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Kidney Week

Abstract: SA-PO1201

Urine mRNA Assay to Measure Compartment-Specific Kidney Injury

Session Information

Category: CKD (Non-Dialysis)

  • 2302 CKD (Non-Dialysis): Clinical, Outcomes, and Trials

Authors

  • Caldato Barsotti, Gabriel, Yale School of Medicine, New Haven, Connecticut, United States
  • Kumar, Ashwani, Yale School of Medicine, New Haven, Connecticut, United States
  • Yi, Zhengzi, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Pell, John F., Yale School of Medicine, New Haven, Connecticut, United States
  • Tanvir, E M, Yale School of Medicine, New Haven, Connecticut, United States
  • Moledina, Dennis G., Yale School of Medicine, New Haven, Connecticut, United States
  • Luciano, Randy L., Yale School of Medicine, New Haven, Connecticut, United States
  • Reghuvaran, Anand, Yale School of Medicine, New Haven, Connecticut, United States
  • Meliambro, Kristin, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Perincheri, Sudhir, Yale School of Medicine, New Haven, Connecticut, United States
  • Zhang, Weijia, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • He, John Cijiang, Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Menon, Madhav C., Yale School of Medicine, New Haven, Connecticut, United States
Background

While kidney biopsy is the diagnostic gold standard, it is invasive. We developed a 10-gene urinary mRNA qPCR assay to reflect histologic injury and predict outcomes

Methods

Urine cell pellet RNA from 54 patients (pre-biopsy, CKD stages 2-5) and 20 healthy controls was analyzed by TaqMan qPCR. Ten genes reflecting glomerular, tubular, inflammatory, and fibrotic injury were chosen for cell-type specificity, injury signals, and presence in urine scRNAseq [Fig-A]. Absolute expression was calculated and normalized to controls. A novel automated digital pathology platform assessed compartment-specific injury.

Results

All 10 transcripts were significantly elevated in urine of patients with any injury vs controls [Fig-B]. Urinary mRNAs selected to reflect cell-specific injury were highly correlated with corresponding compartment specific pathologic features [Table-1]. NPHS1 associated with morphologic normal glomeruli (adjusted for biopsy area), while NPHS2 correlated with glomerulomegaly and increased proteinuria. KIM1 aligned with acute tubular injury score, and VCAM1 correlated with atrophy/fibrosis. Patients were followed for 6 months (n=45). A regression model combining progressive injury markers (VCAM1, SHROOM3) & clinical data (age, eGFR, proteinuria) outperformed clinical data alone in predicting eGFR decline (AUC=0.90 vs 0.78) [C-G]

Conclusion

Our non-invasive, scalable urinary mRNA assay accurately reflects histologic injury and predicts functional decline enabling molecular monitoring of CKD.

Correlation of Digital Pathology and Gene Expression
Digital PathologyGeneCorrelation CoefficientP-Value
Normal GlomeruliNPHS10.55<0.01
GlomerulomegalyNPHS20.310.03
ProteinuriaNPHS20.35<0.01
Normal tubular areaShroom3-0.39<0.01
Atrophic tubular numberVCAM10.44<0.01
Interstitial areaVCAM10.46<0.01
Lymphocyte infiltration areaKIM10.320.03

Funding

  • NIDDK Support

Digital Object Identifier (DOI)