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

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  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 ii  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 iii  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 post- challenge 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. iv  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. v  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 vi    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 vii    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 viii   Appendix 8 Eosinophil-Correlated Probe Sets Significantly Higher-Expressed in DR than ER, Post-Allergen Inhalation Challenge (FDR≤0.30) .................. 148  ix  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 x  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 Post- Allergen Challenge .................................................................................. 75 Figure 4.4 Linoleic Acid Metabolism ......................................................................... 80 xi  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. xii  DEDICATION   To my family and friends, who have always believed in me. 1  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 2  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). 3  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/ 4  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 over- dosage.  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 5  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 6  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. 7  Figure 1.2 — Typical Response Profiles after Allergen Inhalation Challenge.   After AIC, subjects typically display one of three lung function profiles, as assessed by FEV1 measurements.  (a) An isolated early response, (b) an isolated late response, and (c) a dual 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  Figure 1.  Common patterns of response following allergen inhalation challenge.  (a) Isolated early asthmatic response (EAR); (b) isolated late asthmatic response (LAR); (c) dual response.  (From Varner & Lemanske, 2000.) 8  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 9  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 10  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. 11  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. 12  Figure 1.3 — Mechanisms of the Early and Late Response.   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  Early Phase Late Phase Other inflammatory cells Bronchoconstriction 13  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 (RT- qPCR).  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, genome- wide 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 14  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 whole- blood 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 15  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 post- challenge data.  A concluding chapter summarizes the overall findings, future directions, and implications of the results. 16  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 17  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. 18  Table 2.1 — Subject Demographics (Pre versus Post). Cohort Subject Site Age (yr) Sex Mch PC20 a  (mg/ml) Allergen b  % Fall in FEV1 (EAR) % Fall in FEV1 (LAR) PAXgene (4 Subjects) 1 VGH 36 M 3.2 Timothy Grass -61 -38 2 VGH 35 F 0.64 Timothy Grass -27 -5 3 VGH 47 M 0.28 Orchard Grass -23 -17 4 McM 21 F 1.09 HDMDP -32.1 -12.5  EDTA (5 Subjects) 5 McM 20 F 9.62 Cat -37.7 -17.3 6 McM 27 F 1.45 HDMDP -43.3 -16.7 7 McM 23 M 10.9 Cat -31.4 -15.1 8 McM 60 F 2.19 Cat -25.5 -6.7 9 McM 22 M 4.28 HDMDP -22.7 -19.9  PAXgene Validation (7 Subjects) 10 VGH 42 M 0.13 Cat -23 -9 11 VGH 41 M 1 Grass Mix -21 -7 11R c  VGH 41 M 0.69 Grass Mix -42 -31 12 VGH 52 F N/A Cat -33 -27 13 McM 21 F 6.96 Ragweed -26.9 0 14 McM 33 M 3.17 HDMDP -29.5 -19.7 15 McM 18 F 27.86 HDMDP -46.4 -25.9 16 McM 21 F 4.72 Cat -20 -20  Lipids and Oxidative Molecules (8 Subjects) 1 VGH 36 M 3.2 Timothy Grass -61 -38 2 VGH 35 F 0.64 Timothy Grass -27 -5 3 VGH 47 M 0.28 Orchard Grass -23 -17 10 VGH 42 M 0.13 Cat -23 -9 13 McM 21 F 6.96 Ragweed -26.9 0 14 McM 33 M 3.17 HDMDP -29.5 -19.7 15 McM 18 F 27.86 HDMDP -46.4 -25.9 16 McM 21 F 4.72 Cat -20 -20  a Methacholine PC20. b HDMDP=House dust mite (Dermatophagoides pteronyssinus). c Subject 11 received a repeated allergen inhalation challenge one month later. 19  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).  20  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-3- phosphate dehydrogenase (GAPDH) and Phosphoglycerokinase (PGK1), were selected based on their low coefficient of variation (CV) values across all samples in the 21  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 22  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 23  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, two- tailed 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 24  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 25  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). 26  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. 27  Table 2.2 — Nine Differentially Expressed Genes in Nrf2-Mediated Oxidative Stress Response Pathway. Probe Set ID 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  a P values were not corrected for multiple testing. 28  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 one- tailed 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. 29  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. 30  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 pre- and 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. 31  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 32  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 RT- qPCR 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 33  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. 34  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 35  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. 36  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. 37  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 38  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 39  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 non- allergic individuals.  These three males and three females were age-matched as closely as possible with the subjects in the atopic asthmatic cohort. 40  Table 3.1 — Subject Demographics (CCL2). Cohort Sub- groups # Subjects # Challenges Site (# Challenges) Mean Age Sex (M:F) Allergen (# Challenges) Responsese (# Challenges) Atopic Asthma (n=39) 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  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. 41  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 (non- responder). 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 42  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 43  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 44  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 one- tailed t-test, assuming that the directionality of change would replicate. Significance cut- off 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 45  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 46  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 post- plicatic 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 post- challenge, 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). 47  Figure 3.1 — Plasma CCL2 Levels at Pre- and Post-Allergen Challenge. a) Dot Plot Representations Cat Allergen* Grass Allergen*    HDM Allergen Methacholine    48  Plicatic Acid* Ragweed Allergen*     Controls*      9 AM 12 Noon 49  b) Histogram Representation  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. CCL2 C C L 2  50  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 51  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. 52  Figure 3.2 — Baseline CCL2 Level and Age Association.   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). Age B a s e lin e  C C L 2  ( p g /m L ) 53  Figure 3.3 — Baseline CCL2 Level with Age in Allergen Cohorts.     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). Age B a s e lin e  C C L 2  ( p g /m L ) 54  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 55  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 56  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 non- atopic 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, 57  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 time- course 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).  Garcia- Alonso 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 58  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 down- regulation was also observed in healthy control subjects, indicating that the decrease in 59  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. 60  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 pre- and 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 61  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 62  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. 63  Table 4.1 — Subject Demographics (ER versus DR). Response Subject Site Age (yr) Sex Pre Mch PC20 a,b (mg/ml) Post Mch PC20 a,b (mg/ml) Allergen % Fall in FEV1 (EAR) % Fall in FEV1 (LAR) Isolated Early Responders (n=8) 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 Mean ± SEM  32.6 ± 2.2 3:5 2.82  7.50  29.6 ± 3.4 5.1 ± 1.5    Dual Responders (n=6) 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 Mean ± SEM  33.8 ± 5.3 1:5 1.27 0.51  34.7 ± 3.2 21.3 ± 3.2  a Methacholine PC20 was taken one day pre- and one day post-allergen inhalation challenge. b Geometric means were calculated separately for the ER and the DR groups. 64  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 65  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 post- challenge 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 type- specific 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. 66  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 pre- and 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 67  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). 68  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 FEV1 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. 69  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 70  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 Kallikrein- 1 (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). 71  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.  72  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. 73  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. 74  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. 75  Figure 4.3 — SAM and csSAM Results for the Analysis of ER versus DR at Post- Allergen 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  76  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. 77  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 78  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 79  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. 80  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. 81  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 post- AIC.  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 82  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.  83  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. 84  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 85  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. 86  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. 87  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 pre- and 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.  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Cell. 2009 Jan 23;136(2):215–33.   