BJ. Cysteinyl leukotrienes in asthma: old mediators up to new tricks. Trends in Pharmacological Sciences. 1995 Sep;16(9):304–9.  97  134. Mastalerz L, Kumik J. Antileukotriene drugs in the treatment of asthma. Polskie Archiwum Medycyny Wewnętrznej. 2010 Mar;120(3):103–8. 135. Rosewich M, Rose MA, Eickmeier O, Travaci M, Kitz R, Zielen S. Montelukast as add-on therapy to beta-agonists and late airway response. The European Respiratory Journal. 2007 Jul;30(1):56–61. 136. Fairfax AJ, Hanson JM, Morley J. The late reaction following bronchial provocation with house dust mite allergen. Dependence on arachidonic acid metabolism. Clinical and Experimental Immunology. 1983 May;52(2):393–8. 137. Nabe T, Yamamoto M, Suga M, Kohno S. Intratracheal dosing with disodium cromoglycate inhibits late asthmatic response by attenuating eicosanoid production in guinea pigs. European Journal of Pharmacology. 2004 Aug 16;497(1):97–104. 138. Miyake Y, Sasaki S, Arakawa M, Tanaka K, Murakami K, Ohya Y. Fatty acid intake and asthma symptoms in Japanese children: the Ryukyus Child Health Study. Clinical and Experimental Allergy. 2008 Oct;38(10):1644–50. 139. Black PN, Sharpe S. Dietary fat and asthma: is there a connection? The European Respiratory Journal. 1997 Jan;10(1):6–12. 140. Morris A, Noakes M, Clifton PM. The role of n-6 polyunsaturated fat in stable asthmatics. The Journal of Asthma. 2001 Jun;38(4):311–9. 141. Troisi RJ, Willett WC, Weiss ST, Trichopoulos D, Rosner B, Speizer FE. A prospective study of diet and adult-onset asthma. American Journal of Respiratory and Critical Care Medicine. 1995 May;151(5):1401–8. 142. Verstraelen S, Bloemen K, Nelissen I, Witters H, Schoeters G, Van Den Heuvel R. Cell types involved in allergic asthma and their use in in vitro models to assess respiratory sensitization. Toxicology in vitro. 2008 Sep;22(6):1419–31. 143. Kay AB, Klion AD. Anti-interleukin-5 therapy for asthma and hypereosinophilic syndrome. Immunology and Allergy Clinics of North America. 2004 Nov;24(4):645–66, vii. 144. Brightling CE, Symon FA, Birring SS, Bradding P, Pavord ID, Wardlaw AJ. TH2 cytokine expression in bronchoalveolar lavage fluid T lymphocytes and bronchial submucosa is a feature of asthma and eosinophilic bronchitis. Journal of Allergy and Clinical Immunology. 2002 Dec;110(6):899–905. 145. Gauvreau GM, O’Byrne PM, Moqbel R, Velazquez J, Watson RM, Howie KJ, et al. Enhanced expression of GM-CSF in differentiating eosinophils of atopic and atopic asthmatic subjects. American Journal of Respiratory and Critical Care Medicine. 1998 Jul;19(1):55–62. 146. Durham SR, Kay AB. Eosinophils, bronchial hyperreactivity and late-phase asthmatic reactions. Clinical Allergy. 1985 Sep;15(5):411–8. 147. Hamid QA, Cameron LA. Recruitment of T cells to the lung in response to antigen challenge. Journal of Allergy and Clinical Immunology. 2000 Nov;106(5):S227–34. 148. Gerblich AA, Salik H, Schuyler MR. Dynamic T-cell changes in peripheral blood and bronchoalveolar lavage after antigen bronchoprovocation in asthmatics. The American Review of Respiratory Disease. 1991 Mar;143(3):533–7. 149. Frew AJ, St-Pierre J, Teran LM, Trefilieff A, Madden J, Peroni D, et al. Cellular and mediator responses twenty-four hours after local endobronchial allergen  98  150.  151.  152.  153.  154. 155. 156.  challenge of asthmatic airways. The Journal of Allergy and Clinical Immunology. 1996 Jul;98(1):133–43. de Pater-Huijsen FL, Pompen M, Jansen HM, Out TA. Products from mast cells influence T lymphocyte proliferation and cytokine production--relevant to allergic asthma? Immunology Letters. 1997 Jun 1;57(1-3):47–51. Gonzalez MC, Diaz P, Galleguillos FR, Ancic P, Cromwell O, Kay AB. Allergeninduced recruitment of bronchoalveolar helper (OKT4) and suppressor (OKT8) Tcells in asthma. Relative increases in OKT8 cells in single early responders compared with those in late-phase responders. The American Review of Respiratory Disease. 1987 Sep;136(3):600–4. Benson M, Olsson M, Rudemo M, Wennergren G, Cardell LO. Pros and cons of microarray technology in allergy research. Clinical and Experimental Allergy. 2004 Jul;34(7):1001–6. Khatri P, Sirota M, Butte AJ. Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges. PLoS Computational Biology. 2012 Feb 23;8(2):e1002375. Provenzano M, Mocellin S. Complementary Techniques: Validation of Gene Expression Data by Quantitative Real Time PCR. Nature Biotechnology. 2007; VanGuilder HD, Vrana KE, Freeman WM. Twenty-five years of quantitative PCR for gene expression analysis. BioTechniques. 2008 Apr;44(5):619–26. Bartel DP. MicroRNAs: target recognition and regulatory functions. Cell. 2009 Jan 23;136(2):215–33.  99  APPENDICES Appendix 1 — Sequences of Probes and Primers used in RT-qPCR  Gene  ABCC1  CUL3  DNAJA2  DNAJC1  DNAJC19  DNAJC21  PTPLAD1  Component  No. of Bases  Sequencea  Forward primer 5′-3′  20  CTC AGG AGC ACA CGA AAG TC  Reverse primer 5′-3′  19  GGC CAT GGA GTA GCC AAA C  Probe 5′-3′  23  /56-FAM/CTG GGC ATT /ZEN/TCA CAA GGG ATC GC/3IABkFQ/  Forward primer 5′-3′  20  CAA CAC TTG GCA AGG AGA CT  Reverse primer 5′-3′  23  TGC TCA TAT CCC TAA ACA TTC CT  Probe 5′-3′  30  /56-FAM/AGT TTT GAC /ZEN/GTG AAC TGA CAT CCA CAT TCA /3IABkFQ/  Forward primer 5′-3′  21  GAT CAA CCC AGA CAA GCT TTC  Reverse primer 5′-3′  22  CTC TAC CTC CTC TGT TTC TCC A  Probe 5′-3′  25  /56-FAM/TCT GCC ATC /ZEN/TAG ACC GGA AGT TCC T/3IABkFQ/  Forward primer 5′-3′  23  ACA CTA AAA GCA TTA CCT CAC CT  Reverse primer 5′-3′  23  TCA GTT CTA GTC AGT GCA TCT TC  Probe 5′-3′  28  /56-FAM/ATT TAG CAT /ZEN/AAA ACT GCC CAG CAT CCT G/3IABkFQ/  Forward primer 5′-3′  21  AGT GAA GAT GAC AGT CCT TGC  Reverse primer 5′-3′  23  CAC CGA ATA AGA AGA GTC CCT AC  Probe 5′-3′  33  /56-FAM/TCA CAG TCT /ZEN/AAT TAC CAG TTT ATC AGT CTC CCA /3IABkFQ/  Forward primer 5′-3′  21  AGT TTG GAG ATG GAT CGG ATG  Reverse primer 5′-3′  20  GTC ATC ATA GAG CTC AGC GT  Probe 5′-3′  28  /56-FAM/AGG AGG ATG /ZEN/GTA AAG ACA GTG ATG AGG C/3IABkFQ/  Forward primer 5′-3′  22  GGA TTC TCC TGG ATC TTT GTC A  Reverse primer 5′-3′  21  ATA CAT CAT GTC AGC CAC AGT  Probe 5′-3′  28  /56-FAM/TTC CCA AGA /ZEN/TAC AGA ATC GCA CAG TCA G/3IABkFQ/  100  Gene  KRAS  SOD1  GAPDH  PGK1  GUSB  a  Component  No. of Bases  Sequence*  Forward primer 5′-3′  23  TGC CCT ACA TCT TAT TTC CTC AG  Reverse primer 5′-3′  22  CCT ACT GTC GCT AAT GGA TTG G  Probe 5′-3′  24  /56-FAM/AGG TGG TGG /ZEN/CTG ATG CTT TGA ACA /3IABkFQ/  Forward primer 5′-3′  22  CGA GCA GAA GGA AAG TAA TGG A  Reverse primer 5′-3′  25  CTG GAT AGA GGA TTA AAG TGA GGA C  Probe 5′-3′  26  /56-FAM/TGA AGG TGT /ZEN/GGG GAA GCA TTA AAG GA/3IABkFQ/  Forward primer 5′-3′  21  CAG CCT CAA GAT CAT CAG CAA  Reverse primer 5′-3′  19  GGC CAT CCA CAG TCT TCT G  Probe 5′-3′  24  /56-FAM/ATG ACC ACA /ZEN/GTC CAT GCC ATC ACT /3IABkFQ/  Forward primer 5′-3′  21  GTA GGA GTC AAT CTG CCA CAG  Reverse primer 5′-3′  23  GAT CTT GTC TGC AAC TTT AGC TC  Probe 5′-3′  26  /56-FAM/CCT TCT TCA /ZEN/TCA AAA ACC CAC CAG CC/3IABkFQ/  Forward primer 5′-3′  22  AAG AGC CAG TTC CTC ATC AAT G  Reverse primer 5′-3′  19  AGC GAA GCA GGT TGA AGT C  Probe 5′-3′  22  /56-FAM/CGA AGC CCT /ZEN/TCC CTC GGA TGT C/3IABkFQ/  ZEN = Internal ZEN quencher  101  Appendix 2 — Differentially Expressed Probe Sets, Post- versus Pre-Allergen Inhalation Challenge (p≤0.01 and fold change≥1.1) Probe Set ID 8112310 8150592 7936968 8030804 7989193 8068305 8079060 8151281 8032275 8070714 8029136 7923442 7902512 8120579 8157686 8038126 8076169 8000779 7966517 8036072 8140967 7968926 8070953 8108330 8165486  Gene Symbol  Gene Name  RefSeq  P Value  --CEBPD ADAM12 CD33 --ITSN1 VIPR1 TRAM1 MBD3 --CD79A SYT2 DNAJB4 C6orf57 OR1L4 CA11 NPTXR TBX6 C12orf51 KRTDAP SAMD9 --C21orf56 KDM3B TMEM203  --CCAAT/enhancer binding protein (C/EBP), delta ADAM metallopeptidase domain 12 CD33 molecule --Intersectin 1 (SH3 domain protein) Vasoactive intestinal peptide receptor 1 Translocation associated membrane protein 1 Methyl-cpg binding domain protein 3 --CD79a molecule, immunoglobulin-associated alpha Synaptotagmin II Dnaj (Hsp40) homolog, subfamily B, member 4 Chromosome 6 open reading frame 57 Olfactory receptor, family 1, subfamily L, member 4 Carbonic anhydrase XI Neuronal pentraxin receptor T-box 6 Chromosome 12 open reading frame 51 Keratinocyte differentiation-associated protein Sterile alpha motif domain containing 9 --Chromosome 21 open reading frame 56 Lysine (K)-specific demethylase 3B Transmembrane protein 203  --NM_005195 NM_003474 NM_001772 --NM_003024 NM_004624 NM_014294 NM_003926 --NM_001783 NM_177402 NM_007034 NM_145267 NM_001005235 NM_001217 NM_014293 NM_004608 NM_001109662 NM_207392 NM_017654 --NM_001142854 NM_016604 NM_053045  1.03E-05 1.72E-05 2.96E-05 4.37E-05 7.21E-05 9.00E-05 1.50E-04 1.77E-04 1.97E-04 2.06E-04 2.42E-04 3.16E-04 3.42E-04 3.55E-04 3.63E-04 3.69E-04 3.70E-04 3.87E-04 3.95E-04 4.10E-04 4.29E-04 4.69E-04 4.79E-04 4.98E-04 5.09E-04  Fold Change -1.26567 -1.20166 -1.14475 -1.27568 1.51098 -1.17278 -1.13714 1.19815 -1.10751 1.28628 1.12324 -1.18247 1.36707 1.13744 -1.15665 -1.14335 -1.11711 -1.12436 -1.11606 -1.30462 1.48976 -1.3093 -1.12526 -1.19477 1.13055  102  Probe Set ID 8092541  Gene Symbol  Gene Name  RefSeq  P Value  LIPH  NM_139248  5.17E-04  Fold Change -1.21411  NM_015962  5.25E-04  1.25408  NM_001451  5.40E-04  -1.246  NM_004996  5.41E-04  -1.16902  NM_024422 NM_145197 NM_003717 NM_018139 NM_001836 NM_006687 NM_004385 NM_030815 NM_006917 ENST000003097 75 NM_019053 NM_021129 AF284753 AF284753 NM_001386 NM_198074 NM_005871 NM_001010855 NM_022365 NM_004865 NM_147202 NM_002413 NM_004630  5.43E-04 5.79E-04 5.80E-04 6.09E-04 6.34E-04 6.93E-04 7.30E-04 7.34E-04 7.35E-04  -1.11312 1.31002 -1.11916 1.16651 -1.25589 -1.17691 -1.44049 1.2478 -1.16363  7.38E-04  -1.13759  7.57E-04 7.65E-04 7.79E-04 7.79E-04 7.90E-04 8.01E-04 8.20E-04 8.38E-04 8.60E-04 8.83E-04 9.11E-04 9.26E-04 9.32E-04  1.1611 1.23236 -1.16777 -1.16777 -1.24796 -1.21979 1.12645 -1.26548 1.15399 1.17923 -1.24083 -1.1378 -1.10772  7975713  FCF1  7997726  FOXF1  7993478  ABCC1  8022711 8043840 7963689 7978838 7978343 8157141 8106743 8065596 7921955  DSC2 LIPT1 NPFF C14orf104 CMA1 ACTL7A VCAN PDRG1 RXRG  Lipase, member H FCF1 small subunit (SSU) processome component homolog Forkhead box F1 ATP-binding cassette, sub-family C (CFTR/MRP), member 1 Desmocollin 2 Lipoyltransferase 1 Neuropeptide FF-amide peptide precursor Chromosome 14 open reading frame 104 Chymase 1, mast cell Actin-like 7A Versican P53 and DNA-damage regulated 1 Retinoid X receptor, gamma  7941269  LOC100291851  Similar to Putative ubiquitin-like protein FU  7929288 7934133 7911343 8165703 8145470 7925720 7936307 8012539 7932512 8122182 8160805 8097513 7949146  EXOC6 PPA1 UIMC1 UIMC1 DPYSL2 OR2C3 SMNDC1 PIK3R6 DNAJC1 TBPL1 C9orf25 MGST2 SF1  Exocyst complex component 6 Pyrophosphatase (inorganic) 1 Ubiquitin interaction motif containing 1 Ubiquitin interaction motif containing 1 Dihydropyrimidinase-like 2 Olfactory receptor, family 2, subfamily C, member 3 Survival motor neuron domain containing 1 Phosphoinositide-3-kinase, regulatory subunit 6 Dnaj (Hsp40) homolog, subfamily C, member 1 TBP-like 1 Chromosome 9 open reading frame 25 Microsomal glutathione S-transferase 2 Splicing factor 1  103  Probe Set ID 8157233 8083000 7930487 8049952 7940688 8030871 8036865 8076403 8137979 8025984 8144586 8113073 8081333 7953428  Gene Symbol  Gene Name  RefSeq  P Value  HSDL2 FAIM TECTB C2orf85 POLR2G ZNF613 --NAGA ACTB ZNF844 MTMR9 ARRDC3 --CD4  Hydroxysteroid dehydrogenase like 2 Fas apoptotic inhibitory molecule Tectorin beta Chromosome 2 open reading frame 85 Polymerase (RNA) II (DNA directed) polypeptide G Zinc finger protein 613 --N-acetylgalactosaminidase, alpha Actin, beta Zinc finger protein 844 Myotubularin related protein 9 Arrestin domain containing 3 --CD4 molecule  9.91E-04 1.01E-03 1.04E-03 1.05E-03 1.06E-03 1.08E-03 1.12E-03 1.13E-03 1.14E-03 1.14E-03 1.16E-03 1.17E-03 1.18E-03 1.20E-03  8111216  LOC391769  Histone cluster 2, H3c pseudogene  1.24E-03  -1.16401  8038347 7899377 8010426 8066776 7978628 8016452 8138363 8170013 8175317 7984112 8171533 8125341 7952737 8016546  TEAD2 PPP1R8 RNF213 TP53RK PPP2R3C HOXB4 SOSTDC1 ----RAB8B --AGER --ZNF652  TEA domain family member 2 Protein phosphatase 1, regulatory (inhibitor) subunit 8 Ring finger protein 213 TP53 regulating kinase Protein phosphatase 2 (formerly 2A), regulatory subunit Homeobox B4 Sclerostin domain containing 1 ----RAB8B, member RAS oncogene family --Advanced glycosylation end product-specific receptor --Zinc finger protein 652  NM_032303 NM_001033030 NM_058222 NM_173821 NM_002696 NM_001031721 --NM_000262 NM_001101 NM_001136501 NM_015458 NM_020801 --NM_000616 ENST000004264 11 NM_003598 NM_138558 NM_020914 NM_033550 NM_017917 NM_024015 NM_015464 ----NM_016530 --NM_001136 --NM_014897  Fold Change 1.13678 1.15125 -1.12094 -1.18451 1.10543 1.3041 1.69279 -1.23033 -1.13277 1.4582 1.23267 1.49373 1.11655 -1.22191  1.27E-03 1.29E-03 1.30E-03 1.36E-03 1.38E-03 1.40E-03 1.41E-03 1.41E-03 1.41E-03 1.42E-03 1.44E-03 1.46E-03 1.46E-03 1.47E-03  -1.14317 1.14782 -1.14256 1.18965 1.24676 1.12138 -1.17249 -1.3876 -1.3876 1.15603 1.15697 -1.1612 -1.16748 -1.18  104  Probe Set ID 7899173 8151525 7901895 8118571 8178211 8179495 8153920 7964745 8163948 8151254 8146669 7946569 7930537 8169949 8061685 8041000 7972428 7935425 7987180 7961453 7995258 7948364 8104760 8075390 7913776 7967810 8106429 8156519 8047505  Gene Symbol  Gene Name  RefSeq  P Value  DHDDS PMP2 ATG4C PSMB9 PSMB9 PSMB9 ZNF250 TMBIM4 RBM18 NCOA2 TRIM55 RNF141 TCF7L2 MST4 TM9SF4 GPN1 OXGR1 RRP12 C15orf29 --ZNF267 MPEG1 TARS SEC14L4 IL28RA GOLGA3 AGGF1 MIRLET7A1 FLJ39061  Dehydrodolichyl diphosphate synthase Peripheral myelin protein 2 ATG4 autophagy related 4 homolog C (S. Cerevisiae) Proteasome (prosome, macropain) subunit, beta type, 9 Proteasome (prosome, macropain) subunit, beta type, 9 Proteasome (prosome, macropain) subunit, beta type, 9 Zinc finger protein 250 Transmembrane BAX inhibitor motif containing 4 RNA binding motif protein 18 Nuclear receptor coactivator 2 Tripartite motif-containing 55 Ring finger protein 141 Transcription factor 7-like 2 (T-cell specific) Serine/threonine protein kinase MST4 Transmembrane 9 superfamily protein member 4 GPN-loop gtpase 1 Oxoglutarate (alpha-ketoglutarate) receptor 1 Ribosomal RNA processing 12 homolog (S. Cerevisiae) Chromosome 15 open reading frame 29 --Zinc finger protein 267 Macrophage expressed 1 Threonyl-trna synthetase SEC14-like 4 (S. Cerevisiae) Interleukin 28 receptor, alpha (interferon, lambda receptor) Golgin A3 Angiogenic factor with G patch and FHA domains 1 Microrna let-7a-1 Hypothetical protein FLJ39061  NM_024887 NM_002677 NM_032852 NM_002800 NM_002800 NM_002800 NM_021061 NM_016056 NM_033117 NM_006540 NM_033058 NM_016422 NM_001146274 NM_016542 NM_014742 NM_007266 NM_080818 NM_015179 NM_024713 --NM_003414 NM_001039396 NM_152295 NM_174977 NM_170743 NM_005895 NM_018046 NR_029476 BC118982  1.47E-03 1.57E-03 1.58E-03 1.62E-03 1.62E-03 1.62E-03 1.62E-03 1.66E-03 1.66E-03 1.70E-03 1.70E-03 1.72E-03 1.72E-03 1.79E-03 1.81E-03 1.90E-03 1.90E-03 1.91E-03 1.91E-03 1.94E-03 2.00E-03 2.03E-03 2.04E-03 2.06E-03 2.22E-03 2.25E-03 2.27E-03 2.27E-03 2.29E-03  Fold Change 1.11766 -1.18956 1.32368 1.13513 1.13513 1.13513 1.12214 1.15701 1.24803 -1.10391 -1.12018 1.2994 -1.3209 1.10567 -1.11646 1.12161 -1.24016 -1.17084 1.20996 -1.18735 1.36448 -1.20873 1.14868 -1.17798 -1.1591 -1.12119 1.17784 1.46682 1.30762  105  Probe Set ID 8081953 8042993 7967082 8028213 7929768 7981335 8003075 8022892 7918487 8154283 8055909 8126147 7985695 8139706 8025998 8081343 8169701 8147461 7981290 7983763 8035793 7960553  Gene Symbol  Gene Name  RefSeq  P Value  GTF2E1 CTNNA2 --ZNF568 CUTC HSP90AA1 --ZNF396 DENND2D ----C6orf64 AKAP13 SEC61G ZNF136 RG9MTD1 MCTS1 SDC2 WARS MAPK6 ZNF737 MRPL51  General transcription factor IIE, polypeptide 1, alpha 56 Catenin (cadherin-associated protein), alpha 2 --Zinc finger protein 568 Cutc copper transporter homolog (E. Coli) Heat shock protein 90kda alpha (cytosolic), class A --Zinc finger protein 396 Denn ----Chromosome 6 open reading frame 64 A kinase (PRKA) anchor protein 13 Sec61 gamma subunit Zinc finger protein 136 RNA (guanine-9-) methyltransferase domain containing 1 Malignant T cell amplified sequence 1 Syndecan 2 Tryptophanyl-trna synthetase Mitogen-activated protein kinase 6 Zinc finger protein 737 Mitochondrial ribosomal protein L51  2.31E-03 2.31E-03 2.31E-03 2.33E-03 2.33E-03 2.33E-03 2.35E-03 2.36E-03 2.37E-03 2.37E-03 2.37E-03 2.39E-03 2.42E-03 2.45E-03 2.47E-03 2.47E-03 2.49E-03 2.50E-03 2.51E-03 2.52E-03 2.57E-03 2.58E-03  7912622  LRRC38  Leucine rich repeat containing 38  2.59E-03  -1.11591  8087985 8130032 8162294 7977820 8158976 8101844  GLT8D1 FBXO30 SPTLC1 PRMT5 CEL ADH5  Glycosyltransferase 8 domain containing 1 F-box protein 30 Serine palmitoyltransferase, long chain base subunit 1 Protein arginine methyltransferase 5 Carboxyl ester lipase (bile salt-stimulated lipase) Alcohol dehydrogenase 5 (class III), chi polypeptide  NM_005513 NM_004389 --NM_198539 NM_015960 NM_001017963 --NM_145756 NM_024901 ----BC022007 NM_006738 NM_014302 NM_003437 NM_017819 NM_014060 NM_002998 NM_004184 NM_002748 NM_001159293 NM_016497 ENST000003760 85 NM_001010983 NM_032145 NM_006415 NM_001039619 NM_001807 NM_000671  Fold Change 1.25709 -1.20376 -1.28529 1.29579 1.1695 1.25236 -1.18137 1.21188 1.11399 1.18639 -1.15294 1.27922 -1.17961 1.28001 1.34469 1.19456 1.31653 -1.17103 -1.12132 1.3585 1.64101 1.14919  2.65E-03 2.65E-03 2.65E-03 2.65E-03 2.67E-03 2.68E-03  1.1045 1.21992 1.10764 -1.1109 -1.12395 1.21997  106  Probe Set ID 8116867 8005785 8143247 8135214 8134470 8111552 7955179 8040552 8149942 7998952 8106999 8176576 7900426 7956470 8104746 8096361 8008870 8102162 8028991 7961083 7983606 8130674 8006298 8001185  Gene Symbol  Gene Name  RefSeq  P Value  TMEM14B KSR1 KIAA1549 --TRRAP C5orf33 TUBA1C NCOA1 CCDC25 TIGD7 C5orf27 --SMAP2 MBD6 NPR3 HERC5 TMEM49 INTS12 CYP2S1 CLEC2B EID1 PDE10A RAB11FIP4 DNAJA2  Transmembrane protein 14B Kinase suppressor of ras 1 Kiaa1549 --Transformation/transcription domain-associated protein Chromosome 5 open reading frame 33 Tubulin, alpha 1c Nuclear receptor coactivator 1 Coiled-coil domain containing 25 Tigger transposable element derived 7 Chromosome 5 open reading frame 27 --Small arfgap2 Methyl-cpg binding domain protein 6 Natriuretic peptide receptor C/guanylate cyclase C (atriona) Hect domain and RLD 5 Transmembrane protein 49 Integrator complex subunit 12 Cytochrome P450, family 2, subfamily S, polypeptide 1 C-type lectin domain family 2, member B EP300 interacting inhibitor of differentiation 1 Phosphodiesterase 10A RAB11 family interacting protein 4 (class II) Dnaj (Hsp40) homolog, subfamily A, member 2 V-ets erythroblastosis virus E26 oncogene homolog 2 (avian) Spinster homolog 3 (Drosophila) RB1-inducible coiled-coil 1 Chromosome 17 open reading frame 44 Inm04  NM_030969 NM_014238 NM_020910 --NM_003496 NM_001085411 NM_032704 NM_147223 NM_018246 NM_033208 NR_026936 --NM_022733 NM_052897 NM_000908 NM_016323 NM_030938 NM_020395 NM_030622 NM_005127 NM_014335 NM_006661 NM_032932 NM_005880  2.70E-03 2.72E-03 2.74E-03 2.75E-03 2.76E-03 2.78E-03 2.80E-03 2.82E-03 2.84E-03 2.87E-03 2.89E-03 2.91E-03 2.91E-03 2.93E-03 2.95E-03 3.08E-03 3.09E-03 3.10E-03 3.12E-03 3.13E-03 3.17E-03 3.20E-03 3.20E-03 3.21E-03  Fold Change 1.17658 -1.31962 -1.17018 1.10153 -1.17021 1.26942 -1.17772 -1.1738 1.14967 1.43642 -1.20616 1.31481 -1.24032 -1.243 -1.19369 1.2598 1.13606 1.22349 -1.1428 1.43407 1.207 1.15849 -1.10213 1.17375  NM_005239  3.21E-03  -1.17137  NM_182538 NM_014781 NR_026951 AY194294  3.23E-03 3.23E-03 3.23E-03 3.24E-03  -1.14045 1.2585 1.15166 -1.13747  8068593  ETS2  8003861 8150757 8012416 7907090  SPNS3 RB1CC1 C17orf44 LOC100128751  107  Probe Set ID 8095360 8119974 8000746 8103859 8071107 8009713 8175169 8109350 7951652 7916130 8013331 8135544 7999171 8152133 8175558 8038839 8162669 8038305 8081055 8102817 8151906 7944359 8130765 7972055 7940000 8171747 7972711 8001496 8169294  Gene Symbol  Gene Name  RefSeq  P Value  --SLC29A1 --DCTD SLC25A18 OTOP3 RAP2C SLC36A1 --KTI12 B9D1 FOXP2 --RRM2B SPANXE SIGLEC8 ZNF322A NTF4 CHMP2B ELF2 GDF6 --FAM103A1 KCTD12 OR5AK2 EIF1AX --NUDT21 COL4A5  --Solute carrier family 29 (nucleoside transporters), m --Dcmp deaminase Solute carrier family 25 (mitochondrial carrier), membe Otopetrin 3 RAP2C, member of RAS oncogene family Solute carrier family 36 (proton/amino acid symporter) --KTI12 homolog, chromatin associated (S. Cerevisiae) B9 protein domain 1 Forkhead box P2 --Ribonucleotide reductase M2 B (TP53 inducible) SPANX family, member E Sialic acid binding Ig-like lectin 8 Zinc finger protein 322A Neurotrophin 4 Chromatin modifying protein 2B E74-like factor 2 (ets domain transcription factor) Growth differentiation factor 6 --Family with sequence similarity 103, member A1 Potassium channel tetramerisation domain containing 12 Olfactory receptor, family 5, subfamily AK, member 2 Eukaryotic translation initiation factor 1A, X-linked --Nudix (nucleoside diphosphate linked moiety X)-type motif Collagen, type IV, alpha 5  --NM_001078175 --NM_001012732 NM_031481 NM_178233 NM_021183 NM_078483 --NM_138417 NM_015681 NM_148898 --NM_015713 NM_145665 NM_014442 NM_024639 NM_006179 NM_014043 NM_201999 NM_001001557 --BC112329 NM_138444 NM_001005323 NM_001412 --NM_007006 NM_000495  3.26E-03 3.28E-03 3.29E-03 3.31E-03 3.34E-03 3.34E-03 3.37E-03 3.37E-03 3.39E-03 3.48E-03 3.51E-03 3.51E-03 3.52E-03 3.53E-03 3.58E-03 3.58E-03 3.58E-03 3.60E-03 3.61E-03 3.61E-03 3.65E-03 3.69E-03 3.69E-03 3.71E-03 3.75E-03 3.79E-03 3.81E-03 3.83E-03 3.84E-03  Fold Change 1.21952 -1.21406 -1.72316 1.16184 -1.23484 -1.17842 1.10334 -1.18422 -1.30607 1.23518 -1.17347 1.25093 -1.23007 1.26378 1.11203 -1.4403 1.29728 -1.23748 1.27483 1.13295 -1.23203 1.20255 1.12894 -1.23263 -1.50096 1.30772 1.18899 1.12702 -1.11804  108  Probe Set ID 7960666 8030978 7999936 8113591 7925511 8043480 8059578 8025058  Gene Symbol  Gene Name  RefSeq  P Value  ZNF384 ZNF845 UMOD PGGT1B PLD5 ----TRIP10  Zinc finger protein 384 Zinc finger protein 845 Uromodulin Protein geranylgeranyltransferase type I, beta subunit Phospholipase D family, member 5 ----Thyroid hormone receptor interactor 10 Carbamoyl-phosphate synthetase 2, aspartate transcarbamylase Mediator complex subunit 7 --Family with sequence similarity 127, member B Zinc finger protein 121 Interferon-induced protein with tetratricopeptide repeats Hydroxyacyl-coa dehydrogenase Interleukin 11 Sorting nexin 6 Neuron navigator 1 5-hydroxytryptamine (serotonin) receptor 5A Heat shock transcription factor family member 5 --TRAF-interacting protein with forkhead-associated domain --Histone cluster 1, h2ai Chemokine (C-C motif) ligand 27 Olfactory receptor, family 2, subfamily T, member 33 Hypothetical LOC390414 -----  NM_133476 NM_138374 NM_003361 NM_005023 NM_152666 ----NM_004240  3.84E-03 3.85E-03 3.85E-03 3.87E-03 3.90E-03 3.92E-03 3.93E-03 3.94E-03  Fold Change -1.10853 1.88412 -1.11571 1.24213 -1.32485 1.10136 -1.7047 -1.10619  NM_004341  3.94E-03  -1.16946  NM_004270 --NM_001078172 NM_001008727 NM_012420 NM_005327 NM_000641 NM_021249 NM_020443 NM_024012 NM_001080439 --NM_052864 --NM_003509 NM_006664 NM_001004695 AK094743 -----  3.95E-03 3.95E-03 3.96E-03 3.96E-03 3.98E-03 3.99E-03 3.99E-03 3.99E-03 4.00E-03 4.13E-03 4.16E-03 4.17E-03 4.21E-03 4.23E-03 4.24E-03 4.27E-03 4.36E-03 4.37E-03 4.37E-03 4.38E-03  1.32722 -1.15156 -1.15817 1.23886 1.42628 1.1301 -1.13164 1.2031 -1.12593 -1.10157 1.18222 -1.13458 1.24717 -1.58565 1.19217 -1.20421 -1.14785 1.12186 -1.19685 -1.27925  8040843  CAD  8115476 8080853 8175302 8033789 7929072 8096753 8039484 7978570 7908694 8137517 8017010 8023591 8102362 8150689 8117580 8160870 7925741 7932881 7897293 8102936  MED7 --FAM127B ZNF121 IFIT5 HADH IL11 SNX6 NAV1 HTR5A HSF5 --TIFA HIST1H2AI CCL27 OR2T33 LOC390414 -----  109  Probe Set ID 8088979 7964250 8071877 7931348 7986010 8018972 8042086 8121861 8102775 8041122 8176698 8023703 8094609 8126428 7951807  Gene Symbol  Gene Name  RefSeq  P Value  VGLL3 PTGES3 POM121L9P FOXI2 IQGAP1 TIMP2 VRK2 NCOA7 --PPP1CB CYorf15A C18orf20 FAM114A1 TRERF1 CADM1  Vestigial like 3 (Drosophila) Prostaglandin E synthase 3 (cytosolic) POM121 membrane glycoprotein-like 9 (rat) pseudogene Forkhead box I2 IQ motif containing gtpase activating protein 1 TIMP metallopeptidase inhibitor 2 Vaccinia related kinase 2 Nuclear receptor coactivator 7 --Protein phosphatase 1, catalytic subunit, beta isozyme Chromosome Y open reading frame 15A Chromosome 18 open reading frame 20 Family with sequence similarity 114, member A1 Transcriptional regulating factor 1 Cell adhesion molecule 1 Aminoadipate-semialdehyde dehydrogenasephosphopantethe Trna splicing endonuclease 15 homolog (S. Cerevisiae) --Potassium large conductance calcium-activated channel Glucuronidase, beta-like 2 --Zinc finger protein 135 Polymerase (DNA directed), beta --Non-protein coding RNA 173 Kelch-like 9 (Drosophila) Hydroxy-delta-5-steroid dehydrogenase, 3 beta- and steroi --Growth arrest-specific 2 like 3  NM_016206 NM_006601 NR_003714 NM_207426 NM_003870 AK057217 NM_006296 NM_181782 --NM_002709 NM_001005852 BC029565 NM_138389 NM_033502 NM_014333  4.46E-03 4.47E-03 4.52E-03 4.54E-03 4.56E-03 4.58E-03 4.60E-03 4.62E-03 4.68E-03 4.69E-03 4.69E-03 4.71E-03 4.73E-03 4.75E-03 4.76E-03  Fold Change 1.14327 1.27373 1.17563 -1.36326 -1.1765 -1.29485 1.37976 1.23347 -1.17632 1.19299 1.30982 -1.34055 -1.24832 -1.11786 1.2536  NM_015423  4.77E-03  1.23434  NM_052965 --NM_004137 NR_003660 --NM_003436 NM_002690 --NR_027345 NM_018847 NM_000862 --NM_174942  4.82E-03 4.84E-03 4.87E-03 4.89E-03 4.92E-03 4.93E-03 4.96E-03 4.96E-03 4.96E-03 5.00E-03 5.00E-03 5.01E-03 5.05E-03  