Scientific Publications

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Exposure to high levels of fine particulate matter (PM) with aerodynamic diameter () via air pollution may be a risk factor for psychiatric disorders during adulthood. Yet few studies have examined associations between exposure and the trajectory of symptoms across late childhood and early adolescence.

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Youth screen media activity is a growing concern, though few studies include objective usage data. Through the longitudinal, U.S.-based Adolescent Brain Cognitive Development (ABCD) Study, youth (m = 14; n = 1415) self-reported their typical smartphone use and passively recorded three weeks of smartphone use via the ABCD-specific Effortless Assessment Research System (EARS) application. Here we describe and validate passively-sensed smartphone keyboard and app use measures, provide code to harmonize measures across operating systems, and describe trends in adolescent smartphone use. Keyboard and app-use measures were reliable and positively correlated with one another (r = 0.33) and with self-reported use (rs = 0.21-0.35). Participants recorded a mean of 5 h of daily smartphone use, which is two more hours than they self-reported. Further, females logged more smartphone use than males. Smartphone use was recorded at all hours, peaking on average from 8 to 10 PM and lowest from 3 to 5 AM. Social media and texting apps comprised nearly half of all use. Data are openly available to approved investigators ( https://nda.nih.gov/abcd/ ). Information herein can inform use of the ABCD dataset to longitudinally study health and neurodevelopmental correlates of adolescent smartphone use.

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Although psychotic behaviors can be difficult to assess in children, early identification of children at high risk for the emergence of psychotic symptoms may facilitate the prevention of related disorders. Psychotic-like experiences (PLEs), or subthreshold thought and perceptual disturbances, could be early manifestations of psychosis that may predict a future diagnosis of a psychosis-related disorder or nonspecific correlates of a wide range of psychological problems. Additional research is needed regarding how PLEs map onto dimensions of psychopathology in children.

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Conduct disorder is associated with the highest burden of any mental disorder in childhood, yet its neurobiology remains unclear. Inconsistent findings limit our understanding of the role of brain structure alterations in conduct disorder. This study aims to identify the most robust and replicable brain structural correlates of conduct disorder.

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Air pollution is ubiquitous, yet questions remain regarding its impact on the developing brain. Large changes occur in white matter microstructure across adolescence, with notable differences by sex.

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Children’s brains dynamically adapt to the stimuli from the internal state and the external environment, allowing for changes in cognitive and mental behavior. In this work, we performed a large-scale analysis of dynamic functional connectivity (DFC) in children aged 9~11 years, investigating how brain dynamics relate to cognitive performance and mental health at an early age. A hybrid independent component analysis framework was applied to the Adolescent Brain Cognitive Development (ABCD) data containing 10,988 children. We combined a sliding-window approach with k-means clustering to identify five brain states with distinct DFC patterns. Interestingly, the occurrence of a strongly connected state with the most within-network synchrony and the anticorrelations between networks, especially between the sensory networks and between the cerebellum and other networks, was negatively correlated with cognitive performance and positively correlated with dimensional psychopathology in children. Meanwhile, opposite relationships were observed for a DFC state showing integration of sensory networks and antagonism between default-mode and sensorimotor networks but weak segregation of the cerebellum. The mediation analysis further showed that attention problems mediated the effect of DFC states on cognitive performance. This investigation unveils the neurological underpinnings of DFC states, which suggests that tracking the transient dynamic connectivity may help to characterize cognitive and mental problems in children and guide people to provide early intervention to buffer adverse influences.

