Evaluation of Biopsy-Based Molecular Risk Prediction in Crescentic Glomerulonephritis

Abstract Introduction: Novel molecular tools have the potential to improve current clinical and histology-based risk classification systems for various medical renal diseases including glomerulonephritis (GN). We aimed to assess the utility of gene expression for improving biopsy-based risk prediction in patients with GN with and without crescent formation. Methods: This retrospective case-control study used NanoString nCounter to measure the expression of 54 previously described inflammation, nephron injury, endothelium, and crescent-related genes in 335 archival, formalin-fixed paraffin-embedded native kidney biopsies, including a 288-biopsy discovery cohort representing a broad spectrum of crescentic GN subtypes, and an independent 47-biopsy validation cohort focused on ANCA-associated crescentic GN. Clinical, histologic, and gene expression data were compared. Results: Discovery cohort analysis demonstrated increased expression of 13 genes in crescentic GN cases that developed end-stage renal disease (ESRD) versus those that did not (false discovery rate <0.05). Within the 75-biopsy subset of ANCA-associated crescentic GN cases in the discovery cohort, this 13-gene set was found to be independently predictive of ESRD in multivariate Cox proportional hazards regression analysis (p = 0.015), with significant differentiation of high and low risk patients in the Kaplan-Meier renal survival analysis (log-rank test, p = 0.002). However, validation cohort analysis did not demonstrate significant improvement in risk stratification with the 13-gene set when compared with established clinicopathologic models. Conclusion: These results suggest that biopsy-based gene expression may provide the opportunity for improved risk stratification in crescentic GN; however, the genes evaluated in this study appear to have limited added clinical utility over existing risk scores.

• Publication year

  2025

• Venue

  Glomerular Diseases

• Publication date

  2025-11-13

• Fields of study

  Medicine

• Identifiers
  DOI 10.1159/000549541PMID 41384044PMCID 12695120
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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