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

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

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

2022
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Overview
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.