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 at high accuracy (R2>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; 600 of the 675 variants (89%) were not present in the NHGRI-EBI GWAS Catalog. We replicated the effect directions of 28 of 28 height-associated variants genotyped in previous exome array studies, including missense variants in newly-associated collagen genes COL16A1 and COL11A2. Across all traits, 49% of associations (578/1,189) occurred in genes with two or more hits; follow-up analyses of these genes identified long allelic series containing up to 45 distinct likely-causal variants within the same gene (on average exhibiting 93%-concordant effect directions). In particular, 24 rare coding variants in IFRD2 independently associated with reticulocyte indices, suggesting an important role of IFRD2 in red blood cell development, and 11 rare coding variants in NPR2 (a gene previously implicated in Mendelian skeletal disorders) exhibited intermediate-to-strong effects on height (0.18-1.09 s.d.). 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.