Integrative genomic, transcriptomic and proteomic studies of pulmonary function and COPD

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Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States. COPD is defined by a decrease in lung function as measured by pulmonary function testing (PFT), namely forced expiratory volume in one second (FEV1) and its ratio to forced vital capacity (FEV1/FVC). While the main risk factor for COPD is cigarette smoking, the risk of COPD also increases with age, and COPD can progress despite smoking cessation. There are no current pharmacologic therapies that slow progression of COPD or affect mortality. Large-scale genome-wide association studies (GWAS) of PFT and COPD have identified > 200 associated genetic loci. However, COPD and PFT GWAS have been limited by imperfect matching and sample sizes of reference panels (e.g. HapMap or 1000 Genomes), and downstream interpretation has been limited by lack of disease- and tissue-specific eQTL and pQTL resources and under-represention in African American and Hispanic/Latino subjects for both common and rare variants. In addition, all studies used for GWAS performed to date have limited representation of rare and infrequent risk-associated variants. The NHLBI TOPMed program is now generating RNA-seq and proteomics data for thousands of TOPMed participants with whole genome sequence (WGS) data. TOPMed specifically is enhanced with subjects of non- European ancestry populations, thereby increasing ethnic diversity and including participants from the population-based Multi-Ethnic Study of Atherosclerosis [MESA], the COPD-enriched COPDGene study, and the Lung Tissue Research Consortium [LTRC]). We hypothesize systematic integration of multi-omic data with novel rare/infrequent variant associations identified through TOPMed will accelerate discovery and validation of novel biomarkers, definition of the molecular mechanisms underlying pathogenesis of COPD, and construction of improved genetic risk models for diverse ancestry populations. To address these overarching hypotheses, we propose two Specific Aims. In Aim 1, we will identify rare/infrequent and common variation underlying PFT and COPD through expanded WGS analysis in TOPMed, perform multi-ancestry fine mapping, and construct new genetic risk prediction models tailored to African ancestry and multi-ancestry applications. In Aim 2, we will identify and validate candidate genes and molecular targets underlying known and novel genetic associations for PFT / COPD through comprehensive multi-omic and functional studies. To accomplish these Aims, we will combine the most current methods for WGS analysis with novel multi-omics approaches to leverage our large-scale high quality RNA-seq and proteomic resources. We have assembled an interdisciplinary collaborative group representing expertise in statistical genetics, pulmonary epidemiology, integrative genomics, proteomics, and pulmonary medicine. Completion of these Aims will establish an expanded view of rare and common genetic variation and their downstream molecular targets in multi-ethnic samples from population-based and COPD-enriched cohorts.