Metabolomic Fingerprint of Behavioral Changes in Response to Full-Spectrum Cannabis Extracts - Maayah, Zaid H.; Raposo, Pamela J. F.; Silver, Heidi; Mandal, Rupasri; Ellis, Lee; Alam, Abrar S.; Takahara, Shingo; Ferdaoussi, Mourad; Mathewson, Kyle E.; Eurich, Dean T.; Fouad, Karim; Wishart, David S.; et al. (Frontiers in Pharmacology, 2022)
Background: Numerous existing full cannabis extract products have been used in clinical trials for the treatment of various diseases. Despite their efficacy, the clinical use of some of these full cannabis extracts is limited by behavioral side effect such as cognitive dysfunction and impaired motor skills. To better understand what constitutes cannabis-induced behavioral effects, our objective was to identify a novel panel of blood-based metabolites that are predictive, diagnostic, and/or prognostic of behavioral effects. Method: At 8 weeks of age, male rats were randomly assigned into groups and were gavage fed with full-spectrum cannabis extract (tetrahydrocannabinol/cannabidiol (THC/CBD) along with all other compounds, 15 mg/kg), broad-spectrum cannabis extract (CBD along with all other compounds, 15 mg/kg) or vehicle oil. Four hours after being gavage fed, behavioral assessments were determined using the open field test and the elevated plus maze. Following these assessments, serum was collected from all rats and the serum metabolites were identified and quantified by LC-MS/MS and 1H-NMR spectroscopy. Results: We found that only rats treated with full-spectrum cannabis extract exhibited behavioral changes. Compared to vehicle and broad-spectrum extract-treated rats, full-spectrum extract-treated rats demonstrated higher serum concentrations of the amino acid phenylalanine and long-chain acylcarnitines, as well as lower serum concentrations of butyric acid and lysophosphatidylcholines. This unique metabolomic fingerprint in response to cannabis extracts administration is linked to behavioral effects and may represent a biomarker profile of cannabis-induced behavioral changes. If validated, this work may allow a metabolomics-based decision tree that would aid in the rapid diagnosis of cannabis-induced behavioral changes including cognitive impairment.