Doping control using high and ultra-high resolution mass spectrometry based non-targeted metabolomics-a case study of salbutamol and budesonide abuse

Measurement Uncertainty and Validation for Quantitation of Salbutamol in Human Urine by Gas Chromatography-Tandem Mass Spectrometry

A simple, rapid, sensitive and specific gas chromatography-tandem mass spectrometry (GC-MS/MS) method was developed for quantitation of salbutamol in human urine using salbutamol-d3 as the internal standard. The processing of urines samples includes deconjugation with enzymatic hydrolysis, solid phase extraction procedure utilizing XAD2 column and liquid-liquid extraction accompanied by the derivatization by means of MSTFA/IODO-TMS/DTE mixture. The GC column was a HP Ultra-1 (17 m × 0.22 mm × 0.11 μm) used to separate the peak of interest. The data for GC-MS/MS were acquired and processed utilizing GC Labs Solution and Insight GCMS Software. The detection of spectra was performed on TQ 8050. This method included a chromatographic run of 13.67 min and the linearity was found over the concentration range of 250-2000 ng/mL with a regression coefficient (r2) of 0.99. The coefficient of variation for intra and interday assay precision was between 1.85 and 2.85% and the accuracy was between 95.50 and 107.04% for low quality control (QC), medium QC and high QC. The recovery was adequate to reliable detect the analyte at or below the level recommended by the World Anti-Doping Agency i.e., threshold 1000 ng/mL. The limit of detection and limit of quantification were found to be 10 and 100 ng/mL, respectively. The expanded measurement uncertainty (Uexp%) was found to be 8.28%.

A novel tool to screen for treatments with clenbuterol in bovine: Identification of two hepatic markers by metabolomics investigation

Surveillance of illegal use of growth promoters such as β₂-agonists in food producing animals rely on the detection of drug residues by LC-MS/MS. Screening strategies focusing on indirect physiological responses following administration of active compounds are promising approaches to strengthen existing targeted methods and ensure food safety. A metabolomics analysis based on LC-HRMS was carried out on liver extracts from bulls experimentally treated with clenbuterol combined with dexamethasone (n = 8) to mimic a potential anabolic practice, and control animals (n = 8). Nicotinic acid and 5'-deoxy-5'-methylthioadenosine were identified as biomarkers of treatment. Ratio values of such markers to others of the same metabolic pathways (nicotinamide or methionine) were used to develop a classification model to assign animals as treated with clenbuterol or non-treated. The classification model was tested on an external validation set comprising 74 animals either treated with different anabolic compounds (β₂-agonists, sexual steroids, corticosteroid), or non-treated, showing 100% sensitivity and specificity.

Ultrahigh-Resolution Mass Spectrometry-Based Platform for Plasma Metabolomics Applied to Type 2 Diabetes Research

Metabolomics-the endpoint of the omics cascade-is increasingly recognized as a preferred method for understanding the ultimate responses of biological systems to stress. Flow injection electrospray (FIE) mass spectrometry (MS) has advantages for untargeted metabolic fingerprinting due to its simplicity and capability for high-throughput screening but requires a high-resolution mass spectrometer to resolve metabolite features. In this study, we developed and validated a high-throughput and highly reproducible metabolomics platform integrating FIE with ultrahigh-resolution Fourier transform ion cyclotron resonance (FTICR) MS for analysis of both polar and nonpolar metabolite features from plasma samples. FIE-FTICR MS enables high-throughput detection of hundreds of metabolite features in a single mass spectrum without a front-end separation step. Using plasma samples from genetically identical obese mice with or without type 2 diabetes (T2D), we validated the intra and intersample reproducibility of our method and its robustness for simultaneously detecting alterations in both polar and nonpolar metabolite features. Only 5 min is needed to acquire an ultra-high resolution mass spectrum in either a positive or negative ionization mode. Approximately 1000 metabolic features were reproducibly detected and annotated in each mouse plasma group. For significantly altered and highly abundant metabolite features, targeted tandem MS (MS/MS) analyses can be applied to confirm their identity. With this integrated platform, we successfully detected over 300 statistically significant metabolic features in T2D mouse plasma as compared to controls and identified new T2D biomarker candidates. This FIE-FTICR MS-based method is of high throughput and highly reproducible with great promise for metabolomics studies toward a better understanding and diagnosis of human diseases.

