Harmonized Quality Assurance/Quality Control Provisions for Nontargeted Measurement of Urinary Pesticide Biomarkers in the HBM4EU Multisite SPECIMEn Study.

A set of quality assurance/quality control (QA/QC) criteria for nontargeted measurement of pesticide exposure markers in a large-scale study of human urine has been proposed and applied across five laboratories within the HBM4EU project. Quality control material, including reference standards and fortified pooled urine samples (QC urine) were prepared in a centralized way and distributed across participants to monitor analytical performance and consistency of the liquid chromatography coupled to high-resolution mass spectrometry data generated with a harmonized workflow. Signal intensities, mass accuracy, and retention times of selected QA/QC markers covering a broad range of physicochemical properties were monitored across QC solvent standards, QC urine samples, study urine samples, and procedural blanks, setting acceptance thresholds for repeatability and accuracy. Overall, results showed high repeatability of the collected data. The RSDs of the signal intensities were typically below 20-30% in QC and study samples, with good stability of the chromatographic separation (retention time drift within 2-4 s intrabatch and 5 s interbatch) and excellent mass accuracy (average error < 2 ppm). The use of the proposed criteria allowed for the identification of handling errors, instrumental issues, and potential batch effects. This is the first elaboration of harmonized QA/QC criteria applied across multiple laboratories to assess the quality of data generated by nontargeted analysis of human samples.

Ultra-fast retroactive processing by MetAlign of liquid chromatography/high-resolution full-scan Orbitrap mass spectrometry data in WADA Human Urine Sample Monitoring Program.

RATIONALE: The World Antidoping Agency (WADA) Monitoring program concentrates analytical data from the WADA Accredited Laboratories for substances which are not prohibited but whose potential misuse must be known. The WADA List of Monitoring substances is updated annually, where substances may be removed, introduced or transferred to the Prohibited List, depending on the prevalence of their use. Retroactive processing of old sample datafiles has the potential to create information for the prevalence of use of candidate substances for the Monitoring List in previous years. MetAlign is a freeware software with functionality to reduce the size of liquid chromatography (LC)/high-resolution (HR) full-scan (FS) mass spectrometry (MS) datafiles and to perform a fast search for the presence of substances in thousands of reduced datafiles. METHODS: Validation was performed to the search procedure of MetAlign applied to Anti-Doping Lab Qatar (ADLQ)-screened LC/HR-FS-MS reduced datafiles originated from antidoping samples for tramadol (TRA), ecdysterone (ECDY) and the ECDY metabolite 14-desoxyecdysterone (DESECDY) of the WADA Monitoring List. Searching parameters were related to combinations of accurate masses and retention times (RTs). RESULTS: MetAlign search validation criteria were based on the creation of correct identifications, false positives (FPs) and false negatives (FNs). The search for TRA in 7410 ADLQ routine LC/HR-FS-MS datafiles from the years 2017 to 2020 revealed no false identification (FPs and FNs) compared with the ADLQ WADA reports. ECDY and DESECDY were detected by MetAlign search in approximately 5% of the same cohort of antidoping samples. CONCLUSIONS: MetAlign is a powerful tool for the fast retroactive processing of old reduced datafiles collected in screening by LC/HR-FS-MS to reveal the prevalence of use of antidoping substances. The current study proposed the validation scheme of the MetAlign search procedure, to be implemented per individual substance in the WADA Monitoring program, for the elimination of FNs and FPs.

Ultra-fast retroactive processing of liquid chromatography high-resolution full-scan Orbitrap mass spectrometry data in anti-doping screening of human urine.

