Unraveling the molecular relevance of brain phenotypes: A comparative analysis of null models and test statistics

Correlating transcriptional profiles with imaging-derived phenotypes has the potential to reveal possible molecular architectures associated with cognitive functions, brain development and disorders. Competitive null models built by resampling genes and self-contained null models built by spinning brain regions, along with varying test statistics, have been used to determine the significance of transcriptional associations. However, there has been no systematic evaluation of their performance in imaging transcriptomics analyses. Here, we evaluated the performance of eight different test statistics (mean, mean absolute value, mean squared value, max mean, median, Kolmogorov-Smirnov (KS), Weighted KS and the number of significant correlations) in both competitive null models and self-contained null models. Simulated brain maps (n = 1,000) and gene sets (n = 500) were used to calculate the probability of significance (Psig) for each statistical test. Our results suggested that competitive null models may result in false positive results driven by co-expression within gene sets. Furthermore, we demonstrated that the self-contained null models may fail to account for distribution characteristics (e.g., bimodality) of correlations between all available genes and brain phenotypes, leading to false positives. These two confounding factors interacted differently with test statistics, resulting in varying outcomes. Specifically, the sign-sensitive test statistics (i.e., mean, median, KS, Weighted KS) were influenced by co-expression bias in the competitive null models, while median and sign-insensitive test statistics were sensitive to the bimodality bias in the self-contained null models. Additionally, KS-based statistics produced conservative results in the self-contained null models, which increased the risk of false negatives. Comprehensive supplementary analyses with various configurations, including realistic scenarios, supported the results. These findings suggest utilizing sign-insensitive test statistics such as mean absolute value, max mean in the competitive null models and the mean as the test statistic for the self-contained null models. Additionally, adopting the confounder-matched (e.g., coexpression-matched) null models as an alternative to standard null models can be a viable strategy. Overall, the present study offers insights into the selection of statistical tests for imaging transcriptomics studies, highlighting areas for further investigation and refinement in the evaluation of novel and commonly used tests.

Parameter Space and Potential for Biomarker Development in 25 Years of fMRI Drug Cue Reactivity: A Systematic Review

Importance

In the last 25 years, functional magnetic resonance imaging drug cue reactivity (FDCR) studies have characterized some core aspects in the neurobiology of drug addiction. However, no FDCR-derived biomarkers have been approved for treatment development or clinical adoption. Traversing this translational gap requires a systematic assessment of the FDCR literature evidence, its heterogeneity, and an evaluation of possible clinical uses of FDCR-derived biomarkers.

Objective

To summarize the state of the field of FDCR, assess their potential for biomarker development, and outline a clear process for biomarker qualification to guide future research and validation efforts.

Evidence Review

The PubMed and Medline databases were searched for every original FDCR investigation published from database inception until December 2022. Collected data covered study design, participant characteristics, FDCR task design, and whether each study provided evidence that might potentially help develop susceptibility, diagnostic, response, prognostic, predictive, or severity biomarkers for 1 or more addictive disorders.

Findings

There were 415 FDCR studies published between 1998 and 2022. Most focused on nicotine (122 [29.6%]), alcohol (120 [29.2%]), or cocaine (46 [11.1%]), and most used visual cues (354 [85.3%]). Together, these studies recruited 19 311 participants, including 13 812 individuals with past or current substance use disorders. Most studies could potentially support biomarker development, including diagnostic (143 [32.7%]), treatment response (141 [32.3%]), severity (84 [19.2%]), prognostic (30 [6.9%]), predictive (25 [5.7%]), monitoring (12 [2.7%]), and susceptibility (2 [0.5%]) biomarkers. A total of 155 interventional studies used FDCR, mostly to investigate pharmacological (67 [43.2%]) or cognitive/behavioral (51 [32.9%]) interventions; 141 studies used FDCR as a response measure, of which 125 (88.7%) reported significant interventional FDCR alterations; and 25 studies used FDCR as an intervention outcome predictor, with 24 (96%) finding significant associations between FDCR markers and treatment outcomes.

Conclusions and Relevance

Based on this systematic review and the proposed biomarker development framework, there is a pathway for the development and regulatory qualification of FDCR-based biomarkers of addiction and recovery. Further validation could support the use of FDCR-derived measures, potentially accelerating treatment development and improving diagnostic, prognostic, and predictive clinical judgments.

Cannabis Dependence is Associated with Reduced Hippocampal Subregion Volumes Independently of Sex: Findings from an ENIGMA Addiction Working Group Multi-Country Study

Background: Males and females who consume cannabis can experience different mental health and cognitive problems. Neuroscientific theories of addiction postulate that dependence is underscored by neuroadaptations, but do not account for the contribution of distinct sexes. Further, there is little evidence for sex differences in the neurobiology of cannabis dependence as most neuroimaging studies have been conducted in largely male samples in which cannabis dependence, as opposed to use, is often not ascertained. Methods: We examined subregional hippocampus and amygdala volumetry in a sample of 206 people recruited from the ENIGMA Addiction Working Group. They included 59 people with cannabis dependence (17 females), 49 cannabis users without cannabis dependence (20 females), and 98 controls (33 females). Results: We found no group-by-sex effect on subregional volumetry. The left hippocampal cornu ammonis subfield 1 (CA1) volumes were lower in dependent cannabis users compared with non-dependent cannabis users (p<0.001, d=0.32) and with controls (p=0.022, d=0.18). Further, the left cornu ammonis subfield 3 (CA3) and left dentate gyrus volumes were lower in dependent versus non-dependent cannabis users but not versus controls (p=0.002, d=0.37, and p=0.002, d=0.31, respectively). All models controlled for age, intelligence quotient (IQ), alcohol and tobacco use, and intracranial volume. Amygdala volumetry was not affected by group or group-by-sex, but was smaller in females than males. Conclusions: Our findings suggest that the relationship between cannabis dependence and subregional volumetry was not moderated by sex. Specifically, dependent (rather than non-dependent) cannabis use may be associated with alterations in selected hippocampus subfields high in cannabinoid type 1 (CB1) receptors and implicated in addictive behavior. As these data are cross-sectional, it is plausible that differences predate cannabis dependence onset and contribute to the initiation of cannabis dependence. Longitudinal neuroimaging work is required to examine the time-course of the onset of subregional hippocampal alterations in cannabis dependence, and their progression as cannabis dependence exacerbates or recovers over time.

Neuroanatomical variability associated with early substance use initiation: Results from the ABCD Study

The extent to which neuroanatomical variability associated with substance involvement reflects pre-existing risk and/or consequences of substance exposure remains poorly understood. In the Adolescent Brain Cognitive DevelopmentSM (ABCD®) Study, we identify associations between global and regional differences in brain structure and early substance use initiation (i.e., occurring <15 years of age; nsanalytic=6,556-9,804), with evidence that associations precede initiation. Neurodevelopmental variability in brain structure may confer risk for substance involvement.

Brain structural covariance network features are robust markers of early heavy alcohol use

BACKGROUND AND AIMS

Recently, we demonstrated that a distinct pattern of structural covariance networks (SCN) from magnetic resonance imaging (MRI)-derived measurements of brain cortical thickness characterized young adults with alcohol use disorder (AUD) and predicted current and future problematic drinking in adolescents relative to controls. Here, we establish the robustness and value of SCN for identifying heavy alcohol users in three additional independent studies.

