A novel strategy based on targeted cellular metabolomics for quantitatively evaluating anti-aging effect and...

The complexity of ingredients in traditional Chinese medicine (TCM) makes it challenging to clarify its efficacy in an acceptable and scientific approach. The present study was aimed to use quantification results from targeted cellular metabolomics to evaluate anti-aging efficacy of a famous Chinese medicine formula, Erzhi Wan (EZW), and screen possible effective extracts, depending on the developed strategy integrating multivariate receiver operating characteristic (ROC) curve and analytic hierarchy process (AHP). In this study, senescent NRK cells induced by D-galactose were treated with drug-containing serum of EZW and four kinds of extracts (petroleum ether, ethyl acetate, butanol and water). Intermediates of two major metabolic pathways for energy synthesis, tricarboxylic acid (TCA) cycle and glycolysis, were accurately quantified by GC-MS/MS to identify discriminate metabolites for clarifying therapeutic mechanism of EZW based on multivariate statistical analysis. Senescent and non-senescent cells were successfully distinguished using these metabolites by ROC curve analysis. Next, these metabolites were used as evaluation indexes to quantitatively reflect different effect of EZW and its extracts, according to the role of them in distinguishing groups and in conjunction with AHP. In vitro detection of senescence-associated β-galactosidase (SA-β-gal) activity was used to verify the reliability of evaluation results. The reversal after treatment of drug-containing serum of EZW and extracts was observed, and the petroleum ether extract might be the potential active extract responsible for the major anti-aging effect of EZW, which was in agreement with in vitro experiments. Altogether, metabolomics was a powerful approach for evaluation efficacy and elucidation action mechanisms of TCM. The integrated evaluation strategy in this paper with properties of high practicality, feasibility and effectivity was expected to provide a new insight into comprehensive and quantitative efficacy evaluation.