Integrated Analysis of Ferroptosis and Immunity-Related Genes Associated with Diabetic Kidney Disease

Purpose: Diabetic kidney disease (DKD) is the leading cause of chronic kidney disease (CKD) worldwide. Elucidation of the molecular mechanisms underlying ferroptosis and immunity in DKD could aid the development of potentially effective therapeutics. This study aimed to perform an integrated analysis of ferroptosis and immune-related differentially expressed mRNAs (DEGs) in DKD. Materials and Methods: Gene expression profiles of samples obtained from patients with DKD and controls were downloaded from the Gene Expression Omnibus (GEO) database. The potential differentially expressed genes (DEGs) were screened using R software, and ferroptosis immune-related differentially expressed genes (FIRDEGs) were extracted from the DEGs. We performed functional enrichment analyses, and constructed protein-protein interaction (PPI) networks, transcription factor (TFs)-gene networks, and gene drug networks to explore their potential biological functions. Correlation analysis and receiver operating characteristic curves were used for evaluating the FIRDEGs. We used the CIBERSORT algorithm to examine the composition of immune cells and determine the relationship between FIRDEG signatures and immune cells. Finally, the RNA expression of six FIRDEGs was validated in animal kidney samples using RT-PCR.Results: We identified 80 FIRDEGs and performed their functional analyses. We identified six hub genes (Ccl5, Il18, Cybb, Fcgr2b, Myd88, and Ccr2) using PPI networks and predicted potential TF gene networks and gene-drug pairs. Immune cells, including M2 macrophages, resting mast cells, and gamma-delta T cells, were altered in DKD; the FIRDEGs (Fcgr2b, Cybb, Ccr2, and Ccl5) were closely correlated with the infiltration abundance of M2 macrophages and gamma-delta T cells. Finally, the hub genes were verified in mouse kidney samples.Conclusion: We identified six hub FIRDEGs (Ccl5, Il18, Cybb, Fcgr2b, Myd88, and Ccr2) in DKD, and predicted the potential transcription factor gene networks and possible treatment targets for future research.