Evaluation of the mechanism of Danggui-Shaoyao-San in regulating the metabolome of nephrotic syndrome based on urinary metabonomics and bioinformatics approaches.

ETHNOPHARMACOLOGICAL RELEVANCE

Danggui-Shaoyao-San (DSS), a well-known classic Traditional Chinese medicine (TCM) formula for enhancing Qi (vital energy and spirit), invigorating blood circulation and promoting diuresis, has been widely used in the treatment of nephrotic syndrome (NS). Previously, we have reported some protective effects of DSS against NS, but the in-depth mechanisms remain unclear.

AIM OF THE STUDY

In this study, an ultra performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (UPLC-Q/TOF-MS)-based urinary metabonomics coupled with bioinformatics method was employed to evaluate the mechanisms of DSS in treating NS from the perspective of metabolism.

MATERIALS AND METHODS

The rat models of NS were established using adriamycin injection. The regulative effects of DSS on NS in rats were first assessed by non-targeted metabonomics, which was based on UPLC-Q/TOF-MS. A series of target prediction models were used to predict the target of components identified in DSS and potential metabolites in NS, combined with the experimental results of metabonomics, to construct the biological network.

RESULTS

A total of 16 potential metabolites were screened in NS, of which 13 were significantly regulated by DSS. Metabolic pathway analysis showed that the therapeutic effect of DSS on NS was mainly involved in regulating the amino acid metabolism and energy metabolism. The component-target-metabolites-pathway network revealed 29 targets associated with metabolites that were linked to 27 components of DSS. Bioinformatics analysis showed that the potential targets have various molecular functions (especially serine-type endopeptidase inhibitor activity) and biological process (such as positive regulation of peptidyl-tyrosine phosphorylation or autophosphorylation).

CONCLUSIONS

The regulation of disrupted metabolic pathways and the relative targets may be the mechanism for DSS in the treatment of NS. Notably, metabonomics coupled with bioinformatics would be useful to explore the mechanism of DSS against NS and provide better insights on DSS for clinical use.