Integrated network pharmacology analysis and serum metabolomics to reveal the cognitive improvement effect of Bushen Tiansui formula on Alzheimer's disease

Bushen Tiansui Formula (BSTSF) is a traditional Chinese medicine formula used clinically to treat Alzheimer's disease (AD) for many years. Previously, we have partially elucidated the mechanisms involved in the therapeutic effects of BSTSF on AD. However, the underlying mechanisms remain largely unclear. The aim of this study was to further investigate the therapeutic effects of BSTSF on AD using an integrated strategy of network pharmacology and serum metabolomics. The rat models of AD were established using Aβ 1–42 injection, and morris water maze test was used to evaluate the efficacy of BSTSF on AD. Next, network pharmacology analysis was applied to identify the active compounds and target genes, which might be responsible for the effect of BSTSF. Then, a metabolomics strategy has been developed to find the possible significant serum metabolites and metabolic pathway induced by BSTSF. Additionally, two parts of the results were integrated to confirm each other. The results of the network pharmacology analysis showed 37 compounds and 64 potential target genes related to the treatment of AD with BSTSF. The functional enrichment analysis indicated that the potential mechanism was mainly associated with the tumor necrosis factor signaling pathway and phosphatidylinositol 3 kinase/protein kinase B signaling pathway. Based on metabolomics, 78 differential endogenous metabolites were identified as potential biomarkers related to the BSTSF for treating AD. These metabolites were mainly involved in the relevant pathways of linoleic acid metabolism, α-linolenic acid metabolism, glycerophospholipid metabolism, tryptophan metabolism, and arginine and proline metabolism. These findings were partly consistent with the findings of the network pharmacology analysis. In conclusion, our results solidly supported and enhanced out current understanding of the therapeutic effects of BSTSF on AD. Meanwhile, our work revealed that the proposed network pharmacology-integrated metabolomics strategy was a powerful means for identifying active components and mechanisms contributing to the pharmacological effects of traditional Chinese medicine.