Whole-exome imputation within UK Biobank powers rare coding variant association and fine-mapping analyses

Exome association studies to date have generally been underpowered to systematically evaluate the phenotypic impact of very rare coding variants. We leveraged extensive haplotype sharing between 49,960 exome-sequenced UK Biobank participants and the remainder of the cohort (total N~500K) to impute exome-wide variants with accuracy (R(2)>0.5) down to minor allele frequency (MAF) ~0.00005. Association and fine-mapping analyses of 54 quantitative traits identified 1,189 significant associations (P<5 x 10(−8)) involving 675 distinct rare protein-altering variants (MAF<0.01) that passed stringent filters for likely causality. Across all traits, 49% of associations (578/1,189) occurred in genes with two or more hits; follow-up analyses of these genes identified allelic series containing up to 45 distinct likely-causal variants. Our results demonstrate the utility of within-cohort imputation in population-scale GWAS cohorts, provide a catalog of likely-causal, large-effect coding variant associations, and foreshadow the insights that will be revealed as genetic biobank studies continue to grow.