title: Evaluation of direct and indirect ethanol biomarkers using a likelihood ratio approach to identify chronic alcohol abusers for forensic purposes.
abstract: 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.
authors.affiliation: Dipartimento di Chimica, Università degli Studi di Torino, Via P. Giuria 7, 10125 Torino, Italy; Centro Regionale Antidoping e di Tossicologia "A. Bertinaria", Regione Gonzole 10/1, 10043 Orbassano, Torino, Italy. Electronic address: ealladio@unito.it.
authors.forename: Eugenio
authors.initials: E
authors.lastname: Alladio
authors.affiliation: Department of Analytical Chemistry, Chemometric Research Group, Institute of Chemistry, The University of Silesia, Szkolna 9, 40-006 Katowice, Poland. Electronic address: ag.rzepecka@gmail.com.
authors.forename: Agnieszka
authors.initials: A
authors.lastname: Martyna
authors.affiliation: Centro Regionale Antidoping e di Tossicologia "A. Bertinaria", Regione Gonzole 10/1, 10043 Orbassano, Torino, Italy. Electronic address: alberto.salomone@antidoping.piemonte.it.
authors.forename: Alberto
authors.initials: A
authors.lastname: Salomone
authors.affiliation: Department of Chemistry, Purdue University, 560 Oval Drive, West Lafayette, 47907 IN, USA. Electronic address: vpirro@purdue.edu.
authors.forename: Valentina
authors.initials: V
authors.lastname: Pirro
authors.affiliation: Dipartimento di Chimica, Università degli Studi di Torino, Via P. Giuria 7, 10125 Torino, Italy; Centro Regionale Antidoping e di Tossicologia "A. Bertinaria", Regione Gonzole 10/1, 10043 Orbassano, Torino, Italy. Electronic address: marco.vincenti@unito.it.
authors.forename: Marco
authors.initials: M
authors.lastname: Vincenti
authors.affiliation: Department of Analytical Chemistry, Chemometric Research Group, Institute of Chemistry, The University of Silesia, Szkolna 9, 40-006 Katowice, Poland; Institute of Forensic Research, Westerplatte 9, 31-033 Krakow, Poland. Electronic address: gzadora@ies.krakow.pl.
authors.forename: Grzegorz
authors.initials: G
authors.lastname: Zadora
mesh_terms: D000437:Alcoholism / Q000175:diagnosis*; D015415:Biomarkers / Q000032:analysis; D016002:Discriminant Analysis; D004952:Esters / Q000032:analysis*; D005227:Fatty Acids / Q000032:analysis*; D005260:Female; D053593:Forensic Toxicology / Q000379:methods; D005965:Glucuronates / Q000032:analysis*; D006197:Hair / Q000737:chemistry*; D006801:Humans; D016013:Likelihood Functions; D008297:Male; D025341:Principal Component Analysis
chemical_list: D015415:Biomarkers; D004952:Esters; D005227:Fatty Acids; D005965:Glucuronates; C093924:ethyl glucuronide
keywords: Alcohol; Empirical cross entropy; EtG; FAEE; Hair analysis; Likelihood ratio