{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T20:05:06Z","timestamp":1792785906193,"version":"4.5.0"},"reference-count":35,"publisher":"Oxford University Press (OUP)","issue":"11","license":[{"start":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T00:00:00Z","timestamp":1789430400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"name":"National Institute of Allergy and Infectious Diseases of the National Institutes of Health","award":["R01AI164947"],"award-info":[{"award-number":["R01AI164947"]}],"id":[{"id":"https:\/\/ror.org\/043z4tv69","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,10,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Aging is the strongest risk factor for most chronic diseases, yet aging-related diseases (ARDs) lack consistent, data-driven definitions. Prior work has proposed frameworks to classify ARDs based on age-specific onset patterns, but applications have largely relied on demographically homogeneous populations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We extended a data-driven framework integrating unsupervised clustering and actuarial modeling to electronic health record data from 633\u00a0547 participants in the US All of Us Research Program. Age-specific onset rates for 274 high-burden diseases between ages 21 and 74 were analyzed. Standardized onset curves were grouped using hierarchical agglomerative clustering. Aging-related patterns were assessed with Gompertz and Gompertz-Makeham (GM) models to quantify age-dependent increases in disease onset.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Eleven clusters of disease onset trajectories were identified, with 4 main clusters encompassing 96.0% of diseases. Two clusters exhibited pronounced late-life increases in onset rate, while 1 showed earlier but moderate age-related increases, and another displayed largely age-independent patterns. Cardiovascular diseases and cancers were enriched in clusters with strong aging-related onset trajectories. Overall, 165 diseases demonstrated strong evidence of being aging-related, characterized by positive Gompertz age coefficients and good GM model fit. Median onset ages varied across clusters and disease categories and showed statistically significant discrepancies compared with UK populations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>In a large, racially diverse US cohort, we identified distinct ARD clusters with shared age-related onset patterns. These findings extend prior work to a more diverse population and support integrated clustering and actuarial approaches to systematically define ARDs and inform aging research and public health strategies.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/gerona\/glag231","type":"journal-article","created":{"date-parts":[[2026,9,14]],"date-time":"2026-09-14T11:22:05Z","timestamp":1789384925000},"source":"Crossref","is-referenced-by-count":0,"title":["Aging-related diseases in the US population: a data-driven approach using All of Us electronic health record data"],"prefix":"10.1093","volume":"81","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-3361-4479","authenticated-orcid":false,"given":"Buwei","family":"He","sequence":"first","affiliation":[{"name":"Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina , Columbia, South Carolina,","place":["United 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