Publication Date:
2019
Description:
Abstract
A limited understanding of inter‐ and intra‐subject 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 1263 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 (inter‐subject), time (intra‐subject) and noise (intra‐subject). Biomolecules such as CMPF, PDGF 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 to choose sampling times carefully.
This article is protected by copyright. All rights reserved.
Print ISSN:
0009-9236
Electronic ISSN:
1532-6535
Topics:
Chemistry and Pharmacology
,
Medicine
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