Kidney Week

Abstract: TH-PO616

Identification of Urinary Biomarkers for Outcome-Associated Digital Pathology Descriptors in Patients with Nephrotic Syndrome

Session Information

• Membranous Nephropathy, FSGS, and Minimal Change Disease
  October 24, 2024 | 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

Viji Nair, PhD

• Hodgin, Jeffrey B., University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States

Jeffrey B. Hodgin, MD, PhD

• Fermin, Damian, University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States

Damian Fermin, PhD

• Lee, Edmond, University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States

Edmond Lee

• Barisoni, Laura, Duke University, Durham, North Carolina, United States

Laura Barisoni, MD

• Kretzler, Matthias, University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States

Matthias Kretzler, MD

• Ju, Wenjun, University of Michigan Michigan Medicine, Ann Arbor, Michigan, United States

Wenjun Ju, PhD

Background

Interstitial fibrosis (IF), tubular atrophy (TA) and Mononuclear white blood cells (MWBC) have been shown to be strongly associated with kidney disease outcome in patients with nephrotic syndrome. However, due to the invasive nature of kidney biopsy process, it is impractical to perform repeated assessments hence potentially missing crucial periods for early prognosis and intervention. There is an unmet need to develop non-invasive biomarkers that can represent underlying disease mechanisms and can serve as surrogates for outcome-associated digital pathology descriptors (DPD)s.

Methods

Urine proteomics data (SomaScan assay v4.1), kidney transcriptomic profiles, and DPD including IF, TA, and MWBC of 64 patients with nephrotic syndrome from the NEPTUNE cohort, were integrated to identify urinary protein markers. Statstical methods employed included pearson correlation, linear regression with signifcance set at p ≤0.05. Significance was adjusted for multiple testing. Ingenuity pathway analysis was used to identify enriched canonical pathways. Cox model was used to determine the association of markers with kidney composite endpoint of kidney failure and 40% reduction of GFR.

Results

274 urine proteins and 2,031 tubulointerstitial genes were identified showing significant correlation with IF (adj. p ≤0.05). Pathway enrichment analysis of IF-correlated genes identified 480 significantly enriched canonical pathways, including interleukin signaling pathways, axonal guidance, STAT3 pathway that have been known as associated with kidney disease progression were among top pathways. Integrating the urine markers and the pathway representing genes, we identified urine protein signatures that predict IF (linear regression, p ≤ 0.05) and a subset of these markers (n=27) also predicted the composite outcome. Similarly, we also identified TA and MWBC associated urinary biomarkers.

Conclusion

We identified pathway representing urine biomarkers that can predict IF and clinical outcomes in patients with NS. Such biomarkers would enable frequent non-invasive pathway-specific disease monitoring, offering the possibility for timely prognosis and targeted treatment. Our finding warrants further validation in larger and independent cohorts.

Funding

• NIDDK Support