title: Leveraging Multi-ethnic Evidence for Mapping Complex Traits in Minority Populations: An Empirical Bayes Approach.
abstract: Elucidating the genetic basis of complex traits and diseases in non-European populations is particularly challenging because US minority populations have been under-represented in genetic association studies. We developed an empirical Bayes approach named XPEB (cross-population empirical Bayes), designed to improve the power for mapping complex-trait-associated loci in a minority population by exploiting information from genome-wide association studies (GWASs) from another ethnic population. Taking as input summary statistics from two GWASs-a target GWAS from an ethnic minority population of primary interest and an auxiliary base GWAS (such as a larger GWAS in Europeans)-our XPEB approach reprioritizes SNPs in the target population to compute local false-discovery rates. We demonstrated, through simulations, that whenever the base GWAS harbors relevant information, XPEB gains efficiency. Moreover, XPEB has the ability to discard irrelevant auxiliary information, providing a safeguard against inflated false-discovery rates due to genetic heterogeneity between populations. Applied to a blood-lipids study in African Americans, XPEB more than quadrupled the discoveries from the conventional approach, which used a target GWAS alone, bringing the number of significant loci from 14 to 65. Thus, XPEB offers a flexible framework for mapping complex traits in minority populations.
authors.affiliation: Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA 94305, USA.
authors.forename: Marc A
authors.initials: MA
authors.lastname: Coram
authors.affiliation: Department of Genetics, Stanford University School of Medicine, Stanford CA 94305, USA.
authors.forename: Sophie I
authors.initials: SI
authors.lastname: Candille
authors.affiliation: Departments of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
authors.forename: Qing
authors.initials: Q
authors.lastname: Duan
authors.affiliation: Laboratory of Molecular Epidemiology and Nutrition, Department of Epidemiology, Brown University, Providence, RI 02912, USA.
authors.forename: Kei Hang K
authors.initials: KH
authors.lastname: Chan
authors.affiliation: Departments of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA.
authors.forename: Yun
authors.initials: Y
authors.lastname: Li
authors.affiliation: Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
authors.forename: Charles
authors.initials: C
authors.lastname: Kooperberg
authors.affiliation: Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA; Department of Epidemiology, University of Washington, Seattle, WA 98195, USA.
authors.forename: Alex P
authors.initials: AP
authors.lastname: Reiner
authors.affiliation: Department of Genetics, Stanford University School of Medicine, Stanford CA 94305, USA. Electronic address: huatang@stanford.edu.
authors.forename: Hua
authors.initials: H
authors.lastname: Tang
mesh_terms: D001741:Black or African American; D001499:Bayes Theorem; D005006:Ethnicity; D055106:Genome-Wide Association Study / Q000379:methods*; D006801:Humans; D008055:Lipids / Q000235:genetics; D008913:Minority Groups; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D044465:White People
chemical_list: D008055:Lipids