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

Multimodal Measurement of Pubertal Development: Stage, Timing, Tempo, and Hormones

Using data from the Human Connectome Project in Development (N = 1304; ages 5-21 years; 50% male; 59% White, 17% Hispanic, 13% Black, 9% Asian), multiple measures (self-report, salivary hormones) and research designs (longitudinal, cross-sectional) were used to characterize age-related changes and sex differences in pubertal development. Both sexes exhibit a sigmoid trajectory of pubertal development; females show earlier pubertal timing and increased tempo ~9-13 years, while males show greater tempo ~14-18 years. All hormones increased with age, with sex differences in testosterone and DHEA levels and in testosterone rates of change. Higher testosterone and DHEA corresponded with earlier pubertal timing in both sexes. These findings characterize typical pubertal and hormonal development and inform best practices for handling puberty data.

Responsible research in health disparities using the Adolescent Brain Cognitive DevelopmentSM (ABCD) study

PURPOSE

The Adolescent Brain Cognitive DevelopmentSM (ABCD) Study is the largest longitudinal study on brain development and adolescent health in the United States. The study includes a sociodemographically diverse cohort of nearly 12,000 youth born 2005-2009, with an open science model of making data rapidly available to the scientific community. The ABCD Study® data has been used in over 1100 peer-reviewed publications since its first data release in 2018. The dataset contains a broad scope and comprehensive set of measures of youths' behavioral, health, and brain outcomes, as well as extensive contextual and environmental measures that map onto the social determinants of health (SDOH). Understanding the impact of SDOH on the developmental trajectories of youth will help to address early lifecourse health inequities that lead to disparities later in life. However, the open science model and extensive use of ABCD data highlight the need for guidance on appropriate, responsible, and equitable use of the data.

DESIGN METHODS

Our conceptual framework integrates the National Institute on Minority Health and Health Disparities (NIMHD) Research Framework with strength-based and data equity perspectives. We use this framework to articulate best practices and methods for investigations that aim to identify the multilevel pathways by which structural and systemic inequities impact adolescent health trajectories.

RESULTS

Using our conceptual model, we provide recommendations for equitable health disparities research using ABCD Study data. We identify over fifty ABCD measures that can encompass SDOH across five levels of influence: individual, interpersonal, school, community, and societal. We expand the societal level to acknowledge structural discrimination as the root cause of systemic and structural inequities resulting in health disparities among marginalized youth. We apply the methodological recommendations in an example data analysis using a multi-level approach that integrates strength-based and data equity perspectives to elucidate pathways by which social and structural inequities may influence cognitive decision making in youth. We conclude with recommendations for strengthening the utility of ABCD data for health disparities research now and in the future.

CONCLUSION

Adolescence is a critical period of development with subsequent ramifications for health outcomes across the lifespan. Thus, understanding SDOH among diverse youth can inform prevention interventions before the emergence of health disparities in adulthood.

Leveraging Distributed Brain Signal at Rest to Predict Internalizing Symptoms in Youth: Deriving a Polyneuro Risk Score From the ABCD Study Cohort

BACKGROUND

The prevalence of internalizing psychopathology rises precipitously from early to mid-adolescence, yet the underlying neural phenotypes that give rise to depression and anxiety during this developmental period remain unclear.

METHODS

Youths from the Adolescent Brain Cognitive Development (ABCD) Study (ages 9-10 years at baseline) with a resting-state functional magnetic resonance imaging scan and mental health data were eligible for inclusion. Internalizing subscale scores from the Brief Problem Monitor-Youth Form were combined across 2 years of follow-up to generate a cumulative measure of internalizing symptoms. The total sample (N = 6521) was split into a large discovery dataset and a smaller validation dataset. Brain-behavior associations of resting-state functional connectivity with internalizing symptoms were estimated in the discovery dataset. The weighted contributions of each functional connection were aggregated using multivariate statistics to generate a polyneuro risk score (PNRS). The predictive power of the PNRS was evaluated in the validation dataset.

RESULTS

The PNRS explained 10.73% of the observed variance in internalizing symptom scores in the validation dataset. Model performance peaked when the top 2% functional connections identified in the discovery dataset (ranked by absolute β weight) were retained. The resting-state functional connectivity networks that were implicated most prominently were the default mode, dorsal attention, and cingulo-parietal networks. These findings were significant (p < 1 × 10-6) as accounted for by permutation testing (n = 7000).

CONCLUSIONS

These results suggest that the neural phenotype associated with internalizing symptoms during adolescence is functionally distributed. The PNRS approach is a novel method for capturing relationships between resting-state functional connectivity and behavior.

Polygenic risk for epigenetic aging and adverse life experiences interact to predict growth in adolescent depression in a racially/ethnically diverse sample

Introduction

Research has yet to examine the interplay between indices of environmental risk and resilience processes and genetic predisposition for epigenetic aging in predicting early adolescent depressive symptoms. In the current study we examine whether adverse life events and parental acceptance moderate polygenic predisposition for GrimAge epigenetic aging in predicting trajectories of depressive symptoms across early adolescence.

Method

Using data from the Adolescent Brain Development Study (ABCD, N = 11,875), we created polygenic scores for GrimAge, and examined whether exposure to adverse life events and parental acceptance moderated the relation between genetic risk and depressive symptom trajectories from age 10/11 to 12/13 using growth mixture modelling. We examined models separately in European American (EA), African American (AA), and Latinx (LX) subgroups of ABCD.

Results

In the EA and AA subgroups, adverse life events moderated polygenic scores for GrimAge such that there was increased likelihood of membership in a higher vs. lower depression trajectory.

Discussion

We extend literature by identifying genetic contributions to epigenetic aging as a depression diathesis in adolescence. Findings also highlight the detrimental role of adverse life events in exacerbating genetic risk for the development of depression in adolescence.

Impact of Environmental Noise and Sleep Health on Pediatric Hypertension Incidence: ABCD Study

BACKGROUND

Pediatric hypertension is linked to environmental factors like neighborhood noise disrupting sleep, which is crucial for health. The specific interaction between noise and sleep health in causing hypertension still needs to be explored.

METHODS AND RESULTS

We analyzed data from 3320 participants of the ABCD (Adolescent Brain Cognitive Development) study, recruited across 21 US cities and monitored from 2018 to 2020 through 2020 to 2022. Participants with complete data on Fitbit-tracked sleep, blood pressure, height, neighborhood noise, and covariates (biological sex, race and ethnicity, pubertal stage, waist circumference) were included. Hypertension was defined as average blood pressure ≥95th percentile for age, sex, and height. Sleep health was categorized on the basis of daily duration: healthy (9-12 hours), moderately healthy (±1 hour from optimal), and low (≥1 hour deviation). Noise exposure was measured as median nighttime anthropogenic noise levels by zip code. The incidence of hypertension increased from 1.7% (95% CI, 1.4-2.1) in 2018 to 2020 to 2.9% (95% CI, 2.4-3.6) in 2020 to 2022. Adolescents with healthier sleep had a lower risk of developing hypertension (relative risk, 0.63 [95% CI, 0.25-0.82]), while no significant effects were found for neighborhood noise alone or in combination with sleep health.

CONCLUSIONS

Adequate sleep significantly reduces the risk of hypertension in adolescents, independent of environmental noise exposure. These findings underscore the importance of promoting good sleep hygiene among youth to mitigate hypertension risk.

Polygenic Risk Underlies Youth Psychopathology and Personalized Functional Brain Network Topography

Importance

Functional brain networks are associated with both behavior and genetic factors. To uncover clinically translatable mechanisms of psychopathology, it is critical to define how the spatial organization of these networks relates to genetic risk during development.

Objective

To determine the relationship between transdiagnostic polygenic risk scores (PRSs), personalized functional brain networks (PFNs), and overall psychopathology (p-factor) during early adolescence.

Design

The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing longitudinal cohort study of 21 collection sites across the United States. Here, we conduct a cross-sectional analysis of ABCD baseline data, collected 2017-2018.

Setting

The ABCD Study ® is a multi-site community-based study.

Participants

The sample is largely recruited through school systems. Exclusion criteria included severe sensory, intellectual, medical, or neurological issues that interfere with protocol and scanner contraindications. Split-half subsets were used for cross-validation, matched on age, ethnicity, family structure, handedness, parental education, site, sex, and anesthesia exposure.

Exposures

Polygenic risk scores of transdiagnostic genetic factors F1 (PRS-F1) and F2 (PRS-F2) derived from adults in Psychiatric Genomic Consortium and UK Biobanks datasets. PRS-F1 indexes liability for common psychiatric symptoms and disorders related to mood disturbance; PRS-F2 indexes liability for rarer forms of mental illness characterized by mania and psychosis.