RATIONALE: Retroactive analysis of previously tested urine samples has become an important sports anti-doping tool. Retroactive reprocessing of old data files acquired from a generic screening procedure can reveal detection of initially unknown substances, like illegal drugs and newly identified metabolites. METHODS: To be able to efficiently search through hundreds to thousands of liquid chromatography high-resolution full-scan Orbitrap mass spectrometry data files of anti-doping samples, a combination of MetAlign and HR_MS_Search software has been developed. MetAlign reduced the data size ca 100-fold making possible local storage of a massive volume of data. RESULTS: The newly developed HR_MS_Search module can search through the reduced data files for new compounds (mass or isotope pattern) defined by mass windows and retention time windows. A search for 33 analytes in 940 reduced data files lasted 10 s. The output of the automatic search was compared to the standard manual routine evaluation. The results of searching were evaluated in terms of false negatives and false positives. The newly banned b2-agonist higenamine and its metabolite coclaurine were successfully searched in reduced data files originating from a testing period for which these substances were not banned, as an example of retroactive analysis. CONCLUSIONS: The freeware MetAlign software and its automatic searching module HR_MS_Search facilitated the retroactive reprocessing of reduced full-scan high-resolution liquid chromatography/mass spectrometry screening data files and created a new tool in anti-doping laboratories' network.

Comparison of gas chromatography/quadrupole time-of-flight and quadrupole Orbitrap mass spectrometry in anti-doping analysis: I. Detection of anabolic-androgenic steroids.

RATIONALE: The World Anti-Doping Agency (WADA) encourages drug-testing laboratories to develop screening methods that can detect as many doping substances as possible in urine. The use of full-scan high-resolution acquisition (FS/HR) with gas chromatography/mass spectrometry (GC/MS) for the detection of known and unknown trimethylsilyl (TMS) derivatives of anabolic-androgenic steroids (AAS) provides anti-doping testing bodies with a new analytical tool. METHODS: The AAS were extracted from urine samples by generic liquid-liquid extraction, after enzymatic hydrolysis, and TMS derivatization. The extracted urine was analyzed by GC/Q-TOF and GC/Q-Orbitrap to compare the performance of the two instrument types for the detection of 46 AAS in human urine. The quantitation of endogenous anabolic steroids and the ability of the two analytical platforms to comply with the requirements for testing as part of the WADA Athlete Biological Passport (ABP) were also assessed. RESULTS: The data presented show that the analytical performance for both instruments complies with the WADA specifications. The limits of detection (LODs) for both instruments are well below the WADA 50% Minimum Required Performance Levels. The mass errors in the current study for the GC/Q-Orbitrap platform are lower than those obtained for the GC/Q-TOF instrument. CONCLUSIONS: The data presented herein proved that both molecular profiling platforms can be used for antidoping screening. The mass accuracies are excellent in both instruments; however, the GC/Q-Orbitrap performs better as it provides higher resolution than the GC/Q-TOF platform.

Interindividual variation in gene expression responses and metabolite formation in acetaminophen-exposed primary human hepatocytes.

Acetaminophen (APAP) is a readily available over-the-counter drug and is one of the most commonly used analgesics/antipyretics worldwide. Large interindividual variation in susceptibility toward APAP-induced liver failure has been reported. However, the exact underlying factors causing this variability in susceptibility are still largely unknown. The aim of this study was to better understand this variability in response to APAP by evaluating interindividual differences in gene expression changes and APAP metabolite formation in primary human hepatocytes (PHH) from several donors (n = 5) exposed in vitro to a non-toxic to toxic APAP dose range. To evaluate interindividual variation, gene expression data/levels of metabolites were plotted against APAP dose/donor. The correlation in APAP dose response between donors was calculated by comparing data points from one donor to the data points of all other donors using a Pearson-based correlation analysis. From that, a correlation score/donor for each gene/metabolite was defined, representing the similarity of the omics response to APAP in PHH of a particular donor to all other donors. The top 1 % highest variable genes were selected for further evaluation using gene set overrepresentation analysis. The biological processes in which the genes with high interindividual variation in expression were involved include liver regeneration, inflammatory responses, mitochondrial stress responses, hepatocarcinogenesis, cell cycle, and drug efficacy. Additionally, the interindividual variation in the expression of these genes could be associated with the variability in expression levels of hydroxyl/methoxy-APAP and C8H13O5N-APAP-glucuronide. The before-mentioned metabolites or their derivatives have also been reported in blood of humans exposed to therapeutic APAP doses. Possibly these findings can contribute to elucidating the causative factors of interindividual susceptibility toward APAP.