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Brain-phenotype predictive models seek to identify reproducible and generalizable brain-phenotype associations. External validation, or the evaluation of a model in external datasets, is the gold standard in evaluating the generalizability of models in neuroimaging. Unlike typical studies, external validation involves two sample sizes: the training and the external sample sizes. Thus, traditional power calculations may not be appropriate. Here we ran over 900 million resampling-based simulations in functional and structural connectivity data to investigate the relationship between training sample size, external sample size, phenotype effect size, theoretical power and simulated power. Our analysis included a wide range of datasets: the Healthy Brain Network, the Adolescent Brain Cognitive Development Study, the Human Connectome Project (Development and Young Adult), the Philadelphia Neurodevelopmental Cohort, the Queensland Twin Adolescent Brain Project, and the Chinese Human Connectome Project; and phenotypes: age, body mass index, matrix reasoning, working memory, attention problems, anxiety/depression symptoms and relational processing. High effect size predictions achieved adequate power with training and external sample sizes of a few hundred individuals, whereas low and medium effect size predictions required hundreds to thousands of training and external samples. In addition, most previous external validation studies used sample sizes prone to low power, and theoretical power curves should be adjusted for the training sample size. Furthermore, model performance in internal validation often informed subsequent external validation performance (Pearson’s r difference <0.2), particularly for well-harmonized datasets. These results could help decide how to power future external validation studies.

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Trauma exposure (TE) and cognitive flexibility (CF) are risk factors for self-injurious thoughts and behaviors (SITBs). However, it is unknown whether these risk factors contribute to mechanisms associated with distinct categories of SITBs. The current study examined the potential moderating role of TE in the relationships between CF and multiple SITBs, including active suicidal ideation (SI), passive SI, non-suicidal self-injury (NSSI), and history of suicide attempt (SA), among pre-adolescent children.

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Different types of early-life adversity have been associated with children’s brain structure and function. However, understanding the disparate influence of distinct adversity exposures on the developing brain remains a major challenge.

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Twin births are related with maternal and fetal adverse outcomes. Little was known about the comparability of the cognitive, behavioral development and brain structure between twins and singletons in early adolescence. This retrospective cohort study was based on data from the United States population-based, prospective, longitudinal observational Adolescent Brain Cognitive Development study. Children with complete twin status information were enrolled, and the exposure variable was twin status. Primary outcomes were cognitive, behavioral development and brain structure in early adolescence. Cognitive and behavioral outcomes were assessed by using the NIH Toolbox and Child Behavioral Checklist, respectively. Brain structure was evaluated by the cortical thickness, area, and volume extracted from the magnetic resonance imaging (MRI) data. Subgroup analyses were conducted by prematurity, birth weight, with sibling, genetic profiles, and twin types (zygosity). From 1st September 2016 to 15th November 2018, 11545 children (9477 singletons and 2068 twins) aged 9-10 years were enrolled. Twins showed mildly lower cognitive performance (|t|> 5.104, P-values < 0.001, False Discovery Rate [FDR] < 0.001), better behavioral outcome (|t|> 2.441, P-values < 0.015, FDR < 0.042), such as lower scores for multiple psychiatric disorders and behavioral issues, and smaller cortical volume (t = - 3.854, P-values < 0.001, FDR < 0.001) and cortical area (t = - 3.872, P-values < 0.001, FDR < 0.001). The observed differences still held when stratified for prematurity, birth weight, presence of siblings, genetic profiles, and twin types (zygosity). Furthermore, analyses on the two-year follow-up data showed consistent results with baseline data. Twin status is associated with lower cognitive and better behavioral development in early adolescence accompanied by altered brain structure. Clinicians should be aware of the possible difference when generalizing results from adolescent twin samples to singletons.

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Decades of research document an association between neurocognitive dysfunction and externalizing behaviors, including rule-breaking, aggression, and impulsivity. However, there has been very little work that examines how multiple neurocognitive functions co-occur within individuals and which combinations of neurocognitive functions are most relevant for externalizing behaviors. Moreover, Latent Profile Analysis (LPA), a widely used method for grouping individuals in person-centered analysis, often struggles to balance the tradeoff between good model fit (splitting participants into many latent profiles) and model interpretability (using only a few, highly distinct latent profiles). To address these problems, we implemented a non-parametric Bayesian form of LPA based on the Dirichlet process mixture model (DPM-LPA) and used it to study the relationship between neurocognitive functioning and externalizing behaviors in adolescents participating in the Adolescent Brain Cognitive Development Study. First, we found that DPM-LPA outperformed conventional LPA, revealing more distinct profiles and classifying participants with higher certainty. Second, latent profiles extracted from DPM-LPA were differentially related to externalizing behaviors: profiles with deficits in working memory, inhibition, and/or language abilities were robustly related to different expressions of externalizing. Together, these findings represent a step towards addressing the challenge of finding novel ways to use neurocognitive data to better describe the individual. By precisely identifying and specifying the variation in neurocognitive and behavioral patterns this work offers an innovative empirical foundation for the development of assessments and interventions that address these costly behaviors.

