BACKGROUNDS: The mechanisms contributing to diabetic vasculopathy have not been fully understand. METHODS: First, we identified differentially expressed genes (DEGs) of diabetic vasculopathy via GSE13760. Enrichment analysis was conducted. We utilized the cMAP database to identify potential small-molecular drugs targeting diabetic vasculopathy based on upregulated DEGs. Hub genes were extracted from protein-protein interaction (PPI) networks, and their expression and correlation patterns were further evaluated. Key genes implicated in diabetic vasculopathy were determined by integrating three distinct algorithmic approaches. Additionally, we constructed mRNA-miRNA and mRNA-transcription factor (TF) regulatory networks and performed immune infiltration as well as single-cell RNA sequencing (scRNA-seq) analyses. Finally, animal studies were carried out to provide preliminary experimental validation. RESULTS: One hundred thirty-nine DEGs were identified in the comparison between Type 2 diabetes mellitus (T2DM) and control (Con) arterial samples. Then, enrichment analysis revealed that the DEGs were associated with several key pathways, including cytokine-cytokine receptor interaction, regulation of phosphatidylinositol 3-kinase activity, and the TGF-beta signaling pathway. Ten leading small-molecular compounds with therapeutic potential for diabetic vasculopathy were identified. Among the upregulated genes, BMP4 and LEP were selected as key candidates. Regulatory network analyses, including mRNA-miRNA and mRNA-TF interactions, along with immune infiltration profiling, suggested that multiple miRNAs, TFs, and immune cells may collectively influence BMP4 and LEP expression. scRNA-seq further indicated predominant expression of BMP4 within endothelial cells and fibroblasts. Finally, experimental validation in the T2DM mouse model corroborated the expression patterns of these key genes and enrichment findings. CONCLUSIONS: Findings indicate that the two upregulated genes, BMP4 and LEP, are implicated in the pathophysiology of diabetic vasculopathy.
Identification and Validation of the Key Genes of Diabetic Vasculopathy: Evidence Based on Bioinformatics Analysis and Animal Study.
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作者:Li Feng, Geng Chi, Xu Xing, Zhou Yu-Lun, Guo Xin-Ru, Wang Rui-Tao, Zhang You, Peng Si-Liang, Jin Meng-Chao, Huang Jian, Bai Hui-Yu, Li Hui, Gu Xiao-Song, Zhao Songyun
| 期刊: | International Journal of Genomics | 影响因子: | 1.900 |
| 时间: | 2025 | 起止号: | 2025 Oct 24; 2025:7850852 |
| doi: | 10.1155/ijog/7850852 | ||
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