A robust brain network for sustained attention from adolescence to adulthood that predicts later substance use.

Substance use, including cigarettes and cannabis, is associated with poorer sustained attention in late adolescence and early adulthood. Previous studies were predominantly cross-sectional or under-powered and could not indicate if impairment in sustained attention was a consequence of substance-use or a marker of the inclination to engage in such behaviour. This study explored the relationship between sustained attention and substance use across a longitudinal span from ages 14 to 23 in over 1,000 participants. Behaviours and brain connectivity associated with diminished sustained attention at age 14 predicted subsequent increases in cannabis and cigarette smoking, establishing sustained attention as a robust biomarker for vulnerability to substance use. Individual differences in network strength relevant to sustained attention were preserved across developmental stages and sustained attention networks generalized to participants in an external dataset. In summary, brain networks of sustained attention are robust, consistent, and able to predict aspects of later substance use.

Brain Networks and Adolescent Alcohol Use.

Importance: Alcohol misuse in adolescence is a leading cause of disability and mortality in youth and is associated with higher risk for alcohol use disorder. Brain mechanisms underlying risk of alcohol misuse may inform prevention and intervention efforts. Objective: To identify neuromarkers of alcohol misuse using a data-driven approach, with specific consideration of neurodevelopmental sex differences. Design, Setting, and Participants: Longitudinal multisite functional magnetic resonance imaging (fMRI) data collected at ages 14 and 19 years were used to assess whole-brain patterns of functional organization associated with current and future alcohol use risk as measured by the Alcohol Use Disorder Identification Test (AUDIT). Primary data were collected by the IMAGEN consortium, a European multisite study of adolescent neurodevelopment. Model generalizability was further tested using data acquired in a single-site study of college alcohol consumption conducted in the US. The primary sample was a developmental cohort of 1359 adolescents with neuroimaging, phenotyping, and alcohol use data. Model generalizability was further assessed in a separate cohort of 114 individuals. Main Outcomes and Measures: Brain-behavior model accuracy, as defined by the correspondence between model-predicted and actual AUDIT scores in held-out testing data, Bonferroni corrected across the number of models run at each time point, 2-tailed α < .008, as determined via permutation testing. Results: Among 1359 individuals in the study, the mean (SD) age was 14.42 (0.40) years, and 729 individuals (54%) were female. The data-driven, whole-brain connectivity approach identified networks associated with vulnerability for future and current AUDIT-defined alcohol use risk (primary outcome, as specified above, future: ρ, 0.22; P < .001 and present: ρ, 0.27; P < .001). Results further indicated sex divergence in the accuracies of brain-behavior models, such that female-only models consistently outperformed male-only models. Specifically, female-only models identified networks conferring vulnerability for future and current severity using data acquired during both reward and inhibitory fMRI tasks. In contrast, male-only models were successful in accurately identifying networks using data acquired during the inhibitory control-but not reward-task, indicating domain specificity of alcohol use risk networks in male adolescents only. Conclusions and Relevance: These data suggest that interventions focusing on inhibitory control processes may be effective in combating alcohol use risk in male adolescents but that both inhibitory and reward-related processes are likely of relevance to alcohol use behaviors in female adolescents. They further identify novel networks of alcohol use risk in youth, which may be used to identify adolescents who are at risk and inform intervention efforts.

Federated Analysis in COINSTAC Reveals Functional Network Connectivity and Spectral Links to Smoking and Alcohol Consumption in Nearly 2,000 Adolescent Brains.

With the growth of decentralized/federated analysis approaches in neuroimaging, the opportunities to study brain disorders using data from multiple sites has grown multi-fold. One such initiative is the Neuromark, a fully automated spatially constrained independent component analysis (ICA) that is used to link brain network abnormalities among different datasets, studies, and disorders while leveraging subject-specific networks. In this study, we implement the neuromark pipeline in COINSTAC, an open-source neuroimaging framework for collaborative/decentralized analysis. Decentralized exploratory analysis of nearly 2000 resting-state functional magnetic resonance imaging datasets collected at different sites across two cohorts and co-located in different countries was performed to study the resting brain functional network connectivity changes in adolescents who smoke and consume alcohol. Results showed hypoconnectivity across the majority of networks including sensory, default mode, and subcortical domains, more for alcohol than smoking, and decreased low frequency power. These findings suggest that global reduced synchronization is associated with both tobacco and alcohol use. This proof-of-concept work demonstrates the utility and incentives associated with large-scale decentralized collaborations spanning multiple sites.

