ASN's Mission

ASN leads the fight to prevent, treat, and cure kidney diseases throughout the world by educating health professionals and scientists, advancing research and innovation, communicating new knowledge, and advocating for the highest quality care for patients.

learn more

Contact ASN

1401 H St, NW, Ste 900, Washington, DC 20005

email@asn-online.org

202-640-4660

The Latest on Twitter

Kidney Week

Abstract: TH-PO086

Ultrastructural Descriptors for Clinically Relevant Categorization of MCD/FSGS NEPTUNE Patients

Session Information

Category: Glomerular

  • 1004 Clinical/Diagnostic Renal Pathology and Lab Medicine

Authors

  • Zee, Jarcy, Arbor Research Collaborative for Health, Ann Arbor, Michigan, United States
  • Liu, Q, Arbor Research Collaborative for Health, Ann Arbor, Michigan, United States
  • Smith, A R, Arbor Research Collaborative for Health, Ann Arbor, Michigan, United States
  • Avila-Casado, Carmen, University of Toronto, Toronto, Ontario, Canada
  • Hodgin, Jeffrey B., University of Michigan, Ann Arbor, Michigan, United States
  • Holzman, Lawrence B., University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Gillespie, Brenda W., University of Michigan, Ann Arbor, Michigan, United States
  • Barisoni, L., University of Miami, Miami, Florida, United States
  • Royal, Virginie, Université de Montréal, Montréal, Quebec, Canada
Background

Ultrastructural features of renal biopsies are rarely used in conventional classification systems, and their reporting is often limited to a few parameters. The aim of this study was to investigate the prognostic value of 12 electron microscopy (EM) descriptors from the NEPTUNE Digital Pathology Scoring System (NDPSS).

Methods

Study pathologists scored digital EM images from 172 MCD/FSGS patients using the NDPSS. We performed hierarchical clustering of patients based on EM descriptors. We compared demographics, clinical characteristics, time to proteinuria remission, and time to the composite of 40% reduction in eGFR or ESRD across the clusters. We used penalized multinomial regression with cross-validation to test descriptors driving cluster membership and Cox proportional hazards models to link EM descriptors to clinical outcomes.

Results

Of the 3 clusters found [figure], cluster 1 patients had the most EM damage, were older (p=0.018), had lower eGFR (p<0.001) and higher urine protein creatinine ratio (p=0.029) at baseline, had higher rates of the composite outcome (p=0.005) and lowest rates of remission (p=0.033). Clusters 2 and 3 did not have significantly different demographics, baseline clinical characteristics, or outcomes. Microvillous transformation was not predictive of clusters, but was independently predictive of remission (p=0.001).

Conclusion

The NDPSS descriptor-based assessment of EM uncovered the significance of ultrastructural parameters usually under-reported in clinical practice. EM descriptor-based patient clusters predicted remission and progression outcomes, reflecting quantifiable transitional vs. permanent damage.

Funding

  • NIDDK Support