100  APPENDICES Appendix 1 — Sequences of Probes and Primers used in RT-qPCR Gene Component No. of Bases Sequencea ABCC1 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/ CUL3 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/ DNAJA2 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/ DNAJC1 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/ DNAJC19 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/ DNAJC21 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/ PTPLAD1 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/  101  Gene Component No. of Bases Sequence* KRAS 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/ SOD1 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/ GAPDH 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/ PGK1 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/ GUSB 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/  a ZEN = Internal ZEN quencher 102  Appendix 2 — Differentially Expressed Probe Sets, Post- versus Pre-Allergen Inhalation Challenge (p≤0.01 and fold change≥1.1) Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 8112310 --- --- --- 1.03E-05 -1.26567 8150592 CEBPD CCAAT/enhancer binding protein (C/EBP), delta NM_005195 1.72E-05 -1.20166 7936968 ADAM12 ADAM metallopeptidase domain 12 NM_003474 2.96E-05 -1.14475 8030804 CD33 CD33 molecule NM_001772 4.37E-05 -1.27568 7989193 --- --- --- 7.21E-05 1.51098 8068305 ITSN1 Intersectin 1 (SH3 domain protein) NM_003024 9.00E-05 -1.17278 8079060 VIPR1 Vasoactive intestinal peptide receptor 1 NM_004624 1.50E-04 -1.13714 8151281 TRAM1 Translocation associated membrane protein 1 NM_014294 1.77E-04 1.19815 8032275 MBD3 Methyl-cpg binding domain protein 3 NM_003926 1.97E-04 -1.10751 8070714 --- --- --- 2.06E-04 1.28628 8029136 CD79A CD79a molecule, immunoglobulin-associated alpha NM_001783 2.42E-04 1.12324 7923442 SYT2 Synaptotagmin II NM_177402 3.16E-04 -1.18247 7902512 DNAJB4 Dnaj (Hsp40) homolog, subfamily B, member 4 NM_007034 3.42E-04 1.36707 8120579 C6orf57 Chromosome 6 open reading frame 57 NM_145267 3.55E-04 1.13744 8157686 OR1L4 Olfactory receptor, family 1, subfamily L, member 4 NM_001005235 3.63E-04 -1.15665 8038126 CA11 Carbonic anhydrase XI NM_001217 3.69E-04 -1.14335 8076169 NPTXR Neuronal pentraxin receptor NM_014293 3.70E-04 -1.11711 8000779 TBX6 T-box 6 NM_004608 3.87E-04 -1.12436 7966517 C12orf51 Chromosome 12 open reading frame 51 NM_001109662 3.95E-04 -1.11606 8036072 KRTDAP Keratinocyte differentiation-associated protein NM_207392 4.10E-04 -1.30462 8140967 SAMD9 Sterile alpha motif domain containing 9 NM_017654 4.29E-04 1.48976 7968926 --- --- --- 4.69E-04 -1.3093 8070953 C21orf56 Chromosome 21 open reading frame 56 NM_001142854 4.79E-04 -1.12526 8108330 KDM3B Lysine (K)-specific demethylase 3B NM_016604 4.98E-04 -1.19477 8165486 TMEM203 Transmembrane protein 203 NM_053045 5.09E-04 1.13055 103  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 8092541 LIPH Lipase, member H NM_139248 5.17E-04 -1.21411 7975713 FCF1 FCF1 small subunit (SSU) processome component homolog NM_015962 5.25E-04 1.25408 7997726 FOXF1 Forkhead box F1 NM_001451 5.40E-04 -1.246 7993478 ABCC1 ATP-binding cassette, sub-family C (CFTR/MRP), member 1 NM_004996 5.41E-04 -1.16902 8022711 DSC2 Desmocollin 2 NM_024422 5.43E-04 -1.11312 8043840 LIPT1 Lipoyltransferase 1 NM_145197 5.79E-04 1.31002 7963689 NPFF Neuropeptide FF-amide peptide precursor NM_003717 5.80E-04 -1.11916 7978838 C14orf104 Chromosome 14 open reading frame 104 NM_018139 6.09E-04 1.16651 7978343 CMA1 Chymase 1, mast cell NM_001836 6.34E-04 -1.25589 8157141 ACTL7A Actin-like 7A NM_006687 6.93E-04 -1.17691 8106743 VCAN Versican NM_004385 7.30E-04 -1.44049 8065596 PDRG1 P53 and DNA-damage regulated 1 NM_030815 7.34E-04 1.2478 7921955 RXRG Retinoid X receptor, gamma NM_006917 7.35E-04 -1.16363 7941269 LOC100291851 Similar to Putative ubiquitin-like protein FU ENST000003097 75 7.38E-04 -1.13759 7929288 EXOC6 Exocyst complex component 6 NM_019053 7.57E-04 1.1611 7934133 PPA1 Pyrophosphatase (inorganic) 1 NM_021129 7.65E-04 1.23236 7911343 UIMC1 Ubiquitin interaction motif containing 1 AF284753 7.79E-04 -1.16777 8165703 UIMC1 Ubiquitin interaction motif containing 1 AF284753 7.79E-04 -1.16777 8145470 DPYSL2 Dihydropyrimidinase-like 2 NM_001386 7.90E-04 -1.24796 7925720 OR2C3 Olfactory receptor, family 2, subfamily C, member 3 NM_198074 8.01E-04 -1.21979 7936307 SMNDC1 Survival motor neuron domain containing 1 NM_005871 8.20E-04 1.12645 8012539 PIK3R6 Phosphoinositide-3-kinase, regulatory subunit 6 NM_001010855 8.38E-04 -1.26548 7932512 DNAJC1 Dnaj (Hsp40) homolog, subfamily C, member 1 NM_022365 8.60E-04 1.15399 8122182 TBPL1 TBP-like 1 NM_004865 8.83E-04 1.17923 8160805 C9orf25 Chromosome 9 open reading frame 25 NM_147202 9.11E-04 -1.24083 8097513 MGST2 Microsomal glutathione S-transferase 2 NM_002413 9.26E-04 -1.1378 7949146 SF1 Splicing factor 1 NM_004630 9.32E-04 -1.10772 104  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 8157233 HSDL2 Hydroxysteroid dehydrogenase like 2 NM_032303 9.91E-04 1.13678 8083000 FAIM Fas apoptotic inhibitory molecule NM_001033030 1.01E-03 1.15125 7930487 TECTB Tectorin beta NM_058222 1.04E-03 -1.12094 8049952 C2orf85 Chromosome 2 open reading frame 85 NM_173821 1.05E-03 -1.18451 7940688 POLR2G Polymerase (RNA) II (DNA directed) polypeptide G NM_002696 1.06E-03 1.10543 8030871 ZNF613 Zinc finger protein 613 NM_001031721 1.08E-03 1.3041 8036865 --- --- --- 1.12E-03 1.69279 8076403 NAGA N-acetylgalactosaminidase, alpha NM_000262 1.13E-03 -1.23033 8137979 ACTB Actin, beta NM_001101 1.14E-03 -1.13277 8025984 ZNF844 Zinc finger protein 844 NM_001136501 1.14E-03 1.4582 8144586 MTMR9 Myotubularin related protein 9 NM_015458 1.16E-03 1.23267 8113073 ARRDC3 Arrestin domain containing 3 NM_020801 1.17E-03 1.49373 8081333 --- --- --- 1.18E-03 1.11655 7953428 CD4 CD4 molecule NM_000616 1.20E-03 -1.22191 8111216 LOC391769 Histone cluster 2, H3c pseudogene ENST000004264 11 1.24E-03 -1.16401 8038347 TEAD2 TEA domain family member 2 NM_003598 1.27E-03 -1.14317 7899377 PPP1R8 Protein phosphatase 1, regulatory (inhibitor) subunit 8 NM_138558 1.29E-03 1.14782 8010426 RNF213 Ring finger protein 213 NM_020914 1.30E-03 -1.14256 8066776 TP53RK TP53 regulating kinase NM_033550 1.36E-03 1.18965 7978628 PPP2R3C Protein phosphatase 2 (formerly 2A), regulatory subunit NM_017917 1.38E-03 1.24676 8016452 HOXB4 Homeobox B4 NM_024015 1.40E-03 1.12138 8138363 SOSTDC1 Sclerostin domain containing 1 NM_015464 1.41E-03 -1.17249 8170013 --- --- --- 1.41E-03 -1.3876 8175317 --- --- --- 1.41E-03 -1.3876 7984112 RAB8B RAB8B, member RAS oncogene family NM_016530 1.42E-03 1.15603 8171533 --- --- --- 1.44E-03 1.15697 8125341 AGER Advanced glycosylation end product-specific receptor NM_001136 1.46E-03 -1.1612 7952737 --- --- --- 1.46E-03 -1.16748 8016546 ZNF652 Zinc finger protein 652 NM_014897 1.47E-03 -1.18 105  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 7899173 DHDDS Dehydrodolichyl diphosphate synthase NM_024887 1.47E-03 1.11766 8151525 PMP2 Peripheral myelin protein 2 NM_002677 1.57E-03 -1.18956 7901895 ATG4C ATG4 autophagy related 4 homolog C (S. Cerevisiae) NM_032852 1.58E-03 1.32368 8118571 PSMB9 Proteasome (prosome, macropain) subunit, beta type, 9 NM_002800 1.62E-03 1.13513 8178211 PSMB9 Proteasome (prosome, macropain) subunit, beta type, 9 NM_002800 1.62E-03 1.13513 8179495 PSMB9 Proteasome (prosome, macropain) subunit, beta type, 9 NM_002800 1.62E-03 1.13513 8153920 ZNF250 Zinc finger protein 250 NM_021061 1.62E-03 1.12214 7964745 TMBIM4 Transmembrane BAX inhibitor motif containing 4 NM_016056 1.66E-03 1.15701 8163948 RBM18 RNA binding motif protein 18 NM_033117 1.66E-03 1.24803 8151254 NCOA2 Nuclear receptor coactivator 2 NM_006540 1.70E-03 -1.10391 8146669 TRIM55 Tripartite motif-containing 55 NM_033058 1.70E-03 -1.12018 7946569 RNF141 Ring finger protein 141 NM_016422 1.72E-03 1.2994 7930537 TCF7L2 Transcription factor 7-like 2 (T-cell specific) NM_001146274 1.72E-03 -1.3209 8169949 MST4 Serine/threonine protein kinase MST4 NM_016542 1.79E-03 1.10567 8061685 TM9SF4 Transmembrane 9 superfamily protein member 4 NM_014742 1.81E-03 -1.11646 8041000 GPN1 GPN-loop gtpase 1 NM_007266 1.90E-03 1.12161 7972428 OXGR1 Oxoglutarate (alpha-ketoglutarate) receptor 1 NM_080818 1.90E-03 -1.24016 7935425 RRP12 Ribosomal RNA processing 12 homolog (S. Cerevisiae) NM_015179 1.91E-03 -1.17084 7987180 C15orf29 Chromosome 15 open reading frame 29 NM_024713 1.91E-03 1.20996 7961453 --- --- --- 1.94E-03 -1.18735 7995258 ZNF267 Zinc finger protein 267 NM_003414 2.00E-03 1.36448 7948364 MPEG1 Macrophage expressed 1 NM_001039396 2.03E-03 -1.20873 8104760 TARS Threonyl-trna synthetase NM_152295 2.04E-03 1.14868 8075390 SEC14L4 SEC14-like 4 (S. Cerevisiae) NM_174977 2.06E-03 -1.17798 7913776 IL28RA Interleukin 28 receptor, alpha (interferon, lambda receptor) NM_170743 2.22E-03 -1.1591 7967810 GOLGA3 Golgin A3 NM_005895 2.25E-03 -1.12119 8106429 AGGF1 Angiogenic factor with G patch and FHA domains 1 NM_018046 2.27E-03 1.17784 8156519 MIRLET7A1 Microrna let-7a-1 NR_029476 2.27E-03 1.46682 8047505 FLJ39061 Hypothetical protein FLJ39061 BC118982 2.29E-03 1.30762 106  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 8081953 GTF2E1 General transcription factor IIE, polypeptide 1, alpha 56 NM_005513 2.31E-03 1.25709 8042993 CTNNA2 Catenin (cadherin-associated protein), alpha 2 NM_004389 2.31E-03 -1.20376 7967082 --- --- --- 2.31E-03 -1.28529 8028213 ZNF568 Zinc finger protein 568 NM_198539 2.33E-03 1.29579 7929768 CUTC Cutc copper transporter homolog (E. Coli) NM_015960 2.33E-03 1.1695 7981335 HSP90AA1 Heat shock protein 90kda alpha (cytosolic), class A NM_001017963 2.33E-03 1.25236 8003075 --- --- --- 2.35E-03 -1.18137 8022892 ZNF396 Zinc finger protein 396 NM_145756 2.36E-03 1.21188 7918487 DENND2D Denn NM_024901 2.37E-03 1.11399 8154283 --- --- --- 2.37E-03 1.18639 8055909 --- --- --- 2.37E-03 -1.15294 8126147 C6orf64 Chromosome 6 open reading frame 64 BC022007 2.39E-03 1.27922 7985695 AKAP13 A kinase (PRKA) anchor protein 13 NM_006738 2.42E-03 -1.17961 8139706 SEC61G Sec61 gamma subunit NM_014302 2.45E-03 1.28001 8025998 ZNF136 Zinc finger protein 136 NM_003437 2.47E-03 1.34469 8081343 RG9MTD1 RNA (guanine-9-) methyltransferase domain containing 1 NM_017819 2.47E-03 1.19456 8169701 MCTS1 Malignant T cell amplified sequence 1 NM_014060 2.49E-03 1.31653 8147461 SDC2 Syndecan 2 NM_002998 2.50E-03 -1.17103 7981290 WARS Tryptophanyl-trna synthetase NM_004184 2.51E-03 -1.12132 7983763 MAPK6 Mitogen-activated protein kinase 6 NM_002748 2.52E-03 1.3585 8035793 ZNF737 Zinc finger protein 737 NM_001159293 2.57E-03 1.64101 7960553 MRPL51 Mitochondrial ribosomal protein L51 NM_016497 2.58E-03 1.14919 7912622 LRRC38 Leucine rich repeat containing 38 ENST000003760 85 2.59E-03 -1.11591 8087985 GLT8D1 Glycosyltransferase 8 domain containing 1 NM_001010983 2.65E-03 1.1045 8130032 FBXO30 F-box protein 30 NM_032145 2.65E-03 1.21992 8162294 SPTLC1 Serine palmitoyltransferase, long chain base subunit 1 NM_006415 2.65E-03 1.10764 7977820 PRMT5 Protein arginine methyltransferase 5 NM_001039619 2.65E-03 -1.1109 8158976 CEL Carboxyl ester lipase (bile salt-stimulated lipase) NM_001807 2.67E-03 -1.12395 8101844 ADH5 Alcohol dehydrogenase 5 (class III), chi polypeptide NM_000671 2.68E-03 1.21997 107  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 8116867 TMEM14B Transmembrane protein 14B NM_030969 2.70E-03 1.17658 8005785 KSR1 Kinase suppressor of ras 1 NM_014238 2.72E-03 -1.31962 8143247 KIAA1549 Kiaa1549 NM_020910 2.74E-03 -1.17018 8135214 --- --- --- 2.75E-03 1.10153 8134470 TRRAP Transformation/transcription domain-associated protein NM_003496 2.76E-03 -1.17021 8111552 C5orf33 Chromosome 5 open reading frame 33 NM_001085411 2.78E-03 1.26942 7955179 TUBA1C Tubulin, alpha 1c NM_032704 2.80E-03 -1.17772 8040552 NCOA1 Nuclear receptor coactivator 1 NM_147223 2.82E-03 -1.1738 8149942 CCDC25 Coiled-coil domain containing 25 NM_018246 2.84E-03 1.14967 7998952 TIGD7 Tigger transposable element derived 7 NM_033208 2.87E-03 1.43642 8106999 C5orf27 Chromosome 5 open reading frame 27 NR_026936 2.89E-03 -1.20616 8176576 --- --- --- 2.91E-03 1.31481 7900426 SMAP2 Small arfgap2 NM_022733 2.91E-03 -1.24032 7956470 MBD6 Methyl-cpg binding domain protein 6 NM_052897 2.93E-03 -1.243 8104746 NPR3 Natriuretic peptide receptor C/guanylate cyclase C (atriona) NM_000908 2.95E-03 -1.19369 8096361 HERC5 Hect domain and RLD 5 NM_016323 3.08E-03 1.2598 8008870 TMEM49 Transmembrane protein 49 NM_030938 3.09E-03 1.13606 8102162 INTS12 Integrator complex subunit 12 NM_020395 3.10E-03 1.22349 8028991 CYP2S1 Cytochrome P450, family 2, subfamily S, polypeptide 1 NM_030622 3.12E-03 -1.1428 7961083 CLEC2B C-type lectin domain family 2, member B NM_005127 3.13E-03 1.43407 7983606 EID1 EP300 interacting inhibitor of differentiation 1 NM_014335 3.17E-03 1.207 8130674 PDE10A Phosphodiesterase 10A NM_006661 3.20E-03 1.15849 8006298 RAB11FIP4 RAB11 family interacting protein 4 (class II) NM_032932 3.20E-03 -1.10213 8001185 DNAJA2 Dnaj (Hsp40) homolog, subfamily A, member 2 NM_005880 3.21E-03 1.17375 8068593 ETS2 V-ets erythroblastosis virus E26 oncogene homolog 2 (avian) NM_005239 3.21E-03 -1.17137 8003861 SPNS3 Spinster homolog 3 (Drosophila) NM_182538 3.23E-03 -1.14045 8150757 RB1CC1 RB1-inducible coiled-coil 1 NM_014781 3.23E-03 1.2585 8012416 C17orf44 Chromosome 17 open reading frame 44 NR_026951 3.23E-03 1.15166 7907090 LOC100128751 Inm04 AY194294 3.24E-03 -1.13747 108  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 8095360 --- --- --- 3.26E-03 1.21952 8119974 SLC29A1 Solute carrier family 29 (nucleoside transporters), m NM_001078175 3.28E-03 -1.21406 8000746 --- --- --- 3.29E-03 -1.72316 8103859 DCTD Dcmp deaminase NM_001012732 3.31E-03 1.16184 8071107 SLC25A18 Solute carrier family 25 (mitochondrial carrier), membe NM_031481 3.34E-03 -1.23484 8009713 OTOP3 Otopetrin 3 NM_178233 3.34E-03 -1.17842 8175169 RAP2C RAP2C, member of RAS oncogene family NM_021183 3.37E-03 1.10334 8109350 SLC36A1 Solute carrier family 36 (proton/amino acid symporter) NM_078483 3.37E-03 -1.18422 7951652 --- --- --- 3.39E-03 -1.30607 7916130 KTI12 KTI12 homolog, chromatin associated (S. Cerevisiae) NM_138417 3.48E-03 1.23518 8013331 B9D1 B9 protein domain 1 NM_015681 3.51E-03 -1.17347 8135544 FOXP2 Forkhead box P2 NM_148898 3.51E-03 1.25093 7999171 --- --- --- 3.52E-03 -1.23007 8152133 RRM2B Ribonucleotide reductase M2 B (TP53 inducible) NM_015713 3.53E-03 1.26378 8175558 SPANXE SPANX family, member E NM_145665 3.58E-03 1.11203 8038839 SIGLEC8 Sialic acid binding Ig-like lectin 8 NM_014442 3.58E-03 -1.4403 8162669 ZNF322A Zinc finger protein 322A NM_024639 3.58E-03 1.29728 8038305 NTF4 Neurotrophin 4 