Metabolic profiling of the traditional Chinese medicine formulation Yu Ping Feng San for the identification of constituents relevant for effects on expression of TNF-α, IFN-γ, IL-1β and IL-4 in U937 cells

Nikles Stefanie, Monschein Marlene, Zou Huiqin, Liu Yong, Xiaojuan He, Fan Danping, Aiping LYU, Yu Kate, Isaac Giorgis, Bauer Rudolf*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

31 Citations (Scopus)

Abstract

Yu Ping Feng San (YPFS) is a classical TCM formulation which has been traditionally used for treatment of immune system related diseases such as chronic bronchitis, allergic rhinitis and asthma. The formula is a mixture of Radix Saposhnikoviae (Fangfeng), Radix Astragali (Huangqi), and Rhizoma Atractylodis macrocephalae (Baizhu). TLC- and LC-DAD-ESI-MS/MS methods have been developed for the analysis of the metabolic profiles of the single herbs and of the formula. Decoctions and ASE extracts were analyzed in order to trace components of the individual herbs in YPFS. Nine constituents of Radix Saposhnikoviae, ten constituents of Radix Astragali and five constituents of Rhizoma Atractylodis macrocephalae have been assigned in the chemical profiles of the formula, which now allow the standardisation of YPFS. The pharmacological testing showed that all extracts significantly inhibited expression of TNF-α, IFN-γ, and IL-1β in U937 cells, while the inhibition of IL-4 was consistently low. Compared to conventional analyses which are focused on a limited set of compounds, metabolomics approaches, together with novel data processing tools, enable a more holistic comparison of the herbal extracts. In order to identify the constituents which are relevant for the immunomodulatory effects of the formula, metabolomics studies (PCA, OPLS-DA) have been performed using UPLC/QTOF MS data.

Original languageEnglish
Pages (from-to)219-229
Number of pages11
JournalJournal of Pharmaceutical and Biomedical Analysis
Volume145
DOIs
Publication statusPublished - 25 Oct 2017

Scopus Subject Areas

  • Analytical Chemistry
  • Pharmaceutical Science
  • Drug Discovery
  • Spectroscopy
  • Clinical Biochemistry

User-Defined Keywords

  • Astragalus mongholicus
  • Atractylodes macrocephala
  • HPLC
  • Metabolic profiling
  • Metabolomics
  • OPLS-DA
  • PCA
  • Saposhnikovia divaricata
  • TCM
  • TLC
  • Yu Ping Feng San

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