ArticleHGG advances2024
MRBEE: A bias-corrected multivariable Mendelian randomization method.
Article in HGG advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
- Genetic evidence supports a cortical neuroprotective role of GLP-1 receptor activation in Alzheimer's disease: A drug-target Mendelian randomization study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Multivariate GWAS framework for family trios with parental phenotypes to control dynastic effects.BMC bioinformatics · 2026Article
- TL-HDMR: a transfer learning framework for advancing equitable causal inference reveals metabolic signatures of stroke across multiple ancestries.Briefings in bioinformatics · 2026Article
- Partitioned blood pressure polygenic risk reveals differential genetic effects of tissue-specific enhancers and their interactions on cardiovascular disease.Research square · 2026Article
- Recalibrating Mendelian randomization under winner's curse, sample structure and polygenicity.medRxiv : the preprint server for health sciences · 2026Article
- Multi-ancestry transcriptome-wide association study reveals shared and population-specific genetic effects in Alzheimer disease.American journal of human genetics · 2026Article
- MR2G: A novel framework for causal network inference using GWAS summary data.PLoS genetics · 2026Article
- Estimating causal effects of C-reactive protein on disease and health outcomes using multivariable Mendelian randomization adjusting for heritable confounding.International journal of epidemiology · 2026Article
- MRBEE-TL: improving causal effect estimation in multi-ancestry multivariable Mendelian randomization with transfer learning.Genome biology · 2026Article
- Shared genetic and neuroimmune architecture links type 1 diabetes with neurocognitive traits.Nature communications · 2026Article
- Mind the gap: Characterizing bias due to population mismatch in two-sample Mendelian randomization.American journal of human genetics · 2026Article
- Combining xQTL and genome-wide association studies from diverse populations improves druggable gene discovery.Nature communications · 2026Article
- Exploring the genetic link between type 2 diabetes and its complications and esophageal malignancy: A Mendelian randomization study.Medicine · 2026Article
- Multi-ancestry Transcriptome-Wide Association Study Reveals Shared and Population-Specific Genetic Effects in Alzheimer's Disease.bioRxiv : the preprint server for biology · 2025Article
- Improving causal effect estimation in multi-ancestry multivariable Mendelian randomization with transfer learning.bioRxiv : the preprint server for biology · 2025Article
- Efficient Mendelian randomization analysis with self-adaptive determination of sample structure and multiple pleiotropic effects.American journal of human genetics · 2025Article
- Mind the gap: characterizing bias due to population mismatch in two-sample Mendelian randomization.medRxiv : the preprint server for health sciences · 2025Article
- A More Robust Approach to Multivariable Mendelian Randomization.Biometrika · 2025Article
- Uncovering causal gene-tissue pairs and variants through a multivariate TWAS controlling for infinitesimal effects.Nature communications · 2025Article
- Proteome-Wide Mendelian Randomization Identifies Candidate Causal Proteins for Cardiovascular Diseases.Advanced genetics (Hoboken, N.J.) · 2025Article
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Abstract
Mendelian randomization (MR) is an instrumental variable approach used to infer causal relationships between exposures and outcomes, which is becoming increasingly popular because of its ability to handle summary statistics from genome-wide association studies. However, existing MR approaches often suffer the bias from weak instrumental variables, horizontal pleiotropy and sample overlap. We introduce MRBEE (MR using bias-corrected estimating equation), a multivariable MR method capable of simultaneously removing weak instrument and sample overlap bias and identifying horizontal pleiotropy. Our extensive simulations and real data analyses reveal that MRBEE provides nearly unbiased estimates of causal effects, well-controlled type I error rates and higher power than comparably robust methods and is computationally efficient. Our real data analyses result in consistent causal effect estimates and offer valuable guidance for conducting multivariable MR studies, elucidating the roles of pleiotropy, and identifying total 42 horizontal pleiotropic loci missed previously that are associated with myopia, schizophrenia, and coronary artery disease.
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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.