Lifetime residential history collection and processing for environmental data linkages in the ABCD study

By using geospatial information such as participants' residential history along with external datasets of environmental exposures, ongoing studies can enrich their cohorts to investigate the role of the environment on brain-behavior health outcomes. However, challenges may arise if clear guidance and key quality control steps are not taken at the outset of data collection of residential information. Here, we detail the protocol development aimed at improving the collection of lifetime residential address information from the Adolescent Brain Cognitive Development (ABCD) Study. This protocol generates a workflow for minimizing gaps in residential information, improving data collection processes, and reducing misclassification error in exposure estimates.

Longitudinal associations of screen time, physical activity, and sleep duration with body mass index in U.S. youth

BACKGROUND

Youth use different forms of screen time (e.g., streaming, gaming) that may be related to body mass index (BMI). Screen time is non-independent from other behaviors, including physical activity and sleep duration. Statistical approaches such as isotemporal substitution or compositional data analysis (CoDA) can model associations between these non-independent behaviors and health outcomes. Few studies have examined different types of screen time, physical activity, and sleep duration simultaneously in relation to BMI.

METHODS

Data were baseline (2017-2018) and one-year follow-up (2018-2019) from the Adolescent Brain Cognitive Development Study, a multi-site study of a nationally representative sample of U.S. youth (N = 10,544, mean [SE] baseline age = 9.9 [0.03] years, 48.9% female, 45.4% non-White). Participants reported daily minutes of screen time (streaming, gaming, socializing), physical activity, and sleep. Sex-stratified models estimated the association between baseline behaviors and follow-up BMI z-score, controlling for demographic characteristics, internalizing symptoms, and BMI z-score at baseline.

RESULTS

In females, isotemporal substitution models estimated that replacing 30 min of socializing (β [95% CI] = -0.03 [-0.05, -0.002]), streaming (-0.03 [-0.05, -0.01]), or gaming (-0.03 [-0.06, -0.01]) with 30 min of physical activity was associated with a lower follow-up BMI z-score. In males, replacing 30 min of socializing (-0.03 [-0.05, -0.01]), streaming (-0.02 [-0.03, -0.01]), or gaming (-0.02 [-0.03, -0.01]) with 30 min of sleep was associated with a lower follow-up BMI z-score. In males, replacing 30 min of socializing with 30 min of gaming was associated with a lower follow-up BMI z-score (-0.01 [-0.03, -0.0001]). CoDA estimated that in males, a greater proportion of time spent in baseline socializing, relative to the remaining behaviors, was associated with a higher follow-up BMI z-score (0.05 [0.02, 0.08]). In females, no associations between screen time and BMI were observed using CoDA.

CONCLUSIONS

One-year longitudinal associations between screen time and BMI may depend on form of screen time, what behavior it replaces (physical activity or sleep), and participant sex. The alternative statistical approaches yielded somewhat different results. Experimental manipulation of screen time and investigation of biopsychosocial mechanisms underlying the observed sex differences will allow for causal inference and can inform interventions.

Functional connectivity and complexity analyses of resting-state fMRI in pre-adolescents demonstrating the behavioral symptoms of ADHD

Attention deficit hyperactivity disorder (ADHD) has been characterized by impairments among distributed functional brain networks, e.g., the frontoparietal network (FPN), default mode network (DMN), reward and motivation-related circuits (RMN), and salience network (SAL). In the current study, we evaluated the complexity and functional connectivity (FC) of resting state fMRI (rsfMRI) in pre-adolescents with the behavioral symptoms of ADHD, for pathology-relevant networks. We leveraged data from the Adolescent Brain and Cognitive Development (ABCD) Study. The final study sample included 63 children demonstrating the behavioral features of ADHD and 92 healthy control children matched on age, sex, and pubertal development status. For selected regions in the relevant networks, ANCOVA compared multiscale entropy (MSE) and FC between the groups. Finally, differences in the association between MSE and FC were evaluated. We found significantly reduced MSE along with increased FC within the FPN of pre-adolescents demonstrating the behavior symptoms of ADHD compared to matched healthy controls. Significant partial correlations between MSE and FC emerged in the FPN and RMN in the healthy controls however the association was absent in the participants demonstrating the behavior symptoms of ADHD. The current findings of complexity and FC in ADHD pathology support hypotheses of altered function of inhibitory control networks in ADHD.