NM_006179 3.60E-03 -1.23748 8081055 CHMP2B Chromatin modifying protein 2B NM_014043 3.61E-03 1.27483 8102817 ELF2 E74-like factor 2 (ets domain transcription factor) NM_201999 3.61E-03 1.13295 8151906 GDF6 Growth differentiation factor 6 NM_001001557 3.65E-03 -1.23203 7944359 --- --- --- 3.69E-03 1.20255 8130765 FAM103A1 Family with sequence similarity 103, member A1 BC112329 3.69E-03 1.12894 7972055 KCTD12 Potassium channel tetramerisation domain containing 12 NM_138444 3.71E-03 -1.23263 7940000 OR5AK2 Olfactory receptor, family 5, subfamily AK, member 2 NM_001005323 3.75E-03 -1.50096 8171747 EIF1AX Eukaryotic translation initiation factor 1A, X-linked NM_001412 3.79E-03 1.30772 7972711 --- --- --- 3.81E-03 1.18899 8001496 NUDT21 Nudix (nucleoside diphosphate linked moiety X)-type motif NM_007006 3.83E-03 1.12702 8169294 COL4A5 Collagen, type IV, alpha 5 NM_000495 3.84E-03 -1.11804 109  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 7960666 ZNF384 Zinc finger protein 384 NM_133476 3.84E-03 -1.10853 8030978 ZNF845 Zinc finger protein 845 NM_138374 3.85E-03 1.88412 7999936 UMOD Uromodulin NM_003361 3.85E-03 -1.11571 8113591 PGGT1B Protein geranylgeranyltransferase type I, beta subunit NM_005023 3.87E-03 1.24213 7925511 PLD5 Phospholipase D family, member 5 NM_152666 3.90E-03 -1.32485 8043480 --- --- --- 3.92E-03 1.10136 8059578 --- --- --- 3.93E-03 -1.7047 8025058 TRIP10 Thyroid hormone receptor interactor 10 NM_004240 3.94E-03 -1.10619 8040843 CAD Carbamoyl-phosphate synthetase 2, aspartate transcarbamylase NM_004341 3.94E-03 -1.16946 8115476 MED7 Mediator complex subunit 7 NM_004270 3.95E-03 1.32722 8080853 --- --- --- 3.95E-03 -1.15156 8175302 FAM127B Family with sequence similarity 127, member B NM_001078172 3.96E-03 -1.15817 8033789 ZNF121 Zinc finger protein 121 NM_001008727 3.96E-03 1.23886 7929072 IFIT5 Interferon-induced protein with tetratricopeptide repeats NM_012420 3.98E-03 1.42628 8096753 HADH Hydroxyacyl-coa dehydrogenase NM_005327 3.99E-03 1.1301 8039484 IL11 Interleukin 11 NM_000641 3.99E-03 -1.13164 7978570 SNX6 Sorting nexin 6 NM_021249 3.99E-03 1.2031 7908694 NAV1 Neuron navigator 1 NM_020443 4.00E-03 -1.12593 8137517 HTR5A 5-hydroxytryptamine (serotonin) receptor 5A NM_024012 4.13E-03 -1.10157 8017010 HSF5 Heat shock transcription factor family member 5 NM_001080439 4.16E-03 1.18222 8023591 --- --- --- 4.17E-03 -1.13458 8102362 TIFA TRAF-interacting protein with forkhead-associated domain NM_052864 4.21E-03 1.24717 8150689  --- --- 4.23E-03 -1.58565 8117580 HIST1H2AI Histone cluster 1, h2ai NM_003509 4.24E-03 1.19217 8160870 CCL27 Chemokine (C-C motif) ligand 27 NM_006664 4.27E-03 -1.20421 7925741 OR2T33 Olfactory receptor, family 2, subfamily T, member 33 NM_001004695 4.36E-03 -1.14785 7932881 LOC390414 Hypothetical LOC390414 AK094743 4.37E-03 1.12186 7897293 --- --- --- 4.37E-03 -1.19685 8102936 --- --- --- 4.38E-03 -1.27925 110  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 8088979 VGLL3 Vestigial like 3 (Drosophila) NM_016206 4.46E-03 1.14327 7964250 PTGES3 Prostaglandin E synthase 3 (cytosolic) NM_006601 4.47E-03 1.27373 8071877 POM121L9P POM121 membrane glycoprotein-like 9 (rat) pseudogene NR_003714 4.52E-03 1.17563 7931348 FOXI2 Forkhead box I2 NM_207426 4.54E-03 -1.36326 7986010 IQGAP1 IQ motif containing gtpase activating protein 1 NM_003870 4.56E-03 -1.1765 8018972 TIMP2 TIMP metallopeptidase inhibitor 2 AK057217 4.58E-03 -1.29485 8042086 VRK2 Vaccinia related kinase 2 NM_006296 4.60E-03 1.37976 8121861 NCOA7 Nuclear receptor coactivator 7 NM_181782 4.62E-03 1.23347 8102775 --- --- --- 4.68E-03 -1.17632 8041122 PPP1CB Protein phosphatase 1, catalytic subunit, beta isozyme NM_002709 4.69E-03 1.19299 8176698 CYorf15A Chromosome Y open reading frame 15A NM_001005852 4.69E-03 1.30982 8023703 C18orf20 Chromosome 18 open reading frame 20 BC029565 4.71E-03 -1.34055 8094609 FAM114A1 Family with sequence similarity 114, member A1 NM_138389 4.73E-03 -1.24832 8126428 TRERF1 Transcriptional regulating factor 1 NM_033502 4.75E-03 -1.11786 7951807 CADM1 Cell adhesion molecule 1 NM_014333 4.76E-03 1.2536 7943552 AASDHPPT Aminoadipate-semialdehyde dehydrogenase- phosphopantethe NM_015423 4.77E-03 1.23434 7908147 TSEN15 Trna splicing endonuclease 15 homolog (S. Cerevisiae) NM_052965 4.82E-03 1.19128 8177044 --- --- --- 4.84E-03 -1.24861 8115756 KCNMB1 Potassium large conductance calcium-activated channel NM_004137 4.87E-03 -1.1305 8127364 GUSBL2 Glucuronidase, beta-like 2 NR_003660 4.89E-03 1.18323 8174494 --- --- --- 4.92E-03 -1.21063 8031857 ZNF135 Zinc finger protein 135 NM_003436 4.93E-03 1.11346 8146198 POLB Polymerase (DNA directed), beta NM_002690 4.96E-03 1.18361 7938561 --- --- --- 4.96E-03 -1.11715 7959016 NCRNA00173 Non-protein coding RNA 173 NR_027345 4.96E-03 -1.3502 8160405 KLHL9 Kelch-like 9 (Drosophila) NM_018847 5.00E-03 1.21661 7904421 HSD3B1 Hydroxy-delta-5-steroid dehydrogenase, 3 beta- and steroi NM_000862 5.00E-03 -1.18104 7899849 --- --- --- 5.01E-03 -1.11461 7957850 GAS2L3 Growth arrest-specific 2 like 3 NM_174942 5.05E-03 -1.19668 111  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 8101648 HSD17B11 Hydroxysteroid (17-beta) dehydrogenase 11 NM_016245 5.06E-03 1.17003 8127425 LMBRD1 LMBR1 domain containing 1 NM_018368 5.07E-03 1.32028 7910146 PSEN2 Presenilin 2 (Alzheimer disease 4) NM_000447 5.10E-03 -1.14841 8117522 ABT1 Activator of basal transcription 1 NM_013375 5.12E-03 1.13459 8120194 TFAP2B Transcription factor AP-2 beta (activating enhancer binding NM_003221 5.13E-03 -1.29097 8013529 --- --- --- 5.16E-03 1.56883 8137081 --- --- --- 5.16E-03 1.17944 7998367 RPUSD1 RNA pseudouridylate synthase domain containing 1 NM_058192 5.17E-03 -1.16696 8104449 CCT5 Chaperonin containing TCP1, subunit 5 (epsilon) NM_012073 5.17E-03 1.11649 8178771 AGER Advanced glycosylation end product-specific receptor NM_001136 5.18E-03 -1.17383 8011131 RILP Rab interacting lysosomal protein NM_031430 5.20E-03 -1.2329 8094974 OCIAD1 OCIA domain containing 1 NM_017830 5.20E-03 1.14929 8093943 LOC93622 Hypothetical LOC93622 NR_015433 5.22E-03 1.20837 8016366 MRPL10 Mitochondrial ribosomal protein L10 NM_145255 5.23E-03 1.21708 8120378 KIAA1586 Kiaa1586 NM_020931 5.27E-03 1.37772 8116996 --- --- --- 5.31E-03 -1.28381 8024584 NCLN Nicalin homolog (zebrafish) NM_020170 5.33E-03 -1.13934 8099912 C4orf34 Chromosome 4 open reading frame 34 BC008502 5.37E-03 1.18735 8032094 LPPR3 Lipid phosphate phosphatase-related protein type 3 NM_024888 5.42E-03 -1.167 8104838 DNAJC21 Dnaj (Hsp40) homolog, subfamily C, member 21 NM_194283 5.43E-03 1.14285 7995252 ZNF720 Zinc finger protein 720 NM_001130913 5.45E-03 1.32296 8116113 FAM193B Family with sequence similarity 193, member B NR_024019 5.47E-03 -1.16049 8098414 SPCS3 Signal peptidase complex subunit 3 homolog (S. Cerevisiae) NM_021928 5.47E-03 1.26024 7918857 TSPAN2 Tetraspanin 2 NM_005725 5.48E-03 1.14187 7979260 GMFB Glia maturation factor, beta NM_004124 5.51E-03 1.49342 8105146 MGC42105 Serine/threonine-protein kinase NIM1 NM_153361 5.51E-03 1.15908 8172252 --- --- --- 5.51E-03 -1.37094 7902308 FPGT Fucose-1-phosphate guanylyltransferase NM_003838 5.54E-03 1.35375 8153959 DOCK8 Dedicator of cytokinesis 8 NM_203447 5.56E-03 -1.18992 112  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 7911767 MMEL1 Membrane metallo-endopeptidase-like 1 NM_033467 5.59E-03 -1.10775 7936529 KIAA1598 Kiaa1598 NM_001127211 5.63E-03 -1.40202 8020382 ROCK1 Rho-associated, coiled-coil containing protein kinase 1 NM_005406 5.65E-03 -1.24697 8108217 TGFBI Transforming growth factor, beta-induced, 68kda NM_000358 5.70E-03 -1.3237 8058182 FAM126B Family with sequence similarity 126, member B NM_173822 5.71E-03 1.19851 8073309 LOC100288034 Similar to FKSG62 XM_002346783 5.71E-03 -1.29482 8083808 LRRIQ4 Leucine-rich repeats and IQ motif containing 4 NM_001080460 5.73E-03 -1.21301 8090448 RUVBL1 Ruvb-like 1 (E. Coli) NM_003707 5.76E-03 1.10492 8174527 CAPN6 Calpain 6 NM_014289 5.78E-03 -1.24495 8087250 MIR425 Microrna 425 NR_029948 5.78E-03 -1.1211 8096635 NFKB1 Nuclear factor of kappa light polypeptide gene enhancer NM_003998 5.81E-03 -1.16142 7899898 HMGB4 High-mobility group box 4 NM_145205 5.81E-03 -1.13529 8074748 PI4KAP2 Phosphatidylinositol 4-kinase, catalytic, alpha pseudoge NR_003700 5.83E-03 -1.12807 7942553 SPCS2 Signal peptidase complex subunit 2 homolog (S. Cerevisiae) NM_014752 5.83E-03 1.25436 7964033 ANKRD52 Ankyrin repeat domain 52 NM_173595 5.86E-03 -1.15954 7929247 5-Mar Membrane-associated ring finger (C3HC4) 5 NM_017824 5.89E-03 1.15729 8092083 SLC2A2 Solute carrier family 2 (facilitated glucose transporter) NM_000340 5.89E-03 1.30066 7959251 P2RX7 Purinergic receptor P2X, ligand-gated ion channel, 7 NM_002562 5.90E-03 -1.36582 7960794 CD163 CD163 molecule NM_004244 5.91E-03 -1.53933 8151136 COPS5 COP9 constitutive photomorphogenic homolog subunit 5 NM_006837 5.93E-03 1.26846 8035156 CHERP Calcium homeostasis endoplasmic reticulum protein NM_006387 5.94E-03 -1.18384 7913547 WNT4 Wingless-type MMTV integration site family, member 4 NM_030761 5.97E-03 -1.12117 8148796 SCXA Scleraxis homolog A (mouse) NM_001008271 6.02E-03 -1.22332 8148821 SCXA Scleraxis homolog A (mouse) NM_001008271 6.02E-03 -1.22332 8121193 KLHL32 Kelch-like 32 (Drosophila) NM_052904 6.07E-03 1.12749 8152656 ZHX1 Zinc fingers and homeoboxes 1 NM_001017926 6.09E-03 1.1922 7965112 PAWR PRKC, apoptosis, WT1, regulator NM_002583 6.14E-03 1.23685 7932552 PRO3077 Hypothetical protein PRO3077 ENST000004518 89 6.17E-03 -1.15013 113  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 8157608 --- --- --- 6.20E-03 -1.15644 8039680 ZNF671 Zinc finger protein 671 NM_024833 6.21E-03 1.15837 8061426 --- --- --- 6.21E-03 -1.20461 8049888 ATG4B ATG4 autophagy related 4 homolog B (S. Cerevisiae) NM_013325 6.23E-03 -1.11258 8054092 TMEM131 Transmembrane protein 131 NM_015348 6.27E-03 -1.12901 7942409 P2RY6 Pyrimidinergic receptor P2Y, G-protein coupled, 6 NM_176796 6.27E-03 -1.27005 7949916 CHKA Choline kinase alpha NM_001277 6.30E-03 -1.12516 8156450 --- --- --- 6.32E-03 1.168 7917904 LOC100286918 Similar to NADH dehydrogenase [ubiquinone] iron XM_002342095 6.34E-03 1.17976 7999317 TMEM186 Transmembrane protein 186 NM_015421 6.38E-03 1.26018 7911376 HES4 Hairy and enhancer of split 4 (Drosophila) NM_001142467 6.41E-03 -1.16515 8042830 MTHFD2 Methylenetetrahydrofolate dehydrogenase (NADP+ dependent) NR_027405 6.41E-03 1.2007 7935746 BLOC1S2 Biogenesis of lysosomal organelles complex-1, subunit NM_001001342 6.41E-03 1.14561 8064868 GPCPD1 Glycerophosphocholine phosphodiesterase GDE1 homolog NM_019593 6.42E-03 1.20813 7998978 ZNF597 Zinc finger protein 597 NM_152457 6.42E-03 1.14856 8031640 ZNF583 Zinc finger protein 583 NM_152478 6.45E-03 1.3487 7960381 EFCAB4B EF-hand calcium binding domain 4B CR627161 6.45E-03 1.21593 7997832 FLJ40448 Hypothetical protein FLJ40448 ENST000003336 66 6.49E-03 -1.10069 7988077 LCMT2 Leucine carboxyl methyltransferase 2 NM_014793 6.51E-03 1.21419 8165642 TMEM203 Transmembrane protein 203 NM_053045 6.51E-03 1.17362 7974303 TMX1 Thioredoxin-related transmembrane protein 1 NM_030755 6.52E-03 1.30075 7920487 C1orf189 Chromosome 1 open reading frame 189 BC127710 6.55E-03 1.16694 7903586 TMEM167B Transmembrane protein 167B NM_020141 6.56E-03 1.19438 8039905 TMEM167B Transmembrane protein 167B NM_020141 6.56E-03 1.19438 7916372 TMEM59 Transmembrane protein 59 NM_004872 6.56E-03 1.16785 8124459 ZNF322A Zinc finger protein 322A NM_024639 6.56E-03 1.30038 8073578 C22orf32 Chromosome 22 open reading frame 32 BC024237 6.59E-03 1.15679 7989887 MEGF11 Multiple EGF-like-domains 11 NM_032445 6.60E-03 -1.13047 114  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 8053666 --- --- --- 6.61E-03 -1.16697 8084092 NDUFB5 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 5, 16k NM_002492 6.61E-03 1.19391 7978666 MBIP MAP3K12 binding inhibitory protein 1 NM_016586 6.64E-03 1.24038 7948303 --- --- --- 6.66E-03 -1.10451 7955119 C12orf54 Chromosome 12 open reading frame 54 NM_152319 6.66E-03 -1.15551 7968370 B3GALTL Beta 1,3-galactosyltransferase-like NM_194318 6.67E-03 1.14704 8151795 CDH17 Cadherin 17, LI cadherin (liver-intestine) NM_004063 6.67E-03 -1.20232 8121066 SPACA1 Sperm acrosome associated 1 NM_030960 6.70E-03 -1.1173 7961067 --- --- --- 6.71E-03 -1.11767 7981824 CYFIP1 Cytoplasmic FMR1 interacting protein 1 NM_014608 6.71E-03 -1.33191 8011141 PRPF8 PRP8 pre-mrna processing factor 8 homolog (S. Cerevisiae) NM_006445 6.72E-03 -1.17393 8113064 LYSMD3 Lysm, putative peptidoglycan-binding, domain containing 3 NM_198273 6.75E-03 1.39831 7931455 LRRC27 Leucine rich repeat containing 27 NM_001143757 6.77E-03 -1.1114 8151250 --- --- --- 6.77E-03 -1.24611 8088846 --- --- --- 6.78E-03 1.13931 8051226 TRMT61B Trna methyltransferase 61 homolog B (S. Cerevisiae) NM_017910 6.89E-03 1.39182 8029340 ZNF155 Zinc finger protein 155 NM_003445 6.90E-03 1.29108 7964064 CS Citrate synthase NM_004077 6.91E-03 -1.20299 7902493 --- --- --- 6.91E-03 -1.18574 8110018 RPL26L1 Ribosomal protein L26-like 1 NM_016093 6.92E-03 1.23744 8096957 --- --- --- 6.92E-03 1.26108 8167998 AR Androgen receptor NM_000044 6.97E-03 -1.20819 8126279 TREM2 Triggering receptor expressed on myeloid cells 2 NM_018965 7.00E-03 -1.12687 8050548 LAPTM4A Lysosomal protein