Consortium Profile: The Methylation, Imaging and NeuroDevelopment (MIND) Consortium.

Epigenetic processes, such as DNA methylation, show potential as biological markers and mechanisms underlying gene-environment interplay in the prediction of mental health and other brain-based phenotypes. However, little is known about how peripheral epigenetic patterns relate to individual differences in the brain itself. An increasingly popular approach to address this is by combining epigenetic and neuroimaging data; yet, research in this area is almost entirely comprised of cross-sectional studies in adults. To bridge this gap, we established the Methylation, Imaging and NeuroDevelopment (MIND) Consortium, which aims to bring a developmental focus to the emerging field of Neuroimaging Epigenetics by (i) promoting collaborative, adequately powered developmental research via multi-cohort analyses; (ii) increasing scientific rigor through the establishment of shared pipelines and open science practices; and (iii) advancing our understanding of DNA methylation-brain dynamics at different developmental periods (from birth to emerging adulthood), by leveraging data from prospective, longitudinal pediatric studies. MIND currently integrates 15 cohorts worldwide, comprising (repeated) measures of DNA methylation in peripheral tissues (blood, buccal cells, and saliva) and neuroimaging by magnetic resonance imaging across up to five time points over a period of up to 21 years (Npooled DNAm = 11,299; Npooled neuroimaging = 10,133; Npooled combined = 4,914). By triangulating associations across multiple developmental time points and study types, we hope to generate new insights into the dynamic relationships between peripheral DNA methylation and the brain, and how these ultimately relate to neurodevelopmental and psychiatric phenotypes.

Persistent increased severity of cannabis use disorder symptoms in adolescents compared to adults: a one-year longitudinal study.

Adolescence is a developmental period characterised by increased vulnerability to cannabis use disorder (CUD). However, previous investigations of this vulnerability have relied on cross-sectional comparisons and lack a detailed assessment of cannabis quantity, a potentially important confounding factor. Here, we aimed to investigate the one-year course of CUD in adolescents compared to adults who currently use cannabis, adjusting for a comprehensive measure of cannabis quantity. Data are from a one-year observational longitudinal study (CannTeen) of adolescents and adults who currently used cannabis regularly with five waves of assessment at 3-monthly intervals, based in London, UK. Participants were n = 70 adults (26-29, 45.7% female), who did not regularly use cannabis when they were under age 18, and n = 76 adolescents (16-17, 50.0% female). The exposure was adolescent (compared to adult) frequent cannabis use. The primary outcome was CUD symptoms measured using the cannabis use disorder identification test revised (CUDIT-R) at five time points. Models were adjusted for cannabis quantity using mean weekly standard THC units (one unit = 5 mg THC). Other covariates included gender, and whether each session occurred before or during the COVID-19 pandemic. In models adjusted for pre-registered covariates, adolescents scored 3.7 points higher on the CUDIT-R compared to the adult group across the 5 assessment waves (3.66 95% CIs 1.99, 5.34). There was also evidence of a linear reduction in symptoms over time in both groups (-0.47, 95%CIs -0.67, -0.27). Adolescents had persistently increased CUD symptoms compared to adults across the 12-month period. This association was robust after adjusting for the quantity of cannabis consumed and other covariates.

Applying machine learning to international drug monitoring: classifying cannabis resin collected in Europe using cannabinoid concentrations.

