#162 Single-nucleus RNA-seq of biopsy-confirmed IgA nephropathy reveals cell-specific transcriptomic alteration

Abstract

Abstract Background and Aims Single-nucleus RNA-seq (SnRNA-seq) is a valuable method for identifying cell-specific transcriptomic alterations in kidney cells. Our objective was to investigate SnRNA-seq data from biopsy-confirmed IgA nephropathy (IgAN) cases and identify cell-specific alterations in the transcriptome. Method We collected snap-frozen kidney biopsy tissues from 6 cases of IgA nephropathy (IgAN) and 7 nephrectomy control cases. The disease control group included 3 cases of diabetic kidney disease, 6 cases of minimal change disease, and 6 PLA2R-Ab positive membranous nephropathy cases. SnRNA-seq was performed on the kidney tissues, and kidney cells were identified in the dataset through UMAP clustering. We investigated differences in the proportion of kidney cell types and identified differentially expressed genes (DEGs). Additionally, we searched for representative gene loci previously reported in a multiethnic genome-wide association study (GWAS). Results We successfully collected transcriptomic profiles of >50 000 cells from IgAN, with a considerable enrichment of intraglomerular cells. The DEG analysis revealed a high number of DEGs in mesangial cells, fibroblasts, and vascular smooth muscle cells in the IgAN transcriptome compared to the nephrectomy and disease control cases. In the gene set enrichment analysis, the epithelial-mesenchymal transition pathway was enriched in the glomerular cells of IgAN. Furthermore, among various GWAS loci, ETS1 was the gene significantly highly expressed in the mesangial cells of IgAN, consistent across the compared control groups. Conclusion This investigation represents the largest SnRNA-Seq profiling of IgAN kidney cells to date. We identified notable enriched cell-specific pathways in IgAN. ETS1 may be a kidney-indwelling causal factor for IgAN pathophysiology, considering its notable significance in both previous GWAS results and the current SnRNA-Seq data.