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Dissecting the Genetic Architecture of Airway Hyperresponsiveness

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Asthma is a common, complex disease characterized by airway inflammation, reversible airway obstruction, and airway hyperresponsiveness (AHR), excessive narrowing of airways in response to a variety of stimuli including allergens and environmental factors. AHR is a key feature of asthma with a strong genetic component; however, with few exceptions, genes implicated in asthma susceptibility are primarily involved in the allergic arms of the disease, leaving the specific genetic architecture of AHR largely unknown. Two cytokines implicated in asthma pathogenesis, IL-13 and IL-17, can cause normal airway smooth muscle (ASM) to acquire AHR behavior, and yet the global transcriptional response of ASM to these cytokines - and how that transcriptional response relates to contractility changes - remains largely unexplored. In this application, we propose a novel, systems genetic approach to gene discovery that goes from a cellular model of ASM response to a human phenotype (AHR), with the ultimate goal of integrating genetic, genomic, cellular, and physiological approaches to unravel the genetic architecture of AHR and asthma. The major objective of the proposed study is to determine the genetic variants that influence ASM contractility and gene expression changes in response to IL-13 and/or IL-17, and to evaluate whether those variants predict AHR and asthma in people. We propose using three complementary approaches for discovering functional single nucleotide polymorphisms (SNPs) that influence AHR and asthma: (i) contractility studies in ASM cells from 120 individuals cultured with and without IL-13 and/or IL-17 using traction force microscopy before and after histamine exposure, followed by QTL mapping of cytokine-induced contractility; ii) expression quantitative trait locus (eQTL) mapping to identify SNPs that influence transcriptional response to these asthma-associated cytokines in the same ASM cells; and (iii) functional, gene-based GWAS of AHR and asthma using the overlapping QTLs and eQTLs identified in Aims 1 and 2, in ~1000 members of a large Hutterite pedigree who have been characterized for asthma and AHR phenotypes, and in non-Hutterite, ethnically diverse populations with asthma GWAS results. To our knowledge this is the first study to integrate these strategies to discover functional variation that influences asthma risk and to help interpret results of GWAS. This integrated strategy will ultimately lead to the identification of novel genes and pathways in asthma pathogenesis, and will yield insights into the contribution of important gene-environment interaction effects on gene expression and contractility in a cell model of a critical component of the disease. These novel approaches may serve as a paradigm for future genetic studies of asthma and other complex diseases.
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