1.19128 -1.24861 -1.1305 1.18323 -1.21063 1.11346 1.18361 -1.11715 -1.3502 1.21661 -1.18104 -1.11461 -1.19668  7943552  AASDHPPT  7908147 8177044 8115756 8127364 8174494 8031857 8146198 7938561 7959016 8160405 7904421 7899849 7957850  TSEN15 --KCNMB1 GUSBL2 --ZNF135 POLB --NCRNA00173 KLHL9 HSD3B1 --GAS2L3  110  Probe Set ID 8101648 8127425 7910146 8117522 8120194 8013529 8137081 7998367 8104449 8178771 8011131 8094974 8093943 8016366 8120378 8116996 8024584 8099912 8032094 8104838 7995252 8116113  Gene Symbol  Gene Name  RefSeq  P Value  HSD17B11 LMBRD1 PSEN2 ABT1 TFAP2B ----RPUSD1 CCT5 AGER RILP OCIAD1 LOC93622 MRPL10 KIAA1586 --NCLN C4orf34 LPPR3 DNAJC21 ZNF720 FAM193B  Hydroxysteroid (17-beta) dehydrogenase 11 LMBR1 domain containing 1 Presenilin 2 (Alzheimer disease 4) Activator of basal transcription 1 Transcription factor AP-2 beta (activating enhancer binding ----RNA pseudouridylate synthase domain containing 1 Chaperonin containing TCP1, subunit 5 (epsilon) Advanced glycosylation end product-specific receptor Rab interacting lysosomal protein OCIA domain containing 1 Hypothetical LOC93622 Mitochondrial ribosomal protein L10 Kiaa1586 --Nicalin homolog (zebrafish) Chromosome 4 open reading frame 34 Lipid phosphate phosphatase-related protein type 3 Dnaj (Hsp40) homolog, subfamily C, member 21 Zinc finger protein 720 Family with sequence similarity 193, member B Signal peptidase complex subunit 3 homolog (S. Cerevisiae) Tetraspanin 2 Glia maturation factor, beta Serine/threonine-protein kinase NIM1 --Fucose-1-phosphate guanylyltransferase Dedicator of cytokinesis 8  NM_016245 NM_018368 NM_000447 NM_013375 NM_003221 ----NM_058192 NM_012073 NM_001136 NM_031430 NM_017830 NR_015433 NM_145255 NM_020931 --NM_020170 BC008502 NM_024888 NM_194283 NM_001130913 NR_024019  5.06E-03 5.07E-03 5.10E-03 5.12E-03 5.13E-03 5.16E-03 5.16E-03 5.17E-03 5.17E-03 5.18E-03 5.20E-03 5.20E-03 5.22E-03 5.23E-03 5.27E-03 5.31E-03 5.33E-03 5.37E-03 5.42E-03 5.43E-03 5.45E-03 5.47E-03  Fold Change 1.17003 1.32028 -1.14841 1.13459 -1.29097 1.56883 1.17944 -1.16696 1.11649 -1.17383 -1.2329 1.14929 1.20837 1.21708 1.37772 -1.28381 -1.13934 1.18735 -1.167 1.14285 1.32296 -1.16049  NM_021928  5.47E-03  1.26024  NM_005725 NM_004124 NM_153361 --NM_003838 NM_203447  5.48E-03 5.51E-03 5.51E-03 5.51E-03 5.54E-03 5.56E-03  1.14187 1.49342 1.15908 -1.37094 1.35375 -1.18992  8098414  SPCS3  7918857 7979260 8105146 8172252 7902308 8153959  TSPAN2 GMFB MGC42105 --FPGT DOCK8  111  Probe Set ID 7911767 7936529 8020382 8108217 8058182 8073309 8083808 8090448 8174527 8087250 8096635 7899898 8074748  Gene Symbol  Gene Name  RefSeq  P Value  MMEL1 KIAA1598 ROCK1 TGFBI FAM126B LOC100288034 LRRIQ4 RUVBL1 CAPN6 MIR425 NFKB1 HMGB4 PI4KAP2  NM_033467 NM_001127211 NM_005406 NM_000358 NM_173822 XM_002346783 NM_001080460 NM_003707 NM_014289 NR_029948 NM_003998 NM_145205 NR_003700  5.59E-03 5.63E-03 5.65E-03 5.70E-03 5.71E-03 5.71E-03 5.73E-03 5.76E-03 5.78E-03 5.78E-03 5.81E-03 5.81E-03 5.83E-03  Fold Change -1.10775 -1.40202 -1.24697 -1.3237 1.19851 -1.29482 -1.21301 1.10492 -1.24495 -1.1211 -1.16142 -1.13529 -1.12807  NM_014752  5.83E-03  1.25436  NM_173595 NM_017824 NM_000340 NM_002562 NM_004244 NM_006837 NM_006387 NM_030761 NM_001008271 NM_001008271 NM_052904 NM_001017926 NM_002583 ENST000004518 89  5.86E-03 5.89E-03 5.89E-03 5.90E-03 5.91E-03 5.93E-03 5.94E-03 5.97E-03 6.02E-03 6.02E-03 6.07E-03 6.09E-03 6.14E-03  -1.15954 1.15729 1.30066 -1.36582 -1.53933 1.26846 -1.18384 -1.12117 -1.22332 -1.22332 1.12749 1.1922 1.23685  6.17E-03  -1.15013  7942553  SPCS2  7964033 7929247 8092083 7959251 7960794 8151136 8035156 7913547 8148796 8148821 8121193 8152656 7965112  ANKRD52 5-Mar SLC2A2 P2RX7 CD163 COPS5 CHERP WNT4 SCXA SCXA KLHL32 ZHX1 PAWR  Membrane metallo-endopeptidase-like 1 Kiaa1598 Rho-associated, coiled-coil containing protein kinase 1 Transforming growth factor, beta-induced, 68kda Family with sequence similarity 126, member B Similar to FKSG62 Leucine-rich repeats and IQ motif containing 4 Ruvb-like 1 (E. Coli) Calpain 6 Microrna 425 Nuclear factor of kappa light polypeptide gene enhancer High-mobility group box 4 Phosphatidylinositol 4-kinase, catalytic, alpha pseudoge Signal peptidase complex subunit 2 homolog (S. Cerevisiae) Ankyrin repeat domain 52 Membrane-associated ring finger (C3HC4) 5 Solute carrier family 2 (facilitated glucose transporter) Purinergic receptor P2X, ligand-gated ion channel, 7 CD163 molecule COP9 constitutive photomorphogenic homolog subunit 5 Calcium homeostasis endoplasmic reticulum protein Wingless-type MMTV integration site family, member 4 Scleraxis homolog A (mouse) Scleraxis homolog A (mouse) Kelch-like 32 (Drosophila) Zinc fingers and homeoboxes 1 PRKC, apoptosis, WT1, regulator  7932552  PRO3077  Hypothetical protein PRO3077  112  Probe Set ID 8157608 8039680 8061426 8049888 8054092 7942409 7949916 8156450 7917904 7999317 7911376  Gene Symbol  Gene Name  RefSeq  P Value  --ZNF671 --ATG4B TMEM131 P2RY6 CHKA --LOC100286918 TMEM186 HES4  --NM_024833 --NM_013325 NM_015348 NM_176796 NM_001277 --XM_002342095 NM_015421 NM_001142467  6.20E-03 6.21E-03 6.21E-03 6.23E-03 6.27E-03 6.27E-03 6.30E-03 6.32E-03 6.34E-03 6.38E-03 6.41E-03  Fold Change -1.15644 1.15837 -1.20461 -1.11258 -1.12901 -1.27005 -1.12516 1.168 1.17976 1.26018 -1.16515  NR_027405  6.41E-03  1.2007  NM_001001342 NM_019593 NM_152457 NM_152478 CR627161 ENST000003336 66 NM_014793 NM_053045 NM_030755 BC127710 NM_020141 NM_020141 NM_004872 NM_024639 BC024237 NM_032445  6.41E-03 6.42E-03 6.42E-03 6.45E-03 6.45E-03  1.14561 1.20813 1.14856 1.3487 1.21593  6.49E-03  -1.10069  6.51E-03 6.51E-03 6.52E-03 6.55E-03 6.56E-03 6.56E-03 6.56E-03 6.56E-03 6.59E-03 6.60E-03  1.21419 1.17362 1.30075 1.16694 1.19438 1.19438 1.16785 1.30038 1.15679 -1.13047  8042830  MTHFD2  7935746 8064868 7998978 8031640 7960381  BLOC1S2 GPCPD1 ZNF597 ZNF583 EFCAB4B  --Zinc finger protein 671 --ATG4 autophagy related 4 homolog B (S. Cerevisiae) Transmembrane protein 131 Pyrimidinergic receptor P2Y, G-protein coupled, 6 Choline kinase alpha --Similar to NADH dehydrogenase [ubiquinone] iron Transmembrane protein 186 Hairy and enhancer of split 4 (Drosophila) Methylenetetrahydrofolate dehydrogenase (NADP+ dependent) Biogenesis of lysosomal organelles complex-1, subunit Glycerophosphocholine phosphodiesterase GDE1 homolog Zinc finger protein 597 Zinc finger protein 583 EF-hand calcium binding domain 4B  7997832  FLJ40448  Hypothetical protein FLJ40448  7988077 8165642 7974303 7920487 7903586 8039905 7916372 8124459 8073578 7989887  LCMT2 TMEM203 TMX1 C1orf189 TMEM167B TMEM167B TMEM59 ZNF322A C22orf32 MEGF11  Leucine carboxyl methyltransferase 2 Transmembrane protein 203 Thioredoxin-related transmembrane protein 1 Chromosome 1 open reading frame 189 Transmembrane protein 167B Transmembrane protein 167B Transmembrane protein 59 Zinc finger protein 322A Chromosome 22 open reading frame 32 Multiple EGF-like-domains 11  113  Probe Set ID 8053666  Gene Symbol  Gene Name  RefSeq  P Value  ---  ---  6.61E-03  Fold Change -1.16697  NM_002492  6.61E-03  1.19391  NM_016586 --NM_152319 NM_194318 NM_004063 NM_030960 --NM_014608  6.64E-03 6.66E-03 6.66E-03 6.67E-03 6.67E-03 6.70E-03 6.71E-03 6.71E-03  1.24038 -1.10451 -1.15551 1.14704 -1.20232 -1.1173 -1.11767 -1.33191  NM_006445  6.72E-03  -1.17393  NM_198273 NM_001143757 ----NM_017910 NM_003445 NM_004077 --NM_016093 --NM_000044 NM_018965 NM_014713 NM_152266 ENST000003422 24 ---  6.75E-03 6.77E-03 6.77E-03 6.78E-03 6.89E-03 6.90E-03 6.91E-03 6.91E-03 6.92E-03 6.92E-03 6.97E-03 7.00E-03 7.01E-03 7.05E-03  1.39831 -1.1114 -1.24611 1.13931 1.39182 1.29108 -1.20299 -1.18574 1.23744 1.26108 -1.20819 -1.12687 1.12742 1.11488  7.07E-03  -1.33448  7.08E-03  -1.13436  8084092  NDUFB5  7978666 7948303 7955119 7968370 8151795 8121066 7961067 7981824  MBIP --C12orf54 B3GALTL CDH17 SPACA1 --CYFIP1  8011141  PRPF8  8113064 7931455 8151250 8088846 8051226 8029340 7964064 7902493 8110018 8096957 8167998 8126279 8050548 8027510  LYSMD3 LRRC27 ----TRMT61B ZNF155 CS --RPL26L1 --AR TREM2 LAPTM4A C19orf40  --NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 5, 16k MAP3K12 binding inhibitory protein 1 --Chromosome 12 open reading frame 54 Beta 1,3-galactosyltransferase-like Cadherin 17, LI cadherin (liver-intestine) Sperm acrosome associated 1 --Cytoplasmic FMR1 interacting protein 1 PRP8 pre-mrna processing factor 8 homolog (S. Cerevisiae) Lysm, putative peptidoglycan-binding, domain containing 3 Leucine rich repeat containing 27 ----Trna methyltransferase 61 homolog B (S. Cerevisiae) Zinc finger protein 155 Citrate synthase --Ribosomal protein L26-like 1 --Androgen receptor Triggering receptor expressed on myeloid cells 2 Lysosomal protein transmembrane 4 alpha Chromosome 19 open reading frame 40  8022426  LOC646359  Similar to telomeric repeat binding factor (NIMA  7944162  ---  ---  114  Probe Set ID 8018731 8103520 7964701 7902911 8177068 7903203 7999304 8131000 7916562 8110618 8112807 7907171 8155550 7954029 8163257 8124484 8081820 8086607 8131867 8106107 8106702 8068168 8001385 8084630 8096081 7970655 8178095 8179331 7938263  Gene Symbol  Gene Name  RefSeq  P Value  RHBDF2 TRIM61 GNS ----SNX7 FAM86A HEATR2 HNRNPA1 ARPP19 ARSB BLZF1 LOC554249 CDKN1B LPAR1 HIST1H2BJ --LTF --PTCD2 ZCCHC9 SOD1 ----ENOPH1 MTMR6 C2 C2 EIF3F  Rhomboid 5 homolog 2 (Drosophila) Tripartite motif-containing 61 Glucosamine (N-acetyl)-6-sulfatase ----Sorting nexin 7 Family with sequence similarity 86, member A HEAT repeat containing 2 Heterogeneous nuclear ribonucleoprotein A1 Camp-regulated phosphoprotein, 19kda Arylsulfatase B Basic leucine zipper nuclear factor 1 Hypothetical LOC554249 Cyclin-dependent kinase inhibitor 1B (p27, Kip1) Lysophosphatidic acid receptor 1 Histone cluster 1, h2bj --Lactotransferrin --Pentatricopeptide repeat domain 2 Zinc finger, CCHC domain containing 9 Superoxide dismutase 1, soluble ----Enolase-phosphatase 1 Myotubularin related protein 6 Complement component 2 Complement component 2 Eukaryotic translation initiation factor 3, subunit F  NM_024599 NM_001012414 NM_002076 ----NM_015976 NM_201400 NM_017802 NM_002136 NM_006628 NM_000046 NM_003666 AK292642 NM_004064 NM_057159 NM_021058 --NM_002343 --NM_024754 NM_032280 NM_000454 ----NM_021204 NM_004685 NM_000063 NM_000063 NM_003754  7.08E-03 7.13E-03 7.14E-03 7.15E-03 7.21E-03 7.22E-03 7.25E-03 7.28E-03 7.35E-03 7.36E-03 7.37E-03 7.40E-03 7.42E-03 7.49E-03 7.50E-03 7.50E-03 7.58E-03 7.58E-03 7.60E-03 7.61E-03 7.62E-03 7.63E-03 7.64E-03 7.65E-03 7.69E-03 7.69E-03 7.70E-03 7.70E-03 7.73E-03  Fold Change -1.14046 1.18905 -1.27976 -1.2657 -1.25224 -1.17834 -1.11058 -1.1045 1.13724 1.10296 -1.1574 1.2842 1.1044 1.19399 -1.18531 -1.1749 -1.24684 -1.26088 -1.23084 1.28064 1.16093 1.14687 -1.15954 -1.17809 1.15722 1.24128 -1.16351 -1.16351 1.14948  115  Probe Set ID 7979455 7933084 8096251 8077528 7945859 8151234 8119034 7943519 8100756 7899604 8016232 8173745 8102037 7971950 8069644 8049534 7920165 7977435 7989953 8155453 8161375 7900413 8108873 8141708 7973754 8146894 8029399 8038989 8089128  Gene Symbol  Gene Name  RefSeq  P Value  RTN1 NAMPT NUDT9 SETD5 MRGPRE SLCO5A1 BRPF3 ----ZCCHC17 SH3D20 CYSLTR1 --DACH1 APP LRRFIP1 FLG --AAGAB LOC100289385 LOC100289385 ZMPSTE24 ARHGAP26 CLDN15 ----ZNF226 ZNF600  Reticulon 1 Nicotinamide phosphoribosyltransferase Nudix (nucleoside diphosphate linked moiety X)-type motif SET domain containing 5 MAS-related GPR, member E Solute carrier organic anion transporter family, member 5 Bromodomain and PHD finger containing, 3 ----Zinc finger, CCHC domain containing 17 SH3 domain containing 20 Cysteinyl leukotriene receptor 1 --Dachshund homolog 1 (Drosophila) Amyloid beta (A4) precursor protein Leucine rich repeat (in FLII) interacting protein 1 Filaggrin --Alpha- and gamma-adaptin binding protein Hypothetical protein LOC100289385 Hypothetical protein LOC100289385 Zinc metallopeptidase (STE24 homolog, S. Cerevisiae) Rho gtpase activating protein 26 Claudin 15 ----Zinc finger protein 226 Zinc finger protein 600 Translocase of outer mitochondrial membrane 70 homolog A  NM_021136 NM_005746 NM_024047 NM_001080517 NM_001039165 AF205075 NM_015695 ----NM_016505 NM_174919 NM_006639 --NM_080759 NM_000484 NM_001137550 NM_002016 --NM_024666 XM_002342912 XM_002342912 NM_005857 NM_015071 NM_014343 ----NM_001032372 NM_198457  7.75E-03 7.76E-03 7.77E-03 7.79E-03 7.80E-03 7.80E-03 7.84E-03 7.90E-03 7.91E-03 7.93E-03 7.94E-03 7.95E-03 7.98E-03 7.98E-03 7.99E-03 7.99E-03 7.99E-03 8.00E-03 8.02E-03 8.08E-03 8.08E-03 8.08E-03 8.09E-03 8.13E-03 8.14E-03 8.14E-03 8.17E-03 8.20E-03  Fold Change -1.37064 1.19403 1.17498 -1.12273 -1.2183 -1.28021 -1.1626 1.1165 -1.26327 1.15967 -1.19651 1.21873 1.27825 -1.17053 -1.3248 -1.2279 -1.11366 1.27651 1.15777 1.31562 1.31562 1.2369 -1.15711 -1.15809 -1.14992 1.13833 1.40976 1.2762  NM_014820  8.22E-03  1.10493  TOMM70A  116  Probe Set ID 8006345 8037103 8099897 