Eugenio Alladio

Effects of various sample pretreatment procedures on ethyl glucuronide quantification in hair samples: Comparison of positivity rates and appraisal of cut-off values.

The quantification of ethylglucuronide (EtG) in hair is nowadays recognized as the approach with the highest diagnostic performance to evaluate harmful drinking. A widely accepted cut-off of 30pg/mg has been selected after several accurate compared studies. While most of the studies that were used to establish the appropriate cut-off value prescribed to cut hair into small segments before their extraction, hair milling has subsequently been identified as the most efficient pretreatment procedure and was therefore recommended in the last Consensus document issued by the Society of Hair Testing. In this study, we initially compared the results obtained with the two sample preparations, namely cutting and milling, both being applied to the same specimens (n=781). Among these, 205 samples produced measurable EtG values with both methods, with differences ranging from -41.7% up to +415% (the mean increase in EtG concentration, switching from cutting to milling, was +62.1% and the median was +42.3%). Among the aforementioned 205 samples, 29 specimens (3.7% of the total 781 samples) produced significantly different outcome, being classified as negative (i.e., below 30pg/mg) if the cutting procedure is used, but largely positive (above 40pg/mg) when milling is used. Subsequently, the positivity rates obtained on a large population dataset (>27,000 samples) with the two procedures, were retrospectively compared using variable cut-offs values. The percentage of head hair samples with EtG concentration exceeding 30pg/mg upon application of the milling procedure shows a 45% increase (from 10.9% to 15.8%) with respect to cutting procedure, whereas the fraction of hair samples with EtG exceeding 40pg/mg (10.5%) overlaps the percentage of positive samples obtained after cutting pretreatment and applying a cut-off of 30pg/mg. On the basis of these results, it would be worth considering the application of cut-off values linked with the pretreatment procedure, taking into account the results of forthcoming inter-laboratory calibrations.

Evaluation of direct and indirect ethanol biomarkers using a likelihood ratio approach to identify chronic alcohol abusers for forensic purposes

The detection of direct ethanol metabolites, such as ethyl glucuronide (EtG) and fatty acid ethyl esters (FAEEs), in scalp hair is considered the optimal strategy to effectively recognize chronic alcohol misuses by means of specific cut-offs suggested by the Society of Hair Testing. However, several factors (e.g. hair treatments) may alter the correlation between alcohol intake and biomarkers concentrations, possibly introducing bias in the interpretative process and conclusions. 125 subjects with various drinking habits were subjected to blood and hair sampling to determine indirect (e.g. CDT) and direct alcohol biomarkers. The overall data were investigated using several multivariate statistical methods. A likelihood ratio (LR) approach was used for the first time to provide predictive models for the diagnosis of alcohol abuse, based on different combinations of direct and indirect alcohol biomarkers. LR strategies provide a more robust outcome than the plain comparison with cut-off values, where tiny changes in the analytical results can lead to dramatic divergence in the way they are interpreted. An LR model combining EtG and FAEEs hair concentrations proved to discriminate non-chronic from chronic consumers with ideal correct classification rates, whereas the contribution of indirect biomarkers proved to be negligible. Optimal results were observed using a novel approach that associates LR methods with multivariate statistics. In particular, the combination of LR approach with either Principal Component Analysis (PCA) or Linear Discriminant Analysis (LDA) proved successful in discriminating chronic from non-chronic alcohol drinkers. These LR models were subsequently tested on an independent dataset of 43 individuals, which confirmed their high efficiency. These models proved to be less prone to bias than EtG and FAEEs independently considered. In conclusion, LR models may represent an efficient strategy to sustain the diagnosis of chronic alcohol consumption and provide a suitable gradation to support the judgment.

