Evaluation of novel candidate filtration markers from a global metabolomic discovery for glomerular filtration rate estimation

Nora F. Fino, Ogechi M. Adingwupu, Josef Coresh, Tom Greene, Ben Haaland, Michael G. Shlipak, Veronica T. Costa e Silva, Roberto Kalil, Ayse L. Mindikoglu, Susan L. Furth, Jesse C. Seegmiller, Andrew S. Levey, Lesley A. Inker

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Creatinine and cystatin-C are recommended for estimating glomerular filtration rate (eGFR) but accuracy is suboptimal. Here, using untargeted metabolomics data, we sought to identify candidate filtration markers for a new targeted assay using a novel approach based on their maximal joint association with measured GFR (mGFR) and with flexibility to consider their biological properties. We analyzed metabolites measured in seven diverse studies encompasing 2,851 participants on the Metabolon H4 platform that had Pearson correlations with log mGFR and used a stepwise approach to develop models to < —0.5 estimate mGFR with and without inclusion of creatinine that enabled selection of candidate markers. In total, 456 identified metabolites were present in all studies, and 36 had correlations with mGFR < —0.5. A total of 2,225 models were developed that included these metabolites; all with lower root mean square errors and smaller coefficients for demographic variables compared to estimates using untargeted creatinine. Seventeen metabolites were chosen, including 12 new candidate filtration markers. The selected metabolites had strong associations with mGFR and little dependence on demographic factors. Candidate metabolites were identified with maximal joint association with mGFR and minimal dependence on demographic variables across many varied clinical settings. These metabolites are excreted in urine and represent diverse metabolic pathways and tubular handling. Thus, our data can be used to select metabolites for a multi-analyte eGFR determination assay using mass spectrometry that potentially offers better accuracy and is less prone to non-GFR determinants than the current eGFR biomarkers.

Original languageEnglish (US)
Pages (from-to)582-592
Number of pages11
JournalKidney international
Volume105
Issue number3
StatePublished - Mar 2024

Bibliographical note

Publisher Copyright:
© 2023 International Society of Nephrology

Keywords

  • filtration markers
  • glomerular filtration rate
  • metabolomics

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