Analysis of ferroptosis-related genes in rheumatoid arthritis:a study based on bioinformatics and network pharmacology
Objective To analyze the ferroptosis-related genes in rheumatoid arthritis (RA) based on bioinformatics and network pharmacology.Methods RA datasets were obtained from the Gene Expression Omnibus database,the dataset of ferroptosis-related genes was downloaded from FerrDb database.Differentially expressed genes between RA patients and healthy subjects were analysed,and ferroptosis-related differentially expressed genes (FRDEGs) were obtained.Gene ontology functional enrichment analysis,Kyoto encyclopedia of genes and genomes signalling pathway enrichment analysis and protein-protein interaction network (PPI) analysis were performed on FRDEGs.Key genes were screened using the CytoHubba plugin.The diagnostic ability of key genes to predict RA was evaluated with ROC curve.The relevant Chinese medicines were predicted using CoreMine online database,and the target proteins of key genes were molecularly docked with the active ingredients of Chinese medicines.Results A total of 18 FRDEGs were screened out,which were mainly enriched in cell proliferation and immune-related response pathways.PPI analysis obtained 7 key genes,among which cyclin-dependent kinase inhibitor 1A (CDKN1A) gene,dual-specificity phosphatase 1 (DUSP1) gene and mitogen-activated protein kinase (MAPK) 8,had AUCs of 0.875,0.812,and 0.804,respectively.The molecular docking results showed that the major components leguminol,β-sitosterol and (4R)-4-pentanoic acids from Turmeric,Scutellaria baicalensis and Ganoderma lucidum were bound stably to the key genes,with β-sitosterol having the lowest docking binding energy to CDKNA1.Conclusion Three potential key biomarkers and therapeutic targets for the treatment of RA,including CDKN1A,DUSP1 and MAPK8 have been identified based on bioinformatics and network pharmacology analysis,which provides reference for subsequent studies on the mechanism of ferroptosis-related genes in RA.
万方数据
维普