Development and validation of a GC–MS method for nicotine detection in Calliphora vomitoria (L.) (Diptera: Calliphoridae)

Entomotoxicology is the application of toxicological methods and analytical procedures on necrophagous insects feeding on decomposing tissues to detect drugs and other chemical components, and their mechanisms affecting insect development and morphology and modifying the methodology for estimation of minimum time since death. Nicotine is a readily available potent poison. Because of its criminal use, a gas chromatography-mass spectrometry (GC-MS) method for the detection of nicotine in Calliphora vomitoria L. (Diptera: Calliphoridae) was developed and validated. Furthermore, the effect of nicotine on the development, growth rate, and survival of this blowfly was studied. Larvae were reared on liver substrates homogeneously spiked with measured amounts of nicotine (2, 4, and 6 ng/mg) based on concentrations that are lethal to humans. The results demonstrated that (a) the GC-MS method can detect both nicotine and its metabolite cotinine in immature C. vomitoria; (b) the presence of nicotine in the aforementioned three concentrations in food substrates did not modify the developmental time of C. vomitoria; (c) during the pupation period, larvae exposed to nicotine died depending on the concentration of nicotine in the substrate; and (d) the resultant lengths of larvae and pupae exposed to 4 and 6 ng/mg concentrations of nicotine were significantly shorter than those of the control.

Direct and indirect alcohol biomarkers data collected in hair samples - multivariate data analysis and likelihood ratio interpretation perspectives

The concentration values of direct and indirect biomarkers of ethanol consumption were detected in blood (indirect) or hair (direct) samples from a pool of 125 individuals classified as either chronic (i.e. positive) and non-chronic (i.e. negative) alcohol drinkers. These experimental values formed the dataset under examination (Table 1). Indirect biomarkers included: aspartate transferase (AST), alanine transferase (ALT), gamma-glutamyl transferase (GGT), mean corpuscular volume of the erythrocytes (MCV), carbohydrate-deficient-transferrin (CDT). The following direct biomarkers were also detected in hair: ethyl myristate (E14:0), ethyl palmitate (E16:0), ethyl stearate (E18:1), ethyl oleate (E18:0), the sum of their four concentrations (FAEEs, i.e. Fatty Acid Ethyl Esters) and ethyl glucuronide (EtG; pg/mg). Body mass index (BMI) was also collected as a potential influencing factor. Likelihood ratio (LR) approaches have been used to provide predictive models for the diagnosis of alcohol abuse, based on different combinations of direct and indirect alcohol biomarkers, as described in “Evaluation of direct and indirect ethanol biomarkers using a likelihood ratio approach to identify chronic alcohol abusers for forensic purposes” (E. Alladio, A. Martyna, A. Salomone, V. Pirro, M. Vincenti, G. Zadora, 2017) [1].

Development and validation of a Partial Least Squares − Discriminant Analysis (PLS-DA) model based on the determination of Ethyl Glucuronide (EtG) and Fatty Acid Ethyl Esters (FAEEs) in hair for the diagnosis of chronic alcohol abuse

The chronic intake of an excessive amount of alcohol is currently ascertained by determining the concentration of direct alcohol metabolites in the hair samples of the alleged abusers, including ethyl glucuronide (EtG) and, less frequently, fatty acid ethyl esters (FAEEs). Indirect blood biomarkers of alcohol abuse are still determined to support hair EtG results and diagnose a consequent liver impairment. In the present study, the supporting role of hair FAEEs is compared with indirect blood biomarkers with respect to the contexts in which hair EtG interpretation is uncertain. Receiver Operating Characteristics (ROC) curves and multivariate Principal Component Analysis (PCA) demonstrated much stronger correlation of EtG results with FAEEs than with any single indirect biomarker or their combinations. Partial Least Squares Discriminant Analysis (PLS-DA) models based on hair EtG and FAEEs were developed to maximize the biomarkers information content on a multivariate background. The final PLS-DA model yielded 100% correct classification on a training/evaluation dataset of 155 subjects, including both chronic alcohol abusers and social drinkers. Then, the PLS-DA model was validated on an external dataset of 81 individual providing optimal discrimination ability between chronic alcohol abusers and social drinkers, in terms of specificity and sensitivity. The PLS-DA scores obtained for each subject, with respect to the PLS-DA model threshold that separates the probabilistic distributions for the two classes, furnished a likelihood ratio value, which in turn conveys the strength of the experimental data support to the classification decision, within a Bayesian logic. Typical boundary real cases from daily work are discussed, too.

