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 approximate to 500,000) 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 genome-wide association studies, 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.

Automated summary

This study leveraged haplotype sharing in the UK Biobank to impute exome-wide variants and identified significant associations involving rare protein-altering variants. The research revealed significant associations in multiple genes and proposed allelic series containing multiple "likely-causal" variants.