Shading new light on the systemic response following new synthetic opioid intake through metabolomics

Novel psychoactive substances (NPS) represent a broad class of new drugs that often allow passing drug-screening tests. They are characterized by a variety of structures, thus creating an ever-changing scenario with evolving analytical targets. This study aimed at developing an indirect screening strategy for NPS monitoring, and specifically for new synthetic opioids, based on assessing changes in endogenous urinary metabolite levels resulting from the systemic response following their intake. The experimental design involved in-vivo CD-1 mice models. Twenty animals (10 male, 10 female) received different treatments. At day 0, mice were treated with a vehicle and urine was collected at 0-12h and 12-24h. On day 1, brorphine was administrated to half of the animals of both genders, while the other half received etonitazene; urine samples were collected at the same time intervals. A second drug administration and subsequent urine collection occurred at day 8. Finally, following a one-week washout, urine was collected again at day 15. Animal urine samples were analyzed by LC-HRMS/MS with an untargeted metabolomics platform. Mass spectra were acquired on an Orbitrap Q-Exactive mass spectrometer in full scan/data dependent acquisition mode; every sample was analyzed with both RP and HILIC chromatography in both polarities. Given the large amount of information in the metabolomic matrix, the data underwent a pre-treatment phase to ensure uniformity. By combining multivariate analysis (PLS-DA) and univariate analysis (Volcano plot), it was possible to identify the most altered metabolites following acute drug administration. These included metabolites involved in lipid peroxidation, inflammatory processes, oxidative stress, nucleotide metabolism and others. To assess metabolome changes based on different factors such as collection time, gender, and drug treatment, advanced chemometrics techniques were used. The adopted approach offered a new perspective to address the scarcity of studies on the urinary metabolic profile of opiate-treated mice.