Identifies effective biomarkers for renal interstitial fibrosis, suggesting new diagnostic models.
Purpose: Renal interstitial fibrosis (RIF) is a critical pathological process in the progression of chronic kidney disease (CKD). This study aimed to identify and validate inflammation- and hypoxia-related differentially expressed genes (IHRDEGs) associated with RIF and to construct a robust diagnostic model with potential clinical applications. Patients and Methods: Three public GEO datasets (GSE22459, GSE76882, GSE53605) comprising 76 RIF and 142 control samples were integrated following batch correction and normalization. Differentially expressed IHRDEGs were screened and analyzed using GO and KEGG pathway enrichment. A diagnostic model was constructed using logistic regression and optimized through SVM and LASSO algorithms. Immune infiltration was evaluated using ssGSEA, and consensus clustering was used to define molecular subtypes. Experimental validation was conducted in a rat model of RIF using RT-qPCR, Western blotting, and immunohistochemistry. Results: A total of five hub IHRDEGs (EDN1, HLA-G, MYC, HIF1A, and TLR2) were identified and incorporated into a diagnostic model that demonstrated strong predictive ability (AUC 0.7– 0.9; sensitivity and specificity > 70– 90%). These genes were significantly correlated with immune cell infiltration patterns. Subtype analysis revealed two distinct molecular clusters of RIF with different immunopathological features. Co-expression and regulatory interaction analyses further elucidated the involvement of hub genes in fibrotic mechanisms. Experimental validation confirmed the upregulation of hub genes at both mRNA and protein levels in the RIF model. Conclusion: This study uncovers the diagnostic and mechanistic significance of inflammation- and hypoxia-related genes in RIF. The five identified hub genes may serve as promising biomarkers and therapeutic targets. These findings provide novel insights into the immune-hypoxia interplay in renal fibrosis and offer a potential framework for early diagnosis and targeted treatment of CKD-related fibrosis.
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Zhang et al. (2026) studied this question.
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