Identification of Differentially Expressed Genes and Pathways in Non-Diabetic CKD and Diabetic CKD by Integrated Human Transcriptomic Bioinformatics Analysis.

Chronic kidney disease (CKD) is a heterogeneous condition with various etiologies, including type 2 diabetes mellitus (T2D), hypertension, and autoimmune disorders. Both diabetic CKD (CKD_T2D) and non-diabetic CKD (CKD_nonT2D) share overlapping clinical features, but understanding the molecular mechanisms underlying each subtype and distinguishing diabetic from non-diabetic forms remain poorly defined. To identify differentially expressed genes (DEGs) and enriched biological pathways between CKD_T2D and CKD_nonT2D cohorts, including autoimmune (CKD_nonT2D_AI) and hypertensive (CKD_nonT2D_HT) subtypes, through integrative transcriptomic analysis. Publicly available gene expression datasets from human glomerular and tubulointerstitial kidney tissues were curated and analyzed from GEO and ArrayExpress. Differential expression analysis and Gene Set Enrichment Analysis (GSEA) were conducted to assess cohort-specific molecular signatures. A considerable overlap in DEGs was observed between CKD_T2D and CKD_nonT2D, with CKD_T2D exhibiting more extensive gene expression changes. Hypertensive-CKD shared greater transcriptomic similarity with CKD_T2D than autoimmune-CKD. Key DEGs involved in fibrosis, inflammation, and complement activation-including , , , and -were differentially regulated in diabetic samples, where GSEA revealed immune pathway enrichment in glomeruli and metabolic pathway enrichment in tubulointerstitium. The transcriptomic landscape of CKD_T2D reveals stronger immune and metabolic dysregulation compared to non-diabetic CKD. These findings suggest divergent pathological mechanisms and support the need for tailored therapeutic approaches.