Network Analysis of Anti-inflammatory Phytochemicals and Omics Data for Rheumatoid Arthritis.

Abstract

Rheumatoid arthritis (RA) is an inflammatory autoimmune disease that affects the synovial joints. Nearly 1.6 billion patients are affected by RA worldwide and the incidence of RA is about 0.5 to 1%. Recent studies reveal that immune cell responses and secretion of inflammatory factors are important for the control of RA. In this study, a set of 402 phytochemicals with anti-inflammatory properties and 16 target proteins related to anti-inflammatory diseases were identified from the literature and they were subjected to network analysis. The protein-protein interaction (PPI) network was constructed using STRING (Search Tool for the Retrieval of Interacting Genes database) database. Visualization of the target gene-phytochemical network and its protein-protein interaction network was conducted using Cytoscape and further analyzed using MCODE (Molecular Complex Detection). The gene ontology and KEGG pathway analysis was performed using DAVID tool. Our results from the network approach indicate that the phytochemicals such as Withanolide, Diosgenin, and Butulin could act as potential substitute for anti-inflammatory drugs, including DMARDs. Genes such as Mitogen-activated protein kinase (MAPK) and Interleukin were found as hub genes and acted as best inhibitors for the target protein pathways. Curcumin, Catechin was also found to be involved in various signaling pathways such as NF-kappa B signaling pathway, ErbB signaling pathway and acted as the best inhibitor along with other candidate phytochemicals. In the current study, we were able to identify Withanolide, Diosgenin, and Butulin as potential anti-inflammatory phytochemicals and determine their association with key pathways involved in RA through network analysis. We hypothesized that natural compounds could significantly contribute to the reduction of dosage, improve the treatment and act as a therapeutic agent for more economical and safer treatment of RA.