**3. Discussion**

The experimental study was carried out in pigs with the main aim of demonstrating the suitability or unsuitability of metabolomic approaches and techniques for detecting the use of banned androgenic anabolic steroids in animal feed and food of animal origin in European countries. All experimental data obtained from the performed study were statistically evaluated using interactive computer-oriented approaches and specialized statistical software with the main emphasis on the correct interpretation of results and endeavour for obtaining a more comprehensive view of the analyzed and assessed topics of our study. The results were presented primarily in a graphical form, as opposed to the mathematical evaluation of the performed statistical analyses, because they generally have a higher predictive ability for the overall evaluation of the achieved effect.

#### *3.1. Anabolic E*ff*ect of 17*β*-Testosterone (Esters)*

From the obtained experimental data of BW measurements in a weekly time interval, estimates of standard univariate statistics (mean, variance, standard deviation, median, median standard deviation and 95% confidence interval) were calculated for each time period, separately for the treated pigs and the control group (Tables 1 and 2). The mean BW of pigs from the treated group was lower (mean = 27.7 kg, CI = [24.5; 30.9]) 1 week after 17β-testosterone administration than the mean BW of pigs from the control group (mean = 28.3 kg, CI [26.4; 30.1]). At the end of the weighing at week 7 after the administration, this situation was reversed. The mean BW of pigs from the treated group (mean = 64.4 kg, CI = [58.6; 70.2]) was 9% higher than the mean BW of pigs from the control group (mean = 58.5 kg, CI = [56.8; 60.2]) and averages differed significantly (*t*-test, *p* < 0.05).

Two linear regression models of BW growth versus time were designed to test the anabolic effect, each model especially for the group of treated pigs and the data of the control group (Figure 1). Both models were tested by regression diagnostics. Testing of the regression triplet (data + model

+ method) showed that the proposed linear models were significant and correct. Estimates of the regression parameters of both linear models are given in Supplementary Materials Table S2. Statistical testing of a comprehensive comparison of both models over the whole-time interval was performed. The Chow test [39] was used to test equality between sets of coe fficients in two linear models, using the Fisher-Snedecor distribution with *m* and *r* degrees of freedom as statistics. The calculated statistic FCh = 13.583 was greater than the critical value of F0.95(2.62) = 3.150. It could be concluded that the hypothesis H0 was rejected at the significance level α = 0.05 and both models were not equal. Applying the conclusion of the Chow test, it can be concluded that the results of BW growth detected in pigs in relation to the time interval can be considered di fferent for both groups of pigs, e.g., the e ffect of the anabolic e ffect of testosterone was demonstrated. Since the initial weights of the two groups of pigs did not di ffer significantly, it can be stated that in this case the slope of the two linear models compared is statistically significantly di fferent. This partial conclusion of the study is also evident from the graphical comparison of the linear curves of both groups of pigs (see Figure 1). The anabolic effect, but in this case of nandrolone (19-nor 17β-testosterone), a synthetic analogue of testosterone, has recently been similarly demonstrated in treated barrows vs. control barrows [40].

#### *3.2. Targeted Determination of 17*β*-Testosterone in Plasma*

An analytical method for the targeted determination of 17β-testosterone in pig plasma based on LC-MS/(HR)MS was developed as part of this study to estimate the pharmacokinetic curve. The quantitative method of analysis was developed and validated as a confirmatory method as required by the European Directive for residues [34]. The correct identification of targeted analytes using the mass accuracy (MA) criterion [41,42] and quantification based on a matrix calibration curve with parameter estimates for precision and repeatability were part of the validation of the confirmation method; the results are given in Section 2.2. A detailed description of the methodology used for the identification and validation of targeted analytes has been previously described by Stastny et al. [43].

All calculated MA values (Supplementary Materials Table S2) ranged from 0.1 to 1.9 ( Δppm) for the individual analytes determined, and these calculated values were lower than the allowed instrumental tolerance ≤ 3 ppm for the QExactive mass spectrometer used. The tolerance of retention times (RT) was below ± 10% in all cases. Furthermore, a very good chromatographic separation of the analytical method from the chromatogram shown in Figure 2 is evident, where the signal-to-noise ratio (SN) value shown is significantly higher than the generally recommended value (SN > 3), e.g., for 17β-testosterone, the ratio was SN = 2987:1. Correlation coe fficients (r) estimated for the target analytes were ≥0.9991 (17β-testosterone), ≥0.9979 (17β-testosterone propionate) and 0.9996 (17β-testosterone decanoate) in plasma (Table 4). The obtained regression models showed good linearity. The sensitivity of the method was determined by the critical values LOD = 0.32 ng mL−<sup>1</sup> and LOQ = 0.63 ng mL−<sup>1</sup> for 17β-testosterone based on estimated from the matrix calibration curve model. The precision of the method as a simple repeatability, expressed as the value of the relative standard deviation (RSD), was 3.09% for 17β-testosterone to a concentration level of 5 ng mL−1. Based on the results obtained from the validation study, it was possible to conclude that the developed analytical method is suitable for the identification and quantification of free 17β-testosterone in pig plasma in the range of matrix calibration 0.5 to 80 ng mL−1.

The pharmacokinetic curve of free 17β-testosterone in pig plasma after the administration of 0.6 mL/pig of the hormonal preparation SUSTANON 250 was constructed on the basis of the results of detected concentrations in selected time intervals (Figure 3). The application dosage of the hormonal drug used was calculated on the basis of the recommended dosage for this drug in human medicine. The pharmacokinetic curves for castrated boars and sows were identical. The maximum Cmax concentration (29.31 ng mL−<sup>1</sup> ≈ 102 nmol L−<sup>1</sup> for castrated pigs, 31.73 ng mL−<sup>1</sup> ≈ 110 nmol L−<sup>1</sup> for sows) was reached tmax 24 h after the administration. Plasma testosterone levels returned to the mean endogenous testosterone levels in castrated boars and sows in approximately 21 days. The PK results for pigs corresponded to the pharmacokinetic properties of i.m. administration of testosterone in men listed in the summary of product characteristics (SPC) of the hormonal drug used (Cmax = 70 nmol <sup>L</sup>−1, tmax = 24–48 h, elimination time approximately 21 days). Although there are a number of published results on PK testosterone levels in human medicine, the authors of this study of testosterone pharmacokinetics could not compare their results with other authors because such results in animals (pigs) have not been ye<sup>t</sup> published in veterinary medicine.

The determined concentrations of endogenous free 17β-testosterone in the plasma of castrated boars of the hybrid Lage White/Czech White breed (50/50) ranged from 0.55 to 2.58 ng mL−<sup>1</sup> (mean = 1.56 ng mL−1). These determined concentrations for endogenous testosterone corresponded to the values reported in the literature: White composite breed 4.0 ng mL−<sup>1</sup> [44], Yorkshire 2.5–5.1 ng mL−1, and Duroc 0.7–3.1 ng mL−<sup>1</sup> [45]. The determined concentrations of endogenous free 17β-testosterone in sow plasma were below the limit of detection (<LOD) of the analytical method.

The individual testosterone esters contained in SUSTANON 250 hydrolyzed very rapidly in the bloodstream of pigs and were no longer detecable 24 h after application, the concentration was <LOD of the targeted quantitative method. Authors Rejtharová et al. [46] describes the methodology of targeted analysis of testosterone esters in model samples of bovine and porcine serum by LC-MS/MS. On the contrary, as the results of our study show, the targeted determination of testosterone esters in pig serum samples to directly demonstrate the illegal use of banned testosterone is not very suitable for a very short hydrolysis time after application in a real biological system.

#### *3.3. Metabolomic Profiling of Changes in Plasma and Urine*

The matrices of metabolomics data *X* obtained from an experiment performed in pigs and measured on a high-resolution mass spectrometer contain data of the same type *<sup>m</sup>*/*<sup>z</sup>*, i.e., they are homogeneous matrices (low molecular weight compounds, metabolites). To search for latent structure and reveal interrelationships in characters (X-variables) and mainly in objects, cases (pigs) in metric scale, two generally used multivariate statistical methods for character reduction to latent variables were used: principal component analysis (PCA) and cluster analysis (CA). To investigate the dependences between the independent matrix X of metabolomics data and the second dependent variable matrix Y (single-column matrix with binary data, treated group = 1 and control group = 2), another powerful statistical method, partial least squares projection to latent structures PLS was used in the form of di fferential PLS-DA analysis and in the orthogonal variant O-PLS-DA. Unsupervised PCA and supervised OPLS-DA are today the most widely used multidimensional statistical methods in metabolomics for non-targeted monitoring of changes in biochemical pathways in various biological samples, for their ability to reduce data dimensions or reduce large numbers of variables without much loss of information contained in their first few principal components (most often 2–3).

