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 ≈ 500,000) to impute exome-wide variants with 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 × 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.
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Access to the UKB Resource is available by application (http://www.ukbiobank.ac.uk/). Exome-wide summary association statistics for the 54 quantitative traits we analyzed are available at https://data.broadinstitute.org/lohlab/UKB_exomeWAS/ and data files containing allelic series for all gene–trait associations with multiple likely-causal variants are also available at this website.
The following publicly available software packages were used to perform analyses: Eagle2 (v.2.3.5), https://data.broadinstitute.org/alkesgroup/Eagle/; Minimac4 (v.1.0.1), https://genome.sph.umich.edu/wiki/Minimac4; BOLT–LMM (v.2.3.4), https://data.broadinstitute.org/alkesgroup/BOLT-LMM/; FINEMAP (v.1.3.1), http://www.christianbenner.com/; plink (v.1.9 and v.2.0), https://www.cog-genomics.org/plink2/ and tsinfer (v.0.1.4), https://tsinfer.readthedocs.io/en/latest/. Information from the following databases were also used: VEP (v.95 on GRCh37 with GENCODE 19), https://www.ensembl.org/vep; CADD (v.1.5), https://cadd.gs.washington.edu/download; SpliceAI (v.1.2.1) https://github.com/Illumina/SpliceAI; NHGRI–EBI GWAS Catalog (v.1.0), https://www.ebi.ac.uk/gwas/home; TOPMed (v.r2, 97,256 TOPMed samples), https://imputation.biodatacatalyst.nhlbi.nih.gov/#!pages/about; Protein Data Bank, https://www.rcsb.org/; SWISS-MODEL, https://swissmodel.expasy.org/ and PANTHER (v.15.0), http://www.pantherdb.org/. Scripts used to perform the downstream analyses described above are available at https://data.broadinstitute.org/lohlab/UKB_exomeWAS/ (https://doi.org/10.5281/zenodo.4771214).
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We thank A. Gusev, M. Hujoel, P. Palamara, A. Price and S. Sunyaev for helpful discussions. This research was conducted using the UKB Resource under application no. 10438. A.R.B. was supported by US NIH grant T32 HG229516 and fellowship F31 HL154537. M.A.S. was supported by the MIT John W. Jarve (1978) Seed Fund for Science Innovation and US NIH Fellowship F31 MH124393. R.E.M. was supported by US NIH grant K25 HL150334 and NSF grant DMS-1939015. P.-R.L. was supported by US NIH grant DP2 ES030554, a Burroughs Wellcome Fund Career Award at the Scientific Interfaces, the Next Generation Fund at the Broad Institute of MIT and Harvard, and a Sloan Research Fellowship. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Computational analyses were performed on the O2 High Performance Compute Cluster, supported by the Research Computing Group, at Harvard Medical School (http://rc.hms.harvard.edu).
The authors declare no competing interests.
Peer review information Nature Genetics thanks S. Petrovski and S. Carmi for their contribution to the peer review of this work. Peer reviewer reports are available.
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Barton, A.R., Sherman, M.A., Mukamel, R.E. et al. Whole-exome imputation within UK Biobank powers rare coding variant association and fine-mapping analyses. Nat Genet 53, 1260–1269 (2021). https://doi.org/10.1038/s41588-021-00892-1