Associations of DNA Methylation With Behavioral Problems, Gray Matter Volumes, and Negative Life Events Across Adolescence: Evidence From the Longitudinal IMAGEN Study.

BACKGROUND: Negative life events (NLEs) increase the risk for externalizing behaviors (EBs) and internalizing behaviors (IBs) in adolescence and adult psychopathology. DNA methylation associated with behavioral problems may reflect this risk and long-lasting effects of NLEs. METHODS: To identify consistent associations between blood DNA methylation and EBs or IBs across adolescence, we conducted longitudinal epigenome-wide association studies (EWASs) using data from the IMAGEN cohort, collected at ages 14 and 19 years (n = 506). Significant findings were validated in a separate subsample (n = 823). Methylation risk scores were generated by 10-fold cross-validation and further tested for their associations with gray matter volumes and NLEs. RESULTS: No significant findings were obtained for the IB-EWAS. The EB-EWAS identified a genome-wide significant locus in a gene linked to attention-deficit/hyperactivity disorder (ADHD) (IQSEC1, cg01460382; p = 1.26 × 10-8). Other most significant CpG sites were near ADHD-related genes and enriched for genes regulating tumor necrosis factor and interferon-γ signaling, highlighting the relevance of EB-EWAS findings for ADHD. Analyses with the EB methylation risk scores suggested that it partly reflected comorbidity with IBs in late adolescence. Specific to EBs, EB methylation risk scores correlated with smaller gray matter volumes in medial orbitofrontal and anterior/middle cingulate cortices, brain regions known to associate with ADHD and conduct problems. Longitudinal mediation analyses indicated that EB-related DNA methylation were more likely the outcomes of problematic behaviors accentuated by NLEs, and less likely the epigenetic bases of such behaviors. CONCLUSIONS: Our findings suggest that novel epigenetic mechanisms through which NLEs exert short and longer-term effects on behavior may contribute to ADHD.

Genetic variants associated with longitudinal changes in brain structure across the lifespan.

Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.

A Developmental Perspective on Facets of Impulsivity and Brain Activity Correlates From Adolescence to Adulthood.

BACKGROUND: On a theoretical level, impulsivity represents a multidimensional construct associated with acting without foresight, inefficient inhibitory response control, and alterations in reward processing. On an empirical level, relationships and changes in associations between different measures of impulsivity from adolescence into young adulthood and their relation to neural activity during inhibitory control and reward anticipation have not been fully understood. METHODS: We used data from IMAGEN, a longitudinal multicenter, population-based cohort study in which 2034 healthy adolescents were investigated at age 14, and 1383 were reassessed as young adults at age 19. We measured the construct of trait impulsivity using self-report questionnaires and neurocognitive indices of decisional impulsivity. With functional magnetic resonance imaging, we assessed brain activity during inhibition error processing using the stop signal task and during reward anticipation in the monetary incentive delay task. Correlations were analyzed, and mixed-effect models were fitted to explore developmental and predictive effects. RESULTS: All self-report and neurocognitive measures of impulsivity proved to be correlated during adolescence and young adulthood. Further, pre-supplementary motor area and inferior frontal gyrus activity during inhibition error processing was associated with trait impulsivity in adolescence, whereas in young adulthood, a trend-level association with reward anticipation activity in the ventral striatum was found. For adult delay discounting, a trend-level predictive effect of adolescent neural activity during inhibition error processing emerged. CONCLUSIONS: Our findings help to inform theories of impulsivity about the development of its multidimensional nature and associated brain activity patterns and highlight the need for taking functional brain development into account when evaluating neuromarker candidates.

Orbitofrontal cortex volume links polygenic risk for smoking with tobacco use in healthy adolescents.

