Journal Highlight: Efficient approach for the detection and identification of new androgenic metabolites by applying SRM GC-CI-MS/MS: a methandienone case study

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  • Published: Jul 11, 2016
  • Author: spectroscopyNOW
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thumbnail image: Journal Highlight: Efficient approach for the detection and identification of new androgenic metabolites by applying SRM GC-CI-MS/MS: a methandienone case study
The metabolism of methandienone was used as a case study to demonstrate the utility of a GC-CI/MS/MS method with selected reaction monitoring for finding new metabolites of anabolic steroids.

Efficient approach for the detection and identification of new androgenic metabolites by applying SRM GC-CI-MS/MS: a methandienone case study

Journal of Mass Spectrometry, 2016, 51, 524-534
Michael Polet, Wim Van Gansbeke, Peter Van Eenoo and Koen Deventer

Abstract: Identification of anabolic androgenic steroids (AAS) is a vital issue in doping control and toxicology, and searching for metabolites with longer detection times remains an important task. Recently, a gas chromatography chemical ionization triple quadrupole mass spectrometry (GC-CI-MS/MS) method was introduced, and CI, in comparison with electron ionization (EI), proved to be capable of increasing the sensitivity significantly. In addition, correlations between AAS structure and fragmentation behavior could be revealed. This enables the search for previously unknown but expected metabolites by selection of their predicted transitions. The combination of both factors allows the setup of an efficient approach to search for new metabolites. The approach uses selected reaction monitoring which is inherently more sensitive than full scan or precursor ion scan. Additionally, structural information obtained from the structure specific CI fragmentation pattern facilitates metabolite identification. The procedure was demonstrated by a methandienone case study. Its metabolites have been studied extensively in the past, and this allowed an adequate evaluation of the efficiency of the approach. Thirty three metabolites were detected, including all relevant previously discovered metabolites. In our study, the previously reported long-term metabolite (18-nor-17β-hydroxymethyl,17α-methyl-androst-1,4,13-trien-3-one) could be detected up to 26 days by using GC-CI-MS/MS. The study proves the validity of the approach to search for metabolites of new synthetic AAS and new long-term metabolites of less studied AAS and illustrates the increase in sensitivity by using CI.

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