Simultaneous Quantitative Analysis of Q-Marker with One Single Reference in Glycyrrhiza uralensis Fisch

J Chromatogr Sci. 2020 Jun 5;58(6):511-519. doi: 10.1093/chromsci/bmaa015.

Abstract

In traditional Chinese medicine (TCM) studies, it is difficult to choose evaluation markers for the strict quality control of herbs. A high performance liquid chromatography coupled with metabolomics for simultaneous quantitative analysis of quality markers (Q-markers) in Glycyrrhiza uralensis Fisch was established, which could not only ensure the quality and batch-to-batch consistency of TCMs, but also achieve a quantitative analysis of multi-components by the single reference standard. Based on the construction of chromatographic profiles by high performance liquid chromatography (HPLC) and HPLC-Q-Exactive/MS methods, different multivariate analyses were employed. Seven quantitative indices were selected as the Q-markers, and a reliable quantification method was established. The quantitative method was acceptable with good linearity with correlation coefficients >0.9993 and satisfactory repeatability (relative standard deviation (RSD) < 0.05%), precision (RSD < 0.24%), reproducibility (RSD < 0.97%), stability (RSD < 2.52%) and recoveries (96.96%-98.52%, RSD < 3.24%), and no significant differences were observed between the external standard method and the new method as determined by calculating standard method difference. Overall, the study suggests that the simultaneous quantitative analysis of main Q-marker in G. uralensis Fisch with one single marker can be considered good quality criteria for performing quality control of G. uralensis Fisch.

MeSH terms

  • Biomarkers / analysis
  • Chromatography, High Pressure Liquid / methods
  • Drugs, Chinese Herbal* / chemistry
  • Drugs, Chinese Herbal* / standards
  • Flavanones / analysis
  • Glucosides / analysis
  • Glycyrrhiza uralensis* / chemistry
  • Glycyrrhiza uralensis* / metabolism
  • Linear Models
  • Mass Spectrometry / methods
  • Medicine, Chinese Traditional
  • Metabolomics
  • Quality Control
  • Reproducibility of Results
  • Sensitivity and Specificity

Substances

  • Biomarkers
  • Drugs, Chinese Herbal
  • Flavanones
  • Glucosides