Abstract not found

The case-control study design is popular for genetic association studies of complex human diseases. However, case-control studies may suffer from bias due to population stratification. In this paper, the authors present simple formulas that can set a limit to the havoc population stratification bias can wreak (the lower and upper bounds of the confounding rate ratio and the upper bound of the type I error rate). The authors demonstrate applications of these formulas using two examples. The formulas can help researchers make more prudent interpretations of their (potentially biased) results. bias (epidemiology); case-control studies; data interpretation, statistical; epidemiologic methods; genetics Abbreviations: CRR, confounding rate ratio; ER-a, estrogen receptor alpha; IL, interleukin. The case-control study design is popular for genetic as-sociation studies of complex human diseases (1, 2). How-ever, case-control studies may suffer from bias due to population stratification, if the study is conducted in a pop-ulation comprising two or more strata in which allele fre-quencies and disease rates differ across the strata (3, 4). Population stratification bias may manifest itself in a gene-