DESIGN AND SETTING

Cross-sectional and longitudinal studies using data from the Pediatric Imaging, Neurocognition and Genetics (PING) study (n = 400, age range = 14-22 years), the National Consortium on Alcohol and Neurodevelopment in Adolescence (NCANDA) (n = 272, age range = 17-22 years) and the Human Connectome Project (HCP) (n = 375, age range = 22-37 years).

CASES

Cases were defined based on heavy alcohol use patterns or former alcohol use disorder (AUD) diagnoses: 50, 68 and 61 cases were identified. Controls had none or low alcohol use or absence of AUD: 350, 204 and 314 controls were selected.

MEASUREMENTS

Graph theory metrics of segregation and integration were used to summarize SCN.

FINDINGS

Mirroring our prior findings, and across the three data sets, cases had a lower clustering coefficient [area under the curve (AUC) = -0.029, P = 0.002], lower modularity (AUC = -0.14, P = 0.004), lower average shortest path length (AUC = -0.078, P = 0.017) and higher global efficiency (AUC = 0.007, P = 0.010). Local efficiency differences were marginal (AUC = -0.017, P = 0.052). That is, cases exhibited lower network segregation and higher integration, suggesting that adjacent nodes (i.e. brain regions) were less similar in thickness whereas spatially distant nodes were more similar.

CONCLUSION

Structural covariance network (SCN) differences in the brain appear to constitute an early marker of heavy alcohol use in three new data sets and, more generally, demonstrate the utility of SCN-derived metrics to detect brain-related psychopathology.

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 < 0.001) and positively correlated with empirically estimated sampling variance (r = 0.40, p < 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.

Prevalence and predictors for postpartum sleep disorders: a nationwide analysis

OBJECTIVE

To describe the prevalence and predictors of postpartum sleep disorders.

DESIGN

A retrospective cohort study.

SETTING

Postpartum.

POPULATION

Commercially insured women delivering in California (USA) between 2011 and 2014.

METHODS

Using the Optum Clinformatics Datamart Database.

MAIN OUTCOME MEASURES

Prevalence of a postpartum sleep disorder diagnosis with and without a depression diagnosis up to 12 months following hospital discharge for inpatient delivery. We also identified predictors of a postpartum sleep disorder diagnosis using multivariable logistic regression.

RESULTS

We identified 3535 (1.9%) women with a postpartum sleep disorder diagnosis. The prevalence of sleep disorder diagnoses was insomnia (1.3%), sleep apnea (0.25%), and other sleep disorder (0.25%). The odds of a postpartum sleep disorder were highest among women with a history of drug abuse (adjusted odds ratio (aOR): 2.70, 95% confidence interval (CI): 1.79-4.09); a stillbirth delivery (aOR: 2.15, 95% CI: 1.53-3.01); and chronic hypertension (aOR: 1.82; 95% CI: 1.57-2.11). A comorbid diagnosis of a postpartum sleep disorder and depression occurred in 1182 women (0.6%). These women accounted for 33.4% of all women with a postpartum sleep disorder. The strongest predictors of a comorbid diagnosis were a history of drug abuse (aOR: 4.13; 95% CI: 2.37-7.21) and a stillbirth delivery (aOR: 2.93; 95% CI: 1.74-4.92).

CONCLUSIONS

Postpartum sleep disorders are underdiagnosed conditions, with only 2% of postpartum women in this cohort receiving a sleep diagnosis using International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes. Insomnia was the most common disorder and one-third of women diagnosed with a postpartum sleep disorder had a co-morbid diagnosis of depression. Future studies are needed to improve the screening and diagnostic accuracy of postpartum sleep disorders.

Differential associations of adolescent versus young adult cannabis initiation with longitudinal brain change and behavior

Leveraging ~10 years of prospective longitudinal data on 704 participants, we examined the effects of adolescent versus young adult cannabis initiation on MRI-assessed cortical thickness development and behavior. Data were obtained from the IMAGEN study conducted across eight European sites. We identified IMAGEN participants who reported being cannabis-naïve at baseline and had data available at baseline, 5-year, and 9-year follow-up visits. Cannabis use was assessed with the European School Survey Project on Alcohol and Drugs. T1-weighted MR images were processed through the CIVET pipeline. Cannabis initiation occurring during adolescence (14-19 years) and young adulthood (19-22 years) was associated with differing patterns of longitudinal cortical thickness change. Associations between adolescent cannabis initiation and cortical thickness change were observed primarily in dorso- and ventrolateral portions of the prefrontal cortex. In contrast, cannabis initiation occurring between 19 and 22 years of age was associated with thickness change in temporal and cortical midline areas. Follow-up analysis revealed that longitudinal brain change related to adolescent initiation persisted into young adulthood and partially mediated the association between adolescent cannabis use and past-month cocaine, ecstasy, and cannabis use at age 22. Extent of cannabis initiation during young adulthood (from 19 to 22 years) had an indirect effect on psychotic symptoms at age 22 through thickness change in temporal areas. Results suggest that developmental timing of cannabis exposure may have a marked effect on neuroanatomical correlates of cannabis use as well as associated behavioral sequelae. Critically, this work provides a foundation for neurodevelopmentally informed models of cannabis exposure in humans.

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, voxel-based, multi-tissue mega-analytic approach, thereby extending our recent surface-based 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 group-by-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.

Association Between Brain Structure and Alcohol Use Behaviors in Adults: A Mendelian Randomization and Multiomics Study

IMPORTANCE

Past studies have identified associations between brain macrostructure and alcohol use behaviors. However, identifying directional associations between these phenotypes is difficult due to the limitations of observational studies.

OBJECTIVE

To use mendelian randomization (MR) to identify directional associations between brain structure and alcohol use and elucidate the transcriptomic and cellular underpinnings of identified associations.

DESIGN, SETTING, AND PARTICIPANTS

The main source data comprised summary statistics from population-based and case-control genome-wide association studies (GWAS) of neuroimaging, behavioral, and clinical phenotypes (N = 763 874). Using these data, bidirectional and multivariable MR was performed analyzing associations between brain macrostructure and alcohol use. Downstream transcriptome-wide association studies (TWAS) and cell-type enrichment analyses investigated the biology underlying identified associations. The study approach was data driven and did not test any a priori hypotheses. Data were analyzed August 2021 to May 2022.

MAIN OUTCOMES AND MEASURES

Brain structure phenotypes (global cortical thickness [GCT] and global cortical surface area [GCSA] in 33 709 individuals and left-right subcortical volumes in 19 629 individuals) and alcohol use behaviors (alcoholic drinks per week [DPW] in 537 349 individuals, binge drinking frequency in 143 685 individuals, and alcohol use disorder in 8845 individuals vs 20 657 control individuals [total of 29 502]).