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Stress is associated with increased vulnerability to psychosis, yet the mechanisms that contribute to these effects are poorly understood. Substantial literature has linked reduced hippocampal volume to both psychosis risk and early life stress. However, less work has explored the direct and indirect effects of stress on psychosis through the hippocampus in preclinical samples- when vulnerability for psychosis is accumulating. The current paper leverages the Adolescent Brain Cognitive Development (ABCD) Study sample to examine whether objective psychosocial stressors, specifically adverse childhood experiences (ACE), are linked to vulnerability for psychosis, measured by psychotic-like experiences (PLE) severity, in late childhood and early adolescence, both directly and indirectly through the deleterious effects of stress on the hippocampus. Baseline data from 11,728 individuals included previously examined and validated items to assess ACE exposure, hippocampal volume, and PLE severity – a developmentally appropriate metric of risk for psychosis. Objective psychosocial stress exposure in childhood was associated with elevated PLE severity during the transition from childhood to adolescence. Hippocampal volume was significantly reduced in individuals with greater PLE severity and greater childhood stress exposure compared to peers with low symptoms or low stress exposure. These findings are consistent with a hippocampal vulnerability model of psychosis risk. Stress exposure may cumulatively impact hippocampal volume and may also reflect a direct pathway of psychosis risk. Objective psychosocial stress should be considered as a treatment target that may impact neurodevelopment and psychosis risk.

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Attention-deficit/hyperactivity disorder (ADHD) is among the most prevalent, inheritable, and heterogeneous childhood-onset neurodevelopmental disorders. Children with a hereditary background of ADHD have heightened risk of having ADHD and persistent impairment symptoms into adulthood. These facts suggest distinct familial-specific neuropathological substrates in ADHD that may exist in anatomical components subserving attention and cognitive control processing pathways during development. The objective of this study is to investigate the topological properties of the gray matter (GM) structural brain networks in children with familial ADHD (ADHD-F), non-familial ADHD (ADHD-NF), as well as matched controls. A total of 452 participants were involved, including 132, 165 and 155 in groups of ADHD-F, ADHD-NF and typically developed children, respectively. The GM structural brain network was constructed for each group using graph theoretical techniques with cortical and subcortical structures as nodes and correlations between volume of each pair of the nodes within each group as edges, while controlled for confounding factors using regression analysis. Relative to controls, children in both ADHD-F and ADHD-NF groups showed significantly higher nodal global and nodal local efficiencies in the left caudal middle frontal gyrus. Compared to controls and ADHD-NF, children with ADHD-F showed distinct structural network topological patterns associated with right precuneus (significantly higher nodal global efficiency and significantly higher nodal strength), left paracentral gyrus (significantly higher nodal strength and trend toward significantly higher nodal local efficiency) and left putamen (significantly higher nodal global efficiency and trend toward significantly higher nodal local efficiency). Our results for the first time in the field provide evidence of familial-specific structural brain network alterations in ADHD, that may contribute to distinct clinical/behavioral symptomology and developmental trajectories in children with ADHD-F.

