Recent advances in mass spectrometry for the detection of doping

INTRODUCTION

The analysis of doping control samples is preferably performed by mass spectrometry, because obtained results meet the highest analytical standards and ensure an impressive degree of reliability. The advancement in mass spectrometry and all its associated technologies thus allow for continuous improvements in doping control analysis.

AREAS COVERED

Modern mass spectrometric systems have reached a status of increased sensitivity, robustness, and specificity within the last decade. The improved sensitivity in particular has, on the other hand, also led to the detection of drug residues that were attributable to scenarios where the prohibited substances were not administered consciously but rather by the unconscious ingestion of or exposure to contaminated products. These scenarios and their doubtless clarification represent a great challenge. Here, too, modern MS systems and their applications can provide good insights in the interpretation of dose-related metabolism of prohibited substances. In addition to the development of new instruments itself, software-assisted analysis of the sometimes highly complex data is playing an increasingly important role and facilitating the work of doping control laboratories.

EXPERT OPINION

The sensitive analysis and evaluation of a higher number of samples in a shorter time is made possible by the ongoing developments in mass spectrometry.

A practical strategy enabling more reliable identification of ginsenosides from Panax quinquefolius flower by dimension-enhanced liquid chromatography/mass spectrometry and quantitative structure-retention relationship-based retention behavior prediction

To accurately identify the metabolites is crucial in a number of research fields, and discovery of new compounds from the natural products can benefit the development of new drugs. However, the preferable phytochemistry or liquid chromatography/mass spectrometry approach is time-/labor-extensive or receives unconvincing identifications. Herein, we presented a strategy, by integrating offline two-dimensional liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (2D-LC/IM-QTOF-MS), exclusion list-containing high-definition data-dependent acquisition (HDDDA-EL), and quantitative structure-retention relationship (QSRR) prediction of the retention time (tR), to facilitate the in-depth and more reliable identification of herbal components and thus to discover new compounds more efficiently. Using the saponins in Panax quinquefolius flower (PQF) as a case, high orthogonality (0.79) in separating ginsenosides was enabled by configuring the XBridge Amide and CSH C18 columns. HDDDA-EL could improve the coverage in MS2 acquisition by 2.26 folds compared with HDDDA (2933 VS 1298). Utilizing 106 reference compounds, an accurate QSRR prediction model (R2 = 0.9985 for the training set and R2 = 0.88 for the validation set) was developed based on Gradient Boosting Machine (GBM), by which the predicted tR matching could significantly reduce the isomeric candidates identification for unknown ginsenosides. Isolation and establishment of the structures of two malonylginsenosides by NMR partially verified the practicability of the integral strategy. By these efforts, 421 ginsenosides were identified or tentatively characterized, and 284 thereof were not ever reported from the Panax species. The current strategy is thus powerful in the comprehensive metabolites characterization and rapid discovery of new compounds from the natural products.

From a single steroid to the steroidome: Trends and analytical challenges

For several decades now, the analysis of steroids has been a key tool in the diagnosis and monitoring of numerous endocrine pathologies. Thus, the available methods used to analyze steroids in biological samples have dramatically evolved over time following the rapid pace of technology and scientific knowledge. This review aims to synthetize the advances in steroids' analysis, from classical approaches considering only a few steroids or a limited number of steroid ratios, up to the new steroid profiling strategies (steroidomics) monitoring large sets of steroids in biological matrices. In this context, the use of liquid chromatography coupled to mass spectrometry has emerged as the technique of choice for the simultaneous determination of a high number of steroids, including phase II metabolites, due to its sensitivity and robustness. However, the large dynamic range to be covered, the low natural abundance of some key steroids, the selectivity of the analytical methods, the extraction protocols, and the steroid ionization remain some of the current challenges in steroid analysis. This review provides an overview of the different analytical workflows available depending on the number of steroids under study. Special emphasis is given to sample treatment, acquisition strategy, data processing, steroid identification and quantification using LC-MS approaches. This work also outlines how the availability of steroid standards, the need for complementary analytical strategies and the improvement of calibration approaches are crucial for achieving complete steroidome quantification.

