OBJECTIVE

IgA nephropathy (IgAN) is the most prevalent form of primary glomerular disease. However, its diagnosis is contingent on kidney biopsy. Therefore, noninvasive biomarkers are urgently needed for diagnosis. This study aims to identify novel urinary biomarkers that differentiate IgAN from other common primary glomerular diseases, specifically membranous nephropathy (MN) and minimal change disease (MCD).

METHODS

The peripheral blood mononuclear cell (PBMC) transcriptome dataset GSE73953 was obtained from the GEO database. Differential gene expression, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, Gene Ontology (GO) enrichment, and immune infiltration analyses were performed. Protein-protein interaction (PPI) analysis and lysosome-related genes were used to identify hub genes. The expression of the hub gene ATP6V1D in urine and kidney tissues from individuals with IgAN, healthy controls, MCD and MN patients was assessed using enzyme-linked immunosorbent assay (ELISA), Western blotting, and immunostaining techniques. Spearman's correlation analysis was employed to investigate the relationships between the concentration of ATP6V1D in urine, the concentration of galactose-deficient IgA1 (GD-IgA1), and the clinical data of patients. The receiver operating characteristic (ROC) curve was used to assess the role of urine ATP6V1D levels in distinguishing IgAN from MN and MCD.

RESULTS

ATPase was identified as the principal intracellular structure associated with differentially expressed genes (DEGs) between IgAN patients and healthy controls in PBMCs. ATP6V1D was identified as a hub gene at the intersection of lysosome-related and differential genes. ATP6V1D levels were lower in PBMCs, urine, and kidney samples from IgAN patients than in those from healthy individuals, MCD and MN patients. The decreased urinary ATP6V1D levels and increased GD-IgA1 levels in IgAN patients were further validated. These changes were positively correlated with 24-h urine protein levels. Notably, a negative correlation was observed between ATP6V1D and GD-IgA1 levels. ROC curve analysis demonstrated that urinary ATP6V1D (AUC = 0.972) and GD-IgA1 (AUC = 0.952) had significant discriminative power in distinguishing IgAN patients from MCD and MN patients, with no significant difference in predictive performance between the two biomarkers (P > 0.05).

CONCLUSIONS

The findings underscore the potential utility of the urine ATP6V1D concentration as a biomarker to distinguish IgAN from MN and MCD.