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Dr. James Skinner, Griffith University, Australia

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Code: 10A1PV

The project aims to contribute to the development of the steroidal subunit of the Athlete’s Biological Passport (ABP) which is hitherto solely validated on a few markers, such as the T/E ratio.  

Recently, novel biomarkers were found that increase significantly the time detection window after administration of small doses of T, DHT and DHEA using the Adaptive Model of the ABP. These biomarkers consist of steroid ratios including minor metabolites sensitive to steroid administration. More data on intra-individual variation of the involved minor metabolites are nevertheless necessary to validate the proposed biomarkers. Therefore a large-scale investigation of long-term within-subject behaviour of an extended steroid profile will be conducted.

Data obtained on a larger cohort with comprehensive steroid profiling methods will allow the development of a multi-parametric marker of steroid doping that comprises the whole steroid profile. This model statistically classifies abnormal steroid profiles by outputting a single score. Longitudinal evaluation of this ‘Abnormal Steroid Profile Score’ (cfr. Abnormal Blood Profile Score in the Blood Passport) monitors any alteration in the steroid profile regardless to its cause. The goals are twofold. Firstly, when applied at the individual level, this model will allow the general screening of doping with endogenous steroids, food supplements and substances manipulating the steroid profile, such as after ethanol consumption. Secondly, and in contrary to blood doping and doping with growth hormone wherein markers having a detection time long enough to estimate the prevalence of doping already exist, this score might provide accurate estimates of the prevalence of steroid doping in elite sports when applied at the population level.

Moreover, the influence of genetic polymorphism on the new steroid profile parameters and an Abnormal Steroid Profile Score will be studied in order to increase the sensitivity of the model.

Main Findings:

A combination of the Support Vector Machine (SVM) algorithm with a comprehensive approach of steroid profiling resulted in a steroidomic model that enables to differentiate normal steroid profiles from abnormal ones. Theoretically, the SVM tool plots all monitored\steroids in a multi-dimensional hyperspace which makes the use of steroid ratios redundant to obtain a strategy with optimal detection sensitivity. Hence, the whole set of steroid profile values can be evaluated at once. In our model, however, the degree of abnormality was quantified by an Abnormal Steroid Profile Score (ASPS) for which values greater than 0.79 could be considered as deviating from normal.  
Since the introduction of the Athlete Biological Passport, the results of steroid profiling tests can be systematically stored in a central database enabling the estimation of the individual reference ranges. From such databases, longitudinal steroid profiling data can be made readily available to elaborate longitudinal strategies, thereby omitting a large contribution of the inter-individual variance. Similarly, the raw SVM model was improved by standardizing the training set using individual mean and standard deviation obtained with the adaptive model. The combination of the adaptive model and the SVM enhances the general performance accuracy of the raw SVM model from 62% to 84%, disregarding the kind of endogenous steroid administered. The diagnostic sensitivity of the resulting ASPS was 55% in a post-administration period of 7 days. Altered steroid profiles can be found until 5 days after ingesting a small single doses of T or DHEA or after topical application of T or DHT in therapeutically recommended doses. This drastic increase in sensitivity can be explained by the ability of the model to sensitively distinguish a prolonged recovery state of the steroid metabolism which is restoring the homeostasis of steroid profile to known basal levels.  
Since the model was trained on data obtained after T, DHT and DHEA administration, the model risked to be overfitted i.e. a specific detection tool for these steroids. This problem was addressed by leave-one-subject-out cross-validation and testing of the model on another volunteer, with another dose of DHEA and with other steroids. Testing of the excretion data from a 100mg dose of DHEA, 50mg Adion and 7-keto-DHEA ingested by another volunteer showed a clear response of the ASPSs. This indicates the polyvalent nature of the SVM model to detect any small disturbance of the steroid profile. Moreover, the high sensitivity of 97% obtained for this new test set illustrates the potential of the ASPS as a powerful biomarker for the general detection of misuse with endogenous steroids. Although, this single model shows excellent sensitivity for a wide range of administered steroids, it cannot specify which cause resulted in an aberrant steroid profile. For this information, specific metabolites should be evaluated separately. 
Despite the excellent preliminary results on low dose administration studies conducted on a limited study population - including subjects with atypical T/E’s that challenge the classification -, the applicability of this strategy will require further work and large scale validation procedure. In order to implement the ASPS in routine testing as a sensitive marker for of any misuse with endogenous steroids, the model should be tested on larger cohorts of data and external influences on the steroid profile that can alter the ASPS should be scrutinized in the future.  
In conclusion, a new strategy was developed that returns a single value ASPS as a denotation of the degree of abnormality of a steroid profile containing 24 steroid metabolites. With this strategy, the alteration of the steroid profile, caused by a variety of endogenous steroids, can be detected very sensitively. The longitudinal SVM model was shown to be a general model which can result in long detection of small doses of oral and topical steroid formulations up to 5 days. The overall model performance was very good, particularly when coupled with the longitudinal results from the adaptive Bayesian model. The combination of computer aided techniques as the Bayesian adaptive model and SVM algorithm provide a valuable steroidomic strategy for the long term detection of misuse with endogenous steroids in complement with current steroid profiling methods.