7925128 8061445 8091385 7990848 7925691 8046997 7907353 7911199  Gene Symbol  Gene Name  RefSeq  P Value  RHOT1 GRIK5 UGDH ----CP TMC3 ZNF124 ASNSD1 METTL13 C1orf150  NM_001033568 NM_002088 NM_003359 ----NM_000096 NM_001080532 NM_003431 NM_019048 NM_015935 NM_145278  8.23E-03 8.23E-03 8.24E-03 8.28E-03 8.32E-03 8.32E-03 8.38E-03 8.39E-03 8.40E-03 8.41E-03 8.45E-03  Fold Change 1.24848 -1.2738 1.27072 -1.20397 -1.15966 1.33097 -1.10521 1.29967 1.25924 1.12419 1.16755  NM_004549  8.47E-03  1.22001  NM_153827 NM_002036 NM_001168357 ENST000003216 88 NM_203307 NM_078474 NM_003853  8.47E-03 8.51E-03 8.52E-03  -1.19442 -1.22871 -1.10783  8.54E-03  1.27053  8.54E-03 8.56E-03 8.61E-03  1.35424 1.17958 1.2754  NM_006496  8.62E-03  1.2552  NM_020197 NM_015932 NR_026825 NM_015089 NM_002312 NM_003704 BC086877  8.62E-03 8.65E-03 8.68E-03 8.68E-03 8.71E-03 8.72E-03 8.72E-03  1.18907 1.16822 1.32673 -1.11298 1.28653 -1.1764 -1.24198  7950644  NDUFC2  8003991 7906435 8126784  MINK1 DARC PLA2G7  Ras homolog gene family, member T1 Glutamate receptor, ionotropic, kainate 5 UDP-glucose 6-dehydrogenase ----Ceruloplasmin (ferroxidase) Transmembrane channel-like 3 Zinc finger protein 124 Asparagine synthetase domain containing 1 Methyltransferase like 13 Chromosome 1 open reading frame 150 NADH dehydrogenase (ubiquinone) 1, subcomplex unknown, 2 Misshapen-like kinase 1 (zebrafish) Duffy blood group, chemokine receptor Phospholipase A2, group VII (platelet-activating factor  7956005  OR2AP1  Olfactory receptor, family 2, subfamily AP, member  8039013 7991630 8044049  ZNF321 TM2D3 IL18RAP  7903703  GNAI3  7909689 7968297 7964733 8119722 7972737 8093601 8162191  SMYD2 POMP RPSAP52 CUL9 LIG4 FAM193A LOC392364  Zinc finger protein 321 TM2 domain containing 3 Interleukin 18 receptor accessory protein Guanine nucleotide binding protein (G protein), alpha inhibitor SET and MYND domain containing 2 Proteasome maturation protein Ribosomal protein SA pseudogene 52 Cullin 9 Ligase IV, DNA, ATP-dependent Family with sequence similarity 193, member A Chromosome 15 open reading frame 2 pseudogene  117  Probe Set ID 8152867 8035304 7901867 8047286 7935968 8102006 8094378 7911676 8096461 8055862 8011542 7996377 8046003 8026007 8025103 8128626 8024019 7989315 8137264 8135909 7945420 8091698 8076339 7964832  Gene Symbol  Gene Name  RefSeq  P Value  ASAP1 BST2 USP1 --LDB1 MANBA PI4K2B --ATOH1 ARL5A ZZEF1 CES8 GCA ZNF791 EMR1 PDSS2 PTBP1 GTF2A2 TMEM176A LEP RNH1 SHOX2 PHF5A ---  Arfgap with SH3 domain, ankyrin repeat and PH domain 1 Bone marrow stromal cell antigen 2 Ubiquitin specific peptidase 1 --LIM domain binding 1 Mannosidase, beta A, lysosomal Phosphatidylinositol 4-kinase type 2 beta --Atonal homolog 1 (Drosophila) ADP-ribosylation factor-like 5A Zinc finger, ZZ-type with EF-hand domain 1 Carboxylesterase 8 (putative) Grancalcin, EF-hand calcium binding protein Zinc finger protein 791 Egf-like module containing, mucin-like, hormone receptor-li Prenyl (decaprenyl) diphosphate synthase, subunit 2 Polypyrimidine tract binding protein 1 General transcription factor IIA, 2, 12kda Transmembrane protein 176A Leptin Ribonuclease/angiogenin inhibitor 1 Short stature homeobox 2 PHD finger protein 5A --SWI/SNF related, matrix associated, actin dependent regulator Fumarylacetoacetate hydrolase (fumarylacetoacetase) BCL2-associated athanogene 3 -----  NM_018482 NM_004335 NM_003368 --NM_003893 NM_005908 NM_018323 --NM_005172 NM_012097 NM_015113 NM_173815 NM_012198 NM_153358 NM_001974 NM_020381 NM_002819 NM_004492 NM_018487 NM_000230 NM_002939 NM_003030 NM_032758 ---  8.80E-03 8.82E-03 8.82E-03 8.83E-03 8.84E-03 8.88E-03 8.91E-03 8.92E-03 8.92E-03 8.96E-03 8.96E-03 8.97E-03 8.98E-03 8.98E-03 9.01E-03 9.03E-03 9.04E-03 9.06E-03 9.06E-03 9.08E-03 9.08E-03 9.08E-03 9.08E-03 9.08E-03  Fold Change -1.32645 1.16059 1.39398 -1.3013 -1.14475 -1.19819 1.19533 -1.29941 -1.11833 1.22757 -1.17171 -1.13189 1.26908 1.22662 -1.47335 1.27126 -1.11968 1.26504 -1.35027 -1.15852 -1.11763 -1.18357 1.21107 1.1847  NM_003075  9.14E-03  -1.14109  NM_000137 NM_004281 -----  9.16E-03 9.17E-03 9.18E-03 9.20E-03  -1.21621 -1.21844 -1.19381 1.10952  7963988  SMARCC2  7985268 7930921 8102210 8037535  FAH BAG3 -----  118  Probe Set ID 7927505 8122637 8003156 8148265 8104443 7924817 7985587 7959995 8151788 8043487 7904965 8045919 7945182 8022295 8104625 8131600 8054075 7976876 8059648 7978558 7961363 7932796 8022118 8163729 8036956 8066567  Gene Symbol  Gene Name  RefSeq  P Value  C10orf53 SASH1 --RNF139 --PRO2012 SCAND2 EP400 RBM12B FKSG73 PDE4DIP 7-Mar APLP2 FAM38B --TSPAN13 UBTFL1 DYNC1H1 --EAPP --SVIL EPB41L3 MIR147 C19orf54 ---  Chromosome 10 open reading frame 53 SAM and SH3 domain containing 1 --Ring finger protein 139 --Hypothetical protein PRO2012 SCAN domain containing 2 pseudogene E1A binding protein p400 RNA binding motif protein 12B ARP3 actin-related protein 3 homolog B pseudogene Phosphodiesterase 4D interacting protein Membrane-associated ring finger (C3HC4) 7 Amyloid beta (A4) precursor-like protein 2 Family with sequence similarity 38, member B --Tetraspanin 13 Upstream binding transcription factor, RNA polymerase Dynein, cytoplasmic 1, heavy chain 1 --E2F-associated phosphoprotein --Supervillin Erythrocyte membrane protein band 4.1-like 3 Microrna 147 Chromosome 19 open reading frame 54 --UDP-glcnac:betagal beta-1,3-Nacetylglucosaminyltransferase Synovial sarcoma translocation gene on chromosome 18like  NM_182554 NM_015278 --NM_007218 --BC019830 NR_004859 NM_015409 NM_203390 NR_027714 AB042555 NM_022826 NM_001642 NM_022068 --NM_014399 NM_001143975 NM_001376 --NM_018453 --NM_021738 NM_012307 NR_029604 NM_198476 ---  9.21E-03 9.25E-03 9.27E-03 9.27E-03 9.28E-03 9.28E-03 9.30E-03 9.38E-03 9.40E-03 9.41E-03 9.42E-03 9.45E-03 9.48E-03 9.48E-03 9.49E-03 9.50E-03 9.50E-03 9.53E-03 9.53E-03 9.54E-03 9.58E-03 9.59E-03 9.60E-03 9.60E-03 9.61E-03 9.63E-03  Fold Change -1.13661 -1.16624 1.23751 1.20819 -1.207 1.27355 1.24522 -1.18418 1.4164 -1.13056 1.31278 1.26964 -1.12202 1.17219 1.24254 1.20646 -1.15066 -1.21384 1.31455 1.37411 -1.21749 -1.13936 -1.23694 -1.18801 -1.13823 1.19606  AK126018  9.64E-03  -1.15365  NM_016305  9.69E-03  1.15093  8019559  B3GNTL1  8079074  SS18L2  119  Probe Set ID 8130211 7901982 8054943 7957245 8019149 8080973 7992692 8014241 8120943 7897288 7913814  Gene Symbol  Gene Name  RefSeq  P Value  SYNE1 UBE2U --GLIPR1L1 SLC38A10 PPP4R2 SRRM2 SLFN12 CYB5R4 ESPN SYF2  Spectrin repeat containing, nuclear envelope 1 Ubiquitin-conjugating enzyme E2U (putative) --GLI pathogenesis-related 1 like 1 Solute carrier family 38, member 10 Protein phosphatase 4, regulatory subunit 2 Serine/arginine repetitive matrix 2 Schlafen family member 12 Cytochrome b5 reductase 4 Espin SYF2 homolog, RNA splicing factor (S. Cerevisiae) Potassium inwardly-rectifying channel, subfamily J, member 14 Zinc finger protein 91 Zinc finger protein 761 ---  NM_182961 NM_152489 --NM_152779 NM_001037984 NM_174907 NM_016333 NM_018042 NM_016230 NM_031475 NM_015484  9.75E-03 9.77E-03 9.80E-03 9.84E-03 9.85E-03 9.85E-03 9.85E-03 9.85E-03 9.91E-03 9.91E-03 9.92E-03  Fold Change -1.13687 -1.20212 -1.22989 1.20256 -1.16543 1.26828 -1.22791 1.28066 1.20619 -1.2696 1.18457  NM_170720  9.94E-03  -1.19379  NM_003430 NM_001008401 ---  9.97E-03 9.99E-03 9.99E-03  1.37192 1.44775 1.28596  8030044  KCNJ14  8035842 8030993 8173609  ZNF91 ZNF761 ---  120  Appendix 3 — Down-Regulated Gene Sets (FDR≤0.25)  Gene Set  Size  FDR  NAKAJIMA_MCSMBP_EOS  28  3.82E-02  PASSERINI_INFLAMMATION  24  6.44E-02  ACTIN_CYTOSKELETON_ORGANIZATION_AND_ BIOGENESIS  100  8.59E-02  ACTIN_FILAMENT_BINDING  23  8.62E-02  ROSS_MLL_FUSION  70  8.95E-02  RAS_GUANYL_NUCLEOTIDE_EXCHANGE_FACTOR_ ACTIVITY  17  8.97E-02  ROSS_CBF_MYH  46  9.01E-02  INTEGRIN_MEDIATED_CELL_ADHESION_KEGG  83  9.11E-02  SCHURINGA_STAT5A_UP  16  9.15E-02  HBX_HCC_DN  22  9.23E-02  REGULATION_OF_SMALL_GTPASE_MEDIATED_SIGNAL_ TRANSDUCTION  22  9.29E-02  HSA04670_LEUKOCYTE_TRANSENDOTHELIAL_MIGRATION  98  9.57E-02  STEMCELL_COMMON_DN  55  9.68E-02  ACTIN_FILAMENT_BASED_PROCESS  109  9.71E-02  REGULATION_OF_RAS_PROTEIN_SIGNAL_ TRANSDUCTION  18  9.92E-02  YAGI_AML_PROGNOSIS  29  1.04E-01  GLUTATHIONE_METABOLISM  28  1.07E-01  HSA04330_NOTCH_SIGNALING_PATHWAY  38  1.13E-01  HEARTFAILURE_ATRIA_UP  23  1.14E-01  TGF_BETA_SIGNALING_PATHWAY  47  1.17E-01  INTEGRIN_COMPLEX  18  1.42E-01  JECHLINGER_EMT_DN  38  1.77E-01  ETSPATHWAY  17  1.80E-01  HEMATOPOESIS_RELATED_TRANSCRIPTION_FACTORS  78  1.81E-01  HSA01510_NEURODEGENERATIVE_DISEASES  36  1.81E-01  CORTICAL_CYTOSKELETON  19  1.82E-01  CELL_ADHESION_RECEPTOR_ACTIVITY  32  1.82E-01  121  Gene Set  Size  FDR  ATPASE_ACTIVITY__COUPLED_TO_TRANSMEMBRANE_ MOVEMENT_OF_IONS__PHOSPHORYLATIVE_MECHANISM  19  1.83E-01  RUFFLE  28  1.84E-01  HSA00480_GLUTATHIONE_METABOLISM  34  1.85E-01  PROTEASE_INHIBITOR_ACTIVITY  41  1.86E-01  CARDIACEGFPATHWAY  16  1.86E-01  GUANYL_NUCLEOTIDE_EXCHANGE_FACTOR_ACTIVITY  41  1.87E-01  CELL_CORTEX_PART  22  1.87E-01  BRG1_ALAB_UP  39  1.88E-01  AGED_MOUSE_CEREBELLUM_UP  57  1.89E-01  ABBUD_LIF_DN  23  1.89E-01  HSA04520_ADHERENS_JUNCTION  74  1.94E-01  CYTOSKELETAL_PROTEIN_BINDING  145  1.95E-01  CELL_JUNCTION  75  1.97E-01  CELL_CORTEX  35  1.99E-01  HSA04810_REGULATION_OF_ACTIN_CYTOSKELETON  186  2.00E-01  BRENTANI_CYTOSKELETON  19  2.01E-01  ACTIN_BINDING  68  2.03E-01  HSA04630_JAK_STAT_SIGNALING_PATHWAY  140  2.04E-01  PROTEIN_DOMAIN_SPECIFIC_BINDING  60  2.04E-01  TGFBETA_ALL_UP  77  2.14E-01  ACTIN_CYTOSKELETON  119  2.15E-01  HSA01032_GLYCAN_STRUCTURES_DEGRADATION  28  2.37E-01  UCALPAINPATHWAY  15  2.41E-01  EMT_DN  51  2.49E-01  122  Appendix 4 — Up-Regulated Gene Sets (FDR≤0.25) Gene Set  Size  FDR  PROTEIN_AMINO_ACID_LIPIDATION  22  1.20E-02  LIPOPROTEIN_BIOSYNTHETIC_PROCESS  24  1.20E-02  TRANSCRIPTION_FROM_RNA_POLYMERASE_III_ PROMOTER  16  1.64E-02  HSA03022_BASAL_TRANSCRIPTION_FACTORS  29  1.75E-02  LIPOPROTEIN_METABOLIC_PROCESS  31  1.93E-02  IFN_BETA_UP  61  4.04E-02  CELLULAR_RESPIRATION  18  4.47E-02  NF90_UP  22  5.21E-02  HSA03050_PROTEASOME  22  7.09E-02  ZHAN_MM_CD1_VS_CD2_UP  69  7.18E-02  NOUZOVA_CPG_H4_UP  91  7.26E-02  NUCLEOTIDE_BIOSYNTHETIC_PROCESS  17  7.41E-02  MITOCHONDRIAL_RIBOSOME  17  7.66E-02  CASPASEPATHWAY  21  7.80E-02  TAKEDA_NUP8_HOXA9_10D_UP  155  7.87E-02  RIBOSOMAL_SUBUNIT  15  7.95E-02  DNA_DEPENDENT_DNA_REPLICATION  51  8.05E-02  CHEN_HOXA5_TARGETS_UP  187  8.06E-02  ORGANELLAR_RIBOSOME  17  8.21E-02  ERM_KO_TESTES_DN  18  9.41E-02  AGUIRRE_PANCREAS_CHR6  25  1.19E-01  DNA_HELICASE_ACTIVITY  22  1.22E-01  MITOCHONDRIAL_LUMEN  40  1.40E-01  HSA00670_ONE_CARBON_POOL_BY_FOLATE  15  1.41E-01  PEROXISOME  42  1.42E-01  CHROMATIN  34  1.43E-01  IFN_ANY_UP  76  1.44E-01  MITOCHONDRIAL_RESPIRATORY_CHAIN  21  1.44E-01  MITOCHONDRIAL_MATRIX  40  1.45E-01  MICROBODY  42  1.47E-01  123  Gene Set  Size  FDR  S_ADENOSYLMETHIONINE_DEPENDENT_ METHYLTRANSFERASE_ ACTIVITY  22  1.49E-01  DNA_POLYMERASE_ACTIVITY  17  1.51E-01  MITOCHONDRION_ORGANIZATION_AND_BIOGENESIS  42  1.65E-01  DER_IFNB_UP  85  1.71E-01  PROTEASOME  16  1.71E-01  CMV_HCMV_6HRS_UP  21  1.74E-01  REOVIRUS_HEK293_UP  200  1.75E-01  RNA_TRANSCRIPTION_REACTOME  31  1.75E-01  PHOSPHATASE_REGULATOR_ACTIVITY  25  1.76E-01  MOREAUX_TACI_HI_VS_LOW_DN  138  1.78E-01  BLEO_MOUSE_LYMPH_LOW_24HRS_DN  24  1.79E-01  PROPANOATE_METABOLISM  29  1.81E-01  KIM_TH_CELLS_UP  41  1.82E-01  MITOCHONDRIAL_PART  124  1.90E-01  G1_S_TRANSITION_OF_MITOTIC_CELL_CYCLE  25  1.93E-01  RIBONUCLEOPROTEIN_COMPLEX  117  2.03E-01  PROTEASOMEPATHWAY  19  2.05E-01  MITOCHONDRION  298  2.05E-01  IFNA_HCMV_6HRS_UP  47  2.05E-01  DNA_DIRECTED_RNA_POLYMERASE_II__HOLOENZYME  61  2.06E-01  ZHAN_MMPC_LATEVS  41  2.23E-01  RIBOSOME  33  2.24E-01  BRCA_BRCA1_POS  92  2.24E-01  124  Appendix 5 — Cytokine Level Changes after Allergen Inhalation Challenge a) P Values and Fold Changes Cytokines  P Valuea  Fold Changeb  EGF  7.01E-01  1.067  Eotaxin  4.93E-01  1.038  FGF-2  1.79E-01  1.141  Flt-3 ligand  4.62E-01  1.489  Fractalkine  2.18E-01  1.069  G-CSF  4.01E-01  1.076  GM-CSF  3.47E-01  1.093  GRO  3.73E-01  1.065  IFN-α2  9.57E-01  1.021  IFN-γ  7.05E-01  1.028  IL-1α  6.83E-01  1.117  IL-1β  2.68E-01  1.290  IL-1Rα  2.11E-01  1.237  IL-2  1.91E-01  1.297  IL-3  2.19E-01  1.293  IL-4  7.43E-01  1.182  IL-5  4.26E-01  -1.464  IL-6  5.77E-01  -1.174  IL-7  6.39E-01  1.150  IL-8  8.42E-01  -1.017  IL-9  2.75E-01  1.055  IL-10  7.33E-01  1.081  IL-12 (p40)  4.21E-01  -1.153  IL-12 (p70)  3.83E-01  -1.581  IL-13  3.94E-01  -1.711  125  Cytokines  P Valuea  Fold Changeb  IL-15  5.14E-01  1.006  IL-17  7.50E-01  1.004  IP-10  6.68E-01  -1.033  MCP-1  5.74E-04  -1.227  MCP-3  9.07E-01  -1.034  MDC (CCL22)  9.45E-01  1.003  MIP-1α  4.74E-01  1.038  MIP-1β  9.16E-01  -1.005  PDGF-AA  1.60E-01  1.162  PDGF-AB/BB  3.92E-01  1.057  RANTES  2.24E-02  1.204  sCD40L  9.87E-01  1.002  sIL-2Rα  2.34E-01  1.801  TGF-α  4.57E-01  -2.218  TNF-α  9.52E-01  -1.024  