ArticleHGG advances2024
Extensive co-regulation of neighboring genes complicates the use of eQTLs in target gene prioritization.
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 21 papers, 1 of them a synthesis that pooled it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Neuronal Cell-Specific sc-eQTL and Integrative eQTL-pQTL Mendelian Randomization Prioritize CKAP2 as a Candidate Gene for Major Depressive Disorder.Journal of molecular neuroscience : MN · 2026Observational
- Migraine immune cell gene targets and their relationship to psychiatric disorders.The journal of headache and pain · 2026Article
- From GWAS Signals to Molecular Mechanisms: Explainable AI for Causal Gene Prioritization and Biomolecular Target Interpretation.Biomolecules · 2026Review
- Ultra-fast genetic colocalisation across millions of association signals.PLoS genetics · 2026Article
- Integrating genetic data with biological insight: A practical guide to cis-Mendelian randomization.American journal of human genetics · 2026Review
- Design and interpretation of eQTL-GWAS colocalisation studies: Lessons from a large-scale evaluation.PLoS genetics · 2026Article
- Higher eQTL power reveals signals that boost GWAS colocalization.American journal of human genetics · 2026Article
- Focus on single-gene effects limits discovery and interpretation of complex-trait-associated variants.American journal of human genetics · 2026Article
- Article
- Mapping atherogenesis mechanisms in smooth muscle cells by targeting genes linked to coronary artery disease.iScience · 2025Article
- Integrative Genetic, Proteogenomic, and Multi-omics Analyses Reveal Sex-Biased Causal Genes and Drug Targets in Alzheimer's Disease.medRxiv : the preprint server for health sciences · 2025Article
- Mitigating inconsistencies in GWAS follow-up analyses with LocusCompare2.Nature genetics · 2025Article
- Higher eQTL power reveals signals that boost GWAS colocalization.bioRxiv : the preprint server for biology · 2025Article
- Human Genetics Informing Drug Development in Cardiovascular Disease: Interleukin-6 Signaling as a Case Study.Circulation. Genomic and precision medicine · 2025Review
- MR-link-2: pleiotropy robust cis Mendelian randomization validated in three independent reference datasets of causality.Nature communications · 2025Article
- Single-cell transcriptome-wide Mendelian randomization and colocalization analyses uncover cell-specific mechanisms in atherosclerotic cardiovascular disease.American journal of human genetics · 2025Article
- Distinct pathway-based effects of blood pressure and body mass index on cardiovascular traits: comparison of novel Mendelian randomization approaches.Genome medicine · 2025Article
- Variant-specific priors clarify colocalisation analysis.PLoS genetics · 2025Article
- Genome-wide association study for circulating metabolic traits in 619,372 individuals.medRxiv : the preprint server for health sciences · 2025Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Identifying causal genes underlying genome-wide association studies (GWASs) is a fundamental problem in human genetics. Although colocalization with gene expression quantitative trait loci (eQTLs) is often used to prioritize GWAS target genes, systematic benchmarking has been limited due to unavailability of large ground truth datasets. Here, we re-analyzed plasma protein QTL data from 3,301 individuals of the INTERVAL cohort together with 131 eQTL Catalog datasets. Focusing on variants located within or close to the affected protein identified 793 proteins with at least one cis-pQTL where we could assume that the most likely causal gene was the gene coding for the protein. We then benchmarked the ability of cis-eQTLs to recover these causal genes by comparing three Bayesian colocalization methods (coloc.susie, coloc.abf, and CLPP) and five Mendelian randomization (MR) approaches (three varieties of inverse-variance weighted MR, MR-RAPS, and MRLocus). We found that assigning fine-mapped pQTLs to their closest protein coding genes outperformed all colocalization methods regarding both precision (71.9%) and recall (76.9%). Furthermore, the colocalization method with the highest recall (coloc.susie - 46.3%) also had the lowest precision (45.1%). Combining evidence from multiple conditionally distinct colocalizing QTLs with MR increased precision to 81%, but this was accompanied by a large reduction in recall to 7.1%. Furthermore, the choice of the MR method greatly affected performance, with the standard inverse-variance-weighted MR often producing many false positives. Our results highlight that linking GWAS variants to target genes remains challenging with eQTL evidence alone, and prioritizing novel targets requires triangulation of evidence from multiple sources.
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