Code: 10D3AR

Anabolic androgenic steroids (AAS) behave differently in the human body. The human organism deals with these compounds differently in respect of uptake, distribution into different organs, metabolism and excretion. We recently demonstrated that ¾ of Oriental people have a severely compromised capacity to excrete testosterone in the urine compared to only 10 % in people from the west. This is a confounder in the doping test program. In the way towards personalised test programmes, Bayesian inference techniques are known to suit particularly well. To further improve the new individualised steroid profile passport, we will conduct several human studies with different routes of administration, preparations, and doses of testosterone in order to assess the sensitivity and specificity of the test program. Our research program encompasses projects designed to investigate variation in AAS disposition including inter-ethnic and gender differences. We will study both testosterone and synthesized agents with anabolic androgenic effects (nandrolone, stanozolone). We also plan to study interactions between AAS turnover and common drugs used by sportsmen, e.g. non steroidal antiinflammatory drugs. Theoretically such drugs may mask the use and enhance the effect of AAS.

Main Findings: 

The overall aim of the project has been to identify and quantitate genetic and other mechanisms of variation in the bioavailability, metabolism, and excretion of androgens (endogenous as well as exogenous). We have also focussed on the serum concentration profiles of testosterone in genetic panels of healthy volunteers. Serum concentrations are relevant comparators to effects of, and adverse reactions to androgens. Therefore, they are highly interesting. 
Serum concentrations and bioavailability have been studied and related to bioactivating enzymes and transporters. Variation in these parameters are likely determinants of the effects of androgens and of interest not only for the capacity of doping tests but also for the user profile, risk exposure etc.
a) Validation of putative biomarkers that could be used to increase the positive and the negative predictive values of testosterone doping (PPV, NPV) was addressed in the following publication: Schulze JJ, Thörngren JO, Garle M, Ekström L, Rane A. “Androgen sulfation in healthy UDP-glucuronosyl transferase 2B17 enzyme-deficient men” J Clin Endocrinol Metab. 2011 Nov;96(11):3440-7. Epub 2011 Aug 17.
b) Other endpoints related to adverse effects of testosterone were also studied in healthy volunteers, e.g. the serum lipid profile. Garevik N, Skogastierna C, Rane A, Ekstrom L. “Single dose testosterone increases total cholesterol levels and induces the expression of HMG CoA Reductase” Subst Abuse Treat Prev Policy. 2012 Mar 20;7(1):12. [Epub ahead of print]                                     c) The effect of androgen abuse on endocrine pituitary-gonadal axis was studied in Gårevik N, Strahm E, Garle M, Lundmark J, Ståhle L, Ekström L, Rane A. “Long term perturbation of endocrine parameters and cholesterol metabolism after discontinued abuse of anabolic androgenic steroids” J Steroid Biochem Mol Biol. 2011 Nov;127(3-5):295-300. Epub 2011 Aug 22
d) We have shown that the main nandrolone metabolite (19 norandrosterone glucuronide) could be detected in urine up to one year in AAS abusers.
e) The androgen profile in urine in different female populations was studied. It is of great importance that the athlete’s steroid passport program, will be able to correct for and consider all possible variability in longitudinal steroid profiles in women.  Ekström L, Gök E, Johansson M, Garle M, Rane A and Schulze JJ. Doping and Genetic Testing: Sex Difference in UGT2B15 expression, Testosterone Glucuronidation Activity and Urinary Testosterone/Epitestosterone ratio. Current Pharmacogenomics and Personalized medicine, 2012, June 10:125-131
f) We have observed conspicuous inter-individual differences in serum concentrations of testosterone after administration of the same testosterone dose to healthy volunteers.  Ekström, L., Schulze, J., Guillemette, C., Belanger, A., Rane A. “Bioavailability of testosterone enanthate dependent on genetic variation in the phosphodiesterase 7B (PDE7B) but not on the UDP-glucuronosyltransferase (UGT2B17) gene” Pharmacogenetics and genomics 2011 Jun;21(6):325-32.            
g)  Determinants of androgen access to androgen receptors also include transporters, along with metabolising enzymes form various families. We have investigated organic anion transporting polypeptides (OATP). Schulze JJ, Johansson M, Rane A, Ekström L. “Genetic variation in SLCO2B1 is associated with serum levels of testosterone and its metabolites prior to and two days after testosterone administration” Current Pharmacogenomics and Personalized Medicine” to be published Vol. 10, No. 3, 2012.      h) In one publication; Sten, T., Finel, M., Ask, B., Rane, A., Ekström, L. “Non-steroidal anti-inflammatory drugs interact with testosterone glucuronidation”, Steroids 2009 Nov;74(12):971-7, we have studied the inhibitory effect of these NSAIDs on recombinant UGT2B17 and UGT2B15, as well as other human hepatic UGTs that revealed low but detectable testosterone glucuronidation activity, namely UGT1A3, UGT1A4, UGT1A9 and UGT2B7. 
i)  Since many of the individuals devoid of the UGT2B17 gene would not reach a T/E ratio of 4.0 after testosterone intake future test programs will most likely shift from the population based- to an individual-based T/E cut-off ratios using Bayesian inference.   Schulze, JJ., Lundmark, J., Garle., Ekström, L., Sottas, PE., Rane, A. ” Substantial advantage of a combined bayesian and genotyping approach in testosterone doping tests.” Steroids. 2009 Mar;74(3):365-8