In Europe, concentrations of ∆9-tetrahydrocannabinol (THC) in cannabis resin (also known as hash) have risen markedly in the past decade, potentially increasing risks of mental health disorders. Current approaches to international drug monitoring cannot distinguish between different types of cannabis resin which may have contrasting health effects due to THC and cannabidiol (CBD) content. Here, we compared concentrations of THC and CBD in different types of cannabis resin collected in Europe (either Moroccan-type, or Dutch-type). We then tested the ability of machine learning algorithms to classify the type of cannabis resin (either Moroccan-type, or Dutch-type) using routinely collected monitoring data on THC and CBD. Finally, we applied the optimal algorithm to new samples collected in countries where the type of cannabis resin was unknown, the UK and Denmark. Results showed that overall, Dutch-type samples had higher THC (Hedges' g = 2.39) and lower CBD (Hedges' g = 0.81) than Moroccan-type samples. A Support Vector Machine algorithm achieved classification accuracy exceeding 95%, with little variation in this estimate, good interpretability, and plausibility. It made contrasting predictions about the type of cannabis resin collected in the UK (94% Moroccan-type; 6% Dutch-type) and Denmark (36% Moroccan-type; 64% Dutch-type). In conclusion, we provide proof-of-concept evidence for the potential of machine learning to inform international drug monitoring. Our findings should not be interpreted as objective confirmatory evidence but suggest that Dutch-type cannabis resin has higher THC concentrations than Moroccan-type cannabis resin, which may contribute to variation in drug markets and health outcomes for people who use cannabis in Europe.

Acute effects of different types of cannabis on young adult and adolescent resting-state brain networks.

Adolescence is a time of rapid neurodevelopment and the endocannabinoid system is particularly prone to change during this time. Cannabis is a commonly used drug with a particularly high prevalence of use among adolescents. The two predominant phytocannabinoids are Delta-9-tetrahydrocannabinol (THC) and cannabidiol (CBD), which affect the endocannabinoid system. It is unknown whether this period of rapid development makes adolescents more or less vulnerable to the effects of cannabis on brain-network connectivity, and whether CBD may attenuate the effects of THC. Using fMRI, we explored the impact of vaporized cannabis (placebo, THC: 8 mg/75 kg, THC + CBD: 8 mg/75 kg THC & 24 mg/75 kg CBD) on resting-state networks in groups of semi-regular cannabis users (usage frequency between 0.5 and 3 days/week), consisting of 22 adolescents (16-17 years) and 24 young adults (26-29 years) matched for cannabis use frequency. Cannabis caused reductions in within-network connectivity in the default mode (F[2,88] = 3.97, P = 0.022, η² = 0.018), executive control (F[2,88] = 18.62, P < 0.001, η² = 0.123), salience (F[2,88] = 12.12, P < 0.001, η² = 0.076), hippocampal (F[2,88] = 14.65, P < 0.001, η² = 0.087), and limbic striatal (F[2,88] = 16.19, P < 0.001, η² = 0.102) networks compared to placebo. Whole-brain analysis showed cannabis significantly disrupted functional connectivity with cortical regions and the executive control, salience, hippocampal, and limbic striatal networks compared to placebo. CBD did not counteract THC's effects and further reduced connectivity both within networks and the whole brain. While age-related differences were observed, there were no interactions between age group and cannabis treatment in any brain network. Overall, these results challenge the assumption that CBD can make cannabis safer, as CBD did not attenuate THC effects (and in some cases potentiated them); furthermore, they show that cannabis causes similar disruption to resting-state connectivity in the adolescent and adult brain.

The acute effects of cannabis, with and without cannabidiol, on attentional bias to cannabis related cues: a randomised, double-blind, placebo-controlled, cross-over study.

RATIONALE: Attentional bias to drug-related stimuli is hypothesised to contribute towards addiction. However, the acute effects of Δ9-tetrahydrocannabinol (THC) on attentional bias to cannabis cues, the differential response in adults and adolescents, and the moderating effect of cannabidiol (CBD) are unknown. OBJECTIVES: Our study investigated (1) the acute effects of vaporised cannabis on attentional bias to cannabis-related images in adults and adolescents and (2) the moderating influences of age and CBD. METHODS: We conducted a randomised, double-blind, placebo-controlled, cross-over study where three weight-adjusted vaporised cannabis preparations: 'THC' (8 mg THC for a 75-kg person), 'THC + CBD' (8 mg THC and 24 mg CBD for a 75-kg person) and PLA (matched placebo). Cannabis was administered on 3 separate days to 48 participants, who used cannabis 0.5-3 days/week: 24 adolescents (12 females, aged 16-17) and 24 adults (12 females, aged 26-29). Participants completed a visual probe task with cannabis cues. Our primary outcome was attentional bias to cannabis stimuli, measured using the differential reaction time to a cannabis vs. neutral probe, on 200-ms trials. RESULTS: In contrast to hypotheses, attention was directed away from cannabis cues on placebo, and there was a main effect of the drug (F(2,92) = 3.865, p = 0.024, η2p = 0.077), indicating THC administration eliminated this bias. There was no significant impact of CBD nor an age-by-drug interaction. CONCLUSIONS: Acute THC intoxication eliminated attentional bias away from cannabis cues. There was no evidence of differential response in adolescents compared to adults and no evidence that a moderate vaporised dose of CBD altered the impact of cannabis on attentional bias. TRIAL REGISTRATION: This study was listed with the US National Library of Medicine and registered on ClinicalTrials.gov, URL: Do Adolescents and Adults Differ in Their Acute Response to Cannabis?-Full Text View-ClinicalTrials.gov, registration number: NCT04851392.

