Multiomics Analysis of Plasma Proteomics and Metabolomics of Steroid Resistance in Childhood Nephrotic Syndrome Using a "Patient-Specific" Approach

Sagar Bhayana; Yue Zhao; Michael Merchant; Timothy Cummins; Julie A Dougherty; Yu Kamigaki; Wimal Pathmasiri; Susan McRitchie; Laura H Mariani; Susan Sumner; Jon B Klein; Lang Li; William E Smoyer; Pediatric Nephrology Research Consortium

doi:10.1016/j.ekir.2023.03.015

Multiomics Analysis of Plasma Proteomics and Metabolomics of Steroid Resistance in Childhood Nephrotic Syndrome Using a "Patient-Specific" Approach

Kidney Int Rep. 2023 Mar 23;8(6):1239-1254. doi: 10.1016/j.ekir.2023.03.015. eCollection 2023 Jun.

Authors

Collaborators

Pediatric Nephrology Research Consortium:
John Mahan, Hiren Patel, Richard F Ransom, Cynthia Pan, Denis F Geary, Myra L Chang, Keisha L Gibson, Franca M Iorember, Patrick D Brophy, Tarak Srivastava, Larry A Greenbaum

Affiliations

¹ Center for Clinical and Translational Research, Nationwide Children's Hospital; Columbus, Ohio, USA.
² Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, USA.
³ Department of Medicine, Division of Nephrology and Hypertension, University of Louisville; Louisville, Kentucky, USA.
⁴ Department of Nutrition, Nutrition Research Institute, University of North Carolina at Chapel Hill; Kannapolis, North Carolina, USA.
⁵ Division of Nephrology, Department of Internal Medicine, Michigan Medicine, Ann Arbor, Michigan, USA.
⁶ Robley Rex VA Medical Center, Louisville, Kentucky, USA.
⁷ Department of Pediatrics, College of Medicine, The Ohio State University, Columbus, Ohio, USA.

Abstract

Introduction: Nephrotic syndrome (NS) occurs commonly in children with glomerular disease and glucocorticoids (GCs) are the mainstay treatment. Steroid resistant NS (SRNS) develops in 15% to 20% of children, increasing the risk of chronic kidney disease compared to steroid sensitive NS (SSNS). NS pathogenesis is unclear in most children, and no biomarkers exist that predict the development of pediatric SRNS.

Methods: We studied a unique patient cohort with plasma specimens collected before GC treatment, yielding a disease-only sample not confounded by steroid-induced gene expression changes (SSNS n = 8; SRNS n = 7). A novel "patient-specific" bioinformatic approach merged paired pretreatment and posttreatment proteomic and metabolomic data and identified candidate SRNS biomarkers and altered molecular pathways in SRNS versus SSNS.

Results: Joint pathway analyses revealed perturbations in nicotinate or nicotinamide and butanoate metabolic pathways in patients with SRNS. Patients with SSNS had perturbations of lysine degradation, mucin type O-glycan biosynthesis, and glycolysis or gluconeogenesis pathways. Molecular analyses revealed frequent alteration of molecules within these pathways that had not been observed by separate proteomic and metabolomic studies. We observed upregulation of NAMPT, NMNAT1, and SETMAR in patients with SRNS, in contrast to upregulation of ALDH1B1, ACAT1, AASS, ENPP1, and pyruvate in patients with SSNS. Pyruvate regulation was the change seen in our previous analysis; all other targets were novel. Immunoblotting confirmed increased NAMPT expression in SRNS and increased ALDH1B1 and ACAT1 expression in SSNS, following GC treatment.

Conclusion: These studies confirmed that a novel "patient-specific" bioinformatic approach can integrate disparate omics datasets and identify candidate SRNS biomarkers not observed by separate proteomic or metabolomic analysis.

Keywords: MetaboAnalystR; biomarker; informatics; nephrosis; personalized; steroid resistance.

Abstract

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