Defining the functional variation underlying atrial fibrillation risk

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Project Summary: Atrial fibrillation (AF) is the most common cardiac arrhythmia, which affects over 3 million Americans. AF confers an increased risk of hospitalization, stroke, dementia, heart failure and death and places a major burden on the healthcare system. AF, particularly in younger individuals, arises from the ectopic stimuli within the pulmonary veins with propagation to left atrium; however, many other aspects of the underlying mechanisms for AF remain unresolved. Although many clinical risk factors have been identified, in recent years we have come to appreciate that AF is heritable. A proportion of this heritability is conferred through common genetic variation. Using, genome-wide association studies (GWAS), our group and others have identified 26 independent genetic loci for AF. These loci can provide a unique and often unexpected window into the mechanisms of disease; however, as with other GWAS studies, a primary challenge is moving from an association to a specific disease mechanism. There are at least three major challenges that make it difficult to link a genetic association to a specific disease mechanism. First, GWAS loci often reside in gene-dense regions, making it difficult to identify which gene is associated with disease. Second, the overwhelming majority of GWAS loci reside in non-coding regions of the genome. The disease risk variants are presumed to alter the activity of regulatory elements that modulate nearby gene expression in a cell-specific manner. Finally, these GWAS loci can be large, and it can be challenge to identify the functional variant from among the many common variants at a locus. Given these challenges, the truly causative variants and the gene of interest are unknown for most GWAS loci. This knowledge gap greatly impedes the ability to leverage GWAS data for translational potential, as any modeling of gene function at these loci would be speculative. These issues are not exclusive to AF, instead pertaining not only to similar studies across other cardiovascular diseases and traits, but also the thousands of GWAS loci in the full spectrum of human diseases and traits uncovered in the past decade. The focus of the current proposal is to address these knowledge gaps for AF GWAS loci, with the ultimate goal of applying new insights to other cardiovascular disease loci. Given the genomic localization of most GWAS signals, this proposal operates under the overarching hypothesis that non-coding variation at AF- association loci alters gene expression in adult human left atrium, ultimately leading to AF susceptibility. We propose to leverage the genome sequencing based association data and our left atrial tissue repository for epigenetic definition and functional variant discovery. We will then use the same genotype information to identify the gene targets of each association locus.