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Generalization and dilution of association results from European GWAS in populations of non-European ancestry: the PAGE study.

TitleGeneralization and dilution of association results from European GWAS in populations of non-European ancestry: the PAGE study.
Publication TypeJournal Article
Year of Publication2013
AuthorsCarlson, CS, Matise, TC, North, KE, Haiman, CA, Fesinmeyer, MD, Buyske, S, Schumacher, FR, Peters, U, Franceschini, N, Ritchie, MD, Duggan, DJ, Spencer, KL, Dumitrescu, L, Eaton, CB, Thomas, F, Young, A, Carty, C, Heiss, G, Le Marchand, L, Crawford, DC, Hindorff, LA, Kooperberg, CL
Corporate/Institutional AuthorsPAGE Consortium
JournalPLoS Biol
Volume11
Issue9
Paginatione1001661
Date Published2013 Sep
ISSN1545-7885
KeywordsAfrican Americans, Asian Americans, Body Mass Index, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Hispanic Americans, Humans, Indians, North American, Lipids, Metagenomics, Oceanic Ancestry Group, Polymorphism, Single Nucleotide
Abstract<p>The vast majority of genome-wide association study (GWAS) findings reported to date are from populations with European Ancestry (EA), and it is not yet clear how broadly the genetic associations described will generalize to populations of diverse ancestry. The Population Architecture Using Genomics and Epidemiology (PAGE) study is a consortium of multi-ancestry, population-based studies formed with the objective of refining our understanding of the genetic architecture of common traits emerging from GWAS. In the present analysis of five common diseases and traits, including body mass index, type 2 diabetes, and lipid levels, we compare direction and magnitude of effects for GWAS-identified variants in multiple non-EA populations against EA findings. We demonstrate that, in all populations analyzed, a significant majority of GWAS-identified variants have allelic associations in the same direction as in EA, with none showing a statistically significant effect in the opposite direction, after adjustment for multiple testing. However, 25% of tagSNPs identified in EA GWAS have significantly different effect sizes in at least one non-EA population, and these differential effects were most frequent in African Americans where all differential effects were diluted toward the null. We demonstrate that differential LD between tagSNPs and functional variants within populations contributes significantly to dilute effect sizes in this population. Although most variants identified from GWAS in EA populations generalize to all non-EA populations assessed, genetic models derived from GWAS findings in EA may generate spurious results in non-EA populations due to differential effect sizes. Regardless of the origin of the differential effects, caution should be exercised in applying any genetic risk prediction model based on tagSNPs outside of the ancestry group in which it was derived. Models based directly on functional variation may generalize more robustly, but the identification of functional variants remains challenging. </p>
DOI10.1371/journal.pbio.1001661
Alternate JournalPLoS Biol.
PubMed ID24068893
PubMed Central IDPMC3775722
Grant ListM01-RR00425 / RR / NCRR NIH HHS / United States
N01-HC-45205 / HC / NHLBI NIH HHS / United States
N01WH22110 / WH / WHI NIH HHS / United States
N01-HC-05187 / HC / NHLBI NIH HHS / United States
U01CA98758 / CA / NCI NIH HHS / United States
U01 HL65520 / HL / NHLBI NIH HHS / United States
N01WH42129-32 / WH / WHI NIH HHS / United States
N01-HV-48195 / HV / NHLBI NIH HHS / United States
U01 HG004790 / HG / NHGRI NIH HHS / United States
N01-HC-48047 / HC / NHLBI NIH HHS / United States
U01 HL65521 / HL / NHLBI NIH HHS / United States
N01-HC-55022 / HC / NHLBI NIH HHS / United States
U01 HG007416 / HG / NHGRI NIH HHS / United States
U01 HL41642 / HL / NHLBI NIH HHS / United States
N01-HC-55016 / HC / NHLBI NIH HHS / United States
N01WH32100-2 / WH / WHI NIH HHS / United States
AG-15928 / AG / NIA NIH HHS / United States
U01CA136792 / CA / NCI NIH HHS / United States
N01WH32108-9 / WH / WHI NIH HHS / United States
U01HG004803 / HG / NHGRI NIH HHS / United States
AG-20098 / AG / NIA NIH HHS / United States
N01-HC-95095 / HC / NHLBI NIH HHS / United States
N01-HC-55021 / HC / NHLBI NIH HHS / United States
U01HG004802 / HG / NHGRI NIH HHS / United States
N01-HC-85086 / HC / NHLBI NIH HHS / United States
N01WH42107-26 / WH / WHI NIH HHS / United States
N01-HC-48050 / HC / NHLBI NIH HHS / United States
U01 HL41654 / HL / NHLBI NIH HHS / United States
AG-027058 / AG / NIA NIH HHS / United States
N01-HC-35129 / HC / NHLBI NIH HHS / United States
N01-HC-45134 / HC / NHLBI NIH HHS / United States
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N01-HC-55019 / HC / NHLBI NIH HHS / United States
U01 HL41652 / HL / NHLBI NIH HHS / United States
N01-HC-55015 / HC / NHLBI NIH HHS / United States
N01WH32122 / WH / WHI NIH HHS / United States
N01-HC-48049 / HC / NHLBI NIH HHS / United States
U01HG004798-01 / HG / NHGRI NIH HHS / United States
N01-HC-75150 / HC / NHLBI NIH HHS / United States
N01-HC-55020 / HC / NHLBI NIH HHS / United States
N01 HC-15103 / HC / NHLBI NIH HHS / United States
N01WH32105-6 / WH / WHI NIH HHS / United States
N01WH32111-13 / WH / WHI NIH HHS / United States
N01WH32118-32119 / WH / WHI NIH HHS / United States
R37CA54281 / CA / NCI NIH HHS / United States
DK063491 / DK / NIDDK NIH HHS / United States
N01-HC-45133 / HC / NHLBI NIH HHS / United States
N01-HC-85079 / HC / NHLBI NIH HHS / United States
HHSN268201200036C / / PHS HHS / United States
U01HG004790 / HG / NHGRI NIH HHS / United States
HL080295 / HL / NHLBI NIH HHS / United States
U01HG004801-01 / HG / NHGRI NIH HHS / United States
N01-HC-85239 / HC / NHLBI NIH HHS / United States
N01-HC-48048 / HC / NHLBI NIH HHS / United States
AG-023629 / AG / NIA NIH HHS / United States
N01-HC-55018 / HC / NHLBI NIH HHS / United States
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P30 CA071789 / CA / NCI NIH HHS / United States
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P01CA33619 / CA / NCI NIH HHS / United States
N01WH24152 / WH / WHI NIH HHS / United States