Toward Prevention of Doping in Youth Sport: Cross-Sectional Analysis of Correlates of Doping Tendency in Swimming

Doping is recognized as one of the most important problems in sports, but a limited number of studies have investigated doping problems in youth athletes. This study aimed to evaluate doping tendency (potential doping behavior (PDB)) and correlates of PDB in youth age swimmers. The participants were 241 competitive swimmers (131 females; 15.3 ± 1.1 years of age, all under 18 years old). Variables included predictors and PDB (criterion). Predictors consisted of sociodemographic factors (gender and age), sport-related variables (i.e., experience in swimming and sport achievement), variables explaining coaching strategy and training methodology, consumption of dietary supplements (DS), knowledge about doping, and knowledge about sports nutrition and DS (KSN). In addition to the descriptive statistics and differences between genders, a multinomial regression using PDB as the criterion (negative-, neutral-, or positive-PDB, with a negative-PDB as the reference value) was calculated to define associations between predictors and criterion. With only 71% of swimmers who declared negative-PDB results indicated an alarming figure. Boys with better KSN were more negatively oriented toward positive-PDB (OR: 0.77, 95%CI: 0.60–0.95). In girls, lower competitive achievement was evidenced as a risk factor for neutral-PDB (OR: 0.39, 95%CI: 0.24–0.63). Also, higher neutral-PDB (OR: 0.88, 95%CI: 0.81–0.96) and positive-PDB (OR: 0.90, 95%CI: 0.83–0.99) were identified in girls who began with intensive training in younger age. Because of the alarming figures of PDB, there is an evident need for the development of systematic antidoping educational programs in youth swimming. In doing so, focus should be placed on girls who began intensive training at an earlier age and those who did not achieve high competitive results.

Tracking main environmental factors masking a minor steroidal doping effect using metabolomic analysis of horse urine by liquid chromatography-high-resolution mass spectrometry

There is an urgent need to implement holistic and untargeted doping control protocols with improved discriminatory power, compared to conventional methods that only target doping agents. Metabolomics, which aims to characterize all metabolites present in biological matrices, could fulfill this need. In this context, the aim of this study was to evaluate the impact of environmental factors on the ability to obtain a metabolic signature of stanozolol administration in horse doping situation. Urine samples from 16 horses breeded in two different places were collected over a one-year period, before, during and seven months after the administration of stanozolol, a horse doping agent. Metabolomic analysis was performed using ultra-high pressure reverse phase liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (MS). Results showed a major impact of the nutritional regimen, drug administration (for de-worming purpose) and breeding place on the metabolite profiles of horse urines, which hampered the detection of metabolic perturbations induced by stanozolol administration. After having used MS/MS experiments to characterize some MS features related to these environmental factors, we showed that highlighting and then removing the features impacted by these confounding factors before performing supervised multivariate statistical analyses could address this issue. In conclusion, adequate consideration should be given to environmental and physiological factors; otherwise, they can emerge as confounding factors and conceal doping administration.

Ion traps in modern mass spectrometry

This review is devoted to trapping mass spectrometry wherein ions are confined by electromagnetic fields for prolonged periods of time within limited volume, with mass measurement taking place within the same volume. Three major types of trapping mass spectrometers are discussed, specifically radiofrequency ion trap, Fourier transform ion cyclotron resonance and Orbitrap. While these three branches are intricately interwoven with each other over their recent history, they also differ greatly in their fundamentals, roots and historical origin. This diversity is reflected also in the difference of viewpoints from which each of these directions is addressed in this review. Following the theme of the issue, we focus on developments mainly associated with the country of Germany but, at the same time, we use this review as an illustration of the rapidly increasing globalization of science and expanding multi-national collaborations.