RESULTS

The main bidirectional MR analyses were performed in samples totaling 763 874 individuals, among whom more than 94% were of European ancestry, 52% to 54% were female, and the mean cohort ages were 40 to 63 years. Negative associations were identified between genetically predicted GCT and binge drinking (β, -2.52; 95% CI, -4.13 to -0.91) and DPW (β, -0.88; 95% CI, -1.37 to -0.40) at a false discovery rate (FDR) of 0.05. These associations remained significant in multivariable MR models that accounted for neuropsychiatric phenotypes, substance use, trauma, and neurodegeneration. TWAS of GCT and alcohol use behaviors identified 5 genes at the 17q21.31 locus oppositely associated with GCT and binge drinking or DPW (FDR = 0.05). Cell-type enrichment analyses implicated glutamatergic cortical neurons in alcohol use behaviors.

CONCLUSIONS AND RELEVANCE

The findings in this study show that the associations between GCT and alcohol use may reflect a predispositional influence of GCT and that 17q21.31 genes and glutamatergic cortical neurons may play a role in this association. While replication studies are needed, these findings should enhance the understanding of associations between brain structure and alcohol use.

Bayesian causal network modeling suggests adolescent cannabis use accelerates prefrontal cortical thinning

While there is substantial evidence that cannabis use is associated with differences in human brain development, most of this evidence is correlational in nature. Bayesian causal network (BCN) modeling attempts to identify probable causal relationships in correlational data using conditional probabilities to estimate directional associations between a set of interrelated variables. In this study, we employed BCN modeling in 637 adolescents from the IMAGEN study who were cannabis naïve at age 14 to provide evidence that the accelerated prefrontal cortical thinning found previously in adolescent cannabis users by Albaugh et al. [1] is a result of cannabis use causally affecting neurodevelopment. BCNs incorporated data on cannabis use, prefrontal cortical thickness, and other factors related to both brain development and cannabis use, including demographics, psychopathology, childhood adversity, and other substance use. All BCN algorithms strongly suggested a directional relationship from adolescent cannabis use to accelerated cortical thinning. While BCN modeling alone does not prove a causal relationship, these results are consistent with a body of animal and human research suggesting that adolescent cannabis use adversely affects brain development.

Common and gender-specific associations with cocaine use on gray matter volume: Data from the ENIGMA addiction working group

Gray matter volume (GMV) in frontal cortical and limbic regions is susceptible to cocaine-associated reductions in cocaine-dependent individuals (CD) and is negatively associated with duration of cocaine use. Gender differences in CD individuals have been reported clinically and in the context of neural responses to cue-induced craving and stress reactivity. The variability of GMV in select brain areas between men and women (e.g., limbic regions) underscores the importance of exploring interaction effects between gender and cocaine dependence on brain structure. Therefore, voxel-based morphometry data derived from the ENIGMA Addiction Consortium were used to investigate potential gender differences in GMV in CD individuals compared to matched controls (CTL). T1-weighted MRI scans and clinical data were pooled from seven sites yielding 420 gender- and age-matched participants: CD men (CDM, n = 140); CD women (CDW, n = 70); control men (CTLM, n = 140); and control women (CTLW, n = 70). Differences in GMV were assessed using a 2 × 2 ANCOVA, and voxelwise whole-brain linear regressions were conducted to explore relationships between GMV and duration of cocaine use. All analyses were corrected for age, total intracranial volume, and site. Diagnostic differences were predominantly found in frontal regions (CD < CTL). Interestingly, gender × diagnosis interactions in the left anterior insula and left lingual gyrus were also documented, driven by differences in women (CDW < CTLW). Further, lower right hippocampal GMV was associated with greater cocaine duration in CDM. Given the importance of the anterior insula to interoception and the hippocampus to learning contextual associations, results may point to gender-specific mechanisms in cocaine addiction.

White matter microstructure differences in individuals with dependence on cocaine, methamphetamine, and nicotine: Findings from the ENIGMA-Addiction working group

BACKGROUND

Nicotine and illicit stimulants are very addictive substances. Although associations between grey matter and dependence on stimulants have been frequently reported, white matter correlates have received less attention.

METHODS

Eleven international sites ascribed to the ENIGMA-Addiction consortium contributed data from individuals with dependence on cocaine (n = 147), methamphetamine (n = 132) and nicotine (n = 189), as well as non-dependent controls (n = 333). We compared the fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) of 20 bilateral tracts. Also, we compared the performance of various machine learning algorithms in deriving brain-based classifications on stimulant dependence.

RESULTS

The cocaine and methamphetamine groups had lower regional FA and higher RD in several association, commissural, and projection white matter tracts. The methamphetamine dependent group additionally showed lower regional AD. The nicotine group had lower FA and higher RD limited to the anterior limb of the internal capsule. The best performing machine learning algorithm was the support vector machine (SVM). The SVM successfully classified individuals with dependence on cocaine (AUC = 0.70, p < 0.001) and methamphetamine (AUC = 0.71, p < 0.001) relative to non-dependent controls. Classifications related to nicotine dependence proved modest (AUC = 0.62, p = 0.014).

CONCLUSIONS

Stimulant dependence was related to FA disturbances within tracts consistent with a role in addiction. The multivariate pattern of white matter differences proved sufficient to identify individuals with stimulant dependence, particularly for cocaine and methamphetamine.

Characterizing reward system neural trajectories from adolescence to young adulthood

Mixed findings exist in studies comparing brain responses to reward in adolescents and adults. Here we examined the trajectories of brain response, functional connectivity and task-modulated network properties during reward processing with a large-sample longitudinal design. Participants from the IMAGEN study performed a Monetary Incentive Delay task during fMRI at timepoint 1 (T1; n = 1304, mean age=14.44 years old) and timepoint 2 (T2; n = 1241, mean age=19.09 years). The Alcohol Use Disorders Identification Test (AUDIT) was administrated at both T1 and T2 to assess a participant’s alcohol use during the past year. Voxel-wise linear mixed effect models were used to compare whole brain response as well as functional connectivity of the ventral striatum (VS) during reward anticipation (large reward vs no-reward cue) between T1 and T2. In addition, task-modulated networks were constructed using generalized psychophysiological interaction analysis and summarized with graph theory metrics. To explore alcohol use in relation to development, participants with no/low alcohol use at T1 but increased alcohol use to hazardous use level at T2 (i.e., participants with AUDIT≤2 at T1 and ≥8 at T2) were compared against those with consistently low scores (i.e., participants with AUDIT≤2 at T1 and ≤7 at T2). Across the whole sample, lower brain response during reward anticipation was observed at T2 compared with T1 in bilateral caudate nucleus, VS, thalamus, midbrain, dorsal anterior cingulate as well as left precentral and postcentral gyrus. Conversely, greater response was observed bilaterally in the inferior and middle frontal gyrus and right precentral and postcentral gyrus at T2 (vs. T1). Increased functional connectivity with VS was found in frontal, temporal, parietal and occipital regions at T2. Graph theory metrics of the task-modulated network showed higher inter-regional connectivity and topological efficiency at T2. Interactive effects between time (T1 vs. T2) and alcohol use group (low vs. high) on the functional connectivity were observed between left middle temporal gyrus and right VS and the characteristic shortest path length of the task-modulated networks. Collectively, these results demonstrate the utility of the MID task as a probe of typical brain response and network properties during development and of differences in these features related to adolescent drinking, a reward-related behaviour associated with heightened risk for future negative health outcomes.

•

Imaging data during reward anticipation at T1 (age 14) and T2 (age 19) was compared.

