Identification and Validation of the Key Genes of Diabetic Vasculopathy: Evidence Based on Bioinformatics Analysis and Animal Study
Feng Li, Chi Geng, Xing Xu, Yu-Lun Zhou, Xin-Ru Guo, Rui-Tao Wang, You Zhang, Si-Liang Peng, Meng-Chao Jin, Jian Huang, Hui-Yu Bai, Hui Li, Xiao-Song Gu, Songyun Zhao
TL;DR
This study identifies key genes involved in diabetic vasculopathy using bioinformatics and animal experiments, highlighting BMP4 and LEP as potential therapeutic targets.
Contribution
The study integrates multiple computational and experimental approaches to identify and validate key genes in diabetic vasculopathy.
Findings
BMP4 and LEP are upregulated and implicated in diabetic vasculopathy pathophysiology.
Regulatory networks suggest miRNAs, transcription factors, and immune cells influence BMP4 and LEP expression.
Experimental validation in a T2DM mouse model supports the bioinformatics findings.
Abstract
The mechanisms contributing to diabetic vasculopathy have not been fully understand. 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. One…
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Taxonomy
TopicsNeurological Disease Mechanisms and Treatments · Neurological Disorders and Treatments · Cerebrovascular and genetic disorders