Brain responses and approach bias to social alcohol cues and their association with drinking in a social setting in young adult males

Alcohol is mainly consumed in social settings, in which people often adapt their drinking behaviour to that of others, also called imitation of drinking. Yet, it remains unclear what drives this drinking in a social setting. In this study, we expected to see stronger brain and behavioural responses to social compared to non-social alcohol cues, and these responses to be associated with drinking in a social setting. The sample consisted of 153 beer-drinking males, aged 18–25 years. Brain responses to social alcohol cues were measured during an alcohol cue-exposure task performed in an fMRI scanner. Behavioural responses to social alcohol cues were measured using a stimulus-response compatibility task, providing an index of approach bias towards these cues. Drinking in a social setting was measured in a laboratory mimicking a bar environment. Specific brain responses to social alcohol cues were observed in the bilateral superior temporal sulcus and the left inferior parietal lobe. There was no approach bias towards social alcohol cues specifically; however, we did find an approach bias towards alcohol (versus soda) cues in general. Brain responses and approach bias towards social alcohol cues were unrelated and not associated with actual drinking. Thus, we found no support for a relation between drinking in a social setting on the one hand, and brain cue-reactivity or behavioural approach biases to social alcohol cues on the other hand. This suggests that, in contrast to our hypothesis, drinking in a social setting may not be driven by brain or behavioural responses to social alcohol cues

Brain volumes in alcohol use disorder : Do females and males differ? A whole-brain magnetic resonance imaging mega-analysis

Emerging evidence suggests distinct neurobiological correlates of alcohol use disorder (AUD) between sexes, which however remain largely unexplored. This work from ENIGMA Addiction Working Group aimed to characterize the sex differences in gray matter (GM) and white matter (WM) correlates of AUD using a whole-brain, voxelbased, multi-tissue mega-analytic approach, thereby extending our recent surfacebased region of interest findings on a nearly matching sample using a complementary methodological approach. T1-weighted magnetic resonance imaging (MRI) data from 653 people with AUD and 326 controls was analyzed using voxel-based morphometry. The effects of group, sex, group-by-sex, and substance use severity in AUD on brain volumes were assessed using General Linear Models. Individuals with AUD relative to controls had lower GM volume in striatal, thalamic, cerebellar, and widespread cortical clusters. Group-by-sex effects were found in cerebellar GM and WM volumes, which were more affected by AUD in females than males. Smaller groupby- sex effects were also found in frontotemporal WM tracts, which were more affected in AUD females, and in temporo-occipital and midcingulate GM volumes, which were more affected in AUD males. AUD females but not males showed a negative association between monthly drinks and precentral GM volume. Our results suggest that AUD is associated with both shared and distinct widespread effects on GM and WM volumes in females and males. This evidence advances our previous region of interest knowledge, supporting the usefulness of adopting an exploratory perspective and the need to include sex as a relevant moderator variable in AUD

Recalibrating single-study effect sizes using hierarchical Bayesian models

INTRODUCTION: There are growing concerns about commonly inflated effect sizes in small neuroimaging studies, yet no study has addressed recalibrating effect size estimates for small samples. To tackle this issue, we propose a hierarchical Bayesian model to adjust the magnitude of single-study effect sizes while incorporating a tailored estimation of sampling variance.METHODS: We estimated the effect sizes of case-control differences on brain structural features between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis and non-dependent participants for 21 individual studies (Total cases: 903; Total controls: 996). Then, the study-specific effect sizes were modeled using a hierarchical Bayesian approach in which the parameters of the study-specific effect size distributions were sampled from a higher-order overarching distribution. The posterior distribution of the overarching and study-specific parameters was approximated using the Gibbs sampling method.RESULTS: The results showed shrinkage of the posterior distribution of the study-specific estimates toward the overarching estimates given the original effect sizes observed in individual studies. Differences between the original effect sizes (i.e., Cohen's d) and the point estimate of the posterior distribution ranged from 0 to 0.97. The magnitude of adjustment was negatively correlated with the sample size (r = -0.27, p &lt; 0.001) and positively correlated with empirically estimated sampling variance (r = 0.40, p &lt; 0.001), suggesting studies with smaller samples and larger sampling variance tended to have greater adjustments. DISCUSSION: Our findings demonstrate the utility of the hierarchical Bayesian model in recalibrating single-study effect sizes using information from similar studies. This suggests that Bayesian utilization of existing knowledge can be an effective alternative approach to improve the effect size estimation in individual studies, particularly for those with smaller samples.</p

Predicting alcohol dependence frommulti-sitebrain structural measures

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification models that are explicitly generalizable to unseen sites and populations. This problem was explored in a mega‐analysis of previously published datasets from 2,034 AD and comparison participants spanning 27 sites curated by the ENIGMA Addiction Working Group. Data were grouped into a training set used for internal validation including 1,652 participants (692 AD, 24 sites), and a test set used for external validation with 382 participants (146 AD, 3 sites). An exploratory data analysis was first conducted, followed by an evolutionary search based feature selection to site generalizable and high performing subsets of brain measurements. Exploratory data analysis revealed that inclusion of case‐ and control‐only sites led to the inadvertent learning of site‐effects. Cross validation methods that do not properly account for site can drastically overestimate results. Evolutionary‐based feature selection leveraging leave‐one‐site‐out cross‐validation, to combat unintentional learning, identified cortical thickness in the left superior frontal gyrus and right lateral orbitofrontal cortex, cortical surface area in the right transverse temporal gyrus, and left putamen volume as final features. Ridge regression restricted to these features yielded a test‐set area under the receiver operating characteristic curve of 0.768. These findings evaluate strategies for handling multi‐site data with varied underlying class distributions and identify potential biomarkers for individuals with current AD