Multiple Discrimination and Substance Use Intention in Late Childhood: Findings From the Adolescent Brain Cognitive Development (ABCD) Study

PURPOSE

The study aimed to investigate longitudinal, bidirectional associations between discrimination due to multiple reasons (race/ethnicity, sexual orientation, weight; termed multiple discrimination) and substance use (SU) intention in late childhood. These associations were compared across youth with no, single, and multiple (i.e., intersecting) marginalized identities based on race/ethnicity, sexual orientation, and overweight status.

METHODS

Data were drawn from a national sample of youth in the Adolescent Brain Cognitive Development study (N = 8,530; 9-12 years old). Youth reported both their experiences of multiple discrimination (the number of forms of discrimination youth experienced) and SU intention at one-year and two-year follow-ups. Theoretically relevant covariates were included.

RESULTS

Compared to non-marginalized youth (n = 2,689) and youth with single marginalized identities (n = 3,399), youth with intersecting marginalized identities (n = 2,442) reported the highest SU intention and multiple discrimination across waves. Only for this last group, multiple discrimination predicted stronger SU intention subsequently (β = 0.07, 95% confidence interval [0.02, 0.11]), whereas stronger SU intention predicted lower levels of multiple discrimination over time (β = -0.06, 95% confidence interval [-0.09, -0.02]). Sensitivity analyses yielded similar patterns with some nuances among subgroups of youth with varying intersecting marginalized identities.

DISCUSSION

Multiple discrimination predicted stronger SU intention over time in late childhood, particularly among youth with intersecting marginalized identities. Policies and practices should consider addressing multiple discrimination to reduce SU disparities among diverse youth.

Genetic and brain similarity independently predict childhood anthropometrics and neighborhood socioeconomic conditions

Linking the developing brain with individual differences in clinical and demographic traits is challenging due to the substantial interindividual heterogeneity of brain anatomy and organization. Here we employ an integrative approach that parses individual differences in both cortical thickness and common genetic variants, and assess their effects on a wide set of childhood traits. The approach uses a linear mixed model framework to obtain the unique effects of each type of similarity, as well as their covariance. We employ this approach in a sample of 7760 unrelated children in the ABCD cohort baseline sample (mean age 9.9, 46.8% female). In general, associations between cortical thickness similarity and traits were limited to anthropometrics such as height, weight, and birth weight, as well as a marker of neighborhood socioeconomic conditions. Common genetic variants explained significant proportions of variance across nearly all included outcomes, although estimates were somewhat lower than previous reports. No significant covariance of the effects of genetic and cortical thickness similarity was found. The present findings highlight the connection between anthropometrics as well as neighborhood socioeconomic conditions and the developing brain, which appear to be independent from individual differences in common genetic variants in this population-based sample.

Can we diagnose mental disorders in children? A large-scale assessment of machine learning on structural neuroimaging of 6916 children in the adolescent brain cognitive development study

Background

Prediction of mental disorders based on neuroimaging is an emerging area of research with promising first results in adults. However, research on the unique demographic of children is underrepresented and it is doubtful whether findings obtained on adults can be transferred to children.

Methods

Using data from 6916 children aged 9-10 in the multicenter Adolescent Brain Cognitive Development study, we extracted 136 regional volume and thickness measures from structural magnetic resonance images to rigorously evaluate the capabilities of machine learning to predict 10 different psychiatric disorders: major depressive disorder, bipolar disorder (BD), psychotic symptoms, attention deficit hyperactivity disorder (ADHD), oppositional defiant disorder, conduct disorder, post-traumatic stress disorder, obsessive-compulsive disorder, generalized anxiety disorder, and social anxiety disorder. For each disorder, we performed cross-validation and assessed whether models discovered a true pattern in the data via permutation testing.

Results

Two of 10 disorders can be detected with statistical significance when using advanced models that (i) allow for non-linear relationships between neuroanatomy and disorder, (ii) model interdependencies between disorders, and (iii) avoid confounding due to sociodemographic factors: ADHD (AUROC = 0.567, p = 0.002) and BD (AUROC = 0.551, p = 0.002). In contrast, traditional models perform consistently worse and predict only ADHD with statistical significance (AUROC = 0.529, p = 0.002).