transmembrane 4 alpha NM_014713 7.01E-03 1.12742 8027510 C19orf40 Chromosome 19 open reading frame 40 NM_152266 7.05E-03 1.11488 8022426 LOC646359 Similar to telomeric repeat binding factor (NIMA ENST000003422 24 7.07E-03 -1.33448 7944162 --- --- --- 7.08E-03 -1.13436 115  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 8018731 RHBDF2 Rhomboid 5 homolog 2 (Drosophila) NM_024599 7.08E-03 -1.14046 8103520 TRIM61 Tripartite motif-containing 61 NM_001012414 7.13E-03 1.18905 7964701 GNS Glucosamine (N-acetyl)-6-sulfatase NM_002076 7.14E-03 -1.27976 7902911 --- --- --- 7.15E-03 -1.2657 8177068 --- --- --- 7.21E-03 -1.25224 7903203 SNX7 Sorting nexin 7 NM_015976 7.22E-03 -1.17834 7999304 FAM86A Family with sequence similarity 86, member A NM_201400 7.25E-03 -1.11058 8131000 HEATR2 HEAT repeat containing 2 NM_017802 7.28E-03 -1.1045 7916562 HNRNPA1 Heterogeneous nuclear ribonucleoprotein A1 NM_002136 7.35E-03 1.13724 8110618 ARPP19 Camp-regulated phosphoprotein, 19kda NM_006628 7.36E-03 1.10296 8112807 ARSB Arylsulfatase B NM_000046 7.37E-03 -1.1574 7907171 BLZF1 Basic leucine zipper nuclear factor 1 NM_003666 7.40E-03 1.2842 8155550 LOC554249 Hypothetical LOC554249 AK292642 7.42E-03 1.1044 7954029 CDKN1B Cyclin-dependent kinase inhibitor 1B (p27, Kip1) NM_004064 7.49E-03 1.19399 8163257 LPAR1 Lysophosphatidic acid receptor 1 NM_057159 7.50E-03 -1.18531 8124484 HIST1H2BJ Histone cluster 1, h2bj NM_021058 7.50E-03 -1.1749 8081820 --- --- --- 7.58E-03 -1.24684 8086607 LTF Lactotransferrin NM_002343 7.58E-03 -1.26088 8131867 --- --- --- 7.60E-03 -1.23084 8106107 PTCD2 Pentatricopeptide repeat domain 2 NM_024754 7.61E-03 1.28064 8106702 ZCCHC9 Zinc finger, CCHC domain containing 9 NM_032280 7.62E-03 1.16093 8068168 SOD1 Superoxide dismutase 1, soluble NM_000454 7.63E-03 1.14687 8001385 --- --- --- 7.64E-03 -1.15954 8084630 --- --- --- 7.65E-03 -1.17809 8096081 ENOPH1 Enolase-phosphatase 1 NM_021204 7.69E-03 1.15722 7970655 MTMR6 Myotubularin related protein 6 NM_004685 7.69E-03 1.24128 8178095 C2 Complement component 2 NM_000063 7.70E-03 -1.16351 8179331 C2 Complement component 2 NM_000063 7.70E-03 -1.16351 7938263 EIF3F Eukaryotic translation initiation factor 3, subunit F NM_003754 7.73E-03 1.14948 116  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 7979455 RTN1 Reticulon 1 NM_021136 7.75E-03 -1.37064 7933084 NAMPT Nicotinamide phosphoribosyltransferase NM_005746 7.76E-03 1.19403 8096251 NUDT9 Nudix (nucleoside diphosphate linked moiety X)-type motif NM_024047 7.77E-03 1.17498 8077528 SETD5 SET domain containing 5 NM_001080517 7.79E-03 -1.12273 7945859 MRGPRE MAS-related GPR, member E NM_001039165 7.80E-03 -1.2183 8151234 SLCO5A1 Solute carrier organic anion transporter family, member 5 AF205075 7.80E-03 -1.28021 8119034 BRPF3 Bromodomain and PHD finger containing, 3 NM_015695 7.84E-03 -1.1626 7943519 --- --- --- 7.90E-03 1.1165 8100756 --- --- --- 7.91E-03 -1.26327 7899604 ZCCHC17 Zinc finger, CCHC domain containing 17 NM_016505 7.93E-03 1.15967 8016232 SH3D20 SH3 domain containing 20 NM_174919 7.94E-03 -1.19651 8173745 CYSLTR1 Cysteinyl leukotriene receptor 1 NM_006639 7.95E-03 1.21873 8102037 --- --- --- 7.98E-03 1.27825 7971950 DACH1 Dachshund homolog 1 (Drosophila) NM_080759 7.98E-03 -1.17053 8069644 APP Amyloid beta (A4) precursor protein NM_000484 7.99E-03 -1.3248 8049534 LRRFIP1 Leucine rich repeat (in FLII) interacting protein 1 NM_001137550 7.99E-03 -1.2279 7920165 FLG Filaggrin NM_002016 7.99E-03 -1.11366 7977435 --- --- --- 8.00E-03 1.27651 7989953 AAGAB Alpha- and gamma-adaptin binding protein NM_024666 8.02E-03 1.15777 8155453 LOC100289385 Hypothetical protein LOC100289385 XM_002342912 8.08E-03 1.31562 8161375 LOC100289385 Hypothetical protein LOC100289385 XM_002342912 8.08E-03 1.31562 7900413 ZMPSTE24 Zinc metallopeptidase (STE24 homolog, S. Cerevisiae) NM_005857 8.08E-03 1.2369 8108873 ARHGAP26 Rho gtpase activating protein 26 NM_015071 8.09E-03 -1.15711 8141708 CLDN15 Claudin 15 NM_014343 8.13E-03 -1.15809 7973754 --- --- --- 8.14E-03 -1.14992 8146894 --- --- --- 8.14E-03 1.13833 8029399 ZNF226 Zinc finger protein 226 NM_001032372 8.17E-03 1.40976 8038989 ZNF600 Zinc finger protein 600 NM_198457 8.20E-03 1.2762 8089128 TOMM70A Translocase of outer mitochondrial membrane 70 homolog A NM_014820 8.22E-03 1.10493 117  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 8006345 RHOT1 Ras homolog gene family, member T1 NM_001033568 8.23E-03 1.24848 8037103 GRIK5 Glutamate receptor, ionotropic, kainate 5 NM_002088 8.23E-03 -1.2738 8099897 UGDH UDP-glucose 6-dehydrogenase NM_003359 8.24E-03 1.27072 7925128 --- --- --- 8.28E-03 -1.20397 8061445 --- --- --- 8.32E-03 -1.15966 8091385 CP Ceruloplasmin (ferroxidase) NM_000096 8.32E-03 1.33097 7990848 TMC3 Transmembrane channel-like 3 NM_001080532 8.38E-03 -1.10521 7925691 ZNF124 Zinc finger protein 124 NM_003431 8.39E-03 1.29967 8046997 ASNSD1 Asparagine synthetase domain containing 1 NM_019048 8.40E-03 1.25924 7907353 METTL13 Methyltransferase like 13 NM_015935 8.41E-03 1.12419 7911199 C1orf150 Chromosome 1 open reading frame 150 NM_145278 8.45E-03 1.16755 7950644 NDUFC2 NADH dehydrogenase (ubiquinone) 1, subcomplex unknown, 2 NM_004549 8.47E-03 1.22001 8003991 MINK1 Misshapen-like kinase 1 (zebrafish) NM_153827 8.47E-03 -1.19442 7906435 DARC Duffy blood group, chemokine receptor NM_002036 8.51E-03 -1.22871 8126784 PLA2G7 Phospholipase A2, group VII (platelet-activating factor NM_001168357 8.52E-03 -1.10783 7956005 OR2AP1 Olfactory receptor, family 2, subfamily AP, member ENST000003216 88 8.54E-03 1.27053 8039013 ZNF321 Zinc finger protein 321 NM_203307 8.54E-03 1.35424 7991630 TM2D3 TM2 domain containing 3 NM_078474 8.56E-03 1.17958 8044049 IL18RAP Interleukin 18 receptor accessory protein NM_003853 8.61E-03 1.2754 7903703 GNAI3 Guanine nucleotide binding protein (G protein), alpha inhibitor NM_006496 8.62E-03 1.2552 7909689 SMYD2 SET and MYND domain containing 2 NM_020197 8.62E-03 1.18907 7968297 POMP Proteasome maturation protein NM_015932 8.65E-03 1.16822 7964733 RPSAP52 Ribosomal protein SA pseudogene 52 NR_026825 8.68E-03 1.32673 8119722 CUL9 Cullin 9 NM_015089 8.68E-03 -1.11298 7972737 LIG4 Ligase IV, DNA, ATP-dependent NM_002312 8.71E-03 1.28653 8093601 FAM193A Family with sequence similarity 193, member A NM_003704 8.72E-03 -1.1764 8162191 LOC392364 Chromosome 15 open reading frame 2 pseudogene BC086877 8.72E-03 -1.24198 118  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 8152867 ASAP1 Arfgap with SH3 domain, ankyrin repeat and PH domain 1 NM_018482 8.80E-03 -1.32645 8035304 BST2 Bone marrow stromal cell antigen 2 NM_004335 8.82E-03 1.16059 7901867 USP1 Ubiquitin specific peptidase 1 NM_003368 8.82E-03 1.39398 8047286 --- --- --- 8.83E-03 -1.3013 7935968 LDB1 LIM domain binding 1 NM_003893 8.84E-03 -1.14475 8102006 MANBA Mannosidase, beta A, lysosomal NM_005908 8.88E-03 -1.19819 8094378 PI4K2B Phosphatidylinositol 4-kinase type 2 beta NM_018323 8.91E-03 1.19533 7911676 --- --- --- 8.92E-03 -1.29941 8096461 ATOH1 Atonal homolog 1 (Drosophila) NM_005172 8.92E-03 -1.11833 8055862 ARL5A ADP-ribosylation factor-like 5A NM_012097 8.96E-03 1.22757 8011542 ZZEF1 Zinc finger, ZZ-type with EF-hand domain 1 NM_015113 8.96E-03 -1.17171 7996377 CES8 Carboxylesterase 8 (putative) NM_173815 8.97E-03 -1.13189 8046003 GCA Grancalcin, EF-hand calcium binding protein NM_012198 8.98E-03 1.26908 8026007 ZNF791 Zinc finger protein 791 NM_153358 8.98E-03 1.22662 8025103 EMR1 Egf-like module containing, mucin-like, hormone receptor-li NM_001974 9.01E-03 -1.47335 8128626 PDSS2 Prenyl (decaprenyl) diphosphate synthase, subunit 2 NM_020381 9.03E-03 1.27126 8024019 PTBP1 Polypyrimidine tract binding protein 1 NM_002819 9.04E-03 -1.11968 7989315 GTF2A2 General transcription factor IIA, 2, 12kda NM_004492 9.06E-03 1.26504 8137264 TMEM176A Transmembrane protein 176A NM_018487 9.06E-03 -1.35027 8135909 LEP Leptin NM_000230 9.08E-03 -1.15852 7945420 RNH1 Ribonuclease/angiogenin inhibitor 1 NM_002939 9.08E-03 -1.11763 8091698 SHOX2 Short stature homeobox 2 NM_003030 9.08E-03 -1.18357 8076339 PHF5A PHD finger protein 5A NM_032758 9.08E-03 1.21107 7964832 --- --- --- 9.08E-03 1.1847 7963988 SMARCC2 SWI/SNF related, matrix associated, actin dependent regulator NM_003075 9.14E-03 -1.14109 7985268 FAH Fumarylacetoacetate hydrolase (fumarylacetoacetase) NM_000137 9.16E-03 -1.21621 7930921 BAG3 BCL2-associated athanogene 3 NM_004281 9.17E-03 -1.21844 8102210 --- --- --- 9.18E-03 -1.19381 8037535 --- --- --- 9.20E-03 1.10952 119  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 7927505 C10orf53 Chromosome 10 open reading frame 53 NM_182554 9.21E-03 -1.13661 8122637 SASH1 SAM and SH3 domain containing 1 NM_015278 9.25E-03 -1.16624 8003156 --- --- --- 9.27E-03 1.23751 8148265 RNF139 Ring finger protein 139 NM_007218 9.27E-03 1.20819 8104443 --- --- --- 9.28E-03 -1.207 7924817 PRO2012 Hypothetical protein PRO2012 BC019830 9.28E-03 1.27355 7985587 SCAND2 SCAN domain containing 2 pseudogene NR_004859 9.30E-03 1.24522 7959995 EP400 E1A binding protein p400 NM_015409 9.38E-03 -1.18418 8151788 RBM12B RNA binding motif protein 12B NM_203390 9.40E-03 1.4164 8043487 FKSG73 ARP3 actin-related protein 3 homolog B pseudogene NR_027714 9.41E-03 -1.13056 7904965 PDE4DIP Phosphodiesterase 4D interacting protein AB042555 9.42E-03 1.31278 8045919 7-Mar Membrane-associated ring finger (C3HC4) 7 NM_022826 9.45E-03 1.26964 7945182 APLP2 Amyloid beta (A4) precursor-like protein 2 NM_001642 9.48E-03 -1.12202 8022295 FAM38B Family with sequence similarity 38, member B NM_022068 9.48E-03 1.17219 8104625 --- --- --- 9.49E-03 1.24254 8131600 TSPAN13 Tetraspanin 13 NM_014399 9.50E-03 1.20646 8054075 UBTFL1 Upstream binding transcription factor, RNA polymerase NM_001143975 9.50E-03 -1.15066 7976876 DYNC1H1 Dynein, cytoplasmic 1, heavy chain 1 NM_001376 9.53E-03 -1.21384 8059648 --- --- --- 9.53E-03 1.31455 7978558 EAPP E2F-associated phosphoprotein NM_018453 9.54E-03 1.37411 7961363 --- --- --- 9.58E-03 -1.21749 7932796 SVIL Supervillin NM_021738 9.59E-03 -1.13936 8022118 EPB41L3 Erythrocyte membrane protein band 4.1-like 3 NM_012307 9.60E-03 -1.23694 8163729 MIR147 Microrna 147 NR_029604 9.60E-03 -1.18801 8036956 C19orf54 Chromosome 19 open reading frame 54 NM_198476 9.61E-03 -1.13823 8066567 --- --- --- 9.63E-03 1.19606 8019559 B3GNTL1 UDP-glcnac:betagal beta-1,3-N- acetylglucosaminyltransferase AK126018 9.64E-03 -1.15365 8079074 SS18L2 Synovial sarcoma translocation gene on chromosome 18- like NM_016305 9.69E-03 1.15093 120  Probe Set ID Gene Symbol Gene Name RefSeq P Value Fold Change 8130211 SYNE1 Spectrin repeat containing, nuclear envelope 1 NM_182961 9.75E-03 -1.13687 7901982 UBE2U Ubiquitin-conjugating enzyme E2U (putative) NM_152489 9.77E-03 -1.20212 8054943 --- --- --- 9.80E-03 -1.22989 7957245 GLIPR1L1 GLI pathogenesis-related 1 like 1 NM_152779 9.84E-03 1.20256 8019149 SLC38A10 Solute carrier family 38, member 10 NM_001037984 9.85E-03 -1.16543 8080973 PPP4R2 Protein phosphatase 4, regulatory subunit 2 NM_174907 9.85E-03 1.26828 7992692 SRRM2 Serine/arginine repetitive matrix 2 NM_016333 9.85E-03 -1.22791 8014241 SLFN12 Schlafen family member 12 NM_018042 9.85E-03 1.28066 8120943 CYB5R4 Cytochrome b5 reductase 4 NM_016230 9.91E-03 1.20619 7897288 ESPN Espin NM_031475 9.91E-03 -1.2696 7913814 SYF2 SYF2 homolog, RNA splicing factor (S. Cerevisiae) NM_015484 9.92E-03 1.18457 8030044 KCNJ14 Potassium inwardly-rectifying channel, subfamily J, member 14 NM_170720 9.94E-03 -1.19379 8035842 ZNF91 Zinc finger protein 91 NM_003430 9.97E-03 1.37192 8030993 ZNF761 Zinc finger protein 761 NM_001008401 9.99E-03 1.44775 8173609 --- --- --- 9.99E-03 1.28596  121  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-01 122  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  123  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-01 124  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-01 125  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 -1.711 126  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. b Fold change was calculated from averaged pre- and post-values, without accounting for subject pairs. 