作者
Christopher S Carlson, Tara C Matise, Kari E North, Christopher A Haiman, Megan D Fesinmeyer, Steven Buyske, Fredrick R Schumacher, Ulrike Peters, Nora Franceschini, Marylyn D Ritchie, David J Duggan, Kylee L Spencer, Logan Dumitrescu, Charles B Eaton, Fridtjof Thomas, Alicia Young, Cara Carty, Gerardo Heiss, Loic Le Marchand, Dana C Crawford, Lucia A Hindorff, Charles L Kooperberg, Page Consortium
发表日期
2013/9/17
期刊
PLoS biology
卷号
11
期号
9
页码范围
e1001661
出版商
Public Library of Science
简介
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 …
引用总数
20142015201620172018201920202021202220232024121926233032163326257