Systematic optimisation of ethyl glucuronide extraction conditions from scalp hair by design of experiments and its potential effect on cut-off values appraisal

The quantitative determination of ethyl glucuronide (EtG) in hair samples is consistently used throughout the world to assess chronic excessive alcohol consumption. For administrative and legal purposes, the analytical results are compared with cut-off values recognised by regulatory authorities and scientific societies. However, it has been recently recognised that the analytical results depend on the hair sample pretreatment procedures, including the crumbling and extraction conditions. A systematic evaluation of the EtG extraction conditions from pulverised scalp hair was conducted by Design of Experiments (DoE) considering the extraction time, temperature, pH, and solvent composition as potential influencing factors. It was concluded that an overnight extraction at 60°C with pure water at neutral pH represents the most effective conditions to achieve high extraction yields. The absence of differential degradation of the internal standard (isotopically-labelled EtG) under such conditions was confirmed and the overall analytical method was validated according to SGWTOX and ISO17025 criteria. Twenty real hair samples with different EtG content were analysed with 3 commonly accepted procedures: (a) hair manually cut in snippets and extracted at room temperature; (b) pulverised hair extracted at room temperature; (c) hair treated with the optimised method. Average increments of EtG concentration around 69% (from a to c) and 29% (from b to c) were recorded. In light of these results, the authors urge the scientific community to undertake an inter-laboratory study with the aim of defining more in detail the optimal hair EtG detection method and verifying the corresponding cut-off level for legal enforcements.

Chemometric approach to open validation protocols: Prediction of validation parameters in multi-residue ultra-high performance liquid chromatography–tandem mass spectrometry methods

The recent technological advancements of liquid chromatography-tandem mass spectrometry allow the simultaneous determination of tens, or even hundreds, of target analytes. In such cases, the traditional approach to quantitative method validation presents three major drawbacks: (i) it is extremely laborious, repetitive and rigid; (ii) it does not allow to introduce new target analytes without starting the validation from its very beginning and (iii) it is performed on spiked blank matrices, whose very nature is significantly modified by the addition of a large number of spiking substances, especially at high concentration. In the present study, several predictive chemometric models were developed from closed sets of analytes in order to estimate validation parameters on molecules of the same class, but not included in the original training set. Retention time, matrix effect, recovery, detection and quantification limits were predicted with partial least squares regression method. In particular, iterative stepwise elimination, iterative predictors weighting and genetic algorithms approaches were utilized and compared to achieve effective variables selection. These procedures were applied to data reported in our previously validated ultra-high performance liquid chromatography-tandem mass spectrometry multi-residue method for the determination of pharmaceutical and illicit drugs in oral fluid samples in accordance with national and international guidelines. Then, the partial least squares model was successfully tested on naloxone and lormetazepam, in order to introduce these new compounds in the oral fluid validated method, which adopts reverse-phase chromatography. Retention time, matrix effect, recovery, limit of detection and limit of quantification parameters for naloxone and lormetazepam were predicted by the model and then positively compared with their corresponding experimental values. The whole study represents a proof-of-concept of chemometrics potential to reduce the routine workload during multi-residue methods validation and suggests a rational alternative to ever-expanding procedures progressively drifting apart from real sample analysis.

Correlation between chronological and physiological age of males from their multivariate urinary endogenous steroid profile and prostatic carcinoma-induced deviation

