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Genetic analyses of diverse populations improves discovery for complex traits.

TitleGenetic analyses of diverse populations improves discovery for complex traits.
Publication TypeJournal Article
Year of Publication2019
AuthorsWojcik GL, Graff M, Nishimura KK, Tao R, Haessler J, Gignoux CR, Highland HM, Patel YM, Sorokin EP, Avery CL, Belbin GM, Bien SA, Cheng I, Cullina S, Hodonsky CJ, Hu Y, Huckins LM, Jeff J, Justice AE, Kocarnik JM, Lim U, Lin BM, Lu Y, Nelson SC, Park S-SL, Poisner H, Preuss MH, Richard MA, Schurmann C, Setiawan VW, Sockell A, Vahi K, Verbanck M, Vishnu A, Walker RW, Young KL, Zubair N, Acuña-Alonso V, Ambite JLuis, Barnes KC, Boerwinkle E, Bottinger EP, Bustamante CD, Caberto C, Canizales-Quinteros S, Conomos MP, Deelman E, Do R, Doheny K, Fernández-Rhodes L, Fornage M, Hailu B, Heiss G, Henn BM, Hindorff LA, Jackson RD, Laurie CA, Laurie CC, Li Y, Lin D-Y, Moreno-Estrada A, Nadkarni G, Norman PJ, Pooler LC, Reiner AP, Romm J, Sabatti C, Sandoval K, Sheng X, Stahl EA, Stram DO, Thornton TA, Wassel CL, Wilkens LR, Winkler CA, Yoneyama S, Buyske S, Haiman CA, Kooperberg C, Le Marchand L, Loos RJF, Matise TC, North KE, Peters U, Kenny EE
Secondary AuthorsCarlson CS
Date Published2019 06
KeywordsAfrican Continental Ancestry Group, Asian Continental Ancestry Group, Body Height, Cohort Studies, Female, Genetics, Medical, Genome-Wide Association Study, Health Equity, Health Status Disparities, Hispanic Americans, Humans, Male, Minority Groups, Multifactorial Inheritance, United States, Women's Health

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.

Alternate JournalNature
PubMed ID31217584
PubMed Central IDPMC6785182
Grant ListK99 HL130580 / HL / NHLBI NIH HHS / United States
L60 MD008384 / MD / NIMHD NIH HHS / United States
L30 HG009840 / HG / NHGRI NIH HHS / United States
U01 HG007376 / HG / NHGRI NIH HHS / United States
R01 HL104608 / HL / NHLBI NIH HHS / United States
U01 HG009080 / HG / NHGRI NIH HHS / United States
T32 HD007168 / HD / NICHD NIH HHS / United States
S10 OD020069 / OD / NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
P30 CA071789 / CA / NCI NIH HHS / United States
U01 HG007416 / HG / NHGRI NIH HHS / United States
R01 HG009974 / HG / NHGRI NIH HHS / United States
U01 HG009610 / HG / NHGRI NIH HHS / United States
U01 AI090905 / AI / NIAID NIH HHS / United States
S10 OD018522 / OD / NIH HHS / United States
P2C HD050924 / HD / NICHD NIH HHS / United States
T32 HL007055 / HL / NHLBI NIH HHS / United States