Abstract
Peripheral blood metabolite concentrations vary with food intake and time of day, risking confounding effects in metabolomics studies with non-standardised sampling conditions or incomplete metadata. Such effects are often overlooked during study design, limiting the clinical translation of biomarkers and wasting resources for researchers, funders and clinicians. In our random sample of 100 human metabolomics studies, 56% did not control for food intake, and 59% did not explicitly control for sampling time. To provide a study design resource, we analysed a liquid-chromatography–mass-spectrometry-targeted da-taset from controlled laboratory studies of 24 young, healthy participants (12 male, 12 female) sampled every 2 h for 34 h, with fixed-macronutrient meals provided at set times. Acute postprandial responses were quantified by effect size using pre-and post-meal windows , while daily rhythmicity was assessed using a mixed-effects cosinor model. Analyses were sex-stratified, and metabolites were classified as meal-responsive, time-of-day-responsive, both, or neither. Amino acids and their derivatives showed strong postpran-dial increases, whereas lipid classes showed minimal changes. Rhythmicity varied across metabolites, enabling the identification of features sensitive to meal timing and/or time of day. These results aim to provide a comprehensive dictionary of metabolite effect sizes for study design and metadata collection to support reproducibility and the clinical translation of potential biomarkers.