BACKGROUND: Tobacco smoking remains one of the leading causes of preventable illness and death and is heritable with complex underpinnings. Converging evidence suggests a contribution of the polygenic risk for smoking to the use of tobacco and other substances. Yet, the underlying brain mechanisms between the genetic risk and tobacco smoking remain poorly understood. METHODS: Genomic, neuroimaging, and self-report data were acquired from a large cohort of adolescents from the IMAGEN study (a European multicenter study). Polygenic risk scores (PGRS) for smoking were calculated based on a genome-wide association study meta-analysis conducted by the Tobacco and Genetics Consortium. We examined the interrelationships among the genetic risk for smoking initiation, brain structure, and the number of occasions of tobacco use. RESULTS: A higher smoking PGRS was significantly associated with both an increased number of occasions of tobacco use and smaller cortical volume of the right orbitofrontal cortex (OFC). Furthermore, reduced cortical volume within this cluster correlated with greater tobacco use. A subsequent path analysis suggested that the cortical volume within this cluster partially mediated the association between the genetic risk for smoking and the number of occasions of tobacco use. CONCLUSIONS: Our data provide the first evidence for the involvement of the OFC in the relationship between smoking PGRS and tobacco use. Future studies of the molecular mechanisms underlying tobacco smoking should consider the mediation effect of the related neural structure.

Reward Processing in Novelty Seekers: A Transdiagnostic Psychiatric Imaging Biomarker.

BACKGROUND: Dysfunctional reward processing is implicated in multiple mental disorders. Novelty seeking (NS) assesses preference for seeking novel experiences, which is linked to sensitivity to reward environmental cues. METHODS: A subset of 14-year-old adolescents (IMAGEN) with the top 20% ranked high-NS scores was used to identify high-NS-associated multimodal components by supervised fusion. These features were then used to longitudinally predict five different risk scales for the same and unseen subjects (an independent dataset of subjects at 19 years of age that was not used in predictive modeling training at 14 years of age) (within IMAGEN, n ≈1100) and even for the corresponding symptom scores of five types of patient cohorts (non-IMAGEN), including drinking (n = 313), smoking (n = 104), attention-deficit/hyperactivity disorder (n = 320), major depressive disorder (n = 81), and schizophrenia (n = 147), as well as to classify different patient groups with diagnostic labels. RESULTS: Multimodal biomarkers, including the prefrontal cortex, striatum, amygdala, and hippocampus, associated with high NS in 14-year-old adolescents were identified. The prediction models built on these features are able to longitudinally predict five different risk scales, including alcohol drinking, smoking, hyperactivity, depression, and psychosis for the same and unseen 19-year-old adolescents and even predict the corresponding symptom scores of five types of patient cohorts. Furthermore, the identified reward-related multimodal features can classify among attention-deficit/hyperactivity disorder, major depressive disorder, and schizophrenia with an accuracy of 87.2%. CONCLUSIONS: Adolescents with higher NS scores can be used to reveal brain alterations in the reward-related system, implicating potential higher risk for subsequent development of multiple disorders. The identified high-NS-associated multimodal reward-related signatures may serve as a transdiagnostic neuroimaging biomarker to predict disease risks or severity.

Neuroimaging evidence for structural correlates in adolescents resilient to polysubstance use: A five-year follow-up study.

Early initiation of polysubstance use (PSU) is a strong predictor of subsequent addiction, however scarce individuals present resilience capacity. This neuroimaging study aimed to investigate structural correlates associated with cessation or reduction of PSU and determine the extent to which brain structural features accounted for this resilient outcome. Participants from a European community-based cohort self-reported their alcohol, tobacco and cannabis use frequency at ages 14, 16 and 19 and had neuroimaging sessions at ages 14 and 19. We included three groups in the study: the resilient-to-PSU participants showed PSU at 16 and/or 14 but no more at 19 (n = 18), the enduring polysubstance users at 19 displayed PSU continuation from 14 or 16 (n = 193) and the controls were abstinent or low drinking participants (n = 460). We conducted between-group comparisons of grey matter volumes on whole brain using voxel-based morphometry and regional fractional anisotropy using tract-based spatial statistics. Random-forests machine-learning approach generated individual-level PSU-behavior predictions based on personality and neuroimaging features. Adolescents resilient to PSU showed significant larger grey matter volumes in the bilateral cingulate gyrus compared with enduring polysubstance users and controls at ages 19 and 14 (p<0.05 corrected) but no difference in fractional anisotropy. The larger cingulate volumes and personality trait "openness to experience" were the best precursors of resilience to PSU. Early in adolescence, a larger cingulate gyrus differentiated adolescents resilient to PSU, and this feature was critical in predicting this outcome. This study encourages further research into the neurobiological bases of resilience to addictive behaviors.

