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

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.

Key Points

Question: Are copy number variants (CNVs) contributing to individualized variability in psychopathology outcomes and cognitive functions in children?Findings: Both regional CNVs at 1q12.1, 10q26.3 and 14q11.2 and global CNV burden accounted for the variance in dimensions of psychopathology, particularly for attention and social problems, as well as cognitive performance, especially for working memory and reading ability.Meaning: Our findings suggest that, in addition to common genetic variants, gene dosage changes confer genetic susceptibility to child psychopathology and cognitive development.

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.

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 (PM_2.5), 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. PM_2.5 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.

Attention-Deficit/Hyperactivity Disorder: Restricted Phenotypes Prevalence, Comorbidity, and Polygenic Risk Sensitivity in the ABCD Baseline Cohort

OBJECTIVE

To evaluate the prevalence and major comorbidities of ADHD using different operational definitions in a newly available national dataset and to test the utility of operational definitions against genetic and cognitive correlates.

METHOD

The US Adolescent Brain Cognitive Development (ABCD) Study enrolled 11,878 children aged 9-10 years at baseline. ADHD prevalence, comorbidity, and association with polygenic risk score and laboratory-assessed executive functions were calculated at 4 thresholds of ADHD phenotype restrictiveness. Bias from missingness, sampling, and nesting were addressed statistically.

RESULTS

Prevalence of current ADHD for 9- to 10-year old children was 3.53% (95% CI 3.14%-3.92%) when Computerized Schedule for Affective Disorders and Schizophrenia for School-Age Children (K-SADS-COMP) score and parent and teacher ratings were required to converge. Of ADHD cases so defined, 70% had a comorbid psychiatric disorder. After control for overlapping comorbidity and ruling out for psychosis or low IQ, 30.9% (95% CI 25.7%-36.7%) had a comorbid disruptive behavior disorder, 27.4% (95% CI 22.3%-33.1%) had an anxiety or fear disorder, and 2.1% (95% CI 1.2%-3.8%) had a mood disorder. Children in the top decile of polygenic load incurred a 63% increased chance of having ADHD vs the bottom half of polygenic load (p < .01)-an effect detected only with a stringent phenotype definition. Dimensional latent variables for irritability, externalizing, and ADHD yielded convergent results for cognitive correlates.

CONCLUSION

This fresh estimate of national prevalence of ADHD in the United States suggests that the DSM-5 definition requiring multiple informants yields a prevalence of about 3.5%. Results may inform further ADHD studies in the ABCD sample.

Application of the RDoC Framework to Predict Alcohol Use and Suicidal Thoughts and Behaviors among Early Adolescents in the Adolescent Brain and Cognitive Development (ABCD) Study

Alcohol use confers risk for suicidal thoughts and behaviors (ideation, attempt) in early adolescents. The Research Domain Criteria provides a framework for examination of multidimensional and modifiable risk factors. We examined distinct latent profiles based on patterns of positive valence (reward responsivity) and cognitive systems (neurocognition) from the ABCD Study (age 9−10, N = 10,414) at baseline enrollment. Longitudinal associations were determined between baseline positive valence and cognitive profiles and group classification (alcohol use, suicidal thoughts and behaviors, or their co-occurrence) two-years after initial assessment (ages 11−12). Three unique profiles of positive valence, cognition, alcohol use, and suicidal thoughts and behaviors were identified. Two baseline profiles predicted alcohol use and suicidal thoughts and behaviors, two-years after initial assessment. Low positive valence with high cognition (but low impulsivity) predicted alcohol use (OR = 1.414, p< 0.001), while high positive valence with low cognition (but high impulsivity) predicted suicidal thoughts and behaviors (OR = 1.25, p = 0.038), compared to average positive valence and cognition. Unique profiles of positive valence and cognitive systems among 9−12-year-olds may be predictive of alcohol use and suicidal thoughts and behaviors over a two-year period. Findings underscore the potential for trajectory research on positive valence and cognitive profiles to enhance prevention for early-adolescents.

