Conducting a Reproducible Mendelian Randomization Analysis Using the R Analytic Statistical Environment

• Published in: Current protocols in human genetics Vol. 101; no. 1; p. e82
• Main Authors: Rasooly, Danielle, Patel, Chirag J
• Format: Journal Article
• Language: English
• Published: United States 01.04.2019
• Subjects: Alleles; Genetic Variation - genetics; Genome-Wide Association Study; Humans; Mendelian Randomization Analysis - methods; Models, Statistical; Polymorphism, Genetic - genetics; Software; genetic variation; instrumental variable analysis; Mendelian randomization; summarized genetic data; TwoSampleMR
• ISSN: 1934-8258
• DOI: 10.1002/cphg.82

Mendelian randomization (MR) is defined as the utilization of genetic variants as instrumental variables to assess the causal relationship between an exposure and an outcome. By leveraging genetic polymorphisms as proxy for an exposure, the causal effect of an exposure on an outcome can be assessed while addressing susceptibility to biases prone to conventional observational studies, including confounding and reverse causation, where the outcome causes the exposure. Analogous to a randomized controlled trial where patients are randomly assigned to subgroups based on different treatments, in an MR analysis, the random allocation of alleles during meiosis from parent to offspring assigns individuals to different subgroups based on genetic variants. Recent methods use summary statistics from genome-wide association studies to perform MR, bypassing the need for individual-level data. Here, we provide a straightforward protocol for using summary-level data to perform MR and provide guidance for utilizing available software. © 2019 by John Wiley & Sons, Inc.