Comprehensive Analysis and Experimental Validation of Immune-Related Biomarkers and Immune Microenvironment in Diabetic Nephropathy.

Background: The molecular mechanism of diabetic nephropathy (DN) is still not fully understood. There is ample evidence that the immune system plays a crucial role in the progression of DN. Further exploration of immune-related genes (IRGs) for DN diagnosis is therefore of significant clinical value.

Methods: Gene expression data from DN patients were obtained from the GEO database, and a weighted gene co-expression network analysis (WGCNA) was constructed. The overlapping IRGs derived by the least absolute shrinkage and selection operator (LASSO) and recursive feature elimination (RF) algorithms were identified as DN diagnostic biomarkers. A nomogram model was established to evaluate the diagnostic ability of feature biomarkers. The expression levels of the screened IRGs were validated in vitro using qRT-PCR. Type 2 diabetes mellitus (T2DM) mouse model with DN was also established to confirm the consistency with bioinformatic predictions.

Results: Three IRG-related DN characteristic diagnostic biomarkers (CCL9, EDN1 and HSPA1L) were identified. After verifying the DN diagnostic capability with nomogram model, pathway enrichment analysis, immunoinfiltration characteristics and correlation analysis were used to comprehensively analyze the potential effects of selected IRGs on DN. The differential expressions of screened IRGs were further confirmed by cell line and T2DM mouse model.

Conclusion: Our findings nominate CCL9, EDN1, and HSPA1L as key mediators of DN progression and unveil their potential as diagnostic biomarkers. Although prospective validation in human cohorts is a prerequisite for clinical translation, these IRGs represent a compelling foundation for a precision medicine tool. This tool could transform patient management by facilitating pre-symptomatic diagnosis and informing tailored interventions to halt DN development.