Bayesian meta‐analysis and meta‐regression for gene–disease associations and deviations from Hardy–Weinberg equilibrium

Abstract Violation of Hardy–Weinberg equilibrium (HWE) can raise doubts about the validity of the conclusions from genetic association studies. However, for most currently performed gene–disease association studies, the available tests have low power to detect deviations from HWE. We consider this issue from a meta‐analysis perspective, and suggest an approach to estimate the deviation and investigate its relationship with the observed genetic effects. Different degrees of deviation from HWE have previously been proposed as a potential source of heterogeneity across studies. We present a hierarchical meta‐regression model that can be applied to test this assumption, using the concept of the fixation coefficient. We re‐analyse seven meta‐analyses to illustrate these methods. The uncertainty in the genetic effect estimate tended to increase once the fixation coefficient was taken into account. Dependence of the genetic effect size on the deviation from HWE was found in one meta‐analysis, while in the other six examples, deviations from HWE did not clearly explain between‐study heterogeneity in the genetic effects. The proposed hierarchical models allow the synthesis of data across gene–disease association studies with appropriate consideration of HWE issues. Copyright © 2006 John Wiley & Sons, Ltd.