Motivation and Cognitive Abilities as Mediators Between Polygenic Scores and Psychopathology in Children

OBJECTIVE

Fundamental questions in biological psychiatry concern the mechanisms that mediate between genetic liability and psychiatric symptoms. Genetic liability for many common psychiatric disorders often confers transdiagnostic risk to develop a wide variety of psychopathological symptoms through yet unknown pathways. This study examined the psychological and cognitive pathways that might mediate the relationship between genetic liability (indexed by polygenic scores; PS) and broad psychopathology (indexed by p factor and its underlying dimensions).

METHOD

First, which of the common psychiatric PSs (major depressive disorder [MDD], attention-deficit/hyperactivity disorder [ADHD], anxiety, bipolar disorder, schizophrenia, autism) that were associated with p factor were identified. Then focused was shifted to 3 pathways: punishment sensitivity (reflected by behavioral inhibition system), reward sensitivity (reflected by behavioral activation system), and cognitive abilities (reflected by g factor based on 10 neurocognitive tasks). We applied structural equation modeling on the Adolescent Brain Cognitive Development (ABCD) Study dataset (n = 4,814; 2,263 girls; 9-10 years old).

RESULTS

MDD and ADHD PSs were associated with p factor. The association between MDD PS and psychopathology was partially mediated by punishment sensitivity and cognitive abilities (proportion mediated = 22.35%). Conversely, the influence of ADHD PS on psychopathology was partially mediated by reward sensitivity and cognitive abilities (proportion mediated = 30.04%). The mediating role of punishment sensitivity was specific to emotional/internalizing. The mediating role of both reward sensitivity and cognitive abilities was specific to behavioral/externalizing and neurodevelopmental dimensions of psychopathology.

CONCLUSION

This study provides a better understanding of how genetic risks for MDD and ADHD confer risks for psychopathology and suggests potential prevention/intervention targets for children at risk.

A practical guide for researchers and reviewers using the ABCD Study and other large longitudinal datasets

As the largest longitudinal study of adolescent brain development and behavior to date, the Adolescent Brain Cognitive Development (ABCD) Study® has provided immense opportunities for researchers across disciplines since its first data release in 2018. The size and scope of the study also present a number of hurdles, which range from becoming familiar with the study design and data structure to employing rigorous and reproducible analyses. The current paper is intended as a guide for researchers and reviewers working with ABCD data, highlighting the features of the data (and the strengths and limitations therein) as well as relevant analytical and methodological considerations. Additionally, we explore justice, equity, diversity, and inclusion efforts as they pertain to the ABCD Study and other large-scale datasets. In doing so, we hope to increase both accessibility of the ABCD Study and transparency within the field of developmental cognitive neuroscience.

Stability of polygenic scores across discovery genome-wide association studies

Polygenic scores (PGS) are commonly evaluated in terms of their predictive accuracy at the population level by the proportion of phenotypic variance they explain. To be useful for precision medicine applications, they also need to be evaluated at the individual level when phenotypes are not necessarily already known. We investigated the stability of PGS in European American (EUR) and African American (AFR)-ancestry individuals from the Philadelphia Neurodevelopmental Cohort and the Adolescent Brain Cognitive Development study using different discovery genome-wide association study (GWAS) results for post-traumatic stress disorder (PTSD), type 2 diabetes (T2D), and height. We found that pairs of EUR-ancestry GWAS for the same trait had genetic correlations >0.92. However, PGS calculated from pairs of same-ancestry and different-ancestry GWAS had correlations that ranged from <0.01 to 0.74. PGS stability was greater for height than for PTSD or T2D. A series of height GWAS in the UK Biobank suggested that correlation between PGS is strongly dependent on the extent of sample overlap between the discovery GWAS. Focusing on the upper end of the PGS distribution, different discovery GWAS do not consistently identify the same individuals in the upper quantiles, with the best case being 60% of individuals above the 80th percentile of PGS overlapping from one height GWAS to another. The degree of overlap decreases sharply as higher quantiles, less heritable traits, and different-ancestry GWAS are considered. PGS computed from different discovery GWAS have only modest correlation at the individual level, underscoring the need to proceed cautiously with integrating PGS into precision medicine applications.

