Laboratorio Antidoping, Federazione Medico Sportiva Italiana, Rome, Italy.
Institute of Pharmacy, Freie Universität Berlin, Berlin, Germany.
Rapid Commun Mass Spectrom. 2023 Jul 30;37(14):e9532. doi: 10.1002/rcm.9532.
The proposed metabolomic workflow, based on coupling high-resolution mass spectrometry with computational tools, can be an alternative strategy for metabolite detection and identification. This approach allows the extension of the investigation field to chemically different compounds, maximizing the information obtainable from the data and minimizing the time and resources required.
Urine samples were collected from five healthy volunteers before and after oral administration of 3β-hydroxyandrost-5-ene-7,17-dione as a model compound and defining three excretion time intervals. Raw data were acquired in both positive and negative ionization modes using an Agilent Technologies 1290 Infinity II series HPLC coupled to a 6545 Accurate-Mass Quadrupole Time-of-Flight. They were then processed to align peak retention times with the same accurate mass, and the resulting data matrix was subjected to multivariate analysis.
Multivariate analysis (PCA and PLS-DA models) demonstrated high similarity between samples belonging to the same collection time interval and clear discrimination between different excretion intervals. The blank and long excretion groups were distinguished, suggesting the presence of long excretion markers, which are of remarkable interest in anti-doping analyses. The correspondence of some significant features with metabolites reported in the literature confirmed the rationale and usefulness of the proposed metabolomic approach.
The presented study proposes a metabolomics workflow for the early detection and characterization of drug metabolites by untargeted urinary analysis to reduce the range of substances still excluded from routine screening. Its application has detected minor steroid metabolites, as well as unexpected endogenous alterations, proving to be an alternative strategy that can allow gathering a more complete range of information in the antidoping field.
基于将高分辨率质谱与计算工具相结合的代谢组学工作流程,可以作为检测和鉴定代谢物的替代策略。这种方法允许将研究领域扩展到化学性质不同的化合物,从而最大限度地提高数据中可获得的信息量,并最小化所需的时间和资源。
在口服 3β-羟基雄甾-5-烯-7,17-二酮作为模型化合物前后,从五名健康志愿者中收集尿液样本,并定义三个排泄时间间隔。使用安捷伦技术 1290 无限 II 系列 HPLC 与 6545 精确质量四极杆飞行时间联用,在正离子和负离子模式下采集原始数据。然后对其进行处理,使峰保留时间与相同精确质量对齐,所得数据矩阵进行多元分析。
多元分析(PCA 和 PLS-DA 模型)表明,同一采集时间间隔的样品之间具有高度相似性,不同排泄间隔之间具有明显的区分。空白和长排泄组被区分开来,表明存在长排泄标志物,这在反兴奋剂分析中具有重要意义。一些显著特征与文献中报道的代谢物相对应,证实了所提出的代谢组学方法的原理和实用性。
本研究提出了一种代谢组学工作流程,通过非靶向性尿液分析早期检测和表征药物代谢物,以减少仍被常规筛查排除的物质范围。其应用检测到了较小的类固醇代谢物,以及意外的内源性变化,证明这是一种替代策略,可以在反兴奋剂领域中收集更全面的信息。