Predictive Modeling of Adolescent Cannabis Use From Multimodal Data

Predicting teenage drug use is key to understanding the etiology of substance abuse. However, classic predictive modeling procedures are prone to overfitting and fail to generalize to independent observations. To mitigate these concerns, cross-validated logistic regression with elastic-net regularization was used to predict cannabis use by age 16 from a large sample of fourteen year olds (N=1,319). High-dimensional data (p = 2,413) including parent and child psychometric data, child structural and functional MRI data, and genetic data (candidate single-nucleotide polymorphisms, SNPs ) collected at age 14 were used to predict the initiation of cannabis use (minimum six occasions) by age 16. Analyses were conducted separately for males and females to uncover sex-specific predictive profiles. The performance of the predictive models were assessed using the area under the receiver-operating characteristic curve ( ROC AUC ). Final models returned high predictive performance (generalization mean ROC AUCmales=.71, mean ROC AUCfemales=.81) and contained psychometric features common to both sexes. These common psychometric predictors included greater stressful life events, novelty-seeking personality traits of both the parent and child, and parental cannabis use. In contrast, males exhibited distinct functional neurobiological predictors related to a response- inhibition fMRI task, whereas females exhibited distinct neurobiological predictors related to a social processing fMRI task. Furthermore, the brain predictors exhibited sex- specific effects as the brain predictors of cannabis use for one sex failed to predict cannabis use for the opposite sex. These sex-specific brain predictors also exhibited drug- specific effects as they failed to predict binge-drinking by age 16 in an independent sample of youths. When collapsed across sex, a gene-specific analysis suggested that opioid receptor genetic variation also predicted cannabis use by age 16. Two SNPs on the gene coding for the primary mu-opioid receptor exhibited genetic risk effects, while one SNP on the gene coding for the primary delta-opioid receptor exhibited genetic protective effects. Taken together, these results demonstrate that adolescent cannabis use is reliably predicted in males and females from shared and unique biobehavioral features. These analyses also underscore the need for refined predictive modeling procedures as well as sex-specific inquiries into the etiology of substance abuse. The sex-specific risk-profiles uncovered from these analyses might inform potential etiological mechanisms contributing to substance abuse in adolescence as all predictors were measured prior to the onset of cannabis use

Biobehavioral Predictors Of Cannabis Use In Adolescence

Cannabis use initiated during adolescence may precipitate lasting consequences on the brain and behavioral health of the individual. However, research on the risk factors for cannabis use during adolescence has been largely cross-sectional in design. Despite the few prospective studies, even less is known about the neurobiological predictors. This dissertation improves on the extant literature by leveraging a large longitudinal study to uncover the predictors of cannabis use in adolescent samples collected prior to exposure. All data were drawn from the IMAGEN study and contained a large sample of adolescents studied at age 14 (N=2,224), and followed up at age 16 and 19. Participants were richly characterized using psychosocial questionnaires, structural and functional MRI, and genetic measurements. Two hypothesis-driven studies focused on amygdala reactivity and two data-driven studies across the feature domains were completed to characterize cannabis use in adolescence. The first study was cross-sectional and identified bilateral amygdala hyperactivity to angry faces in a sample reporting cannabis use by age 14 (n=70). The second study determined this amygdala effect was predictive of cannabis use by studying a sample of cannabis-naïve participants at age 14 who then used cannabis by age 19 (n=525). A dose-response relationship was observed such that heavy cannabis users exhibited higher amygdala reactivity. Exploratory analyses suggested amygdala reactivity decreased from age 14 to 19 within the cannabis sample, although statistical significance was not found. In the third study, data-driven machine learning analyses predicted cannabis initiation by age 16 separately for males (n=207) and females (n=158) using data from all feature domains. These analyses identified a sparse set of shared psychosocial predictors, whereas the identified brain predictors exhibited sex- and drug-specificity. Additional analyses predicted initiation by age 19 and identified a sparse set of psychosocial predictors for females only (n=145). The final study improved on drug-specificity by performing differential prediction analyses between matched samples of participants who initiated cannabis+binge drinking vs. binge drinking only by age 16 (males n=178; females n=148). A sparse subset of psychosocial predictors identified in the third study was reproduced, and novel brain predictors were identified. Those analyses were unique as they compared two machine learning algorithms, namely regularized logistic regression and random forest analyses. These studies substantiated the use of both hypothesis- and data-driven prediction analyses applied to large longitudinal datasets. They also addressed common issues related to human addiction research by examining sex-differences and drug-specificity. Critically, these studies uncovered predictors of use in samples collected prior to cannabis-exposure. The identified predictors are therefore disentangled from consequences of use. Results from all studies inform etiological mechanisms influencing cannabis use in adolescence. These findings can also be used to stratify risk in vulnerable adolescents and inform targets for interventions designed to curb use

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

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

Functional connectivity evidence of cortico-cortico inhibition in temporal lobe epilepsy.

Epileptic seizures can initiate a neural circuit and lead to aberrant neural communication with brain areas outside the epileptogenic region. We focus on interictal activity in focal temporal lobe epilepsy and evaluate functional connectivity (FC) differences that emerge as function of bilateral versus strictly unilateral epileptiform activity. We assess the strength of FC at rest between the ictal and non-ictal temporal lobes, in addition to whole brain connectivity with the ictal temporal lobe. Results revealed strong connectivity between the temporal lobes for both patient groups, but this did not vary as a function of unilateral versus bilateral interictal status. Both the left and right unilateral temporal lobe groups showed significant anti-correlated activity in regions outside the epileptogenic temporal lobe, primarily involving the contralateral (non-ictal/non-pathologic) hemisphere, with precuneus involvement prominent. The bilateral groups did not show this contralateral anti-correlated activity. This anti-correlated connectivity may represent a form of protective and adaptive inhibition, helping to constrain epileptiform activity to the pathologic temporal lobe. The absence of this activity in the bilateral groups may be indicative of flawed inhibitory mechanisms, helping to explain their more widespread epileptiform activity. Our data suggest that the location and build up of epilepsy networks in the brain are not truly random, and are not limited to the formation of strictly epileptogenic networks. Functional networks may develop to take advantage of the regulatory function of structures such as the precuneus to instantiate an anti-correlated network, generating protective cortico-cortico inhibition for the purpose of limiting seizure spread or epileptogenesis

Interrater Reliability of Functional Lumen Imaging Probe Panometry and High-Resolution Manometry for the Assessment of Esophageal Motility Disorders.

INTRODUCTION: High-resolution manometry (HRM) and functional lumen imaging probe (FLIP) are primary and/or complementary diagnostic tools for the evaluation of esophageal motility. We aimed to assess the interrater agreement and accuracy of HRM and FLIP interpretations. METHODS: Esophageal motility specialists from multiple institutions completed the interpretation of 40 consecutive HRM and 40 FLIP studies. Interrater agreement was assessed using intraclass correlation coefficient (ICC) for continuous variables and Fleiss κ statistics for nominal variables. Accuracies of rater interpretation were assessed using the consensus of 3 experienced raters as the reference standard. RESULTS: Fifteen raters completed the HRM and FLIP studies. An excellent interrater agreement was seen in supine median integral relaxation pressure (ICC 0.96, 95% confidence interval 0.95-0.98), and a good agreement was seen with the assessment of esophagogastric junction (EGJ) outflow, peristalsis, and assignment of a Chicago Classification version 4.0 diagnosis using HRM (κ = 0.71, 0.75, and 0.70, respectively). An excellent interrater agreement for EGJ distensibility index and maximum diameter (0.91 [0.90-0.94], 0.92 [0.89-0.95]) was seen, and a moderate-to-good agreement was seen in the assignment of EGJ opening classification, contractile response pattern, and motility classification (κ = 0.68, 0.56, and 0.59, respectively) on FLIP. Rater accuracy for Chicago Classification version 4.0 diagnosis on HRM was 82% (95% confidence interval 78%-84%) and for motility diagnosis on FLIP Panometry was 78% (95% confidence interval 72%-81%). DISCUSSION: Our study demonstrates high levels of interrater agreement and accuracy in the interpretation of HRM and FLIP metrics and moderate-to-high levels for motility classification in FLIP, supporting the use of these approaches for primary or complementary evaluation of esophageal motility disorders

Examination of the neural basis of psychotic-like experiences in adolescence during processing of emotional faces

Contemporary theories propose that dysregulation of emotional perception is involved in the aetiology of psychosis. 298 healthy adolescents were assessed at age 14- and 19-years using fMRI while performing a facial emotion task. Psychotic-like experiences (PLEs) were assessed with the CAPE-42 questionnaire at age 19. The high PLEs group at age 19 years exhibited an enhanced response in right insular cortex and decreased response in right prefrontal, right parahippocampal and left striatal regions; also, a gradient of decreasing response to emotional faces with age, from 14 to 19 years, in the right parahippocampal region and left insular cortical area. The right insula demonstrated an increasing response to emotional faces with increasing age in the low PLEs group, and a decreasing response over time in the high PLEs group. The change in parahippocampal/amygdala and insula responses during the perception of emotional faces in adolescents with high PLEs between the ages of 14 and 19 suggests a potential ‘aberrant’ neurodevelopmental trajectory for critical limbic areas. Our findings emphasize the role of the frontal and limbic areas in the aetiology of psychotic symptoms, in subjects without the illness phenotype and the confounds introduced by antipsychotic medication

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. 1,104 participants (M = 14.52 yrs, SD = 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 = -.274, p < .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

Evidence of amygdala hypersensitivity to signals of threat

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

Low smoking-exposure, the adolescent brain, and the modulating role of CHRNA5 polymorphisms

© 2019 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

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