127  b) Histogram Representations 128  129  130   131  Appendix 6 — Differentially Expressed Probe Sets Identified by Interaction Analysis (FDR≤0.30) Probe Set ID Gene Symbol Gene Name FDR 8065396 CST9L Cystatin 9-like 0.00E+00 8168817 DRP2 Dystrophin related protein 2 0.00E+00 7937707 FAM99A Family with sequence similarity 99, member A 0.00E+00 8075555 C22orf42 Chromosome 22 open reading frame 42 1.42E-01 7923907 IL10 Interleukin 10 1.42E-01 8152314 RSPO2 R-spondin 2 homolog (Xenopus laevis) 1.42E-01 8087547 MST1R Macrophage stimulating 1 receptor (c-met-related tyrosine kinase) 1.42E-01 7994074 SCNN1B Sodium channel, nonvoltage-gated 1, beta 1.42E-01 7943521 DDI1 DNA-damage inducible 1 homolog 1 (S. Cerevisiae) 1.42E-01 8104163 LRRC14B Leucine rich repeat containing 14B 1.42E-01 7986977 TJP1 Tight junction protein 1 (zona occludens 1) 1.42E-01 8066161 C20orf132 Chromosome 20 open reading frame 132 1.42E-01 8024676 GIPC3 GIPC PDZ domain containing family, member 3 1.42E-01 7977771 OR10G2 Olfactory receptor, family 10, subfamily G, member 2 1.42E-01 8038633 KLK1 Kallikrein 1 1.42E-01 7960529 SCNN1A Sodium channel, nonvoltage-gated 1 alpha 1.42E-01 8145691 UBXN8 UBX domain protein 8 1.42E-01 8091515 GPR87 G protein-coupled receptor 87 1.42E-01 7917634 HFM1 HFM1, ATP-dependent DNA helicase homolog (S. Cerevisiae) 1.42E-01 8048749 KCNE4 Potassium voltage-gated channel, Isk-related family, member 4 1.42E-01 7912975 ALDH4A1 Aldehyde dehydrogenase 4 family, member A1 1.42E-01 8139640 DDC Dopa decarboxylase (aromatic L-amino acid decarboxylase) 1.42E-01 8166705 PRRG1 Proline rich Gla (G-carboxyglutamic acid) 1 1.42E-01 8124495 POM121L2 POM121 membrane glycoprotein-like 2 1.70E-01 8053872 ASTL Astacin-like metallo-endopeptidase (M12 family) 1.70E-01 8071541 TMEM191A Transmembrane protein 191A 1.70E-01 7970954 DCLK1 Doublecortin-like kinase 1 1.70E-01 8124129 NHLRC1 NHL repeat containing 1 1.70E-01 8118995 LHFPL5 Lipoma HMGIC fusion partner-like 5 1.70E-01 8173189 SPIN2B Spindlin family, member 2B 1.70E-01 8113660 RPS25 Ribosomal protein S25 1.70E-01 7948630 FADS3 Fatty acid desaturase 3 1.70E-01 8094184 C1QTNF7 C1q and tumor necrosis factor related protein 7 1.70E-01 7995030 ZNF668 Zinc finger protein 668 1.70E-01 132  Probe Set ID Gene Symbol Gene Name FDR 7929932 KAZALD1 Kazal-type serine peptidase inhibitor domain 1 1.70E-01 7985238 ANKRD34C Ankyrin repeat domain 34C 1.70E-01 7938646 CALCB Calcitonin-related polypeptide beta 1.70E-01 8007701 HIGD1B HIG1 hypoxia inducible domain family, member 1B 1.73E-01 8162674 LOC286359 Hypothetical LOC286359 1.73E-01 8178291 OR11A1 Olfactory receptor, family 11, subfamily A, member 1 1.73E-01 8179591 OR11A1 Olfactory receptor, family 11, subfamily A, member 1 1.73E-01 8056151 PLA2R1 Phospholipase A2 receptor 1, 180kda 1.73E-01 8066542 SPINLW1 Serine peptidase inhibitor-like, with Kunitz and WAP domains 1 (eppin) 1.73E-01 8167758 GPR173 G protein-coupled receptor 173 1.81E-01 8060086 MYEOV2 Myeloma overexpressed 2 1.81E-01 7979529 KCNH5 Potassium voltage-gated channel, subfamily H (eag- related), member 5 1.81E-01 8139456 SNORA9 Small nucleolar RNA, H/ACA box 9 1.81E-01 7911233 OR2T8 Olfactory receptor, family 2, subfamily T, member 8 1.81E-01 8020411 SNRPD1 Small nuclear ribonucleoprotein D1 polypeptide 16kda 1.81E-01 8022856 NOL4 Nucleolar protein 4 1.81E-01 8045795 KCNJ3 Potassium inwardly-rectifying channel, subfamily J, member 3 1.81E-01 8061082 OTOR Otoraplin 1.81E-01 8145570 ESCO2 Establishment of cohesion 1 homolog 2 (S. Cerevisiae) 1.81E-01 8071368 TMEM191A Transmembrane protein 191A 1.81E-01 8131965 LOC441204 Hypothetical locus LOC441204 1.81E-01 8025452 MBD3L1 Methyl-cpg binding domain protein 3-like 1 1.81E-01 7906355 CD1E CD1e molecule 1.81E-01 8160900 C9orf144 Transmembrane protein c9orf144b pseudogene 1.81E-01 8064976 DNAJC9 Dnaj (Hsp40) homolog, subfamily C, member 9 1.81E-01 8108912 SH3RF2 SH3 domain containing ring finger 2 1.96E-01 8088986 POU1F1 POU class 1 homeobox 1 1.96E-01 8096528 PDHA2 Pyruvate dehydrogenase (lipoamide) alpha 2 1.96E-01 8163678 ASTN2 Astrotactin 2 1.96E-01 8047829 CPO Carboxypeptidase O 1.96E-01 7906163 RHBG Rh family, B glycoprotein (gene/pseudogene) 1.96E-01 7919208 GNRHR2 Gonadotropin-releasing hormone (type 2) receptor 2 1.96E-01 8039593 ZNF667 Zinc finger protein 667 1.96E-01 8074856 PRAME Preferentially expressed antigen in melanoma 1.96E-01 8125936 CLPS Colipase, pancreatic 1.96E-01 7898002 PRAMEF22 PRAME family member 22 1.96E-01 8098214 TLL1 Tolloid-like 1 1.96E-01 7900340 BMP8A Bone morphogenetic protein 8a 1.96E-01 8122127 TAAR9 Trace amine associated receptor 9 (gene/pseudogene) 1.96E-01 133  Probe Set ID Gene Symbol Gene Name FDR 7927202 ZNF22 Zinc finger protein 22 (KOX 15) 1.96E-01 8098307 GALNTL6 UDP-N-acetyl-alpha-D-galactosamine:polypeptide N- acetylgalactosaminyltransferase-like 6 1.96E-01 8071953 SGSM1 Small G protein signaling modulator 1 1.96E-01 8159850 VLDLR Very low density lipoprotein receptor 1.96E-01 8007348 RAMP2 Receptor (G protein-coupled) activity modifying protein 2 1.96E-01 7955317 ACCN2 Amiloride-sensitive cation channel 2, neuronal 1.96E-01 8037283 PSG4 Pregnancy specific beta-1-glycoprotein 4 1.96E-01 7940108 OR6Q1 Olfactory receptor, family 6, subfamily Q, member 1 1.96E-01 8052940 PAIP2B Poly(A) binding protein interacting protein 2B 1.96E-01 8149629 GFRA2 GDNF family receptor alpha 2 1.96E-01 8055239 CFC1 Cripto, FRL-1, cryptic family 1 1.96E-01 8150879 MOS V-mos Moloney murine sarcoma viral oncogene homolog 1.96E-01 8038942 ZNF432 Zinc finger protein 432 1.96E-01 8068139 KRTAP15-1 Keratin associated protein 15-1 1.96E-01 7985233 RASGRF1 Ras protein-specific guanine nucleotide-releasing factor 1 1.96E-01 8142452 TFEC Transcription factor EC 1.96E-01 8036420 ZFP30 Zinc finger protein 30 homolog (mouse) 1.96E-01 8100007 PHOX2B Paired-like homeobox 2b 1.96E-01 8039892 KIR2DS5 Killer cell immunoglobulin-like receptor, two domains, short cytoplasmic tail, 5 1.96E-01 8024792 EBI3 Epstein-Barr virus induced 3 1.96E-01 8086908 PLXNB1 Plexin B1 2.01E-01 8013473 LOC339240 Keratin pseudogene 2.01E-01 7953181 PRMT8 Protein arginine methyltransferase 8 2.01E-01 8156393 SUSD3 Sushi domain containing 3 2.01E-01 8000028 DCUN1D3 DCN1, defective in cullin neddylation 1, domain containing 3 (S. Cerevisiae) 2.01E-01 8089082 DCBLD2 Discoidin, CUB and LCCL domain containing 2 2.01E-01 7969861 ITGBL1 Integrin, beta-like 1 (with EGF-like repeat domains) 2.01E-01 8174207 NXF3 Nuclear RNA export factor 3 2.01E-01 7976852 MIR377 Microrna 377 2.01E-01 7945660 FAM99A Family with sequence similarity 99, member A 2.01E-01 8154563 ACER2 Alkaline ceramidase 2 2.01E-01 7909155 AVPR1B Arginine vasopressin receptor 1B 2.01E-01 8076424 CYP2D6 Cytochrome P450, family 2, subfamily D, polypeptide 6 2.01E-01 8153835 PPP1R16A Protein phosphatase 1, regulatory (inhibitor) subunit 16A 2.01E-01 8024808 SHD Src homology 2 domain containing transforming protein D 2.01E-01 7905490 LCE3C Late cornified envelope 3C 2.01E-01 7907907 LOC10028794 8 Hypothetical LOC100287948 2.01E-01 8124645 OR12D3 Olfactory receptor, family 12, subfamily D, member 3 2.01E-01 134  Probe Set ID Gene Symbol Gene Name FDR 8076113 LOC646851 Hypothetical LOC646851 2.01E-01 7980024 HEATR4 HEAT repeat containing 4 2.01E-01 8169115 NRK Nik related kinase 2.01E-01 8174737 NKAP NFKB activating protein 2.01E-01 8152062 SNX31 Sorting nexin 31 2.01E-01 8170704 ABCD1 ATP-binding cassette, sub-family D (ALD), member 1 2.01E-01 7976842 MIR382 Microrna 382 2.01E-01 8015884 PPY Pancreatic polypeptide 2.01E-01 8028984 CYP2F1 Cytochrome P450, family 2, subfamily F, polypeptide 1 2.01E-01 7924842 C1orf35 Chromosome 1 open reading frame 35 2.01E-01 8135763 WNT16 Wingless-type MMTV integration site family, member 16 2.01E-01 8044804 DBI Diazepam binding inhibitor (GABA receptor modulator, acyl-coa binding protein) 2.01E-01 7901048 SNORD46 Small nucleolar RNA, C/D box 46 2.01E-01 7901720 PRKAA2 Protein kinase, AMP-activated, alpha 2 catalytic subunit 2.01E-01 7987230 LPCAT4 Lysophosphatidylcholine acyltransferase 4 2.01E-01 7957140 LGR5 Leucine-rich repeat containing G protein-coupled receptor 5 2.16E-01 8027473 PDCD5 Programmed cell death 5 2.16E-01 8026568 C19orf44 Chromosome 19 open reading frame 44 2.16E-01 8010787 HEXDC Hexosaminidase (glycosyl hydrolase family 20, catalytic domain) containing 2.16E-01 8097692 EDNRA Endothelin receptor type A 2.16E-01 8068894 C21orf125 Chromosome 21 open reading frame 125 2.16E-01 8026496 LOC126536 Hypothetical LOC126536 2.16E-01 8108716 PCDHB16 Protocadherin beta 16 2.16E-01 7942328 FOLR3 Folate receptor 3 (gamma) 2.16E-01 8008914 C17orf64 Chromosome 17 open reading frame 64 2.16E-01 8146625 NKAIN3 Na+/K+ transporting atpase interacting 3 2.16E-01 7985253 C15orf37 Chromosome 15 open reading frame 37 2.16E-01 8178289 OR12D3 Olfactory receptor, family 12, subfamily D, member 3 2.16E-01 7896863 MIR429 Microrna 429 2.16E-01 8068496 SIM2 Single-minded homolog 2 (Drosophila) 2.16E-01 8021416 MIR122 Microrna 122 2.16E-01 7922229 SELE Selectin E 2.16E-01 8070315 NCRNA00114 Non-protein coding RNA 114 2.16E-01 8022295 FAM38B Family with sequence similarity 38, member B 2.16E-01 8175685 MAGEA5 Melanoma antigen family A, 5 2.16E-01 8180303 SAA2 Serum amyloid A2 2.16E-01 8033445 CD209 CD209 molecule 2.16E-01 7905483 LCE5A Late cornified envelope 5A 2.16E-01 7985025 ODF3L1 Outer dense fiber of sperm tails 3-like 1 2.16E-01 135  Probe Set ID Gene Symbol Gene Name FDR 8157632 MORN5 MORN repeat containing 5 2.16E-01 7942261 KRTAP5-9 Keratin associated protein 5-9 2.16E-01 8074880 RAB36 RAB36, member RAS oncogene family 2.16E-01 8003656 SERPINF2 Serpin peptidase inhibitor, clade F (alpha-2 antiplasmin, pigment epithelium derived factor), member 2 2.16E-01 8086595 XCR1 Chemokine (C motif) receptor 1 2.16E-01 8046186 KLHL23 Kelch-like 23 (Drosophila) 2.16E-01 7924403 MIR194-1 Microrna 194-1 2.37E-01 7937483 SNORA52 Small nucleolar RNA, H/ACA box 52 2.37E-01 8113726 PPIC Peptidylprolyl isomerase C (cyclophilin C) 2.37E-01 7948643 RAB3IL1 RAB3A interacting protein (rabin3)-like 1 2.37E-01 8037947 TPRX1 Tetra-peptide repeat homeobox 1 2.37E-01 7955993 OR6C75 Olfactory receptor, family 6, subfamily C, member 75 2.37E-01 8021461 GRP Gastrin-releasing peptide 2.37E-01 8059868 ASB18 Ankyrin repeat and SOCS box containing 18 2.37E-01 8038505 SIGLEC11 Sialic acid binding Ig-like lectin 11 2.37E-01 8138799 TRIL TLR4 interactor with leucine-rich repeats 2.37E-01 8095628 ALB Albumin 2.37E-01 8036151 HSPB6 Heat shock protein, alpha-crystallin-related, B6 2.37E-01 8175808 TREX2 Three prime repair exonuclease 2 2.37E-01 7909422 MIR205 Microrna 205 2.37E-01 8067233 PMEPA1 Prostate transmembrane protein, androgen induced 1 2.37E-01 8180374 APOBEC3F Apolipoprotein B mrna editing enzyme, catalytic polypeptide-like 3F 2.37E-01 7943749 LAYN Layilin 2.37E-01 7958620 IFT81 Intraflagellar transport 81 homolog (Chlamydomonas) 2.37E-01 7946436 ASCL3 Achaete-scute complex homolog 3 (Drosophila) 2.37E-01 7939959 OR5AS1 Olfactory receptor, family 5, subfamily AS, member 1 2.37E-01 8144473 DEFB103B Defensin, beta 103B 2.37E-01 8149172 DEFB103B Defensin, beta 103B 2.37E-01 8082926 SOX14 SRY (sex determining region Y)-box 14 2.37E-01 8159211 FCN2 Ficolin (collagen/fibrinogen domain containing lectin) 2 (hucolin) 2.37E-01 8106722 ATP6AP1L Atpase, H+ transporting, lysosomal accessory protein 1- like 2.37E-01 7905507 LCE2A Late cornified envelope 2A 2.37E-01 8138930 RP9P Retinitis pigmentosa 9 pseudogene 2.37E-01 8157090 TAL2 T-cell acute lymphocytic leukemia 2 2.37E-01 8014812 STAC2 SH3 and cysteine rich domain 2 2.37E-01 8116168 NHP2 NHP2 ribonucleoprotein homolog (yeast) 2.37E-01 8177130 NHEDC1 Na+/H+ exchanger domain containing 1 2.37E-01 8038695 KLK7 Kallikrein-related peptidase 7 2.37E-01 8166587 MAGEB10 Melanoma antigen family B, 10 2.37E-01 136  Probe Set ID Gene Symbol Gene Name FDR 7997059 DDX19A DEAD (Asp-Glu-Ala-As) box polypeptide 19A 2.37E-01 8173059 WNK3 WNK lysine deficient protein kinase 3 2.37E-01 8084832 PYDC2 Pyrin domain containing 2 2.37E-01 7902512 DNAJB4 Dnaj (Hsp40) homolog, subfamily B, member 4 2.37E-01 8002882 CHST6 Carbohydrate (N-acetylglucosamine 6-O) sulfotransferase 6 2.37E-01 7952631 TP53AIP1 Tumor protein p53 regulated apoptosis inducing protein 1 2.37E-01 8152902 ADCY8 Adenylate cyclase 8 (brain) 2.37E-01 8173551 PHKA1 Phosphorylase kinase, alpha 1 (muscle) 2.47E-01 7991577 LOC440313 Hypothetical LOC440313 2.47E-01 8043040 FUNDC2P2 FUN14 domain containing 2 pseudogene 2 2.47E-01 7992409 RNF151 Ring finger protein 151 2.47E-01 7984862 CYP1A2 Cytochrome P450, family 1, subfamily A, polypeptide 2 2.47E-01 8108900 HMHB1 Histocompatibility (minor) HB-1 2.47E-01 8108706 PCDHB17 Protocadherin beta 17 pseudogene 2.47E-01 8137707 MIR339 Microrna 339 2.47E-01 7989887 MEGF11 Multiple EGF-like-domains 11 2.47E-01 8096568 C4orf17 Chromosome 4 open reading frame 17 2.47E-01 8110821 SLC6A3 Solute carrier family 6 (neurotransmitter transporter, dopamine), member 3 2.47E-01 8149955 PBK PDZ binding kinase 2.47E-01 8138231 THSD7A Thrombospondin, type I, domain containing 7A 2.47E-01 7993848 OTOA Otoancorin 2.47E-01 7899562 PTPRU Protein tyrosine phosphatase, receptor type, U 2.47E-01 8003939 TM4SF5 Transmembrane 4 L six family member 5 2.47E-01 8130837 FRMD1 FERM domain containing 1 2.47E-01 8126891 CRISP2 Cysteine-rich secretory protein 2 2.47E-01 7928126 KIAA1274 Kiaa1274 2.47E-01 8142663 NDUFA5 NADH dehydrogenase (ubiquinone) 1 alpha subcomplex, 5, 13kda 2.47E-01 8100768 UGT2B10 UDP glucuronosyltransferase 2 family, polypeptide B10 2.47E-01 7988350 DUOX2 Dual oxidase 2 2.47E-01 8004394 SPEM1 Spermatid maturation 1 2.47E-01 8016433 HOXB1 Homeobox B1 2.47E-01 7947599 CHST1 Carbohydrate (keratan sulfate Gal-6) sulfotransferase 1 2.47E-01 8068157 KRTAP20-4 Keratin associated protein 20-4 2.47E-01 8144880 SH2D4A SH2 domain containing 4A 2.47E-01 8109752 ODZ2 Odz, odd Oz/ten-m homolog 2 (Drosophila) 2.47E-01 8092520 C3orf70 Chromosome 3 open reading frame 70 2.47E-01 8019177 TMEM105 Transmembrane protein 105 2.47E-01 8150244 GOT1L1 Glutamic-oxaloacetic transaminase 1-like 1 2.47E-01 8111203 LOC285696 Hypothetical LOC285696 2.47E-01 137  Probe Set ID Gene Symbol Gene Name FDR 7965206 SLC6A15 Solute carrier family 6 (neutral amino acid transporter), member 15 2.47E-01 8030299 CCDC155 Coiled-coil domain containing 155 2.47E-01 8026388 OR7C2 Olfactory receptor, family 