Mendelian Randomization

Abstract

Confounding and reverse causality have prevented us from drawing meaningful clinical interpretation even in well-powered observational studies. Confounding may be attributed to our inability to randomize the exposure variable in observational studies. Mendelian randomization (MR) is one approach to overcome confounding. It utilizes one or more genetic polymorphisms as a proxy for the exposure variable of interest. Polymorphisms are randomly distributed in a population, they are static throughout an individual's lifetime, and may thus help in inferring directionality in exposure-outcome associations. Genome-wide association studies (GWAS) or meta-analyses of GWAS are characterized by large sample sizes and the availability of many single nucleotide polymorphisms (SNPs), making GWAS-based MR an attractive approach. GWAS-based MR comes with specific challenges, including multiple causality. Despite shortcomings, it still remains one of the most powerful techniques for inferring causality.With MR still an evolving concept with complex statistical challenges, the literature is relatively scarce in terms of providing working examples incorporating real datasets. In this chapter, we provide a step-by-step guide for causal inference based on the principles of MR with a real dataset using both individual and summary data from unrelated individuals. We suggest best possible practices and give recommendations based on the current literature.

Mendelian randomization: Progressing towards understanding causality

“…A more recently suggested method to approach this problem is the Mendelian randomization (MR) design 5, 6, 7. Basically, one or a number of genetic variants are identified that can act as instrumental variables for the risk factor in that they are associated with the risk factor, but have no direct effect on PD.…”

A Mendelian randomization study of glycemic and anthropometric traits and Parkinson’s disease

“…altered glucose metabolism or body mass index) and an outcome (e.g. PD) 13,14 . In principle, MR allows the use of genetic variants as proxy representatives of exposure from one population to test an association with an outcome in a completely independent population 15 .…”

Role of educational attainment, cognitive performance and intelligence in neurodegeneration: a bidirectional Mendelian randomization study

“…The MR employs genetic variants as randomized proxy markers of risk factors, also known as genetic instruments to check for directionality in a relationship between a risk factor such as educational attainment and a disease or outcome like AD or PD 10 . Using the largest cohorts on AD and PD available to date, educational attainment was most recently shown to play a protective casual role in AD and risky casual role in PD 8,9 .…”