Cannabidiol does not attenuate acute delta-9-tetrahydrocannabinol-induced attentional bias in healthy volunteers: A randomised, double-blind, cross-over study.

AIMS: To test how attentional bias and explicit liking are influenced by delta-9-tetrahydrocannabinol (THC) and whether these effects are moderated by cannabidiol (CBD). DESIGN: Double-blind, randomised, within-subjects cross-over study. SETTING: NIHR Wellcome Trust Clinical Research Facility at King's College Hospital, London, United Kingdom. PARTICIPANTS/CASES: Forty-six infrequent cannabis users (cannabis use <1 per week). INTERVENTION(S): Across four sessions, participants inhaled vaporised cannabis containing 10 mg of THC and either 0 mg (0:1 CBD:THC), 10 mg (1:1), 20 mg (2:1) or 30 mg (3:1) of CBD, administered in a randomised order and counter-balanced across participants (a total of 24 order groups). MEASUREMENTS: Participants completed two tasks: (1) Attentional Bias (AB), comparing reaction times toward visual probes presented behind 28 target stimuli (cannabis/food) compared with probes behind corresponding non-target (neutral) stimuli. Participants responding more quickly to probes behind target than non-target stimuli would indicate greater attentional bias to cannabis/food; (2) Picture Rating (PR), where all AB stimuli were rated on a 7-point pleasantness scale, measuring explicit liking. FINDINGS: During the AB task, participants were more biased toward cannabis stimuli in the 0:1 condition compared with baseline (mean difference = 12.2, 95% confidence intervals [CIs] = 1.20-23.3, d = 0.41, P = 0.03). No other significant AB or PR differences were found between cannabis and food stimuli between baseline and 0:1 condition (P > 0.05). No significant CBD effect was found on AB or PR task performance at any dose (P > 0.05). There was additionally no cumulative effect of THC exposure on AB or PR outcomes (P > 0.05). CONCLUSIONS: A double-blind, randomised, cross-over study among infrequent cannabis users found that inhaled delta-9-tetrahydrocannabinol increased attentional bias toward cannabis in the absence of explicit liking, a marker of liability toward cannabis use disorder. At the concentrations normally found in legal and illegal cannabis, cannabidiol had no influence on this effect.

The Long-Term Relationship Between Cannabis and Heroin Use: An 18- to 20-year Follow-Up of the Australian Treatment Outcome Study (ATOS).