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Parental incarceration is an adverse childhood experience that inequitably burdens families of color and affects millions of U.S. children and adolescents. Although racialized disparities in exposure to parental incarceration are often acknowledged, researchers have yet to examine whether manifestations of racism may affect the link between parental incarceration and youth outcomes. This study provides a first look at how parental incarceration relates to health vulnerabilities in the Adolescent Brain Cognitive Development (ABCD) study, an ongoing, population-based study of U.S. children born between 2006 and 2008. We start by describing exposure to parental incarceration and then examine how parental incarceration, state-level racial prejudice, and discrimination relate to health risks among 9191 White (66%), Black (19%), or Hispanic (15%) youth. Consistent with what we know about pervasive racialized disparities in the U.S. criminal legal system, we find that 19.3% of Black children in our sample have experienced parental incarceration, followed by 7.8% of Hispanic children, and 4.8% of White children. Results of multilevel mixed models further indicate that parental incarceration was associated with increased health risks among White children whereas family economic hardship and discrimination experiences were more robustly associated with health vulnerabilities among Black and Hispanic children. Additional analyses explored whether parental incarceration was associated with other outcomes among Black and Hispanic children, revealing increased risk for behavior problems contingent upon parental incarceration and discrimination for Black children and Hispanic boys. Among Hispanic girls, parental incarceration was associated with increased risk of behavior problems in states with higher levels of racism. Results suggest that parental incarceration contributes to risk among early adolescents across racialized groups, but that the specific toll it takes depends on outcomes assessed and the context in which it occurs.

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Girls and boys presenting disruptive behavior disorders (DBDs) display differences in white matter microstructure (WMM) relative to typically developing (TD) sex-matched peers. Boys with DBDs are at increased risk for traumatic brain injuries (TBIs), which are also known to impact WMM. This study aimed to disentangle associations of WMM with DBDs and TBIs.

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The current study investigated the prospective relationships between parental monitoring, family conflict, and screen time across six screen time modalities in early adolescents in the USA.

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Having multiple previous generations with depression in the family increases offspring risk for psychopathology. Parental depression has been associated with smaller subcortical brain volumes in their children, but whether two prior generations with depression is associated with further decreases is unclear.

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A single dose of psilocybin, a psychedelic that acutely causes distortions of space-time perception and ego dissolution, produces rapid and persistent therapeutic effects in human clinical trials. In animal models, psilocybin induces neuroplasticity in cortex and hippocampus. It remains unclear how human brain network changes relate to subjective and lasting effects of psychedelics. Here we tracked individual-specific brain changes with longitudinal precision functional mapping (roughly 18 magnetic resonance imaging visits per participant). Healthy adults were tracked before, during and for 3 weeks after high-dose psilocybin (25 mg) and methylphenidate (40 mg), and brought back for an additional psilocybin dose 6-12 months later. Psilocybin massively disrupted functional connectivity (FC) in cortex and subcortex, acutely causing more than threefold greater change than methylphenidate. These FC changes were driven by brain desynchronization across spatial scales (areal, global), which dissolved network distinctions by reducing correlations within and anticorrelations between networks. Psilocybin-driven FC changes were strongest in the default mode network, which is connected to the anterior hippocampus and is thought to create our sense of space, time and self. Individual differences in FC changes were strongly linked to the subjective psychedelic experience. Performing a perceptual task reduced psilocybin-driven FC changes. Psilocybin caused persistent decrease in FC between the anterior hippocampus and default mode network, lasting for weeks. Persistent reduction of hippocampal-default mode network connectivity may represent a neuroanatomical and mechanistic correlate of the proplasticity and therapeutic effects of psychedelics.

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Suicide is the third-leading cause of death among US adolescents. Environmental and lifestyle factors influence suicidal behavior and can inform risk classification, yet quantifying and incorporating them in risk assessment presents a significant challenge for reproducibility and clinical translation.

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Adolescents exhibit remarkable heterogeneity in the structural architecture of brain development. However, due to limited large-scale longitudinal neuroimaging studies, existing research has largely focused on population averages, and the neurobiological basis underlying individual heterogeneity remains poorly understood. Here we identify, using the IMAGEN adolescent cohort followed up over 9 years (14-23 y), three groups of adolescents characterized by distinct developmental patterns of whole-brain gray matter volume (GMV). Group 1 show continuously decreasing GMV associated with higher neurocognitive performances than the other two groups during adolescence. Group 2 exhibit a slower rate of GMV decrease and lower neurocognitive performances compared with Group 1, which was associated with epigenetic differences and greater environmental burden. Group 3 show increasing GMV and lower baseline neurocognitive performances due to a genetic variation. Using the UK Biobank, we show these differences may be attenuated in mid-to-late adulthood. Our study reveals clusters of adolescent neurodevelopment based on GMV and the potential long-term impact.

