Plasma proteomics framework predicts metabolic dysfunction-associated steatotic liver disease up to 16 years before onset.

Authors

Shiyi Yu, Chunling Chen, Jing Feng, Qinming Li, Shuo Chen, Ruijie Zeng, Dongling Luo, Wentao Huang, Kexin Zhang, Yuying Ma, Lijun Zhang, Meijun Meng, Yanjun Wu, Dong Chen, Qizhou Lian, Felix W Leung, Chusi Wang, Weihong Sha, Hao Chen

Published in

Nature aging. Jul 30, 2026. Epub Jul 30, 2026.

Abstract

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global health challenge, yet preclinical identification remains difficult owing to a lack of reliable predictive tools. Here we show that a panel of five plasma proteins, FUOM, ACY1, KRT18, CDHR2 and GGT1, identified and validated across over 50,000 participants from the Southern UK, Northern UK, EPIC-Norfolk and Southern China cohorts, serves as a predictive signature for incident MASLD. Our five-protein model achieves predictive accuracy of 0.838 (5 year area under the curve (AUC)) and 0.756 (16.6 year AUC), with performance sustained longitudinally in the EPIC-Norfolk cohort (16.6 year AUC = 0.710) and confirmed in the Southern China Inception Cohort (AUC = 0.912). Integrating these biomarkers with routine clinical data further enhances performance (5 year AUC = 0.904; 16.6 year AUC = 0.822). These findings establish a scalable proteomic framework for ultra-early risk stratification and targeted intervention in MASLD up to 16 years before clinical onset.

PMID:
42533107
Bibliographic data and abstract were imported from PubMed on 31 Jul 2026.

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