Linked patterns of biological and environmental covariation with brain structure in adolescence: a population-based longitudinal study.

Adolescence is a period of major brain reorganization shaped by biologically timed and by environmental factors. We sought to discover linked patterns of covariation between brain structural development and a wide array of these factors by leveraging data from the IMAGEN study, a longitudinal population-based cohort of adolescents. Brain structural measures and a comprehensive array of non-imaging features (relating to demographic, anthropometric, and psychosocial characteristics) were available on 1476 IMAGEN participants aged 14 years and from a subsample reassessed at age 19 years (n = 714). We applied sparse canonical correlation analyses (sCCA) to the cross-sectional and longitudinal data to extract modes with maximum covariation between neuroimaging and non-imaging measures. Separate sCCAs for cortical thickness, cortical surface area and subcortical volumes confirmed that each imaging phenotype was correlated with non-imaging features (sCCA r range: 0.30-0.65, all PFDR < 0.001). Total intracranial volume and global measures of cortical thickness and surface area had the highest canonical cross-loadings (|ρ| = 0.31-0.61). Age, physical growth and sex had the highest association with adolescent brain structure (|ρ| = 0.24-0.62); at baseline, further significant positive associations were noted for cognitive measures while negative associations were observed at both time points for prenatal parental smoking, life events, and negative affect and substance use in youth (|ρ| = 0.10-0.23). Sex, physical growth and age are the dominant influences on adolescent brain development. We highlight the persistent negative influences of prenatal parental smoking and youth substance use as they are modifiable and of relevance for public health initiatives.

Longitudinal associations between amygdala reactivity and cannabis use in a large sample of adolescents.

RATIONALE: The amygdala is a key brain structure to study in relation to cannabis use as reflected by its high-density of cannabinoid receptors and functional reactivity to processes relevant to drug use. Previously, we identified a correlation between cannabis use in early adolescence and amygdala hyper-reactivity to angry faces (Spechler et al. 2015). OBJECTIVES: Here, we leveraged the longitudinal aspect of the same dataset (the IMAGEN study) to determine (1) if amygdala hyper-reactivity predicts future cannabis use and (2) if amygdala reactivity is affected by prolonged cannabis exposure during adolescence. METHODS: First, linear regressions predicted the level of cannabis use by age 19 using amygdala reactivity to angry faces measured at age 14 prior to cannabis exposure in a sample of 1119 participants. Next, we evaluated the time course of amygdala functional development from age 14 to 19 for angry face processing and how it might be associated with protracted cannabis use throughout this developmental window. We compared the sample from Spechler et al. 2015, the majority of whom escalated their use over the 5-year interval, to a matched sample of non-users. RESULTS: Right amygdala reactivity to angry faces significantly predicted cannabis use 5 years later in a dose-response fashion. Cannabis-naïve adolescents demonstrated the lowest levels of amygdala reactivity. No such predictive relationship was identified for alcohol or cigarette use. Next, follow-up analyses indicated a significant group-by-time interaction for the right amygdala. CONCLUSIONS: (1) Right amygdala hyper-reactivity is predictive of future cannabis use, and (2) protracted cannabis exposure during adolescence may alter the rate of neurotypical functional development.

Decreased brain connectivity in smoking contrasts with increased connectivity in drinking.