Main Outcomes and Measures

(1) P-factor derived from bifactor models of youth- and parent-reported mental health assessments. (2) Person-specific functional brain network topography derived from functional magnetic resonance imaging (fMRI) scans.

Results

Total participants included 11,873 youths ages 9-10 years old; 5,678 (47.8%) were female, and the mean (SD) age was 9.92 (0.62) years. PFN topography was found to be heritable (N=7,459, 57.06% of vertices h 2 p FDR <0.05, mean h 2 =0.35). PRS-F1 was associated with p-factor (N=5,815, r=0.12, 95% CI [0.09-0.15], p<0.001). Interindividual differences in functional network topography were associated with p-factor (N=7,459, mean r=0.12), PRS-F1 (N=3,982, mean r=0.05), and PRS-F2 (N=3,982, mean r=0.08). Cortical maps of p-factor and PRS-F1 regression coefficients were highly correlated (r=0.7, p=0.003).

Conclusions and Relevance

Polygenic risk for transdiagnostic adulthood psychopathology is associated with both p-factor and heritable PFN topography during early adolescence. These results advance our understanding of the developmental drivers of psychopathology.

Impact of Pre-Adolescent Substance Familiarity on Subsequent Use: Longitudinal Analysis of Risk by Latent Classes in the Adolescent Brain Cognitive Development Sample

BACKGROUND

Predicting substance use in adolescence is a difficult yet important task in developing effective prevention. We aim to extend previous findings on the linear associations between familiarity with (knowledge of) substances in childhood and subsequent substance use in adolescence through a latent class analysis (LCA) to create risk profiles based on substance familiarity.

METHOD

Using the ABCD Study® sample, we conducted an LCA using 18 binary substance familiarity variables (n = 11,694 substance-naïve youth). Complementary analyses investigated the relationship between LCA groups and (1) longitudinal use, (2) use initiation, and (3) early use.

RESULTS

The optimal LCA resulted in a four-class solution: Naïve, Common, Uncommon, and Rare, with each group increasing in both the number and rarity of known substances. Analysis 1 revealed an increased risk in use over time among both the Uncommon and Rare groups (ORs = 2.08 and 5.55, respectively, p's < 0.001) compared to the Common group. Analysis 2 observed a decreased risk for initiation between the Naïve and Common groups (OR = 0.61, p = 0.009); however, the Uncommon and Rare groups were at an increased risk compared to the Common group (ORs = 2.08 and 3.42, respectively, p's < 0.001). Analysis 3 found an increased risk of early use between the Common and Uncommon groups (OR = 1.92, p < 0.001) with a similar trend between the Common and Rare groups (OR = 1.90, p = 0.06).

CONCLUSION

These results highlight distinct risk profiles for adolescent substance use based on substance familiarity in middle childhood. Current work could be applied as an early screening tool for clinicians to identify those at risk for adolescent substance use.

Cognitive processing speed and accuracy are intrinsically different in genetic architecture and brain phenotypes

Since the birth of cognitive science, researchers have used reaction time and accuracy to measure cognitive ability. Although recognition of these two measures is often based on empirical observations, the underlying consensus is that most cognitive behaviors may be along two fundamental dimensions: cognitive processing speed (CPS) and cognitive processing accuracy (CPA). In this study, we used genomic-wide association studies (GWAS) data from 14 cognitive traits to show the presence of those two factors and revealed the specific neurobiological basis underlying them. We identified that CPS and CPA had distinct brain phenotypes (e.g. white matter microstructure), neurobiological bases (e.g. postsynaptic membrane), and developmental periods (i.e. late infancy). Moreover, those two factors showed differential associations with other health-related traits such as screen exposure and sleep status, and a significant causal relationship with psychiatric disorders such as major depressive disorder and schizophrenia. Utilizing an independent cohort from the Adolescent Brain Cognitive Development (ABCD) study, we also uncovered the distinct contributions of those two factors on the cognitive development of young adolescents. These findings reveal two fundamental factors underlying various cognitive abilities, elucidate the distinct brain structural fingerprint and genetic architecture of CPS and CPA, and hint at the complex interrelationship between cognitive ability, lifestyle, and mental health.

Longitudinal tracking of alcohol expectancies and their associations with impulsivity in alcohol naïve youth in the adolescent brain cognitive development (ABCD) study

Background

Positive and negative alcohol expectancies (PAEs and NAEs, respectively) and impulsivity are key risk factors for the onset of alcohol use. While both factors independently contribute to alcohol initiation, the developmental aspects of AEs and their nuanced relationship with impulsivity are not adequately understood. Understanding these relationships is imperative for developing targeted interventions to prevent or delay alcohol use onset in youth.

Methods

This study utilized the Adolescent Brain Cognitive Development cohort to examine how PAEs and NAEs develop over time and relate to each other. We also explored how self-reported and behavioral impulsivity at baseline (~10 years old) are associated with the longitudinal development of PAEs and NAEs in youth Ages 11, 12, and 13 (n = 7493; 7500; and 6981, respectively), as well as their time-specific relationships.

Results

Findings revealed while PAEs increased steadily over all three years, NAEs increased from ages 11-12 and then remained unchanged between 12 and 13. Overall, PAEs and NAEs were inversely related. Moreover, PAEs positively correlated with sensation seeking and lack of premeditation, while NAEs negatively correlated with positive urgency. Interestingly, a time-specific association was observed with PAEs and lack of perseverance, with a stronger correlation to PAEs at Age 11 compared to Age 12.

Conclusions

Overall, this study provides valuable insights into the divergent developmental trajectory of PAEs and NAEs, and their overall and time-specific associations with impulsivity. These findings may guide focused and time-sensitive prevention and intervention initiatives, aiming to modify AEs and reduce underage drinking.

Neurodevelopmental signature of a transcriptome-based polygenic risk score for depression

Disentangling the molecular underpinnings of major depressive disorder (MDD) is necessary for identifying new treatment and prevention targets. The functional impact of depression-related transcriptomic changes on the brain remains relatively unexplored. We recently developed a novel transcriptome-based polygenic risk score (tPRS) composed of genes transcriptionally altered in MDD. Here, we sought to investigate effects of tPRS on brain structure in a developmental cohort (Adolescent Brain Cognitive Development study; n = 5124; 2387 female) at baseline (9-10 years) and 2-year follow-up (11-12 years). We tested associations between tPRS and Freesurfer-derived measures of cortical thickness, cortical surface area, and subcortical volume. Across the whole sample, higher tPRS was significantly associated with thicker left posterior cingulate cortex at both baseline and 2-year follow-up. In females only, tPRS was associated with lower right hippocampal volume at baseline and 2-year follow-up, and lower right pallidal volume at baseline. Furthermore, regional subcortical volume significantly mediated an indirect effect of tPRS on depressive symptoms in females at both timepoints. Conversely, tPRS did not have significant effects on cortical surface area. These findings suggest the existence of a sex-specific neurodevelopmental signature associated with shifts towards a more depression-like brain transcriptome, and highlight novel pathways of developmentally mediated MDD risk.

Amygdala volume and depression symptoms in young adolescents who use cannabis

INTRODUCTION

Both cannabis use and depressive symptomology increase in prevalence throughout adolescence. Concurrently, the brain is undergoing neurodevelopment in important limbic regions, such as the amygdala. Prior research indicates the amygdala may also be related to cannabis use and depressive symptoms. We aimed to investigate the effects of adolescent cannabis use on amygdala volumes as well as the interaction of cannabis use and amygdala morphometry on depressive symptoms in youth.

METHOD

Two-hundred-twenty-four participants (ages 12-15), balanced by sex assigned at birth, were selected from a sub-sample of the Adolescent Brain Cognitive Development (ABCD) Study based on hair toxicology and self-report measures of cannabis use. Participants positive for cannabinoids in hair and/or self-reported cannabis use were demographically matched to youth with no self-reported or confirmed cannabis use. The guardians of these youth reported depression symptoms on the Child Behavioral Checklist. Linear mixed effect models were run investigating cannabis use group on amygdala volumes bilaterally, controlling for whole brain volume and random effects of scanner type. Additional analyses examined cannabis group status and bilateral amygdala volume on depression symptoms.

RESULTS

Cannabis use was not significantly associated with amygdala volume but was associated with increased depressive symptoms (p<0.01). Cannabis group interacted with amygdala volume, such that individuals with smaller volumes had increased depressive symptoms within the cannabis group (p's<0.01-0.02).

