Assessment of short- and long-term biological variation for 39 serum metabolites using an NMR-based metabolomics approach

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 CV I and CV G 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 (CV A ) 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 CV I . Weekly and monthly CV I and CV G were similar, indicating stable metabolic variability over time. Sex-stratified analyses showed CV I 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.