Conclusion

While the modest absolute classification performance does not warrant application in the clinic, our results provide empirical evidence that embracing and explicitly accounting for the complexities of mental disorders via advanced machine learning models can discover patterns that would remain hidden with traditional models.

Caffeinated Soda Intake in Children Is Associated with Neurobehavioral Risk Factors for Substance Misuse

BACKGROUND AND OBJECTIVES

Use of psychotropic substances in childhood has been associated with both impulsivity and other manifestations of poor executive function as well as escalation over time to use of progressively stronger substances. However, how this relationship may start in earlier childhood has not been well explored. Here, we investigated the neurobehavioral correlates of daily caffeinated soda consumption in preadolescent children and examined whether caffeinated soda intake is associated with a higher risk of subsequent alcohol initiation.

METHODS

Using Adolescent Brain Cognitive Development study data (N = 2,092), we first investigated cross-sectional relationships between frequent caffeinated soda intake and well-known risk factors of substance misuse: impaired working memory, high impulsivity, and aberrant reward processing. We then examined whether caffeinated soda intake at baseline predicts more alcohol sipping at 12 months follow-up using a machine learning algorithm.

RESULTS

Daily consumption of caffeinated soda was cross-sectionally associated with neurobehavioral risk factors for substance misuse such as higher impulsivity scores and lower working memory performance. Furthermore, caffeinated soda intake predicted a 2.04 times greater likelihood of alcohol sipping after 12 months, even after controlling for rates of baseline alcohol sipping rates.

CONCLUSIONS

These findings suggest that previous linkages between caffeine and substance use in adolescence also extend to younger initiation, and may stem from core neurocognitive features thought conducive to substance initiation.

Genetic and environmental influences on early-age susceptibility and initiation of nicotine-containing product use: A twin-pairs study

INTRODUCTION

Nicotine-containing products (NCPs) such as electronic nicotine delivery systems (ENDS) are increasingly common throughout the landscape of youth use of nicotine-containing products (NCP), and have overtaken traditional cigarette smoking modalities. This study seeks to examine the genetic and environmental influences on liability for susceptibility and initiation of ENDS and other NCPs among US children.

METHODS

Data were drawn from 886 monozygotic (MZ) and dizygotic (DZ) twin pairs aged 9-10 years in the Adolescent Brain & Cognitive Development (ABCD) study at the baseline during 2016-2018. Heritability (h2) measured the proportion of the total phenotypic variation attributable to genes. Variance component models were utilized to analyze influences from the common environment (c2) and unique environmental factors (e2), taking into account correlations within twin pairs.

RESULTS

The national sample included 50% females, 69.5% of non-Hispanic Whites, 12.8% of non-Hispanic Blacks, and 11.6% of Hispanics, with a mean age of 121.5 months. The twin sets were 60% DZ and 40% MZ. Heritability was low for NCP susceptibility (h2=0) and moderate for NCP initiation (h2=39%, p=0.02). The variance associated with NCP susceptibility was primarily influenced by environmental factors, especially one's unique factors (c2=37%, p<0.0001 vs e2=63%, p<0.0001). In contrast, the variance associated with NCP initiation was split across common and unique environmental factors (c2=32%, p=0.02 vs e2=29%, p=0.02).

CONCLUSIONS

In the era with ENDS use surging among youth, NCP initiation remains to be a heritable trait with joint influence from the environment. NCP susceptibility is largely influenced by environmental factors, especially unique environments. Continued assessment of gene × environment interaction can better inform future youth NCP interventions.

Acculturative Orientations Among Hispanic/Latinx Caregivers in the ABCD Study: Associations With Caregiver and Youth Mental Health and Youth Brain Function

Background

Population-based neuroscience offers opportunities to examine important but understudied sociocultural factors such as acculturation. Acculturation refers to the extent to which an individual retains their cultural heritage and/or adopts the receiving society's culture and is particularly salient among Hispanic/Latinx immigrants. Specific acculturative orientations have been linked to vulnerability to substance use, depression, and suicide and are known to influence family dynamics between caregivers and their children.

