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Abstract: TH-PO448

Patient-Specific Multi-Omic Analysis of Plasma Proteomics and Metabolomics of Steroid Resistance in Childhood Nephrotic Syndrome

Session Information

Category: Glomerular Diseases

  • 1302 Glomerular Diseases: Immunology and Inflammation

Authors

  • Bhayana, Sagar, Novo Nordisk AS, Bagsvaerd, Hovedstaden, Denmark
  • Zhao, Yue, The Ohio State University, Columbus, Ohio, United States
  • Merchant, Michael, University of Louisville, Louisville, Kentucky, United States
  • Cummins, Timothy, University of Louisville, Louisville, Kentucky, United States
  • Dougherty, Julie, Nationwide Children's Hospital, Columbus, Ohio, United States
  • Kamigaki, Yu, Nationwide Children's Hospital, Columbus, Ohio, United States
  • Pathmasiri, Wimal, University of North Carolina System, Chapel Hill, North Carolina, United States
  • Mcritchie, Susan, University of North Carolina System, Chapel Hill, North Carolina, United States
  • Mariani, Laura H., University of Michigan, Ann Arbor, Michigan, United States
  • Sumner, Susan Jenkins, University of North Carolina System, Chapel Hill, North Carolina, United States
  • Klein, Jon B., University of Louisville, Louisville, Kentucky, United States
  • Smoyer, William E., Nationwide Children's Hospital, Columbus, Ohio, United States
Background

Nephrotic syndrome (NS) is a clinical syndrome defined by massive proteinuria. Glucocorticoid (GC) therapy is the mainstay therapy for inducing remission, but 20-30% of children present with or develop GC resistance. Unfortunately, we lack both effective treatments for steroid resistant NS (SRNS) and clinically validated biomarkers to predict SRNS vs. steroid sensitive NS (SSNS) at presentation. To bridge this gap, we performed a patient-specific integrated analysis of published plasma proteomics and metabolomics data from children with SRNS and SSNS.

Methods

Proteomic LC-MS/MS and metabolomic NMR data from 15 paired (pre-and post-GC treated) NS plasma samples (n=7 SSNS; n=8 SRNS) underwent joint pathway analyses using MetaboAnalystR v3.0. The Log2 fold change (LFC) was calculated as the ratio of post- to pre-GC-treatment. Proteins with LFC<-10 or >10 and metabolites with LFC<-1 or >1 were included. An enrichment index was calculated by:[(#SRNS w/ pathway activated/ Total #SRNS)-(#SSNS w/ pathway activated/ Total #SSNS)]x100%.

Results

Hypergeometric analyses identified 34 pathways (P<0.005) that were enriched in post- vs pre-GC-treated SRNS and/or SSNS patients. Using ±25% cut-off as an enrichment index, 12 of 34 pathways were enriched in SRNS and/or SSNS patients, narrowed to 5 pathways with enrichment in at least 3 patients within either group. Nicotinate/ Nicotinamide pathway & Butanoate metabolism were frequently enriched in SRNS patients, whereas Lysine metabolism, Mucin type O-glycan biosynthesis, & Glycolysis/ Gluconeogenesis were frequently enriched in SSNS patients. In-depth pathway network analyses performed in each patient indicated NAMPT, NMNAT1, NT5C2, SETMAR and 3-hydroxybutyrate as more frequently upregulated in SRNS patients, while ALDH1B1, ACAT1, AASS, ENPP1 and Pyruvate were more frequently upregulated in SSNS patients. Subsequent immunoblotting of the same plasma samples validated significant upregulations of NAMPT in SRNS and ALDH1B1/ACAT1 in SSNS.

Conclusion

These findings demonstrate the ability of patient-specific integration of omics data to distinguish pathway alterations in SRNS vs. SSNS, and highlight potentially distinct perturbations in energy metabolism between these groups.

Funding

  • NIDDK Support