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BackgroundThough largely substance-naïve at enrollment, a proportion of the youth in the Adolescent Brain Cognitive Development (ABCD) Study are expected to initiate substance use (SU) as they transition into later adolescence. With annual data from youth 9-13 years-old, this study aims to describe their SU patterns over time. Here, prevalence rates of use are reported, along with predicted odds of use while analyzing common risk-factors associated with youth SU.MethodsThe ABCD Study® enrolled 11,876 participants at Baseline (ages 9-10) and has followed them annually. Data through half of the third follow-up visit are available (ages 12-13; n = 6,251). SU descriptives for al psychoactive substances over time are outlined. General estimating equations (GEEs) assessed whether sociodemographic factors, internalizing and externalizing symptoms, and parental SU problems were associated with SU between Baseline and Y2 follow-up.ResultsAcross time, alcohol and nicotine remain the most used substances. Yearly rates of any SU increased (past year use: 13.9% in Y1; 14% Y2, 18.4% Y3). Cumulatively, by Y3, 39.7% of the cohort reported experimenting (e.g., sipping alcohol) with SU within their lifetime, while 7.4% reported a "full use" (a full alcohol drink, nicotine use, cannabis use, or any other SU) in their lifetime (past-year: 1.9% alcohol, 2.1% nicotine, 1.1% cannabis, 1.2% other substances). GEEs revealed ongoing longitudinal associations between sociodemographic factors, greater externalizing symptoms, and parental drug problems with increased odds of initiating SU.ConclusionsAs ABCD participants transition into their teenage years, the cohort is initiating SU at increasing (though still low) rates.

BackgroundAlthough a relatively large body of research has identified multiple factors associated with adolescent substance use, less is known about earlier substance-related factors during preadolescence, including curiosity to use substances. The present study examined individual-, peer-, and parent-level domains pertaining to substance use and how these domains vary by sociodemographic subgroups and substance type.MethodsParticipants were 11,864 9- and 10-year-olds from the baseline sample of the Adolescent Brain Cognitive Development (ABCD) Study. Youth-reported measures were curiosity to use substances and perceived peer substance use. Parent-reported measures were availability of and rules about substances. Generalized logistic mixed models (GLMM) were used to compare these measures across alcohol, nicotine, and marijuana and across sociodemographic subgroupings (sex, race/ethnicity, household income, and family history of alcohol problems). GLMM was then used to examine predictors of curiosity to use by substance type.ResultsThe most striking descriptive differences were found between race/ethnicity and income categories (e.g., positive associations between greater income and greater availability of alcohol). In multivariable analyses, greater curiosity to use alcohol was associated with being male, higher household income, perceived peer alcohol use, and easy alcohol availability; greater curiosity to use nicotine was associated with being male, perceived peer cigarette use, easy availability of cigarettes, and no parental rules about cigarette use.ConclusionsThis study identified substance use-related individual-, peer-, and parent-level factors among a diverse, national sample. Findings highlight the importance of considering sociodemographic and substance-specific variability and may help identify risk and protective factors preceding adolescent substance use.

Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2-100) and used normative modeling to characterize lifespan trajectories of cortical thickness and subcortical volume. Models are validated against a manually quality checked subset (N=24,354) and we provide an interface for transferring to new data sources. We showcase the clinical value by applying the models to a transdiagnostic psychiatric sample (N=1985), showing they can be used to quantify variability underlying multiple disorders whilst also refining case-control inferences. These models will be augmented with additional samples and imaging modalities as they become available. This provides a common reference platform to bind results from different studies and ultimately paves the way for personalized clinical decision-making.

