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Large-scale association studies hold substantial promise for unraveling the genetic basis of common human diseases. A well-known problem with such studies is the presence of undetected population structure, which can lead to both false positive results and failures to detect genuine associations. Here we examine approximately 15,000 genome-wide single-nucleotide polymorphisms typed in three population groups to assess the consequences of population structure on the coming generation of association studies. The consequences of population structure on association outcomes increase markedly with sample size. For the size of study needed to detect typical genetic effects in common diseases, even the modest levels of population structure within population groups cannot safely be ignored. We also examine one method for correcting for population structure (Genomic Control). Although it often performs well, it may not correct for structure if too few loci are used and may overcorrect in other settings, leading to substantial loss of power. The results of our analysis can guide the design of large-scale association studies.

Original publication

DOI

10.1038/ng1337

Type

Journal article

Journal

Nat Genet

Publication Date

05/2004

Volume

36

Pages

512 - 517

Keywords

Genetic Markers, Genetic Predisposition to Disease, Genetic Variation, Genetics, Population, Humans, Linkage Disequilibrium, Models, Genetic, Polymorphism, Single Nucleotide, Quantitative Trait, Heritable