A Guide to Understanding Mendelian Randomization Studies

Abstract

Epidemiology provides a powerful framework for characterizing exposure–disease relationships, but its utility for making causal inferences is limited because epidemiologic data are observational in nature and subject to biases stemming from undetected confounding variables and reverse causation. Mendelian randomization (MR) is an increasingly popular method used to circumvent these limitations. MR uses genetic variants, or instruments, as a natural experiment to proxy an exposure, thus allowing estimation of causal effects upon an outcome that are minimally affected by the usual biases present in epidemiologic studies. Notably, MR relies on three core assumptions related to the selection of the genetic instruments, and adherence to these assumptions must be carefully evaluated to assess the validity of the causal estimates. The goal of this review is to provide readers with a basic understanding of MR studies and how to read and evaluate them. Specifically, we outline the basics of how MR analysis is conducted, the assumptions underlying instrument selection, and how to assess the quality of MR studies.