Cross-Cohort Transcriptomic Integration Identifies IFIT2 as a Translational Diagnostic Biomarker and Functional...

Chronic kidney disease (CKD) is a major global health burden characterized by progressive loss of renal function, persistent inflammation, and tubular epithelial injury, yet reproducible diagnostic biomarkers that also have functional relevance remain insufficiently defined. Here, we integrated multiple independent CKD transcriptomic cohorts from GEO (GSE32591 and GSE66494 as training datasets, with GSE180394 as an external validation dataset) using rigorous batch-effect correction and differential expression analysis to identify consistently dysregulated genes across platforms. Shared CKD-upregulated genes were predominantly enriched in immune and inflammatory biological processes, and module-level analyses prioritized a core set of hub genes showing stable activation across cohorts. Based on these hubs, we constructed a composite diagnostic gene signature using a standardized Z-score-based scoring approach, which demonstrated a robust discriminative performance in both training and external validation cohorts. Among candidate genes ranked by diagnostic performance, IFIT2 emerged as a reproducibly upregulated marker with strong diagnostic utility. Mechanistically, IFIT2 was inducible in human renal tubular epithelial cells (HK-2 and primary RPTEC) under CKD-relevant inflammatory (IFN-γ) and profibrotic (TGF-β1) stimulation. Importantly, shRNA-mediated IFIT2 knockdown mitigated IFN-γ-induced reductions in cell viability, decreased apoptosis, and attenuated the induction of tubular injury markers (KIM1 and LCN2) and inflammatory mediators (IL6 and CXCL10). Together, these results support IFIT2 as a promising candidate biomarker linking inflammation to tubular injury in CKD, providing a translational rationale for further biomarker-guided stratification and therapeutic targeting in future studies.