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It aims to develop a plasma proteomic\u2010based LFC score to predict MRI\u2010derived proton density fat fraction (MRI\u2010PDFF), evaluate its association with 14 CKM diseases, and explore interactions with polygenic risk scores (PRS). Both the comprehensive 62\u2010protein and simplified 10\u2010protein LFC scores are developed and validated in 5,320 UK Biobank participants (96.8% White). The 10\u2010protein LFC score, comprising proteins involved in adipogenesis, lipid metabolism, and insulin signaling (IGFBP2, FABP4, MET, CPM, CES1, IGFBP1, CDHR2, RBP5, ERBB2, SSC5D), showed superior diagnostic accuracy for hepatic steatosis compared to fatty liver index(FLI) (AUC = 0.850 vs. 0.794). Among 45,444 participants, it exhibited significant associations with 16 cardiometabolic risk markers and 13 incident CKM outcomes, particularly metabolic dysfunction\u2010associated steatotic liver disease (MASLD), type 2 diabetes (T2D), chronic kidney disease, and coronary heart disease. The score significantly enhanced risk prediction for 8\u201310 CKM outcomes beyond standard risk factors and FLI (e.g., MASLD,C\u2010index improved from 0.743 to 0.774; T2D, from 0.773 to 0.806). The score showed significant interactions with PRS for T2D (\n                    <jats:italic>P<\/jats:italic>\n                    \u2010interaction&lt;0.001). The 62\u2010protein model yielded similar results. A 10\u2010protein score accurately quantifies liver fat, predicts cardiometabolic risk, and integrates with genetic risk for precision prevention, providing a practical MRI alternative.\n                  <\/jats:p>","DOI":"10.1002\/advs.202515645","type":"journal-article","created":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T10:33:21Z","timestamp":1766486001000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Novel 10\u2010Protein Score for Liver Fat Content Predicts Cardiovascular\u2010Kidney\u2010Metabolic Disease Risk"],"prefix":"10.1002","volume":"13","author":[{"given":"Xiaoqin","family":"Gan","sequence":"first","affiliation":[{"name":"Division of Nephrology Nanfang Hospital Southern Medical University National Clinical Research Center for Kidney Disease State\u00a0Key Laboratory of\u00a0Multi\u2010organ Injury\u00a0Prevention and Treatment Guangdong Provincial Institute of Nephrology Guangdong Provincial Key Laboratory of Renal Failure Research  Guangzhou 510515 China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuanxiu","family":"Wei","sequence":"additional","affiliation":[{"name":"Department of Epidemiology and Biostatistics School of Public Health Anhui Medical University  Hefei Anhui China"},{"name":"Institute of Biomedicine Anhui Medical University  Hefei China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiting","family":"Wu","sequence":"additional","affiliation":[{"name":"Division of Nephrology Nanfang Hospital Southern Medical University National Clinical Research Center for Kidney Disease State\u00a0Key Laboratory of\u00a0Multi\u2010organ Injury\u00a0Prevention and Treatment Guangdong Provincial Institute of Nephrology Guangdong Provincial Key Laboratory of Renal Failure Research  Guangzhou 510515 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