The genetics of plant metabolism.

Variation for metabolite composition and content is often observed in plants. However, it is poorly understood to what extent this variation has a genetic basis. Here, we describe the genetic analysis of natural variation in the metabolite composition in Arabidopsis thaliana. Instead of focusing on specific metabolites, we have applied empirical untargeted metabolomics using liquid chromatography-time of flight mass spectrometry (LC-QTOF MS). This uncovered many qualitative and quantitative differences in metabolite accumulation between A. thaliana accessions. Only 13.4% of the mass peaks were detected in all 14 accessions analyzed. Quantitative trait locus (QTL) analysis of more than 2,000 mass peaks, detected in a recombinant inbred line (RIL) population derived from the two most divergent accessions, enabled the identification of QTLs for about 75% of the mass signals. More than one-third of the signals were not detected in either parent, indicating the large potential for modification of metabolic composition through classical breeding.

Ultrafast PubChem searching combined with improved filtering rules for elemental composition analysis.

A new and improved software tool for elemental composition annotation of molecular ions detected in mass spectrometry, based on improved filtering rules followed by ultrafast querying in publicly available compound databases, is provided. Pubchem is used as a general source of 1.3 million unique chemical formulas. A plant metabolomics database containing ca. 100,000 formulas is used as a source of naturally occurring compounds. Four modes with different sets of rules for heuristic filtering of candidate formulas coming from elemental composition analysis are incorporated and tested on both databases. The elemental composition analysis is then coupled to ultrafast PubChem searching based on a mass-indexed intermediate system. The performance of the filters is compared and discussed. When reactive compounds are assumed not to be present, 99.95% of the 1.3 million PubChem formulas is correctly found, while ca. 30% less formulas per mass are given compared to previously published rules. For the ca. 100,000 plant metabolomics based formulas, 100% fit the improved rules.

Assessment of exposure to pesticide mixtures in five European countries by a harmonized urinary suspect screening approach.

Humans are exposed to a mixture of pesticides through diet as well as through the environment. We conducted a suspect-screening based study to describe the probability of (concomitant) exposure to a set of pesticide profiles in five European countries (Latvia, Hungary, Czech Republic, Spain and the Netherlands). We explored whether living in an agricultural area (compared to living in a peri-urban area), being a a child (compared to being an adult), and the season in which the urine sample was collected had an impact on the probability of detection of pesticides (-metabolites). In total 2088 urine samples were collected from 1050 participants (525 parent-child pairs) and analyzed through harmonized suspect screening by five different laboratories. Fourty pesticide biomarkers (either pesticide metabolites or the parent pesticides as such) relating to 29 pesticides were identified at high levels of confidence in samples across all study sites. Most frequently detected were biomarkers related to the parent pesticides acetamiprid and chlorpropham. Other biomarkers with high detection rates in at least four countries related to the parent pesticides boscalid, fludioxonil, pirimiphos-methyl, pyrimethanil, clothianidin, fluazifop and propamocarb. In 84% of the samples at least two different pesticides were detected. The median number of detected pesticides in the urine samples was 3, and the maximum was 13 pesticides detected in a single sample. The most frequently co-occurring substances were acetamiprid with chlorpropham (in 62 urine samples), and acetamiprid with tebuconazole (30 samples). Some variation in the probability of detection of pesticides (-metabolites) was observed with living in an agricultural area or season of urine sampling, though no consistent patterns were observed. We did observe differences in the probability of detection of a pesticide (metabolite) among children compared to adults, suggesting a different exposure and/or elimination patterns between adults and children. This survey demonstrates the feasibility of conducting a harmonized pan-European sample collection, combined with suspect screening to provide insight in the presence of exposure to pesticide mixtures in the European population, including agricultural areas. Future improvements could come from improved (harmonized) quantification of pesticide levels.

'Omics analysis of low dose acetaminophen intake demonstrates novel response pathways in humans.