CONCLUSION

Aberrations in amygdala volume based on cannabis use were not found in early adolescence; however, more depressive symptoms were related to cannabis group. Youth who use cannabis and have smaller amygdala volumes were at increased risk for depressive symptomology, suggesting potential neurovulnerabilities to cannabis use.

The Genetic Architecture of the Human Corpus Callosum and its Subregions

The corpus callosum (CC) is the largest set of white matter fibers connecting the two hemispheres of the brain. In humans, it is essential for coordinating sensorimotor responses, performing associative/executive functions, and representing information in multiple dimensions. Understanding which genetic variants underpin corpus callosum morphometry, and their shared influence on cortical structure and susceptibility to neuropsychiatric disorders, can provide molecular insights into the CC's role in mediating cortical development and its contribution to neuropsychiatric disease. To characterize the morphometry of the midsagittal corpus callosum, we developed a publicly available artificial intelligence based tool to extract, parcellate, and calculate its total and regional area and thickness. Using the UK Biobank (UKB) and the Adolescent Brain Cognitive Development study (ABCD), we extracted measures of midsagittal corpus callosum morphometry and performed a genome-wide association study (GWAS) meta-analysis of European participants (combined N = 46,685). We then examined evidence for generalization to the non-European participants of the UKB and ABCD cohorts (combined N = 7,040). Post-GWAS analyses implicate prenatal intracellular organization and cell growth patterns, and high heritability in regions of open chromatin, suggesting transcriptional activity regulation in early development. Results suggest programmed cell death mediated by the immune system drives the thinning of the posterior body and isthmus. Global and local genetic overlap, along with causal genetic liability, between the corpus callosum, cerebral cortex, and neuropsychiatric disorders such as attention-deficit/hyperactivity and bipolar disorders were identified. These results provide insight into variability of corpus callosum development, its genetic influence on the cerebral cortex, and biological mechanisms related to neuropsychiatric dysfunction.

Long-term impact of digital media on brain development in children

Digital media (DM) takes an increasingly large part of children's time, yet the long-term effect on brain development remains unclear. We investigated how individual effects of DM use (i.e., using social media, playing video games, or watching television/videos) on the development of the cortex (i.e., global cortical surface area), striatum, and cerebellum in children over 4 years, accounting for both socioeconomic status and genetic predisposition. We used a prospective, multicentre, longitudinal cohort of children from the Adolescent Brain and Cognitive Development Study, aged 9.9 years when entering the study, and who were followed for 4 years. Annually, children reported their DM usage through the Youth Screen Time Survey and underwent brain magnetic resonance imaging scans every 2 years. Quadratic-mixed effect modelling was used to investigate the relationship between individual DM usage and brain development. We found that individual DM usage did not alter the development of cortex or striatum volumes. However, high social media usage was associated with a statistically significant change in the developmental trajectory of cerebellum volumes, and the accumulated effect of high-vs-low social media users on cerebellum volumes over 4 years was only β = - 0.03, which was considered insignificant. Nevertheless, the developmental trend for heavy social media users was accelerated at later time points. This calls for further studies and longer follow-ups on the impact of social media on brain development.

Partitioning variance in cortical morphometry into genetic, environmental, and subject-specific components

The relative contributions of genetic variation and experience in shaping the morphology of the adolescent brain are not fully understood. Using longitudinal data from 11,665 subjects in the ABCD Study, we fit vertex-wise variance components including family effects, genetic effects, and subject-level effects using a computationally efficient framework. Variance in cortical thickness and surface area is largely attributable to genetic influence, whereas sulcal depth is primarily explained by subject-level effects. Our results identify areas with heterogeneous distributions of heritability estimates that have not been seen in previous work using data from cortical regions. We discuss the biological importance of subject-specific variance and its implications for environmental influences on cortical development and maturation.

Examining neural responses to anticipating or receiving monetary rewards and the development of binge eating in youth. A registered report using data from the Adolescent Brain Cognitive Development (ABCD) study

Binge eating is characterized as eating a large amount of food and feeling a loss of control while eating. However, the neurobiological mechanisms associated with the onset and maintenance of binge eating are largely unknown. Recent neuroimaging work has suggested that increased responsivity within reward regions of the brain to the anticipation or receipt of rewards is related to binge eating; however, limited longitudinal data has precluded understanding of the role of reward responsivity in the development of binge eating. The current study used data from the Adolescent Brain and Cognitive Development® (ABCD) longitudinal study dataset to assess whether heightened neural responses to different phases of reward processing (reward anticipation and receipt) (1) differentiated individuals with binge eating from matched controls, and (2) predicted the onset of binge eating in an "at risk" sample. Consistent with hypotheses, heightened neural responsivity in the right caudate and bilateral VS during reward anticipation differentiated youth with and without binge eating. Moreover, greater VS response to reward anticipation predicted binge eating two years later. Neural responses to reward receipt also were consistent with hypotheses, such that heightened VS and OFC responses differentiated youth with and without binge eating and predicted the presence of binge eating two years later. Findings from the current study suggest that hypersensitivity to rewards may contribute to the development of binge eating during early adolescence.

Implementing ABCD studyⓇ MRI sequences for multi-site cohort studies: Practical guide to necessary steps, preprocessing methods, and challenges

Large multi-site studies that combine magnetic resonance imaging (MRI) data across research sites present exceptional opportunities to advance neuroscience research. However, scanner or site variability and non-standardised image acquisition protocols, data processing and analysis pipelines can adversely affect the reliability and repeatability of MRI derived brain measures. We implemented a standardised MRI protocol based on that used in the Adolescent Brain Cognition Development (ABCD)Ⓡ study in two sites, and across four MRI scanners. Twice repeated measurements of a single healthy volunteer were obtained in two sites and in four 3T MRI scanners (vendors: Siemens, Philips, and GE). Imaging data included anatomical scans (T1 weighted, T2 weighted), diffusion weighted imaging (DWI) and resting state functional MRI (rs-fMRI). Standardised containerized pipelines were utilised to pre-process the data and different image quality metrics and test-retest variability of different brain metrics were evaluated. The implementation of the MRI protocols was possible with minor adjustments in acquisition (e.g. repetition time (TR), higher b-values) and exporting (DICOM formats) of images due to different technical performance of the scanners. This study provides practical insights into the implementation of standardised sequences and data processing for multisite studies, showcase the benefits of containerised preprocessing tools, and highlights the need for careful optimisation of multisite image acquisition.

The copy number variant architecture of psychopathology and cognitive development in the ABCD® study

Importance

Childhood is a crucial developmental phase for mental health and cognitive function, both of which are commonly affected in patients with psychiatric disorders. This neurodevelopmental trajectory is shaped by a complex interplay of genetic and environmental factors. While common genetic variants account for a large proportion of inherited genetic risk, rare genetic variations, particularly copy number variants (CNVs), play a significant role in the genetic architecture of neurodevelopmental disorders. Despite their importance, the relevance of CNVs to child psychopathology and cognitive function in the general population remains underexplored.

Objective

Investigating CNV associations with dimensions of child psychopathology and cognitive functions.

Design Setting and Participants

ABCD® study focuses on a cohort of over 11,875 youth aged 9 to 10, recruited from 21 sites in the US, aiming to investigate the role of various factors, including brain, environment, and genetic factors, in the etiology of mental and physical health from middle childhood through early adulthood. Data analysis occurred from April 2023 to April 2024.

Main Outcomes and Measures

In this study, we utilized PennCNV and QuantiSNP algorithms to identify duplications and deletions larger than 50Kb across a cohort of 11,088 individuals from the Adolescent Brain Cognitive Development® study. CNVs meeting quality control standards were subjected to a genome-wide association scan to identify regions associated with quantitative measures of broad psychiatric symptom domains and cognitive outcomes. Additionally, a CNV risk score, reflecting the aggregated burden of genetic intolerance to inactivation and dosage sensitivity, was calculated to assess its impact on variability in overall and dimensional child psychiatric and cognitive phenotypes.

Results

In a final sample of 8,564 individuals (mean age=9.9 years, 4,532 males) passing quality control, we identified 4,111 individuals carrying 5,760 autosomal CNVs. Our results revealed significant associations between specific CNVs and our phenotypes of interest, psychopathology and cognitive function. For instance, a duplication at 10q26.3 was associated with overall psychopathology, and somatic complaints in particular. Additionally, deletions at 1q12.1, along with duplications at 14q11.2 and 10q26.3, were linked to overall cognitive function, with particular contributions from fluid intelligence (14q11.2), working memory (10q26.3), and reading ability (14q11.2). Moreover, individuals carrying CNVs previously associated with neurodevelopmental disorders exhibited greater impairment in social functioning and cognitive performance across multiple domains, in particular working memory. Notably, a higher deletion CNV risk score was significantly correlated with increased overall psychopathology (especially in dimensions of social functioning, thought disorder, and attention) as well as cognitive impairment across various domains.

