Separation of Structurally Similar Anabolic Steroids as Cation Adducts in FAIMS-MS / Michael S Wei, Robin H J Kemperman, Michelle A Palumbo, Richard A Yost. - (Journal of the American Society for Mass Spectrometry 31 (2020) 2 (5 February); p. 355-365)
- PMID: 32031405.
- DOI: 10.1021/jasms.9b00127
Novel synthetic anabolic androgenic steroids have been developed not only to dodge current antidoping tests at the professional sports level, but also for consumption by noncompetitive bodybuilders. These novel anabolic steroids are commonly referred to as "designer steroids" and pose a significant risk to users because of the lack of testing for toxicity and safety in animals or humans. Manufacturers of designer steroids dodge regulation by distributing them as nutritional or dietary supplements. Improving the throughput and accuracy of screening tests would help regulators to stay on top of illicit anabolic steroids. High-field asymmetric-waveform ion mobility spectrometry (FAIMS) utilizes an alternating asymmetric electric field to separate ions by their different mobilities at high- and low-fields as they travel through the separation space. When coupled to mass spectrometry (MS), FAIMS enhances the separation of analytes from other interfering compounds with little to no increase in analysis time. Here we investigate the effects of adding various cation species to sample solutions for the separation of structurally similar or isomeric anabolic androgenic steroids. FAIMS-MS spectra for these cation-modified samples show an increased number of compensation field (CF) peaks, some of which are confirmed to be unique for one steroid isomer over another. The CF peaks observed upon addition of cation species correspond to both monomer steroid-cation adduct ions and larger multimer ion complexes. Notably, the number of CF peaks and their CF shifts do not appear to have a straightforward relationship with cation size or electronegativity. Future directions aim at investigating the structures for these analyte-cation adduct ions for building a predictive model for their FAIMS separations.