ArticleStatistics in medicine2022
Profile-likelihood Bayesian model averaging for two-sample summary data Mendelian randomization in the presence of horizontal pleiotropy.
Article in Statistics in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed.
- Transfusion-related immunomodulation effect of erythrocyte characteristics on immune cells traits based on a multivariable Mendelian randomization study.International journal of surgery (London, England) · 2026Article
- National Burden of Breast Cancer in Saudi Arabia, 1990-2023, With Forecasts to 2050: A Systematic Analysis for the Global Burden of Disease Study 2023.Evidance health sciences · 2026Article
- Article
- Accounting for the impact of rare variants on causal inference with RARE: a novel multivariable Mendelian randomization method.Briefings in bioinformatics · 2025Article
- The Causal Mechanism Between the Dipeptidyl Peptidase-4, Heart Failure, and Other Cardiovascular Diseases: A Mendelian Randomization and Mediation Study.International journal of endocrinology · 2025Article
- The genetic landscape of substance use disorders.Molecular psychiatry · 2024Review
- Mendelian randomization analysis using multiple biomarkers of an underlying common exposure.Biostatistics (Oxford, England) · 2024Article
- Systematic proteome-wide Mendelian randomization using the human plasma proteome to identify therapeutic targets for lung adenocarcinoma.Journal of translational medicine · 2024Article
- Association between viral infections and glioma risk: a two-sample bidirectional Mendelian randomization analysis.BMC medicine · 2023Article
- Gut microbiota and risk of five common cancers: A univariable and multivariable Mendelian randomization study.Cancer medicine · 2023Article
- Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology.Nature communications · 2022Article
- Profile-likelihood Bayesian model averaging for two-sample summary data Mendelian randomization in the presence of horizontal pleiotropy.Statistics in medicine · 2022Article
- Mendelian Randomization: Concepts and Scope.Cold Spring Harbor perspectives in medicine · 2022Review
- A comprehensive evaluation of methods for Mendelian randomization using realistic simulations and an analysis of 38 biomarkers for risk of type 2 diabetes.International journal of epidemiology · 2021Article
- Exploiting collider bias to apply two-sample summary data Mendelian randomization methods to one-sample individual level data.PLoS genetics · 2021Article
- Genetic instrumental variable analysis reveals multivariate dietary patterns beneficial to patients with Alzheimer's disease.Journal of Alzheimer's disease reportsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Two-sample summary data Mendelian randomization is a popular method for assessing causality in epidemiology, by using genetic variants as instrumental variables. If genes exert pleiotropic effects on the outcome not entirely through the exposure of interest, this can lead to heterogeneous and (potentially) biased estimates of causal effect. We investigate the use of Bayesian model averaging to preferentially search the space of models with the highest posterior likelihood. We develop a Metropolis-Hasting algorithm to perform the search using the recently developed MR-RAPS as the basis for defining a posterior distribution that efficiently accounts for pleiotropic and weak instrument bias. We demonstrate how our general modeling approach can be extended from a standard one-component causal model to a two-component model, which allows a large proportion of SNPs to violate the InSIDE assumption. We use Monte Carlo simulations to illustrate our methods and compare it to several related approaches. We finish by applying our approach to investigate the causal role of cholesterol on the development age-related macular degeneration.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.