Conclusions and Relevance

In summary, our findings shed light on the contributions of CNVs to interindividual variability in complex traits related to neurocognitive development and child psychopathology.

Household Income and Subsequent Youth Tobacco Initiation: Minorities' Diminished Returns

Introduction

Household income, a prominent socioeconomic status (SES) indicator, is known to mitigate youth engagement in various health risk behaviors, including tobacco use. Nevertheless, the Minorities' Diminished Returns theory suggests that this protective effect may be less pronounced for racial and ethnic minorities compared to majority groups. This study aimed to investigate the protective role of high household income against tobacco use among youth and explore potential variations across different racial and ethnic groups.

Methods

Conducted as a longitudinal analysis, this study utilized data from the initial three years of the Adolescent Brain Cognitive Development (ABCD) Study spanning 2016-2022. The cohort consisted of 11,875 American youth aged 9-10 years, tracked over a three-year period. The dependent variable was tobacco initiation, irrespective of the product, while household income served as the independent variable. Covariates included youth age, gender, family education, structure, and employment, with race/ethnicity acting as the moderating variable.

Results

Out of the 8,754 American youth who were non-smokers at baseline, 3.1% (n = 269) initiated tobacco use during the 30-month follow-up, while 96.9% (n = 8,485) remained non-smokers. A family income exceeding $100,000 per year was associated with a lower hazard ratio for tobacco initiation (transitioning to ever-use) over the follow-up period (HR = 0.620, p = 0.022). However, household income of $50-100k exhibited significant interactions with race/ethnicity on tobacco initiation, indicating weaker protective effects for Black (HR for interaction = 7.860, p < 0.001) and Latino (HR for interaction = 3.461, p = 0.001) youth compared to non-Latino White youth.

Conclusions

Within the United States, the racialization and minoritization of youth diminish the protective effects of economic resources, such as high household income, against the transition to tobacco use. Non-Latino White youth, the most socially privileged group, experience greater protection from their elevated household income regarding tobacco initiation compared to Black and Latino youth, who face minoritization and racialization. Policymakers should address not only the SES gap but also the mechanisms contributing to the heightened risk of tobacco use among racialized and minoritized youth from affluent backgrounds.

Sex, gender diversity, and brain structure in early adolescence

There remains little consensus about the relationship between sex and brain structure, particularly in early adolescence. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest-many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years old (N = 7195). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. Additional sensitivity analyses found that male versus female differences in gyrification and white matter were largely accounted for by total brain volume, rather than sex per se. The model with sex, but not gender diversity, was the best-fitting model in 60.1% of gray matter regions and 61.9% of white matter regions after adjusting for brain volume. The proportion of variance accounted for by sex was negligible to small in all cases. While models including felt-gender explained a greater amount of variance in a few regions, the felt-gender score alone was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

Traumatic brain injury, working memory-related neural processing, and alcohol experimentation behaviors in youth from the ABCD cohort

Adolescent traumatic brain injury (TBI) has long-term effects on brain functioning and behavior, impacting neural activity under cognitive load, especially in the reward network. Adolescent TBI is also linked to risk-taking behaviors including alcohol misuse. It remains unclear how TBI and neural functioning interact to predict alcohol experimentation during adolescence. Using Adolescent Brain Cognitive Development (ABCD) study data, this project examined if TBI at ages 9-10 predicts increased odds of alcohol sipping at ages 11-13 and if this association is moderated by neural activity during the Emotional EN-Back working memory task at ages 11-13. Logistic regression analyses showed that neural activity in regions of the fronto-basal ganglia network predicted increased odds of sipping alcohol by ages 11-13 (p < .05). TBI and left frontal pole activity interacted to predict alcohol sipping (OR = 0.507, 95% CI [0.303 - 0.846], p = .009) - increased activity predicted decreased odds of alcohol sipping for those with a TBI (OR = 0.516, 95% CI [0.314 - 0.850], p = .009), but not for those without (OR = 0.971, 95% CI [0.931 -1.012], p = .159). These findings suggest that for youth with a TBI, increased BOLD activity in the frontal pole, underlying working memory, may be uniquely protective against the early initiation of alcohol experimentation. Future work will examine TBI and alcohol misuse in the ABCD cohort across more time points and the impact of personality traits such as impulsivity on these associations.

Cumulative Effects of Resting-State Connectivity Across All Brain Networks Significantly Correlate with Attention-Deficit Hyperactivity Disorder Symptoms

Identification of replicable neuroimaging correlates of attention-deficit hyperactivity disorder (ADHD) has been hindered by small sample sizes, small effects, and heterogeneity of methods. Given evidence that ADHD is associated with alterations in widely distributed brain networks and the small effects of individual brain features, a whole-brain perspective focusing on cumulative effects is warranted. The use of large, multisite samples is crucial for improving reproducibility and clinical utility of brain-wide MRI association studies. To address this, a polyneuro risk score (PNRS) representing cumulative, brain-wide, ADHD-associated resting-state functional connectivity was constructed and validated using data from the Adolescent Brain Cognitive Development (ABCD, N = 5,543, 51.5% female) study, and was further tested in the independent Oregon-ADHD-1000 case-control cohort (N = 553, 37.4% female). The ADHD PNRS was significantly associated with ADHD symptoms in both cohorts after accounting for relevant covariates (p < 0.001). The most predictive PNRS involved all brain networks, though the strongest effects were concentrated among the default mode and cingulo-opercular networks. In the longitudinal Oregon-ADHD-1000, non-ADHD youth had significantly lower PNRS (Cohen's d = -0.318, robust p = 5.5 × 10-4) than those with persistent ADHD (age 7-19). The PNRS, however, did not mediate polygenic risk for ADHD. Brain-wide connectivity was robustly associated with ADHD symptoms in two independent cohorts, providing further evidence of widespread dysconnectivity in ADHD. Evaluation in enriched samples demonstrates the promise of the PNRS approach for improving reproducibility in neuroimaging studies and unraveling the complex relationships between brain connectivity and behavioral disorders.

Causal Relationships Between Screen Use, Reading, and Brain Development in Early Adolescents

The rise of new media has greatly changed the lifestyles, leading to increased time on these platforms and less time spent reading. This shift has particularly profound impacts on early adolescents, who are in a critical stage of brain development. Previous studies have found associations between screen use and mental health, but it remains unclear whether screen use is the direct cause of the outcomes. Here, the Adolescent Brain Cognitive Development (ABCD) dataset is utlized to examine the causal relationships between screen use and brain development. The results revealed adverse causal effects of screen use on language ability and specific behaviors in early adolescents, while reading has positive causal effects on their language ability and brain volume in the frontal and temporal regions. Interestingly, increased screen use is identified as a result, rather than a cause, of certain behaviors such as rule-breaking and aggressive behaviors. Furthermore, the analysis uncovered an indirect influence of screen use, mediated by changes in reading habits, on brain development. These findings provide new evidence for the causal influences of screen use on brain development and highlight the importance of monitoring media use and related habit change in children.

Leveraging big data for causal understanding in mental health: a research framework

Over the past 30 years there have been numerous large-scale and longitudinal psychiatric research efforts to improve our understanding and treatment of mental health conditions. However, despite the huge effort by the research community and considerable funding, we still lack a causal understanding of most mental health disorders. Consequently, the majority of psychiatric diagnosis and treatment still operates at the level of symptomatic experience, rather than measuring or addressing root causes. This results in a trial-and-error approach that is a poor fit to underlying causality with poor clinical outcomes. Here we discuss how a research framework that originates from exploration of causal factors, rather than symptom groupings, applied to large scale multi-dimensional data can help address some of the current challenges facing mental health research and, in turn, clinical outcomes. Firstly, we describe some of the challenges and complexities underpinning the search for causal drivers of mental health conditions, focusing on current approaches to the assessment and diagnosis of psychiatric disorders, the many-to-many mappings between symptoms and causes, the search for biomarkers of heterogeneous symptom groups, and the multiple, dynamically interacting variables that influence our psychology. Secondly, we put forward a causal-orientated framework in the context of two large-scale datasets arising from the Adolescent Brain Cognitive Development (ABCD) study, the largest long-term study of brain development and child health in the United States, and the Global Mind Project which is the largest database in the world of mental health profiles along with life context information from 1.4 million people across the globe. Finally, we describe how analytical and machine learning approaches such as clustering and causal inference can be used on datasets such as these to help elucidate a more causal understanding of mental health conditions to enable diagnostic approaches and preventative solutions that tackle mental health challenges at their root cause.

