Addiction Biology最新文献

Individuals with Internet addiction disorder (IAD) exhibit deficits in cognitive control, particularly in interference control; however, the behavioural and neural mechanisms underlying these impairments remain unclear. In this study, classic and modified Stroop tasks were administered to individuals with IAD and healthy control (HC) participants, whereas electroencephalography (EEG) was recorded. We hypothesized that individuals with IAD would demonstrate impaired interference control, as evidenced by longer reaction times (RTs) on incongruent trials and that these behavioural deficits would be accompanied by reduced ERP activity in both early and late medial frontal negativity (MFN) components, as well as diminished conflict slow potential (SP). Additionally, our event-related spectral perturbation (ERSP) analysis was designed to examine oscillatory dynamics, including a reduced Stroop effect in theta power along with compensatory increases in beta2 and gamma band activity. The results revealed that individuals with IAD exhibited prolonged RTs, with this difference becoming more pronounced under increased cognitive demands. Furthermore, ERP responses and ERSP patterns across frequency bands were distinct in the IAD group, pointing to deficits in conflict detection and resolution, as well as compensatory neural mechanisms. These findings suggest that cognitive slowing in individuals with IAD is exacerbated under conditions requiring greater interference control, contributing to the executive dysfunction.

In clinical settings targeting alcohol use disorder (AUD), it is often unclear whether a treatment option may best suit a patient's clinical needs. Clinicians providing AUD treatment are often required to predict patients' responses to guide treatment decisions. Recently, machine learning approaches have been used as tools in precision medicine to help guide these clinical decisions. However, the extent of their clinical utility in populations undergoing treatment is largely unknown. Using data from four Phase 2 randomized clinical trials affiliated with the NIAAA Clinical Investigations Group and a Phase 3 trial sponsored by the NIAAA, we developed a machine learning model to predict treatment response phenotypes derived from clustering drinking rates at the end of treatment. Harmonized data included demographics and baseline data from biological and clinical assessments. Follow-up analyses were performed to characterize treatment response phenotypes. Three clusters corresponding to mild (M_SDU = 1.3), moderate (M_SDU = 6.70) and severe (M_SDU = 15.3) alcohol consumption were identified from end-of-treatment drinking data. Performance of the tree-based classifier using out-of-sample test data was 71% with baseline drinking included and 61% without. Exploratory analyses revealed participants clustered as mild drinkers showed reductions in drinking across treatment (M_Difference = −0.731, SE = 0.114, p < 0.001) whereas participants clustered as severe had escalation in use (M_Difference = 6.82, SE = 0.52, p < 0.001). Although males drank more than females at baseline (M_Difference = 1.46, SE = 0.287, p < 0.001), no significant differences in consumption emerged at the end of treatment. Findings from this work indicate that alcohol use derived from patterns of consumption at the end of treatment maps onto unique treatment response trajectories for mild and severe forms of AUD. Furthermore, the identified clusters revealed sex-specific differences in alcohol consumption patterns across different phases of treatment. Overall, this highlights the utility of computational methods for deriving clinically meaningful AUD-related phenotypes across multiple studies, each with different treatments and participant characteristics.

Craving is an intense, strong urge to engage in addictive behaviours. Craving is supposed to be modulated by the connectivity between the amygdala and the ventral striatum (VS), a pivotal pathway for reward-seeking behaviours. However, whether and how this connectivity underlies craving for gambling remains unclear, limiting our understanding of the pathophysiology of gambling disorder (GD). To address this issue, we analysed resting-state functional connectivity (rs-FC) between the amygdala and VS in 51 GD patients and 45 healthy participants. Craving for gambling was assessed using the Gambling Craving Scale (GACS). Among three GACS subscales, Desire exhibited a significant correlation with rs-FC in the right amygdala–VS, while Anticipation and Relief showed no significant associations. Causal mediation analysis revealed that depressive symptoms significantly mediated the relationship between rs-FC in the right amygdala–VS and Desire. These findings suggest that the amygdala–VS connectivity elicits the intense desire for gambling through negative emotions.

RETRACTION: J. Xu, H. Zhao, and Y. Wang, “Comment on: ‘Sex differences in neural networks recruited by frontloaded binge alcohol drinking’,” Addiction Biology 29, no. 10 (2024): e70002, https://doi.org/10.1111/adb.70002.

The above article, published online on 15 October 2024 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the authors; the journal Editor-in-Chief, Rainer Spanagel; the Society for the Study of Addiction; and John Wiley & Sons Ltd.

The retraction of this article, a Letter to the Editor, has been agreed by all parties due to concerns raised by a third party that it contains major scientific flaws. These flaws, which were confirmed during post-publication review, were not identified during the original evaluation process and make the letter irrelevant to the published article on which it comments.

Oxytocin is a promising therapeutic target in the treatment of alcohol use disorder (AUD). However, many studies report contradicting evidence regarding its effect on drug craving, relapse risk and withdrawal symptoms. Epigenetic regulation of the oxytocin and oxytocin receptor (OXTR) gene is altered in several mental disorders and influences social behaviour, often depending on the underlying sex. Evidence suggests that altered promoter methylation could result in oxytocin and OXTR expression differences, thereby possibly influencing drug craving and relapse risk. It is unclear whether promoter methylation changes throughout alcohol withdrawal and is linked to craving and withdrawal symptoms. In this exploratory study, we investigated the effect of 2-week alcohol withdrawal therapy in 99 males on methylation levels (oxytocin and OXTR) compared with 31 healthy controls. We found significantly higher mean methylation values of the OXTR gene in controls than patients across withdrawal (p < 0.001). Regarding oxytocin, we found no differences in mean methylation in healthy controls compared with patients. Across withdrawal, mean methylation decreased in both genes. Fitting a mixed linear model, craving and withdrawal symptoms were associated with changes in methylation levels of the oxytocin gene (p < 0.001), which was also true for the OXTR gene when considering age and smoking as additional covariates. Our study is the first to report an association between AUD, oxytocin and OXTR gene methylation. Methylation of the OXTR gene is reduced in AUD compared with healthy controls, with OT gene methylation linked to craving and withdrawal severity. Our results suggest that investigations of oxytocin as a therapeutic agent need to consider epigenetic regulation of its receptor and gene as a mechanism that could influence oxytocin's effect on craving and withdrawal symptoms.

