ArticleStatistics in medicine2017
A framework for the investigation of pleiotropy in two-sample summary data Mendelian randomization.
Article in Statistics in medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1,119 papers, 10 of them syntheses that pooled it.
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Who cites it
1,119 citing papers in PubMed, 10 syntheses or guidelines pooled it.
- Pooled it
- Multi-Trait Genetic Insights Into Schizophrenia Across Ancestries: Genome-Wide Association Meta-Analyses, Machine Learning, and Drug Repurposing Study.Brain and behavior · 2026Pooled it
- Asthma increased the risk of atrial fibrillation: insights from clinical association to genetic and molecular evidence.BMC pulmonary medicine · 2026Pooled it
- Use of Mendelian Randomization to Unveil Metabolic Markers inJournal of Korean medical science · 2026Pooled it
- Circulating Inflammatory Proteins and Fuchs Endothelial Corneal Dystrophy: A Mendelian Randomization and Bioinformatics-Based Investigation.Translational vision science & technology · 2026Pooled it
- The janus-faced role of uric acid in COPD: evidence from East Asians population.NPJ primary care respiratory medicine · 2026Pooled it
- The mechanisms of kidney-lung interactions in chronic kidney disease-associated pulmonary diseases: A two-sample Mendelian randomization study.Renal failure · 2025Pooled it
- Strengthening the reporting of observational studies in epidemiology using Mendelian randomization (STROBE-MR): a Korean translation of explanation and elaboration.Ewha medical journal · 2025Guideline
- Mendelian randomization studies on ischemic stroke: a field synopsis and systematic review.Journal of translational medicine · 2025Pooled it
- Genome-wide association meta-analysis of human olfactory identification discovers sex-specific and sex-differential genetic variants.Nature communications · 2025Pooled it
- Causal associations between antibody-mediated immune responses to infectious agents and cardiovascular inflammatory diseases: A Mendelian randomization study based on UK Biobank and FinnGen.Human vaccines & immunotherapeutics · 2026Article
- Age at first sexual intercourse and frailty: Mendelian randomization and population-based evidence from NHANES and UK Biobank.Sexual medicine · 2026Article
- Proteomic Pathways Linking Type 2 Diabetes Genetic Clusters to Cardiovascular Diseases: A Network Mendelian Randomisation Study.Diabetes, obesity & metabolism · 2026Article
- Article
- How gut microbiome and blood metabolites drive ossification of the posterior longitudinal ligament of the spine: a genome-wide association study based on the East Asian population.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2026Article
- Causal association between sleep disorders and nephrolithiasis: a two-sample Mendelian randomization study.International urology and nephrology · 2026Article
- Occupational asbestos exposure and lung cancer: contemporary research trends, exploratory genetic evidence, and global burden from 1990 to 2021.Journal of thoracic disease · 2026Article
- Sex-specific biological aging clocks across organs and omics.Nature medicine · 2026Article
- APOC1-Associated VLDL-Pathway Dysregulation in Papillary Thyroid Carcinoma: A Reproducible Cross-Cohort Transcriptomic Signature Associated With the Diagnostic-to-Treatment Interval.Chemical biology & drug design · 2026Article
- Inferring multi-organ genetic connections using imaging and clinical data through Mendelian randomization.Nature biomedical engineering · 2026Article
1,059 more citing papers are in PubMed but not listed here.
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Abstract
Mendelian randomization (MR) uses genetic data to probe questions of causality in epidemiological research, by invoking the Instrumental Variable (IV) assumptions. In recent years, it has become commonplace to attempt MR analyses by synthesising summary data estimates of genetic association gleaned from large and independent study populations. This is referred to as two-sample summary data MR. Unfortunately, due to the sheer number of variants that can be easily included into summary data MR analyses, it is increasingly likely that some do not meet the IV assumptions due to pleiotropy. There is a pressing need to develop methods that can both detect and correct for pleiotropy, in order to preserve the validity of the MR approach in this context. In this paper, we aim to clarify how established methods of meta-regression and random effects modelling from mainstream meta-analysis are being adapted to perform this task. Specifically, we focus on two contrastin g approaches: the Inverse Variance Weighted (IVW) method which assumes in its simplest form that all genetic variants are valid IVs, and the method of MR-Egger regression that allows all variants to violate the IV assumptions, albeit in a specific way. We investigate the ability of two popular random effects models to provide robustness to pleiotropy under the IVW approach, and propose statistics to quantify the relative goodness-of-fit of the IVW approach over MR-Egger regression. © 2017 The Authors. Statistics in Medicine Published by JohnWiley & Sons Ltd.
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