Zhao YH, Leng SS, Wang Y, Kui FZ, Gan W. Non-invasive blood biomarkers for assessment of liver fibrosis in metabolic dysfunction-associated steatotic liver disease. World J Hepatol 2025; 17(11): 110080 [DOI: 10.4254/wjh.v17.i11.110080]
Corresponding Author of This Article
Wei Gan, PhD, Professor, Department of Laboratory Medicine, West China Hospital, Sichuan University; Sichuan Clinical Research Center for Laboratory Medicine, and Clinical Laboratory Medicine Research Center of West China Hospital, No. 37 Guoxue Lane, Wuhou District, Chengdu 610041, Sichuan Province, China. 2004ganwei@scu.edu.cn
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Gastroenterology & Hepatology
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Minireviews
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This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Nov 27, 2025 (publication date) through Dec 4, 2025
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World Journal of Hepatology
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1948-5182
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Zhao YH, Leng SS, Wang Y, Kui FZ, Gan W. Non-invasive blood biomarkers for assessment of liver fibrosis in metabolic dysfunction-associated steatotic liver disease. World J Hepatol 2025; 17(11): 110080 [DOI: 10.4254/wjh.v17.i11.110080]
World J Hepatol. Nov 27, 2025; 17(11): 110080 Published online Nov 27, 2025. doi: 10.4254/wjh.v17.i11.110080
Non-invasive blood biomarkers for assessment of liver fibrosis in metabolic dysfunction-associated steatotic liver disease
Yan-Hua Zhao, Shu-Sheng Leng, Yan Wang, Fa-Zhi Kui, Wei Gan
Yan-Hua Zhao, Yan Wang, Fa-Zhi Kui, Wei Gan, Department of Laboratory Medicine, West China Hospital, Sichuan University; Sichuan Clinical Research Center for Laboratory Medicine, and Clinical Laboratory Medicine Research Center of West China Hospital, Chengdu 610041, Sichuan Province, China
Shu-Sheng Leng, Department of Hepatobiliary and Pancreatic Surgery, Affiliated Hospital/Clinical Medical College of Chengdu University, Chengdu 610081, Sichuan Province, China
Author contributions: Zhao YH reviewed the literature and drafted the manuscript; Leng SS, Wang Y, and Kui FZ reviewed the literature and proofread the manuscript; Gan W conceived the idea for the manuscript; and all authors thoroughly reviewed and endorsed the final manuscript.
Supported by the National Natural Science Foundation of China, No. 82402719, and Sichuan Science and Technology Program, No. 2025ZNSFSC1553.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Wei Gan, PhD, Professor, Department of Laboratory Medicine, West China Hospital, Sichuan University; Sichuan Clinical Research Center for Laboratory Medicine, and Clinical Laboratory Medicine Research Center of West China Hospital, No. 37 Guoxue Lane, Wuhou District, Chengdu 610041, Sichuan Province, China. 2004ganwei@scu.edu.cn
Received: May 29, 2025 Revised: July 1, 2025 Accepted: October 10, 2025 Published online: November 27, 2025 Processing time: 182 Days and 20.5 Hours
Abstract
Metabolic dysfunction-associated steatotic liver disease (MASLD) requires accurate liver fibrosis assessment for management. While liver biopsy remains the gold standard, its invasiveness drives demand for non-invasive biomarkers. This review evaluates blood biomarkers for MASLD fibrosis staging. Established scores (fibrosis-4, non-alcoholic fatty liver disease fibrosis score) offer accessible screening but exhibit variable performance influenced by age, obesity, and comorbidities. Patented panels (e.g., enhanced liver fibrosis test, FibroMeter) improve accuracy by integrating extracellular matrix or metabolic markers, though context-specific thresholds are essential. Emerging biomarkers like propeptide of type 3 collagen, Mac-2 binding protein glycosylation isomer, epigenetic markers (proliferator-activated receptor-γ methylation), and angiopoietin-like proteins a family of eight glycoproteins show promise but require large-scale validation. Genetic risk scores and multi-omics approaches face generalizability challenges. Integration strategies, such as combining serum biomarkers with liver stiffness measurement via Agile scores, enhance diagnostic precision and reduce indeterminate classifications. Current tools aid risk stratification, but no single biomarker replicates biopsy-level precision. Future efforts must prioritize MASLD-specific diagnostic frameworks, standardized protocols, and multi-modal integration to enhance clinical utility and address MASLD’s growing burden.
Core Tip: Current biomarkers (fibrosis-4, non-alcoholic fatty liver disease fibrosis score) provide accessible first-line screening for metabolic dysfunction-associated steatotic liver disease (MASLD) fibrosis but require age/obesity-adjusted thresholds. Patented panels (enhanced liver fibrosis, FibroMeter) enhance precision through metabolic/extracellular matrix markers yet need MASLD-specific validation. Emerging biomarkers (propeptide of type 3 collagen, Mac-2 binding protein glycosylation isomer, epigenetic regulators like proliferator-activated receptor-γ methylation, angiopoietin-like proteins such as angiopoietin-like protein a family of eight glycoproteins) show monitoring potential but need validation. No single biomarker replaces biopsy. Combining existing tools with novel multi-omics approaches and MASLD-specific diagnostic frameworks is critical for improving clinical outcomes in this epidemic.