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.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.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