Substance use onset in high-risk 9-13 year-olds in the ABCD study

AIM

A key aim of the Adolescent Brain Cognitive Development℠ (ABCD) Study is to document substance use onset, patterns, and sequelae across adolescent development. However, substance use misreporting can obscure accurate drug use characterization. Hair toxicology provides objective historical substance use data but is rarely used in studies of youth. Here, we compare objective hair toxicology results with self-reported substance use in high-risk youth.

METHODS

A literature-based substance use risk algorithm prioritized 696 ABCD Study® hair samples from 677 participants for analysis at baseline, and 1 and 2-year follow-ups (spanning ages 9-13). Chi-square and t-tests assessed differences between participants' demographics, positive and negative hair tests, risk-for-use algorithm scores, and self-reported substance use.

RESULTS

Hair testing confirmed that 17% of at-risk 9-13 year-olds hair samples had evidence of past 3-month use of one (n = 97), two (n = 14), three (n = 2), or four (n = 2) drug classes. After considering prescribed medication and self-reported substance use, 10% had a positive test indicating substance use that was not reported. Participants with any positive hair result reported less sipping of alcohol (p < 0.001) and scored higher on the risk-for-use algorithm (p < 0.001) than those with negative toxicology results.

CONCLUSIONS

10% of hair samples from at-risk 9-13 year-olds tested positive for at least one unreported substance, suggesting underreporting in high-risk youth when participating in a research study. As hair testing prioritized youth with risk characteristics, the overall extent of underreporting will be calculated in future studies. Nonetheless, hair toxicology was key to characterizing substance use in high-risk youth.

Long-term effects of prenatal cannabis exposure: Pathways to adolescent and adult outcomes

With the increased prevalence, potency, and acceptability of cannabis use during pregnancy, it is important to understand the developmental effects of prenatal cannabis exposure (PCE). This review discusses methodological considerations for studies of PCE, including the assessment of exposures, covariates, and outcomes, and reviews findings from prospective, longitudinal studies of PCE. There is some evidence for associations between PCE and restricted growth at birth, but not for long-term effects on growth. PCE appears to have subtle yet enduring effects on memory and achievement in children and adolescents. Despite differences in sample demographics and measurement, there are remarkably consistent effects of PCE on externalizing behaviors, such as delinquency and substance use, which persist into adulthood. Longitudinal analyses demonstrate the importance of early cannabis initiation for pathways between PCE and adult functioning, including substance use and abuse, memory deficits, and psychotic symptoms. Animal studies demonstrate direct effects on the development of the brain via activation of endogenous endocannabinoid systems. Cannabis-induced activation of the endocannabinoid system causes alterations in the release of neurotransmitters and the modulation of brain plasticity in neural pathways that underlie cognition, motivation, and behavior regulation. Future research should consider cannabis use before pregnancy, the timing and route of exposure, polysubstance exposures, and inter-generational effects.

Discovery of genomic loci of the human cerebral cortex using genetically informed brain atlases

To determine the impact of genetic variants on the brain, we used genetically informed brain atlases in genome-wide association studies of regional cortical surface area and thickness in 39,898 adults and 9136 children. We uncovered 440 genome-wide significant loci in the discovery cohort and 800 from a post hoc combined meta-analysis. Loci in adulthood were largely captured in childhood, showing signatures of negative selection, and were linked to early neurodevelopment and pathways associated with neuropsychiatric risk. Opposing gradations of decreased surface area and increased thickness were associated with common inversion polymorphisms. Inferior frontal regions, encompassing Broca's area, which is important for speech, were enriched for human-specific genomic elements. Thus, a mixed genetic landscape of conserved and human-specific features is concordant with brain hierarchy and morphogenetic gradients.