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Lack of sleep has been found to be associated with cognitive impairment in children, yet the neural mechanism underlying this relationship remains poorly understood. To address this issue, this study utilized the data from the Adolescent Brain Cognitive Development (ABCD) study ( = 4930, aged 9-10), involving their sleep assessments, cognitive measures, and functional magnetic resonance imaging (fMRI) during an emotional n-back task. Using partial correlations analysis, we found that the out-of-scanner cognitive performance was positively correlated with sleep duration. Additionally, the activation of regions of interest (ROIs) in frontal and parietal cortices for the 2-back versus 0-back contrast was positively correlated with both sleep duration and cognitive performance. Mediation analysis revealed that this activation significantly mediated the relationship between sleep duration and cognitive function at both individual ROI level and network level. After performing analyses separately for different sexes, it was revealed that the mediation effect of the task-related activation was present in girls ( = 2546). These findings suggest that short sleep duration may lead to deficit in cognitive function of children, particularly in girls, through the modulation of frontoparietal activation during working memory load.

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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.

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To progress adolescent mental health research beyond our present achievements – a complex account of brain and environmental risk factors without understanding neurobiological embedding in the environment – we need methods to unveil relationships between the developing brain and real-world environmental experiences.

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This study aimed to investigate the relationships between four types of perceived discrimination (based on race/ethnicity, nationality/country of origin, gender identity, weight/body size), individually and cumulatively; positive childhood experiences (PCEs); and behavioral symptoms among pre-adolescent youth.

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The human subcortex plays a pivotal role in cognition and is widely implicated in the pathophysiology of many psychiatric disorders. However, the heritability of functional gradients based on subcortico-cortical functional connectivity remains elusive. Here, leveraging twin functional MRI (fMRI) data from both the Human Connectome Project (n = 1023) and the Adolescent Brain Cognitive Development study (n = 936) datasets, we construct large-scale subcortical functional gradients and delineate an increased principal functional gradient pattern from unimodal sensory/motor networks to transmodal association networks. We observed that this principal functional gradient is heritable, and the strength of heritability exhibits a heterogeneous pattern along a hierarchical unimodal-transmodal axis in subcortex for both young adults and children. Furthermore, employing a machine learning framework, we show that this heterogeneous pattern of the principal functional gradient in subcortex can accurately discern the relationship between monozygotic twin pairs and dizygotic twin pairs with an accuracy of 76.2% (P < 0.001). The heritability of functional gradients is associated with the anatomical myelin proxied by MRI-derived T1-weighted/T2-weighted (T1w/T2w) ratio mapping in subcortex. This study provides new insights into the biological basis of subcortical functional hierarchy by revealing the structural and genetic properties of the subcortical functional gradients.

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Sex and gender are associated with human behavior throughout the life span and across health and disease, but whether they are associated with similar or distinct neural phenotypes is unknown. Here, we demonstrate that, in children, sex and gender are uniquely reflected in the intrinsic functional connectivity of the brain. Somatomotor, visual, control, and limbic networks are preferentially associated with sex, while network correlates of gender are more distributed throughout the cortex. These results suggest that sex and gender are irreducible to one another not only in society but also in biology.

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Sex and gender differences exist in the prevalence and clinical manifestation of common brain disorders. Identifying their neural correlates may help improve clinical care.

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Research has documented that adolescent sleep is impacted by various stressors, including interpersonal experiences and structural disadvantage. This study extends existing knowledge by empirically examining interconnected individual experiences of structural inequity and assessing its association with subjective and objective sleep outcomes.

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To determine prospective associations between bedtime screen use behaviors and sleep outcomes one year later in a national study of early adolescents in the United States.

