ArticleNucleic acids research2019
ProGeM: a framework for the prioritization of candidate causal genes at molecular quantitative trait loci.
Article in Nucleic acids research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers, 10 of them syntheses that pooled it.
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Who cites it
77 citing papers in PubMed, 10 syntheses or guidelines pooled it.
- Pooled it
- Genome-wide characterization of 54 urinary metabolites reveals molecular impact of kidney function.Nature communications · 2025Pooled it
- European and multi-ancestry genome-wide association meta-analysis of atopic dermatitis highlights importance of systemic immune regulation.Nature communications · 2023Pooled it
- Genome-wide screen of otosclerosis in population biobanks: 27 loci and shared associations with skeletal structure.Nature communications · 2023Pooled it
- Discovery and systematic characterization of risk variants and genes for coronary artery disease in over a million participants.Nature genetics · 2022Pooled it
- Advancing our understanding of genetic risk factors and potential personalized strategies for pelvic organ prolapse.Nature communications · 2022Pooled it
- Comprehensive genetic analysis of the human lipidome identifies loci associated with lipid homeostasis with links to coronary artery disease.Nature communications · 2022Pooled it
- The landscape of GWAS validation; systematic review identifying 309 validated non-coding variants across 130 human diseases.BMC medical genomics · 2022Pooled it
- Genome-wide meta-analysis, fine-mapping and integrative prioritization implicate new Alzheimer's disease risk genes.Nature genetics · 2021Pooled it
- Genome-wide meta-analysis of muscle weakness identifies 15 susceptibility loci in older men and women.Nature communications · 2021Pooled it
- Article
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- Mapping enhancer-gene regulatory interactions from single-cell data.Nature genetics · 2026Article
- Kernelized approach enables explainable gene prioritizations for complex traits.bioRxiv : the preprint server for biology · 2026Article
- Genome-wide association studies of missing metabolite measures from two population-based studies.Genome biology · 2026Article
- Genetically supported drug target prioritization for rare diseases.Genome medicine · 2026Article
- Multi-cohort proteogenomic analyses reveal genetic effects across the proteome and diseasome.Cell · 2026Article
- Population-based genome-wide association study of plasma complex lipid species.Nature communications · 2026Article
- Simplifying causal gene identification in GWAS loci.PLoS genetics · 2026Article
- Genetic screens of imaging-derived kidney volumes identify genes linked to kidney function.Kidney international · 2026Article
17 more citing papers are in PubMed but not listed here.
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9 authors.
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Abstract
Quantitative trait locus (QTL) mapping of molecular phenotypes such as metabolites, lipids and proteins through genome-wide association studies represents a powerful means of highlighting molecular mechanisms relevant to human diseases. However, a major challenge of this approach is to identify the causal gene(s) at the observed QTLs. Here, we present a framework for the 'Prioritization of candidate causal Genes at Molecular QTLs' (ProGeM), which incorporates biological domain-specific annotation data alongside genome annotation data from multiple repositories. We assessed the performance of ProGeM using a reference set of 227 previously reported and extensively curated metabolite QTLs. For 98% of these loci, the expert-curated gene was one of the candidate causal genes prioritized by ProGeM. Benchmarking analyses revealed that 69% of the causal candidates were nearest to the sentinel variant at the investigated molecular QTLs, indicating that genomic proximity is the most reliable indicator of 'true positive' causal genes. In contrast, cis-gene expression QTL data led to three false positive candidate causal gene assignments for every one true positive assignment. We provide evidence that these conclusions also apply to other molecular phenotypes, suggesting that ProGeM is a powerful and versatile tool for annotating molecular QTLs. ProGeM is freely available via GitHub.
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