| Title: | A Novel 10-Protein Score for Liver Fat Content Predicts Cardiovascular-Kidney-Metabolic Disease Risk |
| Journal: | Advanced Science |
| Published: | 23 Dec 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41432036/ |
| DOI: | https://doi.org/10.1002/advs.202515645 |
| URL: | http://dx.doi.org/10.1002/advs.202515645 |
Publication 17050
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Abstract
Liver fat content (LFC) is a key biomarker for cardiovascular-kidney-metabolic (CKM), yet noninvasive assessment remains challenging. It aims to develop a plasma proteomic-based LFC score to predict MRI-derived proton density fat fraction (MRI-PDFF), evaluate its association with 14 CKM diseases, and explore interactions with polygenic risk scores (PRS). Both the comprehensive 62-protein and simplified 10-protein LFC scores are developed and validated in 5,320 UK Biobank participants (96.8% White). The 10-protein 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-associated steatotic liver disease (MASLD), type 2 diabetes (T2D), chronic kidney disease, and coronary heart disease. The score significantly enhanced risk prediction for 8-10 CKM outcomes beyond standard risk factors and FLI (e.g., MASLD,C-index improved from 0.743 to 0.774; T2D, from 0.773 to 0.806). The score showed significant interactions with PRS for T2D (P-interaction<0.001). The 62-protein model yielded similar results. A 10-protein score accurately quantifies liver fat, predicts cardiometabolic risk, and integrates with genetic risk for precision prevention, providing a practical MRI alternative.</p>
13 Authors
- Xiaoqin Gan
- Yuanxiu Wei
- Yiting Wu
- Xinyue Su
- Gangling Wang
- Sisi Yang
- Ziliang Ye
- Yanjun Zhang
- Hao Xiang
- Yu Huang
- Yiwei Zhang
- Yuanyuan Zhang
- Xianhui Qin
1 Application
| Application ID | Title |
|---|---|
| 73201 | Identification of residual risks of non-infectious chronic diseases |
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