Bioinformatics analysis of differentially expressed genes in diabetic foot based on the GEO gene dataset

DOI: 10.12201/bmr.202502.00048

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  Abstract: This study aims to explore the crucial genes associated with the development and progression of diabetic foot by conducting bioinformatics analysis on the GSE143735 dataset within the GEO (Gene Expression Omnibus) database.Methods The GSE143735 mRNA gene chip dataset underwent gene transcription profile analysis. The patients in the dataset were divided into two groups according to whether there was diabetes foot ulcer, namely, diabetes foot ulcer group (DFU) and diabetes foot ulcer without diabetes (DS). The mRNA expression data of the two groups were analyzed for DEGs using online tool GEO2R and a volcano plot was subsequently generated. GO analysis and KEGG pathway analysis were carried out using the DAVID database, and GO and KEGG enrichment analysis plots were created. The identified DEGs were then input into the String public database for further analysis. The data regarding the interactions between target genes and their counterparts were downloaded from the String public database. A protein - protein interaction network diagram was constructed using Cytoscape, and core genes were screened out.Results A total of 706 differentially expressed genes were identified in the DFU and DS groups. Among them, 470 genes were up - regulated, while 236 were down - regulated. The results of GO analysis indicated that the DEGs were primarily concentrated in cellular components such as extracellular fluid, nucleosome, collagen - containing extracellular matrix, and exosome. The main functions of these DEGs as revealed by GO analysis, included DNA binding, protein heterodimer activation, chromatin structure formation, enzyme binding, nucleosome DNA binding, cytokine activation, microtubule binding, extracellular matrix structure composition, structural molecule activation, and serine inhibitor enzyme activation. The biological processes in the GO analysis of the DEGs mainly involved nucleosome assembly, chromatin organization, keratinization, telomere organization, positive regulation of gene expression, positive regulation of cell population proliferation, protein localization in CENP - A - containing chromatin, heterochromatin formation, antibacterial humoral immunity, and antibacterial humoral immune response mediated by antibacterial peptides. The KEGG pathway analysis of the DEGs mainly covered alcoholism, SLE, formation of neutrophil extracellular traps, viral carcinogenesis, transcriptional dysregulation in cancer, neuroactive ligand - receptor interaction, shigellosis, necrotizing blepharoptosis, ATP - dependent chromatin remodeling, and activation of chemical carcinogenesis receptors. From the protein - protein interaction network, ten core genes, namely H2BC14, H3C14, H2BC17, H4C6, H2BC9, H3C1, H2BC3, H3C12, H3C13, and H2AC18, were successfully screened out. According to the volcano plot results, these genes were all expressed at low levels in the DFU group.Conclusion The low expression of H2BC14, H3C14, H2BC17, H4C6, H2BC9, H3C1, H2BC3, H3C12, H3C13, and H2AC18 genes may serve as predictive factors for the occurrence of diabetic foot ulcers in diabetic patients. The risk of diabetic foot in these patients can be predicted by detecting the expression levels of these genes in diabetic patients.

  Key words: diabetic foot; GEO database; differentially expressed genes; bioinformatics analysis

  Submit time: 24 February 2025

  Copyright: The copyright holder for this preprint is the author/funder, who has granted biomedRxiv a license to display the preprint in perpetuity.
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