•

Brain response decreased in subcortical areas and increased in cortical areas at T2.

•

Functional connectivity (FC) with the ventral striatum increased at T2.

•

Topological efficiency of task-modulated network increased at T2.

•

The developmental pattern was altered in those who increased drinking most at T2.

Mapping cortical and subcortical asymmetries in substance dependence: Findings from the ENIGMA Addiction Working Group

Brain asymmetry reflects left-right hemispheric differentiation, which is a quantitative brain phenotype that develops with age and can vary with psychiatric diagnoses. Previous studies have shown that substance dependence is associated with altered brain structure and function. However, it is unknown whether structural brain asymmetries are different in individuals with substance dependence compared with nondependent participants. Here, a mega-analysis was performed using a collection of 22 structural brain MRI datasets from the ENIGMA Addiction Working Group. Structural asymmetries of cortical and subcortical regions were compared between individuals who were dependent on alcohol, nicotine, cocaine, methamphetamine, or cannabis (n = 1,796) and nondependent participants (n = 996). Substance-general and substance-specific effects on structural asymmetry were examined using separate models. We found that substance dependence was significantly associated with differences in volume asymmetry of the nucleus accumbens (NAcc; less rightward; Cohen's d = 0.15). This effect was driven by differences from controls in individuals with alcohol dependence (less rightward; Cohen's d = 0.10) and nicotine dependence (less rightward; Cohen's d = 0.11). These findings suggest that disrupted structural asymmetry in the NAcc may be a characteristic of substance dependence.

Baseline brain function in the preadolescents of the ABCD Study

The Adolescent Brain Cognitive Development (ABCD) Study® is a 10-year longitudinal study of children recruited at ages 9 and 10. A battery of neuroimaging tasks are administered biennially to track neurodevelopment and identify individual differences in brain function. This study reports activation patterns from functional MRI (fMRI) tasks completed at baseline, which were designed to measure cognitive impulse control with a stop signal task (SST; N = 5,547), reward anticipation and receipt with a monetary incentive delay (MID) task (N = 6,657) and working memory and emotion reactivity with an emotional N-back (EN-back) task (N = 6,009). Further, we report the spatial reproducibility of activation patterns by assessing between-group vertex/voxelwise correlations of blood oxygen level-dependent (BOLD) activation. Analyses reveal robust brain activations that are consistent with the published literature, vary across fMRI tasks/contrasts and slightly correlate with individual behavioral performance on the tasks. These results establish the preadolescent brain function baseline, guide interpretation of cross-sectional analyses and will enable the investigation of longitudinal changes during adolescent development.

Multimodal brain predictors of current weight and weight gain in children enrolled in the ABCD study ®

Multimodal neuroimaging assessments were utilized to identify generalizable brain correlates of current body mass index (BMI) and predictors of pathological weight gain (i.e., beyond normative development) one year later. Multimodal data from children enrolled in the Adolescent Brain Cognitive Development Study® at 9-to-10-years-old, consisted of structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), resting state (rs), and three task-based functional (f) MRI scans assessing reward processing, inhibitory control, and working memory. Cross-validated elastic-net regression revealed widespread structural associations with BMI (e.g., cortical thickness, surface area, subcortical volume, and DTI), which explained 35% of the variance in the training set and generalized well to the test set (R2 = 0.27). Widespread rsfMRI inter- and intra-network correlations were related to BMI (R2train = 0.21; R2test = 0.14), as were regional activations on the working memory task (R2train = 0.20; (R2test = 0.16). However, reward and inhibitory control tasks were unrelated to BMI. Further, pathological weight gain was predicted by structural features (Area Under the Curve (AUC)train = 0.83; AUCtest = 0.83, p < 0.001), but not by fMRI nor rsfMRI. These results establish generalizable brain correlates of current weight and future pathological weight gain. These results also suggest that sMRI may have particular value for identifying children at risk for pathological weight gain.

Sex and dependence related neuroanatomical differences in regular cannabis users: findings from the ENIGMA Addiction Working Group

Males and females show different patterns of cannabis use and related psychosocial outcomes. However, the neuroanatomical substrates underlying such differences are poorly understood. The aim of this study was to map sex differences in the neurobiology (as indexed by brain volumes) of dependent and recreational cannabis use. We compared the volume of a priori regions of interest (i.e., amygdala, hippocampus, nucleus accumbens, insula, orbitofrontal cortex (OFC), anterior cingulate cortex and cerebellum) between 129 regular cannabis users (of whom 70 were recreational users and 59 cannabis dependent) and 114 controls recruited from the ENIGMA Addiction Working Group, accounting for intracranial volume, age, IQ, and alcohol and tobacco use. Dependent cannabis users, particularly females, had (marginally significant) smaller volumes of the lateral OFC and cerebellar white matter than recreational users and controls. In dependent (but not recreational) cannabis users, there was a significant association between female sex and smaller volumes of the cerebellar white matter and OFC. Volume of the OFC was also predicted by monthly standard drinks. No significant effects emerged the other brain regions of interest. Our findings warrant future multimodal studies that examine if sex and cannabis dependence are specific key drivers of neurobiological alterations in cannabis users. This, in turn, could help to identify neural pathways specifically involved in vulnerable cannabis users (e.g., females with cannabis dependence) and inform individually tailored neurobiological targets for treatment.

Substance Use Initiation, Particularly Alcohol, in Drug-Naive Adolescents: Possible Predictors and Consequences From a Large Cohort Naturalistic Study

OBJECTIVE

It is unclear whether deviations in brain and behavioral development, which may underpin elevated substance use during adolescence, are predispositions for or consequences of substance use initiation. Here, we examine behavioral and neuroimaging indices at early and mid-adolescence in drug-naive youths to identify possible predisposing factors for substance use initiation and its possible consequences.

METHOD

Among 304 drug-naive adolescents at baseline (age 14 years) from the IMAGEN dataset, 83 stayed drug-naive, 133 used alcohol on 1 to 9 occasions, 42 on 10 to 19 occasions, 27 on 20 to 39 occasions, and 19 on >40 occasions at follow-up (age 16 years). Baseline measures included brain activation during the Monetary Incentive Delay task. Data at both baseline and follow-up included measures of trait impulsivity and delay discounting.

RESULTS

From baseline to follow-up, impulsivity decreased in the 0 and 1- to 9-occasions groups (p < .004), did not change in the 10- to 19-occasions and 20- to 29-occasions groups (p > .294), and uncharacteristically increased in the >40-occasions group (p = .046). Furthermore, blunted medial orbitofrontal cortex activation during reward outcome at baseline significantly predicted higher alcohol use frequency at follow-up, above and beyond behavioral and clinical variables (p = .008).

CONCLUSION

These results suggest that the transition from no use to frequent drinking in early to mid-adolescence may disrupt normative developmental changes in behavioral control. In addition, blunted activity of the medial orbitofrontal cortex during reward outcome may underscore a predisposition toward the development of more severe alcohol use in adolescents. This distinction is clinically important, as it informs early intervention efforts in preventing the onset of substance use disorder in adolescents.

