Abstract: FR-PO0827
Biomarker Characterization of Treatment-Resistant Minimal Change Disease (TR MCD)
Session Information
- Glomerular Diseases: Practice and New Concepts Shaping Modern Care
October 23, 2026 | Location: Exhibit Hall A, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Glomerular Diseases
- 1402 Glomerular Diseases: Clinical, Outcomes, and Therapeutics
Authors
- Zhai, Yan, University of Michigan, Ann Arbor, Michigan, United States
- Rahimi, Ashley E., University of Michigan, Ann Arbor, Michigan, United States
- Ju, Wenjun, University of Michigan, Ann Arbor, Michigan, United States
- Trachtman, Howard, University of Michigan, Ann Arbor, Michigan, United States
- Modi, Zubin J., University of Michigan, Ann Arbor, Michigan, United States
Background
The most common causes of idiopathic nephrotic syndrome (NS) are minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS). In contrast to MCD, FSGS is often refractory to treatment, and nearly 50% of patients progress to kidney failure. The prognosis for patients with TR MCD is uncertain. We conducted this study to assess whether biomarker profiling can improve the characterization of this patient subgroup.
Methods
Patients were categorized as steroid sensitive MCD (SS MCD), treatment resistant MCD (TR MCR), or FSGS based upon available biopsy findings and or the level of proteinuria 2 years after enrollment in the NEPTUNE cohort study. Clinical and laboratory data were retrieved and uirine and serum biomarker concentrations from enrollment samples were determined using the Luminex platform. Pairwise present principal component analysis (PCA) was used to assess the biomarker data.
Results
There were 110 patients with available biomarker data (SS-MCD n=33, TR-MCD n=5, FSGS n=72). Patients with MCD were younger and less likely to be hypertensive compared to those with FSGS. Steroids were prescribed more frequently in children with MCD and immunosuppressive therapy was used most often in those with TR MCD. 22 biomarkers were detectable in at least 80% of the available urine and serum samples. Principal component analysis (PCA) of serum biomarkers identified three dominant components explaining 42.4% of the total variance, reflecting shared biomarker patterns rather than diagnosis specific signatures. Across all PCA projections, SS MCD, FSGS, and TR MCD demonstrated overlap, with FSGS showing greater heterogeneity, SS MCD appearing more centrally clustered, and TR MCD overlapping more closely with FSGS than with SS MCD. Urine biomarker PCA demonstrated a dominant global biomarker signal captured by PC1 (41.7% variance), with subsequent components reflecting additional sources of variation. Diagnostic groups again showed overlap, with greater dispersion observed among patients with FSGS.
Conclusion
Our findings suggest that patients with TR MCD exhibit biomarker profiles that are may be more similar to those observed in FSGS than in SS MCD, based on shared multivariate biomarker patterns rather than diagnosis. These results highlight overlap across diagnostic groups and greater heterogeneity within FSGS. This work provides initial candidate biomarker panels for evaluation on a larger cohort.