Pan-UK Biobank GWAS improves discovery, analysis of genetic architecture, and resolution into ancestry-enriched effects

Konrad J. Karczewski(Broad Institute), Rahul Gupta(Broad Institute), Masahiro Kanai(Broad Institute), Wenhan Lu(Broad Institute), Kristin Tsuo(Broad Institute), Ying Wang(Broad Institute), Raymond K. Walters(Broad Institute), Patrick Turley(University of Southern California), Shawneequa Callier(National Institutes of Health), Nirav N. Shah, Nikolas Baya(Broad Institute), Duncan S. Palmer(Broad Institute), Jacqueline I. Goldstein(Broad Institute), Gopal Sarma(Broad Institute), Matthew Solomonson(Broad Institute), Nathan Cheng(Broad Institute), Sam Bryant(Broad Institute), Claire Churchhouse(Broad Institute), Caroline Cusick(Broad Institute), Timothy Poterba(Broad Institute), John Compitello(Broad Institute), Daniel A. King(Broad Institute), Wei Zhou(Broad Institute), Cotton Seed(Broad Institute), Hilary K. Finucane(Broad Institute), Mark J. Daly(Broad Institute), Benjamin M. Neale(Broad Institute), Elizabeth G. Atkinson(Baylor College of Medicine), Alicia R. Martin(Broad Institute)
medRxiv
March 15, 2024
Cited by 171Open Access
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Abstract

Summary Large biobanks, such as the UK Biobank (UKB), enable massive phenome by genome-wide association studies that elucidate genetic etiology of complex traits. However, individuals from diverse genetic ancestry groups are often excluded from association analyses due to concerns about population structure introducing false positive associations. Here, we generate mixed model associations and meta-analyses across genetic ancestry groups, inclusive of a larger fraction of the UKB than previous efforts, to produce freely-available summary statistics for 7,266 traits. We build a quality control and analysis framework informed by genetic architecture. Overall, we identify 14,676 significant loci (p < 5 x 10 -8 ) in the meta-analysis that were not found in the EUR genetic ancestry group alone, including novel associations for example between CAMK2D and triglycerides. We also highlight associations from ancestry-enriched variation, including a known pleiotropic missense variant in G6PD associated with several biomarker traits. We release these results publicly alongside FAQs that describe caveats for interpretation of results, enhancing available resources for interpretation of risk variants across diverse populations.


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