BACKGROUND: Membranous nephropathy (MN) is one of the most common pathologies of the nephrotic syndrome. MN is closely associated with the autoimmune response but its molecular mechanism remains unclear. Bioinformatic network analysis can be used to identify disease-related hub genes. METHODS: The microarray data set GSE47183 of patients with MN containing 21 MN samples and 13 control samples that were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using the limma package. Thereafter, gene ontology (GO) enrichment was performed for DEGs using the clusterProfiler package. The protein-protein interaction (PPI) network was established through the Search Tool for the Retrieval of Interacting Genes database and visualized using Cytoscape. Finally, the hub genes were identified through the maximal clique centrality method. RESULT: A total of 642 DEGs were recognized, consisting of 458 upregulated genes and 184 downregulated genes. GO enrichment analysis indicates that DEGs for MN are mainly related to antigen processing and presentation. For the PPI network, we identified approximately nine hub genes. Considering data from the literature, we ultimately identified PSMB8 as a novel hub gene, which could play a significant role in the occurrence and development of MN. CONCLUSION: This study is the first to identify novel hub genes with transcriptome microarray data in MN using bioinformatics. The newly discovered hypothetical hub genes should be functionally tested to determine if they truly play an etiologic role in MN.
BACKGROUND:Membranous nephropathy (MN) is one of the most common pathologies of the nephrotic syndrome. MN is closely associated with the autoimmune response but its molecular mechanism remains unclear. Bioinformatic network analysis can be used to identify disease-related hub genes. METHODS: The microarray data set GSE47183 of patients with MN containing 21 MN samples and 13 control samples that were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using the limma package. Thereafter, gene ontology (GO) enrichment was performed for DEGs using the clusterProfiler package. The protein-protein interaction (PPI) network was established through the Search Tool for the Retrieval of Interacting Genes database and visualized using Cytoscape. Finally, the hub genes were identified through the maximal clique centrality method. RESULT: A total of 642 DEGs were recognized, consisting of 458 upregulated genes and 184 downregulated genes. GO enrichment analysis indicates that DEGs for MN are mainly related to antigen processing and presentation. For the PPI network, we identified approximately nine hub genes. Considering data from the literature, we ultimately identified PSMB8 as a novel hub gene, which could play a significant role in the occurrence and development of MN. CONCLUSION: This study is the first to identify novel hub genes with transcriptome microarray data in MN using bioinformatics. The newly discovered hypothetical hub genes should be functionally tested to determine if they truly play an etiologic role in MN.