7, subfamily C, member 2 2.47E-01 7961798 SOX5 SRY (sex determining region Y)-box 5 2.47E-01 8005586 RNF112 Ring finger protein 112 2.47E-01 7973510 CPNE6 Copine VI (neuronal) 2.47E-01 8160360 IFNB1 Interferon, beta 1, fibroblast 2.47E-01 8069146 KRTAP10-7 Keratin associated protein 10-7 2.47E-01 7930208 INA Internexin neuronal intermediate filament protein, alpha 2.47E-01 8084838 HRASLS HRAS-like suppressor 2.47E-01 8005446 LOC339240 Keratin pseudogene 2.47E-01 8165508 NRARP NOTCH-regulated ankyrin repeat protein 2.47E-01 7911529 MXRA8 Matrix-remodelling associated 8 2.47E-01 7977478 OR4K13 Olfactory receptor, family 4, subfamily K, member 13 2.47E-01 7948129 OR5R1 Olfactory receptor, family 5, subfamily R, member 1 2.47E-01 8039389 PTPRH Protein tyrosine phosphatase, receptor type, H 2.47E-01 8161482 ANKRD30BL Ankyrin repeat domain 30B-like 2.47E-01 8027222 CILP2 Cartilage intermediate layer protein 2 2.47E-01 8175666 GABRE Gamma-aminobutyric acid (GABA) A receptor, epsilon 2.47E-01 8150253 STAR Steroidogenic acute regulatory protein 2.47E-01 8147516 MATN2 Matrilin 2 2.47E-01 8045198 CFC1B Cripto, FRL-1, cryptic family 1B 2.47E-01 8061272 C20orf26 Chromosome 20 open reading frame 26 2.47E-01 7957503 C12orf37 Chromosome 12 open reading frame 37 2.69E-01 8011339 OR1E1 Olfactory receptor, family 1, subfamily E, member 1 2.69E-01 7942991 TYR Tyrosinase (oculocutaneous albinism IA) 2.69E-01 8046824 FSIP2 Fibrous sheath interacting protein 2 2.69E-01 7917942 FLJ35409 FLJ35409 protein 2.69E-01 8087252 MIR191 Microrna 191 2.69E-01 8044212 SULT1C2 Sulfotransferase family, cytosolic, 1C, member 2 2.69E-01 8022986 SYT4 Synaptotagmin IV 2.69E-01 8034390 ZNF799 Zinc finger protein 799 2.69E-01 8110382 PRR7 Proline rich 7 (synaptic) 2.69E-01 8160392 IFNA16 Interferon, alpha 16 2.69E-01 8070757 TSPEAR Thrombospondin-type laminin G domain and EAR repeats 2.69E-01 7986426 DNM1P46 DNM1 pseudogene 46 2.69E-01 8127646 FILIP1 Filamin A interacting protein 1 2.69E-01 8013035 ZNF624 Zinc finger protein 624 2.69E-01 8015115 KRT12 Keratin 12 2.69E-01 7905533 IVL Involucrin 2.69E-01 7933194 CXCL12 Chemokine (C-X-C motif) ligand 12 2.69E-01 138  Probe Set ID Gene Symbol Gene Name FDR 7912520 NPPB Natriuretic peptide B 2.69E-01 7926708 THNSL1 Threonine synthase-like 1 (S. Cerevisiae) 2.69E-01 8018754 CYGB Cytoglobin 2.69E-01 8062796 GDAP1L1 Ganglioside-induced differentiation-associated protein 1- like 1 2.69E-01 8058542 C2orf80 Chromosome 2 open reading frame 80 2.69E-01 7987554 DNAJC17 Dnaj (Hsp40) homolog, subfamily C, member 17 2.69E-01 7902353 LHX8 LIM homeobox 8 2.69E-01 8006865 PPP1R1B Protein phosphatase 1, regulatory (inhibitor) subunit 1B 2.69E-01 7947274 MPPED2 Metallophosphoesterase domain containing 2 2.69E-01 8067662 PTK6 PTK6 protein tyrosine kinase 6 2.69E-01 7998427 TPSG1 Tryptase gamma 1 2.69E-01 7976681 CYP46A1 Cytochrome P450, family 46, subfamily A, polypeptide 1 2.69E-01 8180251 FLJ45508 Hypothetical protein LOC643721 2.69E-01 8045229 ARHGEF4 Rho guanine nucleotide exchange factor (GEF) 4 2.69E-01 7917875 F3 Coagulation factor III (thromboplastin, tissue factor) 2.69E-01 7901969 ROR1 Receptor tyrosine kinase-like orphan receptor 1 2.69E-01 8118963 FANCE Fanconi anemia, complementation group E 2.69E-01 8123259 PLG Plasminogen 2.69E-01 8090388 C3orf22 Chromosome 3 open reading frame 22 2.69E-01 8015242 KRTAP4-2 Keratin associated protein 4-2 2.69E-01 7961249 TAS2R10 Taste receptor, type 2, member 10 2.69E-01 8070789 KRTAP12-4 Keratin associated protein 12-4 2.69E-01 7901187 C1orf190 Chromosome 1 open reading frame 190 2.69E-01 7993713 IQCK IQ motif containing K 2.69E-01 7905283 ANXA9 Annexin A9 2.69E-01 8017867 FAM20A Family with sequence similarity 20, member A 2.69E-01 8164396 MIR199B Microrna 199b 2.69E-01 7903358 VCAM1 Vascular cell adhesion molecule 1 2.69E-01 8095728 EREG Epiregulin 2.69E-01 8025169 C19orf45 Chromosome 19 open reading frame 45 2.69E-01 8131705 RPL23P8 Ribosomal protein L23 pseudogene 8 2.69E-01 8091546 TMEM14E Transmembrane protein 14E 2.69E-01 7906900 DDR2 Discoidin domain receptor tyrosine kinase 2 2.69E-01 8177120 LOC10013228 8 Hypothetical protein LOC100132288 2.69E-01 8162006 GKAP1 G kinase anchoring protein 1 2.69E-01 7934178 PCBD1 Pterin-4 alpha-carbinolamine dehydratase/dimerization cofactor of hepatocyte nuclear factor 1 alpha 2.69E-01 8143708 ZNF425 Zinc finger protein 425 2.69E-01 8111821 HEATR7B2 HEAT repeat family member 7B2 2.69E-01 8130993 FAM20C Family with sequence similarity 20, member C 2.69E-01 139  Probe Set ID Gene Symbol Gene Name FDR 8088550 PRICKLE2 Prickle homolog 2 (Drosophila) 2.69E-01 7941917 CABP4 Calcium binding protein 4 2.69E-01 7963513 KRT76 Keratin 76 2.69E-01 8074153 ACR Acrosin 2.69E-01 8098368 ADAM29 ADAM metallopeptidase domain 29 2.69E-01 8099302 MIR95 Microrna 95 2.69E-01 8102468 PRSS12 Protease, serine, 12 (neurotrypsin, motopsin) 2.69E-01 8031253 LILRP2 Leukocyte immunoglobulin-like receptor pseudogene 2 2.69E-01 8060461 TMC2 Transmembrane channel-like 2 2.69E-01 7931097 HTRA1 Htra serine peptidase 1 2.69E-01 8015293 KRT32 Keratin 32 2.69E-01 8175572 SPANXN3 SPANX family, member N3 2.69E-01 7906197 HAPLN2 Hyaluronan and proteoglycan link protein 2 2.69E-01 8075785 FOXRED2 FAD-dependent oxidoreductase domain containing 2 2.69E-01 7929388 PLCE1 Phospholipase C, epsilon 1 2.69E-01 7944351 FOXR1 Forkhead box R1 2.69E-01 8000346 ERN2 Endoplasmic reticulum to nucleus signaling 2 2.69E-01 7903884 PROK1 Prokineticin 1 2.69E-01 7928766 C10orf99 Chromosome 10 open reading frame 99 2.69E-01 8136863 TMEM139 Transmembrane protein 139 2.69E-01 8039577 ZSCAN5A Zinc finger and SCAN domain containing 5A 2.69E-01 8037240 PSG1 Pregnancy specific beta-1-glycoprotein 1 2.69E-01 8173862 SATL1 Spermidine/spermine N1-acetyl transferase-like 1 2.69E-01 8179926 DOM3Z Dom-3 homolog Z (C. Elegans) 2.69E-01 8001163 MYLK3 Myosin light chain kinase 3 2.69E-01 8137485 DPP6 Dipeptidyl-peptidase 6 2.69E-01 8155747 C9orf135 Chromosome 9 open reading frame 135 2.69E-01 7997374 DYNLRB2 Dynein, light chain, roadblock-type 2 2.69E-01 7964535 CYP27B1 Cytochrome P450, family 27, subfamily B, polypeptide 1 2.69E-01 7944302 PHLDB1 Pleckstrin homology-like domain, family B, member 1 2.69E-01 8083576 LEKR1 Leucine, glutamate and lysine rich 1 2.69E-01 7960283 CACNA2D4 Calcium channel, voltage-dependent, alpha 2/delta subunit 4 2.69E-01 7947096 MRGPRX2 MAS-related GPR, member X2 2.69E-01 8092661 MASP1 Mannan-binding lectin serine peptidase 1 (C4/C2 activating component of Ra-reactive factor) 2.69E-01 8038314 C19orf73 Chromosome 19 open reading frame 73 2.69E-01 7964142 APOF Apolipoprotein F 2.69E-01 7987310 GJD2 Gap junction protein, delta 2, 36kda 2.69E-01 8015221 KRTAP4-11 Keratin associated protein 4-11 2.69E-01 8053551 REEP1 Receptor accessory protein 1 2.69E-01 8166619 MAGEB1 Melanoma antigen family B, 1 2.69E-01 140  Probe Set ID Gene Symbol Gene Name FDR 8117537 HIST1H4I Histone cluster 1, h4i 2.69E-01 8091491 CLRN1 Clarin 1 2.69E-01 7905503 LCE2C Late cornified envelope 2C 2.69E-01 8062490 SNORA60 Small nucleolar RNA, H/ACA box 60 2.69E-01 8160417 IFNA6 Interferon, alpha 6 2.69E-01 7934074 TACR2 Tachykinin receptor 2 2.69E-01 8039779 SLC27A5 Solute carrier family 27 (fatty acid transporter), member 5 2.69E-01 7993815 ANKS4B Ankyrin repeat and sterile alpha motif domain containing 4B 2.69E-01 8091972 MECOM MDS1 and EVI1 complex locus 2.69E-01 8015366 KRT14 Keratin 14 2.69E-01 8169836 XPNPEP2 X-prolyl aminopeptidase (aminopeptidase P) 2, membrane-bound 2.69E-01 8160024 GLDC Glycine dehydrogenase (decarboxylating) 2.69E-01 7995242 KIAA0664L3 KIAA0664-like 3 2.69E-01 8015868 MPP2 Membrane protein, palmitoylated 2 (MAGUK p55 subfamily member 2) 2.69E-01 7927723 C10orf107 Chromosome 10 open reading frame 107 2.69E-01 8026442 CYP4F8 Cytochrome P450, family 4, subfamily F, polypeptide 8 2.69E-01 8078435 TRIM71 Tripartite motif containing 71 2.69E-01 8160546 LINGO2 Leucine rich repeat and Ig domain containing 2 2.69E-01 7965231 MGAT4C Mannosyl (alpha-1,3-)-glycoprotein beta-1,4-N- acetylglucosaminyltransferase, isozyme C (putative) 2.69E-01 7972231 SLITRK1 SLIT and NTRK-like family, member 1 2.69E-01 7973022 OR4L1 Olfactory receptor, family 4, subfamily L, member 1 2.69E-01 7931140 FLJ46361 Deleted in malignant brain tumors 1 pseudogene 2.69E-01 8132715 C7orf57 Chromosome 7 open reading frame 57 2.69E-01 8020762 DSG3 Desmoglein 3 2.69E-01 8090955 A4GNT Alpha-1,4-N-acetylglucosaminyltransferase 2.69E-01 7996819 CDH3 Cadherin 3, type 1, P-cadherin (placental) 2.69E-01 7943787 HSPB2 Heat shock 27kda protein 2 2.69E-01 8100808 SULT1E1 Sulfotransferase family 1E, estrogen-preferring, member 1 2.69E-01 8109651 GABRA6 Gamma-aminobutyric acid (GABA) A receptor, alpha 6 2.69E-01 8011214 RTN4RL1 Reticulon 4 receptor-like 1 2.69E-01 8163618 TNFSF15 Tumor necrosis factor (ligand) superfamily, member 15 2.69E-01 8088315 DNAH12 Dynein, axonemal, heavy chain 12 2.69E-01 8064739 C20orf27 Chromosome 20 open reading frame 27 2.69E-01 8050844 LOC10013151 0 Hypothetical LOC100131510 2.69E-01 7982663 BUB1B Budding uninhibited by benzimidazoles 1 homolog beta (yeast) 2.69E-01 7927529 MSMB Microseminoprotein, beta 2.69E-01 7902754 CLCA3P Chloride channel accessory 3 (pseudogene) 2.94E-01 141  Probe Set ID Gene Symbol Gene Name FDR 7913990 GPATCH3 G patch domain containing 3 2.94E-01 8003844 GSG2 Germ cell associated 2 (haspin) 2.94E-01 7909503 SERTAD4 SERTA domain containing 4 2.94E-01 7937882 ART1 ADP-ribosyltransferase 1 2.94E-01 8109908 LOC257358 Hypothetical LOC257358 2.94E-01 7899615 SERINC2 Serine incorporator 2 2.94E-01 7922420 SERPINC1 Serpin peptidase inhibitor, clade C (antithrombin), member 1 2.94E-01 8066536 WFDC6 WAP four-disulfide core domain 6 2.94E-01 7920141 TCHH Trichohyalin 2.94E-01 8154245 PDCD1LG2 Programmed cell death 1 ligand 2 2.94E-01 7965573 NTN4 Netrin 4 2.94E-01 8091991 MECOM MDS1 and EVI1 complex locus 2.94E-01 8053139 C2orf81 Chromosome 2 open reading frame 81 2.94E-01 7937404 C11orf35 Chromosome 11 open reading frame 35 2.94E-01 7986822 GABRB3 Gamma-aminobutyric acid (GABA) A receptor, beta 3 2.94E-01 7931561 ZNF511 Zinc finger protein 511 2.94E-01 8107350 SRP19 Signal recognition particle 19kda 2.94E-01 7989985 ITGA11 Integrin, alpha 11 2.94E-01 8001387 SALL1 Sal-like 1 (Drosophila) 2.94E-01 8037970 PLA2G4C Phospholipase A2, group IVC (cytosolic, calcium- independent) 2.94E-01 8161255 SHB Src homology 2 domain containing adaptor protein B 2.94E-01 8153664 BOP1 Block of proliferation 1 2.94E-01 7978093 JPH4 Junctophilin 4 2.94E-01 8147721 FLJ45248 FLJ45248 protein 2.94E-01 7966229 MGC14436 Hypothetical LOC84983 2.94E-01 8135865 FSCN3 Fascin homolog 3, actin-bundling protein, testicular (Strongylocentrotus purpuratus) 2.94E-01 8074845 ZNF280B Zinc finger protein 280B 2.94E-01 8126240 FLJ41649 Hypothetical LOC401260 2.94E-01 7975562 PAPLN Papilin, proteoglycan-like sulfated glycoprotein 2.94E-01 8090938 DZIP1L DAZ interacting protein 1-like 2.94E-01 7976571 C14orf129 Chromosome 14 open reading frame 129 2.94E-01 8118644 RPS18 Ribosomal protein S18 2.94E-01 8178253 RPS18 Ribosomal protein S18 2.94E-01 8179544 RPS18 Ribosomal protein S18 2.94E-01 8097938 NPY2R Neuropeptide Y receptor Y2 2.94E-01 8071049 LOC51152 Melanoma antigen 2.94E-01 7951545 EXPH5 Exophilin 5 2.94E-01 8109333 GPX3 Glutathione peroxidase 3 (plasma) 2.94E-01 8127754 FLJ13744 Hypothetical FLJ13744 2.94E-01 142  Probe Set ID Gene Symbol Gene Name FDR 8066489 WFDC12 WAP four-disulfide core domain 12 2.94E-01 8103005 ANAPC10 Anaphase promoting complex subunit 10 2.94E-01 8154449 CNTLN Centlein, centrosomal protein 2.94E-01 8141169 MGC72080 MGC72080 pseudogene 2.94E-01 8160597 TAF1L TAF1 RNA polymerase II, TATA box binding protein (TBP)-associated factor, 210kda-like 2.94E-01 8059955 RAB17 RAB17, member RAS oncogene family 2.94E-01 7996034 CCL17 Chemokine (C-C motif) ligand 17 2.94E-01 8086400 LYZL4 Lysozyme-like 4 2.94E-01 7978021 MYH7 Myosin, heavy chain 7, cardiac muscle, beta 2.94E-01 8069744 RWDD2B RWD domain containing 2B 2.94E-01 8126486 CUL7 Cullin 7 2.94E-01 8170786 LCA10 Lung carcinoma-associated protein 10 2.94E-01 7933446 FRMPD2 FERM and PDZ domain containing 2 2.94E-01 8102321 PLA2G12A Phospholipase A2, group XIIA 2.94E-01 8101934 DNAJB14 Dnaj (Hsp40) homolog, subfamily B, member 14 2.94E-01 8117334 HIST1H4A Histone cluster 1, h4a 2.94E-01 7972428 OXGR1 Oxoglutarate (alpha-ketoglutarate) receptor 1 2.94E-01 7957790 FAM71C Family with sequence similarity 71, member C 2.94E-01 8096070 BMP3 Bone morphogenetic protein 3 2.94E-01 8044204 SULT1C3 Sulfotransferase family, cytosolic, 1C, member 3 2.94E-01 7925741 OR2T33 Olfactory receptor, family 2, subfamily T, member 33 2.94E-01 8043782 CNGA3 Cyclic nucleotide gated channel alpha 3 2.94E-01 8115840 NKX2-5 NK2 transcription factor related, locus 5 (Drosophila) 2.94E-01 8083887 CLDN11 Claudin 11 2.94E-01 7977105 TRMT61A Trna methyltransferase 61 homolog A (S. Cerevisiae) 2.94E-01 7949588 CD248 CD248 molecule, endosialin 2.94E-01 8084397 ECE2 Endothelin converting enzyme 2 2.94E-01 7969300 PRR20A Proline rich 20A 2.94E-01 7969306 PRR20A Proline rich 20A 2.94E-01 7969312 PRR20A Proline rich 20A 2.94E-01 7969318 PRR20A Proline rich 20A 2.94E-01 7969324 PRR20A Proline rich 20A 2.94E-01 7896921 TAS1R3 Taste receptor, type 1, member 3 