Razi University

  Abstract Background and Objective: Type 2 diabetes mellitus (T2D) is one of the most important metabolic disorders and can lead to various complications, including diabetic retinopathy (DR). Given the essential role of protein homeostasis in normal cellular function and the association of abnormalities in protein folding, accumulation, degradation, and turnover with disease processes, investigating protein metabolism-related genes may provide insights into the molecular mechanisms shared between T2D and DR. The aim of this study was to identify and analyze protein metabolism-related genes and investigate their molecular and regulatory networks in T2D and DR. Methods: In this study, gene expression data from two datasets, GSE25724 and GSE228900, obtained from the Gene Expression Omnibus (GEO) database, were analyzed. Following differential gene expression analysis, protein metabolism-related genes were identified, and overlapping genes between these genes and the differentially expressed genes were extracted. Protein–protein interaction (PPI) networks were constructed using the STRING database and Cytoscape software, and hub genes were identified using the CytoHubba plugin. Regulatory networks involving transcription factors (TFs), microRNAs (miRNAs), and long non-coding RNAs (lncRNAs) were also investigated. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to determine the biological functions and pathways associated with the identified genes. Results: In the GSE25724 dataset related to T2D, a total of 3,248 differentially expressed genes (DEGs) were identified, including 1,041 upregulated and 2,207 downregulated genes. Among the protein metabolism-related genes, 203 genes overlapped with the DEGs, including 38 upregulated and 165 downregulated genes. In the GSE228900 dataset related to DR, 2,621 DEGs were identified, including 1,066 upregulated and 1,555 downregulated genes. Among the protein metabolism-related genes, 122 overlapping genes were identified, including 53 upregulated and 69 downregulated genes. PPI network analysis and topological evaluation using 12 CytoHubba algorithms resulted in the identification of 10 hub genes in T2D and 11 hub genes in DR. In the T2D network, CUL1, CUL3, SKP1, and RBX1, which are involved in E3 ubiquitin ligase complexes, were among the prominent hub genes. PTEN and EGFR were also identified as important network genes. In DR, proteasome-related genes, including PSMA4, PSMD1, PSMD6, PSMD14, and PSME3, were among the prominent hub genes. Regulatory network analysis identified a number of TFs, miRNAs, and lncRNAs that may potentially regulate the identified hub genes. GO and KEGG enrichment analyses further indicated that the identified genes were associated with protein homeostasis, the ubiquitin–proteasome system, protein folding and degradation, and cellular responses to stress. Conclusion: The findings of this study suggest that dysregulation of protein homeostasis and pathways associated with ubiquitination and the proteasome may represent a shared molecular axis in T2D and DR. Although the network patterns in T2D and DR are not completely identical, the identification of hub genes and regulatory factors, together with the enrichment of proteostasis-related pathways, suggests a potential role for these processes in the pathophysiology of these disorders. However, because the findings are based primarily on bioinformatic and network analyses, functional and clinical validation of the identified genes is necessary to determine their precise roles and evaluate their potential as biomarkers or therapeutic targets.    Keywords: Type 2 diabetes mellitus, diabetic retinopathy, protein metabolism, protein homeostasis, proteostasis, ubiquitin–proteasome system, PPI network, hub genes