In a group of 831 participants from the general population in the Human Connectome Project, smokers exhibited low overall functional connectivity, and more specifically of the lateral orbitofrontal cortex which is associated with non-reward mechanisms, the adjacent inferior frontal gyrus, and the precuneus. Participants who drank a high amount had overall increases in resting state functional connectivity, and specific increases in reward-related systems including the medial orbitofrontal cortex and the cingulate cortex. Increased impulsivity was found in smokers, associated with decreased functional connectivity of the non-reward-related lateral orbitofrontal cortex; and increased impulsivity was found in high amount drinkers, associated with increased functional connectivity of the reward-related medial orbitofrontal cortex. The main findings were cross-validated in an independent longitudinal dataset with 1176 participants, IMAGEN. Further, the functional connectivities in 14-year-old non-smokers (and also in female low-drinkers) were related to who would smoke or drink at age 19. An implication is that these differences in brain functional connectivities play a role in smoking and drinking, together with other factors.

Allele-Specific Methylation of SPDEF: A Novel Moderator of Psychosocial Stress and Substance Abuse.

OBJECTIVE: Psychosocial stress is a key risk factor for substance abuse among adolescents. Recently, epigenetic processes such as DNA methylation have emerged as potential mechanisms that could mediate this relationship. The authors conducted a genome-wide methylation analysis to investigate whether differentially methylated regions are associated with psychosocial stress in an adolescent population. METHODS: A methylome-wide analysis of differentially methylated regions was used to examine a sample of 1,287 14-year-old adolescents (50.7% of them female) from the European IMAGEN study. The Illumina 450k array was used to assess DNA methylation, pyrosequencing was used for technical replication, and linear regression analyses were used to identify associations with psychosocial stress and substance use (alcohol and tobacco). Findings were replicated by pyrosequencing a test sample of 413 participants from the IMAGEN study. RESULTS: Hypermethylation in the sterile alpha motif/pointed domain containing the ETS transcription factor (SPDEF) gene locus was associated with a greater number of stressful life events in an allele-dependent way. Among individuals with the minor G-allele, SPDEF methylation moderated the association between psychosocial stress and substance abuse. SPDEF methylation interacted with lifetime stress in gray matter volume in the right cuneus, which in turn was associated with the frequency of alcohol and tobacco use. SPDEF was involved in the regulation of trans-genes linked to substance use. CONCLUSIONS: Taken together, the study findings describe a novel epigenetic mechanism that helps explain how psychosocial stress exposure influences adolescent substance abuse.

18F-FDG-PET patterns of surgical success and failure in mesial temporal lobe epilepsy.

OBJECTIVE: To search for [18F]-fluorodeoxyglucose (FDG)-PET patterns predictive of long-term prognosis in surgery for drug-resistant mesial temporal lobe epilepsy (MTLE) due to hippocampal sclerosis (HS). METHODS: We analyzed metabolic data with [18F]-FDG-PET in 97 patients with MTLE (53 female participants; age range 15-56 years) with unilateral HS (50 left) and compared the metabolic patterns, electroclinical features, and structural atrophy on MRI in patients with the best outcome after anteromesial temporal resection (Engel class IA, completely seizure-free) to those with a non-IA outcome, including suboptimal outcome and failure. Imaging processing was performed with statistical parametric mapping (SPM5). RESULTS: With a mean follow-up of >6 years (range 2-14 years), 85% of patients achieved a class I outcome, including 45% in class IA. Class IA outcome was associated with a focal anteromesial temporal hypometabolism, whereas non-IA outcome correlated with extratemporal metabolic changes that differed according to the lateralization: ipsilateral mesial frontal and perisylvian hypometabolism in right HS and contralateral fronto-insular hypometabolism and posterior white matter hypermetabolism in left HS. Suboptimal outcome presented a metabolic pattern similar to the best outcome but with a larger involvement of extratemporal areas, including the contralateral side in left HS. Failure was characterized by a mild temporal involvement sparing the hippocampus and relatively high extratemporal hypometabolism on both sides. These findings were concordant with electroclinical features reflecting the organization of the epileptogenic zone but were independent of the structural abnormalities detected on MRI. CONCLUSIONS: [18F]-FDG-PET patterns help refine the prognostic factors in MTLE and should be implemented in predictive models for epilepsy surgery.

Ventral Striatum Connectivity During Reward Anticipation in Adolescent Smokers.

