{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T13:32:36Z","timestamp":1768570356367,"version":"3.49.0"},"posted":{"date-parts":[[2025,7,11]]},"group-title":"Health Informatics","reference-count":89,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T00:00:00Z","timestamp":1752192000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2025,7,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>\n                  Leveraging clinical phenotypes\n                  <jats:sup>1,2<\/jats:sup>\n                  , neuroimaging\n                  <jats:sup>3<\/jats:sup>\n                  , proteomics\n                  <jats:sup>4<\/jats:sup>\n                  , metabolomics\n                  <jats:sup>5<\/jats:sup>\n                  , and epigenetics\n                  <jats:sup>6<\/jats:sup>\n                  , biological aging clocks across organ systems and tissues have advanced our understanding of human aging and disease. In this study, we expand this biological aging clock framework to multi-organ magnetic resonance imaging (MRI) by developing 7 organ-specific MRI-based biological age gaps (MRIBAGs), including the brain, heart, liver, adipose tissue, spleen, kidney, and pancreas. Leveraging imaging, genetic, proteomic, and metabolomic data from 313,645 individuals curated by the MULTI consortium, we link the 7 MRIBAGs to 2,923 plasma proteins, 327 metabolites, and 6,477,810 common genetic variants. These associations reveal organ-specific and cross-organ interconnection landscapes, identifying distinct molecular signatures related to organ aging. Genome-wide associations identify 53 MRIBAG-locus pairs (P&lt;5\u00d710\n                  <jats:sup>D8<\/jats:sup>\n                  ). Genetic correlation and Mendelian randomization analyses further support organ-specific and cross-organ interconnections with 9 phenotype-based\n                  <jats:sup>1,2<\/jats:sup>\n                  , 11 proteome-based\n                  <jats:sup>7<\/jats:sup>\n                  , and 5 metabolome-based aging clocks\n                  <jats:sup>5<\/jats:sup>\n                  , as well as 525 disease endpoints. Through functional gene mapping and Bayesian colocalization analysis linking evidence from genetics, proteomics, and metabolomics, we prioritize 9 druggable genes as targets for future anti-aging treatments. Finally, we demonstrate the clinical relevance of the 7 MRIBAGs in predicting disease endpoints (e.g., diabetes mellitus), all-cause mortality, and capturing differential and heterogeneous cognitive decline trajectories over 240 weeks of treatment with the Alzheimer\u2019s disease drug (Solanezumab). Sex differences are evident across multiple organ systems, manifesting at structural, molecular, and genetic levels. In summary, we developed 7 MRI-based aging clocks that enhance the existing multi-organ biological aging framework, offer multi-scale insights into aging biology, and demonstrate clinical potential to advance future aging research.\n                <\/jats:p>","DOI":"10.1101\/2025.07.10.25331263","type":"posted-content","created":{"date-parts":[[2025,7,12]],"date-time":"2025-07-12T01:55:17Z","timestamp":1752285317000},"source":"Crossref","is-referenced-by-count":0,"title":["Multi-organ MRI digitizes biological aging clocks across proteomics, metabolomics, and genetics"],"prefix":"10.64898","author":[{"name":"The MULTI Consortium","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huizi","family":"Cao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiyuan","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael 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