Journal
PLOS ONE
Volume 3, Issue 1, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0001382
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Funding
- Canadian Institutes of Health Research [Clinician-Scientist Award, Investigator Award]
- Heart and Stroke Foundation of Ontario
- International Clinical Epidemiology Network
- Genome Canada
- Genome Quebec
- Burroughs Wellcome Fund [Clinician-Scientist Award]
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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.
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