Characterisation of key biomarkers in diabetic ulcers via systems bioinformatics

Abstract

Diabetic ulcers (DUs) are characterised by a high incidence and disability rate.However, its pathogenesis remains elusive. Thus, a deep understanding of the underlying mechanisms for the pathogenesis of DUs has vital implications. The weighted gene co-expression network analysis was performed on the main data from the Gene Expression Omnibus database. Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were adopted to analyse the potential biological function of the most relevant module. Furthermore, we utilised CytoHubba and protein-protein interaction network to identify the hub genes.Finally, the hub genes were validated by animal experiments in diabetic ulcer mice models. The expression of genes from the turquoise module was found to be strongly related to DUs. GO terms, KEGG analysis showed that biological functions are closely related to immune response. The hub genes included IFI35, IFIT2, MX2, OASL, RSAD2, and XAF1, which were higher in wounds of DUs mice than that in normal lesions. Additionally, we also demonstrated that the expression of hub genes was correlated with the immune response using immune checkpoint,

Prediction of immune molecules activity during burn wound healing among elderly patients: in-silico analyses-Experimental research

“…Next, applying WGCNA illustrated the heat map of found total genes, and essential modules were obtained. Further, The module’s 100 critical genes with the highest score in terms of mortality were selected 84 and applied for network illustration and “enrich r” analysis to investigate immunity function. Finally, by using Gephi software, the network illustrated, and degree greater than 10 and “betweenness and centrality” greater than 30 were considered 78 .…”