COVID-19: A new barrier to treatment for opioid use disorder in the emergency department

OBJECTIVE

Start Treatment and Recover (STAR) is an emergency department (ED) program that expands access to medication for opioid use disorder by identifying patients with opioid use disorder and offering ED-initiated buprenorphine/naloxone and rapid access to outpatient treatment. We sought to determine the impacts of the coronavirus disease 2019 pandemic on STAR and the patients with opioid use disorder it serves.

METHODS

We conducted a retrospective review of records comparing 2 periods: pre-pandemic (February 1, 2019-February 29, 2020) and pandemic (March 1, 2020-May 31, 2020). Variables evaluated included the number of STAR enrollments, ED census, percentage of census screening positive for opioid use disorder, number and percentage of ED overdose visits, and overdose fatalities by month. All analyses were conducted using 2-sample t tests to calculate the mean and 95% confidence intervals (CIs).

RESULTS

Comparing the pre-pandemic to the pandemic period, the mean monthly ED visits decreased from 5126.9 to 3306.7 (difference = -1820.3; 95% CI, -3406.3 to -234.2), STAR mean monthly enrollments decreased from 9.7 to 1.3 (difference = -8.4; 95% CI, -12.8 to -4.0), and statewide monthly opioid-related fatalities increased from 9.4 to 15.3 (difference = 5.9; 95% CI, 0.8 to 11.1). However, the percentage of individuals who presented to the ED with opioid use disorder or overdose remained unchanged.

CONCLUSION

Although overall ED visits declined during the pandemic period, the percentage of patients presenting with opioid use disorder or overdose remained constant, yet there was a dramatic decline in enrollment in ED-initiated medication for opioid use disorder and an increase in statewide monthly opioid-related fatalities. Strategies to maintain medication for opioid use disorder treatment options must be implemented for this vulnerable population during the ongoing pandemic.

Gender-related neuroanatomical differences in alcohol dependence: findings from the ENIGMA Addiction Working Group

•

We tested gender differences in brain volumes of alcohol dependent vs control groups.

•

Group differences in brain volumes emerged as gross and widespread.

•

Group-by-gender effects emerged in selected brain regions (cerebellum, amygdala)

•

In dependent users, greater alcohol use predicted smaller amygdala and larger cerebellum GM volume.

•

Our results highlight the need to account for gender differences in MRI studies of alcohol dependence.

Gender-related differences in the susceptibility, progression and clinical outcomes of alcohol dependence are well-known. However, the neurobiological substrates underlying such differences remain unclear. Therefore, this study aimed to investigate gender differences in the neuroanatomy (i.e. regional brain volumes) of alcohol dependence. We examined the volume of a priori regions of interest (i.e., orbitofrontal cortex, hippocampus, amygdala, nucleus accumbens, caudate, putamen, pallidum, thalamus, corpus callosum, cerebellum) and global brain measures (i.e., total grey matter (GM), total white matter (WM) and cerebrospinal fluid). Volumes were compared between 660 people with alcohol dependence (228 women) and 326 controls (99 women) recruited from the ENIGMA Addiction Working Group, accounting for intracranial volume, age and education years. Compared to controls, individuals with alcohol dependence on average had (3–9%) smaller volumes of the hippocampus (bilateral), putamen (left), pallidum (left), thalamus (right), corpus callosum, total GM and WM, and cerebellar GM (bilateral), the latter more prominently in women (right). Alcohol-dependent men showed smaller amygdala volume than control men, but this effect was unclear among women. In people with alcohol dependence, more monthly standard drinks predicted smaller amygdala and larger cerebellum GM volumes. The neuroanatomical differences associated with alcohol dependence emerged as gross and widespread, while those associated with a specific gender may be confined to selected brain regions. These findings warrant future neuroscience research to account for gender differences in alcohol dependence to further understand the neurobiological effects of alcohol dependence.

The relation between the flexion relaxation phenomenon onset angle and lumbar spine muscle reflex onset time in response to 30 min of slumped sitting

Viscoelastic creep of spine tissue, induced by submaximal spine flexion in sitting, can delay the onset of the flexion-relaxation phenomenon (FRP) and low back reflexes (LBR). Theoretically, these two outcome measures should be correlated; however, no studies have investigated this. This study aims to determine whether 30 min of near-maximal spine flexion will affect the onset of FRP and LBR in the lumbar erector spinae (LS) and lumbar multifidus (LM), and to examine the relation between these parameters. 15 participants were recruited (9F, 6M). Spine angle (between L1 and S2) was monitored synchronously with bilateral muscle activity in the LS (L1) and the LM (L4). FRP onset and LBR were measured in a randomized order before and after 30 min of slouched sitting. No significant difference was found for any muscle LBR onset time between pre and post-sitting (p > 0.05). A significant increase in FRP onset was found in the RLM (p = 0.016) following sitting. No significant correlation was found between the FRP and the LBR for any muscle. These results suggest that the LBR onset might not be as sensitive as an outcome measure to investigate shorter exposures of sitting as FRP.

57. clinical Characteristics and Outcomes of Patients Hospitalized with COVID-19 in New Orleans, LA: A Cohort Study

Background

In Louisiana, deaths related to COVID-19 have disproportionately occurred in Black persons. Granular data are needed to better understand inequities and develop prevention strategies to mitigate further impact on Black communities.

Methods

We conducted a retrospective cohort study of patients admitted to an urban safety net hospital in New Orleans, LA with reactive SARS-CoV-2 testing from March 9–31, 2020. Clinical characteristics and outcomes of Black and other racial/ethnic group patients were compared using Wilcoxon rank-sum test and Fisher’s exact tests. We examined Day-14 status using an ordinal scale to assess race and outcome.

Table 1. Demographics and Comorbidities by Race for Patients Hospitalized with COVID-19

Results

This study included 249 patients. Median age was 59, 44% were male, 86% were age ≥65 years or had ≥1 comorbidity. Overall, 87% were Black, relative to 55% Black patients typically hospitalized at our center. Black patients had longer symptom duration at presentation (6.41 versus 5.88 days, p=0.05), and were more likely to have asthma (p=0.008), but less likely to have dementia (p=0.002). There were no racial differences in initial respiratory status or laboratory values other than higher initial LDH in Black patients. Patient age and initial oxygen requirement, but not race (adjusted proportional odds ratio = 0.92, 95%CI: 0.70–1.20), were associated with worse Day-14 outcomes.

Figure 1: Admissions over time by Race

Conclusion

Our results demonstrate minor racial differences in comorbidities or disease severity at presentation, and Day-14 outcomes were not different between groups. However, Black patients were disproportionately represented in hospitalizations, suggesting that prevention efforts should include strategies to limit SARS-CoV-2 exposures in Black communities as one step towards reducing racial inequities related to COVID-19.

Figure 3a: Logistic Regression for Initial Oxygen Requirement

Disclosures

Meredith E. Clement, MD, FHI360 (Consultant)Gilead (Research Grant or Support)Janssen (Scientific Research Study Investigator)

Neural Correlates of Adolescent Irritability and Its Comorbidity With Psychiatric Disorders

OBJECTIVE

Irritable mood, a common and impairing symptom in psychopathology, has been proposed to underlie the developmental link between oppositional problems in youth and depression in adulthood. We examined the neural correlates of adolescent irritability in IMAGEN, a sample of 2,024 14-year-old adolescents from 5 European countries.

