{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,3]],"date-time":"2026-07-03T05:10:42Z","timestamp":1783055442498,"version":"3.54.6"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1012725","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2025,1,17]],"date-time":"2025-01-17T00:00:00Z","timestamp":1737072000000}}],"reference-count":74,"publisher":"Public Library of Science (PLoS)","issue":"1","license":[{"start":{"date-parts":[[2025,1,7]],"date-time":"2025-01-07T00:00:00Z","timestamp":1736208000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Cancer Target Discovery and Development","award":["U01CA217846"],"award-info":[{"award-number":["U01CA217846"]}]},{"DOI":"10.13039\/100000050","name":"National Heart, Lung, and Blood Institute","doi-asserted-by":"publisher","award":["R01HL141989"],"award-info":[{"award-number":["R01HL141989"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100016460","name":"Jayne Koskinas Ted Giovanis Foundation for Health and Policy","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100016460","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Motivation: Genome-wide association studies (GWAS) have identified genetic variants, usually single-nucleotide polymorphisms (SNPs), associated with human traits, including disease and disease risk. These variants (or causal variants in linkage disequilibrium with them) usually affect the regulation or function of a nearby gene. A GWAS locus can span many genes, however, and prioritizing which gene or genes in a locus are most likely to be causal remains a challenge. Better prioritization and prediction of causal genes could reveal disease mechanisms and suggest interventions.<\/jats:p>\n<jats:p>Results: We describe a new Bayesian method, termed <jats:sc>SigNet<\/jats:sc> for significance networks, that combines information both within and across loci to identify the most likely causal gene at each locus. The <jats:sc>SigNet<\/jats:sc> method builds on existing methods that focus on individual loci with evidence from gene distance and expression quantitative trait loci (eQTL) by sharing information across loci using protein-protein and gene regulatory interaction network data. In an application to cardiac electrophysiology with 226 GWAS loci, only 46 (20%) have within-locus evidence from Mendelian genes, protein-coding changes, or colocalization with eQTL signals. At the remaining 180 loci lacking functional information, <jats:sc>SigNet<\/jats:sc> selects 56 genes other than the minimum distance gene, equal to 31% of the information-poor loci and 25% of the GWAS loci overall. Assessment by pathway enrichment demonstrates improved performance by <jats:sc>SigNet<\/jats:sc>. Review of individual loci shows literature evidence for genes selected by <jats:sc>SigNet<\/jats:sc>, including <jats:italic>PMP22<\/jats:italic> as a novel causal gene candidate.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1012725","type":"journal-article","created":{"date-parts":[[2025,1,7]],"date-time":"2025-01-07T18:46:41Z","timestamp":1736275601000},"page":"e1012725","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":2,"title":["Prioritization of causal genes from genome-wide association studies by Bayesian data integration across loci"],"prefix":"10.1371","volume":"21","author":[{"given":"Zeinab","family":"Mousavi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marios","family":"Arvanitis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"ThuyVy","family":"Duong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jennifer A.","family":"Brody","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexis","family":"Battle","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nona","family":"Sotoodehnia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Shojaie","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan E.","family":"Arking","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6020-4625","authenticated-orcid":true,"given":"Joel S.","family":"Bader","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,1,7]]},"reference":[{"issue":"6562","key":"pcbi.1012725.ref001","doi-asserted-by":"crossref","first-page":"1464","DOI":"10.1126\/science.abi8207","article-title":"From variant to function in human disease genetics","volume":"373","author":"T Lappalainen","year":"2021","journal-title":"Science"},{"issue":"3","key":"pcbi.1012725.ref002","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1016\/j.ajhg.2022.01.017","article-title":"A multi-dimensional integrative scoring framework for predicting functional variants in the human genome","volume":"109","author":"X Li","year":"2022","journal-title":"The American Journal of Human Genetics"},{"key":"pcbi.1012725.ref003","unstructured":"McKusick V. 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