OBJECTIVE: Cannabis use is common among individuals with opioid use disorder, but it remains unclear whether cannabis use is associated with an increase or a reduction in illicit opioid use. To overcome limitations identified in previous longitudinal studies with limited follow-ups, the authors examined a within-person reciprocal relationship between cannabis and heroin use at several follow-ups over 18 to 20 years. METHODS: The Australian Treatment Outcome Study (ATOS) recruited 615 people with heroin dependence in 2001 and 2002 and reinterviewed them at 3, 12, 24, and 36 months as well as 11 and 18-20 years after baseline. Heroin and cannabis use were assessed at each time point using the Opiate Treatment Index. A random-intercept cross-lagged panel model analysis was conducted to identify within-person relationships between cannabis use and heroin use at subsequent follow-ups. RESULTS: After accounting for a range of demographic variables, other substance use, and mental and physical health measures, an increase in cannabis use 24 months after baseline was significantly associated with an increase in heroin use at 36 months (estimate=0.21, SE=0.10). Additionally, an increase in heroin use at 3 months and 24 months was significantly associated with a decrease in cannabis use at 12 months (estimate=-0.27, SE=0.09) and 36 months (estimate=-0.22, SE=0.08). All other cross-lagged associations were not significant. CONCLUSIONS: Although there was some evidence of a significant relationship between cannabis and heroin use at earlier follow-ups, this was sparse and inconsistent across time points. Overall, there was insufficient evidence to suggest a unidirectional or bidirectional relationship between the use of these substances.

Enhanced cannabis timeline followback (EC-TLFB): Comprehensive assessment of cannabis use including standard THC units and validation through biological measures.

AIMS: The aims of this study were to present an enhanced cannabis timeline followback (EC-TLFB) enabling comprehensive assessment of cannabis use measures, including standard tetrahydrocannabinol (THC) units, and to validate these against objectively indexed urinary 11-nor-9-carboxy-tetrahydrocannabinol (THC-COOH) concentrations. DESIGN: We used cross-sectional baseline data from the 'CannTeen' observational longitudinal study. SETTING: The study was conducted in London, UK. PARTICIPANTS: A total of 147 participants who used cannabis regularly took part in the study (n = 71 female, n = 76 male; mean age = 21.90, standard deviation = 5.32). MEASUREMENTS: The EC-TLFB was used to calculate frequency of cannabis use, method of administration, including co-administration with tobacco, amount of cannabis used (measured with unaided self-report and also using pictorial aided self-report) and type of cannabis product (flower, hash) which was used to estimate THC concentration (both from published data on THC concentration of products and analysis of cannabis samples donated by participants in this study). We calculated total weekly standard THC units (i.e. 5 mg THC for all cannabis products and methods of administration) using the EC-TLFB. The outcome variable for validation of past week EC-TLFB assessments was creatinine-normalized carboxy-tetrahydrocannabinol (THC-COOH) in urine. FINDINGS: All measures of cannabis exposure included in this analysis were positively correlated with levels of THC-COOH in urine (r = 0.41-0.52). Standard THC units, calculated with average concentrations of THC in cannabis in the UK and unaided self-report measures of amount of cannabis used in grams showed the strongest correlation with THC-COOH in urine (r = 0.52, 95% bias-corrected and accelerated = 0.26-0.70). CONCLUSIONS: The enhanced cannabis timeline followback (EC-TLFB) can provide a valid assessment of a comprehensive set of cannabis use measures including standard tetrahydrocannabinol units as well as and traditional TLFB assessments (e.g. frequency of use and grams of cannabis use).

Assessing the association between global structural brain age and polygenic risk for schizophrenia in early adulthood: A recall-by-genotype study.

Neuroimaging studies consistently show advanced brain age in schizophrenia, suggesting that brain structure is often 'older' than expected at a given chronological age. Whether advanced brain age is linked to genetic liability for schizophrenia remains unclear. In this pre-registered secondary data analysis, we utilised a recall-by-genotype approach applied to a population-based subsample from the Avon Longitudinal Study of Parents and Children to assess brain age differences between young adults aged 21-24 years with relatively high (n = 96) and low (n = 93) polygenic risk for schizophrenia (SCZ-PRS). A global index of brain age (or brain-predicted age) was estimated using a publicly available machine learning model previously trained on a combination of region-wise gray-matter measures, including cortical thickness, surface area and subcortical volumes derived from T1-weighted magnetic resonance imaging (MRI) scans. We found no difference in mean brain-PAD (the difference between brain-predicted age and chronological age) between the high- and low-SCZ-PRS groups, controlling for the effects of sex and age at time of scanning (b = -.21; 95% CI -2.00, 1.58; p = .82; Cohen's d = -.034; partial R2 = .00029). These findings do not support an association between SCZ-PRS and brain-PAD based on global age-related structural brain patterns, suggesting that brain age may not be a vulnerability marker of common genetic risk for SCZ. Future studies with larger samples and multimodal brain age measures could further investigate global or localised effects of SCZ-PRS.

