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- PMID: 18196181
- UKPMCID: 18196181
- DOI: 10.1371/journal.pone.0001382
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Correction of population stratification in large multi-ethnic association studies.
Serre, David; Montpetit, Alexandre; Paré, Guillaume; Engert, James C; Yusuf, Salim; Keavney, Bernard; Hudson, Thomas J; Anand, Sonia
PloS one. 2008;3(1):e1382.
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Full-text held externally
- PMID: 18196181
- UKPMCID: 18196181
- DOI: 10.1371/journal.pone.0001382
Abstract
BACKGROUND: The vast majority of genetic risk factors for complex diseases have, taken individually, a small effect on the end phenotype. Population-based association studies therefore need very large sample sizes to detect significant differences between affected and non-affected individuals. Including thousands of affected individuals in a study requires recruitment in numerous centers, possibly from different geographic regions. Unfortunately such a recruitment strategy is likely to complicate the study design and to generate concerns regarding population stratification. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed 9,751 individuals representing three main ethnic groups - Europeans, Arabs and South Asians - that had been enrolled from 154 centers involving 52 countries for a global case/control study of acute myocardial infarction. All individuals were genotyped at 103 candidate genes using 1,536 SNPs selected with a tagging strategy that captures most of the genetic diversity in different populations. We show that relying solely on self-reported ethnicity is not sufficient to exclude population stratification and we present additional methods to identify and correct for stratification. CONCLUSIONS/SIGNIFICANCE: Our results highlight the importance of carefully addressing population stratification and of carefully "cleaning" the sample prior to analyses to obtain stronger signals of association and to avoid spurious results.