title: The use of metabolomics for the discovery of new biomarkers of effect.
abstract: Will metabolomics have a greater chance of success in toxicology and biomarker assessment than genomics and proteomics? Metabolomics has the advantage that (1) it analyses the last step in a series of changes following a toxic insult, (2) many of the metabolites have a known function and (3) changes are detectable in blood. If the analysis of a great number of individual organs can be replaced by one matrix then this will provide significant advantages (less invasive method, no need to kill animals, time course analysis possible). We have chosen to perform the analysis of blood metabolites in such a way as to minimize the risk of artifacts and to have a high number of known metabolites. We have also reduced the amount of variation in the biological system as well as during analysis. In a series of proof of concept studies it could be demonstrated that (1) the metabolome of control animals was stable of a period of nearly 1 year, with a remarkable differentiation between males and females, (2) a dose response relationship in metabolome changes was induced by phenobarbital and that (3) different modes of action could be distinguished by blood metabolome analysis. To investigate the potential of metabolomics to find biomarkers or specific patterns of change we have analyzed the blood metabolome of rats treated with HPPD inhibitors, a novel class of herbicides. The results demonstrated that a single metabolite, tyrosine, can be used as a biomarker. In addition to tyrosine we also found a specific pattern of change that involved nine metabolites. Though the extent of change was less than for tyrosine the consistent change of these metabolites is diagnostic for this (toxicological) mode of action.
authors.affiliation: BASF Aktiengesellschaft, Experimental Toxicology and Ecology, Z 470, D-67056 Ludwigshafen, Germany. bennard.ravenzwaay@basf.com
authors.forename: B
authors.initials: B
authors.lastname: van Ravenzwaay
authors.forename: G Coelho-Palermo
authors.initials: GC
authors.lastname: Cunha
authors.forename: E
authors.initials: E
authors.lastname: Leibold
authors.forename: R
authors.initials: R
authors.lastname: Looser
authors.forename: W
authors.initials: W
authors.lastname: Mellert
authors.forename: A
authors.initials: A
authors.lastname: Prokoudine
authors.forename: T
authors.initials: T
authors.lastname: Walk
authors.forename: J
authors.initials: J
authors.lastname: Wiemer
mesh_terms: D015111:4-Hydroxyphenylpyruvate Dioxygenase / Q000037:antagonists & inhibitors / Q000378:metabolism; D000726:Androgen Antagonists / Q000633:toxicity; D000818:Animals; D013956:Antithyroid Agents / Q000633:toxicity; D015415:Biomarkers / Q000097:blood*; D002853:Chromatography, Liquid; D004305:Dose-Response Relationship, Drug; D004790:Enzyme Induction; D004791:Enzyme Inhibitors / Q000633:toxicity; D005260:Female; D005485:Flutamide / Q000633:toxicity; D008401:Gas Chromatography-Mass Spectrometry; D006540:Herbicides / Q000633:toxicity; D008099:Liver / Q000187:drug effects / Q000201:enzymology; D008297:Male; D053858:Metabolic Networks and Pathways / Q000187:drug effects*; D010634:Phenobarbital / Q000633:toxicity; D011441:Propylthiouracil / Q000633:toxicity; D051381:Rats; D017208:Rats, Wistar; D015203:Reproducibility of Results; D012737:Sex Factors; D049490:Systems Biology; D053719:Tandem Mass Spectrometry; D013997:Time Factors; D014116:Toxicology / Q000379:methods* / Q000592:standards; D014443:Tyrosine / Q000097:blood
chemical_list: D000726:Androgen Antagonists; D013956:Antithyroid Agents; D015415:Biomarkers; D004791:Enzyme Inhibitors; D006540:Herbicides; D014443:Tyrosine; D011441:Propylthiouracil; D005485:Flutamide; D015111:4-Hydroxyphenylpyruvate Dioxygenase; D010634:Phenobarbital