Isobaric Tags for Relative and Absolute Quantification (iTRAQ)-Based Untargeted Quantitative Proteomic Approach To Identify Change of the Plasma Proteins by Salbutamol Abuse in Beef Cattle

Salbutamol, a selective β₂-agonist, endangers the safety of animal products as a result of illegal use in food animals. In this study, an iTRAQ-based untargeted quantitative proteomic approach was applied to screen potential protein biomarkers in plasma of cattle before and after treatment with salbutamol for 21 days. A total of 62 plasma proteins were significantly affected by salbutamol treatment, which can be used as potential biomarkers to screen for the illegal use of salbutamol in beef cattle. Enzyme-linked immunosorbent assay measurements of five selected proteins demonstrated the reliability of iTRAQ-based proteomics in screening of candidate biomarkers among the plasma proteins. The plasma samples collected before and after salbutamol treatment were well-separated by principal component analysis (PCA) using the differentially expressed proteins. These results suggested that an iTRAQ-based untargeted quantitative proteomic strategy combined with PCA pattern recognition methods can discriminate differences in plasma protein profiles collected before and after salbutamol treatment.

Effect of alprazolam on rat serum metabolic profiles

We developed a serum metabolomic method by gas chromatography-mass spectrometry (GC-MS) to evaluate the effect of alprazolam in rats. The GC-MS with HP-5MS (0.25 μm × 30 m × 0.25 mm) mass was conducted in electron impact ionization (EI) mode with electron energy of 70 eV, and full-scan mode with m/z 50-550. The rats were randomly divided to four groups, three alprazolam-treated groups and a control group. The alprazolam-treated rats were given 5, 10 or 20 mg/kg (low, medium, high) of alprazolam by intragastric administration each day for 14 days. The serum samples were corrected on the seventh and fourteenth days for metabolomic study. The blood was collected for biochemical tests. Then liver and brain were rapidly isolated and immersed for pathological study. Compared with the control group, on the seventh and fourteen days, the levels of d-glucose, 9,12-octadecadienoic acid, butanoic acid, l-proline, d-mannose and malic acid had changed, indicating that alprazolam induced energy metabolism, fatty acid metabolism and amino acid metabolism perturbations in rats. There was no significant difference for alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, urea and uric acid between controls and alprazolam groups. According to the pathological results, alprazolam is not hepatotoxic. Metabolomics could distinguish different alprazolam doses in rats.

Non-targeted LC-MS based metabolomics analysis of the urinary steroidal profile

The urinary steroidal fraction has been extensively explored as non-invasive alternative to monitor pathological conditions as well as to unveil the illicit intake of pseudo-endogenous anabolic steroids in sport. However, the majority of previous approaches involved the a priori selection of potentially relevant target analytes. Here we describe the non-targeted analysis of the urinary steroidal profiles. The workflow includes minimal sample pretreatment and normalization according to the specific gravity of urine, a 20 min reverse phase ultra-performance liquid chromatographic separation hyphenated to electrospray time-of-flight mass spectrometry. As initial validation, we analyzed a set of quality control urines spiked with glucurono- and sulfo-conjugated steroids at physiological ranges. We then applied the method for the analysis of samples collected after single transdermal administration of testosterone in hypogonadal men. The method allowed profiling of approximately three thousand metabolic features, including steroids of clinical and forensic relevance. It successfully identified metabolic pathways mostly responsible for groups clustering even in the context of high inter-individual variability and allowed the detection of currently unknown metabolic features correlating with testosterone administration. These outcomes set the stage for future studies aimed at implementing currently monitored urinary steroidal markers both in clinical and forensic analysis.

