Abstract
Background: Vascular calcification and autophagy play pivotal roles in the pathogenesis of diabetic nephropathy (DN), though the underlying molecular mechanisms remain unclear. Methods: Differential expression analysis and weighted gene co-expression network analysis were performed on the GSE30529 dataset to identify candidate genes associated with DN. Subsequently, Mendelian randomization analysis was utilized to isolate genes with a causal relationship to DN. DN biomarkers were further validated based on their expression profiles in both the GSE30529 training set and the GSE96804 validation set. Gene set enrichment analysis, immune infiltration analysis, drug prediction, and molecular regulatory network construction were then conducted. Reverse transcription-quantitative PCR (RT-qPCR) was used to assess the expression of biomarkers in clinical DN and normal samples. Results: A total of 286 candidate genes were identified in the GSE30529 dataset, of which seven were linked to DN progression. JCHAIN and IFI44L were highlighted as biomarkers due to their upregulated expression and their association with DN risk. These biomarkers were predominantly enriched in immune-related pathways and were strongly correlated with specific immune cell populations. Expression of IFI44L was found to be potentially regulated by miRNAs and the transcription factor YY1. Furthermore, potential DN therapeutic targets, including JCHAIN and IFI44L, were identified. RT-qPCR confirmed elevated expression levels of JCHAIN (p = 0.0155) and IFI44L (p = 0.0203) in DN samples, consistent with trends observed in the GSE30529 and GSE96804 datasets. Conclusions: The investigation identified VC-CMARGs JCHAIN and IFI44L as promising biomarkers, offering valuable insights for the clinical diagnosis and treatment of DN.