Artificial neural network for screening characteristic genes of rheumatoid arthritis and analysis of immune cell infiltration
Objective:To identify characteristic genes of rheumatoid arthritis(RA)by artificial neural network and to analyze role of immune cells in RA related microenvironment.Methods:GSE1919 and GSE77298 chips were from GEO database.Two chips were combined and batch corrected using R language to obtain a new data set,and difference was analyzed.Metascape enrichment analysis and GO and KEGG enrichment analysis were conducted for differential expressed genes(DEGs)."randomForest"package in R software was used to screen characteristic genes of RA under random forest(RF)algorithm,and artificial neural network model was constructed according to gene score.Top 4 genes(HubGene)were extracted for subsequent analysis.Single sample gene set enrich-ment analysis(ssGSEA)was used to calculate abundance of immune cells in samples and carry out a series of correlation analysis.Results:Top 15 genes were selected as characteristic genes of RA through artificial neural network model:STAT1,RUNX3,AR,CDH11,LMO4,TIMP1,PLXNC1,CAP2,PRKAA2,VDR,SPP1,HCK,EPHB2,KCNAB1,ITGB7.STAT1,RUNX3 and CDH11 were up-regulated in RA synovial tissue,while AR was down-regulated in RA synovial tissue.Immune cell infiltration results showed that RA had the most significant correlation with activated CD4 T cells.Number of immune cells significantly related to RUNX3 was the largest.RUNX3 was significant positive correlated with activated B cells,activated CD4 T cells,activated CD8 T cells,central memory CD4+T cells,effector memory CD8 T cells,regulatory T cells,γδT cells and macrophages,while significant negative correlated with NK cells.Conclusion:Fifteen characteristic genes related to RA are identified through artificial neural net-work,among which STAT1,RUNX3,AR and CDH11 are top 4 genes.It emphasizes activation of CD4 T cells,regulatory T cells,γδT cells,macrophages,NK cells,activated B cells and other immune cells are important in pathogenesis of RA,providing new in-sights for diagnosis of RA and study of molecular mechanism of immune cells.
国家科技期刊平台
NSTL
万方数据
