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Updated: Oct 24, 2026
Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
Published on: November 29, 2024
Assessment of short- and long-term biological variation for 39 serum metabolites using an NMR-based metabolomics
Manon Campas1,2, Caroline Le Goff1,2, Pascal de Tullio1,2
1Clinical Metabolomics Group (CliMe), Centre for Interdisciplinary Research on Medicines (CIRM), University of Liège, Liège, Belgium.
Objectives:
As personalized medicine expands, metabolomics may support clinical decision-making. However, its integration in routine requires biological variation (BV) data, which remain scarce. Here, we aimed to generate short- and long-term CVI and CVG components, index of individuality (II), reference change values (RCV) and analytical performance specifications (APS) for serum metabolites quantified by NMR spectroscopy.
Methods:
Thirty healthy individuals (14 males, 16 females; age 23-40 years) provided serum weekly for 10 weeks and monthly for 10 months, following European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) Working Group on Biological Variation recommendations. Thirty-nine metabolites were quantified by NMR, while creatinine was also measured enzymatically. Analytical variation (CVA) was calculated from pooled samples. Outliers and trends were evaluated before CV-ANOVA to determine BV estimates with confidence intervals (CIs), II, RCVs, number of specimens estimating the individual's homeostatic set point, and APS.
Results:
NMR-based creatinine BV components aligned with enzymatic results. Comparison with EFLM BV meta-analysis agreed strongly for ascorbate, creatinine, and glucose, while urea exhibited higher CVI. Weekly and monthly CVI and CVG were similar, indicating stable metabolic variability over time. Sex-stratified analyses showed CVI differences for some metabolites, but most CIs overlapped. Eight metabolites exceeded APS for imprecision, six showed II <0.6, and RCVs varied widely across metabolites.
Conclusions:
This study provides method-dependent short- and long-term BV estimates for 39 serum metabolites measured by NMR. These data provide a framework for interpreting metabolomic measurements based on BV but require independent analytical and clinical validation before clinical application.