Graphical abstract Figure. No caption available. HighlightsAn efficient GC–MS method is validated for a panel of 18 urinary steroids.A Kernel‐PLS algorithm investigates the age dependence of the steroid panel.The age‐regression model does not hold for subjects affected by prostate carcinoma.PLS‐DA on steroid panel discriminates healthy from pathological individuals. Abstract The biosynthesis of endogenous androgenic anabolic steroids (EAAS) in males varies with age. Knowledge of the general urinary EAAS profile’s dependence from aging – not reported up to now – may represents a prerequisite for its exploitation in the screening and diagnostic support for several pathologies. Extended urinary EAAS profiles were obtained from healthy and pathological individuals, using a GC–MS method which was fully validated by a stepwise, analyst‐independent scheme. Seventeen EAAS and five of their concentration ratios were determined and investigated using multivariate statistical methods. A regression model based on Kernel partial least squares algorithm was built to correlate the chronological age of healthy male individuals with their “physiological age” as determined from their urinary EAAS profile. Strong correlation (R2 = 0.75; slope = 0.747) and good prediction ability of the real chronological age was inferred from EAAS data. In contrast, patients with recent diagnosis (not pharmacologically treated) of prostatic carcinoma (PCa) exhibited a comprehensive EAAS profile with strong negative deviation from the model, corresponding a younger predicted age. This result is possibly related to the activation of anomalous steroid biosynthesis induced from PCa. Over a restricted 60–80 years‐old population, PLS‐discriminant analysis (DA) was used to distinguish healthy subjects from patients with untreated PCa. PLS‐DA yielded excellent discrimination (sensitivity and specificity >90%) between healthy and pathological individuals. This proof‐of‐concept study provides a preliminary evaluation of multivariate DA on wide EAAS profiles as a screening method to distinguish PCa from non‐pathological conditions, overcoming the potentially interfering effect of ageing.

New insights into the protogenic and spectroscopic properties of commercial tannic acid: the role of gallic acid impurities

Tannic acid (TA) belongs to the class of hydrolysable tannins that are natural polymers derived from the vegetable kingdom. Although TA is described as a molecule with a central core of glucose esterified with five digallic units, its molecular structure has not yet been completely clarified. Actually, TA is described as a mixture of different compounds. In this work, by using potentiometry, UV-vis and fluorescence spectroscopy, as well as ab initio calculations we identified the protonation properties and spectroscopic features of TA. A preliminary investigation on gallic acid (GA), present as an impurity in the commercial TA mixture, and on methyl 3,4,5-trihydroxybenzoate served as a benchmark for the computational work and gave insight into the contribution of GA to the TA properties. GA principally affects the pH of TA solutions and the fluorescence signals. The data showed the presence of three main types of protogenic groups that can be assigned to the typical TA structure, with pKa values included in the range of 6–8.5, which can be ascribed to the phenolic functions. The least acidic site shows the highest concentrations, and the dissociation of half of the TA phenolic groups takes place at pH ∼ 7.8. The UV-vis spectra of the protonated and deprotonated species were obtained through data elaboration by stoichiometric and chemometric approaches. The results show main absorption maxima (277 and 323 nm, respectively) similar to those obtained using ab initio calculations. Overall, we achieved a remarkable coherence among the outcomes obtained by using different methodologies.

Hair analysis can provide additional information in doping and forensic cases involving clostebol

Clostebol is a synthetic anabolic androgenic steroid, with potential use as a performance-enhancing drug if taken for long periods in order to produce the desired effect. Recently, the use of medications containing clostebol acetate has led to the suspension of several athletes in various sports. Previous studies have shown that urine can result positive in case of single intake of a banned substance, including unintentional consumption of steroids. In this context, a hair test can contribute to exculpation of athletes by demonstrating alternative administration or contamination. The development and validation of an ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method to detect clostebol and clostebol acetate in hair is hereby presented. Some real cases of athletes sanctioned for clostebol use, in which we analyzed hair samples to follow up investigations of doping control laboratories and obtain useful elements to understand the origin of clostebol intakes, and two forensic cases of anabolic drugs abuse, are also presented and discussed. In real head- and body-hair samples, clostebol acetate could be detected in the low pg/mg range. As is typical of hair analysis, the interpretation of the quantitative findings may be challenging, and even more in sports owing to the lack of systematic studies. However, the results can be used to produce evidence contrary to any ruling issued against the athletes by the appropriate sports body, and possibly obtain a diminished sanction. Because the sports authorities do not make a distinction among circumstances or means of administration of anabolic compounds, athletes should be warned not to use clostebol-containing medications.