ArticleAmerican journal of human genetics2021
Constrained maximum likelihood-based Mendelian randomization robust to both correlated and uncorrelated pleiotropic effects.
Article in American journal of human genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 231 papers, 7 of them syntheses that pooled it.
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Who cites it
231 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- The mediating effects of plasma proteome on the association between selenium and systemic lupus erythematosus.Clinical rheumatology · 2026Pooled it
- STROBE-causal machine learning for the human microbiome: systematic review on methodological innovations and validation frameworks.Frontiers in microbiology · 2026Pooled it
- Disentangling the inverse relationship between cancer and Alzheimer's or Parkinson's disease: A systematic review on Mendelian randomization studies.Neurobiology of disease · 2025Pooled it
- Genetic evidence reveals phosphatidylcholine as a mediator in the causal relationship between omega-3 and multiple myeloma risk.Scientific reports · 2025Pooled it
- Immunological Insights into the Causal Link Between Arthritis, Osteoarthritis, and Frailty: An Integrated Analytical Study.International journal of medical sciences · 2025Pooled it
- Multi-Ancestry Mendelian Randomization Reveals Lipid-Associated Genetic Risk Factors for COPD.International journal of chronic obstructive pulmonary disease · 2025Pooled it
- Association between gut microbiota and primary ovarian insufficiency: a bidirectional two-sample Mendelian randomization study.Frontiers in endocrinology · 2023Pooled it
- Relationship between Parkinson's disease and cardio-cerebrovascular diseases: a Mendelian randomized study.Scientific reports · 2023Trial
- FA-MFMR: a multivariable functional Mendelian randomization method that accounts for correlated longitudinal exposures via factor augmentation.Bioinformatics (Oxford, England) · 2026Article
- Multivariate GWAS framework for family trios with parental phenotypes to control dynastic effects.BMC bioinformatics · 2026Article
- Mendelian randomization analysis reveals causal links between specific immune cell phenotypes and Parkinson's disease.Clinics (Sao Paulo, Brazil) · 2026Article
- Circulating Inflammatory Markers and Mammographic Density Phenotypes: a Mendelian Randomization Analysis.medRxiv : the preprint server for health sciences · 2026Article
- Genetic Prioritization of Plasma Proteins Across Dementia Subtypes: A Proteome-Wide Mendelian Randomization and Bayesian Colocalization Analysis.Cellular and molecular neurobiology · 2026Article
- A flexible framework for robust and efficient Mendelian randomization with debiasing.Briefings in bioinformatics · 2026Article
- Post-genome-wide association study variant-to-function challenges in asthma research.The Journal of allergy and clinical immunology · 2026Review
- Recalibrating Mendelian randomization under winner's curse, sample structure and polygenicity.medRxiv : the preprint server for health sciences · 2026Article
- METEOR: a data-adaptive Mendelian randomization method for powerful detection of shared and specific exposures underlying multiple outcomes.Briefings in bioinformatics · 2026Article
- Bayesian Bidirectional Mendelian Randomization Under Correlated and Uncorrelated Pleiotropy Using GWAS Summary Statistics.Statistics in medicine · 2026Article
- Elucidating Immune Cell Mediated Causal Pathways Linking Blood Metabolites to Major Depressive Disorder: A Mediation Mendelian Randomization Analysis.Brain and behavior · 2026Article
- Single-cell multi-omic integration analysis prioritizes druggable genes and reveals cell-type-specific causal effects in glioblastomagenesis.Journal of translational medicine · 2026Article
171 more citing papers are in PubMed but not listed here.
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Authors and funding
3 authors.
Funding
Abstract
With the increasing availability of large-scale GWAS summary data on various complex traits and diseases, there have been tremendous interests in applications of Mendelian randomization (MR) to investigate causal relationships between pairs of traits using SNPs as instrumental variables (IVs) based on observational data. In spite of the potential significance of such applications, the validity of their causal conclusions critically depends on some strong modeling assumptions required by MR, which may be violated due to the widespread (horizontal) pleiotropy. Although many MR methods have been proposed recently to relax the assumptions by mainly dealing with uncorrelated pleiotropy, only a few can handle correlated pleiotropy, in which some SNPs/IVs may be associated with hidden confounders, such as some heritable factors shared by both traits. Here we propose a simple and effective approach based on constrained maximum likelihood and model averaging, called cML-MA, applicable to GWAS summary data. To deal with more challenging situations with many invalid IVs with only weak pleiotropic effects, we modify and improve it with data perturbation. Extensive simulations demonstrated that the proposed methods could control the type I error rate better while achieving higher power than other competitors. Applications to 48 risk factor-disease pairs based on large-scale GWAS summary data of 3 cardio-metabolic diseases (coronary artery disease, stroke, and type 2 diabetes), asthma, and 12 risk factors confirmed its superior performance.
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