The positive-negative mode link between brain connectivity, demographics and behaviour: a pre-registered replication of Smith et al. (2015)

In mental health research, it has proven difficult to find measures of brain function that provide reliable indicators of mental health and well-being, including susceptibility to mental health disorders. Recently, a family of data-driven analyses have provided such reliable measures when applied to large, population-level datasets. In the current pre-registered replication study, we show that the canonical correlation analysis (CCA) methods previously developed using resting-state magnetic resonance imaging functional connectivity and subject measures (SMs) of cognition and behaviour from healthy adults are also effective in measuring well-being (a 'positive-negative axis') in an independent developmental dataset. Our replication was successful in two out of three of our pre-registered criteria, such that a primary CCA mode's weights displayed a significant positive relationship and explained a significant amount of variance in both functional connectivity and SMs. The only criterion that was not successful was that compared to other modes the magnitude of variance explained by the primary CCA mode was smaller than predicted, a result that could indicate a developmental trajectory of a primary mode. This replication establishes a signature neurotypical relationship between connectivity and phenotype, opening new avenues of research in neuroscience with clear clinical applications.

Adolescent Verbal Memory as a Psychosis Endophenotype: A Genome-Wide Association Study in an Ancestrally Diverse Sample

Verbal memory impairment is one of the most prominent cognitive deficits in psychosis. However, few studies have investigated the genetic basis of verbal memory in a neurodevelopmental context, and most genome-wide association studies (GWASs) have been conducted in European-ancestry populations. We conducted a GWAS on verbal memory in a maximum of 11,017 participants aged 8.9 to 11.1 years in the Adolescent Brain Cognitive Development Study®, recruited from a diverse population in the United States. Verbal memory was assessed by the Rey Auditory Verbal Learning Test, which included three measures of verbal memory: immediate recall, short-delay recall, and long-delay recall. We adopted a mixed-model approach to perform a joint GWAS of all participants, adjusting for ancestral background and familial relatedness. The inclusion of participants from all ancestries increased the power of the GWAS. Two novel genome-wide significant associations were found for short-delay and long-delay recall verbal memory. In particular, one locus (rs9896243) associated with long-delay recall was mapped to the NSF (N-Ethylmaleimide Sensitive Factor, Vesicle Fusing ATPase) gene, indicating the role of membrane fusion in adolescent verbal memory. Based on the GWAS in the European subset, we estimated the SNP-heritability to be 15% to 29% for the three verbal memory traits. We found that verbal memory was genetically correlated with schizophrenia, providing further evidence supporting verbal memory as an endophenotype for psychosis.

Working memory and reaction time variability mediate the relationship between polygenic risk and ADHD traits in a general population sample

Endophenotypes are heritable and quantifiable traits indexing genetic liability for a disorder. Here, we examined three potential endophenotypes, working memory function, response inhibition, and reaction time variability, for attention-deficit hyperactivity disorder (ADHD) measured as a dimensional latent trait in a large general population sample derived from the Adolescent Brain Cognitive Development^SM Study. The genetic risk for ADHD was estimated using polygenic risk scores (PRS) whereas ADHD traits were quantified as a dimensional continuum using Bartlett factor score estimates, derived from Attention Problems items from the Child Behaviour Checklist and Effortful Control items from the Early Adolescent Temperament Questionnaire-Revised. The three candidate cognitive endophenotypes were quantified using task-based performance measures. Higher ADHD PRSs were associated with higher ADHD traits, as well as poorer working memory performance and increased reaction time variability. Lower working memory performance, poorer response inhibition, and increased reaction time variability were associated with more pronounced ADHD traits. Working memory and reaction time variability partially statistically mediated the relationship between ADHD PRS and ADHD traits, explaining 14% and 16% of the association, respectively. The mediation effect was specific to the genetic risk for ADHD and did not generalise to genetic risk for four other major psychiatric disorders. Together, these findings provide robust evidence from a large general population sample that working memory and reaction time variability can be considered endophenotypes for ADHD that mediate the relationship between ADHD PRS and ADHD traits.

Innovative methods for remote assessment of neurobehavioral development

In response to the COVID-19 pandemic, research institutions across the globe have modified their operations in ways that have limited or eliminated the amount of permissible in-person research interaction. In order to prevent the loss of important developmentally-timed data during the pandemic, researchers have quickly pivoted and developed innovative methods for remote assessment of research participants. In this manuscript, we describe methods developed for remote assessment of a parent child cohort with a focus on examining the perinatal environment, behavioral and biological indicators of child neurobehavioral development, parent-child interaction, as well as parent and child mental and physical health. We include recommendations relevant to adapting in-laboratory assessments for remote data collection and conclude with a description of the successful dissemination of the methods to eight research sites across the United States, each of whom are involved in Phase 1 of the HEALthy Brain and Child Development (HBCD) Study. These remote methods were born out of pandemic-related necessity; however, they have much wider applicability and may offer advantages over in-laboratory neurodevelopmental assessments.

