Gianmarco Pezzutia, Ludovica Chiodoa, Ilenia Bracagliaa,b, Martina Crocea,b, Francesco Bartolinia, Camilla Montesanoa, Adolfo Gregoric, Fabiana Di Rosac, Manuel Sergia

aUniversity of Rome “La Sapienza”, Department of Chemistry, Rome, Italy
bUniversity of Rome “La Sapienza”, Department of Public health and Infectious diseases, Rome, Italy
cCarabinieri, Department of Scientific Investigations (RIS), Viale Tor di Quinto 151, Rome, Italy

New psychoactive substances (NPS) include a wide range of compounds, often called 'legal drugs'. These substances produce central nervous system (CNS) effects similar to those of existing drugs, although in many cases the effects are even more powerful. The identification of NSPs is a major challenge for researchers and law enforcement, given the difficulty in detecting them, it is therefore crucial to develop new methods of identification. Metabolomics-based approaches have recently been published, focusing on the identification of endogenous biomarkers related to NPS consumption [1] rather than on the chemical structure of drugs. Only recently, a study on morphine and fentanyl [2] demonstrated the potential of this approach by observing changes in levels of endogenous urinary metabolites in murine models following opioid administration. 

For this purpose, it is necessary to develop a metabolomic workflow for the identification of biomarkers related to the use of new psychoactive substances. In this work an HPLC-HRMS method was carried out for the identification of a wide range of endogenous metabolites, using an Orbitrap Q Exactive mass spectrometer, working in Data dependent (DDA) acquisition mode, equipped with a HESI source operating both in positive and negative polarity. After optimized the chromatographic columns, mobile phases and gradients, urine mice samples, collected before and after the administration of two opioids (etonitazene and brorphine), were analysed by reverse phase chromatography (RP) and hydrophilic interaction chromatography (HILIC). Therefore, data were processed with Compound DiscovererTM 3.2 (Thermo ScientificTM, USA) using a metabolomic workflow for alignment of retention times, detection of components, prediction of elemental composition and fill gaps. In addition, a spectral library was built by collecting the fragmentation spectra of the monitored analytes and inserted into the metabolic workflow, in order to allow a more immediate recognition of the analytes.

Keywords: Metabolomics, New Psychoactive Substances, HPLC-HRMS.

References

1. Steuer AE, Brockbals L, et al., Front. Chem., 7 (2019), 319.  DOI: 10.3389/fchem.2019.00319 

2. Di Francesco G et al. Scientific Reports, 14 (2024), 9432. DOI: 10.1038/s41598-024-60045-2