Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables.

ABSTRACT: Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context of multiple genetic markers measured in multiple studies, based on the analysis of individual participant data. First, for a single genetic marker in one study, we show that the usual ratio of coefficients approach can be reformulated as a regression with heterogeneous error in the explanatory variable. This can be implemented using a Bayesian approach, which is next extended to include multiple genetic markers. We then propose a hierarchical model for undertaking a meta-analysis of multiple studies

SUBMITTER: Burgess S 

PROVIDER: S-EPMC3648673 | biostudies-literature | 2010 May

REPOSITORIES: biostudies-literature