Heritability estimation of subcortical volumes in a multi-ethnic multi-site cohort study

Heritability of regional subcortical brain volumes (rSBVs) describes the role of genetics in middle and inner brain development. rSBVs are highly heritable in adults but are not characterized well in adolescents. The Adolescent Brain Cognitive Development study (ABCD), taken over 22 US sites, provides data to characterize the heritability of subcortical structures in adolescence. In ABCD, site-specific effects co-occur with genetic effects which can bias heritability estimates. Existing methods adjusting for site effects require additional steps to adjust for site effects and can lead to inconsistent estimation. We propose a random-effect model-based method of moments approach that is a single step estimator and is a theoretically consistent estimator even when sites are imbalanced and performs well under simulations. We compare methods on rSBVs from ABCD. The proposed approach yielded heritability estimates similar to previous results derived from single-site studies. The cerebellum cortex and hippocampus were the most heritable regions (> 50%).

Sex-specific impulsivity, but not other facets of executive function, predicts fat and sugar intake two-years later amongst adolescents with a healthy weight: Findings from the ABCD study

During adolescence, processes that control food intake (executive functions [EF]) undergo extensive refinement; underlying differences in EF may explain the inability to resist overeating unhealthy foods. Yet, overeating fat and sugar also causes changes to EF and cognition but disentangling these relationships has been difficult, as previous studies included youth with obesity. Here, amongst youth initially of a healthy weight, we evaluate whether 1) sex-specific underlying variation in EF/cognition at 9/10-years-old predict fat/sugar two-years later (Y2) and 2) if these relationships are moderated by body mass index (BMI), using linear mixed effects models (controlled for puberty, caregiver education; random effect: study site). Data were leveraged from Adolescent Brain Cognitive Development Study (n = 2987; 50.4% male; 15.4% Latino/a/x; 100% healthy weight at baseline; 12.4% overweight/obese by Y2, data release 4.0). EF and cognition (e.g., inhibition, cognition, motor, memory, impulsivity) were assessed with the NIH toolbox, Rey Auditory Verbal Learning Task, Little Man Task, the BIS/BAS, and UPPS-P. A saturated fat/added sugar (kcals) composite score was extracted from the validated Kids Food Block Screener. For males, greater baseline impulsivity (e.g., Positive Urgency, Lack of Planning and Perseverance) and reward (e.g., Fun seeking, Drive) was related to greater Y2 intake. For both sexes, greater baseline Negative Urgency and higher BMI was related to greater Y2 intake. No other relationships were observed. Our findings highlight a phenotype that may be more at risk for weight gain due to overconsumption of fat/sugar. Thus, prevention efforts may wish to focus on impulsive tendencies for these foods.

Individual Trajectories of Depressive Symptoms Within Racially-Ethnically Diverse Youth: Associations with Polygenic Risk for Depression and Substance Use Intent and Perceived Harm

There are distinct individual trajectories of depressive symptoms across adolescence which are most often differentiated into low, moderate/stable, and high/increasing groups. Research has found genetic predisposition for depression associated with trajectories characterized by greater depressive symptoms. However, the majority of this research has been conducted in White youth. Moreover, a separate literature indicates that trajectories with elevated depressive symptoms can result in substance use. It is critical to identify depressive symptom trajectories, genetic predictors, and substance use outcomes in diverse samples in early adolescence to understand distinct processes and convey equitable benefits from research. Using data from the Adolescent Cognitive Brain Development Study (ABCD), we examined parent-reported depressive symptom trajectories within Black/African American (AA, n = 1783), White/European American (EA, n = 6179), and Hispanic/Latinx (LX, n = 2410) youth across four annual assessments in early adolescence (age 9-10 to 12-13). We examined racially/ethnically aligned polygenic scores (Dep-PGS) as predictors of trajectories as well as substance use intent and perceived substance use harm as outcomes at age 12-13. Differential trajectories were found in AA, EA, and LX youth but low and high trajectories were represented within each group. In EA youth, greater Dep-PGS were broadly associated with membership in trajectories with greater depressive symptoms. Genetic effects were not significant in AA and LX youth. In AA youth, membership in the low trajectory was associated with greater substance use intent. In EA youth, membership in trajectories with higher depressive symptoms was associated with greater substance use intent and less perceived harm. There were no associations between trajectories and substance use intent and perceived harm in LX youth. These findings indicate that there are distinct depressive symptom trajectories in AA, EA, and LX youth, accompanied by unique associations with genetic predisposition for depressive symptoms and substance use outcomes.

Shared Genetic Risk in the Association of Screen Time With Psychiatric Problems in Children

Importance

Children's exposure to screen time has been associated with poor mental health outcomes, yet the role of genetic factors remains largely unknown.

Objective

To assess the extent of genetic confounding in the associations between screen time and attention problems or internalizing problems in preadolescent children.

Design, Setting, and Participants

This cohort study analyzed data obtained between 2016 and 2019 from the Adolescent Brain Cognitive Development Study at 21 sites in the US. The sample included children aged 9 to 11 years of genetically assigned European ancestry with self-reported screen time. Data were analyzed between November 2021 and September 2023.

Exposure

Child-reported daily screen time (in hours) was ascertained from questionnaires completed by the children at baseline.

Main Outcomes and Measures

Child psychiatric problems, specifically attention and internalizing problems, were measured with the parent-completed Achenbach Child Behavior Checklist at the 1-year follow-up. Genetic sensitivity analyses model (Gsens) was used, which incorporated polygenic risk scores (PRSs) of both exposure and outcomes as well as either single-nucleotide variant (SNV; formerly single-nucleotide polymorphism)-based heritability or twin-based heritability to estimate genetic confounding.

Results

The 4262 children in the sample included 2269 males (53.2%) with a mean (SD) age of 9.9 (0.6) years. Child screen time was associated with attention problems (β = 0.10 SD; 95% CI, 0.07-0.13 SD) and internalizing problems (β = 0.03 SD; 95% CI, 0.003-0.06 SD). The television time PRS was associated with child screen time (β = 0.18 SD; 95% CI, 0.14-0.23 SD), the attention-deficit/hyperactivity disorder PRS was associated with attention problems (β = 0.13 SD; 95% CI, 0.10-0.16 SD), and the depression PRS was associated with internalizing problems (β = 0.10 SD; 95% CI, 0.07-0.13 SD). These PRSs were associated with cross-traits, suggesting genetic confounding. Estimates using PRSs and SNV-based heritability showed that genetic confounding accounted for most of the association between child screen time and attention problems and for 42.7% of the association between child screen time and internalizing problems. When PRSs and twin-based heritability estimates were used, genetic confounding fully explained both associations.

Conclusions and Relevance

Results of this study suggest that genetic confounding may explain a substantial part of the associations between child screen time and psychiatric problems. Genetic confounding should be considered in sociobehavioral studies of modifiable factors for youth mental health.

Consistent effects of the genetics of happiness across the lifespan and ancestries in multiple cohorts

Happiness is a fundamental human affective trait, but its biological basis is not well understood. Using a novel approach, we construct LDpred-inf polygenic scores of a general happiness measure in 2 cohorts: the Adolescent Brain Cognitive Development (ABCD) cohort (N = 15,924, age range 9.23-11.8 years), the Add Health cohort (N = 9129, age range 24.5-34.7) to determine associations with several well-being and happiness measures. Additionally, we investigated associations between genetic scores for happiness and brain structure in ABCD (N = 9626, age range (8.9-11) and UK Biobank (N = 16,957, age range 45-83). We detected significant (p.FDR < 0.05) associations between higher genetic scores vs. several well-being measures (best r2 = 0.019) in children of multiple ancestries in ABCD and small yet significant correlations with a happiness measure in European participants in Add Health (r2 = 0.004). Additionally, we show significant associations between lower genetic scores for happiness with smaller structural brain phenotypes in a white British subsample of UK Biobank and a white sub-sample group of ABCD. We demonstrate that the genetic basis for general happiness level appears to have a consistent effect on happiness and wellbeing measures throughout the lifespan, across multiple ancestral backgrounds, and multiple brain structures.

