Generalization and dilution of association results from European GWAS in populations of non-European ancestry: the PAGE study.
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.
Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America.
Christopher S
CS
Carlson
Tara C
TC
Matise
Kari E
KE
North
Christopher A
CA
Haiman
Megan D
MD
Fesinmeyer
Steven
S
Buyske
Fredrick R
FR
Schumacher
Ulrike
U
Peters
Nora
N
Franceschini
Marylyn D
MD
Ritchie
David J
DJ
Duggan
Kylee L
KL
Spencer
Logan
L
Dumitrescu
Charles B
CB
Eaton
Fridtjof
F
Thomas
Alicia
A
Young
Cara
C
Carty
Gerardo
G
Heiss
Loic
L
Le Marchand
Dana C
DC
Crawford
Lucia A
LA
Hindorff
Charles L
CL
Kooperberg
D001741:Black or African American / Q000235:genetics; D001213:Asian / Q000235:genetics; D015992:Body Mass Index; D003924:Diabetes Mellitus, Type 2 / Q000235:genetics; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease; D014644:Genetic Variation; D055106:Genome-Wide Association Study / Q000379:methods*; D006630:Hispanic or Latino / Q000235:genetics; D006801:Humans; D007198:Indians, North American / Q000235:genetics; D008055:Lipids / Q000097:blood / Q000235:genetics; D056186:Metagenomics / Q000379:methods*; D044468:Native Hawaiian or Pacific Islander / Q000235:genetics; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D044465:White People / Q000235:genetics
D008055:Lipids