Identification of autophagy-related genes in diabetic foot ulcer based on bioinformatic analysis.
Dong-Ling LiXin-Yi DingJuan LongQiao-Ling HeQing-Xiang ZengNa LuMeng-Chen ZouPublished in: International wound journal (2023)
Diabetic foot ulcer (DFU) complications involve autophagy dysregulation. This study aimed to identify autophagy-related bioindicators in DFU. Differentially expressed genes (DEGs) between DFU and healthy samples were analysed from the Gene Expression Omnibus (GEO) datasets, GSE7014 and GSE29221. The roles of autophagy-related DEGs were investigated using protein-protein interaction (PPI) networks, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, Gene Ontology (GO) enrichment, and Gene Set Enrichment Analysis (GSEA). Immune cell infiltration's correlation with these DEGs was also assessed. From the Human Autophagy Database (HADB), 232 autophagy-related genes (ARGs) were identified, with an intersection of 17 key DEGs between GSE7014 and GSE29221. These genes are involved in pathways like autophagy-animal, NOD-like receptor signalling, and apoptosis. In the protein network, epidermal growth factor receptor (EGFR) and phosphatase and tensin homologue (PTEN) showed significant interactions with ARGs. Survival analysis indicated the prognostic importance of calpain 2 (CAPN2), integrin subunit beta 1 (ITGB1), and vesicle-associated membrane protein 3 (VAMP3). Lower immune scores were observed in the type 2 diabetes mellitus (DM2) group than in controls. Autophagy and ARGs significantly influence DFU pathophysiology.
Keyphrases
- endoplasmic reticulum stress
- cell death
- oxidative stress
- signaling pathway
- epidermal growth factor receptor
- protein protein
- gene expression
- genome wide
- tyrosine kinase
- bioinformatics analysis
- small molecule
- cell cycle arrest
- small cell lung cancer
- dna methylation
- endothelial cells
- metabolic syndrome
- antibiotic resistance genes
- pi k akt
- mass spectrometry
- genome wide analysis
- insulin resistance
- risk factors
- advanced non small cell lung cancer
- copy number
- microbial community
- rna seq
- high resolution
- weight loss