The metabolomics study was performed in a total of 21 pigs (objects), which were allocated into two groups: a treated group (*n* = 13) and a control group (*n* = 8). The problem of the first metabolomics studies in the field of food safety and illegal use of prohibited substances in livestock fattening performed and published between 2009 and 2010 was mainly the small number of experimental animals [24–26]. The authors of these first metabolomic studies were aware of this problem and subsequent studies carried out and published since 2011 have already been performed in an adequate number of animals (*n* > 10), for example [28–31].

The main results of the PCA method were score plots for plasma and urine data matrix (Figure 4), which showed significant discrimination of all objects (pigs) into two large clusters for both cases of biological matrices. A compact cluster of control group pigs (indicated by a blue ellipse) against two clearly separated clusters (point descriptions marked in red) of pigs from the treated group was found. In the treated group of pigs after testosterone administration, there was another incomplete discrimination according to the characteristics of the sex. However, in the case of plasma, two sows (objects 25 and 25) remained assigned to a cluster of castrated boars, which means that they correlated more with this group. The above results lead to a significant partial conclusion that the built PCA models were able to clearly di fferentiate the group of tested pigs from the control group.

A CA dendrogram of matrix data objects for plasma and urine (Figure 5) were constructed based on the average Euclidean distance and also showed a reliable distinction between the group of tested pigs and the control group, so CA analysis confirmed the previous partial conclusion from PCA. The following graphical outputs from the third supervised OPLS-DA method (Figure 6) scatter plots also confirmed the previous conclusions and were able to significantly di fferentiate the group of control pigs (marked in blue) from the group of tested pigs (descriptions marked in red). The R<sup>2</sup> (X), R<sup>2</sup> (Y) and Q<sup>2</sup> (Y) statistics for the OPLS-DA models were calculated. Multiple correlation R<sup>2</sup> and cross-validated coe fficient Q<sup>2</sup> for control vs. treated group R<sup>2</sup> (X) = 0.616, R<sup>2</sup> (Y) = 0.987 and Q<sup>2</sup> (Y) = 0.898 for plasma and R<sup>2</sup> (X) = 0.469, R<sup>2</sup> (Y) = 0.997 and Q<sup>2</sup> (Y) = 0.879 for urine, confirmed good class separation and a high predictive ability. Coe fficients Q<sup>2</sup> (Y) expressing the predictive abilities of the proposed model were calculated for 75% cross-validation.

The group of tested pigs, analogously as in the PCA and CA models, was further divided in the plane t1 and to1 into two clusters according to their sex. Therefore, the OPLS-DA model for urine was further designed and tested, where in matrix Y (two-column matrix with binary data; treated group = 1, control group = 2 and male group = 1, female group = 2) there was a di fferentiation according to gender (Figure 9). Statistics R<sup>2</sup> (X) = 0.417, R<sup>2</sup> (Y) = 0.973, and Q<sup>2</sup> (Y) = 0.85 also showed good separation and high prediction. The observed di fferentiation of groups of pigs by sex in all three models used after testosterone administration brings a whole new dimension to the whole issue of using metabolomics profiling to prove illegal use of banned substances. This genetic factor will have to be taken into account and further investigated in additional metabolomics studies in pigs.

**Figure 9.** The OPLS-DA score plots for urine data matrix demonstrate discrimination between the control group of pigs and secondary discrimination by sex, objects (pigs) marked with: K—control group, T—treated group, M—male and F—female (PQN scaling, R package). A list of specific numbers of pigs is given in Tables 1 and 2.

All three used multivariable statistical methods, PCA, CA, and OPLS-DA, mathematically independent, were able to significantly di fferentiate the use of synthetic exogenous testosterone from naturally occurring (endogenous) testosterone in pigs of the same breed. This conclusion is in contrast to the findings published in the only study performed to date on ractopamine (a group of banned β-agonists) in 2017 [33]. Here, the authors of this study state that no significant di fference between the

samples from the control group and the ractopamine treated group was observed in the PCA analysis when all features were used. The use of metabolomics approaches and techniques also seems to be very promising from the point of view of the time of detection of banned anabolic steroids. Synthetic exogenous 17β-testosterone was demonstrably detected in plasma and urine in the treated group of pigs 14 days after administration. A similar conclusion was reached by the authors of a metabolomics study performed in cattle with β-agonists [31], when urine samples taken on days 27 and 48 after the administration could no longer be distinguished from the control group using PCA and OPLS-DA statistical models.

Supervised OPLS-DA models for urine and plasma, as one of the important practical results of this work, will be used for further testing of real samples to verify their predictive abilities. The models will be supplemented with other banned anabolic steroids and, especially, with increased numbers of test (training) data. Subsequently, the models will be verified by screening real plasma and urine samples taken as part of the monitoring of foreign substances in the Czech Republic. This is in line with the findings of other metabolomics studies [28,30–32], which also sugges<sup>t</sup> increasing the number of samples used in statistical models and testing the proposed models on real samples obtained from national monitoring of contaminants in other EU countries (e.g., France, The Netherlands, Spain).

#### *3.4. Metabolomic Profiling for Identification of Biomarkers*

In the sequence of metabolomics multivariate statistical analysis, the last and often the most time-consuming step is to identify the most discriminating metabolites which are essential from the point of view of elucidating metabolomics pathways. A volcano plot with variable importance in projection plot (VIP) and S-plot from OPLS-DA were used to determine the most discriminating metabolites between the treatment group and control group (Figure 7 and Supplementary Materials Figure S9). The most discriminating compounds found were compared with the METLIN database, and their list and characteristics are shown in Table 4. Some very discriminating compounds have been identified with known human testostrone metabolites and confirmed against standards based on RT and MA criteria, such as M290T13\_1 which corresponds to 5 α-dihydrotestosterone. Nevertheless, further work needs to be done to identify the compounds and gain detailed explanation of their chemical structure.

#### **4. Materials and Methods**

#### *4.1. Animal Experiment and Urine*/*Plasma Sampling*

The animal experiments were performed at the Veterinary Research Institute in Brno, Czech Republic. Twenty clinically healthy 90-day-old male and female pigs (approximately 28 kg body weight) were randomly assigned to test (13 animals) and control (8 animals) groups. Animals from the test group were treated with an i.m. injection (0.6 mL/pig) of the hormonal preparation (30 mg mL−<sup>1</sup> 17β-testosterone propionate, 60 mg mL−<sup>1</sup> 17β-testosterone phenylpropionate, 60 mg mL−<sup>1</sup> 17β-testosterone isocaproate, 100 mg mL−<sup>1</sup> 17β-testosterone decanoate; Sustanon 250, N.V. Organon, CZ Reg.56/357/91-C). Experimental animals were grower pigs (hybrids of Large White × Landrace (sow) × Duroc (boar)) which were fed twice a day with a standard commercial diet according to the weight category. Pigs were housed in two separate pens (one pen/treatment and one pen/control) of 2.80 × 2.00 m.

The animals were injected on day 12 after the start of the experiment and were euthanized on day 90 of the experiment. Urine samples were collected from both groups 14, 28, 42 and 90 days after treatment and all samples were kept frozen until analysis at −20 ◦C. Plasma samples were collected from day 1, 2, 3, 4, 5, 7, 14, and 28 after treatment to day 90. After blood clotting and 10 min of centrifugation at 6000× *g* of the samples, serum was removed and kept frozen until analysis at −20 ◦C. All pigs were weighted every week within the experiment. All pigs were slaughtered at a body weight of 90–110 kg and the treated animal carcasses were destroyed. The study was performed in compliance

with Act No. 246/1992 Coll. of the Czech National Council for the protection of animals against cruelty and with the agreemen<sup>t</sup> of the Branch Commission for Animal Welfare of the Ministry of Agriculture of the Czech Republic (permission no. MZe 17214).

#### *4.2. Reagents and Materials*

Reference analyte standards (17β-testosterone, 17β-testosterone-D2 as isotopically labeled internal standards) were purchased from Sigma-Aldrich, Prague, Czech Republic. The standards were dissolved in methanol, diluted to a low concentration (mg mL−1) and used as working solutions. The organic solvents used were obtained from Merck (Darmstadt, Germany) and were in the SupraSolv® class. Used water prepared in an ultrapure water system of Golgman's water (Prague, Czech Republic). Centrifugal membrane filters Vivacon 500, cut off at 10 kDa, were obtained from Sartorius, Prague, Czech Republic.
