ArticleGenetic epidemiology2022
A two-sample robust Bayesian Mendelian Randomization method accounting for linkage disequilibrium and idiosyncratic pleiotropy with applications to the COVID-19 outcomes.
Article in Genetic epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Identifying factors contributing to increased susceptibility to COVID-19 risk: a systematic review of Mendelian randomization studies.International journal of epidemiology · 2022Pooled it
- Integrative analysis of gut microbiota, plasma metabolome, and gene expression identifies causal mediators in Graves' disease pathogenesis.Frontiers in microbiology · 2026Article
- RMR-ICP: robust Mendelian randomization method accounting for idiosyncratic and correlated pleiotropy with applications to stroke outcomes.Briefings in bioinformatics · 2025Article
- Polycystic ovary syndrome and risk of pregnancy-induced hypertension, gestational diabetes mellitus, and preeclampsia: a Bayesian Mendelian randomization study.Diabetology & metabolic syndrome · 2025Article
- Role of Immune Cells in Mediating the Effect of Lipids on Preeclampsia.Reproductive sciences (Thousand Oaks, Calif.) · 2025Article
- Causal relationship between inflammatory factors and gynecological cancer: a Bayesian Mendelian randomization study.Scientific reports · 2024Article
- A robust cis-Mendelian randomization method with application to drug target discovery.Nature communications · 2024Article
- A novel penalized inverse-variance weighted estimator for Mendelian randomization with applications to COVID-19 outcomes.Biometrics · 2023Article
- A two-sample robust Bayesian Mendelian Randomization method accounting for linkage disequilibrium and idiosyncratic pleiotropy with applications to the COVID-19 outcomes.Genetic epidemiology · 2022Article
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Abstract
Mendelian randomization (MR) is a statistical method exploiting genetic variants as instrumental variables to estimate the causal effect of modifiable risk factors on an outcome of interest. Despite wide uses of various popular two-sample MR methods based on genome-wide association study summary level data, however, those methods could suffer from potential power loss or/and biased inference when the chosen genetic variants are in linkage disequilibrium (LD), and also have relatively large direct effects on the outcome whose distribution might be heavy-tailed which is commonly referred to as the idiosyncratic pleiotropy phenomenon. To resolve those two issues, we propose a novel Robust Bayesian Mendelian Randomization (RBMR) model that uses the more robust multivariate generalized
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