Substance familiarity in middle childhood and adolescent substance use

BACKGROUND

Childhood familiarity with (knowledge of) substances is a potentially important, currently understudied adolescent substance use risk factor. We aimed to describe changes in childhood familiarity with substances and to test whether baseline familiarity predicts early adolescent substance use.

METHODS

Utilizing the Substance Use Module of the longitudinal cohort study, Adolescent Brain Cognitive Development (ABCD; US youth aged 9-10 years followed for 10 years) through Data Release 4 (n=7896; individuals who completed all six assessments in the first three years), we conducted longitudinal mixed models and survival analyses to describe changes in familiarity and to determine the adjusted odds of substance use by age 13 based on number of familiar substances at baseline.

RESULTS

The sample consisted of 3754 females and 4142 males, aged 9-10 at baseline, with majority White individuals (68.9%). Unconditional time models indicated age significantly predicted familiarity (B=0.08, p<0.001; R2=0.288) with ~3.59 familiar substances at 9 years increasing to ~7.43 substances at 13 years. Family history, home use, peer use, and neighborhood availability predicted familiarity, accounting for 1% of additional variance (R2=0.299; ∆R2=0.011). For each additional familiar substance at baseline, adjusted odds of future use increased 1.28 times (95% CI 1.22, 1.34).

CONCLUSIONS

This is the first study to characterize substance familiarity in this age range as a predictor of future substance use. Familiarity increases with age (age being the most predictive indicator). Familiarity at age 9-10 predicts early adolescent substance use. As such, childhood familiarity may represent an easily implemented screening tool for at-risk youth.

Gray space and default mode network-amygdala connectivity

Introduction

Aspects of the built environment relate to health factors and equity in living conditions, and may contribute to racial, ethnic, or economic health disparities. For example, urbanicity is linked with negative factors including exposure to gray space (e.g., impervious surfaces such as concrete, streets, or rooftops). While there is existing research on access to green space and urbanicity on some mental health and cognitive outcomes, there is limited research on the presence of gray space linked with cognitive functioning in youth. The goal of this study was to investigate the link between gray space and amygdala-default mode network (DMN) connectivity.

Methods

This study used data from the ABCD Study. Participants (n = 10,144; age M = 119.11 months, female = 47.62%) underwent resting-state fMRI acquisition at baseline. Impervious surfaces (gray space) were measured via the Child Opportunity Index (COI). To examine the relationship between presence of gray space and -amygdala-DMN (left/right) connectivity, we employed linear mixed effects models. Correlations were run between amygdala-DMN connectivity and internalizing and externalizing symptoms. Finally, post hoc sensitivity analyses were run to assess the impact of race.

Results

More gray space, adjusting for age, sex, and neighborhood-level variables, was significantly associated with increased left amygdala-DMN connectivity (p = 0.0001). This association remained significant after sensitivity analyses for race were completed (p = 0.01). No significant correlations were observed between amygdala-DMN and internalizing or externalizing symptoms.

Discussion

Findings suggest gray space was linked with increased left amygdala-DMN connectivity, circuits that have been implicated in affective processing, emotion regulation, and psychopathology. Thus gray space may be related to alterations in connectivity that may enhance risk for emotion dysregulation. Future investigation of these relationships is needed, as neuroimaging findings may represent early dysregulation not yet observed in the behavioral analyses at this age (i.e., the present study did not find significant relationships with parent-reported behavioral outcomes). These findings can help to inform future public policy on improving lived and built environments.

Chromosomal inversion polymorphisms shape human brain morphology

The impact of chromosomal inversions on human brain morphology remains underexplored. We studied 35 common inversions classified from genotypes of 33,018 adults with European ancestry. The inversions at 2p22.3, 16p11.2, and 17q21.31 reach genome-wide significance, followed by 8p23.1 and 6p21.33, in their association with cortical and subcortical morphology. The 17q21.31, 8p23.1, and 16p11.2 regions comprise the LRRC37, OR7E, and NPIP duplicated gene families. We find the 17q21.31 MAPT inversion region, known for harboring neurological risk, to be the most salient locus among common variants for shaping and patterning the cortex. Overall, we observe the inverted orientations decreasing brain size, with the exception that the 2p22.3 inversion is associated with increased subcortical volume and the 8p23.1 inversion is associated with increased motor cortex. These significant inversions are in the genomic hotspots of neuropsychiatric loci. Our findings are generalizable to 3,472 children and demonstrate inversions as essential genetic variation to understand human brain phenotypes.

Sex, gender diversity, and brain structure in children ages 9 to 11 years old

There remains little consensus about the relationship between sex and brain structure, particularly in childhood. Moreover, few pediatric neuroimaging studies have analyzed both sex and gender as variables of interest - many of which included small sample sizes and relied on binary definitions of gender. The current study examined gender diversity with a continuous felt-gender score and categorized sex based on X and Y allele frequency in a large sample of children ages 9-11 years-old (N=7693). Then, a statistical model-building approach was employed to determine whether gender diversity and sex independently or jointly relate to brain morphology, including subcortical volume, cortical thickness, gyrification, and white matter microstructure. The model with sex, but not gender diversity, was the best-fitting model in 75% of gray matter regions and 79% of white matter regions examined. The addition of gender to the sex model explained significantly more variance than sex alone with regard to bilateral cerebellum volume, left precentral cortical thickness, as well as gyrification in the right superior frontal gyrus, right parahippocampal gyrus, and several regions in the left parietal lobe. For mean diffusivity in the left uncinate fasciculus, the model with sex, gender, and their interaction captured the most variance. Nonetheless, the magnitude of variance accounted for by sex was small in all cases and felt-gender score was not a significant predictor on its own for any white or gray matter regions examined. Overall, these findings demonstrate that at ages 9-11 years-old, sex accounts for a small proportion of variance in brain structure, while gender diversity is not directly associated with neurostructural diversity.

The implications of socioeconomic factors on salivary bioscience methodological variables in a large pediatric multi-site study

Introduction

Salivary bioscience has found increased utilization within pediatric research, given the non-invasive nature of self-collecting saliva for measuring biological markers. With this growth in pediatric utility, more understanding is needed of how social-contextual factors, such as socioeconomic factors or status (SES), influence salivary bioscience in large multi-site studies. Socioeconomic factors have been shown to influence non-salivary analyte levels across childhood and adolescent development. However, less is understood about relationships between these socioeconomic factors and salivary collection methodological variables (e.g., time of saliva collection from waking, time of day of saliva collection, physical activity prior to saliva collection, and caffeine intake prior to saliva collection). Variability in salivary methodological variables between participants may impact the levels of analytes measured in a salivary sample, thus serving as a potential mechanism for non-random systematic biases in analytes.

Methods

Our objective is to examine relationships between socioeconomic factors and salivary bioscience methodological variables within the Adolescent Brain Cognitive Development Study© cohort of children aged 9-10 years old (n = 10,567 participants with saliva samples).

Results

We observed significant associations between household socioeconomic factors (poverty status, education) and salivary collection methodological variables (time since waking, time of day of sampling, physical activity, and caffeine intake). Moreover, lower levels of household poverty and education were significantly associated with more sources of potential bias in salivary collection methodological variables (e.g., longer times since waking, collections later in the day, higher odds of caffeine consumption, and lower odds of physical activity). Consistent associations were not observed with neighborhood socioeconomic factors and salivary methodological variables.

Discussion

Previous literature demonstrates associations between collection methodological variables and measurements of salivary analyte levels, particularly with analytes that are more sensitive to circadian rhythms, pH levels, or rigorous physical activity. Our novel findings suggest that unintended distortions in measured salivary analyte values, potentially resulting from the non-random systematic biases in salivary methodology, need to be intentionally incorporated into analyses and interpretation of results. This is particularly salient for future studies interested in examining underlying mechanisms of childhood socioeconomic health inequities in future analyses.

Joint polygenic and environmental risks for childhood attention-deficit/hyperactivity disorder (ADHD) and ADHD symptom dimensions

Background

attention-deficit/hyperactivity disorder (ADHD) is associated with both polygenic liability and environmental exposures, both intrinsic to the family, such as family conflict, and extrinsic, such as air pollution. However, much less is known about the interplay between environmental and genetic risks relevant to ADHD-a better understanding of which could inform both mechanistic models and clinical prediction algorithms.