1H NMR-based metabolomics study of liver damage induced by ginkgolic acid (15:1) in mice

Ginkgolic acid (15:1) is a major toxic component in extracts obtained from Ginkgo biloba (EGb) that has allergic and genotoxic effects. This study is the first to explore the hepatotoxicity of ginkgolic acid (15:1) using a NMR (nuclear magnetic resonance)-based metabolomics approach in combination with biochemistry assays. Mice were orally administered two doses of ginkgolic acid (15:1), and mouse livers and serum were then collected for NMR recordings and biochemical assays. The levels of activity of alanine aminotransferase (ALT) and glutamic aspartate transaminase (AST) observed in the ginkgolic acid (15:1)-treated mice suggested that it had induced severe liver damage. An orthogonal signal correction partial least-squares discriminant analysis (OSC-PLSDA) performed to determine the metabolomic profile of mouse liver tissues indicated that many metabolic disturbances, especially oxidative stress and purine metabolism, were induced by ginkgolic acid (15:1). A correlation network analysis combined with information related to structural similarities further confirmed that purine metabolism was disturbed by ginkgolic acid (15:1). This mechanism might represent the link between the antitumour activity and the liver injury-inducing effect of ginkgolic acid (15:1). A SUS (Shared and Unique Structure) plot suggested that a two-dose treatment of ginkgolic acid (15:1) had generally the same effect on metabolic variations but that its effects were dose-dependent, revealing some of the common features of ginkgolic acid (15:1) dosing. This integrated metabolomics approach helped us to characterise ginkgolic acid (15:1)-induced liver damage in mice.

Applications of Fourier Transform Ion Cyclotron Resonance (FT-ICR) and Orbitrap Based High Resolution Mass Spectrometry in Metabolomics and Lipidomics

Metabolomics, along with other "omics" approaches, is rapidly becoming one of the major approaches aimed at understanding the organization and dynamics of metabolic networks. Mass spectrometry is often a technique of choice for metabolomics studies due to its high sensitivity, reproducibility and wide dynamic range. High resolution mass spectrometry (HRMS) is a widely practiced technique in analytical and bioanalytical sciences. It offers exceptionally high resolution and the highest degree of structural confirmation. Many metabolomics studies have been conducted using HRMS over the past decade. In this review, we will explore the latest developments in Fourier transform mass spectrometry (FTMS) and Orbitrap based metabolomics technology, its advantages and drawbacks for using in metabolomics and lipidomics studies, and development of novel approaches for processing HRMS data.

Bioanalytical techniques in discrimination between therapeutic and abusive use of drugs in sport

The discrimination between therapeutic and abusive use of drugs in sports is performed using threshold concentrations or reporting levels, and the detection of the substances in a sample is only reported as an adverse analytical finding when the concentration exceeds the threshold or the reporting level. In this paper, the strategies of discrimination and the analytical methods used for the main groups of substances where the distinction is needed (β-2 agonists, ephedrines, glucocorticoids and morphine) will be reviewed. Nowadays, LC–MS is the method of choice for the analysis of these substances and, in most of the cases, a simple dilution of the urine sample is performed before the chromatographic analysis.

MetICA: independent component analysis for high-resolution mass-spectrometry based non-targeted metabolomics

BACKGROUND

Interpreting non-targeted metabolomics data remains a challenging task. Signals from non-targeted metabolomics studies stem from a combination of biological causes, complex interactions between them and experimental bias/noise. The resulting data matrix usually contain huge number of variables and only few samples, and classical techniques using nonlinear mapping could result in computational complexity and overfitting. Independent Component Analysis (ICA) as a linear method could potentially bring more meaningful results than Principal Component Analysis (PCA). However, a major problem with most ICA algorithms is the output variations between different runs and the result of a single ICA run should be interpreted with reserve.

RESULTS

ICA was applied to simulated and experimental mass spectrometry (MS)-based non-targeted metabolomics data, under the hypothesis that underlying sources are mutually independent. Inspired from the Icasso algorithm, a new ICA method, MetICA was developed to handle the instability of ICA on complex datasets. Like the original Icasso algorithm, MetICA evaluated the algorithmic and statistical reliability of ICA runs. In addition, MetICA suggests two ways to select the optimal number of model components and gives an order of interpretation for the components obtained.

CONCLUSIONS

Correlating the components obtained with prior biological knowledge allows understanding how non-targeted metabolomics data reflect biological nature and technical phenomena. We could also extract mass signals related to this information. This novel approach provides meaningful components due to their independent nature. Furthermore, it provides an innovative concept on which to base model selection: that of optimizing the number of reliable components instead of trying to fit the data. The current version of MetICA is available at https://github.com/daniellyz/MetICA.

