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Kidney Week

Abstract: TH-OR46

Kidney Biopsy Transcript Patterns Offer a Novel Approach to Distinguishing Etiologies of Acute Interstitial Nephritis

Session Information

Category: Pathology and Lab Medicine

  • 1602 Pathology and Lab Medicine: Clinical

Authors

  • Rosales, Ivy, Massachusetts General Hospital, Boston, Massachusetts, United States
  • Tomaszewski, Kristen, Massachusetts General Hospital, Boston, Massachusetts, United States
  • Acheampong, Ellen, Massachusetts General Hospital, Boston, Massachusetts, United States
  • Weins, Astrid, Brigham and Women's Hospital, Boston, Massachusetts, United States
  • Smith, Rex Neal, Massachusetts General Hospital, Boston, Massachusetts, United States
  • Sise, Meghan E., Massachusetts General Hospital, Boston, Massachusetts, United States
  • Colvin, Robert B., Massachusetts General Hospital, Boston, Massachusetts, United States
Background

One of the challenges in renal pathology is distinguishing causes of acute interstitial nephritis (AIN). Based on encouraging results from renal allografts, we sought mRNA transcript profiles of checkpoint inhibitor associated AIN (CPI), drug induced AIN (Drug), AIN in diabetes (DM), IgG4-related renal disease (IgG4) and T cell rejection type I (TCMR1).

Methods

Three 20 um sections were obtained from 65 FFPE blocks: 9 controls, 46 AIN types (10 CPI, 13 DM, 14 Drug, 9 IgG4) and 10 TCMR1. RNA was extracted and hybridized with NanoString HOT Panel of 770 probes and analyzed on an nCounter Max instrument. The gene list is available at nanostring.com. Pathway analysis, differential expression and cell type scores were analyzed from normalized mRNA counts using nSolver.

Results

Similarities were found across AIN however each had one or more distinct patterns of transcripts. CPI AIN was distinguished from the other causes of AIN by higher IFNγ signaling pathway scores (Fig 1). CPI AIN had more exhausted CD8 cells (p<0.05) and NK cells (p<0.001) than drug induced AIN. DM AIN differed from histologically indistinguishable Drug AIN by several genes (e.g. higher TGFβ2, p=0.007). IgG4 AIN showed the highest levels of B cell receptor signaling, MAPK and mTOR pathways, and highest Th17 and Treg differentiation scores. TCMR1 had lower scores for TGFβ and TNF pathways and lower Treg scores compared with the other causes of AIN. TCMR1 had the most favorable scores for AKI and pathways related to outcome (eGFR later, GoCAR progression).

Conclusion

Our initial findings suggest that once extended to customized algorithms and validated, this approach may prove fruitful in distinguishing the underlying diagnosis and pathogenesis of diverse causes of AIN.