Pan-UK Biobank genome-wide association analyses enhance discovery and resolution of ancestry-enriched effects
Authors
Konrad J. Karczewski, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Rahul Gupta, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Masahiro Kanai, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Wenhan Lu, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Kristin Tsuo, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Ying Wang, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Raymond K. Walters, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.
Patrick Turley, Department of Economics, University of Southern California, Los Angeles, CA, USA.
Shawneequa Callier, Department of Clinical Research and Leadership, The George Washington University, Washington, DC, USA.
Nirav N. Shah, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Nikolas Baya, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Duncan S. Palmer, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Jacqueline I. Goldstein, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Gopal Sarma, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Matthew Solomonson, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Nathan Cheng, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Sam Bryant, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Claire Churchhouse, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Caroline M. Cusick, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Timothy Poterba, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
John Compitello, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Daniel King, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Wei Zhou, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Cotton Seed, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Hilary K. Finucane, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Mark J. Daly, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Benjamin M. Neale, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Elizabeth G. Atkinson, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.
Alicia R. Martin, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. armartin@broadinstitute.org.
Document Type
Journal Article
Publication Date
9-18-2025
DOI
10.1038/s41588-025-02335-7
Abstract
Large biobanks, such as the UK Biobank (UKB), enable massive phenome by genome-wide association studies that elucidate genetic etiology of complex traits. However, people 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 UK Biobank 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 × 10) in the meta-analysis that were not found in the EUR genetic ancestry group alone, including new 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 frequently asked questions that describe caveats for interpretation of results, enhancing available resources for interpretation of risk variants across diverse populations.
APA Citation
Karczewski, Konrad J.; Gupta, Rahul; Kanai, Masahiro; Lu, Wenhan; Tsuo, Kristin; Wang, Ying; Walters, Raymond K.; Turley, Patrick; Callier, Shawneequa; Shah, Nirav N.; Baya, Nikolas; Palmer, Duncan S.; Goldstein, Jacqueline I.; Sarma, Gopal; Solomonson, Matthew; Cheng, Nathan; Bryant, Sam; Churchhouse, Claire; Cusick, Caroline M.; Poterba, Timothy; Compitello, John; King, Daniel; Zhou, Wei; Seed, Cotton; Finucane, Hilary K.; Daly, Mark J.; Neale, Benjamin M.; Atkinson, Elizabeth G.; and Martin, Alicia R., "Pan-UK Biobank genome-wide association analyses enhance discovery and resolution of ancestry-enriched effects" (2025). GW Authored Works. Paper 7936.
https://hsrc.himmelfarb.gwu.edu/gwhpubs/7936
Department
Clinical Research and Leadership