Methods

Using data from first- and second-generation Hispanic/Latinx caregivers in the Adolescent Brain Cognitive Development (ABCD) Study (N = 1057), we examined how caregivers' acculturative orientation affects their mental health, as well as the mental health and brain function of their children. Neuroimaging analyses focused on regions associated with self- and affiliation-based social processing (ventromedial prefrontal cortex, insula, and temporoparietal junction).

Results

We identified 2 profiles of caregiver acculturation: bicultural (retains heritage culture while adopting U.S. culture) and detached (discards heritage culture and rejects U.S. culture). Bicultural caregivers exhibited fewer internalizing and externalizing problems than detached caregivers; furthermore, youth exhibited similar internalizing effects across caregiver profiles. In addition, youth with bicultural caregivers displayed increased resting-state brain activity (i.e., fractional amplitude of low-frequency fluctuations and regional homogeneity) in the left insula, which has been linked to psychopathology; however, differences in long-range functional connectivity were not significant.

Conclusions

Caregiver acculturation is an important familial factor that has been linked to significant differences in youth mental health and insula activity. Future work should examine sociocultural and neurodevelopmental changes across adolescence to assess health outcomes and determine whether localized, corticolimbic brain effects are ultimately translated into long-range connectivity differences.

Functional Connectivity and Complexity Analyses of Resting-State fMRI in Pre-Adolescents with ADHD

Attention deficit hyperactivity disorder (ADHD) has been characterized by impairments among distributed functional brain networks, e.g., the frontoparietal network (FPN), default mode network (DMN), and reward and motivation-related circuits (RMN). In the current study, we evaluated the complexity and functional connectivity (FC) of resting state fMRI (rsfMRI) in pre-adolescents with ADHD for pathology-relevant networks. We leveraged data from the Adolescent Brain and Cognitive Development (ABCD) Study. The final study sample included 63 children with ADHD and 92 healthy control children matched on age, sex, and pubertal development status. For selected regions in relevant networks, ANCOVA compared multiscale entropy (MSE) and FC between the groups. Finally, differences in the association between MSE and FC were evaluated. We found significantly reduced MSE along with increased FC within the FPN of pre-adolescents with ADHD compared to matched healthy controls. Significant partial correlations between MSE and FC emerged in fewer regions in the participants with ADHD than in the controls. The observation of reduced entropy is consistent with existing literature using rsfMRI and other neuroimaging modalities. The current findings of complexity and FC in ADHD support hypotheses of altered function of inhibitory control networks in ADHD.

Neural responses to reward valence and magnitude from pre- to early adolescence

BACKGROUND

Neural activation during reward processing is thought to underlie critical behavioral changes that take place during the transition to adolescence (e.g., learning, risk-taking). Though literature on the neural basis of reward processing in adolescence is booming, important gaps remain. First, more information is needed regarding changes in functional neuroanatomy in early adolescence. Another gap is understanding whether sensitivity to different aspects of the incentive (e.g., magnitude and valence) changes during the transition into adolescence. We used fMRI from a large sample of preadolescent children to characterize neural responses to incentive valence vs. magnitude during anticipation and feedback, and their change over a period of two years.

METHODS

Data were taken from the Adolescent Cognitive and Brain DevelopmentSM (ABCD®) study release 3.0. Children completed the Monetary Incentive Delay task at baseline (ages 9-10) and year 2 follow-up (ages 11-12). Based on data from two sites (N = 491), we identified activation-based Regions of Interest (ROIs; e.g., striatum, prefrontal regions, etc.) that were sensitive to trial type (win $5, win $0.20, neutral, lose $0.20, lose $5) during anticipation and feedback phases. Then, in an independent subsample (N = 1470), we examined whether these ROIs were sensitive to valence and magnitude and whether that sensitivity changed over two years.

RESULTS

Our results show that most ROIs involved in reward processing (including the striatum, prefrontal cortex, and insula) are specialized, i.e., mainly sensitive to either incentive valence or magnitude, and this sensitivity was consistent over a 2-year period. The effect sizes of time and its interactions were significantly smaller (0.002≤η2≤0.02) than the effect size of trial type (0.06≤η2≤0.30). Interestingly, specialization was moderated by reward processing phase but was stable across development. Biological sex and pubertal status differences were few and inconsistent. Developmental changes were mostly evident during success feedback, where neural reactivity increased over time.

