Serum metabolite profiles are associated with the presence of advanced liver fibrosis in Chinese patients with chronic hepatitis B viral infection

BMC Medicine

Hua Bian¹  Xin Gao¹  Xinzhu Liu²  Guoxiang Xie²  Xiaoning Wang²  Wei Jia²  Zhun Xiao²  Ping Liu²  Hua Zhang²  Yixing Wang³  Tianlu Chen⁴  Aihua Zhao⁴  Runmin Wei⁵  Linda Wong⁵  Sandi Kwee⁵  Jingye Wang⁵  Youping Deng⁵  Cynthia Rajani⁵ 

[1] Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University;E-Institute of Shanghai Municipal Education Committee, Institute of Interdisciplinary Integrative Medicine Research, Shanghai University of Traditional Chinese Medicine;Key Laboratory of Liver and Kidney Diseases (Ministry of Education), Shuguang Hospital, Shanghai University of Traditional Chinese Medicine;Shanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital;University of Hawaii Cancer Center;

关键词: Bile acids;    Free fatty acids;    Amino acids;    Hepatitis B;    Chronic liver disease;    Liver fibrosis;   

DOI  :  10.1186/s12916-020-01595-w

来源: DOAJ

【 摘 要 】

Abstract Background Accurate and noninvasive diagnosis and staging of liver fibrosis are essential for effective clinical management of chronic liver disease (CLD). We aimed to identify serum metabolite markers that reliably predict the stage of fibrosis in CLD patients. Methods We quantitatively profiled serum metabolites of participants in 2 independent cohorts. Based on the metabolomics data from cohort 1 (504 HBV associated liver fibrosis patients and 502 normal controls, NC), we selected a panel of 4 predictive metabolite markers. Consequently, we constructed 3 machine learning models with the 4 metabolite markers using random forest (RF), to differentiate CLD patients from normal controls (NC), to differentiate cirrhosis patients from fibrosis patients, and to differentiate advanced fibrosis from early fibrosis, respectively. Results The panel of 4 metabolite markers consisted of taurocholate, tyrosine, valine, and linoelaidic acid. The RF models of the metabolite panel demonstrated the strongest stratification ability in cohort 1 to diagnose CLD patients from NC (area under the receiver operating characteristic curve (AUROC) = 0.997 and the precision-recall curve (AUPR) = 0.994), to differentiate fibrosis from cirrhosis (0.941, 0.870), and to stage liver fibrosis (0.918, 0.892). The diagnostic accuracy of the models was further validated in an independent cohort 2 consisting of 300 CLD patients with chronic HBV infection and 90 NC. The AUCs of the models were consistently higher than APRI, FIB-4, and AST/ALT ratio, with both greater sensitivity and specificity. Conclusions Our study showed that this 4-metabolite panel has potential usefulness in clinical assessments of CLD progression in patients with chronic hepatitis B virus infection.

【 授权许可】

Unknown