The Technical Document TD2014EAAS was drafted by the World Anti-Doping Agency (WADA) in order to fight the spread of endogenous anabolic androgenic steroids (EAAS) misuse in several sport disciplines. In particular, adoption of the so-called Athlete Biological Passport (ABP) - Steroidal Module allowed control laboratories to identify anomalous EAAS concentrations within the athletes' physiological urinary steroidal profile. Gas chromatography (GC) combined with mass spectrometry (MS), indicated by WADA as an appropriate technique to detect urinary EAAS, was utilized in the present study to develop and fully-validate an analytical method for the determination of all EAAS markers specified in TD2014EAAS, plus two further markers hypothetically useful to reveal microbial degradation of the sample. In particular, testosterone, epitestosterone, androsterone, etiocholanolone, 5α-androstane-3α,17β-diol, 5β-androstane-3α,17β-diol, dehydroepiandrosterone, 5α-dihydrotestosterone, were included in the analytical method. Afterwards, the multi-parametric feature of ABP profile was exploited to develop a robust approach for the detection of EAAS misuse, based on multivariate statistical analysis. In particular, Principal Component Analysis (PCA) was combined with Hotelling T(2) tests to explore the EAAS data obtained from 60 sequential urine samples collected from six volunteers, in comparison with a reference population of single urine samples collected from 96 volunteers. The new approach proved capable of identifying anomalous results, including (i) the recognition of samples extraneous to each of the individual urine series and (ii) the discrimination of the urine samples collected from individuals to whom "endogenous" steroids had been administrated with respect to the rest of the samples population. The proof-of-concept results presented in this study will need further extension and validation on a population of sport professionals.
Detection of new psychoactive substances and synthetic opioids is generally performed by means of targeted methods in mass spectrometry, as they generally provide adequate sensitivity and specificity. Unfortunately, new and unexpected compounds are continuously introduced in the illegal market of abused drugs, preventing timely updating of the analytical procedures. Moreover, the investigation of biological matrices is influenced by metabolism and excretion, in turn affecting the chance of past intake detectability. In this scenario, new opportunities are offered by both the non-targeted approaches allowed by modern UHPLC-HRMS instrumentation and the investigation of hair as the matrix of choice to detect long-term exposure to toxicologically relevant substances. In this study, we present a comprehensive and validated workflow that combines the use of UHPLC-QTOF-HRMS instrumentation with a simple hair sample extraction procedure for the detection of a variety of fentanyl analogues and metabolites. A simultaneous targeted and untargeted analysis was applied to 100 real samples taken from opiates users. MS and MS/MS data were collected for each sample. Data acquisition included a TOF-MS high-resolution scan combined with TOF-MS/MS acquisition demonstrating considerable capability to detect expected and unexpected substances even at low concentration levels. The predominant diffusion of fentanyl was confirmed by its detection in 68 hair samples. Other prevalent analogues were furanylfentanyl (28 positive samples) and acetylfentanyl (14 positive samples). Carfentanil, methylfentanyl, and ocfentanil were not found in any of the analyzed samples. Furthermore, the retrospective data analysis based on untargeted acquisition allowed the identification of two fentanyl analogues, namely β-hydroxyfentanyl and methoxyacetylfentanyl, which were not originally included in the panel of targeted analytes.
The steroidal module of the athlete biological passport (ABP) introduced by the World Anti‐Doping Agency (WADA) in 2014 includes six endogenous androgenic steroids and five of their concentration ratios, monitored in urine samples collected repeatedly from the same athlete, whose values are interpreted by a Bayesian model on the basis of intra‐individual variability. The same steroid profile, plus dihydrotestosterone (DHT) and DHEA, was determined in 198 urine samples collected from an amateur marathon runner monitored over three months preceding an international competition. Two to three samples were collected each day and subsequently analyzed by a fully validated gas chromatography–mass spectrometry protocol. The objective of the study was to identify the potential effects of physical activity at different intensity levels on the physiological steroid profile of the athlete. The results were interpreted using principal component analysis and Hotelling's T2 vs Q residuals plots, and were compared with a profile model based on the samples collected after rest. The urine samples collected after activity of moderate or high intensity, in terms of cardiac frequency and/or distance run, proved to modify the basal steroid profile, with particular enhancement of testosterone, epitestosterone, and 5α‐androstane‐3α,17β‐diol. In contrast, all steroid concentration ratios were apparently not modified by intense exercise. The alteration of steroid profiles seemingly lasted for few hours, as most of the samples collected 6 or more hours after training showed profiles compatible with the “after rest” model. These observations issue a warning about the ABP results obtained immediately post‐competition.
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