CONCLUSIONS

Our results suggest sub-specialization to valence vs. magnitude within many ROIs of the reward circuitry. Additionally, in line with theoretical models of adolescent development, our results suggest that the ability to benefit from success increases from pre- to early adolescence. These findings can inform educators and clinicians and facilitate empirical research of typical and atypical motivational behaviors during a critical time of development.

Psychiatric Diagnoses and Treatment in Nine- to Ten-Year-Old Participants in the ABCD Study

Objective

Psychiatric disorders commonly emerge prior to adulthood. Identification and intervention may vary significantly across populations. We leveraged a large population-based study to estimate the prevalence of psychiatric disorders and treatments, and evaluate predictors of treatment, in children ages 9-10 in the United States.

Method

We analyzed cross-sectional data from the Adolescent Brain Cognitive Developmental (ABCD) Study. The Computerized Kiddie Schedule for Affective Disorders and Schizophrenia (KSADS-COMP) was used to estimate clinical diagnoses, and the Child Behavior Checklist (CBCL) was used to assess internalizing and externalizing psychopathology. Parents reported on prescription medications and other mental health interventions. Prevalence rates of KSADS diagnoses and treatments were calculated. Logistic regression analyses estimated associations between clinical and sociodemographic predictors (sex at birth, race, ethnicity, income, education, urbanicity) and treatments.

Results

The most common KSADS diagnoses were anxiety disorders, followed by attention deficit/hyperactivity disorder (ADHD) and oppositional defiant disorder. ADHD and depression diagnoses predicted stimulant and antidepressant medication use, respectively. Bipolar and ADHD diagnoses also predicted antidepressant medications, outpatient treatment and psychotherapy. The odds of reporting specific treatments varied by sex, ethnic and racial identities, urbanicity, and income.

Conclusion

Expected rates of KSADS-based psychiatric symptoms are present in the ABCD sample at ages 9-10, with treatment patterns broadly mapping onto psychopathology in expected ways. However, we observed important variations in reported treatment utilization across sociodemographic groups, likely reflecting societal and cultural influences. Findings are considered in the context of potential mental health disparities in U.S. children.

Prevalence, predictors, and treatment of eating disorders in children: a national study

BACKGROUND

Although the prevalence rates of preadolescent eating disorders (EDs) are on the rise, considerably less is known about the correlates and treatment of EDs in this age group. Clarifying the epidemiology of EDs in preadolescent children is a necessary first step to understand the nature and scope of this problem in this age group.

METHODS

Analysis of data collected in the ABCD Study release 2.0.1. The ABCD cohort was a population-based sample that consisted of 11 721 children ages 9-10 years. Measures included reports of a lifetime and current mental disorders determined using a diagnostic interview for DSM-5 disorders, sociodemographic factors, and psychiatric treatment utilization.

RESULTS

The lifetime prevalence of EDs was 0.95%. Being Black, multiracial, having unmarried parents, and family economic insecurity were significant predictors for developing an ED. Among psychiatric conditions, the major depressive disorder was most robustly associated with EDs in both cross-sectional and temporal analyses. Only 47.40% of children who had a lifetime ED received some type of psychiatric treatment. EDs were not a significant predictor of psychiatric treatment utilization after accounting for sex, sexual orientation, parent marital status, economic insecurity, and all other psychiatric diagnoses.

CONCLUSIONS

Despite increasing prevalence rates of preadolescent EDs, the current findings suggest that the majority of children with these disorders remain untreated. Devoting increased attention and resources to reaching families of children with EDs with the least means for receiving care, and screening for EDs in children with depression, may be important steps for reducing this unmet need.

