Identification of ferroptosis-related genes and pathways in diabetic kidney disease using bioinformatics analysis

Diabetic kidney disease (DKD) is a major public health issue because of its refractory nature. Ferroptosis is a newly coined programmed cell death characterized by the accumulation of lipid reactive oxygen species (ROS). However, the prognostic and diagnostic value of ferroptosis-related genes (FRGs) and their biological mechanisms in DKD remain elusive. The gene expression profiles GSE96804, GSE30566, GSE99339 and GSE30528 were obtained and analyzed. We constructed a reliable prognostic model for DKD consisting of eight FRGs (SKIL, RASA1, YTHDC2, SON, MRPL11, HSD17B14, DUSP1 and FOS). The receiver operating characteristic (ROC) curves showed that the ferroptosis-related model had predictive power with an area under the curve (AUC) of 0.818. Gene functional enrichment analysis showed significant differences between the DKD and normal groups, and ferroptosis played an important role in DKD. Consensus clustering analysis showed four different ferroptosis types, and the risk score of type four was significantly higher than that of other groups. Immune infiltration analysis indicated that the expression of macrophages M2 increased significantly, while that of neutrophils and mast cells activated decreased significantly in the high-risk group. Our study identified and validated the molecular mechanisms of ferroptosis in DKD. FRGs could serve as credible diagnostic biomarkers and therapeutic targets for DKD.