Population stratification ; spurious association ; false positive ; haplotype trend test ; measurement error
Abstract
Population stratification can cause spurious associations between genetic markers and disease locus. In order to handle this population stratification in haplotype-based case-control association studies, we added population indicators as covariates to the haplotype trend regression model proposed by Zaykin et al. (2002). We investigated through simulations how both population stratification and measurement error in the estimation of true population of each individual affect type I error probabilities of the association tests based on both Zaykin et al.'s (2002) model and the proposed model. Based on those results, in the situation that there exists population stratification but there is no error in population classification of each individual, our proposed model does satisfy a type I error probability whereas Zaykin et al.'s (2002) model does not. However, as the measurement error increases, a type I error probability of our model correspondingly becomes larger than a nominal significance level. It implies that as long as uncertainty in the estimation of true population of each individual still remains, it is nearly impossible to avoid false positive in case-control association studies based on haplotypes