Abstract: FR-PO300
Identification and Validation of Pivotal Genes Driving Diabetic Kidney Disease Progression through Weighted Gene Co-Expression Network Analysis
Session Information
- Diabetic Kidney Disease: Basic - 1
October 25, 2024 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Diabetic Kidney Disease
- 701 Diabetic Kidney Disease: Basic
Authors
- Ye, Siyang, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
- Zhang, Manhuai, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
- Zhang, Meng, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
- Wang, Dingding, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
- Fan, Jinjin, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
- Li, Bin, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
- Zhou, Yi, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
- Chen, Wei, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
Background
Currently, the core factors governing the progression of diabetic kidney disease (DKD) remain elusive. Our study aims to explore the progression-related genes of DKD through comprehensive bioinformatics analysis and in vivo validation, thus providing novel therapeutic targets for retarding DKD progression.
Methods
Differentially expressed genes (DEGs) within kidney from early and advanced DKD samples were detected using GSE142025 dataset. Besides, the weighted gene co-expression network analysis (WGCNA) and protein-protein interaction (PPI) network were conducted, followed by key module analysis and recognition of pivotal genes driving DKD progression. Furthermore, enrichment analysis was used to determine the biological features of pivotal genes associated with DKD progression, and correlation analysis was utilized to explore the potential link between pivotal genes and altered immune status within DKD tissues. Finally, certain pivotal genes were validated by Western blot and immunohistochemistry (IHC) in diabetic mice kidney.
Results
A total of 44 DEGs were identified between early and advanced DKD specimens. Using WGCNA, the turquoise module was deemed as the DKD progression-related module. A total of 18 genes related to DKD progression were obtained by intersection analysis between the upregulated DEGs and the turquoise module. Enrichment analysis indicated that the above 18 genes were primarily involved in necroptosis and other immune inflammatory responses. Moreover, four genes (STAT1, MYC, NLRP3, and TNFAIP3) were recognized as pivotal genes implicated in DKD progression by PPI analysis. Correlation analysis showed that the above pivotal genes were mainly positively correlated with the infiltration of T cells. More importantly, Western blot and IHC analysis revealed that the protein levels of these pivotal genes were significantly increased in the kidneys of advanced DKD mice compared to those in the early DKD group.
Conclusion
Our findings suggest that necroptosis, as well as immune and inflammatory responses, are crucial biological events driving DKD progression. Of note, STAT1, MYC, NLRP3, and TNFAIP3 were identified as pivotal genes promoting the progression of DKD. Consequently, targeting necroptosis and the above pivotal genes might represent a promising therapeutic strategy for delaying DKD progression.
Funding
- Government Support – Non-U.S.