ArticleBioinformatics (Oxford, England)2018
A Bayesian framework for multiple trait colocalization from summary association statistics.
Article in Bioinformatics (Oxford, England), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 203 papers, 10 of them syntheses that pooled it.
What it found
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Who cites it
203 citing papers in PubMed, 10 syntheses or guidelines pooled it.
- GWAS meta-analysis of cerebrospinal fluid Alzheimer's biomarkers reveals loci regulating lipids, brain volume and autophagy.Nature communications · 2026Pooled it
- Investigating the shared genetic architecture between inflammatory bowel disease and pancreatitis: a genome-wide cross-trait analysis.Molecular genetics and genomics : MGG · 2026Pooled it
- Oxidative Stress-Related Genome-Wide Mendelian Randomization Identifies Causal Genes for Coronary Artery Disease.Cardiovascular therapeutics · 2026Pooled it
- Cross-ancestry genome-wide association study and systems-level integrative analyses implicate new risk genes and therapeutic targets for depression.Nature human behaviour · 2025Pooled it
- Multi-ancestry genome-wide association analyses improve resolution of genes and pathways influencing lung function and chronic obstructive pulmonary disease risk.Nature genetics · 2023Pooled it
- An international genome-wide meta-analysis of primary biliary cholangitis: Novel risk loci and candidate drugs.Journal of hepatology · 2021Pooled it
- Pooled it
- Prostate cancer risk SNP rs10993994 is a trans-eQTL for SNHG11 mediated through MSMB.Human molecular genetics · 2020Pooled it
- Associations of variants In the hexokinase 1 and interleukin 18 receptor regions with oxyhemoglobin saturation during sleep.PLoS genetics · 2019Pooled it
- GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes.Nature communications · 2018Pooled it
- Single-nucleus atlas of cell-type specific genetic regulation in the human brain.Nature genetics · 2026Article
- Multilevel genome-wide analysis reveals shared genetic architecture between acute pancreatitis and body fat distribution.World journal of emergency medicine · 2026Article
- Decoding Primary Open-Angle Glaucoma: A Multi-Omics Approach to Identify Druggable Effector Genes.Investigative ophthalmology & visual science · 2026Article
- Genome-wide DNA methylation analysis revealed epigenetic mechanism underlying end-stage renal disease.Nature communications · 2026Article
- LocusBlend: Flexible multi-index regional visualization of genomic association signals.medRxiv : the preprint server for health sciences · 2026Article
- Characterizing the impact of plasma protein levels on human brain structure and disorders leveraging integrative multi-omics analysis.medRxiv : the preprint server for health sciences · 2026Article
- Uncovering Novel Atrial Fibrillation Genetics Through Pleiotropic Overlap with Life's Essential 8.Biomedicines · 2026Article
- Causal cross-trait mapping at single-cell resolution identifies shared immunogenetic drivers of migraine and Meniere's disease.The journal of headache and pain · 2026Article
- Genome-wide association study and pathway analysis of healthy aging in Super Seniors.GeroScience · 2026Article
- Cell type-specific epigenetic regulatory circuitry of coronary artery disease loci.Nature communications · 2026Article
143 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
Motivation: Most genetic variants implicated in complex diseases by genome-wide association studies (GWAS) are non-coding, making it challenging to understand the causative genes involved in disease. Integrating external information such as quantitative trait locus (QTL) mapping of molecular traits (e.g. expression, methylation) is a powerful approach to identify the subset of GWAS signals explained by regulatory effects. In particular, expression QTLs (eQTLs) help pinpoint the responsible gene among the GWAS regions that harbor many genes, while methylation QTLs (mQTLs) help identify the epigenetic mechanisms that impact gene expression which in turn affect disease risk. In this work, we propose multiple-trait-coloc (moloc), a Bayesian statistical framework that integrates GWAS summary data with multiple molecular QTL data to identify regulatory effects at GWAS risk loci. Results: We applied moloc to schizophrenia (SCZ) and eQTL/mQTL data derived from human brain tissue and identified 52 candidate genes that influence SCZ through methylation. Our method can be applied to any GWAS and relevant functional data to help prioritize disease associated genes. Availability and implementation: moloc is available for download as an R package (https://github.com/clagiamba/moloc). We also developed a web site to visualize the biological findings (icahn.mssm.edu/moloc). The browser allows searches by gene, methylation probe and scenario of interest. Supplementary information: Supplementary data are available at Bioinformatics online.
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Registered trials
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.