Investigating metabolic alterations induced by synthetic opioids using target LC-MS metabolomics

New Psychoactive Substances (NPS) are compounds synthesized from known molecules through chemical structure modifications. These substances continuously emerge on the illicit market, often without any regulatory approval or control, causing thousands of deaths each year. Among the various classes of NPS, synthetic opioids are of greatest global concern. Fentanyl and its analogues have profoundly impacted the landscape of illicit drugs in recent years, while newer substances such as nitazenes are gaining increasing prevalence on the illegal drug market [1]. It is therefore, essential to develop new analytical methodologies capable of providing reliable tools for the monitoring and control of these substances. In recent years, several studies have demonstrated that metabolomics represents a valuable approach for the identification of biomarkers associated with NPS intake, emerging as an innovative strategy in forensic toxicology [2]. The aim of this study is to develop a targeted metabolomics method to investigate the systemic effects induced by opioids belonging to different chemical classes, evaluating their impact on the murine metabolic profile following the administration of four opioids: morphine, brorphine, etonitazene, and fentanyl. The analyses were performed using liquid chromatography coupled with mass spectrometry, employing a QTRAP instrument in Multiple Reaction Monitoring (MRM) mode. A total of twenty-three metabolites were included in the study, previously reported as altered in untargeted metabolomics studies following opioid exposure, primarily associated with amino acid, catecholamine, and tricarboxylic acid pathways. After optimizing the chromatographic and spectrometric parameters for the metabolites of interest, the method was validated and applied to the analysis of murine samples. The selected metabolites were quantified, and multivariate statistical techniques were subsequently employed to identify a common metabolic pattern associated with opioid administration, thereby providing a comprehensive overview of the biological perturbations induced by these substances. The findings obtained offer potential support in forensic contexts for the detection of opioid use or abuse, contributing concretely to strategies aimed at counteracting the spread of NPS