Cannabis use as a potential mediator between childhood adversity and first-episode psychosis: results from the EU-GEI case-control study.

BACKGROUND: Childhood adversity and cannabis use are considered independent risk factors for psychosis, but whether different patterns of cannabis use may be acting as mediator between adversity and psychotic disorders has not yet been explored. The aim of this study is to examine whether cannabis use mediates the relationship between childhood adversity and psychosis. METHODS: Data were utilised on 881 first-episode psychosis patients and 1231 controls from the European network of national schizophrenia networks studying Gene-Environment Interactions (EU-GEI) study. Detailed history of cannabis use was collected with the Cannabis Experience Questionnaire. The Childhood Experience of Care and Abuse Questionnaire was used to assess exposure to household discord, sexual, physical or emotional abuse and bullying in two periods: early (0-11 years), and late (12-17 years). A path decomposition method was used to analyse whether the association between childhood adversity and psychosis was mediated by (1) lifetime cannabis use, (2) cannabis potency and (3) frequency of use. RESULTS: The association between household discord and psychosis was partially mediated by lifetime use of cannabis (indirect effect coef. 0.078, s.e. 0.022, 17%), its potency (indirect effect coef. 0.059, s.e. 0.018, 14%) and by frequency (indirect effect coef. 0.117, s.e. 0.038, 29%). Similar findings were obtained when analyses were restricted to early exposure to household discord. CONCLUSIONS: Harmful patterns of cannabis use mediated the association between specific childhood adversities, like household discord, with later psychosis. Children exposed to particularly challenging environments in their household could benefit from psychosocial interventions aimed at preventing cannabis misuse.

Factors associated with drug use in prison: A systematic review of quantitative and qualitative evidence.

BACKGROUND: About a third of people use drugs during their incarceration, which is associated with multiple adverse health and criminal justice outcomes. Many studies have examined factors associated with in-prison drug use, but this evidence has not yet been systematically reviewed. We aimed to systematically review and synthesise the evidence on factors related to drug use in prison. METHODS: Three databases (PubMed, PsycINFO and Embase) were systematically searched as well as grey literature, for quantitative, qualitative and mixed-methods studies examining factors related to drug use inside prison. We excluded studies that did not explicitly measure in prison drug use or only measured alcohol and/or tobacco use. Study quality was assessed using the Newcastle Ottawa Scale (NOS) for quantitative studies and Critical Appraisal Skills Programme (CASP) for qualitative studies. The review was prospectively registered on PROSPERO (CRD42021295898). RESULTS: Fifty-four studies met the inclusion criteria, reporting data on 26,399 people in prison. Most studies were of low or moderate-quality, and all used self-report to assess drug use. In quantitative studies, studies found that previous criminal justice involvement, poor prison conditions, pre-prison drug use and psychiatric diagnosis were positively associated with drug use in prison. In qualitative studies, reasons for drug use were closely linked to the prison environment lacking purposeful activity and the social context of the prison whereby drug use was seen as acceptable, necessary for cohesion and pressurised. CONCLUSION: In the first systematic review of factors associated with drug use in prison, key modifiable risk factors identified from quantitative and qualitative studies were psychiatric morbidity and poor prison conditions. Non-modifiable factors included previous drug use and criminal history linked to substance use. Our findings indicate an opportunity to intervene and improve the prison environment to reduce drug use and associated adverse outcomes.

Synthetic cannabinoid use in an adult male prison in the UK.

