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Detection time comparison of non-hydrolysed sulfated metabolites of metenolone, mesterolone and 17α-methyltestosterone analysed by four different mass spectrometric techniques.

Aðalheiður Dóra AlbertsdóttirWim Van GansbekePeter Van EenooMichael Polet
Published in: Drug testing and analysis (2023)
The frequent detection of anabolic androgenic steroids (AAS) indicates their popularity among rule-breaking athletes. The so called long-term metabolites play a crucial role in their detection and non-hydrolysed sulfated metabolites have gained renewed interest as research has demonstrated their extended detection time compared to the more conventional markers (e.g. for metenolone and mesterolone). Their potential has been investigated using liquid and gas chromatography-mass spectrometry (LC- and GC-MS). However, due to their complementary nature, chances are that the most promising metabolite on one technique does not necessarily exhibit the same behaviour on the other and vice versa. Therefore, a comparison was carried out where as a trial model, metenolone, mesterolone and 17α-methyltestosterone were selected and the most likely long-term sulfated metabolites identified on four mass spectrometric instruments. Additionally, using a modified sample preparation procedure, comparison between conventional and non-hydrolysed sulfated metabolites between different GC-MS instruments was also included. When focusing on each individual marker no cases were observed where a single metabolite provided a superior detection time on all instruments. Furthermore, for each AAS there were incidences where a metabolite provided the best detection time on one instrument but could only be detected for a shorter period or not at all on other instruments. This demonstrates that metabolite detection windows and hence their added-value as target substance are unique and dependent on the analytical technique and not only on their pharmacokinetic behaviour. Consequently, in each case a metabolite vs. instrument evaluation is needed to maximise the probabilities of detecting doping offences.
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