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Abstract: FR-PO818

Nuclear Magnetic Resonance Metabolomic Profiling in Distinguishing Primary from Secondary FSGS

Session Information

Category: Glomerular Diseases

  • 1202 Glomerular Diseases: Immunology and Inflammation

Authors

  • Bobart, Shane A., Mayo Clinic, Rochester, Minnesota, United States
  • Vaughan, Lisa E., Mayo Clinic, Rochester, Minnesota, United States
  • Vuckovic, Ivan, Mayo Clinic, Rochester, Minnesota, United States
  • Sethi, Sanjeev, Mayo Clinic, Rochester, Minnesota, United States
  • Denic, Aleksandar, Mayo Clinic, Rochester, Minnesota, United States
  • Fervenza, Fernando C., Mayo Clinic, Rochester, Minnesota, United States
Background

FSGS is a renal histologic lesion with diverse etiologies that cause podocyte injury and depletion. Subclasses of FSGS include primary, genetic, and secondary forms. These subclasses differ noticeably in management and prognosis. Without an accepted biomarker that discriminates among these FSGS types, classification of patients is often challenging. NMR-based urine metabolomics has shown potential in biomarker discovery. We hypothesized that urine metabolites can distinguish such patients.

Methods

We used high resolution NMR spectroscopy to study urines of 12 patients with primary FSGS and 14 patients with secondary or genetic FSGS. NMR spectra were binned and normalized by total spectrum area. Using non-specific feature selection, we analyzed the top 50% ranked bins in the dataset by partial least squares discriminant analysis (PLS-DA). Cross-validation was used to choose tuning parameters and to estimate predictive performance. The 95% confidence interval was estimated using the score test.

Results

PLS-DA score plot demonstrated considerable overlap within the secondary/genetic group relative to the primary group (Figure). When comparing these two groups, the top 5 spectra bins corresponding to highest variable importance included the following metabolites: choline, acetyl-carnitine, histidine, betaine, taurine N-phenylacetyglutamine and two unknown metabolites. Estimated predictive accuracy was 65.4% (95% CI 46.2-80.1%). Sensitivity was 58.3% (95% CI: 32.0-80.7%) and specificity was 71.4% (95% CI: 45.4-88.3%).

Conclusion

This study found that a panel of urine metabolites could potentially discriminate primary from secondary FSGS. Further studies are needed to identify the unknown compounds. Understanding the differential expression of these metabolites could shed new insights into the biology of FSGS.

Figure. PLS-DA score plot of NMR spectra showing separation between patients with Primary and Secondary/Genetic FSGS.

Funding

  • Private Foundation Support