TNF-β  5.01E-01  -1.089  VEGF  8.31E-01  -1.044  a  Based on two-tailed paired t-test. Fold change was calculated from averaged pre- and post-values, without accounting for subject pairs. b  126  b) Histogram Representations  127  128  129  130  Appendix 6 — Differentially Expressed Probe Sets Identified by Interaction Analysis (FDR≤0.30) Probe Set ID 8065396 8168817 7937707 8075555 7923907 8152314  Gene Symbol  Gene Name  FDR  CST9L DRP2 FAM99A C22orf42 IL10 RSPO2  Cystatin 9-like Dystrophin related protein 2 Family with sequence similarity 99, member A Chromosome 22 open reading frame 42 Interleukin 10 R-spondin 2 homolog (Xenopus laevis) Macrophage stimulating 1 receptor (c-met-related tyrosine kinase) Sodium channel, nonvoltage-gated 1, beta DNA-damage inducible 1 homolog 1 (S. Cerevisiae) Leucine rich repeat containing 14B Tight junction protein 1 (zona occludens 1) Chromosome 20 open reading frame 132 GIPC PDZ domain containing family, member 3 Olfactory receptor, family 10, subfamily G, member 2 Kallikrein 1 Sodium channel, nonvoltage-gated 1 alpha UBX domain protein 8 G protein-coupled receptor 87 HFM1, ATP-dependent DNA helicase homolog (S. Cerevisiae) Potassium voltage-gated channel, Isk-related family, member 4 Aldehyde dehydrogenase 4 family, member A1 Dopa decarboxylase (aromatic L-amino acid decarboxylase) Proline rich Gla (G-carboxyglutamic acid) 1 POM121 membrane glycoprotein-like 2 Astacin-like metallo-endopeptidase (M12 family) Transmembrane protein 191A Doublecortin-like kinase 1 NHL repeat containing 1 Lipoma HMGIC fusion partner-like 5 Spindlin family, member 2B Ribosomal protein S25 Fatty acid desaturase 3 C1q and tumor necrosis factor related protein 7 Zinc finger protein 668  0.00E+00 0.00E+00 0.00E+00 1.42E-01 1.42E-01 1.42E-01  8087547  MST1R  7994074 7943521 8104163 7986977 8066161 8024676 7977771 8038633 7960529 8145691 8091515  SCNN1B DDI1 LRRC14B TJP1 C20orf132 GIPC3 OR10G2 KLK1 SCNN1A UBXN8 GPR87  7917634  HFM1  8048749  KCNE4  7912975  ALDH4A1  8139640  DDC  8166705 8124495 8053872 8071541 7970954 8124129 8118995 8173189 8113660 7948630 8094184 7995030  PRRG1 POM121L2 ASTL TMEM191A DCLK1 NHLRC1 LHFPL5 SPIN2B RPS25 FADS3 C1QTNF7 ZNF668  1.42E-01 1.42E-01 1.42E-01 1.42E-01 1.42E-01 1.42E-01 1.42E-01 1.42E-01 1.42E-01 1.42E-01 1.42E-01 1.42E-01 1.42E-01 1.42E-01 1.42E-01 1.42E-01 1.42E-01 1.70E-01 1.70E-01 1.70E-01 1.70E-01 1.70E-01 1.70E-01 1.70E-01 1.70E-01 1.70E-01 1.70E-01 1.70E-01  131  Probe Set ID 7929932 7985238 7938646 8007701 8162674 8178291 8179591 8056151  Gene Symbol  Gene Name  FDR  KAZALD1 ANKRD34C CALCB HIGD1B LOC286359 OR11A1 OR11A1 PLA2R1  Kazal-type serine peptidase inhibitor domain 1 Ankyrin repeat domain 34C Calcitonin-related polypeptide beta HIG1 hypoxia inducible domain family, member 1B Hypothetical LOC286359 Olfactory receptor, family 11, subfamily A, member 1 Olfactory receptor, family 11, subfamily A, member 1 Phospholipase A2 receptor 1, 180kda Serine peptidase inhibitor-like, with Kunitz and WAP domains 1 (eppin) G protein-coupled receptor 173 Myeloma overexpressed 2 Potassium voltage-gated channel, subfamily H (eagrelated), member 5 Small nucleolar RNA, H/ACA box 9 Olfactory receptor, family 2, subfamily T, member 8 Small nuclear ribonucleoprotein D1 polypeptide 16kda Nucleolar protein 4 Potassium inwardly-rectifying channel, subfamily J, member 3 Otoraplin Establishment of cohesion 1 homolog 2 (S. Cerevisiae) Transmembrane protein 191A Hypothetical locus LOC441204 Methyl-cpg binding domain protein 3-like 1 CD1e molecule Transmembrane protein c9orf144b pseudogene Dnaj (Hsp40) homolog, subfamily C, member 9 SH3 domain containing ring finger 2 POU class 1 homeobox 1 Pyruvate dehydrogenase (lipoamide) alpha 2 Astrotactin 2 Carboxypeptidase O Rh family, B glycoprotein (gene/pseudogene) Gonadotropin-releasing hormone (type 2) receptor 2 Zinc finger protein 667 Preferentially expressed antigen in melanoma Colipase, pancreatic PRAME family member 22 Tolloid-like 1 Bone morphogenetic protein 8a Trace amine associated receptor 9 (gene/pseudogene)  1.70E-01 1.70E-01 1.70E-01 1.73E-01 1.73E-01 1.73E-01 1.73E-01 1.73E-01  8066542  SPINLW1  8167758 8060086  GPR173 MYEOV2  7979529  KCNH5  8139456 7911233 8020411 8022856  SNORA9 OR2T8 SNRPD1 NOL4  8045795  KCNJ3  8061082 8145570 8071368 8131965 8025452 7906355 8160900 8064976 8108912 8088986 8096528 8163678 8047829 7906163 7919208 8039593 8074856 8125936 7898002 8098214 7900340 8122127  OTOR ESCO2 TMEM191A LOC441204 MBD3L1 CD1E C9orf144 DNAJC9 SH3RF2 POU1F1 PDHA2 ASTN2 CPO RHBG GNRHR2 ZNF667 PRAME CLPS PRAMEF22 TLL1 BMP8A TAAR9  1.73E-01 1.81E-01 1.81E-01 1.81E-01 1.81E-01 1.81E-01 1.81E-01 1.81E-01 1.81E-01 1.81E-01 1.81E-01 1.81E-01 1.81E-01 1.81E-01 1.81E-01 1.81E-01 1.81E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01  132  Probe Set ID 7927202  Gene Symbol  Gene Name  FDR  ZNF22  Zinc finger protein 22 (KOX 15) UDP-N-acetyl-alpha-D-galactosamine:polypeptide Nacetylgalactosaminyltransferase-like 6 Small G protein signaling modulator 1 Very low density lipoprotein receptor Receptor (G protein-coupled) activity modifying protein 2 Amiloride-sensitive cation channel 2, neuronal Pregnancy specific beta-1-glycoprotein 4 Olfactory receptor, family 6, subfamily Q, member 1 Poly(A) binding protein interacting protein 2B GDNF family receptor alpha 2 Cripto, FRL-1, cryptic family 1 V-mos Moloney murine sarcoma viral oncogene homolog Zinc finger protein 432 Keratin associated protein 15-1 Ras protein-specific guanine nucleotide-releasing factor 1 Transcription factor EC Zinc finger protein 30 homolog (mouse) Paired-like homeobox 2b Killer cell immunoglobulin-like receptor, two domains, short cytoplasmic tail, 5 Epstein-Barr virus induced 3 Plexin B1 Keratin pseudogene Protein arginine methyltransferase 8 Sushi domain containing 3 DCN1, defective in cullin neddylation 1, domain containing 3 (S. Cerevisiae) Discoidin, CUB and LCCL domain containing 2 Integrin, beta-like 1 (with EGF-like repeat domains) Nuclear RNA export factor 3 Microrna 377 Family with sequence similarity 99, member A Alkaline ceramidase 2 Arginine vasopressin receptor 1B Cytochrome P450, family 2, subfamily D, polypeptide 6 Protein phosphatase 1, regulatory (inhibitor) subunit 16A Src homology 2 domain containing transforming protein D Late cornified envelope 3C  1.96E-01  Hypothetical LOC100287948  2.01E-01  Olfactory receptor, family 12, subfamily D, member 3  2.01E-01  8098307  GALNTL6  8071953 8159850 8007348 7955317 8037283 7940108 8052940 8149629 8055239 8150879 8038942 8068139 7985233 8142452 8036420 8100007  SGSM1 VLDLR RAMP2 ACCN2 PSG4 OR6Q1 PAIP2B GFRA2 CFC1 MOS ZNF432 KRTAP15-1 RASGRF1 TFEC ZFP30 PHOX2B  8039892  KIR2DS5  8024792 8086908 8013473 7953181 8156393  EBI3 PLXNB1 LOC339240 PRMT8 SUSD3  8000028  DCUN1D3  8089082 7969861 8174207 7976852 7945660 8154563 7909155 8076424 8153835 8024808 7905490  DCBLD2 ITGBL1 NXF3 MIR377 FAM99A ACER2 AVPR1B CYP2D6 PPP1R16A SHD LCE3C LOC10028794 8 OR12D3  7907907 8124645  1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 1.96E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01  133  Probe Set ID 8076113 7980024 8169115 8174737 8152062 8170704 7976842 8015884 8028984 7924842 8135763  Gene Symbol  Gene Name  FDR  LOC646851 HEATR4 NRK NKAP SNX31 ABCD1 MIR382 PPY CYP2F1 C1orf35 WNT16  Hypothetical LOC646851 HEAT repeat containing 4 Nik related kinase NFKB activating protein Sorting nexin 31 ATP-binding cassette, sub-family D (ALD), member 1 Microrna 382 Pancreatic polypeptide Cytochrome P450, family 2, subfamily F, polypeptide 1 Chromosome 1 open reading frame 35 Wingless-type MMTV integration site family, member 16 Diazepam binding inhibitor (GABA receptor modulator, acyl-coa binding protein) Small nucleolar RNA, C/D box 46 Protein kinase, AMP-activated, alpha 2 catalytic subunit Lysophosphatidylcholine acyltransferase 4 Leucine-rich repeat containing G protein-coupled receptor 5 Programmed cell death 5 Chromosome 19 open reading frame 44 Hexosaminidase (glycosyl hydrolase family 20, catalytic domain) containing Endothelin receptor type A Chromosome 21 open reading frame 125 Hypothetical LOC126536 Protocadherin beta 16 Folate receptor 3 (gamma) Chromosome 17 open reading frame 64 Na+/K+ transporting atpase interacting 3 Chromosome 15 open reading frame 37 Olfactory receptor, family 12, subfamily D, member 3 Microrna 429 Single-minded homolog 2 (Drosophila) Microrna 122 Selectin E Non-protein coding RNA 114 Family with sequence similarity 38, member B Melanoma antigen family A, 5 Serum amyloid A2 CD209 molecule Late cornified envelope 5A Outer dense fiber of sperm tails 3-like 1  2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.01E-01  8044804  DBI  7901048 7901720 7987230  SNORD46 PRKAA2 LPCAT4  7957140  LGR5  8027473 8026568  PDCD5 C19orf44  8010787  HEXDC  8097692 8068894 8026496 8108716 7942328 8008914 8146625 7985253 8178289 7896863 8068496 8021416 7922229 8070315 8022295 8175685 8180303 8033445 7905483 7985025  EDNRA C21orf125 LOC126536 PCDHB16 FOLR3 C17orf64 NKAIN3 C15orf37 OR12D3 MIR429 SIM2 MIR122 SELE NCRNA00114 FAM38B MAGEA5 SAA2 CD209 LCE5A ODF3L1  2.01E-01 2.01E-01 2.01E-01 2.01E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01 2.16E-01  134  Probe Set ID 8157632 7942261 8074880  Gene Symbol  Gene Name  FDR  MORN5 KRTAP5-9 RAB36  MORN repeat containing 5 Keratin associated protein 5-9 RAB36, member RAS oncogene family Serpin peptidase inhibitor, clade F (alpha-2 antiplasmin, pigment epithelium derived factor), member 2 Chemokine (C motif) receptor 1 Kelch-like 23 (Drosophila) Microrna 194-1 Small nucleolar RNA, H/ACA box 52 Peptidylprolyl isomerase C (cyclophilin C) RAB3A interacting protein (rabin3)-like 1 Tetra-peptide repeat homeobox 1 Olfactory receptor, family 6, subfamily C, member 75 Gastrin-releasing peptide Ankyrin repeat and SOCS box containing 18 Sialic acid binding Ig-like lectin 11 TLR4 interactor with leucine-rich repeats Albumin Heat shock protein, alpha-crystallin-related, B6 Three prime repair exonuclease 2 Microrna 205 Prostate transmembrane protein, androgen induced 1 Apolipoprotein B mrna editing enzyme, catalytic polypeptide-like 3F Layilin Intraflagellar transport 81 homolog (Chlamydomonas) Achaete-scute complex homolog 3 (Drosophila) Olfactory receptor, family 5, subfamily AS, member 1 Defensin, beta 103B Defensin, beta 103B SRY (sex determining region Y)-box 14 Ficolin (collagen/fibrinogen domain containing lectin) 2 (hucolin) Atpase, H+ transporting, lysosomal accessory protein 1like Late cornified envelope 2A Retinitis pigmentosa 9 pseudogene T-cell acute lymphocytic leukemia 2 SH3 and cysteine rich domain 2 NHP2 ribonucleoprotein homolog (yeast) Na+/H+ exchanger domain containing 1 Kallikrein-related peptidase 7 Melanoma antigen family B, 10  2.16E-01 2.16E-01 2.16E-01  8003656  SERPINF2  8086595 8046186 7924403 7937483 8113726 7948643 8037947 7955993 8021461 8059868 8038505 8138799 8095628 8036151 8175808 7909422 8067233  XCR1 KLHL23 MIR194-1 SNORA52 PPIC RAB3IL1 TPRX1 OR6C75 GRP ASB18 SIGLEC11 TRIL ALB HSPB6 TREX2 MIR205 PMEPA1  8180374  APOBEC3F  7943749 7958620 7946436 7939959 8144473 8149172 8082926  LAYN IFT81 ASCL3 OR5AS1 DEFB103B DEFB103B SOX14  8159211  FCN2  8106722  ATP6AP1L  7905507 8138930 8157090 8014812 8116168 8177130 8038695 8166587  LCE2A RP9P TAL2 STAC2 NHP2 NHEDC1 KLK7 MAGEB10  2.16E-01 2.16E-01 2.16E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01 2.37E-01  135  Probe Set ID 7997059 8173059 8084832 7902512  Gene Symbol  Gene Name  FDR  DDX19A WNK3 PYDC2 DNAJB4  DEAD (Asp-Glu-Ala-As) box polypeptide 19A WNK lysine deficient protein kinase 3 Pyrin domain containing 2 Dnaj (Hsp40) homolog, subfamily B, member 4 Carbohydrate (N-acetylglucosamine 6-O) sulfotransferase 6 Tumor protein p53 regulated apoptosis inducing protein 1 Adenylate cyclase 8 (brain) Phosphorylase kinase, alpha 1 (muscle) Hypothetical LOC440313 FUN14 domain containing 2 pseudogene 2 Ring finger protein 151 Cytochrome P450, family 1, subfamily A, polypeptide 2 Histocompatibility (minor) HB-1 Protocadherin beta 17 pseudogene Microrna 339 Multiple EGF-like-domains 11 Chromosome 4 open reading frame 17 Solute carrier family 6 (neurotransmitter transporter, dopamine), member 3 PDZ binding kinase Thrombospondin, type I, domain containing 7A Otoancorin Protein tyrosine phosphatase, receptor type, U Transmembrane 4 L six family member 5 FERM domain containing 1 Cysteine-rich secretory protein 2 Kiaa1274 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 5, 13kda UDP glucuronosyltransferase 2 family, polypeptide B10 Dual oxidase 2 Spermatid maturation 1 Homeobox B1 Carbohydrate (keratan sulfate Gal-6) sulfotransferase 1 Keratin associated protein 20-4 SH2 domain containing 4A Odz, odd Oz/ten-m homolog 2 (Drosophila) Chromosome 3 open reading frame 70 Transmembrane protein 105 Glutamic-oxaloacetic transaminase 1-like 1 Hypothetical