Kidney Week

Abstract: TH-PO0344

Weighted Gene Coexpression Network Analysis (WGCNA) Identifies GAS6/AXL and Hedgehog/GLI1 Signaling as Associated with Fibrotic Progression in ANCA-Associated Vasculitis Glomerulonephritis

Session Information

• Glomerular Diseases: Omics
  October 22, 2026 | Location: Exhibit Hall A, Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Glomerular Diseases

• 1401 Glomerular Diseases: Mechanisms, including Podocyte Biology

Authors

• Stojkic, Ivana, Nationwide Children's Hospital, Columbus, Ohio, United States

Ivana Stojkic, MD, MS

• Arazi, Arnon, Northwell Health Feinstein Institutes for Medical Research, Manhasset, New York, United States

Arnon Arazi, PhD

• Song, Huijuan, The Ohio State University, Columbus, Ohio, United States

Huijuan Song

• Yan, Pearlly, The Ohio State University, Columbus, Ohio, United States

Pearlly Yan, PhD

• Wang, Xin, Nationwide Children's Hospital, Columbus, Ohio, United States

Xin Wang, PhD

• Fussner, Lynn A., The Ohio State University, Columbus, Ohio, United States

Lynn A. Fussner, MD

• Parikh, Samir V., The Ohio State University, Columbus, Ohio, United States

Samir V. Parikh, MD, FASN

• Ardoin, Stacy, Nationwide Children's Hospital, Columbus, Ohio, United States

Stacy Ardoin, MD, MSc

• Smoyer, William E., Nationwide Children's Hospital, Columbus, Ohio, United States

William E. Smoyer, MD

• Rovin, Brad, The Ohio State University, Columbus, Ohio, United States

Brad Rovin, MD, FASN

• Almaani, Salem, Cleveland Clinic, Cleveland, Ohio, United States

Salem Almaani, MBBS, MS, FASN

Background

ANCA-associated vasculitis with glomerulonephritis (AAV-GN) progresses to kidney failure in ~25% of patients. Molecular heterogeneity contributes to variable disease trajectory, but clinically relevant drivers of kidney risk remain poorly defined.

Methods

We performed gene network analysis on bulk transcriptomic data from 22 FFPE kidney biopsies to identify pathways associated with the ANCA renal risk score (ARRS). A signed co-expression network was constructed (β=14) to approximate scale-free topology. Genes with similar expression patterns were grouped into modules based on topological overlap, followed by dynamic tree cutting for module detection. Within modules showing the strongest clinical associations, intramodular connectivity (kME) was used to identify highly connected hub genes. Functional enrichment via GSEA was performed to characterize the biological pathways represented by key clinical modules.

Results

Signed WGCNA identified 68 co-expression modules, of which 13 correlated with ARRS (|r| ≥ 0.40). The Salmon module showed the strongest positive correlation (r = 0.49 and p = 0.02); its hub genes (IFNA17, IFNL2, IL2RB, CLEC4F) indicate a robust Type I/III interferon signature and sustained immune activation driving disease severity (Fig. 1a,b). The Green module (r = 0.45 and p = 0.04) was defined by GAS6 and GLI1 (Fig. 1c,d). GAS6 is linked to AXL-mediated extracellular matrix production in tubular cells, while GLI1, a Hedgehog pathway regulator, is implicated in mesangial activation and progression to interstitial fibrosis. Rhodopsin was identified as a progression marker with divergent regulation across modules.

Conclusion

Our WGCNA identifies associations between GAS6/AXL and Hedgehog/GLI1 pathways and fibrotic progression. These findings provide molecular insight into AAV-GN renal progression and highlight AXL and Hedgehog signaling as potential therapeutic targets.

Funding

• Private Foundation Support