2.94E-01 7977273 ADSSL1 Adenylosuccinate synthase like 1 2.94E-01 8043682 FAHD2B Fumarylacetoacetate hydrolase domain containing 2B 2.94E-01 8067985 NCAM2 Neural cell adhesion molecule 2 2.94E-01 8072328 SEC14L2 SEC14-like 2 (S. Cerevisiae) 2.94E-01 7929901 C10orf2 Chromosome 10 open reading frame 2 2.94E-01 8046048 CSRNP3 Cysteine-serine-rich nuclear protein 3 2.94E-01 8062944 SEMG2 Semenogelin II 2.94E-01 8011990 TEKT1 Tektin 1 2.94E-01 143  Probe Set ID Gene Symbol Gene Name FDR 8136961 OR2F2 Olfactory receptor, family 2, subfamily F, member 2 2.94E-01 7980485 DIO2 Deiodinase, iodothyronine, type II 2.94E-01 7959921 LOC338797 Hypothetical LOC338797 2.94E-01 8056710 C2orf77 Chromosome 2 open reading frame 77 2.94E-01 8061799 BPIL3 Bactericidal/permeability-increasing protein-like 3 2.94E-01 8154848 PRSS3 Protease, serine, 3 2.94E-01 8175933 RENBP Renin binding protein 2.94E-01 8096411 TIGD2 Tigger transposable element derived 2 2.94E-01 7979351 C14orf33 Chromosome 14 open reading frame 33 2.94E-01 7904761 ITGA10 Integrin, alpha 10 2.94E-01 8071206 MRPL40 Mitochondrial ribosomal protein L40 2.94E-01 8157696 OR5C1 Olfactory receptor, family 5, subfamily C, member 1 2.94E-01 7934959 MIR107 Microrna 107 2.94E-01 7924987 AGT Angiotensinogen (serpin peptidase inhibitor, clade A, member 8) 2.94E-01 8105596 RGS7BP Regulator of G-protein signaling 7 binding protein 2.94E-01 8015554 KCNH4 Potassium voltage-gated channel, subfamily H (eag- related), member 4 2.94E-01 8179011 MOG Myelin oligodendrocyte glycoprotein 2.94E-01 8018114 SDK2 Sidekick homolog 2 (chicken) 2.94E-01 8055872 CACNB4 Calcium channel, voltage-dependent, beta 4 subunit 2.94E-01 8151423 JPH1 Junctophilin 1 2.94E-01 7990309 STRA6 Stimulated by retinoic acid gene 6 homolog (mouse) 2.94E-01 8125048 DDAH2 Dimethylarginine dimethylaminohydrolase 2 2.94E-01 7939971 OR5J2 Olfactory receptor, family 5, subfamily J, member 2 2.94E-01 8070563 C21orf128 Chromosome 21 open reading frame 128 2.94E-01 8068231 OLIG2 Oligodendrocyte lineage transcription factor 2 2.94E-01 8049825 HDLBP High density lipoprotein binding protein 2.94E-01 7987145 FMN1 Formin 1 2.94E-01 8166899 NYX Nyctalopin 2.94E-01 8026587 NWD1 NACHT and WD repeat domain containing 1 2.94E-01 8135031 MUC12 Mucin 12, cell surface associated 2.94E-01 8154491 ADAMTSL1 ADAMTS-like 1 2.94E-01 8148966 RPL23AP53 Ribosomal protein L23a pseudogene 53 2.94E-01 8040419 MYCN V-myc myelocytomatosis viral related oncogene, neuroblastoma derived (avian) 2.94E-01 7987511 C15orf52 Chromosome 15 open reading frame 52 2.94E-01 8100664 TMPRSS11D Transmembrane protease, serine 11D 2.94E-01 7930320 CCDC147 Coiled-coil domain containing 147 2.94E-01 144  Appendix 7 — Lymphocyte-Correlated Probe Sets Significantly Lower-Expressed in DR than ER, Post-Allergen Inhalation Challenge (FDR≤0.30) Probe Set ID Gene Symbol Gene Name FDR 7937915 RRM1 Ribonucleotide reductase M1 9.86E-02 7982712 C15orf23 Chromosome 15 open reading frame 23 9.86E-02 8049297 SCARNA5 Small Cajal body-specific RNA 5 9.86E-02 8124521 HIST1H4K Histone cluster 1, h4k 9.86E-02 8124531 HIST1H3I Histone cluster 1, h3i 9.86E-02 8150962 TOX Thymocyte selection-associated high mobility group box 9.86E-02 8180255 HIST2H4B Histone cluster 2, h4b 9.86E-02 8180321 HIST2H4A Histone cluster 2, h4a 9.86E-02 7909601 SNORA16B Small nucleolar RNA, H/ACA box 16B 1.19E-01 7919589 HIST2H3D Histone cluster 2, h3d 1.19E-01 7919606 HIST2H2BF Histone cluster 2, h2bf 1.19E-01 7938348 WEE1 WEE1 homolog (S. Pombe) 1.19E-01 7952914 CCDC77 Coiled-coil domain containing 77 1.19E-01 7984263 PTPLAD1 Protein tyrosine phosphatase-like A domain containing 1 1.19E-01 8009417 KPNA2 Karyopherin alpha 2 (RAG cohort 1, importin alpha 1) 1.19E-01 8019737 KPNA2 Karyopherin alpha 2 (RAG cohort 1, importin alpha 1) 1.19E-01 8060813 MCM8 Minichromosome maintenance complex component 8 1.19E-01 8117598 HIST1H4J Histone cluster 1, h4j 1.19E-01 7919612 HIST2H3D Histone cluster 2, h3d 1.20E-01 8055426 MCM6 Minichromosome maintenance complex component 6 1.20E-01 7920244 S100A8 S100 calcium binding protein A8 1.39E-01 8047702 ICOS Inducible T-cell co-stimulator 1.39E-01 8060503 SNORD57 Small nucleolar RNA, C/D box 57 1.39E-01 8105828 CCNB1 Cyclin B1 1.39E-01 8106006 SMN1 Survival of motor neuron 1, telomeric 1.39E-01 8124416 HIST1H3D Histone cluster 1, h3d 1.39E-01 7913869 STMN1 Stathmin 1 1.41E-01 7919642 HIST2H2AB Histone cluster 2, h2ab 1.41E-01 7967386 MPHOSPH9 M-phase phosphoprotein 9 1.41E-01 7979307 DLGAP5 Discs, large (Drosophila) homolog-associated protein 5 1.41E-01 7985829 FANCI Fanconi anemia, complementation group I 1.41E-01 8049299 SCARNA6 Small Cajal body-specific RNA 6 1.41E-01 8053584 CD8A CD8a molecule 1.41E-01 8068898 HIST1H2BK Histone cluster 1, h2bk 1.41E-01 8083272 GYG1 Glycogenin 1 1.41E-01 8124397 HIST1H1C Histone cluster 1, h1c 1.41E-01 8135576 TES Testis derived transcript (3 LIM domains) 1.41E-01 7902398 SNORD45A Small nucleolar RNA, C/D box 45A 1.74E-01 145  Probe Set ID Gene Symbol Gene Name FDR 7952339 SNORD14C Small nucleolar RNA, C/D box 14C 1.74E-01 8053366 SUCLG1 Succinate-coa ligase, alpha subunit 1.74E-01 8095139 SRD5A3 Steroid 5 alpha-reductase 3 1.74E-01 8124534 HIST1H4L Histone cluster 1, h4l 1.74E-01 7905163 MRPS21 Mitochondrial ribosomal protein S21 2.01E-01 7926259 MCM10 Minichromosome maintenance complex component 10 2.01E-01 7947694 CKAP5 Cytoskeleton associated protein 5 2.01E-01 8066074 DSN1 DSN1, MIND kinetochore complex component, homolog (S. Cerevisiae) 2.01E-01 8147396 INTS8 Integrator complex subunit 8 2.01E-01 8160151 ZDHHC21 Zinc finger, DHHC-type containing 21 2.01E-01 7904465 HIST2H2BA Histone cluster 2, h2ba 2.32E-01 7904853 GPR89A G protein-coupled receptor 89A 2.32E-01 7905079 HIST2H2AA3 Histone cluster 2, h2aa3 2.32E-01 7905085 HIST2H3A Histone cluster 2, h3a 2.32E-01 7906386 PYHIN1 Pyrin and HIN domain family, member 1 2.32E-01 7909568 DTL Denticleless homolog (Drosophila) 2.32E-01 7910997 EXO1 Exonuclease 1 2.32E-01 7919243 CD160 CD160 molecule 2.32E-01 7919584 HIST2H2BF Histone cluster 2, h2bf 2.32E-01 7919614 HIST2H3A Histone cluster 2, h3a 2.32E-01 7919619 HIST2H2AA3 Histone cluster 2, h2aa3 2.32E-01 7921434 AIM2 Absent in melanoma 2 2.32E-01 7921900 SH2D1B SH2 domain containing 1B 2.32E-01 7922174 F5 Coagulation factor V (proaccelerin, labile factor) 2.32E-01 7929438 HELLS Helicase, lymphoid-specific 2.32E-01 7934026 DNA2 DNA replication helicase 2 homolog (yeast) 2.32E-01 7937020 MKI67 Antigen identified by monoclonal antibody Ki-67 2.32E-01 7948902 SNORD29 Small nucleolar RNA, C/D box 29 2.32E-01 7948904 SNORD28 Small nucleolar RNA, C/D box 28 2.32E-01 7953351 NCAPD2 Non-SMC condensin I complex, subunit D2 2.32E-01 7960728 SCARNA12 Small Cajal body-specific RNA 12 2.32E-01 7961198 KLRAP1 Killer cell lectin-like receptor subfamily A pseudogene 1 2.32E-01 7969243 CKAP2 Cytoskeleton associated protein 2 2.32E-01 7981181 SCARNA13 Small Cajal body-specific RNA 13 2.32E-01 7982333 LOC1004992 21 Hypothetical LOC100499221 2.32E-01 7982358 ARHGAP11A Rho gtpase activating protein 11A 2.32E-01 7985480 SCARNA15 Small Cajal body-specific RNA 15 2.32E-01 7986068 BLM Bloom syndrome, recq helicase-like 2.32E-01 7994109 PLK1 Polo-like kinase 1 2.32E-01 8005547 SNORD3A Small nucleolar RNA, C/D box 3A 2.32E-01 146  Probe Set ID Gene Symbol Gene Name FDR 8005553 SNORD3A Small nucleolar RNA, C/D box 3A 2.32E-01 8013323 SNORD3A Small nucleolar RNA, C/D box 3A 2.32E-01 8013325 SNORD3A Small nucleolar RNA, C/D box 3A 2.32E-01 8013329 SNORD3A Small nucleolar RNA, C/D box 3A 2.32E-01 8018849 TK1 Thymidine kinase 1, soluble 2.32E-01 8019842 TYMS Thymidylate synthetase 2.32E-01 8022640 DHFR Dihydrofolate reductase 2.32E-01 8033667 ZNF558 Zinc finger protein 558 2.32E-01 8040142 CPSF3 Cleavage and polyadenylation specific factor 3, 73kda 2.32E-01 8042211 B3GNT2 UDP-glcnac:betagal beta-1,3-N- acetylglucosaminyltransferase 2 2.32E-01 8043036 LOC1720 Dihydrofolate reductase pseudogene 2.32E-01 8054580 BUB1 Budding uninhibited by benzimidazoles 1 homolog (yeast) 2.32E-01 8058052 HSPD1 Heat shock 60kda protein 1 (chaperonin) 2.32E-01 8064844 PCNA Proliferating cell nuclear antigen 2.32E-01 8074925 LOC91316 Glucuronidase, beta/immunoglobulin lambda-like polypeptide 1 pseudogene 2.32E-01 8093053 TFRC Transferrin receptor (p90, CD71) 2.32E-01 8094240 CD38 CD38 molecule 2.32E-01 8095986 ANXA3 Annexin A3 2.32E-01 8102643 CCNA2 Cyclin A2 2.32E-01 8105949 SERF1A Small EDRK-rich factor 1A (telomeric) 2.32E-01 8105958 SMN1 Survival of motor neuron 1, telomeric 2.32E-01 8105995 SMA5 Glucuronidase, beta pseudogene 2.32E-01 8105997 SERF1A Small EDRK-rich factor 1A (telomeric) 2.32E-01 8107706 LMNB1 Lamin B1 2.32E-01 8109639 PTTG1 Pituitary tumor-transforming 1 2.32E-01 8111892 OXCT1 3-oxoacid coa transferase 1 2.32E-01 8117395 HIST1H2BF Histone cluster 1, h2bf 2.32E-01 8117408 HIST1H2AE Histone cluster 1, h2ae 2.32E-01 8117422 HIST1H4F Histone cluster 1, h4f 2.32E-01 8117426 HIST1H2BH Histone cluster 1, h2bh 2.32E-01 8124385 HIST1H4B Histone cluster 1, h4b 2.32E-01 8124527 HIST1H1B Histone cluster 1, h1b 2.32E-01 8127364 GUSBP4 Glucuronidase, beta pseudogene 4 2.32E-01 8144228 FLJ36840 Hypothetical LOC645524 2.32E-01 8146357 MCM4 Minichromosome maintenance complex component 4 2.32E-01 8151561 ZFAND1 Zinc finger, AN1-type domain 1 2.32E-01 8160238 PSIP1 PC4 and SFRS1 interacting protein 1 2.32E-01 8168470 COX7B Cytochrome c oxidase subunit viib 2.32E-01 8177647 SMN1 Survival of motor neuron 1, telomeric 2.32E-01 8177658 SERF1A Small EDRK-rich factor 1A (telomeric) 2.32E-01 147  Probe Set ID Gene Symbol Gene Name FDR 7899134 CCDC21 Coiled-coil domain containing 21 2.41E-01 7906613 SLAMF7 SLAM family member 7 2.41E-01 7918657 PTPN22 Protein tyrosine phosphatase, non-receptor type 22 (lymphoid) 2.41E-01 7921625 SLAMF6 SLAM family member 6 2.41E-01 7938366 WEE1 WEE1 homolog (S. Pombe) 2.41E-01 7950906 CTSC Cathepsin C 2.41E-01 7970864 HSPH1 Heat shock 105kda/110kda protein 1 2.41E-01 7989128 CNOT6L CCR4-NOT transcription complex, subunit 6-like 2.41E-01 7989132 RFX7 Regulatory factor X, 7 2.41E-01 7995128 ITGAX Integrin, alpha X (complement component 3 receptor 4 subunit) 2.41E-01 8019802 RNU2-1 RNA, U2 small nuclear 1 2.41E-01 8081953 GTF2E1 General transcription factor IIE, polypeptide 1, alpha 56kda 2.41E-01 8112902 DHFR Dihydrofolate reductase 2.41E-01 8117368 HIST1H4C Histone cluster 1, h4c 2.41E-01 8117594 HIST1H2BM Histone cluster 1, h2bm 2.41E-01 8123044 TULP4 Tubby like protein 4 2.41E-01 8124524 HIST1H2AK Histone cluster 1, h2ak 2.41E-01 8124537 HIST1H3J Histone cluster 1, h3j 2.41E-01 8131709 SP4 Sp4 transcription factor 2.41E-01 8144812 PCM1 Pericentriolar material 1 2.41E-01 8160033 SNRPE Small nuclear ribonucleoprotein polypeptide E 2.41E-01 8166989 ZNF673 Zinc finger family member 673 2.41E-01 148  Appendix 8 — Eosinophil-Correlated Probe Sets Significantly Higher-Expressed in DR than ER, Post-Allergen Inhalation Challenge (FDR≤0.30) Probe Set ID Gene Symbol Gene Name FDR 7905085 HIST2H3A Histone cluster 2, h3a 6.20E-02 7919589 HIST2H3D Histone cluster 2, h3d 6.20E-02 7919612 HIST2H3D Histone cluster 2, h3d 6.20E-02 7919614 HIST2H3A Histone cluster 2, h3a 6.20E-02 7929258 KIF11 Kinesin family member 11 6.20E-02 8105828 CCNB1 Cyclin B1 8.60E-02 8061579 TPX2 TPX2, microtubule-associated, homolog (Xenopus laevis) 8.83E-02 7929541 CC2D2B Coiled-coil and C2 domain containing 2B 8.86E-02 8124527 HIST1H1B Histone cluster 1, h1b 1.06E-01 7941505 CST6 Cystatin E/M 1.68E-01 7926259 MCM10 Minichromosome maintenance complex component 10 1.72E-01 7937020 MKI67 Antigen identified by monoclonal antibody Ki-67 1.72E-01 8001133 SHCBP1 SHC SH2-domain binding protein 1 1.72E-01 8124537 HIST1H3J Histone cluster 1, h3j 1.72E-01 7900699 CDC20 Cell division cycle 20 homolog (S. Cerevisiae) 1.73E-01 7923086 ASPM Asp (abnormal spindle) homolog, microcephaly associated (Drosophila) 1.73E-01 7952914 CCDC77 Coiled-coil domain containing 77 1.73E-01 7983969 CCNB2 Cyclin B2 1.73E-01 7989647 KIAA0101 Kiaa0101 1.73E-01 7993267 TNFRSF17 Tumor necrosis factor receptor superfamily, member 17 1.73E-01 8053584 CD8A CD8a molecule 1.73E-01 8054580 BUB1 Budding uninhibited by benzimidazoles 1 homolog (yeast) 1.73E-01 8089694 ZNF80 Zinc finger protein 80 1.73E-01 8096528 PDHA2 Pyruvate dehydrogenase (lipoamide) alpha 2 1.73E-01 8127987 SNORD50A Small nucleolar RNA, C/D box 50A 1.73E-01 8149109 DEFA4 Defensin, alpha 4, corticostatin 1.73E-01 8179564 KIFC1 Kinesin family member C1 1.73E-01 7913869 STMN1 Stathmin 1 1.89E-01 8068740 UMODL1 Uromodulin-like 1 1.89E-01 8103932 MLF1IP MLF1 interacting protein 1.89E-01 8117594 HIST1H2BM Histone cluster 1, h2bm 1.89E-01 8118669 KIFC1 Kinesin family member C1 1.89E-01 8124531 HIST1H3I Histone cluster 1, h3i 1.89E-01 8124534 HIST1H4L Histone cluster 1, h4l 1.89E-01 7919642 HIST2H2AB Histone cluster 2, h2ab 1.90E-01 7969288 OLFM4 Olfactomedin 4 1.90E-01 8014974 TOP2A Topoisomerase (DNA) II alpha 170kda 1.90E-01 149  Probe Set ID Gene Symbol Gene Name FDR 8025450 OR2Z1 Olfactory receptor, family 2, subfamily Z, member 1 1.90E-01 8090972 TXNDC6 Thioredoxin domain containing 6 1.90E-01 8122058 ARG1 Arginase, liver 1.90E-01 7919606 HIST2H2BF Histone cluster 2, h2bf 2.08E-01 7932221 C10orf111 Chromosome 10 open reading frame 111 2.08E-01 