The role of Neutrophil extracellular traps (NETs) in the immunopathogenesis of Diabetic Kidney Disease (DKD) remains elusive. We used a machine learning approach to identify differentially expressed genes (DEGs) associated with NETs in human DKD kidney biopsy datasets and validated the results using single-nucleus RNA sequencing datasets. The expressions of these candidate genes and related cytokines were verified in blood obtained from DKD patients.
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