METHOD

The Development and Well-Being Assessment (DAWBA) was used to assess attention-deficit/hyperactivity disorder, major depressive disorder, oppositional defiant disorder, and generalized anxiety disorder. Three items from the DAWBA, selected as close matches to the Affective Reactivity Index, were used to assess irritability. Structural magnetic resonance imaging was examined using whole-brain voxel-based morphometry analysis, and functional magnetic resonance imaging was examined during a stop signal task of inhibitory control. Imaging data were included in structural equation models to examine the direct and indirect associations between irritable mood and comorbid DSM diagnoses.

RESULTS

Whole-brain voxelwise analysis showed that adolescent irritable mood was associated with less gray matter volume and less neural activation underlying inhibitory control in frontal and temporal cortical areas (cluster-correction at p < .05). Structural equation models suggested that part of the observed smaller gray matter volume was exclusively driven by irritability separate from direct relationships between generalized anxiety disorder (or attention-deficit/hyperactivity disorder, major depressive disorder, or oppositional defiant disorder) and gray matter volume.

CONCLUSION

This study identifies adolescent irritability as an independent construct and points to a neurobiological correlate to irritability that is an important contributing feature to many psychopathological disorders.

Subcortical surface morphometry in substance dependence: An ENIGMA addiction working group study

While imaging studies have demonstrated volumetric differences in subcortical structures associated with dependence on various abused substances, findings to date have not been wholly consistent. Moreover, most studies have not compared brain morphology across those dependent on different substances of abuse to identify substance-specific and substance-general dependence effects. By pooling large multinational datasets from 33 imaging sites, this study examined subcortical surface morphology in 1628 nondependent controls and 2277 individuals with dependence on alcohol, nicotine, cocaine, methamphetamine, and/or cannabis. Subcortical structures were defined by FreeSurfer segmentation and converted to a mesh surface to extract two vertex-level metrics-the radial distance (RD) of the structure surface from a medial curve and the log of the Jacobian determinant (JD)-that, respectively, describe local thickness and surface area dilation/contraction. Mega-analyses were performed on measures of RD and JD to test for the main effect of substance dependence, controlling for age, sex, intracranial volume, and imaging site. Widespread differences between dependent users and nondependent controls were found across subcortical structures, driven primarily by users dependent on alcohol. Alcohol dependence was associated with localized lower RD and JD across most structures, with the strongest effects in the hippocampus, thalamus, putamen, and amygdala. Meanwhile, nicotine use was associated with greater RD and JD relative to nonsmokers in multiple regions, with the strongest effects in the bilateral hippocampus and right nucleus accumbens. By demonstrating subcortical morphological differences unique to alcohol and nicotine use, rather than dependence across all substances, results suggest substance-specific relationships with subcortical brain structures.

Predicting alcohol dependence from multi-site brain 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.

Critically Ill Adults With Coronavirus Disease 2019 in New Orleans and Care With an Evidence-Based Protocol

Background

Characteristics of critically ill adults with coronavirus disease 2019 (COVID-19) in an academic safety net hospital and the effect of evidence-based practices in these patients are unknown.

Research Question

What are the outcomes of critically ill adults with COVID-19 admitted to a network of hospitals in New Orleans, Louisiana, and what is an evidence-based protocol for care associated with improved outcomes?

Study Design and Methods

In this multi-center, retrospective, observational cohort study of ICUs in four hospitals in New Orleans, Louisiana, we collected data on adults admitted to an ICU and tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between March 9, 2020 and April 14, 2020. The exposure of interest was admission to an ICU that implemented an evidence-based protocol for COVID-19 care. The primary outcome was ventilator-free days.

Results

The initial 147 patients admitted to any ICU and tested positive for SARS-CoV-2 constituted the cohort for this study. In the entire network, exposure to an evidence-based protocol was associated with more ventilator-free days (25 days; 0-28) compared with non-protocolized ICUs (0 days; 0-23, P = .005), including in adjusted analyses (P = .02). Twenty patients (37%) admitted to protocolized ICUs died compared with 51 (56%; P = .02) in non-protocolized ICUs. Among 82 patients admitted to the academic safety net hospital’s ICUs, the median number of ventilator-free days was 22 (interquartile range, 0-27) and mortality rate was 39%.

Interpretation

Care of critically ill COVID-19 patients with an evidence-based protocol is associated with increased time alive and free of invasive mechanical ventilation. In-hospital survival occurred in most critically ill adults with COVID-19 admitted to an academic safety net hospital’s ICUs despite a high rate of comorbidities.

Realization of an intrinsic ferromagnetic topological state in MnBi8Te13

Novel magnetic topological materials pave the way for studying the interplay between band topology and magnetism. However, an intrinsically ferromagnetic topological material with only topological bands at the charge neutrality energy has so far remained elusive. Using rational design, we synthesized MnBi8Te13, a natural heterostructure with [MnBi2Te4] and [Bi2Te3] layers. Thermodynamic, transport, and neutron diffraction measurements show that despite the adjacent [MnBi2Te4] being 44.1 Å apart, MnBi8Te13 manifests long-range ferromagnetism below 10.5 K with strong coupling between magnetism and charge carriers. First-principles calculations and angle-resolved photoemission spectroscopy measurements reveal it is an axion insulator with sizable surface hybridization gaps. Our calculations further demonstrate the hybridization gap persists in the two-dimensional limit with a nontrivial Chern number. Therefore, as an intrinsic ferromagnetic axion insulator with clean low-energy band structures, MnBi8Te13 serves as an ideal system to investigate rich emergent phenomena, including the quantized anomalous Hall effect and quantized magnetoelectric effect.

Ventromedial Prefrontal Volume in Adolescence Predicts Hyperactive/Inattentive Symptoms in Adulthood

Youths with attention-deficit/hyperactivity disorder symptomatology often exhibit residual inattention and/or hyperactivity in adulthood; however, this is not true for all individuals. We recently reported that dimensional, multi-informant ratings of hyperactive/inattentive symptoms are associated with ventromedial prefrontal cortex (vmPFC) structure. Herein, we investigate the degree to which vmPFC structure during adolescence predicts hyperactive/inattentive symptomatology at 5-year follow-up. Structural equation modeling was used to test the extent to which adolescent vmPFC volume predicts hyperactive/inattentive symptomatology 5 years later in early adulthood. 1104 participants (M = 14.52 years, standard deviation = 0.42; 583 females) possessed hyperactive/inattentive symptom data at 5-year follow-up, as well as quality controlled neuroimaging data and complete psychometric data at baseline. Self-reports of hyperactive/inattentive symptomatology were obtained during adolescence and at 5-year follow-up using the Strengths and Difficulties Questionnaire (SDQ). At baseline and 5-year follow-up, a hyperactive/inattentive latent variable was derived from items on the SDQ. Baseline vmPFC volume predicted adult hyperactive/inattentive symptomatology (standardized coefficient = -0.274, P < 0.001) while controlling for baseline hyperactive/inattentive symptomatology. These results are the first to reveal relations between adolescent brain structure and adult hyperactive/inattentive symptomatology, and suggest that early structural development of the vmPFC may be consequential for the subsequent expression of hyperactive/inattentive symptoms.