Prior research has shown that sipping of alcohol begins to emerge during childhood and is potentially etiologically significant for later substance use problems. Using a large, community sample of 9- and 10-year-olds (N = 11,872; 53% female), we examined individual differences in precocious alcohol use in the form of alcohol sipping. We focused explicitly on features that are robust and well-demonstrated correlates of, and antecedents to, alcohol excess and related problems later in the lifespan, including youth- and parent-reported externalizing traits (i.e., impulsivity, behavioral inhibition and activation) and psychopathology. Seventeen percent of the sample reported sipping alcohol outside of a religiously sanctioned activity by age 9 or 10. Several aspects of psychopathology and personality emerged as small but reliable correlates of sipping. Nonreligious sipping was related to youth-reported impulsigenic traits, aspects of behavioral activation, prodromal psychotic-like symptoms, and mood disorder diagnoses, as well as parent-reported externalizing disorder diagnoses. Religious sipping was unexpectedly associated with certain aspects of impulsivity. Together, our findings point to the potential importance of impulsivity and other transdiagnostic indicators of psychopathology (e.g., emotion dysregulation, novelty seeking) in the earliest forms of drinking behavior.

AimTo examine individual variability between perceived physical features and hormones of pubertal maturation in 9-10-year-old children as a function of sociodemographic characteristics.MethodsCross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study-a multi-site sample of 9-10 year-olds (n = 11,875)-and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels.ResultsPDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child's weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample.ConclusionsSociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9-10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes.

AimTo examine individual variability between perceived physical features and hormones of pubertal maturation in 9-10-year-old children as a function of sociodemographic characteristics.MethodsCross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study-a multi-site sample of 9-10 year-olds (n = 11,875)-and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels.ResultsPDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child's weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample.ConclusionsSociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9-10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes.

The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.

ObjectiveAlthough 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.MethodBrain 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.ResultsLower 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.ConclusionsThe 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.

The ABCD study is recruiting and following the brain development and health of over 10,000 9-10 year olds through adolescence. The imaging component of the study was developed by the ABCD Data Analysis and Informatics Center (DAIC) and the ABCD Imaging Acquisition Workgroup. Imaging methods and assessments were selected, optimized and harmonized across all 21 sites to measure brain structure and function relevant to adolescent development and addiction. This article provides an overview of the imaging procedures of the ABCD study, the basis for their selection and preliminary quality assurance and results that provide evidence for the feasibility and age-appropriateness of procedures and generalizability of findings to the existent literature.

Since the sample size of a typical neuroimaging study lacks sufficient statistical power to explore unknown genomic associations with brain phenotypes, several international genetic imaging consortia have been organized in recent years to pool data across sites. The challenges and achievements of these consortia are considered here with the goal of leveraging these resources to study addiction. The authors of this review have joined together to form an Addiction working group within the framework of the ENIGMA project, a meta-analytic approach to multisite genetic imaging data. Collectively, the Addiction working group possesses neuroimaging and genomic data obtained from over 10,000 subjects. The deadline for contributing data to the first round of analyses occurred at the beginning of May 2015. The studies performed on this data should significantly impact our understanding of the genetic and neurobiological basis of addiction.

Youth self-reports are a mainstay of delinquency assessment; however, making valid inferences about delinquency using these assessments requires equivalent measurement across groups of theoretical interest. We examined whether a brief 10-item delinquency measure exhibited measurement invariance across non-Hispanic White (n = 6,064) and Black (n = 1,666) youth (ages 10–11 years old) in the Adolescent Brain Cognitive Development sm Study (ABCD Study®). We detected differential item functioning (DIF) in two items. Black youth were more likely to report being arrested or picked up by police than White youth with the same score on the latent delinquency trait. Although multiple covariates (income, urgency, and callous–unemotional traits) reduced mean-level difference in overall delinquency, they were generally unrelated to the DIF in the Arrest item. However, the DIF in the Arrest item was reduced in size and no longer significant after adjusting for neighborhood safety. Results illustrate the importance of considering measurement invariance when using self-reported delinquency scores to draw inferences about group differences, and the utility of measurement invariance analyses for helping to identify mechanisms that contribute to group differences generally. [ABSTRACT FROM AUTHOR]