ArticleGenetic epidemiology2021
A robust two-sample transcriptome-wide Mendelian randomization method integrating GWAS with multi-tissue eQTL summary statistics.
Article in Genetic epidemiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 36 citations in OpenAlex.
- A multi-tissue mendelian randomization method based on eQTL data for mapping tissue-specific disease genes.BMC bioinformatics · 2026Article
- A flexible and unified framework for single- and multi-outcome Mendelian randomization using summary statistics.American journal of human genetics · 2026Article
- Mendelian randomization analysis of PKD1 in endometrial cancer and comparative multi-cancer study with renal cell carcinoma.Discover oncology · 2026Article
- Causal Effects of Circulating Inflammatory Proteins on Postmenopausal Atrophic Vaginitis in European Populations: A Mendelian Randomization Study with Transcriptomic Validation.International journal of women's health · 2026Article
- Multi-omics integration identifies PGAP3 as a tumor-intrinsic factor associated with CD8Frontiers in molecular biosciences · 2026Article
- Integrative multi-omics framework for causal gene discovery in Long COVID.PLoS computational biology · 2025Article
- Integrative multi-omics and single-cell transcriptomics reveal ARHGEF12 driving chemoresistance in bladder cancer.Hereditas · 2025Article
- Multi-omics analysis identifies diagnostic circulating biomarkers and potential therapeutic targets, revealing IQGAP1 as an oncogene in gastric cancer.NPJ precision oncology · 2025Article
- Enhancing nonlinear transcriptome- and proteome-wide association studies via trait imputation with applications to Alzheimer's disease.PLoS genetics · 2025Article
- HORNET: tools to find genes with causal evidence and their regulatory networks using eQTLs.Bioinformatics advances · 2025Article
- Unraveling the significance of AGPAT4 for the pathogenesis of endometriosis via a multi-omics approach.Human genetics · 2024Article
- The goldmine of GWAS summary statistics: a systematic review of methods and tools.BioData mining · 2024Article
- An integrative multi-context Mendelian randomization method for identifying risk genes across human tissues.American journal of human genetics · 2024Article
- The Application of Mendelian Randomization in Cardiovascular Disease Risk Prediction: Current Status and Future Prospects.Reviews in cardiovascular medicine · 2024Review
- MR-GGI: accurate inference of gene-gene interactions using Mendelian randomization.BMC bioinformatics · 2024Article
- simmrd: An open-source tool to perform simulations in Mendelian randomization.Genetic epidemiology · 2024Article
- Combining Mendelian randomization and network deconvolution for inference of causal networks with GWAS summary data.PLoS genetics · 2023Article
- Modeling of horizontal pleiotropy identifies possible causal gene expression in systemic lupus erythematosus.Frontiers in lupus · 2023Article
- Investigating the potential impact of PCSK9-inhibitors on mood disorders using eQTL-based Mendelian randomization.PloS one · 2022Article
- Combining the strengths of inverse-variance weighting and Egger regression in Mendelian randomization using a mixture of regressions model.PLoS genetics · 2021Article
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
By treating genetic variants as instrumental variables (IVs), two-sample Mendelian randomization (MR) methods detect genetically regulated risk exposures for complex diseases using only summary statistics. When considering gene expression as exposure in transcriptome-wide MR (TWMR) analyses, the eQTLs (expression-quantitative-trait-loci) may have pleiotropic effects or be correlated with variants that have effects on disease not via expression, and the presence of those invalid IVs would lead to biased inference. Moreover, the number of eQTLs as IVs for a gene is generally limited, making the detection of invalid IVs challenging. We propose a method, "MR-MtRobin," for accurate TWMR inference in the presence of invalid IVs. By leveraging multi-tissue eQTL data in a mixed model, the proposed method makes identifiable the IV-specific random effects due to pleiotropy from estimation errors of eQTL summary statistics, and can provide accurate inference on the dependence (fixed effects) between eQTL and GWAS (genome-wide association study) effects in the presence of invalid IVs. Moreover, our method can improve power and precision in inference by selecting cross-tissue eQTLs as IVs that have improved consistency of effects across eQTL and GWAS data. We applied MR-MtRobin to detect genes associated with schizophrenia risk by integrating summary-level data from the Psychiatric Genomics Consortium and the Genotype-Tissue Expression project (V8).
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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.