Identification and Validation of Biomarkers in Metabolic Dysfunction-Associated Steatohepatitis Using Machine Learning and Bioinformatics.

Journal: Molecular genetics & genomic medicine
PMID: 39995143

Abstract

BACKGROUND: The incidence of metabolic dysfunction-associated steatohepatitis (MASH) is increasing annually. MASH can progress to cirrhosis and hepatocellular carcinoma. However, the early diagnosis of MASH is challenging.

Authors

  • Yu-Ying Zhang
    Department of Endocrinology and Metabolism, The 2nd Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang City, Jiangxi Province, China.
  • Jin-E Li
    Department of Endocrinology and Metabolism, The 2nd Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang City, Jiangxi Province, China.
  • Hai-Xia Zeng
    Department of Endocrinology and Metabolism, The 2nd Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang City, Jiangxi Province, China.
  • Shuang Liu
    Key Laboratory for Applied Technology of Sophisticated Analytical Instruments of Shandong Province, Shandong Analysis and Test Center, Qilu University of Technology (Shandong Academy of Sciences), Jinan, 250014, China.
  • Yun-Fei Luo
    Department of Endocrinology and Metabolism, The 2nd Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang City, Jiangxi Province, China.
  • Peng Yu
    College of Life Science, Northwest Normal University, Lanzhou, 730070, Gansu, People's Republic of China.
  • Jian-Ping Liu
    Centre for Evidence-Based Chinese Medicine, Beijing University of Chinese Medicine, Beijing, China.

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