LOC285696  2.37E-01 2.37E-01 2.37E-01 2.37E-01  8002882  CHST6  7952631 8152902 8173551 7991577 8043040 7992409 7984862 8108900 8108706 8137707 7989887 8096568  TP53AIP1 ADCY8 PHKA1 LOC440313 FUNDC2P2 RNF151 CYP1A2 HMHB1 PCDHB17 MIR339 MEGF11 C4orf17  8110821  SLC6A3  8149955 8138231 7993848 7899562 8003939 8130837 8126891 7928126  PBK THSD7A OTOA PTPRU TM4SF5 FRMD1 CRISP2 KIAA1274  8142663  NDUFA5  8100768 7988350 8004394 8016433 7947599 8068157 8144880 8109752 8092520 8019177 8150244 8111203  UGT2B10 DUOX2 SPEM1 HOXB1 CHST1 KRTAP20-4 SH2D4A ODZ2 C3orf70 TMEM105 GOT1L1 LOC285696  2.37E-01 2.37E-01 2.37E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01  136  Probe Set ID  Gene Symbol  Gene Name  7965206  SLC6A15  8030299 8026388 7961798 8005586 7973510 8160360 8069146 7930208 8084838 8005446 8165508 7911529 7977478 7948129 8039389 8161482 8027222 8175666 8150253 8147516 8045198 8061272 7957503 8011339 7942991 8046824 7917942 8087252 8044212 8022986 8034390 8110382 8160392 8070757 7986426 8127646 8013035 8015115 7905533 7933194  CCDC155 OR7C2 SOX5 RNF112 CPNE6 IFNB1 KRTAP10-7 INA HRASLS LOC339240 NRARP MXRA8 OR4K13 OR5R1 PTPRH ANKRD30BL CILP2 GABRE STAR MATN2 CFC1B C20orf26 C12orf37 OR1E1 TYR FSIP2 FLJ35409 MIR191 SULT1C2 SYT4 ZNF799 PRR7 IFNA16 TSPEAR DNM1P46 FILIP1 ZNF624 KRT12 IVL CXCL12  Solute carrier family 6 (neutral amino acid transporter), member 15 Coiled-coil domain containing 155 Olfactory receptor, family 7, subfamily C, member 2 SRY (sex determining region Y)-box 5 Ring finger protein 112 Copine VI (neuronal) Interferon, beta 1, fibroblast Keratin associated protein 10-7 Internexin neuronal intermediate filament protein, alpha HRAS-like suppressor Keratin pseudogene NOTCH-regulated ankyrin repeat protein Matrix-remodelling associated 8 Olfactory receptor, family 4, subfamily K, member 13 Olfactory receptor, family 5, subfamily R, member 1 Protein tyrosine phosphatase, receptor type, H Ankyrin repeat domain 30B-like Cartilage intermediate layer protein 2 Gamma-aminobutyric acid (GABA) A receptor, epsilon Steroidogenic acute regulatory protein Matrilin 2 Cripto, FRL-1, cryptic family 1B Chromosome 20 open reading frame 26 Chromosome 12 open reading frame 37 Olfactory receptor, family 1, subfamily E, member 1 Tyrosinase (oculocutaneous albinism IA) Fibrous sheath interacting protein 2 FLJ35409 protein Microrna 191 Sulfotransferase family, cytosolic, 1C, member 2 Synaptotagmin IV Zinc finger protein 799 Proline rich 7 (synaptic) Interferon, alpha 16 Thrombospondin-type laminin G domain and EAR repeats DNM1 pseudogene 46 Filamin A interacting protein 1 Zinc finger protein 624 Keratin 12 Involucrin Chemokine (C-X-C motif) ligand 12  FDR 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.47E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01  137  Probe Set ID 7912520 7926708 8018754  Gene Symbol  Gene Name  FDR  NPPB THNSL1 CYGB  Natriuretic peptide B Threonine synthase-like 1 (S. Cerevisiae) Cytoglobin Ganglioside-induced differentiation-associated protein 1like 1 Chromosome 2 open reading frame 80 Dnaj (Hsp40) homolog, subfamily C, member 17 LIM homeobox 8 Protein phosphatase 1, regulatory (inhibitor) subunit 1B Metallophosphoesterase domain containing 2 PTK6 protein tyrosine kinase 6 Tryptase gamma 1 Cytochrome P450, family 46, subfamily A, polypeptide 1 Hypothetical protein LOC643721 Rho guanine nucleotide exchange factor (GEF) 4 Coagulation factor III (thromboplastin, tissue factor) Receptor tyrosine kinase-like orphan receptor 1 Fanconi anemia, complementation group E Plasminogen Chromosome 3 open reading frame 22 Keratin associated protein 4-2 Taste receptor, type 2, member 10 Keratin associated protein 12-4 Chromosome 1 open reading frame 190 IQ motif containing K Annexin A9 Family with sequence similarity 20, member A Microrna 199b Vascular cell adhesion molecule 1 Epiregulin Chromosome 19 open reading frame 45 Ribosomal protein L23 pseudogene 8 Transmembrane protein 14E Discoidin domain receptor tyrosine kinase 2  2.69E-01 2.69E-01 2.69E-01  Hypothetical protein LOC100132288  2.69E-01  G kinase anchoring protein 1 Pterin-4 alpha-carbinolamine dehydratase/dimerization cofactor of hepatocyte nuclear factor 1 alpha Zinc finger protein 425 HEAT repeat family member 7B2 Family with sequence similarity 20, member C  2.69E-01  8062796  GDAP1L1  8058542 7987554 7902353 8006865 7947274 8067662 7998427 7976681 8180251 8045229 7917875 7901969 8118963 8123259 8090388 8015242 7961249 8070789 7901187 7993713 7905283 8017867 8164396 7903358 8095728 8025169 8131705 8091546 7906900  8162006  C2orf80 DNAJC17 LHX8 PPP1R1B MPPED2 PTK6 TPSG1 CYP46A1 FLJ45508 ARHGEF4 F3 ROR1 FANCE PLG C3orf22 KRTAP4-2 TAS2R10 KRTAP12-4 C1orf190 IQCK ANXA9 FAM20A MIR199B VCAM1 EREG C19orf45 RPL23P8 TMEM14E DDR2 LOC10013228 8 GKAP1  7934178  PCBD1  8143708 8111821 8130993  ZNF425 HEATR7B2 FAM20C  8177120  2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01  2.69E-01 2.69E-01 2.69E-01 2.69E-01  138  Probe Set ID 8088550 7941917 7963513 8074153 8098368 8099302 8102468 8031253 8060461 7931097 8015293 8175572 7906197 8075785 7929388 7944351 8000346 7903884 7928766 8136863 8039577 8037240 8173862 8179926 8001163 8137485 8155747 7997374 7964535 7944302 8083576  Gene Symbol  Gene Name  FDR  PRICKLE2 CABP4 KRT76 ACR ADAM29 MIR95 PRSS12 LILRP2 TMC2 HTRA1 KRT32 SPANXN3 HAPLN2 FOXRED2 PLCE1 FOXR1 ERN2 PROK1 C10orf99 TMEM139 ZSCAN5A PSG1 SATL1 DOM3Z MYLK3 DPP6 C9orf135 DYNLRB2 CYP27B1 PHLDB1 LEKR1  Prickle homolog 2 (Drosophila) Calcium binding protein 4 Keratin 76 Acrosin ADAM metallopeptidase domain 29 Microrna 95 Protease, serine, 12 (neurotrypsin, motopsin) Leukocyte immunoglobulin-like receptor pseudogene 2 Transmembrane channel-like 2 Htra serine peptidase 1 Keratin 32 SPANX family, member N3 Hyaluronan and proteoglycan link protein 2 FAD-dependent oxidoreductase domain containing 2 Phospholipase C, epsilon 1 Forkhead box R1 Endoplasmic reticulum to nucleus signaling 2 Prokineticin 1 Chromosome 10 open reading frame 99 Transmembrane protein 139 Zinc finger and SCAN domain containing 5A Pregnancy specific beta-1-glycoprotein 1 Spermidine/spermine N1-acetyl transferase-like 1 Dom-3 homolog Z (C. Elegans) Myosin light chain kinase 3 Dipeptidyl-peptidase 6 Chromosome 9 open reading frame 135 Dynein, light chain, roadblock-type 2 Cytochrome P450, family 27, subfamily B, polypeptide 1 Pleckstrin homology-like domain, family B, member 1 Leucine, glutamate and lysine rich 1 Calcium channel, voltage-dependent, alpha 2/delta subunit 4 MAS-related GPR, member X2 Mannan-binding lectin serine peptidase 1 (C4/C2 activating component of Ra-reactive factor) Chromosome 19 open reading frame 73 Apolipoprotein F Gap junction protein, delta 2, 36kda Keratin associated protein 4-11 Receptor accessory protein 1 Melanoma antigen family B, 1  2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01  7960283  CACNA2D4  7947096  MRGPRX2  8092661  MASP1  8038314 7964142 7987310 8015221 8053551 8166619  C19orf73 APOF GJD2 KRTAP4-11 REEP1 MAGEB1  2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01  139  Probe Set ID 8117537 8091491 7905503 8062490 8160417 7934074 8039779  Gene Symbol  Gene Name  FDR  HIST1H4I CLRN1 LCE2C SNORA60 IFNA6 TACR2 SLC27A5  Histone cluster 1, h4i Clarin 1 Late cornified envelope 2C Small nucleolar RNA, H/ACA box 60 Interferon, alpha 6 Tachykinin receptor 2 Solute carrier family 27 (fatty acid transporter), member 5 Ankyrin repeat and sterile alpha motif domain containing 4B MDS1 and EVI1 complex locus Keratin 14 X-prolyl aminopeptidase (aminopeptidase P) 2, membrane-bound Glycine dehydrogenase (decarboxylating) KIAA0664-like 3 Membrane protein, palmitoylated 2 (MAGUK p55 subfamily member 2) Chromosome 10 open reading frame 107 Cytochrome P450, family 4, subfamily F, polypeptide 8 Tripartite motif containing 71 Leucine rich repeat and Ig domain containing 2 Mannosyl (alpha-1,3-)-glycoprotein beta-1,4-Nacetylglucosaminyltransferase, isozyme C (putative) SLIT and NTRK-like family, member 1 Olfactory receptor, family 4, subfamily L, member 1 Deleted in malignant brain tumors 1 pseudogene Chromosome 7 open reading frame 57 Desmoglein 3 Alpha-1,4-N-acetylglucosaminyltransferase Cadherin 3, type 1, P-cadherin (placental) Heat shock 27kda protein 2 Sulfotransferase family 1E, estrogen-preferring, member 1 Gamma-aminobutyric acid (GABA) A receptor, alpha 6 Reticulon 4 receptor-like 1 Tumor necrosis factor (ligand) superfamily, member 15 Dynein, axonemal, heavy chain 12 Chromosome 20 open reading frame 27  2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01  Hypothetical LOC100131510  2.69E-01  7993815  ANKS4B  8091972 8015366  MECOM KRT14  8169836  XPNPEP2  8160024 7995242  GLDC KIAA0664L3  8015868  MPP2  7927723 8026442 8078435 8160546  C10orf107 CYP4F8 TRIM71 LINGO2  7965231  MGAT4C  7972231 7973022 7931140 8132715 8020762 8090955 7996819 7943787 8100808 8109651 8011214 8163618 8088315 8064739  SLITRK1 OR4L1 FLJ46361 C7orf57 DSG3 A4GNT CDH3 HSPB2 SULT1E1 GABRA6 RTN4RL1 TNFSF15 DNAH12 C20orf27 LOC10013151 0  8050844 7982663  BUB1B  7927529 7902754  MSMB CLCA3P  Budding uninhibited by benzimidazoles 1 homolog beta (yeast) Microseminoprotein, beta Chloride channel accessory 3 (pseudogene)  2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01 2.69E-01  2.69E-01 2.69E-01 2.94E-01  140  Probe Set ID 7913990 8003844 7909503 7937882 8109908 7899615  Gene Symbol  Gene Name  FDR  GPATCH3 GSG2 SERTAD4 ART1 LOC257358 SERINC2  G patch domain containing 3 Germ cell associated 2 (haspin) SERTA domain containing 4 ADP-ribosyltransferase 1 Hypothetical LOC257358 Serine incorporator 2 Serpin peptidase inhibitor, clade C (antithrombin), member 1 WAP four-disulfide core domain 6 Trichohyalin Programmed cell death 1 ligand 2 Netrin 4 MDS1 and EVI1 complex locus Chromosome 2 open reading frame 81 Chromosome 11 open reading frame 35 Gamma-aminobutyric acid (GABA) A receptor, beta 3 Zinc finger protein 511 Signal recognition particle 19kda Integrin, alpha 11 Sal-like 1 (Drosophila) Phospholipase A2, group IVC (cytosolic, calciumindependent) Src homology 2 domain containing adaptor protein B Block of proliferation 1 Junctophilin 4 FLJ45248 protein Hypothetical LOC84983 Fascin homolog 3, actin-bundling protein, testicular (Strongylocentrotus purpuratus) Zinc finger protein 280B Hypothetical LOC401260 Papilin, proteoglycan-like sulfated glycoprotein DAZ interacting protein 1-like Chromosome 14 open reading frame 129 Ribosomal protein S18 Ribosomal protein S18 Ribosomal protein S18 Neuropeptide Y receptor Y2 Melanoma antigen Exophilin 5 Glutathione peroxidase 3 (plasma) Hypothetical FLJ13744  2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01  7922420  SERPINC1  8066536 7920141 8154245 7965573 8091991 8053139 7937404 7986822 7931561 8107350 7989985 8001387  WFDC6 TCHH PDCD1LG2 NTN4 MECOM C2orf81 C11orf35 GABRB3 ZNF511 SRP19 ITGA11 SALL1  8037970  PLA2G4C  8161255 8153664 7978093 8147721 7966229  SHB BOP1 JPH4 FLJ45248 MGC14436  8135865  FSCN3  8074845 8126240 7975562 8090938 7976571 8118644 8178253 8179544 8097938 8071049 7951545 8109333 8127754  ZNF280B FLJ41649 PAPLN DZIP1L C14orf129 RPS18 RPS18 RPS18 NPY2R LOC51152 EXPH5 GPX3 FLJ13744  2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01  141  Probe Set ID 8066489 8103005 8154449 8141169  Gene Symbol  Gene Name  FDR  WFDC12 ANAPC10 CNTLN MGC72080  WAP four-disulfide core domain 12 Anaphase promoting complex subunit 10 Centlein, centrosomal protein MGC72080 pseudogene TAF1 RNA polymerase II, TATA box binding protein (TBP)-associated factor, 210kda-like RAB17, member RAS oncogene family Chemokine (C-C motif) ligand 17 Lysozyme-like 4 Myosin, heavy chain 7, cardiac muscle, beta RWD domain containing 2B Cullin 7 Lung carcinoma-associated protein 10 FERM and PDZ domain containing 2 Phospholipase A2, group XIIA Dnaj (Hsp40) homolog, subfamily B, member 14 Histone cluster 1, h4a Oxoglutarate (alpha-ketoglutarate) receptor 1 Family with sequence similarity 71, member C Bone morphogenetic protein 3 Sulfotransferase family, cytosolic, 1C, member 3 Olfactory receptor, family 2, subfamily T, member 33 Cyclic nucleotide gated channel alpha 3 NK2 transcription factor related, locus 5 (Drosophila) Claudin 11 Trna methyltransferase 61 homolog A (S. Cerevisiae) CD248 molecule, endosialin Endothelin converting enzyme 2 Proline rich 20A Proline rich 20A Proline rich 20A Proline rich 20A Proline rich 20A Taste receptor, type 1, member 3 Adenylosuccinate synthase like 1 Fumarylacetoacetate hydrolase domain containing 2B Neural cell adhesion molecule 2 SEC14-like 2 (S. Cerevisiae) Chromosome 10 open reading frame 2 Cysteine-serine-rich nuclear protein 3 Semenogelin II Tektin 1  2.94E-01 2.94E-01 2.94E-01 2.94E-01  8160597  TAF1L  8059955 7996034 8086400 7978021 8069744 8126486 8170786 7933446 8102321 8101934 8117334 7972428 7957790 8096070 8044204 7925741 8043782 8115840 8083887 7977105 