Therapeutic Role of Curcumin in Diabetes: An Analysis Based on Bioinformatic Findings

Abstract

Background: Diabetes is an increasingly prevalent global disease caused by the impairment in insulin production or insulin function. Diabetes in the long term causes both microvascular and macrovascular complications that may result in retinopathy, nephropathy, neuropathy, peripheral arterial disease, atherosclerotic cardiovascular disease, and cerebrovascular disease. Considerable effort has been expended looking at the numerous genes and pathways to explain the mechanisms leading to diabetes-related complications. Curcumin is a traditional medicine with several properties such as being antioxidant, anti-inflammatory, anti-cancer, and anti-microbial, which may have utility for treating diabetes complications. This study, based on the system biology approach, aimed to investigate the effect of curcumin on critical genes and pathways related to diabetes. Methods: We first searched interactions of curcumin in three different databases, including STITCH, TTD, and DGIdb. Subsequently, we investigated the critical curated protein targets for diabetes on the OMIM and DisGeNET databases. To find important clustering groups (MCODE) and critical hub genes in the network of diseases, we created a PPI network for all proteins obtained for diabetes with the aid of a string database and Cytoscape software. Next, we investigated the possible interactions of curcumin on diabetes-related genes using Venn diagrams. Furthermore, the impact of curcumin on the top scores of modular clusters was analysed. Finally, we conducted biological process and pathway enrichment analysis using Gene Ontology (GO) and KEGG based on the enrichR web server. Results: We acquired 417 genes associated with diabetes, and their constructed PPI network contained 298 nodes and 1651 edges. Next, the analysis of centralities in the PPI network indicated 15 genes with the highest centralities. Additionally, MCODE analysis identified three modular clusters, which highest score cluster (MCODE 1) comprises 19 nodes and 92 edges with 10.22 scores. Screening curcumin interactions in the databases identified 158 protein targets. A Venn diagram of genes related to diabetes and the protein targets of curcumin showed 35 shared proteins, which observed that curcumin could strongly interact with ten of the hub genes. Moreover, we demonstrated that curcumin has the highest interaction with MCODE1 among all MCODs. Several significant biological pathways in KEGG enrichment associated with 35 shared included the AGE-RAGE signaling pathway in diabetic complications, HIF-1 signaling pathway, PI3K-Akt signaling pathway, TNF signaling, and JAK-STAT signaling pathway. The biological processes of GO analysis were involved with the cellular response to cytokine stimulus, the cytokine-mediated signaling pathway, positive regulation of intracellular signal transduction and cytokine production in the inflammatory response. Conclusion: Curcumin targeted several important genes involved in diabetes, supporting the previous research suggesting that it may have utility as a therapeutic agent in diabetes.

Effect of Curcumin on Attenuation of Liver Cirrhosis via Genes/Proteins and Pathways: A System Pharmacology Study

“…However, different genes and pathways are related to inflammation and fibrosis such as tumor necrosis factor (TNF), interleukin 17 A (IL-17 A), interleukin 1 beta (IL-1β), interleukin 6 (IL-6), transforming growth factor beta (TGF-β), phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway, and toll-like receptor 4 (TLR4) mediated activation of the nuclear transcription factor κB (NF-κB) signaling pathway that are the targets of curcumin. In this case, a bioinformatics study was designed to determine curcumin’s possible effect on liver cirrhosis [ 13 , 14 , 15 , 16 ].…”

Identification of Comorbidities, Genomic Associations, and Molecular Mechanisms for COVID‐19 Using Bioinformatics Approaches

“…The ontology “Response to lipopolysaccharide” is involved in hypertension [ 75 ]. Gene ontology, “Cytokine-mediated signaling pathway,” “Neutrophil degranulation,” and “Neutrophil activation involved in immune response,” are associated with and impact diabetes [ 76 – 78 ]. The “Extracellular matrix organization” as well as “Extracellular structure organization” ontologies have implications for the pathogenesis of obesity and metabolic dysfunction [ 79 ].…”

Lactobacillus brevis alleviates the progress of hepatocellular carcinoma and type 2 diabetes in mice model via interplay of gut microflora, bile acid and NOTCH 1 signaling

“…GM-associated and BA-associated genes were manually curated from the previous reports ( 15 , 16 ). Diabetes-associated genes were downloaded from DisGeNET ( https://www.disgenet.org/search ) and the NCBI ( 17 ). Differentially expressed genes between normal and HCC tissues were analyzed using RNA-seq data from 3 sources (TCGA-LIHC ( 18 ), GSE112790 ( 19 ), GSE76427 ( 20 )) via R “limma” package ( 21 ).…”