Therapeutic Effects of Naringin in Rheumatoid Arthritis: Network Pharmacology and Experimental Validation

Abstract

Rheumatoid arthritis is a chronic autoimmune disease characterized by persistent hyperplasia of the synovial membrane and progressive erosion of articular cartilage. Disequilibrium between the proliferation and death of RA fibroblast-like synoviocytes (RA-FLSs) is the critical factor in progression of RA. Naringin has been reported to exert anti-inflammatory and antioxidant effect in acute and chronic animal models of RA. However, the therapeutic effect and underlying mechanisms of naringin in human RA-FLS remain unclear. Based on network pharmacology, the corresponding targets of naringin were identified using SwissTargetPrediction database, STITCH database, and Comparative Toxicogenomics Database. Deferentially expressed genes (DEGs) in RA were obtained from the GEO database. The protein–protein interaction (PPI) networks of intersected targets were constructed using the STRING database and visualized using Cytoscape. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed, and the pathways directly related to pathogenesis of RA were integrated manually. Further, in vitro studies were carried out based on network pharmacology. 99 target genes were intersected between targets of naringin and DEGs. The PPI network and topological analysis indicated that IL-6, MAPK8, MMP-9, TNF, and MAPK1 shared the highest centrality among all. GO analysis and KEGG analysis indicated that target genes were mostly enriched in (hsa05200) pathways in cancer, (hsa05161) hepatitis B, (hsa04380) osteoclast differentiation, (hsa04151) PI3K-Akt signaling pathway, and (hsa05142) Chagas disease (American trypanosomiasis). In vitro studies revealed that naringin exposure was found to promote apoptosis of RA-FLS, increased the activation of caspase-3, and increased the ratio of Bax/Bcl-2 in a dose-dependent manner. Furthermore, treatment of naringin attenuated the production of inflammatory cytokines and matrix metalloproteinases (MMPs) in TNF-ɑ–induced RA-FLS. Moreover, treatment of naringin inhibited the phosphorylation of Akt and ERK in RA-FLS. Network pharmacology provides a predicative strategy to investigate the therapeutic effects and mechanisms of herbs and compounds. Naringin inhibits inflammation and MMPs production and promotes apoptosis in RA-FLS via PI3K/Akt and MAPK/ERK signaling pathways.

Exploring the Therapeutic Mechanism of Tingli Dazao Xiefei Decoction on Heart Failure Based on Network Pharmacology and Experimental Study

“…MAPK1, also known as ERK, regulates Bcl-2 expression and activates the caspase cascade. Several studies have revealed that the MAPK/ERK signaling pathway regulates cell differentiation and apoptosis and participates in the process of myocardial remodeling [ 55 ]. Wohlschlaeger et al confirmed that the levels of P-Akt and P-ERK in the myocardium of patients with HF increased.…”

Bioinformatics Analysis Identified the Hub Genes, mRNA–miRNA–lncRNA Axis, and Signaling Pathways Involved in Rheumatoid Arthritis Pathogenesis

“… 18 In the present study, the limma package of R was used to identify differentially expressed genes in RA synovial tissue and normal synovial tissue in GSE1919 and GSE77298 datasets. 19 Screening conditions were |log(FC)| ≥ 1 and adj. p val < 0.05.…”

“… 26 Cytoscape visualizes PPI networks. 19 Molecular complex detection (MCODE), a plugin for Cytoscape, detects densely connected regions in large PPI networks representing molecular complexes. 27 The method employs vertex weighting based on local neighborhood densities, which allows for fine-tuning of clusters of interest without considering the rest of the network, and examines cluster interconnections associated with protein networks.…”

“… 36 The “limma” package of R was used to perform differential analysis of the GSE128813 dataset to obtain DEGs and differentially expressed lncRNAs (DElncRNAs) of RA synovial tissue and normal synovial tissue. 19 The DEGs and DElncRNAs obtained from GSE128813 intersected with the target lncRNA predicted by starBase. The mRNA–miRNA–lncRNA axis related to RA pathogenesis was determined based on the intersection of lncRNAs and their corresponding miRNAs and mRNAs.…”

“…The mRNA–miRNA–lncRNA axis related to RA pathogenesis was determined based on the intersection of lncRNAs and their corresponding miRNAs and mRNAs. 19 …”