7949588 8084397 7969300 7969306 7969312 7969318 7969324 7896921 7977273 8043682 8067985 8072328 7929901 8046048 8062944 8011990  RAB17 CCL17 LYZL4 MYH7 RWDD2B CUL7 LCA10 FRMPD2 PLA2G12A DNAJB14 HIST1H4A OXGR1 FAM71C BMP3 SULT1C3 OR2T33 CNGA3 NKX2-5 CLDN11 TRMT61A CD248 ECE2 PRR20A PRR20A PRR20A PRR20A PRR20A TAS1R3 ADSSL1 FAHD2B NCAM2 SEC14L2 C10orf2 CSRNP3 SEMG2 TEKT1  2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01  142  Probe Set ID 8136961 7980485 7959921 8056710 8061799 8154848 8175933 8096411 7979351 7904761 8071206 8157696 7934959  Gene Symbol  Gene Name  FDR  OR2F2 DIO2 LOC338797 C2orf77 BPIL3 PRSS3 RENBP TIGD2 C14orf33 ITGA10 MRPL40 OR5C1 MIR107  Olfactory receptor, family 2, subfamily F, member 2 Deiodinase, iodothyronine, type II Hypothetical LOC338797 Chromosome 2 open reading frame 77 Bactericidal/permeability-increasing protein-like 3 Protease, serine, 3 Renin binding protein Tigger transposable element derived 2 Chromosome 14 open reading frame 33 Integrin, alpha 10 Mitochondrial ribosomal protein L40 Olfactory receptor, family 5, subfamily C, member 1 Microrna 107 Angiotensinogen (serpin peptidase inhibitor, clade A, member 8) Regulator of G-protein signaling 7 binding protein Potassium voltage-gated channel, subfamily H (eagrelated), member 4 Myelin oligodendrocyte glycoprotein Sidekick homolog 2 (chicken) Calcium channel, voltage-dependent, beta 4 subunit Junctophilin 1 Stimulated by retinoic acid gene 6 homolog (mouse) Dimethylarginine dimethylaminohydrolase 2 Olfactory receptor, family 5, subfamily J, member 2 Chromosome 21 open reading frame 128 Oligodendrocyte lineage transcription factor 2 High density lipoprotein binding protein Formin 1 Nyctalopin NACHT and WD repeat domain containing 1 Mucin 12, cell surface associated ADAMTS-like 1 Ribosomal protein L23a pseudogene 53 V-myc myelocytomatosis viral related oncogene, neuroblastoma derived (avian) Chromosome 15 open reading frame 52 Transmembrane protease, serine 11D Coiled-coil domain containing 147  2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01  7924987  AGT  8105596  RGS7BP  8015554  KCNH4  8179011 8018114 8055872 8151423 7990309 8125048 7939971 8070563 8068231 8049825 7987145 8166899 8026587 8135031 8154491 8148966  MOG SDK2 CACNB4 JPH1 STRA6 DDAH2 OR5J2 C21orf128 OLIG2 HDLBP FMN1 NYX NWD1 MUC12 ADAMTSL1 RPL23AP53  8040419  MYCN  7987511 8100664 7930320  C15orf52 TMPRSS11D CCDC147  2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01 2.94E-01  143  Appendix 7 — Lymphocyte-Correlated Probe Sets Significantly Lower-Expressed in DR than ER, Post-Allergen Inhalation Challenge (FDR≤0.30) Probe Set ID 7937915 7982712 8049297 8124521 8124531 8150962 8180255 8180321 7909601 7919589 7919606 7938348 7952914 7984263 8009417 8019737 8060813 8117598 7919612 8055426 7920244 8047702 8060503 8105828 8106006 8124416 7913869 7919642 7967386 7979307 7985829 8049299 8053584 8068898 8083272 8124397 8135576 7902398  Gene Symbol RRM1 C15orf23 SCARNA5 HIST1H4K HIST1H3I TOX HIST2H4B HIST2H4A SNORA16B HIST2H3D HIST2H2BF WEE1 CCDC77 PTPLAD1 KPNA2 KPNA2 MCM8 HIST1H4J HIST2H3D MCM6 S100A8 ICOS SNORD57 CCNB1 SMN1 HIST1H3D STMN1 HIST2H2AB MPHOSPH9 DLGAP5 FANCI SCARNA6 CD8A HIST1H2BK GYG1 HIST1H1C TES SNORD45A  Gene Name  FDR  Ribonucleotide reductase M1 Chromosome 15 open reading frame 23 Small Cajal body-specific RNA 5 Histone cluster 1, h4k Histone cluster 1, h3i Thymocyte selection-associated high mobility group box Histone cluster 2, h4b Histone cluster 2, h4a Small nucleolar RNA, H/ACA box 16B Histone cluster 2, h3d Histone cluster 2, h2bf WEE1 homolog (S. Pombe) Coiled-coil domain containing 77 Protein tyrosine phosphatase-like A domain containing 1 Karyopherin alpha 2 (RAG cohort 1, importin alpha 1) Karyopherin alpha 2 (RAG cohort 1, importin alpha 1) Minichromosome maintenance complex component 8 Histone cluster 1, h4j Histone cluster 2, h3d Minichromosome maintenance complex component 6 S100 calcium binding protein A8 Inducible T-cell co-stimulator Small nucleolar RNA, C/D box 57 Cyclin B1 Survival of motor neuron 1, telomeric Histone cluster 1, h3d Stathmin 1 Histone cluster 2, h2ab M-phase phosphoprotein 9 Discs, large (Drosophila) homolog-associated protein 5 Fanconi anemia, complementation group I Small Cajal body-specific RNA 6 CD8a molecule Histone cluster 1, h2bk Glycogenin 1 Histone cluster 1, h1c Testis derived transcript (3 LIM domains) Small nucleolar RNA, C/D box 45A  9.86E-02 9.86E-02 9.86E-02 9.86E-02 9.86E-02 9.86E-02 9.86E-02 9.86E-02 1.19E-01 1.19E-01 1.19E-01 1.19E-01 1.19E-01 1.19E-01 1.19E-01 1.19E-01 1.19E-01 1.19E-01 1.20E-01 1.20E-01 1.39E-01 1.39E-01 1.39E-01 1.39E-01 1.39E-01 1.39E-01 1.41E-01 1.41E-01 1.41E-01 1.41E-01 1.41E-01 1.41E-01 1.41E-01 1.41E-01 1.41E-01 1.41E-01 1.41E-01 1.74E-01  144  Probe Set ID 7952339 8053366 8095139 8124534 7905163 7926259 7947694  Gene Symbol SNORD14C SUCLG1 SRD5A3 HIST1H4L MRPS21 MCM10 CKAP5  8066074  DSN1  8147396 8160151 7904465 7904853 7905079 7905085 7906386 7909568 7910997 7919243 7919584 7919614 7919619 7921434 7921900 7922174 7929438 7934026 7937020 7948902 7948904 7953351 7960728 7961198 7969243 7981181  INTS8 ZDHHC21 HIST2H2BA GPR89A HIST2H2AA3 HIST2H3A PYHIN1 DTL EXO1 CD160 HIST2H2BF HIST2H3A HIST2H2AA3 AIM2 SH2D1B F5 HELLS DNA2 MKI67 SNORD29 SNORD28 NCAPD2 SCARNA12 KLRAP1 CKAP2 SCARNA13 LOC1004992 21 ARHGAP11A SCARNA15 BLM PLK1 SNORD3A  7982333 7982358 7985480 7986068 7994109 8005547  Gene Name  FDR  Small nucleolar RNA, C/D box 14C Succinate-coa ligase, alpha subunit Steroid 5 alpha-reductase 3 Histone cluster 1, h4l Mitochondrial ribosomal protein S21 Minichromosome maintenance complex component 10 Cytoskeleton associated protein 5 DSN1, MIND kinetochore complex component, homolog (S. Cerevisiae) Integrator complex subunit 8 Zinc finger, DHHC-type containing 21 Histone cluster 2, h2ba G protein-coupled receptor 89A Histone cluster 2, h2aa3 Histone cluster 2, h3a Pyrin and HIN domain family, member 1 Denticleless homolog (Drosophila) Exonuclease 1 CD160 molecule Histone cluster 2, h2bf Histone cluster 2, h3a Histone cluster 2, h2aa3 Absent in melanoma 2 SH2 domain containing 1B Coagulation factor V (proaccelerin, labile factor) Helicase, lymphoid-specific DNA replication helicase 2 homolog (yeast) Antigen identified by monoclonal antibody Ki-67 Small nucleolar RNA, C/D box 29 Small nucleolar RNA, C/D box 28 Non-SMC condensin I complex, subunit D2 Small Cajal body-specific RNA 12 Killer cell lectin-like receptor subfamily A pseudogene 1 Cytoskeleton associated protein 2 Small Cajal body-specific RNA 13  1.74E-01 1.74E-01 1.74E-01 1.74E-01 2.01E-01 2.01E-01 2.01E-01  Hypothetical LOC100499221  2.32E-01  Rho gtpase activating protein 11A Small Cajal body-specific RNA 15 Bloom syndrome, recq helicase-like Polo-like kinase 1 Small nucleolar RNA, C/D box 3A  2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01  2.01E-01 2.01E-01 2.01E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01  145  Probe Set ID 8005553 8013323 8013325 8013329 8018849 8019842 8022640 8033667 8040142  Gene Symbol SNORD3A SNORD3A SNORD3A SNORD3A TK1 TYMS DHFR ZNF558 CPSF3  8042211  B3GNT2  8043036 8054580 8058052 8064844  LOC1720 BUB1 HSPD1 PCNA  8074925  LOC91316  8093053 8094240 8095986 8102643 8105949 8105958 8105995 8105997 8107706 8109639 8111892 8117395 8117408 8117422 8117426 8124385 8124527 8127364 8144228 8146357 8151561 8160238 8168470 8177647 8177658  TFRC CD38 ANXA3 CCNA2 SERF1A SMN1 SMA5 SERF1A LMNB1 PTTG1 OXCT1 HIST1H2BF HIST1H2AE HIST1H4F HIST1H2BH HIST1H4B HIST1H1B GUSBP4 FLJ36840 MCM4 ZFAND1 PSIP1 COX7B SMN1 SERF1A  Gene Name  FDR  Small nucleolar RNA, C/D box 3A Small nucleolar RNA, C/D box 3A Small nucleolar RNA, C/D box 3A Small nucleolar RNA, C/D box 3A Thymidine kinase 1, soluble Thymidylate synthetase Dihydrofolate reductase Zinc finger protein 558 Cleavage and polyadenylation specific factor 3, 73kda UDP-glcnac:betagal beta-1,3-Nacetylglucosaminyltransferase 2 Dihydrofolate reductase pseudogene Budding uninhibited by benzimidazoles 1 homolog (yeast) Heat shock 60kda protein 1 (chaperonin) Proliferating cell nuclear antigen Glucuronidase, beta/immunoglobulin lambda-like polypeptide 1 pseudogene Transferrin receptor (p90, CD71) CD38 molecule Annexin A3 Cyclin A2 Small EDRK-rich factor 1A (telomeric) Survival of motor neuron 1, telomeric Glucuronidase, beta pseudogene Small EDRK-rich factor 1A (telomeric) Lamin B1 Pituitary tumor-transforming 1 3-oxoacid coa transferase 1 Histone cluster 1, h2bf Histone cluster 1, h2ae Histone cluster 1, h4f Histone cluster 1, h2bh Histone cluster 1, h4b Histone cluster 1, h1b Glucuronidase, beta pseudogene 4 Hypothetical LOC645524 Minichromosome maintenance complex component 4 Zinc finger, AN1-type domain 1 PC4 and SFRS1 interacting protein 1 Cytochrome c oxidase subunit viib Survival of motor neuron 1, telomeric Small EDRK-rich factor 1A (telomeric)  2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01 2.32E-01  146  Probe Set ID 7899134 7906613  Gene Symbol CCDC21 SLAMF7  7918657  PTPN22  7921625 7938366 7950906 7970864 7989128 7989132  SLAMF6 WEE1 CTSC HSPH1 CNOT6L RFX7  7995128  ITGAX  8019802  RNU2-1  8081953  GTF2E1  8112902 8117368 8117594 8123044 8124524 8124537 8131709 8144812 8160033 8166989  DHFR HIST1H4C HIST1H2BM TULP4 HIST1H2AK HIST1H3J SP4 PCM1 SNRPE ZNF673  Gene Name  FDR  Coiled-coil domain containing 21 SLAM family member 7 Protein tyrosine phosphatase, non-receptor type 22 (lymphoid) SLAM family member 6 WEE1 homolog (S. Pombe) Cathepsin C Heat shock 105kda/110kda protein 1 CCR4-NOT transcription complex, subunit 6-like Regulatory factor X, 7 Integrin, alpha X (complement component 3 receptor 4 subunit) RNA, U2 small nuclear 1 General transcription factor IIE, polypeptide 1, alpha 56kda Dihydrofolate reductase Histone cluster 1, h4c Histone cluster 1, h2bm Tubby like protein 4 Histone cluster 1, h2ak Histone cluster 1, h3j Sp4 transcription factor Pericentriolar material 1 Small nuclear ribonucleoprotein polypeptide E Zinc finger family member 673  2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01 2.41E-01  147  Appendix 8 — Eosinophil-Correlated Probe Sets Significantly Higher-Expressed in DR than ER, Post-Allergen Inhalation Challenge (FDR≤0.30) Probe Set ID 7905085 7919589 7919612 7919614 7929258 8105828 8061579 7929541 8124527 7941505 7926259 7937020 8001133 8124537 7900699  Gene Symbol HIST2H3A HIST2H3D HIST2H3D HIST2H3A KIF11 CCNB1 TPX2 CC2D2B HIST1H1B CST6 MCM10 MKI67 SHCBP1 HIST1H3J CDC20  7923086  ASPM  7952914 7983969 7989647 7993267 8053584 8054580 8089694 8096528 8127987 8149109 8179564 7913869 8068740 8103932 8117594 8118669 8124531 8124534 7919642 7969288 8014974  CCDC77 CCNB2 KIAA0101 TNFRSF17 CD8A BUB1 ZNF80 PDHA2 SNORD50A DEFA4 KIFC1 STMN1 UMODL1 MLF1IP HIST1H2BM KIFC1 HIST1H3I HIST1H4L HIST2H2AB OLFM4 TOP2A  Gene Name  FDR  Histone cluster 2, h3a Histone cluster 2, h3d Histone cluster 2, h3d Histone cluster 2, h3a Kinesin family member 11 Cyclin B1 TPX2, microtubule-associated, homolog (Xenopus laevis) Coiled-coil and C2 domain containing 2B Histone cluster 1, h1b Cystatin E/M Minichromosome maintenance complex component 10 Antigen identified by monoclonal antibody Ki-67 SHC SH2-domain binding protein 1 Histone cluster 1, h3j Cell division cycle 20 homolog (S. Cerevisiae) Asp (abnormal spindle) homolog, microcephaly associated (Drosophila) Coiled-coil domain containing 77 Cyclin B2 Kiaa0101 Tumor necrosis factor receptor superfamily, member 17 CD8a molecule Budding uninhibited by benzimidazoles 1 homolog (yeast) Zinc finger protein 80 Pyruvate dehydrogenase (lipoamide) alpha 2 Small nucleolar RNA, C/D box 50A Defensin, alpha 4, corticostatin Kinesin family member C1 Stathmin 1 Uromodulin-like 1 MLF1 interacting protein Histone cluster 1, h2bm Kinesin family member C1 Histone cluster 1, h3i Histone cluster 1, h4l Histone cluster 2, h2ab Olfactomedin 4 Topoisomerase (DNA) II alpha 170kda  6.20E-02 6.20E-02 6.20E-02 6.20E-02 6.20E-02 8.60E-02 8.83E-02 8.86E-02 1.06E-01 1.68E-01 1.72E-01 1.72E-01 1.72E-01 1.72E-01 1.73E-01 1.73E-01 1.73E-01 1.73E-01 1.73E-01 1.73E-01 1.73E-01 1.73E-01 1.73E-01 1.73E-01 1.73E-01 1.73E-01 1.73E-01 1.89E-01 1.89E-01 1.89E-01 1.89E-01 1.89E-01 1.89E-01 1.89E-01 1.90E-01 1.90E-01 1.90E-01  148  Probe Set ID 8025450 8090972 8122058 7919606 7932221 7940561 7952406 7954065 7963020 7980425 7994109 8016494 8022640 8027748  Gene Symbol OR2Z1 TXNDC6 ARG1 HIST2H2BF C10orf111 FEN1 OR8B12 GPRC5A DHH ISM2 PLK1 TTLL6 DHFR FXYD3  8029098  CEACAM6  8031031 8059864  MIR516B2 GBX2  8087907  SEMA3G  8094278 8108301 8123760 8124391 8149955 8157446 8160417 7914851  7938366 7945660 7951246 7991750 8007071  NCAPG KIF20A LY86-AS1 HIST1H2AB PBK ORM1 IFNA6 CLSPN LOC1001311 95 WEE1 FAM99A MMP8 HBZ CDC6  8037222  CEACAM8  8079370 8100758  CCR9 UGT2B7  8100971  PPBP  8148548 8150962  PSCA TOX  7933190  Gene Name  FDR  Olfactory receptor, family 2, subfamily Z, member 