Association of Outdoor Ambient Fine Particulate Matter With Intracellular White Matter Microstructural Properties Among Children

Importance

Outdoor particulate matter 2.5 μm or less in diameter (PM2.5) is a ubiquitous environmental neurotoxicant that may affect the developing brain. Little is known about associations between PM2.5 and white matter connectivity.

Objectives

To assess associations between annual residential PM2.5 exposure and white matter microstructure health in a US sample of children 9 to 10 years of age and to examine whether associations are specific to certain white matter pathways or vary across neuroimaging diffusion markers reflective of intracellular and extracellular microstructural processes.

Design, Setting, and Participants

This cross-sectional study, the Adolescent Brain and Cognitive Development (ABCD) Study, was composed of 21 study sites across the US and used baseline data collected from children 9 to 10 years of age from September 1, 2016, to October 15, 2018. Data analysis was performed from September 15, 2020, to June 30, 2021.

Exposures

Annual mean PM2.5 exposure estimated by ensemble-based models and assigned to the primary residential addresses at baseline.

Main Outcomes and Measures

Diffusion-weighted imaging (DWI) and tractography were used to delineate white matter tracts. The biophysical modeling technique of restriction spectrum imaging (RSI) was implemented to examine total hindered diffusion and restricted isotropic and anisotropic intracellular diffusion in each tract. Hierarchical mixed-effects models with natural splines were used to analyze the associations between PM2.5 exposure and DWI.

Results

In a study population of 7602 children (mean [SD] age, 119.1 [7.42] months; 3955 [52.0%] female; 160 [ 21.%] Asian, 1025 [13.5%] Black, 1616 [21.3%] Hispanic, 4025 [52.9%] White, and 774 [10.2%] other [identified by parents as American Indian/Native American or Alaska Native; Native Hawaiian, Guamanian, Samoan, other Pacific Islander; Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, or other Asian; or other race]), associations were seen between annual ambient PM2.5 and hemispheric differences in white matter microstructure. Hemisphere-stratified models revealed significant associations between PM2.5 exposure and restricted isotropic intracellular diffusion in the left cingulum, in the left superior longitudinal fasciculus, and bilaterally in the fornix and uncinate fasciculus. In tracts with strong positive associations, a PM2.5 increase from 8 to 12 μg/m3 was associated with increases of 2.16% (95% CI, 0.49%-3.84%) in the left cingulum, 1.95% (95% CI, 0.43%-3.47%) in the left uncinate, and 1.68% (95% CI, 0.01%-3.34%) in the right uncinate. Widespread negative associations were observed between PM2.5 and mean diffusivity.

Conclusions and Relevance

The findings of this cross-sectional study suggest that annual mean PM2.5 exposure during childhood is associated with increased restricted isotropic diffusion and decreased mean diffusivity of specific white matter tracts, potentially reflecting differences in the composition of white matter microarchitecture.

Large, open datasets for human connectomics research: Considerations for reproducible and responsible data use

Large, open datasets have emerged as important resources in the field of human connectomics. In this review, the evolution of data sharing involving magnetic resonance imaging is described. A summary of the challenges and progress in conducting reproducible data analyses is provided, including description of recent progress made in the development of community guidelines and recommendations, software and data management tools, and initiatives to enhance training and education. Finally, this review concludes with a discussion of ethical conduct relevant to analyses of large, open datasets and a researcher's responsibility to prevent further stigmatization of historically marginalized racial and ethnic groups. Moving forward, future work should include an enhanced emphasis on the social determinants of health, which may further contextualize findings among diverse population-based samples. Leveraging the progress to date and guided by interdisciplinary collaborations, the future of connectomics promises to be an impressive era of innovative research, yielding a more inclusive understanding of brain structure and function.