7940561 FEN1 Flap structure-specific endonuclease 1 2.08E-01 7952406 OR8B12 Olfactory receptor, family 8, subfamily B, member 12 2.08E-01 7954065 GPRC5A G protein-coupled receptor, family C, group 5, member A 2.08E-01 7963020 DHH Desert hedgehog 2.08E-01 7980425 ISM2 Isthmin 2 homolog (zebrafish) 2.08E-01 7994109 PLK1 Polo-like kinase 1 2.08E-01 8016494 TTLL6 Tubulin tyrosine ligase-like family, member 6 2.08E-01 8022640 DHFR Dihydrofolate reductase 2.08E-01 8027748 FXYD3 FXYD domain containing ion transport regulator 3 2.08E-01 8029098 CEACAM6 Carcinoembryonic antigen-related cell adhesion molecule 6 (non-specific cross reacting antigen) 2.08E-01 8031031 MIR516B2 Microrna 516b-2 2.08E-01 8059864 GBX2 Gastrulation brain homeobox 2 2.08E-01 8087907 SEMA3G Sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 3G 2.08E-01 8094278 NCAPG Non-SMC condensin I complex, subunit G 2.08E-01 8108301 KIF20A Kinesin family member 20A 2.08E-01 8123760 LY86-AS1 LY86 antisense RNA 1 (non-protein coding) 2.08E-01 8124391 HIST1H2AB Histone cluster 1, h2ab 2.08E-01 8149955 PBK PDZ binding kinase 2.08E-01 8157446 ORM1 Orosomucoid 1 2.08E-01 8160417 IFNA6 Interferon, alpha 6 2.08E-01 7914851 CLSPN Claspin 2.21E-01 7933190 LOC1001311 95 Hypothetical protein LOC100131195 2.21E-01 7938366 WEE1 WEE1 homolog (S. Pombe) 2.21E-01 7945660 FAM99A Family with sequence similarity 99, member A 2.21E-01 7951246 MMP8 Matrix metallopeptidase 8 (neutrophil collagenase) 2.21E-01 7991750 HBZ Hemoglobin, zeta 2.21E-01 8007071 CDC6 Cell division cycle 6 homolog (S. Cerevisiae) 2.21E-01 8037222 CEACAM8 Carcinoembryonic antigen-related cell adhesion molecule 8 2.21E-01 8079370 CCR9 Chemokine (C-C motif) receptor 9 2.21E-01 8100758 UGT2B7 UDP glucuronosyltransferase 2 family, polypeptide B7 2.21E-01 8100971 PPBP Pro-platelet basic protein (chemokine (C-X-C motif) ligand 7) 2.21E-01 8148548 PSCA Prostate stem cell antigen 2.21E-01 8150962 TOX Thymocyte selection-associated high mobility group box 2.21E-01 150  Probe Set ID Gene Symbol Gene Name FDR 8166585 FLJ32742 Hypothetical locus FLJ32742 2.21E-01 7902808 LOC339524 Hypothetical LOC339524 2.34E-01 7903565 GPSM2 G-protein signaling modulator 2 2.34E-01 7908161 C1orf21 Chromosome 1 open reading frame 21 2.34E-01 7909568 DTL Denticleless homolog (Drosophila) 2.34E-01 7909708 CENPF Centromere protein F, 350/400kda (mitosin) 2.34E-01 7919243 CD160 CD160 molecule 2.34E-01 7928882 C10orf116 Chromosome 10 open reading frame 116 2.34E-01 7929334 CEP55 Centrosomal protein 55kda 2.34E-01 7943349 ARHGAP42 Rho gtpase activating protein 42 2.34E-01 7945774 SLC22A18AS Solute carrier family 22 (organic cation transporter), member 18 antisense 2.34E-01 7945857 MRGPRG MAS-related GPR, member G 2.34E-01 7958711 CCDC63 Coiled-coil domain containing 63 2.34E-01 7963817 GTSF1 Gametocyte specific factor 1 2.34E-01 7977732 SNORD8 Small nucleolar RNA, C/D box 8 2.34E-01 7981601 IGHV4-31 Immunoglobulin heavy variable 4-31 2.34E-01 7982889 NUSAP1 Nucleolar and spindle associated protein 1 2.34E-01 7984263 PTPLAD1 Protein tyrosine phosphatase-like A domain containing 1 2.34E-01 7985829 FANCI Fanconi anemia, complementation group I 2.34E-01 7990683 ACSBG1 Acyl-coa synthetase bubblegum family member 1 2.34E-01 7991406 PRC1 Protein regulator of cytokinesis 1 2.34E-01 7998722 SNORD60 Small nucleolar RNA, C/D box 60 2.34E-01 8008201 NGFR Nerve growth factor receptor 2.34E-01 8019842 TYMS Thymidylate synthetase 2.34E-01 8030823 IGLON5 Iglon family member 5 2.34E-01 8034974 EPHX3 Epoxide hydrolase 3 2.34E-01 8040898 TRIM54 Tripartite motif containing 54 2.34E-01 8049297 SCARNA5 Small Cajal body-specific RNA 5 2.34E-01 8055941 RPRM Reprimo, TP53 dependent G2 arrest mediator candidate 2.34E-01 8061471 GINS1 GINS complex subunit 1 (Psf1 homolog) 2.34E-01 8062766 MYBL2 V-myb myeloblastosis viral oncogene homolog (avian)- like 2 2.34E-01 8063043 UBE2C Ubiquitin-conjugating enzyme E2C 2.34E-01 8064939 TMX4 Thioredoxin-related transmembrane protein 4 2.34E-01 8066384 GTSF1L Gametocyte specific factor 1-like 2.34E-01 8068898 HIST1H2BK Histone cluster 1, h2bk 2.34E-01 8092640 RFC4 Replication factor C (activator 1) 4, 37kda 2.34E-01 8092750 FGF12 Fibroblast growth factor 12 2.34E-01 8096875 ENPEP Glutamyl aminopeptidase (aminopeptidase A) 2.34E-01 8102643 CCNA2 Cyclin A2 2.34E-01 8113003 FLJ11292 Hypothetical protein FLJ11292 2.34E-01 151  Probe Set ID Gene Symbol Gene Name FDR 8116707 KU-MEL-3 Ku-mel-3 2.34E-01 8117395 HIST1H2BF Histone cluster 1, h2bf 2.34E-01 8117422 HIST1H4F Histone cluster 1, h4f 2.34E-01 8121784 FABP7 Fatty acid binding protein 7, brain 2.34E-01 8124385 HIST1H4B Histone cluster 1, h4b 2.34E-01 8126244 LRFN2 Leucine rich repeat and fibronectin type III domain containing 2 2.34E-01 8129880 PERP PERP, TP53 apoptosis effector 2.34E-01 8132743 ABCA13 ATP-binding cassette, sub-family A (ABC1), member 13 2.34E-01 8132811 C7orf72 Chromosome 7 open reading frame 72 2.34E-01 8132860 EGFR Epidermal growth factor receptor 2.34E-01 8139796 LOC441233 Hypothetical LOC441233 2.34E-01 8152962 LRRC6 Leucine rich repeat containing 6 2.34E-01 8160033 SNRPE Small nuclear ribonucleoprotein polypeptide E 2.34E-01 8180273 PCDHA12 Protocadherin alpha 12 2.34E-01 7901913 FOXD3 Forkhead box D3 2.45E-01 7904429 HSD3BP4 Hydroxy-delta-5-steroid dehydrogenase, 3 beta, pseudogene 4 2.45E-01 7904465 HIST2H2BA Histone cluster 2, h2ba 2.45E-01 7912629 KAZN Kazrin, periplakin interacting protein 2.45E-01 7921840 NR1I3 Nuclear receptor subfamily 1, group I, member 3 2.45E-01 7923562 CHIT1 Chitinase 1 (chitotriosidase) 2.45E-01 7926638 ARMC3 Armadillo repeat containing 3 2.45E-01 7927710 CDK1 Cyclin-dependent kinase 1 2.45E-01 7929674 C10orf62 Chromosome 10 open reading frame 62 2.45E-01 7934959 MIR107 Microrna 107 2.45E-01 7937868 C11orf36 Chromosome 11 open reading frame 36 2.45E-01 7938008 OR52D1 Olfactory receptor, family 52, subfamily D, member 1 2.45E-01 7938082 CNGA4 Cyclic nucleotide gated channel alpha 4 2.45E-01 7938348 WEE1 WEE1 homolog (S. Pombe) 2.45E-01 7944797 OR10G4 Olfactory receptor, family 10, subfamily G, member 4 2.45E-01 7947110 E2F8 E2F transcription factor 8 2.45E-01 7948107 OR5W2 Olfactory receptor, family 5, subfamily W, member 2 2.45E-01 7959761 FAM101A Family with sequence similarity 101, member A 2.45E-01 7961111 CLEC1A C-type lectin domain family 1, member A 2.45E-01 7964535 CYP27B1 Cytochrome P450, family 27, subfamily B, polypeptide 1 2.45E-01 7967386 MPHOSPH9 M-phase phosphoprotein 9 2.45E-01 7968062 ATP12A Atpase, H+/K+ transporting, nongastric, alpha polypeptide 2.45E-01 7969243 CKAP2 Cytoskeleton associated protein 2 2.45E-01 7972018 LOC1002882 08 Hypothetical protein LOC100288208 2.45E-01 7981020 ASB2 Ankyrin repeat and SOCS box containing 2 2.45E-01 152  Probe Set ID Gene Symbol Gene Name FDR 7982271 GOLGA8IP Golgin A8 family, member I (pseudogene) 2.45E-01 7982287 ARHGAP11B Rho gtpase activating protein 11B 2.45E-01 7983490 HMGN2P46 High-mobility group nucleosomal binding domain 2 pseudogene 46 2.45E-01 7989657 CSNK1G1 Casein kinase 1, gamma 1 2.45E-01 8001402 CHD9 Chromodomain helicase DNA binding protein 9 2.45E-01 8013671 SPAG5 Sperm associated antigen 5 2.45E-01 8018849 TK1 Thymidine kinase 1, soluble 2.45E-01 8025237 KIAA1543 Kiaa1543 2.45E-01 8025470 OR7D2 Olfactory receptor, family 7, subfamily D, member 2 2.45E-01 8026503 FLJ25328 Hypothetical LOC148231 2.45E-01 8026631 F2RL3 Coagulation factor II (thrombin) receptor-like 3 2.45E-01 8036270 THAP8 THAP domain containing 8 2.45E-01 8043890 NMS Neuromedin S 2.45E-01 8053753 TEKT4 Tektin 4 2.45E-01 8055143 LOC440905 Hypothetical LOC440905 2.45E-01 8055606 GTDC1 Glycosyltransferase-like domain containing 1 2.45E-01 8060503 SNORD57 Small nucleolar RNA, C/D box 57 2.45E-01 8060813 MCM8 Minichromosome maintenance complex component 8 2.45E-01 8061303 INSM1 Insulinoma-associated 1 2.45E-01 8079590 CAMP Cathelicidin antimicrobial peptide 2.45E-01 8089714 LSAMP Limbic system-associated membrane protein 2.45E-01 8098576 SLC25A4 Solute carrier family 25 (mitochondrial carrier; adenine nucleotide translocator), member 4 2.45E-01 8100827 IGJ Immunoglobulin J polypeptide, linker protein for immunoglobulin alpha and mu polypeptides 2.45E-01 8108716 PCDHB16 Protocadherin beta 16 2.45E-01 8112260 DEPDC1B DEP domain containing 1B 2.45E-01 8114470 LRRTM2 Leucine rich repeat transmembrane neuronal 2 2.45E-01 8114511 MZB1 Marginal zone B and B1 cell-specific protein 2.45E-01 8117334 HIST1H4A Histone cluster 1, h4a 2.45E-01 8117408 HIST1H2AE Histone cluster 1, h2ae 2.45E-01 8124437 HIST1H3F Histone cluster 1, h3f 2.45E-01 8124521 HIST1H4K Histone cluster 1, h4k 2.45E-01 8126095 C6orf129 Chromosome 6 open reading frame 129 2.45E-01 8127346 RAB23 RAB23, member RAS oncogene family 2.45E-01 8132642 PPIA Peptidylprolyl isomerase A (cyclophilin A) 2.45E-01 8135224 NFE4 Transcription factor NF-E4 2.45E-01 8136837 OR6V1 Olfactory receptor, family 6, subfamily V, member 1 2.45E-01 8138765 HOXA11 Homeobox A11 2.45E-01 8141846 FBXL13 F-box and leucine-rich repeat protein 13 2.45E-01 8144982 NPM2 Nucleophosmin/nucleoplasmin 2 2.45E-01 153  Probe Set ID Gene Symbol Gene Name FDR 8146649 MTFR1 Mitochondrial fission regulator 1 2.45E-01 8150433 NKX6-3 NK6 homeobox 3 2.45E-01 8151032 GGH Gamma-glutamyl hydrolase (conjugase, folylpolygammaglutamyl hydrolase) 2.45E-01 8155214 MELK Maternal embryonic leucine zipper kinase 2.45E-01 8158081 C9orf117 Chromosome 9 open reading frame 117 2.45E-01 8158167 LCN2 Lipocalin 2 2.45E-01 8168976 GPRASP2 G protein-coupled receptor associated sorting protein 2 2.45E-01 8171867 ARX Aristaless related homeobox 2.45E-01 8171885 DCAF8L1 DDB1 and CUL4 associated factor 8-like 1 2.45E-01 8175629 MAGEA11 Melanoma antigen family A, 11 2.45E-01 8180255 HIST2H4B Histone cluster 2, h4b 2.45E-01 8180321 HIST2H4A Histone cluster 2, h4a 2.45E-01 7896863 MIR429 Microrna 429 2.76E-01 7898616 PLA2G2F Phospholipase A2, group IIF 2.76E-01 7905496 C1orf46 Chromosome 1 open reading frame 46 2.76E-01 7905505 LCE2B Late cornified envelope 2B 2.76E-01 7919584 HIST2H2BF Histone cluster 2, h2bf 2.76E-01 7921275 FCRL3 Fc receptor-like 3 2.76E-01 7922174 F5 Coagulation factor V (proaccelerin, labile factor) 2.76E-01 7924096 NEK2 NIMA (never in mitosis gene a)-related kinase 2 2.76E-01 7924821 ZNF847P Zinc finger protein 847, pseudogene 2.76E-01 7937404 C11orf35 Chromosome 11 open reading frame 35 2.76E-01 7939897 FOLH1 Folate hydrolase (prostate-specific membrane antigen) 1 2.76E-01 7940626 SCGB2A1 Secretoglobin, family 2A, member 1 2.76E-01 7947694 CKAP5 Cytoskeleton associated protein 5 2.76E-01 7973105 RNASE3 Ribonuclease, rnase A family, 3 2.76E-01 7973797 COCH Coagulation factor C homolog, cochlin (Limulus polyphemus) 2.76E-01 7979307 DLGAP5 Discs, large (Drosophila) homolog-associated protein 5 2.76E-01 7979963 DPF3 D4, zinc and double PHD fingers, family 3 2.76E-01 7981718 IGHM Immunoglobulin heavy constant mu 2.76E-01 7982333 LOC1004992 21 Hypothetical LOC100499221 2.76E-01 8000779 TBX6 T-box 6 2.76E-01 8004784 ALOX15B Arachidonate 15-lipoxygenase, type B 2.76E-01 8005733 C20orf191 Nuclear receptor co-repressor 1 pseudogene 2.76E-01 8011218 MIR132 Microrna 132 2.76E-01 8020419 MIR320C1 Microrna 320c-1 2.76E-01 8039078 BIRC8 Baculoviral IAP repeat containing 8 2.76E-01 8040469 LOC1001313 73 Hypothetical LOC100131373 2.76E-01 8047702 ICOS Inducible T-cell co-stimulator 2.76E-01 154  Probe Set ID Gene Symbol Gene Name FDR 8062444 BPI Bactericidal/permeability-increasing protein 2.76E-01 8068496 SIM2 Single-minded homolog 2 (Drosophila) 2.76E-01 8070933 FTCD Formiminotransferase cyclodeaminase 2.76E-01 8071086 CECR2 Cat eye syndrome chromosome region, candidate 2 2.76E-01 8083897 TMEM212 Transmembrane protein 212 2.76E-01 8085287 C3orf10 Chromosome 3 open reading frame 10 2.76E-01 8086689 MYL3 Myosin, light chain 3, alkali; ventricular, skeletal, slow 2.76E-01 8101031 CDKL2 Cyclin-dependent kinase-like 2 (CDC2-related kinase) 2.76E-01 8103728 HMGB2 High-mobility group box 2 2.76E-01 8112902 DHFR Dihydrofolate reductase 2.76E-01 8124388 HIST1H3B Histone cluster 1, h3b 2.76E-01 8130785 GPR31 G protein-coupled receptor 31 2.76E-01 8131949 CBX3 Chromobox homolog 3 2.76E-01 8133728 ZP3 Zona pellucida glycoprotein 3 (sperm receptor) 2.76E-01 8134263 COL1A2 Collagen, type I, alpha 2 2.76E-01 8138547 TOMM7 Translocase of outer mitochondrial membrane 7 homolog (yeast) 2.76E-01 8138977 DPY19L1 Dpy-19-like 1 (C. Elegans) 2.76E-01 8144625 BLK B lymphoid tyrosine kinase 2.76E-01 8146357 MCM4 Minichromosome maintenance complex component 4 2.76E-01 8149774 LOXL2 Lysyl oxidase-like 2 2.76E-01 8151709 OSGIN2 Oxidative stress induced growth inhibitor family member 2 2.76E-01 8152715 KLHL38 Kelch-like 38 (Drosophila) 2.76E-01 8160284 HAUS6 HAUS augmin-like complex, subunit 6 2.76E-01 8163107 MIR32 Microrna 32 2.76E-01 8163892 C9orf31 Chromosome 9 open reading frame 31 2.76E-01 8164200 ANGPTL2 Angiopoietin-like 2 2.76E-01 8166665 FAM47B Family with sequence similarity 47, member B 2.76E-01 8166705 PRRG1 Proline rich Gla (G-carboxyglutamic acid) 1 2.76E-01 8168416 USMG5 Up-regulated during skeletal muscle growth 5 homolog (mouse) 2.76E-01 8176336 ASMTL-AS1 ASMTL antisense RNA 1 (non-protein coding) 2.76E-01 


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