ArticleNature communications2024
A robust cis-Mendelian randomization method with application to drug target discovery.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 2 of them syntheses that pooled it.
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Who cites it
40 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Cross-ancestry genome-wide association studies of liver function biomarkers uncover pleiotropic variants, systemic disease links and therapeutic targets.Genome medicine · 2026Pooled it
- Circulating proteins associated with histological subtypes of lung cancer from genetic and population-based perspectives.PLoS genetics · 2025Pooled it
- GLP-1R expression and dermatological diseases: a mendelian randomization and real-world study.Endocrine · 2026Article
- Article
- Review
- Proteome-wide Mendelian randomisation of lung function to identify potential therapeutic targets for respiratory disease.ERJ open research · 2026Article
- A flexible framework for robust and efficient Mendelian randomization with debiasing.Briefings in 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
- Recalibrating Mendelian randomization under winner's curse, sample structure and polygenicity.medRxiv : the preprint server for health sciences · 2026Article
- Integration of transcriptome and mendelian randomization elucidates the protective role of aspirin in pulmonary tuberculosis development.Functional & integrative genomics · 2026Article
- Unravelling the genetic architecture of cerebral small vessel disease in the context of stroke.Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism · 2026Review
- Single-cell multi-omic integration analysis prioritizes druggable genes and reveals cell-type-specific causal effects in glioblastomagenesis.Journal of translational medicine · 2026Article
- Unveiling novel drug targets for atherosclerosis: A Mendelian randomization analysis.Medicine · 2026Article
- A flexible and unified framework for single- and multi-outcome Mendelian randomization using summary statistics.American journal of human genetics · 2026Article
- Integrating genetic data with biological insight: A practical guide to cis-Mendelian randomization.American journal of human genetics · 2026Review
- MR2G: A novel framework for causal network inference using GWAS summary data.PLoS genetics · 2026Article
- Epigenome-wide Mendelian randomization with multi-omics validation identifies epigenetic drivers of idiopathic pulmonary fibrosis.Communications biology · 2026Article
- Repurposing drugs for the prevention of vascular dementia using evidence from drug target Mendelian randomization.Nature aging · 2026Article
- Causal Effects of a Hepatic Senescence Gene Set on MASLD Fibrosis: A Mendelian Randomization Study and Quercetin Molecular Docking Analysis.Biomedicines · 2026Article
- Erythropoietin drug targets and cancer risk: A two-sample Mendelian randomization study.Medicine · 2026Article
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2 authors.
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Abstract
Mendelian randomization (MR) uses genetic variants as instrumental variables (IVs) to investigate causal relationships between traits. Unlike conventional MR, cis-MR focuses on a single genomic region using only cis-SNPs. For example, using cis-pQTLs for a protein as exposure for a disease opens a cost-effective path for drug target discovery. However, few methods effectively handle pleiotropy and linkage disequilibrium (LD) of cis-SNPs. Here, we propose cisMR-cML, a method based on constrained maximum likelihood, robust to IV assumption violations with strong theoretical support. We further clarify the severe but largely neglected consequences of the current practice of modeling marginal, instead of conditional genetic effects, and only using exposure-associated SNPs in cis-MR analysis. Numerical studies demonstrated our method's superiority over other existing methods. In a drug-target analysis for coronary artery disease (CAD), including a proteome-wide application, we identified three potential drug targets, PCSK9, COLEC11 and FGFR1 for CAD.
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