Precision medicine for alcohol use disorder (AUD) allows optimal treatment of the right patient with the right drug at the right time. Here, we generated multivariable models incorporating clinical information and serum metabolite levels to predict acamprosate treatment response. The sample of 120 patients was randomly split into a training set (n = 80) and test set (n = 40) five independent times. Treatment response was defined as complete abstinence (no alcohol consumption during 3 months of acamprosate treatment) while nonresponse was defined as any alcohol consumption during this period. In each of the five training sets, we built a predictive model using a least absolute shrinkage and section operator (LASSO) penalized selection method and then evaluated the predictive performance of each model in the corresponding test set. The models predicted acamprosate treatment response with a mean sensitivity and specificity in the test sets of 0.83 and 0.31, respectively, suggesting our model performed well at predicting responders, but not non-responders (i.e. many non-responders were predicted to respond). Studies with larger sample sizes and additional biomarkers will expand the clinical utility of predictive algorithms for pharmaceutical response in AUD.

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IntroductionComorbidity between alcoholism and depression has long been acknowledged, and the possibility that similar brain mechanisms, involving both serotonergic (5-HT) and noradrenergic systems (NE), underlie both pathologies has been suggested. Thus, inhibitors of NE and 5HT uptake have been proposed for the treatment of alcoholism, as they have shown to reduce alcohol intake in various animal models. However, most of the studies mentioned were carried out acutely and there is a lack of knowledge of the possible long-term effects. Clinical studies report an overall low efficacy of antidepressant treatment on alcohol consumption, or even a worsened prognosis. In addition, several cases of alcohol dependence following antidepressant treatment have been reported in the literature.ObjectivesWe aimed at comparing the acute and chronic effects of the treatment with the antidepressant drug reboxetine on alcohol consumption.MethodsWe used a rat model of alcohol self-administration, and two different schedules of reboxetine administration (acute and chronic).ResultsOur results confirm the acute suppressant effects of reboxetine on alcohol consumption but indicate that, when this drug is administered chronically in a period of abstinence from alcohol, it can significantly increase the rate of alcohol self-administration.ConclusionsThese results are important for the understanding of the clinical reports describing cases of increased alcohol consumption after antidepressant treatment, and suggest that much more research is needed to fully understand the long term effects of antidepressants, which remain the most widely prescribed class of drugs.Disclosure of interestThe authors have not supplied their declaration of competing interest.