Cannabis use and its association with psychopathological symptoms in a Swiss adult population: a cross-sectional analysis.

Background: As the most commonly used illicit substance, cannabis is gaining global acceptance through increasing legalization efforts. This shift intensifies the need for research to guide policymakers and healthcare providers in harm reduction and treatment strategies. Nonetheless, the relationship between psychopathological symptoms and cannabis use remains inadequately understood. Methods: A sample of regular cannabis consumers completed self-reported assessments for depression (Patient Health Questionnaire-9), anxiety (General Anxiety Disorder-7), Attention-Deficit/Hyperactivity Disorder (ADHD; Adult ADHD Self-Report Scale V1.1), and psychosis (Early Recognition Inventory based on IRAOS) as well as previous black-market cannabis use patterns. Cannabis Use Disorder Identification Test Revised (CUDIT-R) was used to identify cannabis use disorder (CUD). To understand psychopathological symptom load related to cannabis consumption as well as cannabis use motives, multiple regression models were performed to identify psychopathological variables predicting cannabis use frequency and quantity. Linear regression and correlation analyses were conducted, adjusting for relevant covariates (age, gender, education, alcohol, other substance use). Results: Three-hundred-sixty regular cannabis users interested in a study on regulated cannabis access in Basel, Switzerland were examined. In bivariate analysis, cannabis use frequency correlated with depressive (r(358) = 0.16, p = 0.003) and anxiety symptom load (r(358) = 0.11, p = 0.034). Cannabis quantity correlated with depressive (r(358) = 0.15, p = 0.005), ADHD (r(358) = 0.14, p = 0.008), and psychosis symptom load (r(358) = 0.16, p = 0.002). However, in the adjusted regression models only depressive and ADHD symptom loads were significantly associated with cannabis use frequency (p = 0.006 and p = 0.034, respectively) and quantity (p = 0.037 and p = 0.019, respectively). No significant correlations between cannabis consumption and anxiety or psychosis remained after adjustment. Conclusion: ADHD and depressive symptoms correlate with increased cannabis use in a cohort of regular users, suggesting potential self-medication in nonclinical populations. With the rising availability of cannabis worldwide, these results highlight the necessity for longitudinal studies to disentangle the complex dynamics between cannabis consumption and mental health symptoms.

Development and validation of an LC-MS/MS method for quantifying diamorphine and its major metabolites 6-monoacetylmorphine, morphine, morphine-3-glucuronide, and morphine-6-glucuronide in human plasma.

Diamorphine, commonly known as heroin, is a semi-synthetic opioid analgesic. In the context of heroin-assisted treatment for opioid-dependent patients, diamorphine is mostly administered intravenously. However, recent attention has shifted towards intranasal administration as a better-tolerated alternative to the intravenous route. Here, we developed and validated a rapid bioanalytical method for the simultaneous quantification of diamorphine and its major metabolites 6-monoacetylmorphine, morphine, morphine-3-glucuronide, and morphine-6-glucuronide in human plasma using liquid chromatography-tandem mass spectrometry (LC-MS/MS). A straightforward protein precipitation extraction step was used for sample preparation. Chromatographic analyte separation was achieved using a Kinetex EVO C18 analytical column and a mobile phase gradient comprising an aqueous solution of ammonium hydrogen carbonate and methanol supplied with formic acid. Employing positive electrospray ionization and scheduled multiple reaction monitoring, we established a quantification range of 1-1,000 ng/mL for all analytes. Our validation results demonstrate a mean intra-assay accuracy of 91-106% and an intra-assay precision (CV) between 2 and 9% for all analytes and over three validation runs. The method exhibits a high extraction recovery (> 87%) and a negligible matrix effect (99-125%). Furthermore, no interferences with endogenous plasma compounds were detected. Lastly, we applied the method to assess the plasma concentrations of an opioid-dependent patient after the intranasal administration of diamorphine in a clinical study. In summary, we have successfully developed a rapid, highly reliable, and straightforward bioanalytical method for quantifying diamorphine and its metabolites in low amounts of clinical plasma samples.