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Here, we integrated metabolomics, proteomics and genetics from UK Biobank to characterize the protein architecture of metabolomic aging. Building on our previous mortality-trained score (MetScore1), we developed MetScore2 from 325 NMR biomarkers in 400,594 participants. Higher MetScore2 values marked earlier onset of age-related diseases, and faster score increases predicted higher mortality. Proteome-wide association study identified MetScore2-associated plasma proteins. Their signature was broadly similar in both sexes but showed undulating changes across mid-to-late adulthood, with peaks at 50, 57 and 65 years. By integrating GWAS, Mendelian randomization and colocalization, we identified IL1RN, ARG1, NCAN, F11R, SERPINF2 and NBL1 as putative causal proteins, each with distinct disease associations. Our findings delineate the proteomic landscape of metabolomic aging and prioritize candidate causal proteins for mechanistic and translational follow-up.<\/jats:p>","DOI":"10.64898\/2026.09.27.26364110","type":"posted-content","created":{"date-parts":[[2026,9,28]],"date-time":"2026-09-28T23:10:10Z","timestamp":1790637010000},"source":"Crossref","is-referenced-by-count":0,"title":["Metabolomic profiling identifies plasma protein biomarkers of biological aging"],"prefix":"10.64898","author":[{"given":"Xinting","family":"Luo","sequence":"first","affiliation":[{"name":"Department of Biomedical Informatics, School of Life Sciences, Central South University, Changsha, Hunan, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chong","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Biomedical Informatics, School of Life Sciences, Central South University, Changsha, Hunan, 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