A limited understanding of intersubject and intrasubject variability hampers effective biomarker translation from in vitro/in vivo studies to clinical trials and clinical decision support. Specifically, variability of biomolecule concentration can play an important role in interpretation, power analysis, and sampling time designation. In the present study, a wide range of 749 plasma metabolites, 62 urine biogenic amines, and 1,263 plasma proteins were analyzed in 10 healthy male volunteers measured repeatedly during 12 hours under tightly controlled conditions. Three variability components in relative concentration data are determined using linear mixed models: between (intersubject), time (intrasubject), and noise (intrasubject). Biomolecules such as 3-carboxy-4-methyl-5-propyl-2-furanpropanoate, platelet-derived growth factor C, and cathepsin D with low noise potentially detect changing conditions within a person. If also the between component is low, biomolecules can easier differentiate conditions between persons, for example cathepsin D, CD27 antigen, and prolylglycine. Variability over time does not necessarily inhibit translatability, but requires choosing sampling times carefully.
© 2019 The Authors Clinical Pharmacology & Therapeutics © 2019 American Society for Clinical Pharmacology and Therapeutics.