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Analyses of biomarker traits in diverse UK biobank participants identify associations missed by European-centric analysis strategies

Journal of Human Genetics volume 67, pages 87–93 (2022)Cite this article

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Abstract

Despite the dramatic underrepresentation of non-European populations in human genetics studies, researchers continue to exclude participants of non-European ancestry, as well as variants rare in European populations, even when these data are available. This practice perpetuates existing research disparities and can lead to important and large effect size associations being missed. Here, we conducted genome-wide association studies (GWAS) of 31 serum and urine biomarker quantitative traits in African (n = 9354), East Asian (n = 2559), and South Asian (n = 9823) ancestry UK Biobank (UKBB) participants. We adjusted for all known GWAS catalog variants for each trait, as well as novel signals identified in a recent European ancestry-focused analysis of UKBB participants. We identify 7 novel signals in African ancestry and 2 novel signals in South Asian ancestry participants (p < 1.61E−10). Many of these signals are highly plausible, including a cis pQTL for the gene encoding gamma-glutamyl transferase and PIEZO1 and G6PD variants with impacts on HbA1c through likely erythrocytic mechanisms. This work illustrates the importance of using the genetic data we already have in diverse populations, with novel discoveries possible in even modest sample sizes.

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Data availability

Data are available upon request from the UK Biobank https://www.ukbiobank.ac.uk/.

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Acknowledgements

This research has been conducted using the UK Biobank Resource under Application Number 25953. LMR is supported by T32 HL129982, R01HG010297, and KL2 TR00249. NF is supported by the NIH DK117445, MD012765, and HL140385. MPL is supported by F32 HL149256. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. We would like to acknowledge the use of the Trans-Omics in Precision Medicine (TOPMed) program imputation panel (freeze 8 versions) supported by the National Heart, Lung and Blood Institute (NHLBI); see www.nhlbiwgs.org. TOPMed study investigators contributed data to the reference panel, which was accessed through https://imputation.biodatacatalyst.nhlbi.nih.gov. The panel was constructed and implemented by the TOPMed Informatics Research Center at the University of Michigan (3R01HL-117626-02S1; contract HHSN268201800002I). The TOPMed Data Coordinating Center (R01HL-120393; U01HL-120393; contract HHSN268201800001I) provided additional data management, sample identity checks, and overall program coordination and support. We gratefully acknowledge the studies and participants who provided biological samples and data for TOPMed. The BioVU projects at Vanderbilt University Medical Center are supported by numerous sources: institutional funding, private agencies, and federal grants. These include the NIH-funded Shared Instrumentation Grant S10OD017985 and S10RR025141; CTSA grants UL1TR002243, UL1TR000445, and UL1RR024975 from the National Center for Advancing Translational Sciences. Its contents are solely the responsibility of the authors and do not necessarily represent official views of the National Center for Advancing Translational Sciences or the National Institutes of Health. Genomic data are also supported by investigator-led projects that include U01HG004798, R01NS032830, RC2GM092618, P50GM115305, U01HG006378, U19HL065962, R01HD074711; and additional funding sources listed at https://victr.vumc.org/biovu-funding/. The PAGE Study is funded by the National Human Genome Research Institute (NHGRI) with co-funding from the National Institute on Minority Health and Health Disparities (NIMHD). The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. Genotyping services were provided by the Center for Inherited Disease Research (CIDR). CIDR is fully funded through a federal contract from the National Institutes of Health to Johns Hopkins University. Genotype data quality control and quality assurance services were provided by the Genetic Analysis Center in the Biostatistics Department of the University of Washington, through support provided by the CIDR contract. Funding support for the “Exonic variants and their relation to complex traits in minorities of the WHI” study is provided through the NHGRI PAGE program (NIH U01HG007376). The WHI program is funded by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C. The authors thank the WHI investigators and staff for their dedication and the study participants for making the program possible. A listing of WHI investigators can be found at: https://www.whi.org/researchers/Documents%20%20Write%20a%20Paper/WHI%20Investigator%20Long%20List.pdf.

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Author notes

  1. These authors contributed equally: Yun Li, Laura M. Raffield.

Authors and Affiliations

  1. Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA

    Quan Sun, Bryce Rowland & Yun Li

  2. Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA

    Misa Graff, Moa P. Lee, Christy L. Avery, Nora Franceschini & Kari E. North

  3. Department of Genetics, University of North Carolina, Chapel Hill, NC, USA

    Jia Wen, Le Huang, Yun Li & Laura M. Raffield

  4. Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA

    Tyne W. Miller-Fleming & Nancy J. Cox

  5. Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    Jeffrey Haessler & Charles Kooperberg

  6. The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Michael H. Preuss

  7. Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore

    Jin-Fang Chai & Xueling Sim

  8. Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore

    Ching-Yu Cheng

  9. Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore

    Ching-Yu Cheng

  10. Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

    Ching-Yu Cheng

  11. Carolina Center of Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA

    Kari E. North

  12. Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA

    Yun Li

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  1. Quan Sun
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Correspondence to Laura M. Raffield.

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Sun, Q., Graff, M., Rowland, B. et al. Analyses of biomarker traits in diverse UK biobank participants identify associations missed by European-centric analysis strategies. J Hum Genet 67, 87–93 (2022). https://doi.org/10.1038/s10038-021-00968-0

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