Summary of project PR000648

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000648. The data can be accessed directly via it's Project DOI: 10.21228/M8X38B This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

Project ID: PR000648
Project DOI:doi: 10.21228/M8X38B
Project Title:Defining and Predicting Steroid-Resistance in Children with Nephrotic Syndrome by Metabolic Profiling
Project Type:Metabolomics
Project Summary:Nephrotic syndrome (NS) is a very common kidney disease in children. Glucocorticoids (GC) are the primary therapy, but are ineffective in ~20% of children and ~50% of adult cases. Patients with steroid resistant NS (SRNS) fail to enter remission after prolonged oral GC treatment, and are at high risk for GC-induced side effects and progression to end-stage kidney disease. This study aimed to discover markers of steroid resistance that could be potentially used to predict SRNS at presentation, and develop an improved mechanistic definition of pediatric SRNS. Plasma samples were collected from 30 steroid sensitive NS (SSNS) and 15 SRNS patients, and paired samples analyzed which were collected both at disease presentation, prior to any steroid therapy, and after ~7 weeks of daily GC treatment. Broad spectrum 1HNMR data were acquired, binned, and concentration fit. Multivariate analyses and hypothesis testing were used to determine the metabolites that best differentiated the four phenotypic groups. Treatment effects on metabolomics profiles were observed between paired Pre- and Post- treatment SSNS groups, and between Post SSNS and SRNS groups. Metabolites most perturbed by GC treatment included lipoproteins , adipate, pyruvate, alanine, creatine, glucose, tyrosine, valine, and glutamine. Logistic regression using a stepwise variable selection method was used on Pre- samples to model the odds at clinical presentation of SRNS. After controlling for age, the step-wise logistic regression model selected increased glutamine (OR= 1.01; 0.99-1.02 95% CI) as a marker of SRNS. A similar model with children age >3 only, indicated that children with reduced levels of malonate (OR=0.94; 0.89-1.00 95% CI) had an increased odds of SRNS . Thus, malonate concentration may be a potential plasma biomarker for identifying SRNS at initial clinical presentation.
Institute:The Ohio State University;Nationwide Children’s Hospital
Department:Department of Pediatrics and Center for Clinical and Translational Research
Last Name:Smoyer; Agrawal
First Name:William; Shipra
Address:700 Children's Drive, Columbus, OH 43205
Email:William.Smoyer@nationwidechildrens.org and shipra.agrawal@nationwidechildrens.org
Phone:(614) 722-4360
Funding Source:NIH Grants 1UMDK10086601, 1U24DK097193, and 7K01GM109320

Summary of all studies in project PR000648

Study IDStudy TitleSpeciesInstituteAnalysis
(* : Contains Untargted data)
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(* : Contains raw data)
ST000939 Predicting and Defining Steroid Resistance in Pediatric Nephrotic Syndrome using Plasma Metabolomics Homo sapiens RTI International NMR 2019-03-06 1 90 Uploaded data (46.4M)*
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