ABCD_Harmonizer: An Open-source Tool for Mapping and Controlling for Scanner Induced Variance in the Adolescent Brain Cognitive Development Study

Data from multisite magnetic resonance imaging (MRI) studies contain variance attributable to the scanner that can reduce statistical power and potentially bias results if not appropriately managed. The Adolescent Cognitive Brain Development (ABCD) study is an ongoing, longitudinal neuroimaging study acquiring data from over 11,000 children starting at 9-10 years of age. These scans are acquired on 29 different scanners of 5 different model types manufactured by 3 different vendors. Publicly available data from the ABCD study include structural MRI (sMRI) measures such as cortical thickness and diffusion MRI (dMRI) measures such as fractional anisotropy. In this work, we 1) quantify the variance attributable to scanner effects in the sMRI and dMRI datasets, 2) demonstrate the effectiveness of the data harmonization approach called ComBat to address scanner effects, and 3) present a simple, open-source tool for investigators to harmonize image features from the ABCD study. Scanner-induced variance was present in every image feature and varied in magnitude by feature type and brain location. For almost all features, scanner variance exceeded variability attributable to age and sex. ComBat harmonization was shown to effectively remove scanner induced variance from all image features while preserving the biological variability in the data. Moreover, we show that for studies examining relatively small subsamples of the ABCD dataset, the use of ComBat harmonized data provides more accurate estimates of effect sizes compared to controlling for scanner effects using ordinary least squares regression.

Substance use patterns in 9 to 13-year-olds: Longitudinal findings from the Adolescent Brain Cognitive Development (ABCD) study

Background

Though 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.

Methods

The 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.

Results

Across 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.

Conclusions

As ABCD participants transition into their teenage years, the cohort is initiating SU at increasing (though still low) rates.

Differentiated nomological networks of internalizing, externalizing, and the general factor of psychopathology ('p factor') in emerging adolescence in the ABCD study

BACKGROUND

Structural models of psychopathology consistently identify internalizing (INT) and externalizing (EXT) specific factors as well as a superordinate factor that captures their shared variance, the p factor. Questions remain, however, about the meaning of these data-driven dimensions and the interpretability and distinguishability of the larger nomological networks in which they are embedded.

METHODS

The sample consisted of 10 645 youth aged 9-10 years participating in the multisite Adolescent Brain and Cognitive Development (ABCD) Study. p, INT, and EXT were modeled using the parent-rated Child Behavior Checklist (CBCL). Patterns of associations were examined with variables drawn from diverse domains including demographics, psychopathology, temperament, family history of substance use and psychopathology, school and family environment, and cognitive ability, using instruments based on youth-, parent-, and teacher-report, and behavioral task performance.

RESULTS

p exhibited a broad pattern of statistically significant associations with risk variables across all domains assessed, including temperament, neurocognition, and social adversity. The specific factors exhibited more domain-specific patterns of associations, with INT exhibiting greater fear/distress and EXT exhibiting greater impulsivity.

CONCLUSIONS

In this largest study of hierarchical models of psychopathology to date, we found that p, INT, and EXT exhibit well-differentiated nomological networks that are interpretable in terms of neurocognition, impulsivity, fear/distress, and social adversity. These networks were, in contrast, obscured when relying on the a priori Internalizing and Externalizing dimensions of the CBCL scales. Our findings add to the evidence for the validity of p, INT, and EXT as theoretically and empirically meaningful broad psychopathology liabilities.

Prenatal caffeine exposure: association with neurodevelopmental outcomes in 9- to 11-year-old children

BACKGROUND

Despite the widespread use of caffeine including consumption during pregnancy, the effect of prenatal caffeine exposure on child brain development and behavior is unclear.

METHODS

To address this, we used data from the Adolescent Brain and Cognitive Development Study (n = 11,875 children aged 9-11 years from 22 sites across the United States). We explored the associations between prenatal caffeine exposure and various developmental outcomes including birth outcomes, physical health, behavior problems, cognition, substance use and brain structure in children, and evaluated dose effects.

RESULTS

Among 9,978 children (4,745 females) who had valid data for prenatal caffeine exposure and whose mothers did not use drugs of abuse after knowing of pregnancy, 4,170 (41.79%) had no prenatal caffeine exposure, 2,292 (22.97%) had daily, 1,933 (19.37%) had weekly, and 1,583 (15.86%) had less than weekly exposures. Prenatal caffeine exposure including the widely recommended 'safe' dose was associated with greater externalizing problems, whereas greater BMI and soda consumption were only observed in children with high dose exposures (3+ per day). Notably, the effect size for association of externalizing problems with prenatal caffeine exposure was comparable with that reported for prenatal alcohol (The American Journal of Psychiatry, 177, 2020 and 1060) and prenatal cannabis (JAMA Psychiatry, 78, 2020 and 64) exposures from previous ABCD publications. Additionally, prenatal caffeine exposure was associated with brain structural changes that included greater posterior and lower frontal cortical thickness and altered parietooccipital sulcal depth.