Substance misusers, including adolescent smokers, often have reduced reward system activity during processing of non-drug rewards. Using a psychophysiological interaction approach, we examined functional connectivity with the ventral striatum during reward anticipation in a large (N = 206) sample of adolescent smokers. Increased smoking frequency was associated with (1) increased connectivity with regions involved in saliency and valuation, including the orbitofrontal cortex and (2) reduced connectivity between the ventral striatum and regions associated with inhibition and risk aversion, including the right inferior frontal gyrus. These results demonstrate that functional connectivity during reward processing is relevant to adolescent addiction.

Cannabis use in early adolescence: Evidence of amygdala hypersensitivity to signals of threat.

Cannabis use in adolescence may be characterized by differences in the neural basis of affective processing. In this study, we used an fMRI affective face processing task to compare a large group (n=70) of 14-year olds with a history of cannabis use to a group (n=70) of never-using controls matched on numerous characteristics including IQ, SES, alcohol and cigarette use. The task contained short movies displaying angry and neutral faces. Results indicated that cannabis users had greater reactivity in the bilateral amygdalae to angry faces than neutral faces, an effect that was not observed in their abstinent peers. In contrast, activity levels in the cannabis users in cortical areas including the right temporal-parietal junction and bilateral dorsolateral prefrontal cortex did not discriminate between the two face conditions, but did differ in controls. Results did not change after excluding subjects with any psychiatric symptomology. Given the high density of cannabinoid receptors in the amygdala, our findings suggest cannabis use in early adolescence is associated with hypersensitivity to signals of threat. Hypersensitivity to negative affect in adolescence may place the subject at-risk for mood disorders in adulthood.

Early Cannabis Use, Polygenic Risk Score for Schizophrenia and Brain Maturation in Adolescence.

IMPORTANCE: Cannabis use during adolescence is known to increase the risk for schizophrenia in men. Sex differences in the dynamics of brain maturation during adolescence may be of particular importance with regard to vulnerability of the male brain to cannabis exposure. OBJECTIVE: To evaluate whether the association between cannabis use and cortical maturation in adolescents is moderated by a polygenic risk score for schizophrenia. DESIGN, SETTING, AND PARTICIPANTS: Observation of 3 population-based samples included initial analysis in 1024 adolescents of both sexes from the Canadian Saguenay Youth Study (SYS) and follow-up in 426 adolescents of both sexes from the IMAGEN Study from 8 European cities and 504 male youth from the Avon Longitudinal Study of Parents and Children (ALSPAC) based in England. A total of 1577 participants (aged 12-21 years; 899 [57.0%] male) had (1) information about cannabis use; (2) imaging studies of the brain; and (3) a polygenic risk score for schizophrenia across 108 genetic loci identified by the Psychiatric Genomics Consortium. Data analysis was performed from March 1 through December 31, 2014. MAIN OUTCOMES AND MEASURES: Cortical thickness derived from T1-weighted magnetic resonance images. Linear regression tests were used to assess the relationships between cannabis use, cortical thickness, and risk score. RESULTS: Across the 3 samples of 1574 participants, a negative association was observed between cannabis use in early adolescence and cortical thickness in male participants with a high polygenic risk score. This observation was not the case for low-risk male participants or for the low- or high-risk female participants. Thus, in SYS male participants, cannabis use interacted with risk score vis-à-vis cortical thickness (P = .009); higher scores were associated with lower thickness only in males who used cannabis. Similarly, in the IMAGEN male participants, cannabis use interacted with increased risk score vis-à-vis a change in decreasing cortical thickness from 14.5 to 18.5 years of age (t137 = -2.36; P = .02). Finally, in the ALSPAC high-risk group of male participants, those who used cannabis most frequently (≥61 occasions) had lower cortical thickness than those who never used cannabis (difference in cortical thickness, 0.07 [95% CI, 0.01-0.12]; P = .02) and those with light use (<5 occasions) (difference in cortical thickness, 0.11 [95% CI, 0.03-0.18]; P = .004). CONCLUSIONS AND RELEVANCE: Cannabis use in early adolescence moderates the association between the genetic risk for schizophrenia and cortical maturation among male individuals. This finding implicates processes underlying cortical maturation in mediating the link between cannabis use and liability to schizophrenia.

Neuropsychosocial profiles of current and future adolescent alcohol misusers.

