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Kidney Week

Abstract: SA-PO455

Metabolite Predictors of CKD Progression in Children

Session Information

  • Pediatric Nephrology - II
    October 27, 2018 | Location: Exhibit Hall, San Diego Convention Center
    Abstract Time: 10:00 AM - 12:00 PM

Category: Pediatric Nephrology

  • 1600 Pediatric Nephrology

Authors

  • Denburg, Michelle, The Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Abraham, Alison G., Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States
  • Coresh, Josef, Welch Center for Prevention, Epidemiology & Clinical Research, Baltimore, Maryland, United States
  • Chen, Jingsha, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States
  • Grams, Morgan, Johns Hopkins University, Baltimore, Maryland, United States
  • Feldman, Harold I., University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Kimmel, Paul L., National Institute of Diabetes and Digestive Kidney Diseases (NIDDK), Bethesda, Maryland, United States
  • Rebholz, Casey, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States
  • Rhee, Eugene P., Massachusetts General Hospital, Newton, Massachusetts, United States
  • Ramachandran, Vasan S., Boston University School of Medicine, Framingham, Massachusetts, United States
  • Warady, Bradley A., Children's Mercy Kansas City , Kansas City, Missouri, United States
  • Furth, Susan L., The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States

Group or Team Name

  • for the CKD Biomarkers Consortium
Background

We sought to perform the first large-scale discovery of novel metabolite biomarkers of CKD progression in children.

Methods

We evaluated an untargeted GC/MS2 and LC/MS2-based metabolomics quantification (Metabolon) of baseline plasma samples from 587 Chronic Kidney Disease in Children (CKiD) participants. Cox proportional hazards and lognormal regression were used to examine the association between standardized, log transformed metabolites and progression to end stage kidney disease (ESKD: dialysis/transplant), adjusting for age, sex, race, body mass index, hypertension, anemia, glomerular (G) vs. non-glomerular (NG) diagnosis, serum albumin, proteinuria, and estimated glomerular filtration rate (eGFR). Stratified analyses were performed within G and NG subgroups.

Results

Cohort characteristics were: 354 male (60%); median age 12.3 years; median eGFR 53.2 mL/min/1.73m2; 409 (70%) NG diagnosis. 171 (29%) developed ESKD over a median observation time of 5.0 years (inter-quartile range 3.1-7.5). Of 949 known non-drug metabolites identified, 16 were associated with time to ESKD in both the fully adjusted Cox and lognormal models by the pathway specific false discovery rate threshold <0.05 (Figure). 13 were lipids and 6 were in the hexosylceramide pathway. 10 of the 16 metabolites remained associated in stratified analyses, mostly within the G subgroup, and the magnitude of the HR was generally greater than that for the full cohort. An additional 9 metabolites (4 in the lysoplasmalogen pathway) were identified in stratified analyses, predominantly within the G group.

Conclusion

Untargeted metabolomic profiling identified several novel metabolite biomarkers associated with CKD progression in children independent of established predictors, including hypertension, proteinuria and eGFR, and distinct from metabolites identified in adult studies. Further studies are needed to replicate these findings and delineate mechanism.

Funding

  • NIDDK Support