Abstract
Background: Diabetic kidney disease (DKD) is one of the serious complications of diabetes. However, there is no unified and clear understanding of the pathogenesis of DKD at present. The evidence suggests that genetic predispositions play a significant role in an individual’s susceptibility to DKD. WGCNA analysis may provide a new way to search for genes closely related to DKD. Methods: In this study we analysed key genes and pathways involved in DKD from RNA-seq count results using 23 peripheral blood samples from patients with DKD. Weighted gene co-expression network analysis (WGCNA) was performed with the WGCNA package.Results: We found turquoise and purple module were characterized as having the highest correlation with large proteinuria stage in DKD. Furthermore, the key genes, including DCN, F2R, LTBP2, B2M, PSMB8, and NLRC5, were evaluated through a protein-protein interaction (PPI) network combined with a co-expression network, which were expected to be potential diagnostic and therapeutic targets of DKD. Conclusions: These signalling pathways and hub genes will provide effective targets and ideas for further study of the pathogenesis of DKD and are expected to have roles in the prevention of, early screening for, and the treatment of DKD.
Identification of key genes for diabetic kidney disease using biological informatics methods
