Using Integrative Genomics To Identify and Characterize Emphysema-Associated eQTL

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DESCRIPTION (provided by applicant): Chronic obstructive pulmonary disease (COPD) is a major public health burden, and it is the third leading cause of death in the US. Genome-wide association studies (GWAS) in COPD have successfully identified disease-associated genetic loci, but most of the genetic susceptibility to this disease has yet to be explained. The translatin of GWAS discoveries into new disease-modifying treatments requires the continued discovery and functional characterization of GWAS-identified loci. It is clear that many GWAS loci are gene expression quantitative trait loci (i.e. eQTLs) and that fine modulation of gene expression patterns is a key component of the genetic architecture of complex diseases, including COPD. COPD is a complex clinical syndrome that may consist of distinct biological processes. One fruitful approach to this complexity is to identify COPD-associated phenotypes, such as emphysema, that have their own strong GWAS signals and distinct biology. Emphysema is a heritable phenotype. However, few studies have been able to generate emphysema phenotypes in samples large enough for adequately-powered GWAS, and existing quantitative emphysema measures have known limitations. Using a novel, approach for emphysema quantification from lung computed tomography scans based on local histograms, we have generated detailed quantitative emphysema measures on over 9,000 subjects in the COPDGene Study that are more informative than traditional emphysema measures. This proposal is based on two hypotheses - 1) GWAS of local histogram emphysema patterns will identify novel emphysema-associated genetic variants and 2) genetic control of gene expression is an important mechanism by which genetic variation impacts the emphysema phenotype. To investigate these hypotheses, we propose the following specific aims. In Aim 1, updated LHE phenotypes will be generated in the COPDGene and ECLIPSE studies, and GWAS will be performed to identify emphysema-associated genetic variants. In Aim 2, eQTL analysis using RNA-Seq data will be performed in bronchial epithelial cells (BECs) and whole blood samples from COPDGene subjects with a range of emphysema. These eQTL and GWAS results will be integrated to identify novel emphysema-associated loci and link these loci to the genes through which they exert their phenotypic effects. In Aim 3a, we will identify genomic regions that are likely to be causally-linked to emphysema susceptibility through an innovative approach integrating GWAS, eQTL, and functional regulatory data from the ENCODE and Roadmap Epigenomics projects. In Aim 3b, the functional relevance of these genomic regions will be examined in cell-based functional assays in BEC cell lines. This work builds on strong preliminary data, and the research team has a history of close collaboration and multidisciplinary expertise in areas critical for this project.