{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T18:05:28Z","timestamp":1789581928854,"version":"build-2803163510"},"update-to":[{"DOI":"10.1371\/journal.pgen.1012126","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T00:00:00Z","timestamp":1789516800000}}],"reference-count":64,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T00:00:00Z","timestamp":1788825600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/publicdomain\/zero\/1.0\/"}],"funder":[{"name":"NIDA of NIH","award":["1K01DA059603-01A1"],"award-info":[{"award-number":["1K01DA059603-01A1"]}]},{"DOI":"10.13039\/100008510","name":"University of Maryland","doi-asserted-by":"publisher","award":["Grand Challenge Grant"],"award-info":[{"award-number":["Grand Challenge Grant"]}],"id":[{"id":"10.13039\/100008510","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100008510","name":"University of Maryland","doi-asserted-by":"publisher","award":["EPIB Pilot Award"],"award-info":[{"award-number":["EPIB Pilot Award"]}],"id":[{"id":"10.13039\/100008510","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosgenetics.org"],"crossmark-restriction":false},"short-container-title":["PLoS Genet"],"abstract":"<jats:p>\n                    Transcriptome-wide association studies (TWAS) integrate genome wide association studies with expression quantitative trait locus reference panels to identify genes associated with traits of interest. However, linkage disequilibrium and correlated gene expression can induce spurious TWAS signals, motivating fine mapping methods to prioritize putatively causal genes within associated loci. The rapid growth of large-scale phenomic resources (e.g., electronic health records (EHRs)) has shifted genetic studies from single-trait analyses to phenome-wide investigations that jointly evaluate many closely related phenotypes. We introduce FM-GPT (\n                    <jats:bold>F<\/jats:bold>\n                    ine-\n                    <jats:bold>m<\/jats:bold>\n                    apping of causal\n                    <jats:bold>G<\/jats:bold>\n                    enes for\n                    <jats:bold>P<\/jats:bold>\n                    henome-wide\n                    <jats:bold>T<\/jats:bold>\n                    ranscriptome-wide association studies), a novel Bayesian fine mapping method for prioritizing causal genes across multiple correlated phenotypes with potentially mixed outcome types (e.g., continuous, binary, multinomial or count) in phenome-wide TWAS. FM-GPT performs gene-guided dimension reduction of the phenotypes and reveals pleiotropic or phenotype-specific effects of the identified genes. In simulations, FM-GPT identified true causal genes more accurately than other fine mapping methods while controlling false positives. We applied FM-GPT to two applications using data from UK Biobank: a brain-wide genetic analysis of MRI data derived regional cortical thickness measures and a phenome-wide genetic analysis of clinical phenotypes derived from EHR data. FM-GPT greatly narrowed down the set size of putatively causal genes and identified: 1. genes with pleiotropic effects on regional cortical thickness across the cerebral cortex, including five genes\n                    <jats:italic>BCAS3<\/jats:italic>\n                    ,\n                    <jats:italic>LRRC37A<\/jats:italic>\n                    ,\n                    <jats:italic>NOS2P3, ARL17B<\/jats:italic>\n                    and\n                    <jats:italic>UBB<\/jats:italic>\n                    on chromosome 17 regulating neuronal morphology and cortical organization; and 2. genes that influence multiple medical conditions across the circulatory, metabolic, digestive, respiratory and genitourinary systems, revealing two major axes of variation among these conditions that point to a potential trade-off in gene regulation between immune and metabolic functions. These results highlight FM-GPT\u2019s power to disentangle complex gene\u2013phenotype relationships in large-scale phenome-wide studies, revealing biological mechanisms underlying diverse human traits and advancing translational and comorbidity research.\n                  <\/jats:p>","DOI":"10.1371\/journal.pgen.1012126","type":"journal-article","created":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T17:59:16Z","timestamp":1788890356000},"page":"e1012126","update-policy":"https:\/\/doi.org\/10.1371\/journal.pgen.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["FM-GPT: Bayesian fine mapping for phenome-wide transcriptome-wide association studies"],"prefix":"10.1371","volume":"22","author":[{"given":"Travis","family":"Canida","sequence":"first","affiliation":[{"name":"University of Maryland","place":["College Park, Maryland, United States of America"],"department":["Department of Epidemiology and Biostatistics, School of Public Health"]},{"name":"University of Maryland","place":["College Park, Maryland, United States of America"],"department":["Department of Mathematics"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhenyao","family":"Ye","sequence":"additional","affiliation":[{"name":"University of Maryland","place":["Baltimore, Maryland, United States of America"],"department":["Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine"]},{"name":"University of Maryland","place":["Baltimore, Maryland, United States of America"],"department":["Department of Epidemiology and Public Health, School of Medicine"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shao-Hsuan","family":"Wang","sequence":"additional","affiliation":[{"name":"National Central University","place":["Taoyuan City, Taiwan"],"department":["Graduate Institute of Statistics"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hsin-Hsiung","family":"Huang","sequence":"additional","affiliation":[{"name":"University of Central Florida","place":["Orlando, Florida, United States of America"],"department":["Department of Statistics and Data Science"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-4014-0302","authenticated-orcid":true,"given":"Yezhi","family":"Pan","sequence":"additional","affiliation":[{"name":"University of Maryland","place":["College Park, Maryland, United States of America"],"department":["Department of Mathematics"]},{"name":"University of Maryland","place":["Baltimore, Maryland, United States of America"],"department":["Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Menglu","family":"Liang","sequence":"additional","affiliation":[{"name":"University of Maryland","place":["College Park, Maryland, United States of America"],"department":["Department of Epidemiology and Biostatistics, School of Public Health"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuo","family":"Chen","sequence":"additional","affiliation":[{"name":"University of Maryland","place":["Baltimore, Maryland, United States of America"],"department":["Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine"]},{"name":"University of Maryland","place":["Baltimore, Maryland, United States of America"],"department":["Department of Epidemiology and Public Health, School of Medicine"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3605-0811","authenticated-orcid":true,"given":"Tianzhou","family":"Ma","sequence":"additional","affiliation":[{"name":"University of Maryland","place":["College Park, Maryland, United States of America"],"department":["Department of Epidemiology and Biostatistics, School of Public Health"]},{"name":"University of Maryland","place":["Baltimore, Maryland, United States of America"],"department":["Maryland Psychiatric Research Center, Department of Psychiatry, School of Medicine"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,9,8]]},"reference":[{"issue":"6","key":"pgen.1012126.ref001","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1038\/ng.2653","article-title":"The Genotype-Tissue Expression (GTEx) project","volume":"45","author":"GTEx Consortium","year":"2013","journal-title":"Nat Genet"},{"issue":"4","key":"pgen.1012126.ref002","doi-asserted-by":"crossref","first-page":"592","DOI":"10.1038\/s41588-019-0385-z","article-title":"Opportunities and challenges for transcriptome-wide association studies","volume":"51","author":"M Wainberg","year":"2019","journal-title":"Nat 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