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In the European Union, the use of thyreostats for animal fattening purposes has been banned and monitoring plans have been established to detect potential abuse. However, this is not always straightforward as thyreostats such as thiouracil may also have a semi-endogenous origin. Therefore, this study aimed at defining urinary metabolites, which may aid in defining the origin of detected thiouracil. Hereto, a parallel-like randomized in vivo study was conducted in which calves (n = 8) and cows (n = 8) were subjected to either a control treatment, rapeseed-enriched diet to induce semi-endogenous formation, or thiouracil treatment. Urine samples (n = 330) were assessed through metabolic fingerprinting, employing liquid-chromatography and Q-ExactiveTM Orbitrap mass spectrometry. Urinary fingerprints comprised up to 40,000 features whereby multivariate discriminant analysis was able to point out significant metabolome differences between treatments (Q2(Y) ≥ 0.873). Using the validated models, a total of twelve metabolites (including thiouracil) were assigned marker potential. Combining these markers into age-dependent biomarker panels rendered a tool by which sample classification could be improved in comparison with thiouracil-based thresholds, and this during on-going thiouracil treatment (specificities ≥ 95.2% and sensitivities ≥ 85.7%), post-treatment (sensitivities ≥ 80% for ≥ 24 h after last administration), and simulated low-dose thiouracil treatment (exogenous thiouracil below 30 ng μL-1). Moreover, the metabolic relevance of revealed markers was supported by the suggested identities, for which a structural link with thiouracil could be determined in most cases. The proposed biomarker panels may contribute to a more justified decision-making in monitoring thiouracil abuse. [ABSTRACT FROM AUTHOR]

We have detected differences in metabolite levels between doped athletes, clean athletes, and volunteers (non athletes). This outcome is obtained by comparing results of measurements from two analytical platforms: UHPLC-QTOF/MS and FT-ICR/MS. Twenty-seven urine samples tested positive for glucocorticoids or beta-2-agonists and twenty samples coming from volunteers and clean athletes were analyzed with the two different mass spectrometry approaches using both positive and negative electrospray ionization modes. Urine is a highly complex matrix containing thousands of metabolites having different chemical properties and a high dynamic range. We used multivariate analysis techniques to unravel this huge data set. Thus, the several groups we created were studied by Principal Components Analysis (PCA) and Partial Least Square regression (PLS-DA and OPLS) in the search of discriminating m/z values. The selected variables were annotated and placed on pathway by using MassTRIX. [ABSTRACT FROM AUTHOR]