Variability of Two Metabolomic Platforms in CKD

CKD Biomarkers Consortium

Research output: Contribution to journalArticle

Abstract

BACKGROUND AND OBJECTIVES: Nontargeted metabolomics can measure thousands of low-molecular-weight biochemicals, but important gaps limit its utility for biomarker discovery in CKD. These include the need to characterize technical and intraperson analyte variation, to pool data across platforms, and to outline analyte relationships with eGFR. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Plasma samples from 49 individuals with CKD (eGFR<60 ml/min per 1.73 m2 and/or ≥1 g proteinuria) were examined from two study visits; 20 samples were repeated as blind replicates. To enable comparison across two nontargeted platforms, samples were profiled at Metabolon and the Broad Institute. RESULTS: The Metabolon platform reported 837 known metabolites and 483 unnamed compounds (selected from 44,953 unknown ion features). The Broad Institute platform reported 594 known metabolites and 26,106 unknown ion features. Median coefficients of variation (CVs) across blind replicates were 14.6% (Metabolon) and 6.3% (Broad Institute) for known metabolites, and 18.9% for (Metabolon) unnamed compounds and 24.5% for (Broad Institute) unknown ion features. Median CVs for day-to-day variability were 29.0% (Metabolon) and 24.9% (Broad Institute) for known metabolites, and 41.8% for (Metabolon) unnamed compounds and 40.9% for (Broad Institute) unknown ion features. A total of 381 known metabolites were shared across platforms (median correlation 0.89). Many metabolites were negatively correlated with eGFR at P<0.05, including 35.7% (Metabolon) and 18.9% (Broad Institute) of known metabolites. CONCLUSIONS: Nontargeted metabolomics quantifies >1000 analytes with low technical CVs, and agreement for overlapping metabolites across two leading platforms is excellent. Many metabolites demonstrate substantial intraperson variation and correlation with eGFR.

Original languageEnglish (US)
Pages (from-to)40-48
Number of pages9
JournalClinical journal of the American Society of Nephrology : CJASN
Volume14
Issue number1
DOIs
StatePublished - Jan 7 2019

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Metabolomics
Biomarkers
Molecular Weight

Keywords

  • biomarker
  • chronic kidney disease
  • EGFR protein
  • Epidermal Growth Factor
  • glomerular filtration rate
  • human
  • metabolomics
  • Molecular Weight
  • proteinuria
  • Receptor
  • Renal Insufficiency, Chronic

ASJC Scopus subject areas

  • Epidemiology
  • Critical Care and Intensive Care Medicine
  • Nephrology
  • Transplantation

Cite this

Variability of Two Metabolomic Platforms in CKD. / CKD Biomarkers Consortium.

In: Clinical journal of the American Society of Nephrology : CJASN, Vol. 14, No. 1, 07.01.2019, p. 40-48.

Research output: Contribution to journalArticle

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author = "{CKD Biomarkers Consortium} and Rhee, {Eugene P.} and Waikar, {Sushrut S.} and Casey Rebholz and Zihe Zheng and Regis Perichon and Clish, {Clary B.} and Evans, {Anne M.} and Julian Avila and Denburg, {Michelle R.} and Anderson, {Amanda Hyre} and Vasan, {Ramachandran S.} and Feldman, {Harold I.} and Kimmel, {Paul L.} and Josef Coresh",
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AU - Waikar, Sushrut S.

AU - Rebholz, Casey

AU - Zheng, Zihe

AU - Perichon, Regis

AU - Clish, Clary B.

AU - Evans, Anne M.

AU - Avila, Julian

AU - Denburg, Michelle R.

AU - Anderson, Amanda Hyre

AU - Vasan, Ramachandran S.

AU - Feldman, Harold I.

AU - Kimmel, Paul L.

AU - Coresh, Josef

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N2 - BACKGROUND AND OBJECTIVES: Nontargeted metabolomics can measure thousands of low-molecular-weight biochemicals, but important gaps limit its utility for biomarker discovery in CKD. These include the need to characterize technical and intraperson analyte variation, to pool data across platforms, and to outline analyte relationships with eGFR. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Plasma samples from 49 individuals with CKD (eGFR<60 ml/min per 1.73 m2 and/or ≥1 g proteinuria) were examined from two study visits; 20 samples were repeated as blind replicates. To enable comparison across two nontargeted platforms, samples were profiled at Metabolon and the Broad Institute. RESULTS: The Metabolon platform reported 837 known metabolites and 483 unnamed compounds (selected from 44,953 unknown ion features). The Broad Institute platform reported 594 known metabolites and 26,106 unknown ion features. Median coefficients of variation (CVs) across blind replicates were 14.6% (Metabolon) and 6.3% (Broad Institute) for known metabolites, and 18.9% for (Metabolon) unnamed compounds and 24.5% for (Broad Institute) unknown ion features. Median CVs for day-to-day variability were 29.0% (Metabolon) and 24.9% (Broad Institute) for known metabolites, and 41.8% for (Metabolon) unnamed compounds and 40.9% for (Broad Institute) unknown ion features. A total of 381 known metabolites were shared across platforms (median correlation 0.89). Many metabolites were negatively correlated with eGFR at P<0.05, including 35.7% (Metabolon) and 18.9% (Broad Institute) of known metabolites. CONCLUSIONS: Nontargeted metabolomics quantifies >1000 analytes with low technical CVs, and agreement for overlapping metabolites across two leading platforms is excellent. Many metabolites demonstrate substantial intraperson variation and correlation with eGFR.

AB - BACKGROUND AND OBJECTIVES: Nontargeted metabolomics can measure thousands of low-molecular-weight biochemicals, but important gaps limit its utility for biomarker discovery in CKD. These include the need to characterize technical and intraperson analyte variation, to pool data across platforms, and to outline analyte relationships with eGFR. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Plasma samples from 49 individuals with CKD (eGFR<60 ml/min per 1.73 m2 and/or ≥1 g proteinuria) were examined from two study visits; 20 samples were repeated as blind replicates. To enable comparison across two nontargeted platforms, samples were profiled at Metabolon and the Broad Institute. RESULTS: The Metabolon platform reported 837 known metabolites and 483 unnamed compounds (selected from 44,953 unknown ion features). The Broad Institute platform reported 594 known metabolites and 26,106 unknown ion features. Median coefficients of variation (CVs) across blind replicates were 14.6% (Metabolon) and 6.3% (Broad Institute) for known metabolites, and 18.9% for (Metabolon) unnamed compounds and 24.5% for (Broad Institute) unknown ion features. Median CVs for day-to-day variability were 29.0% (Metabolon) and 24.9% (Broad Institute) for known metabolites, and 41.8% for (Metabolon) unnamed compounds and 40.9% for (Broad Institute) unknown ion features. A total of 381 known metabolites were shared across platforms (median correlation 0.89). Many metabolites were negatively correlated with eGFR at P<0.05, including 35.7% (Metabolon) and 18.9% (Broad Institute) of known metabolites. CONCLUSIONS: Nontargeted metabolomics quantifies >1000 analytes with low technical CVs, and agreement for overlapping metabolites across two leading platforms is excellent. Many metabolites demonstrate substantial intraperson variation and correlation with eGFR.

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KW - proteinuria

KW - Receptor

KW - Renal Insufficiency, Chronic

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