CONCLUSIONS

The recommended 'safe' dose of caffeine during pregnancy should be carefully studied to assess whether the behavioral and brain correlates observed here are clinically relevant and determine whether it needs adjustment. Because of the high prevalence of caffeine use in the general population, studies on prenatal exposure to drugs of abuse should include prenatal caffeine use as a covariate.

Substance use patterns in 9-10 year olds: Baseline findings from the adolescent brain cognitive development (ABCD) study

BACKGROUND

The Adolescent Brain Cognitive Development ™ Study (ABCD Study®) is an open-science, multi-site, prospective, longitudinal study following over 11,800 9- and 10-year-old youth into early adulthood. The ABCD Study aims to prospectively examine the impact of substance use (SU) on neurocognitive and health outcomes. Although SU initiation typically occurs during teen years, relatively little is known about patterns of SU in children younger than 12.

METHODS

This study aims to report the detailed ABCD Study® SU patterns at baseline (n = 11,875) in order to inform the greater scientific community about cohort's early SU. Along with a detailed description of SU, we ran mixed effects regression models to examine the association between early caffeine and alcohol sipping with demographic factors, externalizing symptoms and parental history of alcohol and substance use disorders (AUD/SUD).

PRIMARY RESULTS

At baseline, the majority of youth had used caffeine (67.6 %) and 22.5 % reported sipping alcohol (22.5 %). There was little to no reported use of other drug categories (0.2 % full alcohol drink, 0.7 % used nicotine, <0.1 % used any other drug of abuse). Analyses revealed that total caffeine use and early alcohol sipping were associated with demographic variables (p's<.05), externalizing symptoms (caffeine p = 0002; sipping p = .0003), and parental history of AUD (sipping p = .03).

CONCLUSIONS

ABCD Study participants aged 9-10 years old reported caffeine use and alcohol sipping experimentation, but very rare other SU. Variables linked with early childhood alcohol sipping and caffeine use should be examined as contributing factors in future longitudinal analyses examining escalating trajectories of SU in the ABCD Study cohort.

Identifying profiles of brain structure and associations with current and future psychopathology in youth

Brain structure is often studied as a marker of youth psychopathology by examining associations between volume or thickness of individual regions and specific diagnoses. However, these univariate approaches do not address whether the effect of a particular region may depend on the structure of other regions. Here, we identified subgroups of individuals with distinct profiles of brain structure and examined how these profiles were associated with concurrent and future youth psychopathology. We used latent profile analysis to identify distinct neuroanatomical profiles of subcortical region volume and orbitofrontal cortical thickness in the ABCD study (N = 9376, mean age = 9.91, SD = 0.62). We identified a five-profile solution consisting of a reduced subcortical volume profile, a reduced orbitofrontal thickness profile, a reduced limbic and elevated striatal volume profile, an elevated orbitofrontal thickness and reduced striatal volume profile, and an elevated orbitofrontal thickness and subcortical volume profile. While controlling for age, sex, and intracranial volume, profiles exhibited differences in concurrent psychopathology measured dimensionally and categorically and in psychopathology at 1-year follow-up measured dimensionally. Results show that profiles of brain structure have incremental validity for associations with youth psychopathology beyond intracranial volume.

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Latent Profile Analysis identified distinct profiles of brain structure in youth.

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Profiles consider multiple brain regions jointly, rather than each independently.

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Profiles differed in multiple current and future forms of psychopathology.

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Differences in psychopathology were beyond age, sex, and intracranial volume.

