Network pharmacology-based identification of miRNA expression of Astragalus membranaceus in the treatment of diabetic nephropathy

Diabetic nephropathy (DN) is a common microvascular complication of diabetic patients, along with hypertension, hyperlipemia, proteinuria, edema, and other clinical manifestations. Astragalus membranaceus (AM) is a traditional Chinese medicine and has shown significant clinical efficacy against DN. However, the overall molecular mechanism of this therapeutic effect has not been entirely elucidated. Using network pharmacology, we aimed to identify the key active ingredients and potential pharmacological mechanisms of AM in treating DN and provide scientific evidence of its clinical efficacy. The active ingredients of AM were obtained from the traditional Chinese medicine systems pharmacology database, and the potential targets of AM were identified using the therapeutic target database. DN-related target genes were acquired from the Gene Expression Omnibus microarray dataset GSE1009 and 3 widely used databases-DisGeNET, GeneCards, and Comparative Toxicogenomics Database. The DN–AM common target protein interaction network was established by using the STRING database. Active ingredients candidate targets proteins networks were constructed using Cytoscape software for visualization. Additionally, gene ontology (GO) and Kyoto encyclopedia of genes and genomes pathway analyses were performed using the Database for Annotation, Visualization, and Integrated Discovery database. Target-regulating microRNAs (miRNAs) of these hub genes were obtained from the therapeutic target database, which could then be used for further identification of AM-regulated key miRNAs. A total of 17 active ingredients and 214 target proteins were screened from AM. 61 candidate co-expressed genes with therapeutic effects against DN were obtained and considered as potential therapeutic targets. GO and Kyoto encyclopedia of genes and genomes enrichment analysis showed that these genes were mainly involved in inflammatory response, angiogenesis, oxidative stress reaction, HIF signaling pathway, tumor necrosis factor signaling pathway, and VEGF signaling pathway. In all, 636 differentially expressed genes were identified between the DN patients and control group by using microarray data, GSE1009. Lastly, VEGFA, epidermal growth factor receptor, STAT1, and GJA1 were screened as hub genes. The relationships between miRNAs and hub genes were constructed, which showed that miR-302-3p, miR-372-3p, miR-373-3p, and miR-520-3p were regulated by VEGFA and epidermal growth factor receptor. Meanwhile, VEGFA also influenced miR-15-5p, miR-16-5p, miR-17-5p, miR-20-5p, miR-93-5p, miR-106-5p, miR-195-5p, miR-424-5p, miR-497-5p, and miR-519-3p. In addition, miR-1-3p and miR-206 were regulated by VEGFA and GJA1, and miR-23-3p was regulated by STAT1 and GJA1. To our knowledge, this study revealed for the first time the characteristic multiple components, multiple targets, and multiple pathways of AM that seem to be the underlying mechanisms of action of AM in the treatment of DN with respect to miRNAs. Private information from individuals will not be published. This systematic review also does not involve endangering participant rights. Ethical approval will not be required. The results may be published in a peer-reviewed journal or disseminated at relevant conferences.