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

Associations Among Body Mass Index, Cortical Thickness, and Executive Function in Children

IMPORTANCE

A total of 25.7 million children in the United States are classified as overweight or obese. Obesity is associated with deficits in executive function, which may contribute to poor dietary decision-making. Less is known about the associations between being overweight or obese and brain development.

OBJECTIVE

To examine whether body mass index (BMI) is associated with thickness of the cerebral cortex and whether cortical thickness mediates the association between BMI and executive function in children.

DESIGN, SETTING, AND PARTICIPANTS

In this cross-sectional study, cortical thickness maps were derived from T1-weighted structural magnetic resonance images of a large, diverse sample of 9 and 10-year-old children from 21 US sites. List sorting, flanker, matrix reasoning, and Wisconsin card sorting tasks were used to assess executive function.

MAIN OUTCOMES AND MEASURES

A 10-fold nested cross-validation general linear model was used to assess mean cortical thickness from BMI across cortical brain regions. Associations between BMI and executive function were explored with Pearson partial correlations. Mediation analysis examined whether mean prefrontal cortex thickness mediated the association between BMI and executive function.

RESULTS

Among 3190 individuals (mean [SD] age, 10.0 [0.61] years; 1627 [51.0%] male), those with higher BMI exhibited lower cortical thickness. Eighteen cortical regions were significantly inversely associated with BMI. The greatest correlations were observed in the prefrontal cortex. The BMI was inversely correlated with dimensional card sorting (r = -0.088, P < .001), list sorting (r = -0.061, P < .003), and matrix reasoning (r = -0.095, P < .001) but not the flanker task. Mean prefrontal cortex thickness mediated the association between BMI and list sorting (mean [SE] indirect effect, 0.014 [0.008]; 95% CI, 0.001-0.031) but not the matrix reasoning or card sorting task.

CONCLUSIONS AND RELEVANCE

These results suggest that BMI is associated with prefrontal cortex development and diminished executive functions, such as working memory.

Neuroimaging Evidence for Right Orbitofrontal Cortex Differences in Adolescents With Emotional and Behavioral Dysregulation

OBJECTIVE

To characterize the structural and functional neurobiology of a large group of adolescents exhibiting a behaviorally and emotionally dysregulated phenotype.

METHOD

Adolescents aged 14 years from the IMAGEN study were investigated. Latent class analysis (LCA) on the Strengths and Difficulties Questionnaire (SDQ) was used to identify a class of individuals with elevated behavioral and emotional difficulties ("dysregulated"; n = 233) who were compared to a matched sample from a low symptom class (controls, n = 233). Whole-brain gray matter volume (GMV) images were compared using a general linear model with 10,000 random label permutations. Regional GMV findings were then probed for functional differences from three functional magnetic resonance imaging (fMRI) tasks. Significant brain features then informed mediation path models linking the likelihood of psychiatric disorders (DSM-IV) with dysregulation.

RESULTS

Whole-brain differences were found in the right orbitofrontal cortex (R.OFC; p < .05; k = 48), with dysregulated individuals exhibiting lower GMV. The dysregulated group also exhibited higher activity in this region during successful inhibitory control (F_1,429 = 7.53, p < .05). Path analyses indicated significant direct effects between the likelihood of psychopathologies and dysregulation. Modeling the R.OFC as a mediator returned modest partial effects, suggesting that the path linking the likelihood of an anxiety or conduct disorder diagnoses to dysregulation is partially explained by this anatomical feature.

CONCLUSION

A large sample of dysregulated adolescents exhibited lower GMV in the R.OFC relative to controls. Dysregulated individuals also exhibited higher regional activations when exercising inhibitory control at performance levels comparable to those of controls. These findings suggest a neurobiological marker of dysregulation and highlight the role of the R.OFC in impaired emotional and behavioral control.

Amygdalar reactivity is associated with prefrontal cortical thickness in a large population-based sample of adolescents

In structural neuroimaging studies, reduced cerebral cortical thickness in orbital and ventromedial prefrontal regions is frequently interpreted as reflecting an impaired ability to downregulate neuronal activity in the amygdalae. Unfortunately, little research has been conducted in order to test this conjecture. We examine the extent to which amygdalar reactivity is associated with cortical thickness in a population-based sample of adolescents. Data were obtained from the IMAGEN study, which includes 2,223 adolescents. While undergoing functional neuroimaging, participants passively viewed video clips of a face that started from a neutral expression and progressively turned angry, or, instead, turned to a second neutral expression. Left and right amygdala ROIs were used to extract mean BOLD signal change for the angry minus neutral face contrast for all subjects. T1-weighted images were processed through the CIVET pipeline (version 2.1.0). In variable-centered analyses, local cortical thickness was regressed against amygdalar reactivity using first and second-order linear models. In a follow-up person-centered analysis, we defined a “high reactive” group of participants based on mean amygdalar BOLD signal change for the angry minus neutral face contrast. Between-group differences in cortical thickness were examined (“high reactive” versus all other participants). A significant association was revealed between the continuous measure of amygdalar reactivity and bilateral ventromedial prefrontal cortical thickness in a second-order linear model (p < 0.05, corrected). The “high reactive” group, in comparison to all other participants, possessed reduced cortical thickness in bilateral orbital and ventromedial prefrontal cortices, bilateral anterior temporal cortices, left caudal middle temporal gyrus, and the left inferior and middle frontal gyri (p < 0.05, corrected). Results are consistent with non-human primate studies, and provide empirical support for an association between reduced prefrontal cortical thickness and amygdalar reactivity. Future research will likely benefit from investigating the degree to which psychopathology qualifies relations between prefrontal cortical structure and amygdalar reactivity.

Low Smoking Exposure, the Adolescent Brain, and the Modulating Role of CHRNA5 Polymorphisms

BACKGROUND

Studying the neural consequences of tobacco smoking during adolescence, including those associated with early light use, may help expose the mechanisms that underlie the transition from initial use to nicotine dependence in adulthood. However, only a few studies in adolescents exist, and they include small samples. In addition, the neural mechanism, if one exists, that links nicotinic receptor genes to smoking behavior in adolescents is still unknown.

METHODS

Structural and diffusion tensor magnetic resonance imaging data were acquired from a large sample of 14-year-old adolescents who completed an extensive battery of neuropsychological, clinical, personality, and drug-use assessments. Additional assessments were conducted at 16 years of age.

RESULTS

Exposure to smoking in adolescents, even at low doses, is linked to volume changes in the ventromedial prefrontal cortex and to altered neuronal connectivity in the corpus callosum. The longitudinal analyses strongly suggest that these effects are not preexisting conditions in those who progress to smoking. There was a genetic contribution wherein the volume reduction effects were magnified in smokers who were carriers of the high-risk genotype of the alpha 5 nicotinic receptor subunit gene, rs16969968.

CONCLUSIONS

These findings give insight into a mechanism involving genes, brain structure, and connectivity underlying why some adolescents find nicotine especially addictive.

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.

Prevalence and Correlates of Loss of Control Eating among Adults Presenting for Methadone Maintenance Treatment

BACKGROUND

Research suggests that substance use disorders and disordered eating are often comorbid. In light of the ongoing opioid epidemic, the purpose of the current study was to understand the prevalence and health-related correlates of loss of control (LOC) eating in adults seeking methadone maintenance treatment primarily for addiction to heroin and/or painkillers.

