Functional metabolomics discover pentose and glucuronate interconversion pathways as promising targets for Yang Huang syndrome treatment with Yinchenhao Tang

Yinchenhao Tang (YCHT), a classic traditional Chinese medicine (TCM) formulae, plays an important role in the treatment of Yang Huang syndrome (YHS). With the emergence of new biomarkers of YHS uncovered metabonomics, the underlying functional mechanisms are still not clear. Functional metabolomics...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:RSC advances 2018-01, Vol.8 (64), p.36831-36839
Hauptverfasser: Sun, Hui, Zhang, Ai-Hua, Song, Qi, Fang, Heng, Liu, Xing-Yuan, Su, Jing, Yang, Le, Yu, Meng-Die, Wang, Xi-Jun
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Yinchenhao Tang (YCHT), a classic traditional Chinese medicine (TCM) formulae, plays an important role in the treatment of Yang Huang syndrome (YHS). With the emergence of new biomarkers of YHS uncovered metabonomics, the underlying functional mechanisms are still not clear. Functional metabolomics aims at converting biomarkers derived from metabonomics into disease mechanisms. Here, an integrated non-target metabolomics and IPA strategy were used to investigate the YCHT intervention on YHS. Our metabolomics study has shown that the potential protective effect of YCHT on YHS mice leads to significant changes in the metabolic profile by modulating the biomarkers and regulating the metabolic disorders. Twenty two differential metabolite biomarkers and fifteen involved metabolic pathways were correlated with the regulation of YCHT treatment on YHS. Functional metabolomics identified a core biomarker, d-glucuronic acid in pentose and glucuronate interconversion pathways, which was directly related to the target prediction of UDP-glucuronosyltransferase 1A1 and eventually leaded to a series of disturbances. In conclusion, this study shows that functional metabolomics can discover metabolic pathways as promising targets.
ISSN:2046-2069
2046-2069
DOI:10.1039/c8ra06553e