Dataset Information

?⁸ -Tetrahydrocannabivarin has potent anti-nicotine effects in several rodent models of nicotine dependence.

ABSTRACT: Background and purpose:Both types of cannabinoid receptors-CB₁ and CB₂ -regulate brain functions relating to addictive drug-induced reward and relapse. CB₁ receptor antagonists and CB₂ receptor agonists have anti-addiction efficacy, in animal models, against a broad range of addictive drugs. ?⁹ -Tetrahydrocannabivarin (?⁹ -THCV)-a cannabis constituent-acts as a CB₁ antagonist and a CB₂ agonist. ?⁸ -Tetrahydrocannabivarin (?⁸ -THCV) is a ?⁹ -THCV analogue with similar combined CB₁ antagonist/CB₂ agonist properties.

Experimental approach:We tested ?⁸ -THCV in seven different rodent models relevant to nicotine dependence-nicotine self-administration, cue-triggered nicotine-seeking behaviour following forced abstinence, nicotine-triggered reinstatement of nicotine-seeking behaviour, acquisition of nicotine-induced conditioned place preference, anxiety-like behaviour induced by nicotine withdrawal, somatic withdrawal signs induced by nicotine withdrawal, and hyperalgesia induced by nicotine withdrawal.

Key results:?⁸ -THCV significantly attenuated intravenous nicotine self-administration and both cue-induced and nicotine-induced relapse to nicotine-seeking behaviour in rats. ?⁸ -THCV also significantly attenuated nicotine-induced conditioned place preference and nicotine withdrawal in mice.

Conclusions and implications:We conclude that ?⁸ -THCV may have therapeutic potential for the treatment of nicotine dependence. We also suggest that tetrahydrocannabivarins should be tested for possible anti-addiction efficacy in a broader range of preclinical animal models, against other addictive drugs, and eventually in humans.

SUBMITTER: Xi ZX

PROVIDER: S-EPMC6965695 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Δ8 -Tetrahydrocannabivarin has potent anti-nicotine effects in several rodent models of nicotine dependence.

Xi Zheng-Xiong ZX Muldoon Pretal P Wang Xiao-Fei XF Bi Guo-Hua GH Damaj M Imad MI Lichtman Aron H AH Pertwee Roger G RG Gardner Eliot L EL

British journal of pharmacology 20191028 24

<h4>Background and purpose</h4>Both types of cannabinoid receptors-CB1 and CB2 -regulate brain functions relating to addictive drug-induced reward and relapse. CB1 receptor antagonists and CB2 receptor agonists have anti-addiction efficacy, in animal models, against a broad range of addictive drugs. Δ9 -Tetrahydrocannabivarin (Δ9 -THCV)-a cannabis constituent-acts as a CB1 antagonist and a CB2 agonist. Δ ...[more]

PMID: 31454413

Similar Datasets

Project description:INTRODUCTION:This study investigated the effects of nicotine/tobacco on neural activation during performance of a monetary incentive delay task. AIMS AND METHODS:Prior to each scan, nonsmokers received nicotine or placebo nasal spray, and smokers were smoking satiated or 24-hour withdrawn. During the scan, participants made timed responses to reward-related cues and received feedback. Parameter estimates from cue- and feedback-related activation in medial prefrontal regions and the nucleus accumbens were extracted and underwent within- and between-group analyses. Smokers' nicotine dependence severity was included as a continuous predictor variable for neural activation. RESULTS:Among smokers (n = 21), withdrawal decreased cue-related activation in the supplementary motor area and ventromedial prefrontal cortex, and the difference in activation (satiety > withdrawal) in these regions negatively correlated with nicotine dependence severity (Fagerström Test for Nicotine Dependence). Among nonsmokers (n = 22), nicotine increased the difference in nucleus accumbens activation between rewarded and nonrewarded feedback phases. Tobacco withdrawal and acute nicotine also had widespread effects on activation throughout the brain during the feedback phase. CONCLUSIONS:Acute nicotine in nonsmokers may have increased the salience of feedback information, but produced few effects on reward-related activation overall, perhaps reflecting nicotine's modest, indirect effects on reward processing. Conversely, tobacco withdrawal decreased activation compared with satiety, and this difference between conditions correlated with nicotine dependence severity. This suggests that as smokers become more dependent on nicotine, tobacco withdrawal has a more pronounced effect on reward processing. IMPLICATIONS:Relative to the acute effects of nicotine in nonsmokers, withdrawal from daily tobacco use had more significant effects on reward-related brain activation. This study suggests that the effects of tobacco withdrawal on reward-related brain function interact with subjects' level of nicotine dependence severity. These are potentially important sources of variability that could contribute to smoking cessation outcomes.

Project description:IntroductionThe nicotine metabolite ratio and nicotine equivalents are measures of metabolism rate and intake. Genome-wide prediction of these nicotine biomarkers in multiethnic samples will enable tobacco-related biomarker, behavioral, and exposure research in studies without measured biomarkers.Aims and methodsWe screened genetic variants genome-wide using marginal scans and applied statistical learning algorithms on top-ranked genetic variants, age, ethnicity and sex, and, in additional modeling, cigarettes per day (CPD), (in additional modeling) to build prediction models for the urinary nicotine metabolite ratio (uNMR) and creatinine-standardized total nicotine equivalents (TNE) in 2239 current cigarette smokers in five ethnic groups. We predicted these nicotine biomarkers using model ensembles and evaluated external validity using dependence measures in 1864 treatment-seeking smokers in two ethnic groups.ResultsThe genomic regions with the most selected and included variants for measured biomarkers were chr19q13.2 (uNMR, without and with CPD) and chr15q25.1 and chr10q25.3 (TNE, without and with CPD). We observed ensemble correlations between measured and predicted biomarker values for the uNMR and TNE without (with CPD) of 0.67 (0.68) and 0.65 (0.72) in the training sample. We observed inconsistency in penalized regression models of TNE (with CPD) with fewer variants at chr15q25.1 selected and included. In treatment-seeking smokers, predicted uNMR (without CPD) was significantly associated with CPD and predicted TNE (without CPD) with CPD, time-to-first-cigarette, and Fagerström total score.ConclusionsNicotine metabolites, genome-wide data, and statistical learning approaches developed novel robust predictive models for urinary nicotine biomarkers in multiple ethnic groups. Predicted biomarker associations helped define genetically influenced components of nicotine dependence.ImplicationsWe demonstrate development of robust models and multiethnic prediction of the uNMR and TNE using statistical and machine learning approaches. Variants included in trained models for nicotine biomarkers include top-ranked variants in multiethnic genome-wide studies of smoking behavior, nicotine metabolites, and related disease. Association of the two predicted nicotine biomarkers with Fagerström Test for Nicotine Dependence items supports models of nicotine biomarkers as predictors of physical dependence and nicotine exposure. Predicted nicotine biomarkers may facilitate tobacco-related disease and treatment research in samples with genomic data and limited nicotine metabolite or tobacco exposure data.

Dataset Information

?⁸ -Tetrahydrocannabivarin has potent anti-nicotine effects in several rodent models of nicotine dependence.

Publications

Δ<sup>8</sup> -Tetrahydrocannabivarin has potent anti-nicotine effects in several rodent models of nicotine dependence.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

?8 -Tetrahydrocannabivarin has potent anti-nicotine effects in several rodent models of nicotine dependence.

Publications

Δ<sup>8</sup> -Tetrahydrocannabivarin has potent anti-nicotine effects in several rodent models of nicotine dependence.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

?⁸ -Tetrahydrocannabivarin has potent anti-nicotine effects in several rodent models of nicotine dependence.