METHODS

Participants were 447 adults surveyed at presentation for methadone maintenance treatment who responded to survey items on LOC eating. Descriptive statistics were used to investigate the prevalence of engaging in LOC eating in the past 2 weeks. Chi-square tests, t tests, and analyses of covariance were used to compare individuals with (LOC+; n = 164) and without (LOC-; n = 283) recent LOC eating on psychosocial, pain-related, and weight-related characteristics.

RESULTS

Approximately one third of respondents endorsed LOC eating in the past 2 weeks. These participants reported greater affective symptoms, interpersonal dysfunction, pain intensity, and pain interference than the LOC- group (Cohen's d effect size range = .24-.94). LOC+ was also more likely to have engaged in recent illicit drug use and to report having concurrent overweight/obesity (φ effect size range = .09-.10).

CONCLUSION

The prevalence of LOC eating in adults seeking methadone maintenance treatment was more than triple what has been reported in previous studies using community samples. Given its associations with other health-related variables, the presence of LOC eating may be a marker for more severe psychopathology in individuals seeking methadone maintenance treatment. Future research is needed to understand mechanisms explaining this comorbidity and to develop novel ways to prevent and treat their co-occurrence.

The initiation of cannabis use in adolescence is predicted by sex-specific psychosocial and neurobiological features

Cannabis use initiated during adolescence might precipitate negative consequences in adulthood. Thus, predicting adolescent cannabis use prior to any exposure will inform the aetiology of substance abuse by disentangling predictors from consequences of use. In this prediction study, data were drawn from the IMAGEN sample, a longitudinal study of adolescence. All selected participants (n = 1,581) were cannabis-naïve at age 14. Those reporting any cannabis use (out of six ordinal use levels) by age 16 were included in the outcome group (N = 365, males n = 207). Cannabis-naïve participants at age 14 and 16 were included in the comparison group (N = 1,216, males n = 538). Psychosocial, brain and genetic features were measured at age 14 prior to any exposure. Cross-validated regularized logistic regressions for each use level by sex were used to perform feature selection and obtain prediction error statistics on independent observations. Predictors were probed for sex- and drug-specificity using post-hoc logistic regressions. Models reliably predicted use as indicated by satisfactory prediction error statistics, and contained psychosocial features common to both sexes. However, males and females exhibited distinct brain predictors that failed to predict use in the opposite sex or predict binge drinking in independent samples of same-sex participants. Collapsed across sex, genetic variation on catecholamine and opioid receptors marginally predicted use. Using machine learning techniques applied to a large multimodal dataset, we identified a risk profile containing psychosocial and sex-specific brain prognostic markers, which were likely to precede and influence cannabis initiation.

Inattention and Reaction Time Variability Are Linked to Ventromedial Prefrontal Volume in Adolescents

BACKGROUND

Neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) have most commonly reported volumetric abnormalities in the basal ganglia, cerebellum, and prefrontal cortices. Few studies have examined the relationship between ADHD symptomatology and brain structure in population-based samples. We investigated the relationship between dimensional measures of ADHD symptomatology, brain structure, and reaction time variability-an index of lapses in attention. We also tested for associations between brain structural correlates of ADHD symptomatology and maps of dopaminergic gene expression.

METHODS

Psychopathology and imaging data were available for 1538 youths. Parent ratings of ADHD symptoms were obtained using the Development and Well-Being Assessment and the Strengths and Difficulties Questionnaire (SDQ). Self-reports of ADHD symptoms were assessed using the youth version of the SDQ. Reaction time variability was available in a subset of participants. For each measure, whole-brain voxelwise regressions with gray matter volume were calculated.

RESULTS

Parent ratings of ADHD symptoms (Development and Well-Being Assessment and SDQ), adolescent self-reports of ADHD symptoms on the SDQ, and reaction time variability were each negatively associated with gray matter volume in an overlapping region of the ventromedial prefrontal cortex. Maps of DRD1 and DRD2 gene expression were associated with brain structural correlates of ADHD symptomatology.

CONCLUSIONS

This is the first study to reveal relationships between ventromedial prefrontal cortex structure and multi-informant measures of ADHD symptoms in a large population-based sample of adolescents. Our results indicate that ventromedial prefrontal cortex structure is a biomarker for ADHD symptomatology. These findings extend previous research implicating the default mode network and dopaminergic dysfunction in ADHD.

Greater preference consistency during the Willingness-to-Pay task is related to higher resting state connectivity between the ventromedial prefrontal cortex and the ventral striatum

The significance of why a similar set of brain regions are associated with the default mode network and value-related neural processes remains to be clarified. Here, we examined i) whether brain regions exhibiting willingness-to-pay (WTP) task-related activity are intrinsically connected when the brain is at rest, ii) whether these regions overlap spatially with the default mode network, and iii) whether individual differences in choice behavior during the WTP task are reflected in functional brain connectivity at rest. Blood-oxygen-level dependent (BOLD) signal was measured by functional magnetic resonance imaging while subjects performed the WTP task and at rest with eyes open. Brain regions that tracked the value of bids during the WTP task were used as seed regions in an analysis of functional connectivity in the resting state data. The seed in the ventromedial prefrontal cortex was functionally connected to core regions of the WTP task-related network. Brain regions within the WTP task-related network, namely the ventral precuneus, ventromedial prefrontal and posterior cingulate cortex overlapped spatially with publically available maps of the default mode network. Also, those individuals with higher functional connectivity during rest between the ventromedial prefrontal cortex and the ventral striatum showed greater preference consistency during the WTP task. Thus, WTP task-related regions are an intrinsic network of the brain that corresponds spatially with the default mode network, and individual differences in functional connectivity within the WTP network at rest may reveal a priori biases in choice behavior.

Brain Regions Related to Impulsivity Mediate the Effects of Early Adversity on Antisocial Behavior

BACKGROUND

Individual differences in impulsivity and early adversity are known to be strong predictors of adolescent antisocial behavior. However, the neurobiological bases of impulsivity and their relation to antisocial behavior and adversity are poorly understood.

METHODS

Impulsivity was estimated with a temporal discounting task. Voxel-based morphometry was used to determine the brain structural correlates of temporal discounting in a large cohort (n = 1830) of 14- to 15-year-old children. Mediation analysis was then used to determine whether the volumes of brain regions associated with temporal discounting mediate the relation between adverse life events (e.g., family conflict, serious accidents) and antisocial behaviors (e.g., precocious sexual activity, bullying, illicit substance use).

RESULTS

Greater temporal discounting (more impulsivity) was associated with 1) lower volume in frontomedial cortex and bilateral insula and 2) greater volume in a subcortical region encompassing the ventral striatum, hypothalamus and anterior thalamus. The volume ratio between these cortical and subcortical regions was found to partially mediate the relation between adverse life events and antisocial behavior.

CONCLUSIONS

Temporal discounting is related to regions of the brain involved in reward processing and interoception. The results support a developmental imbalance model of impulsivity and are consistent with the idea that negative environmental factors can alter the developing brain in ways that promote antisocial behavior.