Kidney Week

Abstract: PO1660

Integration of Plasma Proteomics and Metabolomics Revealed Multiple Protein-Metabolite Networks in Steroid-Resistant Nephrotic Pediatric Patients

Session Information

• Podocyte Injury in Human Disease: Pathomechanism, Diagnosis, and Therapy
  November 04, 2021 | Location: On-Demand, Virtual Only
  Abstract Time: 10:00 AM - 12:00 PM

Category: Glomerular Diseases

• 1201 Glomerular Diseases: Fibrosis and Extracellular Matrix

Authors

• Bhayana, Sagar, Nationwide Children's Hospital, Columbus, Ohio, United States

Sagar Bhayana, PhD

• Zhao, Yue, The Ohio State University Wexner Medical Center, Columbus, Ohio, United States

Yue Zhao,

• Merchant, Michael, University of Louisville, Louisville, Kentucky, United States

Michael Merchant,

• Cummins, Timothy, University of Louisville, Louisville, Kentucky, United States

Timothy Cummins,

• Pathmasiri, Wimal, University of North Carolina System, Chapel Hill, North Carolina, United States

Wimal Pathmasiri,

• Mcritchie, Susan, University of North Carolina System, Chapel Hill, North Carolina, United States

Susan Mcritchie,

• Sumner, Susan Jenkins, University of North Carolina System, Chapel Hill, North Carolina, United States

Susan Jenkins Sumner,

• Klein, Jon B., University of Louisville, Louisville, Kentucky, United States

Jon B. Klein,

• Smoyer, William E., Nationwide Children's Hospital, Columbus, Ohio, United States

William E. Smoyer,

Background

Nephrotic Syndrome (NS) is a common glomerular disease in children. Glucocorticoids (GC) are the mainstay of NS treatment, but steroid-resistant NS (SRNS) develops in 5-20% of children, dramatically increasing risk for progressive CKD vs. children with steroid sensitive NS (SSNS). There are no validated biomarkers able to predict which children will have SRNS. Here, we used previously published plasma proteomic and metabolomic profiles from children with SSNS and SRNS to test the hypothesis that integrating proteomic + metabolomic data could identify biomarkers and/or targets to define SRNS pathways that were not identified in the individual datasets.

Methods

Proteomic data from 15 paired NS plasma samples (n=7 SSNS; n=8 SRNS) and relative concentrations of metabolites estimated from plasma NMR metabolomics data from the same subjects underwent joint pathway analyses using MetaboAnalyst 5.0. software. Fold change (FC) was calculated as the ratio of pre-treatment to post-treatment for each protein and metabolite, and then log2 transformed. Proteins with Log₂FC<-10 or Log₂FC>10 and metabolites with Log₂FC<-1 or Log₂FC>1 were included in the analyses.

Results

Pathway analyses of proteomic data identified “ECM receptor interaction” and “focal adhesion” as the most significantly up- and down-regulated pathways in SRNS vs. SSNS, whereas “Valine, Leucine & Isoleucine biosynthesis”, and “Glycosaminoglycan biosynthesis” were the most up- and down-regulated metabolic pathways in SRNS, respectively. Integrated proteomic + metabolomic pathway analyses identified 3 metabolic pathways that were perturbed in SRNS but not in SSNS: 1) “Nicotinate & Nicotinamide” pathway was perturbed in 50% of SRNS subjects (4 SRNS vs. 0 SSNS), 2) “Butanoate” was perturbed in 37.5% of SRNS subjects (3 vs. 0), and 3) “Glycine, Serine & Threonine” metabolism was perturbed in 25% of SRNS subjects (2 vs. 0).

Conclusion

Integrating proteomic + metabolomic data from children with SRNS vs. SSNS have identified multiple pathways and protein-metabolite linkages with potential to become future candidate biomarkers or drug targets of SRNS