ArticleAmerican journal of human genetics2023
Robust multivariable Mendelian randomization based on constrained maximum likelihood.
Article in American journal of human genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.
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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.
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Who cites it
48 citing papers in PubMed, 47 citations in OpenAlex.
- FA-MFMR: a multivariable functional Mendelian randomization method that accounts for correlated longitudinal exposures via factor augmentation.Bioinformatics (Oxford, England) · 2026Article
- Multivariable Mendelian Randomization With Weak Instruments: A Comparison of Bayesian and Frequentist Methods.Statistics in medicine · 2026Article
- Article
- TL-HDMR: a transfer learning framework for advancing equitable causal inference reveals metabolic signatures of stroke across multiple ancestries.Briefings in bioinformatics · 2026Article
- Integrated single-cell RNA sequencing and mendelian randomization analysis identifies causal immune-related driver genes in the heart failure inflammatory microenvironment.Cardiovascular diagnosis and therapy · 2026Article
- Genetic prioritization of HSDL2 in suicide and intentional self-harm: multi-omics evidence linking lipid metabolism and neuronal vulnerability.BMC medicine · 2026Article
- Recalibrating Mendelian randomization under winner's curse, sample structure and polygenicity.medRxiv : the preprint server for health sciences · 2026Article
- Integration of single-cell cis-expression quantitative trait locus and Mendelian randomization analyses identifies a Treg-specific gene for precision therapy in rheumatoid arthritis, gonarthrosis, and gouty arthritis.The Journal of international medical research · 2026Article
- MR2G: A novel framework for causal network inference using GWAS summary data.PLoS genetics · 2026Article
- MRBEE-TL: improving causal effect estimation in multi-ancestry multivariable Mendelian randomization with transfer learning.Genome biology · 2026Article
- Estimating the causal effect of cardiometabolic conditions on socioeconomic and healthcare outcomes: a scoping review of Mendelian randomization studies.Health economics review · 2026Article
- Circulating sex steroids do not influence risk of thyroid malignancy: insights from a bidirectional Mendelian randomization.Gland surgery · 2026Article
- Mendelian Randomization Methods for Causal Inference: Estimands, Identification and Inference.Statistics in medicine · 2026Review
- Disentangling Links Between Lung Cancer and Infectious Pneumonia via Real-World Data and Integrative Genomics.Human mutation · 2026Article
- Genetically Proxied Biological Aging and Risk of Hypertrophic Scar/Keloid-Coded Phenotypes: An Exploratory Two-Sample Mendelian Randomization Study.Clinical, cosmetic and investigational dermatology · 2026Article
- Co-expression-wide association studies link genetically regulated interactions with complex traits.Nature communications · 2025Article
- From autoimmune inflammation to malignancy: causal genetic evidence for the RA-squamous cell lung cancer axis.Arthritis research & therapy · 2025Article
- Causal link between type 1 diabetes mellitus and juvenile idiopathic arthritis in Europe.Pediatric research · 2025Article
- RMR-ICP: robust Mendelian randomization method accounting for idiosyncratic and correlated pleiotropy with applications to stroke outcomes.Briefings in bioinformatics · 2025Article
- Improving causal effect estimation in multi-ancestry multivariable Mendelian randomization with transfer learning.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
Mendelian randomization (MR) is a powerful tool for causal inference with observational genome-wide association study (GWAS) summary data. Compared to the more commonly used univariable MR (UVMR), multivariable MR (MVMR) not only is more robust to the notorious problem of genetic (horizontal) pleiotropy but also estimates the direct effect of each exposure on the outcome after accounting for possible mediating effects of other exposures. Despite promising applications, there is a lack of studies on MVMR's theoretical properties and robustness in applications. In this work, we propose an efficient and robust MVMR method based on constrained maximum likelihood (cML), called MVMR-cML, with strong theoretical support. Extensive simulations demonstrate that MVMR-cML performs better than other existing MVMR methods while possessing the above two advantages over its univariable counterpart. An application to several large-scale GWAS summary datasets to infer causal relationships between eight cardiometabolic risk factors and coronary artery disease (CAD) highlights the usefulness and some advantages of the proposed method. For example, after accounting for possible pleiotropic and mediating effects, triglyceride (TG), low-density lipoprotein cholesterol (LDL), and systolic blood pressure (SBP) had direct effects on CAD; in contrast, the effects of high-density lipoprotein cholesterol (HDL), diastolic blood pressure (DBP), and body height diminished after accounting for other risk factors.
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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.