Abstract: TH-PO0736
Biological and Molecular Insights from Tubular Pathomic Stratification in Nephrotic Syndrome
Session Information
- Glomerular Innovations: Artificial Intelligence, Multiomics, and Biomarkers
November 06, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Glomerular Diseases
- 1402 Glomerular Diseases: Clinical, Outcomes, and Therapeutics
Authors
- Nair, Viji, University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States
- Fan, Fan, Emory University, Atlanta, Georgia, United States
- Eichinger, Felix H., University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States
- McCown, Phillip J., University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States
- Mariani, Laura H., University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States
- Holzman, Lawrence B., University of Pennsylvania, Philadelphia, Pennsylvania, United States
- Madabhushi, Anant, Emory University, Atlanta, Georgia, United States
- Kretzler, Matthias, University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States
- Barisoni, Laura, Duke University, Durham, North Carolina, United States
- Hodgin, Jeffrey B., University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States
- Janowczyk, Andrew, Emory University, Atlanta, Georgia, United States
Background
Automated segmentation and pathomic characterization of tubular substructures provide novel, quantifiable, and clinically significant signatures from kidney biopsies. We examined the transcriptomic correlates of these signatures in focal segmental glomerulosclerosis (FSGS) and minimal change disease (MCD) to reveal hitherto unknown molecular underpinnings.
Methods
Hierarchical clustering of 14 pathomic signatures stratified NEPTUNE/CureGN participants (n=254:135 FSGS, 119 MCD/MCD-like) into two risk groups. Group 1 had significantly worse proteinuria remission and >40% eGFR decline compared to Group 2. Differentially expressed genes (DEGs) from tubulointerstitial transcriptomic data (31 in Group 1, 116 in Group 2) were mapped to specific cell types using Single-nucleus RNA sequencing (snRNA-seq)
Results
There were 1,157 DEGs between Groups 1 and 2 (log2 fold change >abs(0.6), FDR < 0.05, Fig.1A). Pathways enriched in Group 1 included immune regulation, vascular interactions, the complement cascade, and scavenger receptor-mediated ligand uptake. Top DEGs mapped to immune cells and fibroblasts (Fig. 1B). DEGs included tubular injury/adaptation markers such as VCAM1, DCD2, PROM1, and HAVCR1 (Kim-1), indicating adaptive proximal tubular (aPT) and thick ascending limb (aTAL) cell injury states; LCN2 and SPP1 (tubular injury); and EGF, TIMP1, and MMP2/7/9 (fibrosis and extracellular matrix remodeling).
Conclusion
Transcriptomic profiling of biopsy-derived pathomic risk groups revealed immune and injury-related mechanisms underlying poor outcomes, providing biological plausibility for tubular pathomic signature-based stratification of patients with FSGS/MCD to inform therapeutic decision-making
Funding
- NIDDK Support – BI, Vera, Travere, Sanofi and DImerix