Abstract 14052: Feasibility of Whole Genome Sequencing for Atrial Fibrillation
Background: Genome-wide association studies (GWAS) have identified 14 loci associated with atrial fibrillation (AF). Whole genome sequencing (WGS) may enable the identification of causal variation underlying AF through greater variant ascertainment than with genotyping arrays. We report interim results for a subset of the NHLBI Trans-Omics for Precision Medicine WGS Program, in which ~3000 individuals with early-onset AF (onset ≤65 years of age) and 4000 referent individuals will be sequenced.
Methods: In the current freeze, 1423 individuals with early-onset AF from 9 studies and 1431 referent individuals from the Framingham Heart Study underwent WGS at the Broad Institute (Cambridge, MA) and passed quality control filters. Variants were jointly called at the University of Michigan. European ancestry was verified using principal components. Common variants (≥5%) were tested for association with AF after age- and sex-adjustment. Low-frequency and rare variants were grouped in regions of interest and tested for association with AF.
Results: AF cases were younger than referents (53±14 vs. 59±15, p<0.001) and a greater proportion were male (68% vs 43%, p<0.001). The mean sequencing read depth ranged from 34.5x-38.9x across the different studies. In total, 55,106,124 variants were included in association analyses, a substantially greater number than in studies predating WGS (e.g., ~2.2 million in a prior HapMap GWAS). Most variants were rare (85% with an allele frequency <1%). We observed expected associations between variants at established AF loci from prior GWAS. For example, variants at the top AF susceptibility locus on chromosome 4q25 were highly associated with AF (rs2220427_T, OR 1.68, 95%CI 1.46-1.95, p=2x10-12). Ongoing group-based tests will enable the assessment of variation in individual genes and noncoding regions for an association with AF.
Conclusions: Our results demonstrate the feasibility of performing large-scale WGS for common diseases. WGS enables greater interrogation of genetic variation as compared to GWAS. Future analyses will include larger study samples, assessment of structural genomic variation, and integration with high-throughput assays to discover functional elements underlying AF pathogenesis.
Author Disclosures: S. Lubitz: Research Grant; Significant; NIH, Doris Duke. Consultant/Advisory Board; Significant; St. Jude Medical. H. Lin: None. L. Weng: None. K. Lunetta: Research Grant; Significant; NIH. C. Roselli: None. N. Gupta: None. S. Gabriel: None. G. Abecasis: Consultant/Advisory Board; Significant; Regeneron Genetics Center. D. MacArthur: None. C. Albert: None. A. Alonso: Research Grant; Significant; American Heart Association. D. Arking: None. D. Chasman: None. V. Ramachandran: None. D. Roden: Research Grant; Modest; NIH. M. Shoemaker: None. S. Heckbert: Research Grant; Significant; NIH. D. Darbar: None. E. Benjamin: Research Grant; Significant; NIH. P. Ellinor: Research Grant; Significant; NIH, Bayer HealthCare, AHA.
- © 2016 by American Heart Association, Inc.