Nonparametric bounds in two-sample summary-data Mendelian randomization: Some cautionary tales for practice.

ABSTRACT: Recently, in genetic epidemiology, Mendelian randomization (MR) has become a popular approach to estimate causal exposure effects by using single nucleotide polymorphisms from genome-wide association studies (GWAS) as instruments. The most popular type of MR study, a two-sample summary-data MR study, relies on having summary statistics from two independent GWAS and using parametric methods for estimation. However, little is understood about using a nonparametric bound-based analysis, a popular approach in traditional instrumental variables frameworks, to study causal effects in two-sample MR. In this article, we explore using a nonparametric, bound-based analysis in two-sample MR studies, focusing primarily on implications for practice. We also propose a framework to assess how likely one

SUBMITTER: Trane RM 

PROVIDER: S-EPMC9314714 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature