Robust and sensitive peptidomics workflow for plasma based on specific extraction, lipid removal, capillary LC setup and multinozzle ESI emitter.

We present a new workflow for the LC-MS determination of native peptides in plasma at picomolar levels. Collected whole blood was quickly diluted with an ice-cold solution in order to stop protease activity. Diluted plasma samples were extracted by protein denaturation followed by solid-phase-extraction with a polymeric stationary phase that removed most proteins and lipids. Using a specific LC-MS setup with 3 pumps, 240 µL of extracts were injected without drying-reconstitution, a step known to cause peptide losses. After an 18-fold dilution on-line, peptides were trapped on a 1 × 10 mm C8 column, back-flushed and resolved on a 0.3 × 100 mm C18 column. Extract reproducibility, robustness (column clogging), extraction yields, matrix effects, calibration curves and limits of detection were evaluated with plasma extracts and spiked-in standards. The sensitivity and applicability of 3 electrospray sources were evaluated at capillary flow rates (10 µL/min). We show that ionization sources must have a spray angle with the MS orifice when "real" extracts are injected and that a multinozzle emitter can improve very significantly peptide detection. Finally, using our workflow, we have performed a peptidomics study on dried-blood-spots collected over 65 h in a healthy volunteer and discovered 5 fragments (2.9-3.8 KDa) of the protein statherin showing circadian oscillations. This is the first time that statherin is observed in blood where its role clearly deserves further investigations. Our peptidomic protocol shows low picomolar limits of detection and can be readily applied with or without minor modifications for most peptide determinations in various biomatrices.

Fully automated dried blood spot sample handling and extraction for serological testing of SARS-CoV-2 antibodies.

At the beginning of 2020, an outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reached pandemic dimensions. Throughout the event, diagnostic tests function as an essential tool for understanding, mitigating, and implement strategies to curb and reduce infections. Here, we present a novel method for the fully automated dried blood spot (DBS) sample handling and extraction for serological testing of human IgG antibodies against SARS-CoV-2 using a commercial enzyme-linked immunosorbent assay (ELISA) testing kit. This proof-of-principle pilot study successfully demonstrates the recovery of antibodies in their intact form from DBS using automated, direct sample elution within 100 µl of extraction buffer. The use of minimally invasive DBS sampling provides an alternative to existing analytical procedures such as sampling by venipuncture or nasal swabs. Due to the ease of DBS collection, no third party need be involved, making at-home sampling possible (e.g., during quarantine).

A novel mixed living high training low intervention and the hematological module of the athlete biological passport.

Exposure to either natural or simulated hypoxia induces hematological adaptations that may affect the parameters of the Athlete Biological Passport (ABP). The aim of the present study was to examine the effect of a novel, mixed hypoxic dose protocol on the likelihood of producing an atypical ABP finding. Ten well-trained middle-distance runners participated in a "live high, train low and high" (LHTLH) altitude training camp for 14 days. The participants spent ˜6 hr.d-1 at 3000-5400 m during waking hours and ˜10 h.d-1 overnight at 2400-3000 m simulated altitude. Venous blood samples were collected before (B0), and after 1 (D1), 4 (D4), 7 (D7), and 14 (D14) days of hypoxic exposure, and again 14 days post exposure (P14). Samples were analyzed for key parameters of the ABP including reticulocyte percentage (Ret%), hemoglobin concentration ([Hb]), and the OFF-score. The ABP adaptive model was administered at a specificity of 99% to test for atypical findings. We found significant changes in [Hb] and Ret% during the hypoxic intervention. Consequently, this led to ABP threshold deviations at 99% specificity in three participants. Only one of these was flagged as an "atypical passport finding" (ATPF) due to deviation of the OFF-score. When this sample was evaluated by ABP experts it was considered "normal". In conclusion, it is highly unlikely that the present hypoxic exposure protocol would have led to a citation for a doping violation according to WADA guidelines.

Combined administration of microdoses of growth hormone and erythropoietin: Effects on performance and evaluation of GH detection capability using anti-doping methods.

The combination of growth hormone (GH) and recombinant erythropoietin (rEPO) is thought to be used particularly in endurance sports. Our objective was to reproduce a 2-week administration of rEPO microdoses alone or in combination with GH microdoses (three times a week) on healthy and athletic male subjects and to evaluate if GH had any additional effects compared to EPO treatment alone. The effects of the treatments on hematological parameters and VO2max were studied as well as the detection of GH in serum. While the rEPO microdose regimen was associated with a significant increase in reticulocytes, no clear elevation in hemoglobin concentration (HGB) was observed. Using a correction by plasma volume did not reveal more effects of EPO on HGB. Our results did not show any additional effect when the GH microdoses were co-administered. In addition, no clear increase in VO2max was observed after treatment, with an elevation in only half the subjects in both groups (EPO and EPO+GH). A clear effect of GH on insulin-like growth factor I (IGF-I) was seen but it was lower on procollagen III amino-terminal propeptide (P-III-NP). GH detection using the direct isoform test identified only one subject 24 hours after receiving GH. The GH biomarker test combining IGF-I and P-III-NP was not able to detect the GH administration. However, a longitudinal follow-up of the intraindividual variations showed a significant increase in IGF-I 24 and 48 hours after GH administration in most subjects, while the effect of GH microdoses on P-III-NP was less straightforward.

Standardization of reticulocyte counts in the athlete biological passport.

INTRODUCTION: The percentage of circulating reticulocytes (RET%) is a useful marker of blood doping in the context of the Athlete Biological Passport (ABP). The viability of the ABP depends on the comparability of sample data obtained across multiple laboratories for a given athlete. With the recent introduction of a different technology for the measurement of reticulocytes, the goal of this study was to compare currently employed Sysmex XT/XE analyzers to the recently introduced Sysmex XN analyzer. METHODS: RET% differences were searched in two independent data sets, the first consisting of 95 369 RET% values coming from 29 laboratories located in five continents as part of routine testing for the ABP, the second from a targeted study involving 510 samples analyzed on both a Sysmex XT and XN analyzers by two different laboratories. RESULTS: A relatively small but significant bias of 0.27 ([0.22-0.35] 95% CI) for the first data set and 0.19% ([0.16-0.22] 95% CI) for the second data set was observed with Sysmex XN analyzers returning higher values than Sysmex XT/XE analyzers. This bias appears constant over most of the range of RET% measured in elite athletes. CONCLUSION: When RET% values are obtained for the same athlete with different technologies (XT/XE vs XN), an adjustment of RET% emanating from the XT/XE instruments through a decrease of 0.22% within the ABP calculated ranges appears to be sufficient to integrate the results from the two technologies.

LC-HRMS Metabolomics for Untargeted Diagnostic Screening in Clinical Laboratories: A Feasibility Study.

Today’s high-resolution mass spectrometers (HRMS) allow bioanalysts to perform untargeted/global determinations that can reveal unexpected compounds or concentrations in a patient’s sample. This could be performed for preliminary diagnosis attempts when usual diagnostic processes and targeted determinations fail. We have evaluated an untargeted diagnostic screening (UDS) procedure. UDS is a metabolome analysis that compares one sample (e.g., a patient) with control samples (a healthy population). Using liquid chromatography (LC)-HRMS full-scan analysis of human serum extracts and unsupervised data treatment, we have compared individual samples that were spiked with one xenobiotic or a higher level of one endogenous compound with control samples. After the use of different filters that drastically reduced the number of metabolites detected, the spiked compound was eventually revealed in each test sample and ranked. The proposed UDS procedure appears feasible and reliable to reveal unexpected xenobiotics (toxicology) or higher concentrations of endogenous metabolites. HRMS-based untargeted approaches could be useful as preliminary diagnostic screening when canonical processes do not reveal disease etiology nor establish a clear diagnosis and could reduce misdiagnosis. On the other hand, the risk of overdiagnosis of this approach should be reduced with mandatory biomedical interpretation of the patient’s UDS results and with confirmatory targeted and quantitative determinations.

A step towards removing plasma volume variance from the Athlete's Biological Passport: The use of biomarkers to describe vascular volumes from a simple blood test.

The haematological module of the Athlete's Biological Passport (ABP) has significantly impacted the prevalence of blood manipulations in elite sports. However, the ABP relies on a number of concentration-based markers of erythropoiesis, such as haemoglobin concentration ([Hb]), which are influenced by shifts in plasma volume (PV). Fluctuations in PV contribute to the majority of biological variance associated with volumetric ABP markers. Our laboratory recently identified a panel of common chemistry markers (from a simple blood test) capable of describing ca 67% of PV variance, presenting an applicable method to account for volume shifts within anti-doping practices. Here, this novel PV marker was included into the ABP adaptive model. Over a six-month period (one test per month), 33 healthy, active males provided blood samples and performed the CO-rebreathing method to record PV (control). In the final month participants performed a single maximal exercise effort to promote a PV shift (mean PV decrease -17%, 95% CI -9.75 to -18.13%). Applying the ABP adaptive model, individualized reference limits for [Hb] and the OFF-score were created, with and without the PV correction. With the PV correction, an average of 66% of [Hb] within-subject variance is explained, narrowing the predicted reference limits, and reducing the number of atypical ABP findings post-exercise. Despite an increase in sensitivity there was no observed loss of specificity with the addition of the PV correction. The novel PV marker presented here has the potential to improve the ABP's rate of correct doping detection by removing the confounding effects of PV variance.

Validation of whole-blood transcriptome signature during microdose recombinant human erythropoietin (rHuEpo) administration.

BACKGROUND: Recombinant human erythropoietin (rHuEpo) can improve human performance and is therefore frequently abused by athletes. As a result, the World Anti-Doping Agency (WADA) introduced the Athlete Biological Passport (ABP) as an indirect method to detect blood doping. Despite this progress, challenges remain to detect blood manipulations such as the use of microdoses of rHuEpo. METHODS: Forty-five whole-blood transcriptional markers of rHuEpo previously derived from a high-dose rHuEpo administration trial were used to assess whether microdoses of rHuEpo could be detected in 14 trained subjects and whether these markers may be confounded by exercise (n = 14 trained subjects) and altitude training (n = 21 elite runners and n = 4 elite rowers, respectively). Differential gene expression analysis was carried out following normalisation and significance declared following application of a 5% false discovery rate (FDR) and a 1.5 fold-change. Adaptive model analysis was also applied to incorporate these markers for the detection of rHuEpo. RESULTS: ALAS2, BCL2L1, DCAF12, EPB42, GMPR, SELENBP1, SLC4A1, TMOD1 and TRIM58 were differentially expressed during and throughout the post phase of microdose rHuEpo administration. The CD247 and TRIM58 genes were significantly up- and down-regulated, respectively, immediately following exercise when compared with the baseline both before and after rHuEpo/placebo. No significant gene expression changes were found 30 min after exercise in either rHuEpo or placebo groups. ALAS2, BCL2L1, DCAF12, SLC4A1, TMOD1 and TRIM58 tended to be significantly expressed in the elite runners ten days after arriving at altitude and one week after returning from altitude (FDR > 0.059, fold-change varying from 1.39 to 1.63). Following application of the adaptive model, 15 genes showed a high sensitivity (≥ 93%) and specificity (≥ 71%), with BCL2L1 and CSDA having the highest sensitivity (93%) and specificity (93%). CONCLUSIONS: Current results provide further evidence that transcriptional biomarkers can strengthen the ABP approach by significantly prolonging the detection window and improving the sensitivity and specificity of blood doping detection. Further studies are required to confirm, and if necessary, integrate the confounding effects of altitude training on blood doping.

The Athlete Biological Passport: How to Personalize Anti-Doping Testing across an Athlete's Career?

For decades, drug testing has been the main instrument at the disposal of anti-doping authorities. The availability in the 1980s of substances identical to those produced by the human body, including the "big 3" (erythropoietin, testosterone, and growth hormone), necessitated a new paradigm in anti-doping. The athlete biological passport (ABP) is a new paradigm, complementary to traditional drug testing, based on the personalized monitoring of doping biomarkers. Athletes who abuse doping substances do so to trigger physiological changes that provide performance enhancement. The ABP aims to detect these changes through its 3 hematological, steroidal, and endocrine modules. Any deviation of a biomarker from what is expected in a healthy physiological condition can be attributable to doping or a medical condition, which, interestingly, is also the criterion used to define a banned substance. Recent advances in proteomics and metabolomics offer immense opportunities to enhance the ABP. The ABP shares multiple aspects with the present customization of health care and personalized medicine.

The use of biomarkers to describe plasma-, red cell-, and blood volume from a simple blood test.

Plasma volume and red cell mass are key health markers used to monitor numerous disease states, such as heart failure, kidney disease, or sepsis. Nevertheless, there is currently no practically applicable method to easily measure absolute plasma or red cell volumes in a clinical setting. Here, a novel marker for plasma volume and red cell mass was developed through analysis of the observed variability caused by plasma volume shifts in common biochemical measures, selected based on their propensity to present with low variations over time. Once a month for 6 months, serum and whole blood samples were collected from 33 active males. Concurrently, the CO-rebreathing method was applied to determine target levels of hemoglobin mass (HbM) and blood volumes. The variability of 18 common chemistry markers and 27 Full Blood Count variables was investigated and matched to the observed plasma volume variation. After the removal of between-subject variations using a Bayesian model, multivariate analysis identified two sets of 8 and 15 biomarkers explaining 68% and 69% of plasma volume variance, respectively. The final multiparametric model contains a weighting function to allow for isolated abnormalities in single biomarkers. This proof-of-concept investigation describes a novel approach to estimate absolute vascular volumes, with a simple blood test. Despite the physiological instability of critically ill patients, it is hypothesized the model, with its multiparametric approach and weighting function, maintains the capacity to describe vascular volumes. This model has potential to transform volume management in clinical settings. Am. J. Hematol. 92:62-67, 2017. © 2016 Wiley Periodicals, Inc.

Statistical discrimination of steroid profiles in doping control with support vector machines.

Due to their performance enhancing properties, use of anabolic steroids (e.g. testosterone, nandrolone, etc.) is banned in elite sports. Therefore, doping control laboratories accredited by the World Anti-Doping Agency (WADA) screen among others for these prohibited substances in urine. It is particularly challenging to detect misuse with naturally occurring anabolic steroids such as testosterone (T), which is a popular ergogenic agent in sports and society. To screen for misuse with these compounds, drug testing laboratories monitor the urinary concentrations of endogenous steroid metabolites and their ratios, which constitute the steroid profile and compare them with reference ranges to detect unnaturally high values. However, the interpretation of the steroid profile is difficult due to large inter-individual variances, various confounding factors and different endogenous steroids marketed that influence the steroid profile in various ways. A support vector machine (SVM) algorithm was developed to statistically evaluate urinary steroid profiles composed of an extended range of steroid profile metabolites. This model makes the interpretation of the analytical data in the quest for deviating steroid profiles feasible and shows its versatility towards different kinds of misused endogenous steroids. The SVM model outperforms the current biomarkers with respect to detection sensitivity and accuracy, particularly when it is coupled to individual data as stored in the Athlete Biological Passport.

Adaptive Bayesian approach to clinical trial renal impairment biomarker signal from urea and creatinine.

A major concern with the identification of renal toxicity using the traditional biomarkers, urea and creatinine, is that toxicity signal definitions are not sensitive to medically important changes in these biomarkers. Traditional renal signal definitions for urea and creatinine have not adequately identified drugs that have generated important medical issues later in development. Here, two clinical trial databases with a posteriori known drug induced renal impairment were analyzed for the presence of a renal impairment biomarker signal from urea (590 patients; age 26-92, median 65) and creatinine (532 patients; age 26-97, median 65). Data was analyzed retrospectively using multiple definitions for the biomarker signal to include values outside stratified reference intervals, values exceeding twofold increases from baseline, values classified by the 2009 NIAID renal toxicity table, change from baseline represented as a Z-score based on intra-individual biological variations, and an adaptive Bayesian methodology that generalizes population- with individual-based methods for evaluating a biomarker signal. The data demonstrated that the adaptive Bayesian methodology generated a prominent drug induced signal for renal impairment at the first visit after drug administration. The signal was directly related to dose and time of drug administration. All other data analysis methods produced none or significantly weaker signals than the adaptive Bayesian approach. Interestingly, serum creatinine and urea are able to detect early kidney dysfunction when the biomarker signal is personalized.

Adaptive Bayesian analysis of serum creatinine as a marker for drug-induced renal impairment in an early-phase clinical trial.

BACKGROUND: A concern with using creatinine for the identification of drug-induced renal impairment is that small changes in serum creatinine (SCr) that frequently are perceived as measurement bias or imprecision translate into important changes in the glomerular filtration rate. Important drug-generated changes in creatinine are difficult to detect because they are frequently observed within the reference interval. The design of a crossover drug protocol is an opportunity to use study participants as their own control to identify these small but important changes. METHODS: Twenty individuals participating in a phase I clinical trial were evaluated for SCr changes beyond those expected for biological variation according to individual Z scores derived from an adaptive Bayesian model. After 2 screening tests, participants were administered either drug (n = 11) or placebo (n = 9) during the first dosing interval. A washout period followed, and drug was then administered to the group that initially received placebo, and vice versa (10 visits total per participant). RESULTS: Although all creatinine values fell within the reference interval, 8 participants individually showed increased concentrations (Z scores >2.33). These 8 participants were confirmed at unblinding to have received the drug in the identified dosing period, with 1 exception. CONCLUSIONS: The ability to identify a drug effect on an individual-participant basis in early-phase studies permits drug developers to recognize issues early in development and rapidly engage in risk-benefit analysis. These results suggest that SCr monitoring is able to detect early kidney dysfunction when individual-based reference intervals are used.

Current implementation and future of the Athlete Biological Passport.

During the last four decades, the main instrument at the disposal of anti-doping authorities has been the detection of prohibited substances in biological samples collected from athletes. However, the availability of substances identical to those produced by the human body, such as EPO, testosterone and GH, necessitated a new drug-testing paradigm. From the early 2000's, the Athlete Biological Passport (ABP) was proposed as an alternative means to drug testing. Doping leaves a characteristic fingerprint on the biology of the athlete and the ABP is used to prove the act of doping from the detection of that fingerprint. Once a biomarker of doping is implemented in the ABP, it will continue to remain valid and should be able to detect the physiological changes brought on by performance-enhancing drugs that have not yet been invented. However, the sensitivity of the ABP to detect doping is limited if the physiological result of a low level of doping remains within the individual's own reference range. Recent advances in proteomics and metabolomics show the huge potential of the ABP.

Evolving concepts and techniques for anti-doping.

Technical advances are being made in many areas of biotechnology and genetics that are facilitating the detection of doping in sport. These improvements have been catalyzed by the need to counter the ever-increasing sophistication of the community of athletes and their retinues who are intent on the illicit use of physical, pharmacological and genetic tools and methods to enhance athletic performance, in contravention of established international ethical and legal standards and of international treaty. The methods described in this article present a partial and general picture of only some of these advances.

Hemoglobin mass and biological passport for the detection of autologous blood doping.

PURPOSE: The most promising attempt to reveal otherwise undetectable autologous blood doping is the Athlete Biological Passport enabling a longitudinal monitoring of hematological measures. Recently, the determination of hemoglobin mass (tHb) was suggested to be incorporated in the adaptive model of the Athlete Biological Passport. The purpose therefore was to evaluate the performance of tHb as part of the adaptive model for the detection of autologous blood transfusions in a longitudinal blinded study. METHODS: Twenty-one subjects were divided into a doped group (n = 11) and a control group (n = 10). During the time course of a simulated cycling season (42 wk) including three major competitions (Classics, Grand Tour, World Championships), multiple autologous transfusions of erythrocyte concentrates were assigned in the doped group. A blinded investigator ordered up to 10 tHb measurements (carbon monoxide rebreathing) per subject, mimicking an intelligent doping testing approach in obtaining hematological data (tHb, OFFmass (novel marker including reticulocytes), and respective sequences) for the adaptive model. RESULTS: The final analysis included 199 of 206 overall tHb measurements. The use of tHb, OFFmass, and their sequences as markers of the adaptive model at the 99% specificity level allowed identification of 10 of 11 doped subjects (91% sensitivity) including one false positive in the control group. At the 99.9% specificity level, 8 of 11 subjects were identified without false positives (73% sensitivity). CONCLUSIONS: It seems that the problems of tHb determination by carbon monoxide rebreathing limit the application of this method in antidoping. Because of its potential to detect individual abnormalities associated with autologous blood transfusions shown in this study, a method for tHb determination that is compatible with today's standards of testing should be the focus of future research.

Patient-specific measures of a biomarker for the generation of individual reference intervals: hemoglobin as example.

Although hemoglobin concentration measurement is among the most commonly performed blood tests, the description of global population parameters, heterogeneous factors, and within-subject variations in patients with disease remains incomplete. As absolute action values are being published in the medical literature and by government healthcare agencies, these measures are important to define patient-specific ranges of biomarkers. Here, a global clinical trial data set composed of 1,537,932 hemoglobin values from 416,374 patients and 372 clinical indications was generated over 2 years by automated analyzers in a global network of 5 laboratories. Within- and between-subject components of variance and the effect of factors age, gender, nationality, and clinical indication were determined using unbalanced multiway analysis of variance. Average within-subject variances differed significantly depending on the clinical indication (0.15-1.3 g(2)/dL(2)) but, nevertheless, remained significantly lower than between-subject variances. The main sources of between-subject variation were clinical indication and gender, followed by age and nationality. An adaptive Bayesian approach was then used to generate patient-specific ranges of hemoglobin for drug safety and efficacy assessment in clinical trials. The same methodology can be applied to the evaluation of any biomarker signal in translational medicine.