Current status and recent advantages in derivatization procedures in human doping control

Derivatization is one of the most important steps during sample preparation in doping control analysis. Its main purpose is the enhancement of chromatographic separation and mass spectrometric detection of analytes in the full range of laboratory doping control activities. Its application is shown to broaden the detectable range of compounds, even in LC–MS analysis, where derivatization is not a prerequisite. The impact of derivatization initiates from the stage of the metabolic studies of doping agents up to the discovery of doping markers, by inclusion of the screening and confirmation procedures of prohibited substances in athlete's urine samples. Derivatization renders an unlimited number of opportunities to advanced analyte detection.

Current status and bioanalytical challenges in the detection of unknown anabolic androgenic steroids in doping control analysis

Androgenic anabolic steroids (AAS) are prohibited in sports due to their anabolic effects. Doping control laboratories usually face the screening of AAS misuse by target methods based on MS detection. Although these methods allow for the sensitive and specific detection of targeted compounds and metabolites, the rest remain undetectable. This fact opens a door for cheaters, since different AAS can be synthesized in order to evade doping control tests. This situation was evidenced in 2003 with the discovery of the designer steroid tetrahydrogestrinone. One decade after this discovery, the detection of unknown AAS still remains one of the main analytical challenges in the doping control field. In this manuscript, the current situation in the detection of unknown AAS is reviewed. Although important steps have been made in order to minimize this analytical problem and different analytical strategies have been proposed, there are still some drawbacks related to each approach.

Quantitative structure-retention relationships models for prediction of high performance liquid chromatography retention time of small molecules: endogenous metabolites and banned compounds

Quantitative structure-retention relationship (QSRR) is a technique capable of improving the identification of analytes by predicting their retention time on a liquid chromatography column (LC) and/or their properties. This approach is particularly useful when LC is coupled with a high-resolution mass spectrometry (HRMS) platform. The main aim of the present study was to develop and describe appropriate QSRR models that provide usable predictive capability, allowing false positive identification to be removed during the interpretation of metabolomics data, while additionally increasing confidence of experimental results in doping control area. For this purpose, a dataset consisting of 146 drugs, metabolites and banned compounds from World Anti-Doping Agency (WADA) lists, was used. A QSRR study was carried out separately on high quality retention data determined by reversed-phase (RP-LC-HRMS) and hydrophilic interaction chromatography (HILIC-LC-HRMS) systems, employing a single protocol for each system. Multiple linear regression (MLR) was applied to construct the linear QSRR models based on a variety of theoretical molecular descriptors. The regression equations included a set of three descriptors for each model: ALogP, BELe6, R2p and ALogP(2), FDI, BLTA96, were used in the analysis of reversed-phase and HILIC column models, respectively. Statistically significant QSRR models (squared correlation coefficient for model fitting, R(2)=0.95 for RP and R(2)=0.84 for HILIC) indicate a strong correlation between retention time and the molecular descriptors. An evaluation of the best correlation models, performed by validation of each model using three tests (leave-one-out, leave-many-out, external tests), demonstrated the reliability of the models. This paper provides a practical and effective method for analytical chemists working with LC/HRMS platforms to improve predictive confidence of studies that seek to identify small molecules.

A critical review of microextraction by packed sorbent as a sample preparation approach in drug bioanalysis

Sample preparation is widely accepted as the most labor-intensive and error-prone part of the bioanalytical process. The recent advances in this field have been focused on the miniaturization and integration of sample preparation online with analytical instrumentation, in order to reduce laboratory workload and increase analytical performance. From this perspective, microextraction by packed sorbent (MEPS) has emerged in the last few years as a powerful sample preparation approach suitable to be easily automated with liquid and gas chromatographic systems applied in a variety of bioanalytical areas (pharmaceutical, clinical, toxicological, environmental and food research). This paper aims to provide an overview and a critical discussion of recent bioanalytical methods reported in literature based on MEPS, with special emphasis on those developed for the quantification of therapeutic drugs and/or metabolites in biological samples. The advantages and some limitations of MEPS, as well as its comparison with other extraction techniques, are also addressed herein.