{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T02:59:14Z","timestamp":1790823554502,"version":"4.1.0"},"reference-count":38,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T00:00:00Z","timestamp":1790726400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"},{"start":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T00:00:00Z","timestamp":1790726400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["dom-pubs.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Diabetes Obesity Metabolism"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>Cardiovascular\u2010kidney\u2010metabolic (CKM) stages 0\u20132 represent a potentially modifiable period before overt cardiovascular complications, yet molecular markers that identify individuals at higher downstream risk remain insufficiently defined. We investigated whether plasma proteomic signatures could characterize early CKM\u2010related molecular risk and improve prediction of incident cardiovascular, kidney and mortality outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and Methods<\/jats:title>\n                    <jats:p>We analysed 43\u2009709 UK Biobank participants with CKM stages 0\u20132 and measurements of 2920 plasma proteins. Multivariable Cox models evaluated protein associations with 11 incident outcomes after excluding participants with the corresponding condition at baseline. We further assessed modelled prediagnostic protein patterns, stage\u2010related proteomic patterns across baseline CKM stage groups, and the incremental value of outcome\u2010specific and recurrent protein panels beyond clinical models using Predicting Risk of Cardiovascular Disease Events (PREVENT)\u2010aligned covariates.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 157 proteins showed directionally concordant associations across all 11 outcomes, including 155 positive and 2 inverse associations. Population\u2010level models across time\u2010to\u2010outcome intervals identified differences in GDF15, TNFRSF10B, WFDC2 and NT\u2010proBNP between incident cases and matched reference participants. Eleven of the 155 proteins with positive associations across all 11 outcomes were consistently elevated across baseline CKM stage groups 0\u20132. In repeated internal validation, outcome\u2010specific proteomic signatures improved discrimination beyond the clinical model, with \u0394C\u2010index values of 0.024\u20130.070. An exploratory recurrent 12\u2010protein panel retained incremental value in internal evaluation, with \u0394C\u2010index gains of 0.018\u20130.052.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>In early\u2010stage CKM, plasma proteomic signatures captured preclinical molecular risk and improved prognostic discrimination beyond conventional clinical factors. These findings support further evaluation of targeted proteomic panels for earlier CKM risk stratification and preventive cardiometabolic management.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/dom.71399","type":"journal-article","created":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T02:44:40Z","timestamp":1790822680000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Plasma Proteomic Signatures for Early Risk Stratification Across Cardiovascular\u2010Kidney\u2010Metabolic Stages 0\u20132"],"prefix":"10.1111","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-5578-4693","authenticated-orcid":false,"given":"Xingyu","family":"Li","sequence":"first","affiliation":[{"name":"Department of Endocrinology and Metabolism, the First Affiliated Hospital of USTC, Division of Life Sciences and Medicine University of Science and Technology of China  Hefei Anhui China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongqiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Endocrinology and Metabolism, the First Affiliated Hospital of USTC, Division of Life Sciences and Medicine University of Science and Technology of China  Hefei Anhui China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Suijian","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Endocrinology The First Affiliated Hospital of Anhui Medical University  Hefei Anhui China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Shi","sequence":"additional","affiliation":[{"name":"Department of Endocrinology and Metabolism, the First Affiliated Hospital of USTC, Division of Life Sciences and Medicine University of Science and Technology of China  Hefei Anhui 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