1 Thioredoxin domain containing 6 Arginase, liver Histone cluster 2, h2bf Chromosome 10 open reading frame 111 Flap structure-specific endonuclease 1 Olfactory receptor, family 8, subfamily B, member 12 G protein-coupled receptor, family C, group 5, member A Desert hedgehog Isthmin 2 homolog (zebrafish) Polo-like kinase 1 Tubulin tyrosine ligase-like family, member 6 Dihydrofolate reductase FXYD domain containing ion transport regulator 3 Carcinoembryonic antigen-related cell adhesion molecule 6 (non-specific cross reacting antigen) Microrna 516b-2 Gastrulation brain homeobox 2 Sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 3G Non-SMC condensin I complex, subunit G Kinesin family member 20A LY86 antisense RNA 1 (non-protein coding) Histone cluster 1, h2ab PDZ binding kinase Orosomucoid 1 Interferon, alpha 6 Claspin  1.90E-01 1.90E-01 1.90E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01  Hypothetical protein LOC100131195  2.21E-01  WEE1 homolog (S. Pombe) Family with sequence similarity 99, member A Matrix metallopeptidase 8 (neutrophil collagenase) Hemoglobin, zeta Cell division cycle 6 homolog (S. Cerevisiae) Carcinoembryonic antigen-related cell adhesion molecule 8 Chemokine (C-C motif) receptor 9 UDP glucuronosyltransferase 2 family, polypeptide B7 Pro-platelet basic protein (chemokine (C-X-C motif) ligand 7) Prostate stem cell antigen Thymocyte selection-associated high mobility group box  2.21E-01 2.21E-01 2.21E-01 2.21E-01 2.21E-01  2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.08E-01 2.21E-01  2.21E-01 2.21E-01 2.21E-01 2.21E-01 2.21E-01 2.21E-01  149  Probe Set ID 8166585 7902808 7903565 7908161 7909568 7909708 7919243 7928882 7929334 7943349  Gene Symbol FLJ32742 LOC339524 GPSM2 C1orf21 DTL CENPF CD160 C10orf116 CEP55 ARHGAP42  7945774  SLC22A18AS  7945857 7958711 7963817 7977732 7981601 7982889 7984263 7985829 7990683 7991406 7998722 8008201 8019842 8030823 8034974 8040898 8049297 8055941 8061471  MRGPRG CCDC63 GTSF1 SNORD8 IGHV4-31 NUSAP1 PTPLAD1 FANCI ACSBG1 PRC1 SNORD60 NGFR TYMS IGLON5 EPHX3 TRIM54 SCARNA5 RPRM GINS1  8062766  MYBL2  8063043 8064939 8066384 8068898 8092640 8092750 8096875 8102643 8113003  UBE2C TMX4 GTSF1L HIST1H2BK RFC4 FGF12 ENPEP CCNA2 FLJ11292  Gene Name  FDR  Hypothetical locus FLJ32742 Hypothetical LOC339524 G-protein signaling modulator 2 Chromosome 1 open reading frame 21 Denticleless homolog (Drosophila) Centromere protein F, 350/400kda (mitosin) CD160 molecule Chromosome 10 open reading frame 116 Centrosomal protein 55kda Rho gtpase activating protein 42 Solute carrier family 22 (organic cation transporter), member 18 antisense MAS-related GPR, member G Coiled-coil domain containing 63 Gametocyte specific factor 1 Small nucleolar RNA, C/D box 8 Immunoglobulin heavy variable 4-31 Nucleolar and spindle associated protein 1 Protein tyrosine phosphatase-like A domain containing 1 Fanconi anemia, complementation group I Acyl-coa synthetase bubblegum family member 1 Protein regulator of cytokinesis 1 Small nucleolar RNA, C/D box 60 Nerve growth factor receptor Thymidylate synthetase Iglon family member 5 Epoxide hydrolase 3 Tripartite motif containing 54 Small Cajal body-specific RNA 5 Reprimo, TP53 dependent G2 arrest mediator candidate GINS complex subunit 1 (Psf1 homolog) V-myb myeloblastosis viral oncogene homolog (avian)like 2 Ubiquitin-conjugating enzyme E2C Thioredoxin-related transmembrane protein 4 Gametocyte specific factor 1-like Histone cluster 1, h2bk Replication factor C (activator 1) 4, 37kda Fibroblast growth factor 12 Glutamyl aminopeptidase (aminopeptidase A) Cyclin A2 Hypothetical protein FLJ11292  2.21E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01  150  Probe Set ID 8116707 8117395 8117422 8121784 8124385  Gene Symbol KU-MEL-3 HIST1H2BF HIST1H4F FABP7 HIST1H4B  8126244  LRFN2  8129880 8132743 8132811 8132860 8139796 8152962 8160033 8180273 7901913  PERP ABCA13 C7orf72 EGFR LOC441233 LRRC6 SNRPE PCDHA12 FOXD3  7904429  HSD3BP4  7904465 7912629 7921840 7923562 7926638 7927710 7929674 7934959 7937868 7938008 7938082 7938348 7944797 7947110 7948107 7959761 7961111 7964535 7967386 7968062 7969243  HIST2H2BA KAZN NR1I3 CHIT1 ARMC3 CDK1 C10orf62 MIR107 C11orf36 OR52D1 CNGA4 WEE1 OR10G4 E2F8 OR5W2 FAM101A CLEC1A CYP27B1 MPHOSPH9 ATP12A CKAP2 LOC1002882 08 ASB2  7972018 7981020  Gene Name  FDR  Ku-mel-3 Histone cluster 1, h2bf Histone cluster 1, h4f Fatty acid binding protein 7, brain Histone cluster 1, h4b Leucine rich repeat and fibronectin type III domain containing 2 PERP, TP53 apoptosis effector ATP-binding cassette, sub-family A (ABC1), member 13 Chromosome 7 open reading frame 72 Epidermal growth factor receptor Hypothetical LOC441233 Leucine rich repeat containing 6 Small nuclear ribonucleoprotein polypeptide E Protocadherin alpha 12 Forkhead box D3 Hydroxy-delta-5-steroid dehydrogenase, 3 beta, pseudogene 4 Histone cluster 2, h2ba Kazrin, periplakin interacting protein Nuclear receptor subfamily 1, group I, member 3 Chitinase 1 (chitotriosidase) Armadillo repeat containing 3 Cyclin-dependent kinase 1 Chromosome 10 open reading frame 62 Microrna 107 Chromosome 11 open reading frame 36 Olfactory receptor, family 52, subfamily D, member 1 Cyclic nucleotide gated channel alpha 4 WEE1 homolog (S. Pombe) Olfactory receptor, family 10, subfamily G, member 4 E2F transcription factor 8 Olfactory receptor, family 5, subfamily W, member 2 Family with sequence similarity 101, member A C-type lectin domain family 1, member A Cytochrome P450, family 27, subfamily B, polypeptide 1 M-phase phosphoprotein 9 Atpase, H+/K+ transporting, nongastric, alpha polypeptide Cytoskeleton associated protein 2  2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01  Hypothetical protein LOC100288208  2.45E-01  Ankyrin repeat and SOCS box containing 2  2.45E-01  2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.34E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01  151  Probe Set ID 7982271 7982287  Gene Symbol GOLGA8IP ARHGAP11B  7983490  HMGN2P46  7989657 8001402 8013671 8018849 8025237 8025470 8026503 8026631 8036270 8043890 8053753 8055143 8055606 8060503 8060813 8061303 8079590 8089714  CSNK1G1 CHD9 SPAG5 TK1 KIAA1543 OR7D2 FLJ25328 F2RL3 THAP8 NMS TEKT4 LOC440905 GTDC1 SNORD57 MCM8 INSM1 CAMP LSAMP  8098576  SLC25A4  8100827  IGJ  8108716 8112260 8114470 8114511 8117334 8117408 8124437 8124521 8126095 8127346 8132642 8135224 8136837 8138765 8141846 8144982  PCDHB16 DEPDC1B LRRTM2 MZB1 HIST1H4A HIST1H2AE HIST1H3F HIST1H4K C6orf129 RAB23 PPIA NFE4 OR6V1 HOXA11 FBXL13 NPM2  Gene Name  FDR  Golgin A8 family, member I (pseudogene) Rho gtpase activating protein 11B High-mobility group nucleosomal binding domain 2 pseudogene 46 Casein kinase 1, gamma 1 Chromodomain helicase DNA binding protein 9 Sperm associated antigen 5 Thymidine kinase 1, soluble Kiaa1543 Olfactory receptor, family 7, subfamily D, member 2 Hypothetical LOC148231 Coagulation factor II (thrombin) receptor-like 3 THAP domain containing 8 Neuromedin S Tektin 4 Hypothetical LOC440905 Glycosyltransferase-like domain containing 1 Small nucleolar RNA, C/D box 57 Minichromosome maintenance complex component 8 Insulinoma-associated 1 Cathelicidin antimicrobial peptide Limbic system-associated membrane protein Solute carrier family 25 (mitochondrial carrier; adenine nucleotide translocator), member 4 Immunoglobulin J polypeptide, linker protein for immunoglobulin alpha and mu polypeptides Protocadherin beta 16 DEP domain containing 1B Leucine rich repeat transmembrane neuronal 2 Marginal zone B and B1 cell-specific protein Histone cluster 1, h4a Histone cluster 1, h2ae Histone cluster 1, h3f Histone cluster 1, h4k Chromosome 6 open reading frame 129 RAB23, member RAS oncogene family Peptidylprolyl isomerase A (cyclophilin A) Transcription factor NF-E4 Olfactory receptor, family 6, subfamily V, member 1 Homeobox A11 F-box and leucine-rich repeat protein 13 Nucleophosmin/nucleoplasmin 2  2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01  152  Probe Set ID 8146649 8150433  Gene Symbol MTFR1 NKX6-3  8151032  GGH  8155214 8158081 8158167 8168976 8171867 8171885 8175629 8180255 8180321 7896863 7898616 7905496 7905505 7919584 7921275 7922174 7924096 7924821 7937404 7939897 7940626 7947694 7973105  MELK C9orf117 LCN2 GPRASP2 ARX DCAF8L1 MAGEA11 HIST2H4B HIST2H4A MIR429 PLA2G2F C1orf46 LCE2B HIST2H2BF FCRL3 F5 NEK2 ZNF847P C11orf35 FOLH1 SCGB2A1 CKAP5 RNASE3  7973797  COCH  7979307 7979963 7981718  DLGAP5 DPF3 IGHM LOC1004992 21 TBX6 ALOX15B C20orf191 MIR132 MIR320C1 BIRC8 LOC1001313 73 ICOS  7982333 8000779 8004784 8005733 8011218 8020419 8039078 8040469 8047702  Gene Name  FDR  Mitochondrial fission regulator 1 NK6 homeobox 3 Gamma-glutamyl hydrolase (conjugase, folylpolygammaglutamyl hydrolase) Maternal embryonic leucine zipper kinase Chromosome 9 open reading frame 117 Lipocalin 2 G protein-coupled receptor associated sorting protein 2 Aristaless related homeobox DDB1 and CUL4 associated factor 8-like 1 Melanoma antigen family A, 11 Histone cluster 2, h4b Histone cluster 2, h4a Microrna 429 Phospholipase A2, group IIF Chromosome 1 open reading frame 46 Late cornified envelope 2B Histone cluster 2, h2bf Fc receptor-like 3 Coagulation factor V (proaccelerin, labile factor) NIMA (never in mitosis gene a)-related kinase 2 Zinc finger protein 847, pseudogene Chromosome 11 open reading frame 35 Folate hydrolase (prostate-specific membrane antigen) 1 Secretoglobin, family 2A, member 1 Cytoskeleton associated protein 5 Ribonuclease, rnase A family, 3 Coagulation factor C homolog, cochlin (Limulus polyphemus) Discs, large (Drosophila) homolog-associated protein 5 D4, zinc and double PHD fingers, family 3 Immunoglobulin heavy constant mu  2.45E-01 2.45E-01  Hypothetical LOC100499221  2.76E-01  T-box 6 Arachidonate 15-lipoxygenase, type B Nuclear receptor co-repressor 1 pseudogene Microrna 132 Microrna 320c-1 Baculoviral IAP repeat containing 8  2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01  Hypothetical LOC100131373  2.76E-01  Inducible T-cell co-stimulator  2.76E-01  2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.45E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01  153  Probe Set ID 8062444 8068496 8070933 8071086 8083897 8085287 8086689 8101031 8103728 8112902 8124388 8130785 8131949 8133728 8134263  Gene Symbol BPI SIM2 FTCD CECR2 TMEM212 C3orf10 MYL3 CDKL2 HMGB2 DHFR HIST1H3B GPR31 CBX3 ZP3 COL1A2  8138547  TOMM7  8138977 8144625 8146357 8149774 8151709 8152715 8160284 8163107 8163892 8164200 8166665 8166705  DPY19L1 BLK MCM4 LOXL2 OSGIN2 KLHL38 HAUS6 MIR32 C9orf31 ANGPTL2 FAM47B PRRG1  8168416  USMG5  8176336  ASMTL-AS1  Gene Name  FDR  Bactericidal/permeability-increasing protein Single-minded homolog 2 (Drosophila) Formiminotransferase cyclodeaminase Cat eye syndrome chromosome region, candidate 2 Transmembrane protein 212 Chromosome 3 open reading frame 10 Myosin, light chain 3, alkali; ventricular, skeletal, slow Cyclin-dependent kinase-like 2 (CDC2-related kinase) High-mobility group box 2 Dihydrofolate reductase Histone cluster 1, h3b G protein-coupled receptor 31 Chromobox homolog 3 Zona pellucida glycoprotein 3 (sperm receptor) Collagen, type I, alpha 2 Translocase of outer mitochondrial membrane 7 homolog (yeast) Dpy-19-like 1 (C. Elegans) B lymphoid tyrosine kinase Minichromosome maintenance complex component 4 Lysyl oxidase-like 2 Oxidative stress induced growth inhibitor family member 2 Kelch-like 38 (Drosophila) HAUS augmin-like complex, subunit 6 Microrna 32 Chromosome 9 open reading frame 31 Angiopoietin-like 2 Family with sequence similarity 47, member B Proline rich Gla (G-carboxyglutamic acid) 1 Up-regulated during skeletal muscle growth 5 homolog (mouse) ASMTL antisense RNA 1 (non-protein coding)  2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01 2.76E-01  154  

Cite

Citation Scheme:

        

Citations by CSL (citeproc-js)

Usage Statistics

Share

Embed

Customize your widget with the following options, then copy and paste the code below into the HTML of your page to embed this item in your website.
                        
                            <div id="ubcOpenCollectionsWidgetDisplay">
                            <script id="ubcOpenCollectionsWidget"
                            src="{[{embed.src}]}"
                            data-item="{[{embed.item}]}"
                            data-collection="{[{embed.collection}]}"
                            data-metadata="{[{embed.showMetadata}]}"
                            data-width="{[{embed.width}]}"
                            async >
                            </script>
                            </div>
                        
                    
IIIF logo Our image viewer uses the IIIF 2.0 standard. To load this item in other compatible viewers, use this url:
http://iiif.library.ubc.ca/presentation/dsp.24.1-0103454/manifest

Comment

Related Items