{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"submitter":["MULTI consortium"],"funding":["NIA NIH HHS"],"pubmed_abstract":["Disease heterogeneity and commonality pose significant challenges to precision medicine, as traditional approaches frequently focus on single disease entities and overlook shared mechanisms across conditions<sup>1</sup>. Inspired by pan-cancer<sup>2</sup> and multi-organ research<sup>3</sup>, we introduce the concept of \"pan-disease\" to investigate the heterogeneity and shared etiology in brain, eye, and heart diseases. Leveraging individual-level data from 129,340 participants, as well as summary-level data from the MULTI consortium, we applied a weakly-supervised deep learning model (Surreal-GAN<sup>4,5</sup>) to multi-organ imaging, genetic, proteomic, and RNA-seq data, identifying 11 AI-derived biomarkers - called Multi-organ AI Endophenotypes (MAEs) - for the brain (Brain 1-6), eye (E"],"journal":["medRxiv : the preprint server for health sciences"],"pagination":["2025.08.09.25333350"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12363687"],"repository":["biostudies-literature"],"pubmed_title":["Multi-organ AI Endophenotypes Chart the Heterogeneity of Pan-disease in the Brain, Eye, and Heart."],"pmcid":["PMC12363687"],"funding_grant_id":["RF1 AG092412","RF1 AG054409"],"pubmed_authors":["Zalesky A","Duggan MR","Erus G","Tian YE","Srinivasan D","Bai W","Walker KA","Anagnostakis F","Boquet-Pujadas A","Yang Z","Davatzikos C","Wen J","Joynes CM","Patel PJ","MULTI consortium"],"additional_accession":[]},"is_claimable":false,"name":"Multi-organ AI Endophenotypes Chart the Heterogeneity of Pan-disease in the Brain, Eye, and Heart.","description":"Disease heterogeneity and commonality pose significant challenges to precision medicine, as traditional approaches frequently focus on single disease entities and overlook shared mechanisms across conditions<sup>1</sup>. Inspired by pan-cancer<sup>2</sup> and multi-organ research<sup>3</sup>, we introduce the concept of \"pan-disease\" to investigate the heterogeneity and shared etiology in brain, eye, and heart diseases. Leveraging individual-level data from 129,340 participants, as well as summary-level data from the MULTI consortium, we applied a weakly-supervised deep learning model (Surreal-GAN<sup>4,5</sup>) to multi-organ imaging, genetic, proteomic, and RNA-seq data, identifying 11 AI-derived biomarkers - called Multi-organ AI Endophenotypes (MAEs) - for the brain (Brain 1-6), eye (E","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Aug","modification":"2026-06-19T03:16:49.51Z","creation":"2026-06-19T03:07:39.208Z"},"accession":"S-EPMC12363687","cross_references":{"pubmed":["40832432"],"doi":["10.1101/2025.08.09.25333350"]}}