A biomarker of doping indicates the biological response to the use of a prohibited substance or method. Uncovering novel biomarkers of doping is a key objective in order to improve antidoping outcomes such as the detection of doping and changing athlete behavior toward doping practices. While the antidoping field has been successful in validating novel metabolites of prohibited substances, there has been less success in developing new biomarkers of doping. Employing the most suitable study designs and analytical approaches is critical to successfully uncovering novel biomarkers of doping with a high potential for translation into routine analysis. Here we argue that the antidoping field is well positioned for biomarker discovery and outline considerations for the development of novel biomarkers of doping.

Fluctuations in plasma volume (PV) present potential confounders within the concentration‐based markers of the haematological athlete biological passport (ABP). Here, a multi‐parametric approach involving a simple blood test is applied to the current ABP adaptive model in an attempt to remove the influence of PV expansion, induced by a cycling stage race. Blood samples were obtained from 29 professional cyclists (14 male, 15 female) before, during and after 4–5 consecutive days of racing. Whole blood was analysed in accordance with the World Anti‐Doping Agency ABP guidelines for haemoglobin ([Hb]) concentration and platelets. Serum and plasma were analysed for transferrin, albumin, calcium, creatinine, total protein and low‐density lipoprotein. PV variation (Z‐scores) was estimated using a multi‐parametric model (consisting of the biomarkers mentioned earlier) and compared against calculated variations in PV (measured via CO‐rebreathing). Significant reductions in [Hb] and the OFF‐score were observed in female cyclists after 3 and 4 days of racing, with accompanying increases in PV, which returned to baseline values 4 days post competition. Similarly, a significant increase in PV was observed in male cyclists after 3 and 5 days of racing. When individual estimations of PV variance were applied to the adaptive model, the upper and lower reference predictions for [Hb] and the OFF‐score were refined such that all outliers consistent with racing‐induced PV changes were removed. The PV model appears capable of reducing the influence of PV on concentration‐dependent markers during competition. This is an important step towards the inclusion of the PV correction in the ABP haematological module.

The haematological module of the athlete biological passport (ABP) monitors longitudinal haematological variations that could be indicative of blood manipulation. This study applied a multi-parametric model previously validated in elite cyclists to compare inferred and actual PV variations, whereas the potential influence of the oral contraceptive pill (OCP) cycle on the ABP blood biomarkers and plasma volume (PV) in 14 physically active women taking OCPs was also investigated. Blood and serum samples were collected each week for 8 weeks, and the ABP haematological variables were determined according to the World Anti-Doping Agency guidelines.Transferrin (sTFN), ferritin (FERR), albumin (ALB), calcium (Ca), creatinine (CRE), total protein (TP) and low-density lipoprotein (LDL) were additionally computed as 'volume-sensitive' variables in a multivariate analysis to determine individual estimations of PV variations. Actual PV variations were indirectly measured using a validated carbon monoxide rebreathing method. We hypothesised ABP markers to be stable during a standard OCP cycle and estimated PV variations similar to measured PV variations. Measured PV variations were in good agreement with the predictions and allowed to explain an atypical passport finding (ATPF). The ABP biomarkers, Hbmass and PV were stable over 8 weeks. Significant differences occurred only between Week 7 and Week 1, with lower levels of haemoglobin concentration ([Hb]), haematocrit (HCT) and red blood cell count (RBC)(À4.4%, p < 0.01; À5.1%, p < 0.01; À5.2%, p < 0.01) and higher levels of PV at week 7 (+9%, p = 0.05). We thus concluded that estimating PV variations may help interpret individual ABP haematological profiles in women.

Context Because of its anabolic and lipolytic properties, growth hormone (GH) use is prohibited in sport. Two methods based on population derived decision limits are currently used to detect human GH (hGH) abuse: the hGH Biomarkers Test and the Isoforms Differential Immunoassay. Objective Test the hypothesis that longitudinal profiling of hGH biomarkers through application of the Athlete Biological Passport (ABP) has the potential to flag hGH abuse. Design IGF-1 and P-III-NP distributions were obtained from 7 years of anti-doping data and applied as priors to analyse individual profiles from an hGH administration study in recreational athletes. Setting Academic and anti-doping laboratories. Elite (n=11,455) and recreational athletes (n=35). Intervention(s) An open-label, randomized, single site, placebo-controlled administration study was carried out with individuals randomly assigned to 4 arms: placebo, or 3 different doses of recombinant hGH. Main Outcome Measure(s) Serum samples were analyzed for IGF-1, P-III-NP, and hGH isoforms and the performance of a longitudinal, ABP-based approach was evaluated. Results An ABP-based approach set at a 99% specificity level flagged 20/27 individuals receiving hGH treatment, including 17/27 individuals after cessation of the treatment. ABP sensitivity ranged from 12.5-71.4 % across the hGH concentrations tested following 7 days of treatment, peaking at 57.1-100 % after 21 days of treatment, and was maintained between 37.5-71.4 % for the low and high dose groups one week after cessation of treatment. Conclusions These findings demonstrate that longitudinal profiling of hGH biomarkers can provide suitable performance characteristics for use in anti-doping programs.

Introduction The athlete biological passport monitors blood variables over time to uncover blood doping. With the phasing in of a new series of blood analyzers, the Sysmex XN series, it was necessary to examine the comparability of results with the previously employed XT/XE series. A previous comparison between XN and XT/XE series suggested a small but significant bias between the two instruments in the measurements of RET%. Here, we examined the comparability of RET% on the XN and XT/XE platform using data collected over the first year since the transition. Methods The comparability of results obtained from XN and XT/XE instruments was assessed using three datasets: (i) 767 blood samples measured on both instrument series in 22 WADA‐accredited laboratories, (ii) 27 323 samples measured on either instrument across 31 laboratories, and (iii) 119 clinical samples and 110 anti‐doping samples measured on both instruments in a single laboratory. Results Analysis of the three datasets confirms the previous observation of a bias toward higher RET% values for samples measured on Sysmex XN instruments compared with the XT/XE series. Using data across a larger number of XN instruments and a larger athlete population, the current work suggests that the bias is proportional and slightly higher than previously observed across most of the range RET% values. Conclusion A model is proposed for the comparison of data across XN and XT/XE technologies whereby the instrument bias increases proportionally with RET% measured on Sysmex XN Series, but where the rate of increase is negatively related to IRF%.

Context Detection of endogenous anabolic androgenic steroids (EAAS), like testosterone (T), as doping agents has been improved with the launch of the Steroidal Module of the Athlete Biological Passport (ABP) in urine samples. Objective To target doping practices with EAAS, particularly in individuals with low level of biomarkers excreted in urine, by including new target compounds measured in blood. Design T and T/Androstenedione (T/A4) distributions were obtained from 4 years of anti-doping data and applied as priors to analyze individual profiles from two T administration studies in female and male subjects. Setting Anti-doping laboratory. Elite athletes (n=823) and male and female clinical trials subjects (n=19 and 14, respectively). Intervention(s) Two open-label administration studies were carried out. One involved a control phase period followed by patch and then oral T administration in male volunteers and the other followed female volunteers during three menstrual cycles with 28 days of daily transdermal T application during the second month. Main Outcome Measure(s) Serum samples were analyzed for T and A4 and the performance of a longitudinal, ABP-based approach was evaluated for T and T/A4. Results An ABP-based approach set at a 99% specificity flagged all female subjects during the transdermal T application period and 44% of subjects three days after the treatment. Testosterone showed the best sensitivity (74%) in response to transdermal T application in males. Conclusions Inclusion of T and T/A4 as markers in the Steroidal Module can improve the performance of the ABP to identify T transdermal application, particularly in females.

Background Hematological parameters have many applications in athletes, from monitoring health to uncovering blood doping. This study aimed to deliver biological variation (BV) estimates for 9 hematological parameters by a Biological Variation Data Critical Appraisal Checklist (BIVAC) design in a population of recreational endurance athletes and to assess the effect of self-reported exercise and health-related variables on BV. Methods Samples were drawn from 30 triathletes monthly for 11 months and measured in duplicate for hematological measurands on an Advia 2120 analyzer (Siemens Healthineers). After outlier and homogeneity analysis, within-subject (CVI) and between-subject (CVG) BV estimates were delivered (CV-ANOVA and log-ANOVA, respectively) and a linear mixed model was applied to analyze the effect of exercise and other related variables on the BV estimates. Results CVI estimates ranged from 1.3% (95%CI, 1.2-1.4) for mean corpuscular volume to 23.8% (95%CI, 21.6-26.3) for reticulocytes. Sex differences were observed for platelets and OFF-score. The CVI estimates were higher than those reported for the general population based on meta-analysis of eligible studies in the European Biological Variation Database, but 95%CI overlapped, except for reticulocytes, 23.9% (95%CI, 21.6-26.5) and 9.7% (95%CI, 6.4-11.0), respectively. Factors related to exercise and athletes’ state of health did not appear to influence the BV estimates. Conclusions This is the first BIVAC-compliant study delivering BV estimates that can be applied to athlete populations performing high-level aerobic exercise. CVI estimates of most parameters were similar to the general population and were not influenced by exercise or athletes’ state of health.