A comprehensive account of the causes of alcohol misuse must accommodate individual differences in biology, psychology and environment, and must disentangle cause and effect. Animal models can demonstrate the effects of neurotoxic substances; however, they provide limited insight into the psycho-social and higher cognitive factors involved in the initiation of substance use and progression to misuse. One can search for pre-existing risk factors by testing for endophenotypic biomarkers in non-using relatives; however, these relatives may have personality or neural resilience factors that protect them from developing dependence. A longitudinal study has potential to identify predictors of adolescent substance misuse, particularly if it can incorporate a wide range of potential causal factors, both proximal and distal, and their influence on numerous social, psychological and biological mechanisms. Here we apply machine learning to a wide range of data from a large sample of adolescents (n = 692) to generate models of current and future adolescent alcohol misuse that incorporate brain structure and function, individual personality and cognitive differences, environmental factors (including gestational cigarette and alcohol exposure), life experiences, and candidate genes. These models were accurate and generalized to novel data, and point to life experiences, neurobiological differences and personality as important antecedents of binge drinking. By identifying the vulnerability factors underlying individual differences in alcohol misuse, these models shed light on the aetiology of alcohol misuse and suggest targets for prevention.

Striatal and extrastriatal dopamine transporter in cannabis and tobacco addiction: a high-resolution PET study.

The dopamine (DA) system is known to be involved in the reward and dependence mechanisms of addiction. However, modifications in dopaminergic neurotransmission associated with long-term tobacco and cannabis use have been poorly documented in vivo. In order to assess striatal and extrastriatal dopamine transporter (DAT) availability in tobacco and cannabis addiction, three groups of male age-matched subjects were compared: 11 healthy non-smoker subjects, 14 tobacco-dependent smokers (17.6 ± 5.3 cigarettes/day for 12.1 ± 8.5 years) and 13 cannabis and tobacco smokers (CTS) (4.8 ± 5.3 cannabis joints/day for 8.7 ± 3.9 years). DAT availability was examined in positron emission tomography (HRRT) with a high resolution research tomograph after injection of [11C]PE2I, a selective DAT radioligand. Region of interest and voxel-by-voxel approaches using a simplified reference tissue model were performed for the between-group comparison of DAT availability. Measurements in the dorsal striatum from both analyses were concordant and showed a mean 20% lower DAT availability in drug users compared with controls. Whole-brain analysis also revealed lower DAT availability in the ventral striatum, the midbrain, the middle cingulate and the thalamus (ranging from -15 to -30%). The DAT availability was slightly lower in all regions in CTS than in subjects who smoke tobacco only, but the difference does not reach a significant level. These results support the existence of a decrease in DAT availability associated with tobacco and cannabis addictions involving all dopaminergic brain circuits. These findings are consistent with the idea of a global decrease in cerebral DA activity in dependent subjects.

Exposure to smoking cues during an emotion recognition task can modulate limbic fMRI activation in cigarette smokers.

Smoking cues (SCs) refer to smoking-associated environmental stimuli that may trigger craving and withdrawal symptoms, and predispose to relapse in smokers. Although previous brain imaging studies have explored neural responses to SCs, no study has characterized the effects of SCs on cerebral activity in smokers engaged in an attention-demanding cognitive task that is unrelated to smoking. Thirteen tobacco smokers and a demographically matched group of 13 healthy non-smokers participated in a fast event-related functional magnetic resonance imaging (fMRI) study that involved a visual task integrating SCs and neutral cues (NCs) during emotion recognition trials requiring a high level of attention. No significant SC-induced alterations were detected in smokers' behavioural performance. fMRI results show that non-smokers exhibited no difference between SC and NC trials; in contrast, smokers showed SC-induced widespread deactivations in a limbic, paralimbic and striatal network classically involved in addiction, and activation in the right dorsolateral prefrontal cortex. In addition, a correlation between deactivation of the right insula and the severity of smoking dependence (Fagerström test) was detected in smokers. These results suggest that the neural reactivity of smokers to SCs can be modified in the context of a cognitive challenge. This could reflect smokers' ability to inhibit cue-induced craving and may help in smoking cessation.