Mining and analysis of hub genes in hepatic fibrosis progression of non-alcoholic fatty liver disease based on bioinformatics
Objective To explore the hub genes and potential pathogenesis of hepatic fibrosis in non-alcoholic fatty liver disease based on bioinformatics analysis.Methods Dataset GSE49541 was obtained from GEO database.Differentially expressed genes(DEGs)were screened out in limma package,and their gene ontology(GO)function annotation and Kyoto encyclopedia of genes and genomes(KEGG)pathway analysis were performed.The protein protein interaction network was constructed by STRING database on DEGs,and key genes were screened by Cytoscape.The co-expression network and function of hub genes were analyzed using Gene MANIA.Finally,drug prediction of key genes was performed based on drug signature database.Results In advanced stage NAFLD and mild NAFLD after comparison,there were a total of 65 DEGs,with 58 genes upregulated and 7 genes downregulated.GO functional analysis highlights that the molecular functions of these 65 DEGs were primarily concentrated in extracellular matrix structure components.KEGG pathway analysis shows that DEGs were mainly associated with pathways involving interactions with extracellular matrix receptors.Cytoscape analysis has identified ten key genes,namely COL1A1,COL3A1,COL4A1,COL1A2,COL14A1,FBN1,LUM,THBS1,THBS2,and SPP1.Gene MANIA suggests a highly interconnected co-expression and interaction network among these key genes,related to functions such as extracellular matrix structure components.Finally,drug prediction analysis reveals that Retinoic Acid and Progesterone are the drugs most enriched with the highest number of key genes.Conclusion Ten hub genes associated with NAFLD fibrosis progression were identified by bioinformatics which could be biomarkers for its biological monitoring and providing clues for molecular targeted therapy.
万方数据
维普
