Unbiased Transcriptomic Clustering Reveals an Inflammatory PEC Niche Associated with Cytokine and RAAS Signaling in Glomerular Disease 2260566

Abstract Introduction Kidney diseases are a major cause of morbidity and mortality worldwide. Glomerular pathologies constitute a substantial subset and are typically diagnosed based on histopathological features from kidney biopsy. However, patients with the same pathological diagnosis often present with heterogeneous molecular signatures and clinical outcomes. Because the kidney is a compact organ composed of highly specialized cell types, bulk RNA sequencing has limited ability to resolve cell type—specific molecular alterations. Recent advances in single-nucleus RNA sequencing have enabled transcriptome-level analysis at cellular resolution, and this technology has already revealed novel molecular subtypes in several diseases. Methods In this study, we generated a single-nucleus glomerular disease atlas from treatment-naïve human kidney biopsies and applied a unified pseudobulk-based clustering strategy across major kidney cell types. Results Unbiased transcriptomic clustering identified a previously unrecognized sample cluster characterized by an enrichment of inflammatory parietal epithelial cells (PECs) expressing high levels of chemokines and CD44. These “activated PECs” were spatially localized to the glomerular tip region and displayed strong STAT1 activity, implicating convergent inflammatory signaling. In parallel, macula densa and juxtaglomerular cells within the same cluster exhibited RAAS pathway activation, suggesting a coordinated niche-level inflammatory-RAAS response. Conclusion This inflammatory PEC—centered niche defines a molecular program not aligned with conventional pathological categories, underscoring the limitation of histology-based classification. Our findings propose an inflammation—RAAS—PEC activation axis as a shared pathogenic mechanism and nominate STAT1 signaling as a potential therapeutic target in glomerular disease. Funding Source n/a Topic Categories Immune Mechanisms of Human Disease (HUM)