Low coverage whole genome sequencing enables accurate assessment of common variants and calculation of genome-wide polygenic scores

作者：Julian R. Homburger, Cynthia L. Neben, Gilad Mishne, Alicia Y. Zhou, Sekar Kathiresan, Amit V. Khera · 发表于：Genome Medicine · 年份：2019 · DOI：10.1186/s13073-019-0682-2 · 被引用次数：134 · 研究领域：Genetic Associations and Epidemiology、Genomics and Rare Diseases、BRCA gene mutations in cancer

BACKGROUND: Inherited susceptibility to common, complex diseases may be caused by rare, pathogenic variants ("monogenic") or by the cumulative effect of numerous common variants ("polygenic"). Comprehensive genome interpretation should enable assessment for both monogenic and polygenic components of inherited risk. The traditional approach requires two distinct genetic testing technologies-high coverage sequencing of known genes to detect monogenic variants and a genome-wide genotyping array followed by imputation to calculate genome-wide polygenic scores (GPSs). We assessed the feasibility and accuracy of using low coverage whole genome sequencing (lcWGS) as an alternative to genotyping arrays to calculate GPSs. METHODS: First, we performed downsampling and imputation of WGS data from ten individuals to assess concordance with known genotypes. Second, we assessed the correlation between GPSs for 3 common diseases-coronary artery disease (CAD), breast cancer (BC), and atrial fibrillation (AF)-calculated using lcWGS and genotyping array in 184 samples. Third, we assessed concordance of lcWGS-based genotype calls and GPS calculation in 120 individuals with known genotypes, selected to reflect diverse ancestral backgrounds. Fourth, we assessed the relationship between GPSs calculated using lcWGS and disease phenotypes in a cohort of 11,502 individuals of European ancestry. RESULTS: = 0.93-0.97) with similar score distributions. Using lcWGS data from 120 individuals of diverse an...