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, Genevieve L., Mariaelisa Graff, Katherine K. Nishimura, Ran Tao, Jeffrey Haessler, Christopher R. Gignoux, Heather M. Highland, Yesha M. Patel, Elena P. Sorokin, Christy L. Avery, Gillian M. Belbin, Stephanie A. Bien, Iona Cheng, Sinead Cullina, Chani J. Hodonsky, Yao Hu, Laura M. Huckins, Janina Jeff, Anne E. Justice, Jonathan M. Kocarnik, Unhee Lim, Bridget M. Lin, Yingchang Lu, Sarah C. Nelson, Sung-Shim L. Park, Hannah Poisner, Michael H. Preuss, Melissa A. Richard, Claudia Schurmann, Veronica W. Setiawan, Alexandra Sockell, Karan Vahi, Marie Verbanck, Abhishek Vishnu, Ryan W. Walker, Kristin L. Young, Niha Zubair, Victor Acuña-Alonso, Jose Luis Ambite, Kathleen C. Barnes, Eric Boerwinkle, Erwin P. Bottinger, Carlos D. Bustamante, Christian Caberto, Samuel Canizales-Quinteros, Matthew P. Conomos, Ewa Deelman, Ron Do, Kimberly Doheny, Lindsay Fernández-Rhodes, Myriam Fornage, Benyam Hailu, Gerardo Heiss, Brenna M. Henn, Lucia A. Hindorff, Rebecca D. Jackson, Cecelia A. Laurie, Cathy C. Laurie, Yuqing Li, Dan-Yu Lin, Andres Moreno-Estrada, Girish Nadkarni, Paul J. Norman, Loreall C. Pooler, Alexander P. Reiner, Jane Romm, Chiara Sabatti, Karla Sandoval, Xin Sheng, Eli A. Stahl, Daniel O. Stram, Timothy A. Thornton, Christina L. Wassel, Lynne R. Wilkens, Cheryl A. Winkler, Sachi Yoneyama, Steven Buyske, Christopher A. Haiman, Charles Kooperberg, Loic Le Marchand, Ruth J. F. Loos, Tara C. Matise, Kari E. North, Ulrike Peters, Eimear E. Kenny, and Christopher S. Carlson
JournalNature
Volume570
Issue7762
Pagination514-518
Date Published2019 Jun
ISSN1476-4687
KeywordsAsians, Blacks, Body Height, Cohort Studies, Female, Genetics, Medical, Genome-Wide Association Study, Health Equity, Health Status Disparities, Hispanic or Latino, Humans, Male, Minority Groups, Multifactorial Inheritance, United States, Women's Health
Abstract

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.

DOI10.1038/s41586-019-1310-4
Alternate JournalNature
Original PublicationGenetic analyses of diverse populations improves discovery for complex traits.
PubMed ID31217584
PubMed Central IDPMC6785182
Grant ListU01 HG007419 / HG / NHGRI NIH HHS / United States
HHSN268201100004I / HL / NHLBI NIH HHS / United States
P01 GM099568 / GM / NIGMS NIH HHS / United States
T32 HL129982 / HL / NHLBI NIH HHS / United States
N01HC65233 / HL / NHLBI NIH HHS / United States
R01 DK101855 / DK / NIDDK NIH HHS / United States
T32 HD049311 / HD / NICHD NIH HHS / United States
U01 HG009080 / HG / NHGRI NIH HHS / United States
T32 HG000044 / HG / NHGRI NIH HHS / United States
T32 HD007168 / HD / NICHD NIH HHS / United States
HHSN268201100004C / WH / WHI NIH HHS / United States
R01 CA082659 / CA / NCI NIH HHS / United States
U01 HG007417 / HG / NHGRI NIH HHS / United States
HHSN268201100001I / HL / NHLBI NIH HHS / United States
K99 HL130580 / HL / NHLBI NIH HHS / United States
U01 HG007416 / HG / NHGRI NIH HHS / United States
R01 HG009974 / HG / NHGRI NIH HHS / United States
KL2 TR001109 / TR / NCATS NIH HHS / United States
HHSN268201100046C / HL / NHLBI NIH HHS / United States
R00 HL130580 / HL / NHLBI NIH HHS / United States
L60 MD008384 / MD / NIMHD NIH HHS / United States
R25 CA094880 / CA / NCI NIH HHS / United States
N01HC65236 / HL / NHLBI NIH HHS / United States
L30 HG009840 / HG / NHGRI NIH HHS / United States
HHSN268201100003C / WH / WHI NIH HHS / United States
U01 HG007376 / HG / NHGRI NIH HHS / United States
N01HC65235 / HL / NHLBI NIH HHS / United States
U01 AI090905 / AI / NIAID NIH HHS / United States
S10 OD018522 / OD / NIH HHS / United States
N01HC65234 / HL / NHLBI NIH HHS / United States
HHSN268201200008C / HL / NHLBI NIH HHS / United States
R01 GM047845 / GM / NIGMS NIH HHS / United States
N01HC65237 / HL / NHLBI NIH HHS / United States
HHSN271201100004C / AG / NIA NIH HHS / United States
HHSN268201100002C / WH / WHI NIH HHS / United States
R01 HL104608 / HL / NHLBI NIH HHS / United States
S10 OD020069 / OD / NIH HHS / United States
HHSN268201100003I / HL / NHLBI NIH HHS / United States
HHSN268201100002I / HL / NHLBI NIH HHS / United States
P01 CA142538 / CA / NCI NIH HHS / United States
KL2 TR000421 / TR / NCATS NIH HHS / United States
P2C HD050924 / HD / NICHD NIH HHS / United States
T32 HL007055 / HL / NHLBI NIH HHS / United States
HHSN268201200008I / HL / NHLBI NIH HHS / United States
P30 CA071789 / CA / NCI NIH HHS / United States
U01 HG007397 / HG / NHGRI NIH HHS / United States
U01 CA164973 / CA / NCI NIH HHS / United States
HHSN268201100001C / WH / WHI NIH HHS / United States
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