Methods

Two independent data sets, the population-based Adolescent Brain Cognitive Development Study (ABCD) (N = 11,876) and the case-control Oregon-ADHD-1000 (N = 1449), were used to examine additive (G + E) and interactive (GxE) effects of selected polygenic risk scores (PRS) and environmental factors in a cross-sectional design. Genetic risk was measured using PRS for nine mental health disorders/traits. Exposures included family income, family conflict/negative sentiment, and geocoded measures of area deprivation, lead exposure risk, and air pollution exposure (nitrogen dioxide and fine particulate matter).

Results

ADHD PRS and family conflict jointly predicted concurrent ADHD symptoms in both cohorts. Additive-effects models, including both genetic and environmental factors, explained significantly more variation in symptoms than any individual factor alone (joint R 2 = .091 for total symptoms in ABCD; joint R 2 = .173 in Oregon-ADHD-1000; all delta-R 2 p-values <2e-7). Significant effect size heterogeneity across ancestry groups was observed for genetic and environmental factors (e.g., Q = 9.01, p = .011 for major depressive disorder PRS; Q = 13.34, p = .001 for area deprivation). GxE interactions observed in the full ABCD cohort suggested stronger environmental effects when genetic risk is low, though they did not replicate.

Conclusions

Reproducible additive effects of PRS and family environment on ADHD symptoms were found, but GxE interaction effects were not replicated and appeared confounded by ancestry. Results highlight the potential value of combining exposures and PRS in clinical prediction algorithms. The observed differences in risks across ancestry groups warrant further study to avoid health care disparities.

Heritability Estimation of Cognitive Phenotypes in the ABCD Study® Using Mixed Models

Twin and family studies have historically aimed to partition phenotypic variance into components corresponding to additive genetic effects (A), common environment (C), and unique environment (E). Here we present the ACE Model and several extensions in the Adolescent Brain Cognitive Development℠ Study (ABCD Study®), employed using the new Fast Efficient Mixed Effects Analysis (FEMA) package. In the twin sub-sample (n = 924; 462 twin pairs), heritability estimates were similar to those reported by prior studies for height (twin heritability = 0.86) and cognition (twin heritability between 0.00 and 0.61), respectively. Incorporating SNP-derived genetic relatedness and using the full ABCD Study® sample (n = 9,742) led to narrower confidence intervals for all parameter estimates. By leveraging the sparse clustering method used by FEMA to handle genetic relatedness only for participants within families, we were able to take advantage of the diverse distribution of genetic relatedness within the ABCD Study® sample.

Genotype Data and Derived Genetic Instruments of Adolescent Brain Cognitive Development Study® for Better Understanding of Human Brain Development

The data release of Adolescent Brain Cognitive Development® (ABCD) Study represents an extensive resource for investigating factors relating to child development and mental wellbeing. The genotype data of ABCD has been used extensively in the context of genetic analysis, including genome-wide association studies and polygenic score predictions. However, there are unique opportunities provided by ABCD genetic data that have not yet been fully tapped. The diverse genomic variability, the enriched relatedness among ABCD subsets, and the longitudinal design of the ABCD challenge researchers to perform novel analyses to gain deeper insight into human brain development. Genetic instruments derived from the ABCD genetic data, such as genetic principal components, can help to better control confounds beyond the context of genetic analyses. To facilitate the use genomic information in the ABCD for inference, we here detail the processing procedures, quality controls, general characteristics, and the corresponding resources in the ABCD genotype data of release 4.0.

Comparing Pruning and Thresholding with Continuous Shrinkage Polygenic Score Methods in a Large Sample of Ancestrally Diverse Adolescents from the ABCD Study®

Using individuals' genetic data researchers can generate Polygenic Scores (PS) that are able to predict risk for diseases, variability in different behaviors as well as anthropomorphic measures. This is achieved by leveraging models learned from previously published large Genome-Wide Association Studies (GWASs) associating locations in the genome with a phenotype of interest. Previous GWASs have predominantly been performed in European ancestry individuals. This is of concern as PS generated in samples with a different ancestry to the original training GWAS have been shown to have lower performance and limited portability, and many efforts are now underway to collect genetic databases on individuals of diverse ancestries. In this study, we compare multiple methods of generating PS, including pruning and thresholding and Bayesian continuous shrinkage models, to determine which of them is best able to overcome these limitations. To do this we use the ABCD Study, a longitudinal cohort with deep phenotyping on individuals of diverse ancestry. We generate PS for anthropometric and psychiatric phenotypes using previously published GWAS summary statistics and examine their performance in three subsamples of ABCD: African ancestry individuals (n = 811), European ancestry Individuals (n = 6703), and admixed ancestry individuals (n = 3664). We find that the single ancestry continuous shrinkage method, PRScs (CS), and the multi ancestry meta method, PRScsx Meta (CSx Meta), show the best performance across ancestries and phenotypes.

Ambient fine particulate exposure and subcortical gray matter microarchitecture in 9- and 10-year-old children across the United States

Neuroimaging studies showing the adverse effects of air pollution on neurodevelopment have largely focused on smaller samples from limited geographical locations and have implemented univariant approaches to assess exposure and brain macrostructure. Herein, we implement restriction spectrum imaging and a multivariate approach to examine how one year of annual exposure to daily fine particulate matter (PM2.5), daily nitrogen dioxide (NO2), and 8-h maximum ozone (O3) at ages 9-10 years relates to subcortical gray matter microarchitecture in a geographically diverse subsample of children from the Adolescent Brain Cognitive Development (ABCD) Study℠. Adjusting for confounders, we identified a latent variable representing 66% of the variance between one year of air pollution and subcortical gray matter microarchitecture. PM2.5 was related to greater isotropic intracellular diffusion in the thalamus, brainstem, and accumbens, which related to cognition and internalizing symptoms. These findings may be indicative of previously identified air pollution-related risk for neuroinflammation and early neurodegenerative pathologies.

Larger cerebral cortex is genetically correlated with greater frontal area and dorsal thickness

Human cortical expansion has occurred non-uniformly across the brain. We assessed the genetic architecture of cortical global expansion and regionalization by comparing two sets of genome-wide association studies of 24 cortical regions with and without adjustment for global measures (i.e., total surface area, mean cortical thickness) using a genetically informed parcellation in 32,488 adults. We found 393 and 756 significant loci with and without adjusting for globals, respectively, where 8% and 45% loci were associated with more than one region. Results from analyses without adjustment for globals recovered loci associated with global measures. Genetic factors that contribute to total surface area of the cortex particularly expand anterior/frontal regions, whereas those contributing to thicker cortex predominantly increase dorsal/frontal-parietal thickness. Interactome-based analyses revealed significant genetic overlap of global and dorsolateral prefrontal modules, enriched for neurodevelopmental and immune system pathways. Consideration of global measures is important in understanding the genetic variants underlying cortical morphology.

Longitudinal assessment of brain structure and behaviour in youth with rapid weight gain: Potential contributing causes and consequences

OBJECTIVE

Independent of weight status, rapid weight gain has been associated with underlying brain structure variation in regions associated with food intake and impulsivity among pre-adolescents. Yet, we lack clarity on how developmental maturation coincides with rapid weight gain and weight stability.

METHODS

We identified brain predictors of 2-year rapid weight gain and its longitudinal effects on brain structure and impulsivity in the Adolescent Brain Cognitive DevelopmentSM Study®. Youth were categorized as Healthy Weight/Weight Stable (WSHW , n = 527) or Weight Gainers (WG, n = 221, >38lbs); 63% of the WG group were healthy weight at 9-to-10-years-old.

RESULTS

A fivefold cross-validated logistic elastic-net regression revealed that rapid weight gain was associated with structural variation amongst 39 brain features at 9-to-10-years-old in regions involved with executive functioning, appetitive control and reward sensitivity. Two years later, WG youth showed differences in change over time in several of these regions and performed worse on measures of impulsivity.

CONCLUSIONS

These findings suggest that brain structure in pre-adolescence may predispose some to rapid weight gain and that weight gain itself may alter maturational brain change in regions important for food intake and impulsivity. Behavioural interventions that target inhibitory control may improve trajectories of brain maturation and facilitate healthier behaviours.

