Immune landscape in the glomerular transcriptome of nephrotic syndrome and anca-associated vasculitis

ANCA-associated vasculitis (AAV), and nephrotic syndrome encompassing diseases including minimal change disease (MCD), focal and segmental glomerulosclerosis (FSG), membranous nephropathy (MN), remain a challenge due to their varied immunological characteristics. Recent therapeutic advancements have highlighted the importance of understanding these diseases' immunological landscapes.

This study analyzed transcriptomics data from renal glomerular tissues of patients with AAV, FSG, MCD, MN, and normal controls. Utilizing an immune-related gene set of 883 genes, methods including Gene Set Variation Analysis (GSVA), LASSO regression, and Weighted Correlation Network Analysis (WGCNA) were used. Predictions of immune cell compositions were made through CIBERSORT, TIMER, MCPcounter, and quanTIseq algorithms.

The study revealed distinct immunogenetic pathways enriched in each disease: hematopoietic cell lineage in ANCA, linoleic acid metabolism in FSG, PPAR signaling in MCD, and drug metabolism in MN. Classifiers based on immune gene expression showed high accuracy (AUC: ANCA 0.812, FSG 0.99, MCD 1, MN 0.888). Co-expression modules and PPI networks highlighted unique pathways for each disease. Predictions of immune cell composition showed elevated macrophages in FSG and MN, with Treg levels elevated across all four diseases compared to normal controls and highest in FSG. Correlation analyses demonstrated significant associations between classifier scores and immune cell types.

This study offers accurate classifiers for AAV, FSG, MCD, and MN, and reveals distinct immunological pathways. These findings advance personalized treatments and highlight potential therapeutic targets in AAV and nephrotic syndrome. Further research should validate these results for clinical applications.