Biomedicine

Abstract

Introduction and Aim: Diabetic foot ulcers (DFUs) are a common and debilitating diabetic consequence leading to lower-limb amputations, long-term disability, and reduced lifespan. Hence, the current research aims to find out how differently expressed genes (DEGs) affect the DFU.
Materials and Methods: Bioinformatics analysis was used to evaluate DEGs using the GSE132187 dataset of the NCBI-GEO database, which contained samples from three hyperglycemic and three normoglycemic macrophage-like cell lines. Gene Ontology (GO) and KEGG pathway enrichment analysis was used to study how genes are classified into preset bins based on their functional properties after DEGs were discovered. A network of protein-protein interaction (PPI) was created and five topological characteristics such as degree, stress, closeness centrality, betweenness centrality, and radiality were evaluated to uncover hub DEGs in DFU.
Results: We found 547 DEGs using the GSE132187 dataset, comprising 79 upregulated DEGs and 468 downregulated DEGs. In total, the PPI network included 434 nodes and 1724 edges. The giant network uncovered six modules that are significantly enriched in biological processes like regulation of positive JNK cascade, positive interferon-gamma production and negative cell proliferation, cellular response to zinc ion and lipopolysaccharide, wound healing, and inflammatory response.
Conclusion: Bioinformatics analysis revealed the major differentially expressed hub-genes implicated in DFUs. These findings suggest that these genes could be exploited as DFU prognostic, diagnostic, or therapeutic targets.