Deciphering the therapeutic mechanisms of Xiao-Ke-An in treatment of type 2 diabetes in mice by a Fangjiomics approach
Abstract
Aim: Xiao-Ke-An (XKA) is a traditional Chinese medicine (TCM) formula for the treatment of type 2 diabetes (T2D), and the effective ingredients and their targets as well as the mechanisms of XKA remain to be elucidated. In this study we investigated the therapeutic mechanisms of XKA in the treatment of T2D in mice using a Fangjiomics approach.
Methods: KKAy mice feeding on a high-fat diet were used as models of T2D, and were orally treated with XKA (0.75 or 1.5 g·kg−1·d−1) for 32 d. Microarray mRNA expression data were obtained from the livers of the mice. Differentially expressed genes (DEGs) were identified by reverse rate analysis and ANOVA analysis. The compounds in XKA were identified by LC-MS analysis or collected from TCM databases. The relationships between the compounds and targets were established by combining the DEGs with information derived from mining literature or herb target databases. Relevant pathways were identified through a Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis using WebGestalt.
Results: The compound-target-pathway network based on compounds identified by LC-MS analysis (NCA) included 20 constituent compounds, 46 targets and 36 T2D-related pathways, whereas the compound-target-pathway network based on compounds collected from databases (NCD) consisted of 40 compounds, 68 targets and 21 pathways. In the treatment of T2D, XKA might act mainly by improving carbohydrate and lipid metabolism, as well as ameliorating insulin resistance, inflammation and diabetic vascular complications.
Conclusion: The network-based approach reveals complex therapeutic mechanisms of XKA in the treatment of T2D in mice that involve numerous compounds, targets, and signaling pathways.
Keywords:
type 2 diabetes; Xiao-Ke-An; traditional Chinese medicine; network pharmacology; Fangjiomics
Methods: KKAy mice feeding on a high-fat diet were used as models of T2D, and were orally treated with XKA (0.75 or 1.5 g·kg−1·d−1) for 32 d. Microarray mRNA expression data were obtained from the livers of the mice. Differentially expressed genes (DEGs) were identified by reverse rate analysis and ANOVA analysis. The compounds in XKA were identified by LC-MS analysis or collected from TCM databases. The relationships between the compounds and targets were established by combining the DEGs with information derived from mining literature or herb target databases. Relevant pathways were identified through a Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis using WebGestalt.
Results: The compound-target-pathway network based on compounds identified by LC-MS analysis (NCA) included 20 constituent compounds, 46 targets and 36 T2D-related pathways, whereas the compound-target-pathway network based on compounds collected from databases (NCD) consisted of 40 compounds, 68 targets and 21 pathways. In the treatment of T2D, XKA might act mainly by improving carbohydrate and lipid metabolism, as well as ameliorating insulin resistance, inflammation and diabetic vascular complications.
Conclusion: The network-based approach reveals complex therapeutic mechanisms of XKA in the treatment of T2D in mice that involve numerous compounds, targets, and signaling pathways.