Although substance use is associated with a shortened lifespan, impeded health and accelerated biological ageing, the factors contributing to the associations between substance use and ageing are poorly understood. We used summary statistics from genome-wide association studies (GWAS) to investigate whether substance involvement (N from 28K to 2M)—including alcohol, tobacco, cannabis and opioid use and use disorders—is genetically correlated with various ageing metrics (N from 162K to 2.7M) and whether these correlations reflect shared genetic etiologies or putative causal relationships. Using Linkage Disequilibrium Score Regression (LDSC), we found widespread evidence of genetic correlations between substance use/use disorders and indices of physical, cognitive and biological ageing. We then employed a series of Mendelian randomization–based approaches, finding significant causal effects of genetic predispositions to both tobacco use disorder and quantity of tobacco smoked on various markers of ageing. Causal effects of problematic alcohol use and cannabis use disorder were also found, though findings were mixed. Evidence of reverse causality (i.e., ageing causing substance use), meanwhile, was scant. Collectively, these results demonstrate strong triangulation across approaches and highlight the importance of integrating genetic insights into public health strategies for reducing the burden of SUDs across the lifespan.

Alcohol misuse impairs sleep quality and circadian rhythms. Yet, sleep is essential, as a lack of sleep is a predictive factor for addiction and relapse risk in patients with alcohol use disorder (AUD). On the contrary, effective insomnia treatment after withdrawal increases abstinence. Meanwhile, physical activity (PA) has been shown to improve sleep quality and circadian rhythms in nonclinical population. Hence, it would be interesting to assess the impact of PA on sleep in alcohol users with and without dependence. Systematic search was conducted using Prisma guidelines for the screening and ROB-1 for bias analysis of randomized controlled trial (RCT). Out of 4995 studies screened, none assess as main purpose the impact of PA on sleep in alcohol users. Still, 81.8% of the selected studies, in their secondary outcomes, highlight PA's positive association with sleep in alcohol users with or without dependence. Main positive sleep outcomes were insomnia and sleep fragmentation reduction as well as sleep quality and duration improvement. There is a lack of publication regarding the impact of PA on sleep in nonclinical alcohol users and AUD patients. Still, PA appears to enhance sleep in both populations. Further well-designed RCTs are needed to produce robust data. In the first instance, feasibility study should be performed as adhesion can be an issue in the population. Finally, different PA programs (frequency, intensity, time, type and duration) should be compared to determine the optimal dose in different AUD status (intoxication, withdrawal and abstinence).

Evidence from human self-report and rodent models indicate that cocaine can induce a negative affective state marked by panic and anxiety, which may reduce future cocaine use or promote co-use with opiates. Dynorphin-mediated signalling within the striatum is associated with negative affect following cocaine withdrawal and stress-induced cocaine seeking. Here, we used a trace conditioning procedure to first establish the optimum parameters to capture this transient cocaine negative affective state in wild-type mice, and then we investigated striatal opioid peptides as a substrate mediating cocaine conditioned place avoidance (CPA). Previous reports indicate that trace conditioning, where drug administration occurs after removal from the conditioning chamber, results in CPA to ethanol, nicotine and amphetamine. We tested different cocaine doses, conditioning session lengths and apparatus types to determine which combination yields the best cocaine CPA. Cocaine CPA was moderately larger at the highest cocaine dose (25 mg/kg), but this did not generalize across apparatus types and the effect was transient; thus, data were collapsed across all parameters. Cocaine conditioning scores were variable but also became more polarized across conditioning, with approximately equal proportions developing preference and avoidance. We then correlated cocaine CPA with striatal gene expression levels of the opioid peptides enkephalin (Penk) and dynorphin (Pdyn) using qPCR. Cocaine CPA was correlated with low Pdyn levels and a low Pdyn:Penk ratio in the ventral, but not dorsal, striatum. Consistent with this, mice with higher striatal Pdyn relative to Penk were more resistant to developing cocaine CPA compared with littermate controls. This approach revealed a subset of subjects sensitive to the aversive state immediately following cocaine administration. Our findings suggest that striatal dynorphin has opposing roles in mediating the aversion associated with acute cocaine intoxication versus cocaine withdrawal.

4-hydroxyindole-3-acetic acid (4-HIAA) is a metabolite of psilocin. Here, we explored the ability of 4-HIAA to cross the blood–brain barrier and its potential effects on methamphetamine (METH)-induced conditioned place preference (CPP) in mice. Treatment with 1-mg/kg 4-HIAA inhibited CPP formation during the acquisition phase, promoted METH extinction and inhibited METH relapse. Furthermore, the regulatory effect of 4-HIAA on METH was underscored by altered 5-HT expression in the nucleus accumbens. Collectively, our findings provide novel insights into the molecular mechanisms of the 4-HIAA-induced blockade of the acquisition, extinction and reinstatement of METH-induced CPP.