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Assessing the impact of population stratification on genetic association studies
Authors:Freedman Matthew L  Reich David  Penney Kathryn L  McDonald Gavin J  Mignault Andre A  Patterson Nick  Gabriel Stacey B  Topol Eric J  Smoller Jordan W  Pato Carlos N  Pato Michele T  Petryshen Tracey L  Kolonel Laurence N  Lander Eric S  Sklar Pamela  Henderson Brian  Hirschhorn Joel N  Altshuler David
Affiliation:Department of Medicine and Molecular Biology, Massachusetts General Hospital, Boston, and Program in Medical and Population Genetics, Broad Institute, Cambridge, USA.
Abstract:
Population stratification refers to differences in allele frequencies between cases and controls due to systematic differences in ancestry rather than association of genes with disease. It has been proposed that false positive associations due to stratification can be controlled by genotyping a few dozen unlinked genetic markers. To assess stratification empirically, we analyzed data from 11 case-control and case-cohort association studies. We did not detect statistically significant evidence for stratification but did observe that assessments based on a few dozen markers lack power to rule out moderate levels of stratification that could cause false positive associations in studies designed to detect modest genetic risk factors. After increasing the number of markers and samples in a case-cohort study (the design most immune to stratification), we found that stratification was in fact present. Our results suggest that modest amounts of stratification can exist even in well designed studies.
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