An integrated strategy for ascertaining quality marker of Schisandra chinensis (Turcz.) Baill based on correlation analysis between depression-related monoaminergic metabolites and chemical components profiling

Traditional Chinese Medicines (TCMs) have been widely used in orient countries for thousands of years, while their inconsistent quality and therapy issues have become increasingly serious as a result of the absence of effective methods for quality control. Therefore, it is necessary to develop a novel and specific evaluation system for TCMs’ quality involved with not only composition but also bioactivity. In this study, we used Schisandra chinensis (Turcz.) Baill as an example and developed a novel integrated approach involved with various chemical analysis and data processing methods to explore its quality marker (Q-marker) underlying its anti-depressive effects. First, six bioactive lignans were identified and semi-quantified in rat brain samples via high resolution mass spectrometry. Then, the bioinformation analysis showed that all the six bioactive components could modulate various diseases relative to noradrenergic, dopaminergic and serotonergic pathways. Thus, the monoaminergic metabolites contained in these three pathways were selected to screen potential biomarkers of depression treated by S. chinensis based on target metabolomics using a rapid HPLC-MS/MS method. Finally, the correlation analysis between the six components and potential biomarkers was employed to uncover the Q-markers of S. chinensis. It is suggested that schisandrol A, schisandrin A, schisandrin C and gomisin N could be determined as Q-markers for S. chinensis. Thus, the integrated approach describing here for discovering Q-markers was expected to offer an alternative quality assessment strategy of herbal medicines for the first time.