Sleep Quality and Duration in Children That Consume Caffeine: Impact of Dose and Genetic Variation in ADORA2A and CYP1A

Caffeine is the most consumed drug in the world, and it is commonly used by children. Despite being considered relatively safe, caffeine can have marked effects on sleep. Studies in adults suggest that genetic variants in the adenosine A2A receptor (ADORA2A, rs5751876) and cytochrome P450 1A (CYP1A, rs2472297, rs762551) loci are correlated with caffeine-associated sleep disturbances and caffeine intake (dose), but these associations have not been assessed in children. We examined the independent and interaction effects of daily caffeine dose and candidate variants in ADORA2A and CYP1A on the sleep quality and duration in 6112 children aged 9-10 years who used caffeine and were enrolled in the Adolescent Brain Cognitive Development (ABCD) study. We found that children with higher daily caffeine doses had lower odds of reporting > 9 h of sleep per night (OR = 0.81, 95% CI = 0.74-0.88, and p = 1.2 × 10-6). For every mg/kg/day of caffeine consumed, there was a 19% (95% CI = 12-26%) decrease in the odds of children reporting > 9 h of sleep. However, neither ADORA2A nor CYP1A genetic variants were associated with sleep quality, duration, or caffeine dose. Likewise, genotype by caffeine dose interactions were not detected. Our findings suggest that a daily caffeine dose has a clear negative correlation with sleep duration in children, but this association is not moderated by the ADORA2A or CYP1A genetic variation.

Concordance between substance use self-report and hair analysis in community-based adolescents

Background: Accurate drug use identification through subjective self-report and toxicological biosample (hair) analysis are necessary to determine substance use sequelae in youth. Yet consistency between self-reported substance use and robust, toxicological analysis in a large sample of youth is understudied.Objectives: We aim to assess concordance between self-reported substance use and hair toxicological analysis in community-based adolescents.Methods: Hair results by LC-MS/MS and GC-MS/MS and self-reported past-year substance use from an Adolescent Brain Cognitive Development (ABCD) Study subsample (N = 1,390; ages 9-13; 48% female) were compared. The participants were selected for hair selection through two methods: high scores on a substance risk algorithm selected 93%; 7% were low-risk, randomly selected participants. Kappa coefficients the examined concordance between self-report and hair results.Results: 10% of youth self-reported any past-year substance use (e.g. alcohol, cannabis, nicotine, and opiates), while a mostly non-overlapping 10% had hair results indicating recent substance use (cannabis, alcohol, non-prescription amphetamines, cocaine, nicotine, opiates, and fentanyl). In randomly selected low-risk cases, 7% were confirmed positive in hair. Combining methods, 19% of the sample self-reported substance use and/or had a positive hair sample. Kappa coefficient of concordance between self-report and hair results was low (kappa = 0.07; p = .007).Conclusions: Hair toxicology identified substance use in high-risk and low-risk ABCD cohort subsamples. Given low concordance between hair results and self-report, reliance on either method alone would incorrectly categorize 9% as non-users. Multiple methods for characterizing substance use history in youth improves accuracy. Larger representative samples are needed to assess the prevalence of substance use in youth.

Longitudinally stable, brain-based predictive models mediate the relationships between childhood cognition and socio-demographic, psychological and genetic factors

Cognitive abilities are one of the major transdiagnostic domains in the National Institute of Mental Health's Research Domain Criteria (RDoC). Following RDoC's integrative approach, we aimed to develop brain-based predictive models for cognitive abilities that (a) are developmentally stable over years during adolescence and (b) account for the relationships between cognitive abilities and socio-demographic, psychological and genetic factors. For this, we leveraged the unique power of the large-scale, longitudinal data from the Adolescent Brain Cognitive Development (ABCD) study (n ~ 11 k) and combined MRI data across modalities (task-fMRI from three tasks: resting-state fMRI, structural MRI and DTI) using machine-learning. Our brain-based, predictive models for cognitive abilities were stable across 2 years during young adolescence and generalisable to different sites, partially predicting childhood cognition at around 20% of the variance. Moreover, our use of 'opportunistic stacking' allowed the model to handle missing values, reducing the exclusion from around 80% to around 5% of the data. We found fronto-parietal networks during a working-memory task to drive childhood-cognition prediction. The brain-based, predictive models significantly, albeit partially, accounted for variance in childhood cognition due to (1) key socio-demographic and psychological factors (proportion mediated = 18.65% [17.29%-20.12%]) and (2) genetic variation, as reflected by the polygenic score of cognition (proportion mediated = 15.6% [11%-20.7%]). Thus, our brain-based predictive models for cognitive abilities facilitate the development of a robust, transdiagnostic research tool for cognition at the neural level in keeping with the RDoC's integrative framework.

Access to quality health resources and environmental toxins affect the relationship between brain structure and BMI in a sample of pre and early adolescents

Background

Environmental resources are related to childhood obesity risk and altered brain development, but whether these relationships are stable or if they have sustained impact is unknown. Here, we utilized a multidimensional index of childhood neighborhood conditions to compare the influence of various social and environmental disparities (SED) on body mass index (BMI)-brain relationships over a 2-year period in early adolescence.

Methods

Data were gathered the Adolescent Brain Cognitive Development Study® (n = 2,970, 49.8% female, 69.1% White, no siblings). Structure magnetic resonance imaging (sMRI), anthropometrics, and demographic information were collected at baseline (9/10-years-old) and the 2-year-follow-up (11/12-years-old). Region of interest (ROIs; 68 cortical, 18 subcortical) estimates of cortical thickness and subcortical volume were extracted from sMRI T1w images using the Desikan atlas. Residential addresses at baseline were used to obtain geocoded estimates of SEDs from 3 domains of childhood opportunity index (COI): healthy environment (COIHE), social/economic (COISE), and education (COIED). Nested, random-effects mixed models were conducted to evaluate relationships of BMI with (1) ROI * COI[domain] and (2) ROI * COI[domain] * Time. Models controlled for sex, race, ethnicity, puberty, and the other two COI domains of non-interest, allowing us to estimate the unique variance explained by each domain and its interaction with ROI and time.

Results

Youth living in areas with lower COISE and COIED scores were heavier at the 2-year follow-up than baseline and exhibited greater thinning in the bilateral occipital cortex between visits. Lower COISE scores corresponded with larger volume of the bilateral caudate and greater BMI at the 2-year follow-up. COIHE scores showed the greatest associations (n = 20 ROIs) with brain-BMI relationships: youth living in areas with lower COIHE had thinner cortices in prefrontal regions and larger volumes of the left pallidum and Ventral DC. Time did not moderate the COIHE x ROI interaction for any brain region during the examined 2-year period. Findings were independent of family income (i.e., income-to-needs).

Conclusion

Collectively our findings demonstrate that neighborhood SEDs for health-promoting resources play a particularly important role in moderating relationships between brain and BMI in early adolescence regardless of family-level financial resources.

A multidimensional approach to understanding the emergence of sex differences in internalizing symptoms in adolescence

Women are more vulnerable to internalizing disorders (e.g., depression and anxiety). This study took an integrative developmental approach to investigate multidimensional factors associated with the emergence of sex differences in internalizing symptoms, using data from the Adolescent Brain Cognitive Development (ABCD) study. Indices of sex hormone levels (dehydroepiandrosterone, testosterone, and estradiol), physical pubertal development, task-based functional brain activity, family conflict, and internalizing symptoms were drawn from the ABCD study's baseline sample (9- to 10-year-old; N = 11,844). Principal component analysis served as a data-driven dimensionality reduction technique on the internalizing subscales to yield a single robust measure of internalizing symptoms. Moderated mediation analyses assessed whether associations between known risk factors and internalizing symptoms vary by sex. Results revealed direct and indirect effects of physical pubertal development on internalizing symptoms through family conflict across sexes. No effects were found of sex hormone levels or amygdala response to fearful faces on internalizing symptoms. Females did not report overall greater internalizing symptoms relative to males, suggesting that internalizing symptoms have not yet begun to increase in females at this age. Findings provide an essential baseline for future longitudinal research on the endocrine, neurocognitive, and psychosocial factors associated with sex differences in internalizing symptoms.

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.

Heritability Analysis in Twins Indicates a Genetic Basis for Velopharyngeal Morphology

The velopharyngeal mechanism is comprised of several muscular components that act in a coordinated manner to control airflow through the nose and mouth. Proper velopharyngeal function is essential for normal speech, swallowing, and breathing. The genetic basis of normal-range velopharyngeal morphology is poorly understood. The purpose of this study was to estimate the heritability of velopharyngeal dimensions.

We measured five velopharyngeal variables (velar length, velar thickness, effective velar length, levator muscle length and pharyngeal depth) from MRIs of 155 monozygotic and 208 dizygotic twin pairs and then calculated heritability for these traits using a structural equation modeling approach.

The heritability estimates were statistically significant (95% confidence intervals excluded zero) and ranged from 0.19 to 0.46. There was also evidence of significant genetic correlations between pairs of traits, pointing to the influence of common genetic effects.

These results indicate that genetic factors influence variation in clinically relevant velopharyngeal structures.