Sex differences in the neuroanatomy of alcohol dependence: hippocampus and amygdala subregions in a sample of 966 people from the ENIGMA Addiction Working Group

Males and females with alcohol dependence have distinct mental health and cognitive problems. Animal models of addiction postulate that the underlying neurobiological mechanisms are partially distinct, but there is little evidence of sex differences in humans with alcohol dependence as most neuroimaging studies have been conducted in males. We examined hippocampal and amygdala subregions in a large sample of 966 people from the ENIGMA Addiction Working Group. This comprised 643 people with alcohol dependence (225 females), and a comparison group of 323 people without alcohol dependence (98 females). Males with alcohol dependence had smaller volumes of the total amygdala and its basolateral nucleus than male controls, that exacerbated with alcohol dose. Alcohol dependence was also associated with smaller volumes of the hippocampus and its CA1 and subiculum subfield volumes in both males and females. In summary, hippocampal and amygdalar subregions may be sensitive to both shared and distinct mechanisms in alcohol-dependent males and females

Mega-Analysis of Gray Matter Volume in Substance Dependence: General and Substance-Specific Regional Effects

Objective: Although lower brain volume has been routinely observed in individuals with substance dependence compared with nondependent control subjects, the brain regions exhibiting lower volume have not been consistent across studies. In addition, it is not clear whether a common set of regions are involved in substance dependence regardless of the substance used or whether some brain volume effects are substance specific. Resolution of these issues may contribute to the identification of clinically relevant imaging biomarkers. Using pooled data from 14 countries, the authors sought to identify general and substance-specific associations between dependence and regional brain volumes. Method: Brain structure was examined in a mega-analysis of previously published data pooled from 23 laboratories, including 3,240 individuals, 2,140 of whom had substance dependence on one of five substances: alcohol, nicotine, cocaine, methamphetamine, or cannabis. Subcortical volume and cortical thickness in regions defined by FreeSurfer were compared with nondependent control subjects when all sampled substance categories were combined, as well as separately, while controlling for age, sex, imaging site, and total intracranial volume. Because of extensive associations with alcohol dependence, a secondary contrast was also performed for dependence on all substances except alcohol. An optimized split-half strategy was used to assess the reliability of the findings. Results: Lower volume or thickness was observed in many brain regions in individuals with substance dependence. The greatest effects were associated with alcohol use disorder. A set of affected regions related to dependence in general, regardless of the substance, included the insula and the medial orbitofrontal cortex. Furthermore, a support vector machine multivariate classification of regional brain volumes successfully classified individuals with substance dependence on alcohol or nicotine relative to nondependent control subjects. Conclusions: The results indicate that dependence on a range of different substances shares a common neural substrate and that differential patterns of regional volume could serve as useful biomarkers of dependence on alcohol and nicotine

Schematic diagram illustrating the proposed hypothesis of the new role of 3’UTR-embedded Alus in the genesis of PPs and the herpesviral capture of host genes.

<p>Blue pathway: A highly expressed gene A produces a large amount of transcripts (<b>a</b>) and thus there is a high probability for one of these transcripts to come into contact with a ribosome that is translating an L1 RNA and bind the L1 ORF2p (<b>b</b>), steal it (<b>c</b>), and move back to the nucleus where the ORF2p is used to generate a new processed pseudogene of the gene A (PP A) (<b>d</b>). Red pathway: The few transcripts of a lowly expressed gene B (<b>e</b>) have, by contrast, a low probability to reach a ribosome that is translating an L1 RNA. However, the presence of an Alu element inside the 3’UTR of the gene B allows gene B transcripts to bind the abundant protein complex SRP9/14, promoting transcripts to move to the ribosomes and therefore increasing the likelihood to make contact with a ribosome that is translating an L1 RNA and bind the L1 ORF2p (<b>f</b>), steal it (<b>g</b>), and move to the nucleus where the ORF2p is used to generate a new processed pseudogene of the gene B (PP B) (<b>h</b>) or to insert a transcript retrocopy inside an existing herpesviral episome (the circled DNA of a herpesvirus) (<b>i</b>).</p

Mechanisms underlying alcohol-approach action tendencies: The role of emotional primes and drinking motives

The tendency to approach alcohol-related stimuli is known as the alcohol-approach bias and has been related to heavy alcohol use. It is currently unknown whether the alcohol-approach bias is more pronounced after emotional priming. The main aim of this study was to investigate whether positive and negative emotional primes would modulate the alcohol-approach bias. For this purpose, a new contextual emotional prime-approach avoidance task was developed, containing both negative and positive emotional primes. Explicit coping drinking motives were expected to be related to an increased alcohol-approach bias after negative primes. Results of 65 heavy and 50 occasional drinkers showed that the alcohol-approach bias was increased in both groups during negative emotional priming. This appeared to be due to slower alcohol avoidance rather than faster alcohol approach. This change in alcohol-approach bias was positively related to explicit enhancement drinking motives and negatively related to alcohol use-related problems. A stronger alcohol-approach bias in heavy compared to occasional drinkers could not be replicated here, and coping drinking motives were not related to the alcohol-approach bias in any of the emotional contexts. The current findings suggest that both occasional and heavy drinkers have a selective difficulty to avoid alcohol-related cues in a negative emotional context. Negative reinforcement may therefore be involved in different types of drinking patterns. The influence of emotional primes on alcohol-related action tendencies may become smaller when alcohol use becomes more problematic, which is in line with habit accounts of addiction