INTRODUCTION: Synthetic cannabinoids (i.e. Spice) are a major public health problem in UK prisons, however, research in this area is limited. Here we aimed to draw comparisons between people with and without experience of using synthetic cannabinoids in prison, to characterise the features of, and motivations for use within this setting and evaluate support for different treatment interventions. METHOD: Questionnaires were administered to 122 people in a category-B prison for adult males in England between July 2022 and March 2023. Participants were asked questions related to their sociodemographic and custodial characteristics, use of synthetic cannabinoids (and other drugs) inside and outside of prison and psychological distress was measured via the Brief Symptom Inventory (BSI-18). Those that had ever used synthetic cannabinoids in prison completed additional questions related to features of use, motivations for use and support for various interventions. RESULTS: In total 46.7 % (n = 57) of participants reported use of synthetic cannabinoids in prison and this group experienced significantly greater levels of psychological distress compared to those reporting no use (mean (± standard deviation) BSI-18 scores = 23.7 (±16.7) vs 12.8 (±13.6), p < 0.001). Participants mostly reported using paper-based preparations (77.4 %) and use via e-cigarettes (75.9 %). The most strongly endorsed motivations for use included to alleviate boredom (91.1 % strongly agree/agree), to make the sentence pass faster (89.3 % strongly agree/agree) and to cope with stress (80.4 % strongly agree/agree). The interventions that received most support were strategies to better manage time and medication to manage withdrawal. CONCLUSIONS: The use of synthetic cannabinoids in UK prisons typically involves the use of paper-based preparations via e-cigarettes, and use is associated with greater levels of psychological distress. Motivations for use were mostly pragmatic (e.g. to alleviate boredom or cope with stress) and interventions should prioritise increasing the time individuals spend out of cells and in meaningful activity.

Long-term patterns of treatment use for opioid use disorder (OUD): Findings from the 18-20-year Australian Treatment Outcome Study.

BACKGROUND: Opioid-related deaths continue to increase to unprecedented rates in many regions of the world. While long-term stable treatment has been shown to reduce associated morbidity and mortality, discontinuation and numerous treatment episodes are common, limiting our understanding of the common course of treatment and associated characteristics. Therefore, using an 18-20-year follow-up of people with heroin dependence, we aimed to identify i) distinct trajectories of treatment use, ii) whether baseline characteristics predict treatment trajectory group membership, and ii) if group membership is associated with characteristics at 18-20-years post-baseline. METHODS: A total of 615 people with heroin dependence were recruited from maintenance therapy, detoxification, residential rehabilitation, or needle and syringe programs as part of the Australian Treatment Outcome Study (ATOS), a longitudinal cohort followed up on seven occasions over 18-20-years between 2001 and 2021. Of those who had complete data (n = 393), group-based trajectory modelling and a series of multinomial logistical regressions were conducted. RESULTS: Five trajectories of treatment use were identified: i) 'long-term low treatment' (17.2%), ii) 'rapid increase with gradual decrease' (13.9%), iii) 'late increase' (17.8%), (iv) 'long-term treatment' (27.7%), and (v) 'reduced treatment' (23.5%). Entering maintenance treatment at baseline predicted trajectory group membership, while trajectory group membership was associated with demographics and the use of heroin, methamphetamine, alcohol, and benzodiazepines at 18-20-years. CONCLUSIONS: In one of the longest cohort studies of its kind, we characterised distinct trajectories of treatment use in people with heroin dependence over 18-20-years. Clinicians should be aware of the potential impact of demographics and substance use on long-term treatment use. Despite the well-documented benefits of long-term treatment, some patients may be able to achieve abstinence from opioids without engaging in treatment over the life-course.

Instant Detection of Synthetic Cannabinoids on Physical Matrices, Implemented on a Low-Cost, Ultraportable Device.