Similar but distinct - Effects of different socioeconomic indicators on resting state functional connectivity: Findings from the Adolescent Brain Cognitive Development (ABCD) Study®

Early socioeconomic status (SES) has consistently been associated with child health and cognitive outcomes, in addition to alterations in brain function and connectivity. The goal of the present study was to probe the effects of different facets of SES (parent education, income, and neighborhood disadvantage), that likely represent varying aspects of the environment, on resting state functional connectivity (rsFC). We investigated this question in a large sample of 9475 children (aged 9–10 years) from the Adolescent Brain Cognitive Development (ABCD) Study. Specifically, we analyzed the association between household SES (parent education, income-to-needs ratio) and neighborhood disadvantage, and system-level rsFC using within-sample split-half replication. We then tested whether the associations were unique to each SES measure, and whether household SES and neighborhood disadvantage had interactive effects on rsFC. SES measures had both common and distinct effects on rsFC, with sensory-motor systems (e.g., sensorimotor network) and cognitive networks (e.g., front-parietal network) particularly implicated. Further, the association between neighborhood disadvantage and sensorimotor network connectivity was less pronounced in the presence of high income-to-needs. Findings demonstrate that different facets of SES have distinct and interacting effects on rsFC, highlighting the importance of considering different indicators when studying the effects of SES on the brain.

Multivariate Patterns of Brain-Behavior-Environment Associations in the Adolescent Brain and Cognitive Development Study

BACKGROUND

Adolescence is a critical developmental stage. A key challenge is to characterize how variation in adolescent brain organization relates to psychosocial and environmental influences.

METHODS

We used canonical correlation analysis to discover distinct patterns of covariation between measures of brain organization (brain morphometry, intracortical myelination, white matter integrity, and resting-state functional connectivity) and individual, psychosocial, and environmental factors in a nationally representative U.S. sample of 9623 individuals (aged 9-10 years, 49% female) participating in the Adolescent Brain and Cognitive Development (ABCD) study.

RESULTS

These analyses identified 14 reliable modes of brain-behavior-environment covariation (canonical r_discovery = .21 to .49, canonical r_test = .10 to .39, p_{false discovery rate corrected} < .0001). Across modes, neighborhood environment, parental characteristics, quality of family life, perinatal history, cardiometabolic health, cognition, and psychopathology had the most consistent and replicable associations with multiple measures of brain organization; positive and negative exposures converged to form patterns of psychosocial advantage or adversity. These showed modality-general, respectively positive or negative, associations with brain structure and function with little evidence of regional specificity. Nested within these cross-modal patterns were more specific associations between prefrontal measures of morphometry, intracortical myelination, and functional connectivity with affective psychopathology, cognition, and family environment.

CONCLUSIONS

We identified clusters of exposures that showed consistent modality-general associations with global measures of brain organization. These findings underscore the importance of understanding the complex and intertwined influences on brain organization and mental function during development and have the potential to inform public health policies aiming toward interventions to improve mental well-being.

Biospecimens and the ABCD study: Rationale, methods of collection, measurement and early data

Biospecimen collection in the Adolescent Brain Cognitive Development (ABCD) study – of hair samples, shed deciduous (baby) teeth, and body fluids – will serve dual functions of screening for study eligibility, and providing measures of biological processes thought to predict or correlate with key study outcomes on brain and cognitive development. Biosamples are being collected annually to screen for recency of drug use prior to the neuroimaging or cognitive testing visit, and to store for the following future studies: (1) on the effects of exposure to illicit and recreational drugs (including alcohol and nicotine); (2) of pubertal hormones on brain and cognitive developmental trajectories; (3) on the contribution of genomics and epigenomics to child and adolescent development and behavioral outcomes; and (4) with pre- and post-natal exposure to environmental neurotoxicants and drugs of abuse measured from novel tooth analyses. The present manuscript describes the rationales for inclusion and selection of the specific biospecimens, methodological considerations for each measure, future plans for assessment of biospecimens during follow-up visits, and preliminary ABCD data to illustrate methodological considerations.

Approaching Retention within the ABCD Study

Retention efforts are critical to maintain relationships with research participants over time. This is especially important for the Adolescent Brain Cognitive Development (ABCD) study, where families are asked to stay engaged with the study throughout the course of 10 years. This high-degree of involvement is essential to longitudinally track child and adolescent development. At a minimum, we will connect with families every 6 months by telephone, and every year in person, with closer contact with the youth directly as they transition into adolescence. Differential retention, when related to non-random issues pertaining to demographic or risk features, can negatively impact the generalizability of study outcomes. Thus, to ensure high rates of retention for all participants, the ABCD study employs a number of efforts to support youth and families. This overview details the framework and concrete steps for retention.