Acetaminophen is the primary cause of acute liver toxicity in Europe/USA, which led the FDA to reconsider recommendations concerning safe acetaminophen dosage/use. Unfortunately, the current tests for liver toxicity are no ideal predictive markers for liver injury, i.e. they only measure acetaminophen exposure after profound liver toxicity has already occurred. Furthermore, these tests do not provide mechanistic information. Here, 'omics techniques (global analysis of metabolomic/gene-expression responses) may provide additional insight. To better understand acetaminophen-induced responses at low doses, we evaluated the effects of (sub-)therapeutic acetaminophen doses on metabolite formation and global gene-expression changes (including, for the first time, full-genome human miRNA expression changes) in blood/urine samples from healthy human volunteers. Many known and several new acetaminophen-metabolites were detected, in particular in relation to hepatotoxicity-linked, oxidative metabolism of acetaminophen. Transcriptomic changes indicated immune-modulating effects (2g dose) and oxidative stress responses (4g dose). For the first time, effects of acetaminophen on full-genome human miRNA expression have been considered and confirmed the findings on mRNA level. 'Omics techniques outperformed clinical chemistry tests and revealed novel response pathways to acetaminophen in humans. Although no definitive conclusion about potential immunotoxic effects of acetaminophen can be drawn from this study, there are clear indications that the immune system is triggered even after intake of low doses of acetaminophen. Also, oxidative stress-related gene responses, similar to those seen after high dose acetaminophen exposure, suggest the occurrence of possible pre-toxic effects of therapeutic acetaminophen doses. Possibly, these effects are related to dose-dependent increases in levels of hepatotoxicity-related metabolites.

Screening for modulatory effects on steroidogenesis using the human H295R adrenocortical cell line: a metabolomics approach.

The recently OECD validated H295R steroidogenesis assay provides an in vitro alternative to evaluate the potential interference of exogenous compounds with endogenous steroid hormone synthesis. Currently, this assay is used for a simple negative-positive screening of compounds using testosterone and estradiol levels as end points, measured with specific enzyme immunoassays (EIAs) or targeted liquid chromatography (LC) and gas chromatography (GC)-mass spectrometry (MS) methods. However, recent developments in LC-MS and bioinformatics allow for more comprehensive approaches to evaluate changes in steroid profiles. In the current work, the H295R cell model was combined with a metabolomics approach to monitor changes in metabolite profiles in both a targeted and untargeted way. H295R cells were exposed for 48 h to model compounds, i.e., forskolin, abiraterone, prochloraz, ketoconazole, trilostane, formestane, aminoglutethimide, fadrozole, etomidate, and metyrapone, known to affect steroidogenesis. After exposure, the levels of 9 natural steroids were determined by a quantitative targeted GC-MS/MS method and compared to a metabolomics method using Ultra Performance Liquid Chromatography-Time-of-Flight-Mass Spectrometry (UPLC-ToF-MS). Like the EIAs, both methods were suited for negative-positive screening, but the MS methods also generated specific fingerprints, allowing chemical class prediction of the compound under investigation. Although the targeted GC-MS/MS was more sensitive, which was an advantage regarding analysis of the estrogens 17ß-estradiol and estrone, the untargeted UPLC-ToF-MS was able to evaluate effects on the synthesis of the corticosteroids. Moreover, untargeted comparison of the aligned chemical profiles allowed identification of all m/z-values that are differential between exposed and nonexposed H295R cells. In conclusion, application of a comprehensive metabolite profiling methodology not only provides a tool to screen compounds for steroidogenic modulating properties, but also allows chemical class prediction. As such, steroid profiling methodologies in conjunction with the H295R assay can contribute to the prioritization of chemicals for additional safety testing.

Use of NMR metabolomic plasma profiling methodologies to identify illicit growth-promoting administrations.

Detection of growth-promoter use in animal production systems still proves to be an analytical challenge despite years of activity in the field. This study reports on the capability of NMR metabolomic profiling techniques to discriminate between plasma samples obtained from cattle treated with different groups of growth-promoting hormones (dexamethasone, prednisolone, oestradiol) based on recorded metabolite profiles. Two methods of NMR analysis were investigated-a Carr-Purcell-Meiboom-Gill (CPMG)-pulse sequence technique and a conventional (1)H NMR method using pre-extracted plasma. Using the CPMG method, 17 distinct metabolites could be identified from the spectra. (1)H NMR analysis of extracted plasma facilitated identification of 23 metabolites-six more than the alternative method and all within the aromatic region. Multivariate statistical analysis of acquired data from both forms of NMR analysis separated the plasma metabolite profiles into distinct sample cluster sets representative of the different animal study groups. Samples from both sets of corticosteroid-treated animals-dexamethasone and prednisolone-were found to be clustered relatively closely and had similar alterations to identified metabolite panels. Distinctive metabolite profiles, different from those observed within plasma from corticosteroid-treated animal plasma, were observed in oestradiol-treated animals and samples from these animals formed a cluster spatially isolated from control animal plasma samples. These findings suggest the potential use of NMR methodologies of plasma metabolite analysis as a high-throughput screening technique to aid detection of growth promoter use.

A large scale multi-laboratory suspect screening of pesticide metabolites in human biomonitoring: From tentative annotations to verified occurrences.

Within the Human Biomonitoring for Europe initiative (HBM4EU), a study to determine new biomarkers of exposure to pesticides and to assess exposure patterns was conducted. Human urine samples (N = 2,088) were collected from five European regions in two different seasons. The objective of the study was to identify pesticides and their metabolites in collected urine samples with a harmonized suspect screening approach based on liquid chromatography coupled to high resolution mass spectrometry (LC-HRMS) applied in five laboratories. A combined data processing workflow included comprehensive data reduction, correction of mass error and retention time (RT) drifts, isotopic pattern analysis, adduct and elemental composition annotation, finalized by a mining of the elemental compositions for possible annotations of pesticide metabolites. The obtained tentative annotations (n = 498) were used for acquiring representative data-dependent tandem mass spectra (MS2) and verified by spectral comparison to reference spectra generated from commercially available reference standards or produced through human liver S9 in vitro incubation experiments. 14 parent pesticides and 71 metabolites (including 16 glucuronide and 11 sulfate conjugates) were detected. Collectively these related to 46 unique pesticides. For the remaining tentative annotations either (i) no data-dependent MS2 spectra could be acquired, (ii) the spectral purity was too low for sufficient matching, or (iii) RTs indicated a wrong annotation, leaving potential for more pesticides and/or their metabolites being confirmed in further studies. Thus, the reported results are reflecting only a part of the possible pesticide exposure.

An untargeted multi-technique metabolomics approach to studying intracellular metabolites of HepG2 cells exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin.

BACKGROUND: In vitro cell systems together with omics methods represent promising alternatives to conventional animal models for toxicity testing. Transcriptomic and proteomic approaches have been widely applied in vitro but relatively few studies have used metabolomics. Therefore, the goal of the present study was to develop an untargeted methodology for performing reproducible metabolomics on in vitro systems. The human liver cell line HepG2, and the well-known hepatotoxic and non-genotoxic carcinogen 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), were used as the in vitro model system and model toxicant, respectively. RESULTS: The study focused on the analysis of intracellular metabolites using NMR, LC-MS and GC-MS, with emphasis on the reproducibility and repeatability of the data. State of the art pre-processing and alignment tools and multivariate statistics were used to detect significantly altered levels of metabolites after exposing HepG2 cells to TCDD. Several metabolites identified using databases, literature and LC-nanomate-Orbitrap analysis were affected by the treatment. The observed changes in metabolite levels are discussed in relation to the reported effects of TCDD. CONCLUSIONS: Untargeted profiling of the polar and apolar metabolites of in vitro cultured HepG2 cells is a valid approach to studying the effects of TCDD on the cell metabolome. The approach described in this research demonstrates that highly reproducible experiments and correct normalization of the datasets are essential for obtaining reliable results. The effects of TCDD on HepG2 cells reported herein are in agreement with previous studies and serve to validate the procedures used in the present work.

Volatile compound fingerprinting of mixed-culture fermentations.

With the advent of the -omics era, classical technology platforms, such as hyphenated mass spectrometry, are currently undergoing a transformation toward high-throughput application. These novel platforms yield highly detailed metabolite profiles in large numbers of samples. Such profiles can be used as fingerprints for the accurate identification and classification of samples as well as for the study of effects of experimental conditions on the concentrations of specific metabolites. Challenges for the application of these methods lie in the acquisition of high-quality data, data normalization, and data mining. Here, a high-throughput fingerprinting approach based on analysis of headspace volatiles using ultrafast gas chromatography coupled to time of flight mass spectrometry (ultrafast GC/TOF-MS) was developed and evaluated for classification and screening purposes in food fermentation. GC-MS mass spectra of headspace samples of milk fermented by different mixed cultures of lactic acid bacteria (LAB) were collected and preprocessed in MetAlign, a dedicated software package for the preprocessing and comparison of liquid chromatography (LC)-MS and GC-MS data. The Random Forest algorithm was used to detect mass peaks that discriminated combinations of species or strains used in fermentations. Many of these mass peaks originated from key flavor compounds, indicating that the presence or absence of individual strains or combinations of strains significantly influenced the concentrations of these components. We demonstrate that the approach can be used for purposes like the selection of strains from collections based on flavor characteristics and the screening of (mixed) cultures for the presence or absence of strains. In addition, we show that strain-specific flavor characteristics can be traced back to genetic markers when comparative genome hybridization (CGH) data are available.

MetAlign: interface-driven, versatile metabolomics tool for hyphenated full-scan mass spectrometry data preprocessing.

Hyphenated full-scan MS technology creates large amounts of data. A versatile easy to handle automation tool aiding in the data analysis is very important in handling such a data stream. MetAlign softwareas described in this manuscripthandles a broad range of accurate mass and nominal mass GC/MS and LC/MS data. It is capable of automatic format conversions, accurate mass calculations, baseline corrections, peak-picking, saturation and mass-peak artifact filtering, as well as alignment of up to 1000 data sets. A 100 to 1000-fold data reduction is achieved. MetAlign software output is compatible with most multivariate statistics programs.

Metabolomics approach to anabolic steroid urine profiling of bovines treated with prohormones.

In livestock production, illegal use of natural steroids is hard to prove because metabolites are either unknown or not significantly above highly fluctuating endogenous levels. In this work we outlined for the first time a metabolomics based strategy for anabolic steroid urine profiling. Urine profiles of controls and bovines treated with the prohormones dehydroepiandrosterone (DHEA) and pregnenolone were analyzed with ultraperformance liquid chromatography in combination with time-of-flight accurate mass spectrometry (UPLC-TOFMS). The obtained full scan urinary profiles were compared using sophisticated preprocessing and alignment software (MetAlign) and multivariate statistics, revealing hundreds of mass signals which were differential between untreated control and prohormone-treated animals. Moreover, statistical testing of the individual accurate mass signals showed that several mass peak loadings could be used as biomarkers for DHEA and pregnenolone abuse. In addition, accurate mass derived elemental composition analysis and verification by standards or Orbitrap mass spectrometry demonstrated that the observed differential masses are most likely steroid phase I and glucuronide metabolites excreted as a direct result from the DHEA and pregnenolone administration, thus underlining the relevance of the findings from this untargeted metabolomics approach. It is envisaged that this approach can be used as a holistic screening tool for anabolic steroid abuse in bovines and possibly in sports doping as well.

Omics analyses of potato plant materials using an improved one-class classification tool to identify aberrant compositional profiles in risk assessment procedures.

