{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T21:20:23Z","timestamp":1792790423860,"version":"4.5.0"},"posted":{"date-parts":[[2026,10,6]]},"group-title":"Bioinformatics","reference-count":43,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T00:00:00Z","timestamp":1791244800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"name":"European Union\u2019s Horizon Europe Research and Innovation Programme","award":["101137146"],"award-info":[{"award-number":["101137146"]}]},{"name":"Chan Zuckerberg Foundation","award":["2019-202666"],"award-info":[{"award-number":["2019-202666"]}],"id":[{"id":"https:\/\/ror.org\/02qenvm24","id-type":"ROR","asserted-by":"crossref"}]},{"name":"Chan Zuckerberg Foundation","award":["2021-237882"],"award-info":[{"award-number":["2021-237882"]}],"id":[{"id":"https:\/\/ror.org\/02qenvm24","id-type":"ROR","asserted-by":"crossref"}]},{"name":"DZHK","award":["81Z0600106"],"award-info":[{"award-number":["81Z0600106"]}],"id":[{"id":"https:\/\/ror.org\/031t5w623","id-type":"ROR","asserted-by":"crossref"}]},{"name":"DZHK","award":["81Z0600105"],"award-info":[{"award-number":["81Z0600105"]}],"id":[{"id":"https:\/\/ror.org\/031t5w623","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,10,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>Proteomic aging clocks have emerged as biomarkers of aging, but most rely on cross-sectional data. Here, we present a proteomic aging clock based on longitudinal measurements of liquid chromatography\u2013mass spectrometry plasma proteomics at up to three time points in the population-based KORA cohort, comprising 9,105 samples from 4,100 individuals in the final dataset aged 25\u201388 years. The model predicts chronological age and yields a measure of proteomic age acceleration associated with lifestyle and clinical risk factors. Risk factor\u2013stratified analyses reveal shared proteomic signatures among cardiometabolic exposures and distinct signatures for smoking and physical activity. Within individuals, dyslipidemia and impaired kidney function track transitions to increases in age acceleration, while higher age acceleration is associated with increased all-cause mortality. Mediation analysis suggests that risk factors are linked to mortality indirectly through age acceleration. Affected proteins and pathways highlight extracellular matrix remodeling, complement and coagulation pathways, and liver-derived plasma proteins as key contributors to aging. Mendelian randomization identifies proteins with evidence consistent with a causal role in aging-related traits. Together, these findings are consistent with biological aging being dynamically responsive to changes in modifiable risk factors.<\/jats:p>","DOI":"10.64898\/2026.10.01.755909","type":"posted-content","created":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T17:05:24Z","timestamp":1791306324000},"source":"Crossref","is-referenced-by-count":0,"title":["Intraindividual longitudinal changes of the proteome reveal dynamic markers of biological aging"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-8612-3874","authenticated-orcid":false,"given":"R.","family":"Lermer","sequence":"first","affiliation":[{"name":"Department of Cardiology, German Heart Center, TUM University Hospital, TUM School of Medicine and Health, Technical University Munich, 80636 Munich, Germany"},{"name":"Institute of Computational Biology, German Research Center for Environmental Health, Helmholtz Zentrum M\u00fcnchen, Neuherberg, Germany"},{"name":"Department of Computer Science, TUM School 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