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Updated: Jun 28, 2025

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Published on: April 23, 2019
Methylation of phase II metabolites of endogenous anabolic androgenic steroids to improve analytical performance
Sandra Pfeffer1,2, Guenter Gmeiner2, Guro Forsdahl1,2
1Department of Pharmacy, UiT - The Arctic University of Norway, Tromsø, Norway.
Abstract:
The study of intact phase II metabolites of endogenous anabolic androgenic steroids (EAAS) gives important information about metabolism and has the potential to improve the detection of doping with testosterone. For analysis with liquid chromatography-mass spectrometry (LC-MS), chemical derivatization at the steroid moiety is a technique to improve the positive ionization efficiency of glucuronidated/sulfated EAAS under collision-induced dissociation (CID) conditions. However, regarding the chromatographic performance, there are still challenges to address, for example, poor peak shape, which is mainly caused by nondefined adsorption in the chromatographic system. Here, we show a novel derivatization technique for the analysis of selected phase II metabolites of EAAS, where the acidic moiety of the glucuronide/sulfate is methylated with different methylation reagents to reduce nondefined adsorption. The methylation reagent trimethylsilyl-diazomethane (TMSD) was preferred over the other tested reagents methyl iodide (MeI) and dimethyl sulfate (DMS). Glucuronidated and sulfated testosterone and epitestosterone were methylated, and their chromatographic performance and CID ion mass spectra obtained in positive ionization mode were investigated. The peak width and peak height were significantly improved for all substances. Methylated testosterone sulfate showed the best results with a 3.5 times narrower peak and 14 times increased intensity compared with underivatized testosterone sulfate. Furthermore, CID ion mass spectra obtained in positive ionization mode showed product ions characteristically for the steroidal backbone for all substances. This preliminary study shows the potential of methylation as a supplementary derivatization technique, which can assist in the development of more sensitive methods due to the improvements in method performance.
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