Untargeted metabolomics in doping control: detection of new markers of testosterone misuse by ultrahigh performance liquid chromatography coupled to high-resolution mass spectrometry

The use of untargeted metabolomics for the discovery of markers is a promising and virtually unexplored tool in the doping control field. Hybrid quadrupole time-of-flight (QTOF) and hybrid quadrupole Orbitrap (Q Exactive) mass spectrometers, coupled to ultrahigh pressure liquid chromatography, are excellent tools for this purpose. In the present work, QTOF and Q Exactive have been used to look for markers for testosterone cypionate misuse by means of untargeted metabolomics. Two different groups of urine samples were analyzed, collected before and after the intramuscular administration of testosterone cypionate. In order to avoid analyte losses in the sample treatment, samples were just 2-fold diluted with water and directly injected into the chromatographic system. Samples were analyzed in both positive and negative ionization modes. Data from both systems were treated under untargeted metabolomic strategies using XCMS application and multivariate analysis. Results from the two mass spectrometers differed in the number of detected features, but both led to the same potential marker for the particular testosterone ester misuse. The in-depth study of the MS and MS/MS behavior of this marker allowed for the establishment of 1-cyclopentenoylglycine as a feasible structure. The putative structure was confirmed by comparison with synthesized material. This potential marker seems to come from the metabolism of the cypionic acid release after hydrolysis of the administered ester. Its suitability for doping control has been evaluated.

Brain metabolomics in rats after administration of ketamine

In this study, we developed a brain metabolomic method, based on gas chromatography-mass spectrometry (GC/MS), to evaluate the effect of ketamine on rats. Pattern recognition analysis, including both principal component analysis and partial least squares-discriminate analysis revealed that ketamine induced metabolic perturbations. Compared with the control group, the levels of glycerol, uridine, cholesterol in rat brain of the ketamine group (50 mg/kg, 14 days) decreased, while the urea levels increased. Our results indicate that metabolomic methods based on GC/MS may be useful to elucidate ketamine abuse through the exploration of biomarkers.

Validation of a two-step quality control approach for a large-scale human urine metabolomic study conducted in seven experimental batches with LC/QTOF-MS

After his study of food science at the Rheinische Friedrich-Wilhelms University of Bonn, Tobias J Demetrowitsch obtained his doctoral degree in the research field of metabolomics at the Christian-Albrechts-University of Kiel. The present paper is part of his doctoral thesis and describes an extended strategy to evaluate and verify complex or large-scale experiments and data sets.

Large-scale studies result in high sample numbers, requiring the analysis of samples in different batches. So far, the verification of such LC–MS-based metabolomics studies is difficult. Common approaches have not provided a reliable validation procedure to date. This article shows a novel verification process for a large-scale human urine study (analyzed by a LC/QToF-MS system) using a two-step validation procedure. The first step comprises a targeted approach that aims to examine and exclude statistical outliers. The second step consists of a principle component analysis, with the aim of a tight cluster of all quality controls and a second for all volunteer samples. The applied study design provides a reliable two-step validation procedure for large-scale studies and additionally contains an inhouse verification procedure.

Evaluation of horse urine sample preparation methods for metabolomics using LC coupled to HRMS

Background: Horse urine is the medium of choice for the implementation of metabolomic approaches aimed at improving horse doping control. However, drug analysis in this biofluid is a challenging task due to the presence of large amounts of interfering compounds. Methodology & Results: A comparative study of sample preparation has been conducted to evaluate five sample-preparation methods, namely acetonitrile precipitation, proteinase K hydrolysis, membrane filtration and sample dilution with water by factors of five and 20, for metabolome analysis using liquid chromatography coupled to high resolution mass spectrometry. Assessment was performed at both global and targeted levels, by using a few thousand features obtained from peak detection software, and internal standards and 100 annotated or identified metabolites. Conclusion: By considering the number of detected signals, their intensity and their detection repeatability, acetonitrile precipitation was selected as the most efficient sample-preparation method for the analysis of horse urine metabolome in liquid chromatography coupled to high resolution mass spectrometry conditions.