Robust methods in Mendelian randomization via penalization of heterogeneous causal estimates.

ABSTRACT: Methods have been developed for Mendelian randomization that can obtain consistent causal estimates under weaker assumptions than the standard instrumental variable assumptions. The median-based estimator and MR-Egger are examples of such methods. However, these methods can be sensitive to genetic variants with heterogeneous causal estimates. Such heterogeneity may arise from over-dispersion in the causal estimates, or specific variants with outlying causal estimates. In this paper, we develop three extensions to robust methods for Mendelian randomization with summarized data: 1) robust regression (MM-estimation); 2) penalized weights; and 3) Lasso penalization. Methods using these approaches are considered in two applied examples: one where there is evidence of over-dispersion in the caus

SUBMITTER: Rees JMB 

PROVIDER: S-EPMC6756542 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature