Projets de recherche

Code: 25T03MP

Ecdysterone was demonstrated to exhibit anabolic properties in-vitro and in-vivo (doi10.3390/nu16091382). Thus, ecdysterone supplements are gaining more and more attention in the sports community. In humans, a study funded by WADA (WADA15C18MP, doi10.1007/s00204-019-02490-x) already demonstrated performance enhancement in young man.

To further substantiate the effects and to support an inclusion of ecdysterone in the Prohibited List, the ListEAG suggested to perform additional experiments. A double-blind placebo-controlled intervention trial in humans will be conducted with ecdysterone supplementation in combination with a structured supervised resistance training over 12 weeks in resistance-trained males. Based on previous findings, the study will focus on resistance training and anabolic effects of ecdysterone. A standardized test battery for muscle strength will be used to evaluate potential performance enhancement based on the recommendations of NSCA recommendations with additional on individual muscle thickness etc.

Recovery measures and mechanistic investigations are also added to complement the study. Nutrition will be monitored and all groups are explicitly checked for sufficient protein intake.

Code: 25T242D01CW

The present project will conduct an integrated study on Endogenous Anabolic Androgenic Steroids (EAAS) metabolism in the Chinese population. The population distribution of UGT2B17 gene polymorphism, the long-term comparison of EAAS metabolism among individuals with different UGT2B17 gene deletion polymorphisms, and testosterone intervention experiment are the main focuses of this project. Through population studies, long-term research, and interventional trials, the metabolic profile characteristics of testosterone in the Chinese population will be illustrated. The metabolic characteristics of populations having different UGT2B17 genotypes will be highlighted.

Especially focusing on the long-term study data, which can reflect the environmental influence on urine EAAS and provide a data reference for the optimization of biological passports in the future. By correlating blood steroid profiles, urinary steroid profiles, and stable carbon isotope ratio fingerprint features, basic data and case analyses will be provided for EAAS substance detection in the UGT2B17 del/del population. A comprehensive detection strategy for EAAS, including the combined application of BSP, SP and GC/C/IRMS will be discussed in the project. The influencing factors of diet, region, and other factors on EAAS metabolism in the Chinese population will also be studied. ‌Although DBS analysis is not included in this project, the samples will be collected for subsequent investigation.

Code: 25T04MT

A major concern both for athletes and result management authorities is the possibility of nutritional supplement/dietary product contamination with minute amounts of anabolic agents leading to adverse-analytical findings (AAFs) in doping controls. The analytical sensitivity of anti-doping laboratories has been optimized to allow for utmost retrospectivity in sports drug testing, but the problem arising from such a performance is that also trace amounts introduced into an athlete’s organism by contaminated supplements or food are detected.

To support the process of fair and comprehensive case management, in-depth investigations into the elimination profiles and metabolite ratios of micro-dosed LGD-4033 were conducted in 2020/21. For that purpose, single- and multi-micro-dose excretion studies at 1, 10 and 50 μg LGD-4033 were conducted, and the collected samples analyzed by enzymatic hydrolysis, solid-phase extraction (SPE) and LC-HRMS/MS. A total of 15 phase I metabolites was detected and the ratios of LGD-4033 and the epimer M1 as well as the metabolites M5-a and M5-b were found to shift over time. The combined evaluation of the LGD-4033/metabolite concentrations and ratios can be utilized to estimate whether a minute amount of the drug was recently ingested or a larger, pharmacologically relevant amount of the doping agent was administered several days/weeks ago and thus evaluate the plausibility of potential contamination scenarios.

Within this follow-up research project, the available micro-dose administration study samples will be re-analyzed to quantify the main long-term metabolite of LGD-4033 (M5-a) by using meanwhile available certified reference material.

Code: 25T02AM

Despite suspected high prevalence of Growth Hormone (GH) doping, detection of GH doping is complex. The indirect method based on two biomarkers increased by GH (growth factor IGF-I and procollagen propeptide P-III-NP) has recently been integrated in the endocrine module from the Athlete biological passport (ABP) to better identify doping with GH using a P-III-NP assay for Centaur Analyzer and IGF-I by top-down mass spectrometry.

However Centaur analyzer and its P-III-NP assay are to be ended soon (2027) and need to be replaced. Siemens proposes a new Atellica analyzer with a test for P-III-NP that is described as highly similar to Centaur results in the normal to pathological range, but this need further confirmation in the athletes population range The aims of the project are to evaluate and confirm this new technical option for P-III-NP quantification in the coming years.

1- Comparison of P-III-NP assays performed on two Siemens analyzers and impact of storage : 200 serum samples previously analyzed for endocrine passport will be reanalyzed for P-III-NP in parallel on Advia Centaur and on the new Siemens analyzer Atellica in order to evaluate the similarity of results in an athletes population.

This will also allow a direct comparison to initial values to confirm storage conditions (-80°C) are appropriate for reanalysis;

2- Impact of various degrees of hemolysis on P-III-NP and IGF-I by adding free hemoglobin to clear sample and checking the quantification of both markers.

These data will help to confirm that the new technical options for P-III-NP detection are fit-for-purpose and will increase knowledge on how variations in quality of serum impact endocrine passport.

Code: 25T01RV

Glucocorticoids (GC) are forbidden in sports competitions when used by injectable, oral or rectal routes. They are allowed by other routes for therapeutic purposes. Since most GCs are marketed in different administration forms, the distinction between routes of administration is needed to ensure safe treatments by allowed routes of administration and to detect the use for doping purposes during competitions. Based on scientific data available, compound-specific reporting levels were established for some GC and washout periods after some administration routes.

There is no data in literature regarding concentrations of GCs in urine after intravenous administration. The objective of the present project will be to perform administration studies with dexamethasone (DEX) and methylprednisolone (MP) using intra-venous (IV) administration, to evaluate the suitability of the reporting levels already defined for DEX and MP to detect IV administration and to define the washout periods after IV administration to avoid fase adverse analytical findings due to treatments close to competitions.

Code: 24T06MT

The anti-asthmatic drug salbutamol is prohibited in sports due to its activity as beta-2-sympathomimetic. However, because of its valuable therapeutic use, inhalative administration that does not exceed 600 micrograms over 8 hours (1600 micrograms over 24 hours) is considered as non-prohibited, not even requiring a therapeutic use exception. A threshold for the urinary salbutamol (excreted unchanged or as glucuronide) is set in doping control samples for discrimination of therapeutic and non-therapeutic use, if not proven differently.

As salbutamol is also excreted as sulfoconjugate, drugs interfering with human sulfotransferase enzymes may result in an alteration of the metabolite profile and thereby in an increased concentration of non-sulfonated salbutamol. One of these drugs that is considered to interfere with salbutamol metabolism is the pain killer etoricoxib. An influence of a con-administration with inhaled salbutamol will therefore be studied in human volunteers. Urinary concentrations will be monitored and compared in a paired design to evaluate exceeding threshold levels. For future detection of etoricoxib as potentially confounding factor its detectability in urine will also be studied. As etoricoxib is reported to be excreted mainly oa oxidized metabolites (only minor amounts unchanged), its main metabolites will be targeted as well. Future studies may also evaluate the influence on the excretion of sulfoconjugates of other drugs and excedding threshold or reporting limits to support data interpretation in doping control.

Code: 24T02WM

In this project, tools to support anti-doping decision-making in EPO detection (i.e. the decision to carry out an EPO analysis on an existing sample) shall be studied. Therefore, the ability to identify the presence of EPO in blood samples may be improved by developing a pattern recognition/classification tool that provides a risk score for EPO abuse by sample. Here, the anonymized hematological profiles of athletes shall be studied for finding the most suitable indicators through statistical-based methods, deploying state-of-the-art deep learning algorithms, developing a fully-fledged pipeline model, and performing a decision analysis on the developed model for the detection of suspicious hemtological profiles. The project will focus on further exploring the application of already developed algorithms and the potential of new state-of-the-art algorithms. Here, a set of hematological parameters shall be explored that are consistent with the hematological variables reported in the hematological module of the Althete Biological Passport (ABP) in the Anti-Doping Administration & Management System (ADAMS) database. An assessment of the performance improvement resulting from the addition of variables present in the information set of the previous version of the algorithm but not in ADAMS will be conducted. In the previous phase, due to fewer data samples, each blood sample was considered in isolation, i.e., EPO abuse prediction was made independent of the athletes' history, and the longitudinal behavior of the samples was not explored. In the current project, the longitudinal aspect of the individual's sample series will be explicitly integrated (i.e., to exploit the biological signature by minimizing the impact of between subject marker variance) using state-of-the-art algorithms for processing sequential data. The tool will be optimized for both scenarios. i.e., it will be able to search within already collected samples (updatin the associated probabilities for existing samples each time a new sample is added), and it will be able to compare new hematological data from a new sample to the already existing data in the profile directly after the upload. Within the development phase, different levels of sensitivity and specificity will be tested to figure out reasonable parameters for the approach.

In order to support the deign, development, and future embedding of the machine learning tool into existing procedures, interviews with stakeholders involved in the decision process of EPO detection will be conducted, specifically with Athlete Passport Management Units (APMUs), who are tasked with recommending EPO analysis on specific samples. In addition, we will evaluate the tool together with the APMUs to capture the potential impact of machine learning supported tools on decision-making in EPO detection.

Code: 24T01WM

As sample swapping is an approach to evade doping detection, the use of machine learning-based algorithms has the potential to improve accuracy of fraud detection by improving the sensitivity of detection of urine exchange through improved targeting of DNA identification (i.e. “DNA fingerprinting”), which can be used to demonstrate the exchange of an athlete’s urine with that of another individual. Therefore, this project aims to integrate the already developed algorithm for flagging sample swapping into anti-doping protocols [3], using it both "retrospectively" and "prospectively", and to analyze the passport assessment process to evaluate the impact of the resulting tool in the anti-doping community.

This will be accomplished by providing a standalone and user-friendly tool for testing by APMUs, which will generate a score indicating the degree of similarity between one sample and all other samples within an anonymized longitudinal profile of an athlete. In order to develop the tool in a targeted and beneficial way, an understanding of its impact on the passport assessment process as well as of potential changes through the tool is required. Therefore, the project will entail several stages, following a design science research methodology, covering the following phases:

(1) exploring and understanding the passport assessment process, e.g., through online interviews with Athlete Passport Management Units (APMUs), (2) design and development, i.e., updating the algorithm to provide a score of similarity between a given sample and the other samples in an athlete's longitudinal profile, (3) demonstration i.e., the algorithm will be accessible through a standalone and user-friendly software, enabling domain experts like APMUs to easily access and test the algorithm, (4) evaluation of the impact on passport assessment by the APMUs, using anonymized longitudinal profiles and (5) communication, i.e., presentation and publication. By implementing this project, the capability of anti-doping organizations to identify instances of sample swapping by athletes shall be significantly enhanced. Through the integration of a machine learning-based algorithm, domain experts will be able to make more informed assessments of steroid data, leading to more accurate and effective antidoping efforts. The project will evaluate how, and under which conditions experts use the tool and how it influences their assessment. For this, a combination of quasi-experiments and qualitative or quantitative questionnaires will be applied. Through observations and semi-structured interviews within the quasi-experiment, we aim to analyze tool usability, confidence, and accuracy in steroid data assessment as well as potential changes in productivity through the machine learning-based tool. This allows drawing conclusions on the impact of tool support in sample swapping on the anti-doping community. A validated tool ready to use by the anti-doping community will be delivered.

Code: 242C10ND

There are indications that some freedivers use Benzodizepines to improve sports performance, which is not common in any other sports. The International Federation CMAS (Confederation Mondial des Activities Subaquatiques) has decided to impose sanctions to every freediver who is detected positive for the misuse of benzodiazepines by their Ethical Committee, which is not covered by the World Antidoping Code.

The misuse of Benzodiazepines is potentially against fair play and can be hazardous to the health of freedivers. As the governing body in freediving and thoroughly concerned with fair play in freediving, AIDA (International Association for the Development of Apnea) decided to carry out a project to determine if Benzodiazepines are misused in freediving competitions. In case that benzodiazepines improve freediving performance, these substances should be proposed as doping substances, and they have to be placed into monitoring list and eventually into the prohibited substances list, too.

A preliminary study performed in 2024 with 28 freediving samples from the indoor AIDA Championship revealed that two of these samples contained at least one Benzodiazepine or Benzodiazepine-like substance. The purpose of the hereby proposed project is to investigate whether benzodiazepines are present in the bodies of freedivers during AIDA competitions. Subjects will be elite freedivers at the AIDA World Championships, being selected for doping controls. The analysis will be performed at the Forensic Unit of the Seibersdorf Laboratories (Seibersdorf, Austria).

Code: 241A06JFN

Testosterone (T) abuse is still relatively popular among athletes despite our ability to unambiguously differentiate between T originating from an individual’s body and synthetic T using carbon stable isotope analysis. The cost prohibitive nature of this analysis makes it so that not all urine samples which are collected can be analyzed using this procedure. As such, several steps have been taken by WADA to target samples for this analysis based on several markers of T abuse which have been shown as likely to be influenced by T doping. Currently, these primary markers of T abuse are checked using athlete biological passports and flagged for T confirmation when a suspicious steroid profile is seen. This approach has been relatively successful, as stable isotope confirmation tends to have one of the highest positivity rates per sample analyzed across WADA globally. A blind spot exists due to our ability to confirm T abuse using stable isotope analysis is greater than our ability to decide which samples are to be subjected to this type of analysis, with the makers used to flag samples returning to baseline levels before the stable isotope signature returns to base levels. The extent at which T abuse is possibly under reported must be verified through the confirmation of a significant number of real athlete samples and ideally, new biomarkers of T abuse need to be discovered. We propose to analyse a series of athlete urine samples by 4 complementary analysis procedures targeting a variety of both phase 1 and phase 2 metabolites with all samples being confirmed using stable isotope analysis, allowing us to verify the frequency of T abuse being under reported while also allowing us to better target future samples for T confirmation.