The objective of this study was to quantitatively assess potato omics profiles of new varieties for meaningful differences from analogous profiles of commercial varieties through the SIMCA one-class classification model. Analytical profiles of nine commercial potato varieties, eleven experimental potato varieties, one GM potato variety that had acquired Phytophtora resistance based on a single insert with potato-derived DNA sequences, and its non-GM commercial counterpart were generated. The ten conventional varieties were used to construct the one-class model. Omics profiles from experimental non-GM and GM varieties were assessed using the one-class SIMCA models. No potential unintended effects were identified in the case of the GM variety. The model showed that varieties that were genetically more distant from the commercial varieties were recognized as aberrant, highlighting its potential in determining whether additional evaluation is required for the risk assessment of materials produced from any breeding technique, including genetic modification.

Use of omics analytical methods in the study of genetically modified maize varieties tested in 90 days feeding trials.

Genetically modified (GM) maize and their non-modified counterparts were compared using MON810 varieties, the only GMO event cultivated in Europe. The differences in grain samples were analysed by omics profiles, including transcriptomics, proteomics and metabolomics. Other cultivated maize varieties were analysed as a reference for the variability that will exist between cultivated varieties. The observed differences between modified and non-modified maize varieties do not exceed typical differences between non-modified varieties. The use of these advanced analytical approaches to analyse novel plant materials as compared to the results from animal feeding trials with whole foods is assessed. No indications were observed for changes in the GM varieties that warrant further investigations. Furthermore, it was shown that such indications will be obtained if maize samples of inferior quality are analysed similarly. Omics data provide detailed analytical information of the plant material, which facilitates a risk assessment procedure of new (GM) plant varieties.

High resolution full scan liquid chromatography mass spectrometry comprehensive screening in sports antidoping urine analysis.

The aim of this paper is to present the development and validation of a high-resolution full scan (HR-FS) electrospray ionization (ESI) liquid chromatography coupled to quadrupole Orbitrap mass spectrometer (LC/Q/Orbitrap MS) platform for the screening of prohibited substances in human urine according to World Antidoping Agency (WADA) requirements. The method was also validated for quantitative analysis of six endogenous steroids (epitestosterone, testosterone, 5α-dihydrotestosterone, dehydroepiandrosterone, androsterone and etiocholanolone) in their intact sulfates form. The sample preparation comprised a combination of a hydrolyzed urine liquid-liquid extraction and the dilute & shoot addition of original urine in the extracted aliquot. The HR-FS MS acquisition mode with Polarity Switching was applied in combination of the Quadrupole-Orbitrap mass filter. The HR-FS acquisition of analytical signal, for known and unknown small molecules, allows the inclusion of all analytes detectable with LC-MS for antidoping investigations to identify the use of known or novel prohibited substances and metabolites after electronic data files' reprocessing. The method has been validated to be fit-for-purpose for the antidoping analysis.

Gas chromatographic quadrupole time-of-flight full scan high resolution mass spectrometric screening of human urine in antidoping analysis.

This paper presents the development and validation of a high-resolution full scan (FS) electron impact ionization (EI) gas chromatography coupled to quadrupole Time-of-Flight mass spectrometry (GC/QTOF) platform for screening anabolic androgenic steroids (AAS) in human urine samples. The World Antidoping Agency (WADA) enlists AAS as prohibited doping agents in sports, and our method has been developed to comply with the qualitative specifications of WADA to be applied for the detection of sports antidoping prohibited substances, mainly for AAS. The method also comprises of the quantitative analysis of the WADA's Athlete Biological Passport (ABP) endogenous steroidal parameters. The applied preparation of urine samples includes enzymatic hydrolysis for the cleavage of the Phase II glucuronide conjugates, generic liquid-liquid extraction and trimethylsilyl (TMS) derivatization steps. Tandem mass spectrometry (MS/MS) acquisition was applied on few selected ions to enhance the specificity and sensitivity of GC/TOF signal of few compounds. The full scan high resolution acquisition of analytical signal, for known and unknown TMS derivatives of AAS provides the antidoping system with a new analytical tool for the detection designer drugs and novel metabolites, which prolongs the AAS detection, after electronic data files' reprocessing. The current method is complementary to the respective liquid chromatography coupled to mass spectrometry (LC/MS) methodology widely used to detect prohibited molecules in sport, which cannot be efficiently ionized with atmospheric pressure ionization interface.