Metabolomics in the Diagnosis, Pathogenesis, and Treatment of Chronic Liver Diseases Using Traditional Chinese Medicine

Simiao Yu , Yongle Liu , Chao Zhou , Haocheng Zheng , Sici Wang , Jiahui Li , Tingting He , Yongqiang Sun , Liping Wang , Jing Jing , Xia Ding , Ruilin Wang

›› 2024, Vol. 3 ›› Issue (4) : 262 -273.

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›› 2024, Vol. 3 ›› Issue (4) :262 -273. DOI: 10.14218/FIM.2024.00044
Review Article
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Metabolomics in the Diagnosis, Pathogenesis, and Treatment of Chronic Liver Diseases Using Traditional Chinese Medicine
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Abstract

Chronic liver disease (CLD) is a major global health challenge, characterized by chronic inflammation that can progress to liver fibrosis, cirrhosis, and ultimately hepatocellular carcinoma. Early identification of biomarkers is crucial for effective intervention. Traditional Chinese medicine (TCM) has shown potential in improving CLD symptoms and protecting the liver, although its mechanisms remain unclear. Metabolomics, the comprehensive study of metabolites, offers a promising approach to understanding CLD pathogenesis and identifying biomarkers. Notably, metabolomics aligns with TCM’s holistic approach and may help reveal its therapeutic mechanisms. This review summarizes key metabolites associated with CLD diagnosis and progression and discusses how TCM may modulate metabolic pathways to alleviate CLD symptoms. These insights could lead to improved diagnostic and therapeutic strategies for CLD.

Keywords

Metabolomics / Chronic liver disease / Traditional Chinese medicine / Treatment / Diagnostic / Pathogenesis / Viral hepatitis / Alcoholic liver disease / Non-alcoholic fatty liver disease / Autoimmune liver disease / Drug-induced liver injury / Hepatocellular carcinoma

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Simiao Yu, Yongle Liu, Chao Zhou, Haocheng Zheng, Sici Wang, Jiahui Li, Tingting He, Yongqiang Sun, Liping Wang, Jing Jing, Xia Ding, Ruilin Wang. Metabolomics in the Diagnosis, Pathogenesis, and Treatment of Chronic Liver Diseases Using Traditional Chinese Medicine. , 2024, 3(4): 262-273 DOI:10.14218/FIM.2024.00044

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Acknowledgments

None.

Funding

This work was supported by the National Thirteen Five-year Science and Technology Major Project of China (No. 2018ZX10725506-002), the National Twelve Five-year Science and Technology Major Project of China (No. 2012ZX10005-005), the National Natural Science Foundation of China (No. 81673806), and the National Natural Science Foundation Youth Fund (No. 82104702 and No. 82305067).

Conflict of interest

The authors declare no conflicts of interest in this work.

Author contributions

Conception and preparation of the manuscript (SMY, YLL, CZ), table making (HCZ), drafting the manuscript via an intense litera-ture survey (HCZ, SCW, JHL, TTH, YQS, LPW), review and edit-ing of the manuscript (JJ), and supervision of the manuscript (XD, RLW). All authors have approved the final version and publication of the manuscript.

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