Frontiers in Medicine (Nov 2020)

Metabolomics Profiling and Diagnosis Biomarkers Searching for Drug-Induced Liver Injury Implicated to Polygonum multiflorum: A Cross-Sectional Cohort Study

  • Ying Huang,
  • Ying Huang,
  • Xu Zhao,
  • Zi-teng Zhang,
  • Shuai-shuai Chen,
  • Shan-shan Li,
  • Zhuo Shi,
  • Jing Jing,
  • Ang Huang,
  • Yu-ming Guo,
  • Zhao-fang Bai,
  • Zheng-sheng Zou,
  • Xiao-he Xiao,
  • Jia-bo Wang,
  • Ming Niu,
  • Ming Niu

DOI
https://doi.org/10.3389/fmed.2020.592434
Journal volume & issue
Vol. 7

Abstract

Read online

Aim: The diagnosis of drug-induced liver injury (DILI) remains a challenge and the cases of Polygonum multiflorum Thunb. (PM) induced DILI (PM-DILI) have received much attention This study aimed to identify a simple and high-efficiency approach to PM-DILI diagnosis via metabolomics analysis.Methods: Plasma metabolites in 13 PM-DILI patients were profiled by liquid chromatography along with high-resolution mass spectrometry. Meanwhile, the metabolic characteristics of the PM-DILI were compared with that of autoimmune hepatitis (AIH), hepatitis B (HBV), and healthy volunteers.Results: Twenty-four metabolites were identified to present significantly different levels in PM-DILI patients compared with HBV and AIH groups. These metabolites were enriched into glucose, amino acids, and sphingolipids metabolisms. Among these essential metabolites, the ratios of P-cresol sulfate vs. phenylalanine and inosine vs. bilirubin were further selected using a stepwise decision tree to construct a classification model in order to differentiate PM-DILI from HBV and AIH. The model was highly effective with sensitivity of 92.3% and specificity of 88.9%.Conclusions: This study presents an integrated view of the metabolic features of PM-DILI induced by herbal medicine, and the four-metabolite decision tree technique imparts a potent tool in clinical diagnosis.

Keywords