Identification and Analysis of Prognosis-related Core Genes in Sepsis Based on Bioinformatics
Objective To identify the potential core genes affecting the prognosis of sepsis based on bioinformatics.Methods The Gene Expression Omnibus(GEO)database was used to screen the gene expression datasets GSE54514 and GSE65682 from septic pa-tients.Key genes related to the prognosis of sepsis were screened by weighted gene co-expression network analysis(WGCNA)and Venn analysis.the Metascape database,the RcisTarget package,and the CIBERSORT algorithm were used to perform gene function enrichment analysis,transcription factor enrichment analysis,and immune infiltration analysis.The dataset GSE5772 was selected for validation to screen core genes associated with the prognosis of sepsis,and the survival analysis was performed by the Kaplan-Meier method.Results Co-expression network analysis was performed on the datasets GSE54514 and GSE65682,respectively,and the"green"and"brown"modules with the highest prognostic correlation to sepsis were selected.The intersection of genes in the two modules was taken,and 20 key genes were obtained by Venn analysis.These key genes were mainly enriched into the regulation of cell morphology,monocyte migration,and other pathways.Enrichment analysis of the transcription factor showed that the transcription factor ZNF148 might be one of the main regulators of the gene set.Further verification of data set GSE5772 revealed that the genes FGD3,MBP,MSN,RNF130 and SETD1B were significantly low expressed in septic patients(P＜0.05).Immune infiltration analysis showed that these five core genes were closely related to the content of immune cells.The expressions of FGD3,MSN and RNF130 were correlated with the survival rate of septic pa-tients(P＜0.05).Conclusion Five core genes associated with the prognosis of sepsis were screened via bioinformatics methods,which are closely related to immune cells.The genes FGD3,MSN and RNF130 may be important predictors for the prognosis of sepsis.
万方数据
维普
