Bayesian models for population‐based case‐control studies when the population is in Hardy‐Weinberg equilibrium

Publisher Website
Google Scholar
Abstract
Association analysis of genetic polymorphisms has been mostly performed in a case‐control setting with unrelated affected subjects compared with unrelated unaffected subjects. In this paper, we present a Bayesian method for analyzing such case‐control data when the population is in Hardy‐Weinberg equilibrium. Our Bayesian method depends on the informative prior which is the retrospective likelihood based on historical data, raised to a powera. By modeling the retrospective likelihood properly, different prior information about the studied population can be incorporated into the specification of the prior. The scalarais a precision parameter quantifying the heterogeneity between current and historical data. A guide value forais discussed in this paper. The informative prior and posterior distributions are proper under very general conditions. Therefore, our method can be applied in most case‐control studies. Further, for assessing gene‐environment interactions, our approach will naturally lead to a Bayesian model depending only on the case data, when genotype and environmental factors are independent in the population. Thus our approach can be applied to case‐only studies. A real example is used to show the applications of our method.Genet. Epidemiol.28:183–192, 2005.