Synthetic cannabinoids (SCs) make up a class of novel psychoactive substances (NPS), used predominantly in prisons and homeless communities in the U.K. SCs can have severe side effects, including psychosis, stroke, and seizures, with numerous reported deaths associated with their use. The chemical diversity of SCs presents the major challenge to their detection since approaches relying on specific molecular recognition become outdated almost immediately. Ideally one would have a generic approach to detecting SCs in portable settings. The problem of SC detection is more challenging still because the majority of SCs enter the prison estate adsorbed onto physical matrices such as paper, fabric, or herb materials. That is, regardless of the detection modality used, the necessary extraction step reduces the effectiveness and ability to rapidly screen materials on-site. Herein, we demonstrate a truly instant generic test for SCs, tested against real-world drug seizures. The test is based on two advances. First, we identify a spectrally silent region in the emission spectrum of most physical matrices. Second, the finding that background signals (including from autofluorescence) can be accurately predicted is based on tracking the fraction of absorbed light from the irradiation source. Finally, we demonstrate that the intrinsic fluorescence of a large range of physical substrates can be leveraged to track the presence of other drugs of interest, including the most recent iterations of benzodiazepines and opioids. We demonstrate the implementation of our presumptive test in a portable, pocket-sized device that will find immediate utility in prisons and law enforcement agencies around the world.

Acute effects of Δ9-tetrahydrocannabinol (THC) on resting state connectivity networks and impact of COMT genotype: A multi-site pharmacological fMRI study.

BACKGROUND: Cannabis produces various acute psychotropic effects, with marked individual differences. Cannabis use is a risk factor for developing psychotic disorders. The main component responsible for these effects is Δ9-tetrahydrocannabinol (THC). Here we investigated the neural basis of acute THC effects and its modulation by catechol-methyl-transferase (COMT) Val158Met genotype. METHODS: Resting state functional MRI data of healthy occasional cannabis users were combined and re-analyzed from three double-blind, placebo-controlled, within-subject pharmacological functional magnetic resonance imaging studies (total N=87). Functional connectivity after placebo and THC was compared in three functional networks (salience, executive and default mode network) and a network implicated in psychosis (the hippocampus-midbrain-striatum network). COMT genotype modulation of subjective effects and connectivity was examined. RESULTS: THC reduced connectivity in the salience network, specifically from the right insula to both the left insula and anterior cingulate cortex. We found a trend towards decreased connectivity in the hippocampus-midbrain-striatum network after THC. COMT genotype modulated subjective effects of THC, with strongest dysphoric reactions in Met/Met individuals. In addition, reduced connectivity after THC was demonstrated in the hippocampus-midbrain-striatum network of Met/Met individuals only. CONCLUSIONS: In this large multisite study we found that THC robustly decreases connectivity in the salience network, involved in processing awareness and salient information. Connectivity changes in the hippocampus-midbrain-striatum network may reflect the acute psychotic-like effects of THC. COMT genotype modulation of THC's impact on subjective effects and functional connectivity provides further evidence for involvement of prefrontal dopamine levels in the acute effects of cannabis.

Associations between regular cannabis use and brain resting-state functional connectivity in adolescents and adults.

BACKGROUND/AIM: Cannabis use is highly prevalent in adolescents; however, little is known about its effects on adolescent brain function. METHOD: Resting-state functional magnetic resonance imaging was used in matched groups of regular cannabis users (N = 70, 35 adolescents: 16-17 years old, 35 adults: 26-29 years old) and non-regular-using controls (N = 70, 35 adolescents/35 adults). Pre-registered analyses examined the connectivity of seven major cortical and sub-cortical brain networks (default mode network, executive control network (ECN), salience network, hippocampal network and three striatal networks) using seed-based analysis methods with cross-sectional comparisons between user groups and age groups. RESULTS: The regular cannabis use group (across both age groups), relative to controls, showed localised increases in connectivity only in the ECN analysis. All networks showed localised connectivity differences based on age group, with the adolescents generally showing weaker connectivity than adults, consistent with the developmental effects. Mean connectivity across entire network regions of interest (ROIs) was also significantly decreased in the ECN in adolescents. However, there were no significant interactions found between age group and user group in any of the seed-based or ROI analyses. There were also no associations found between cannabis use frequency and any of the derived connectivity measures. CONCLUSION: Regular cannabis use is associated with changes in connectivity of the ECN, which may reflect allostatic or compensatory changes in response to regular cannabis intoxication. However, these associations were not significantly different in adolescents compared to adults.