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Childhood obesity and its adverse health consequences have risen worldwide, with low socioeconomic status increasing the risk in high-income countries like the US. Understanding the interplay between childhood obesity, cognition, socioeconomic factors, and the brain is crucial for prevention and treatment. Using data from the ABCD study, we investigated how body mass index (BMI) relates to brain structural and functional connectivity metrics. Obese/overweight children (n = 2,356) were more likely to live in poverty and exhibited lower cognitive performance compared to normal weight children (n = 4,754). Higher BMI was associated with multiple brain measures that were strongest for lower longitudinal diffusivity in corpus callosum, increased activity in cerebellum, insula, and somatomotor cortex, and decreased functional connectivity in multimodal brain areas, with effects more pronounced among children from low-income families. Notably, nearly 80% of the association of low income and 70% of the association of impaired cognition on BMI were mediated by higher brain activity in somatomotor areas. Increased resting activity in somatomotor areas and decreased structural and functional connectivity likely contribute to the higher risk of overweight/obesity among children from low-income families. Supporting low-income families and implementing educational interventions to improve cognition may promote healthy brain function and reduce the risk of obesity.

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Sleep is essential to adolescent development. Sexual and gender minority (SGM; e.g., lesbian, gay, bisexual, transgender) adults are at high risk for poor sleep, partially due to minority stress (e.g., discrimination). However, sleep has rarely been studied among SGM adolescents. In a national sample of early adolescents, we analyzed sexual minority (SM) and gender minority (GM) identity, gender incongruence, and gender nonconformity in association with sleep and tested minority and general stressors as mediators.

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There is a dearth of statistical models that adequately capture the total signal attributed to whole-brain imaging features. The total signal is often widely distributed across the brain, with individual imaging features exhibiting small effect sizes for predicting neurobehavioral phenotypes. The challenge of capturing the total signal is compounded by the distribution of neurobehavioral data, particularly responses to psychological questionnaires, which often feature zero-inflated, highly skewed outcomes. To close this gap, we have developed a novel Variational Bayes algorithm that characterizes the total signal captured by whole-brain imaging features for zero-inflated outcomes. Our zero-inflated variance (ZIV) estimator estimates the fraction of variance explained (FVE) and the proportion of non-null effects (PNN) from large-scale imaging data. In simulations, ZIV demonstrates superior performance over other linear models. When applied to data from the Adolescent Brain Cognitive Development (ABCD) Study, we found that whole-brain imaging features contribute to a larger FVE for externalizing behaviors compared to internalizing behaviors. Moreover, focusing on features contributing to the PNN, ZIV estimator localized key neurocircuitry associated with neurobehavioral traits. To the best of our knowledge, the ZIV estimator is the first specialized method for analyzing zero-inflated neuroimaging data, enhancing future studies on brain-behavior relationships and improving the understanding of neurobehavioral disorders.

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This paper investigated the effects of prenatal drug exposure (PDE), childhood trauma (CT), and their interactions on the neurobiological markers for emotion processing.

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Efficiency of evidence accumulation (EEA), an individual’s ability to selectively gather goal-relevant information to make adaptive choices, is thought to be a key neurocomputational mechanism associated with cognitive functioning and transdiagnostic risk for psychopathology. However, the neural basis of individual differences in EEA is poorly understood, especially regarding the role of largescale brain network dynamics. We leverage data from 5198 participants from the Human Connectome Project and Adolescent Brain Cognitive Development Study to demonstrate a strong association between EEA and flexible adaptation to cognitive demand in the “task-positive” frontoparietal and dorsal attention networks. Notably, individuals with higher EEA displayed divergent task-positive network activation across n-back task conditions: higher activation under high cognitive demand (2-back) and lower activation under low demand (0-back). These findings suggest that brain networks’ flexible adaptation to cognitive demands is a key neural underpinning of EEA.

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The need to select mediators from a high dimensional data source, such as neuroimaging data and genetic data, arises in much scientific research. In this work, we formulate a multiple-hypothesis testing framework for mediator selection from a high-dimensional candidate set, and propose a method, which extends the recent development in false discovery rate (FDR)-controlled variable selection with knockoff to select mediators with FDR control. We show that the proposed method and algorithm achieved finite sample FDR control. We present extensive simulation results to demonstrate the power and finite sample performance compared with the existing method. Lastly, we demonstrate the method for analyzing the Adolescent Brain Cognitive Development (ABCD) study, in which the proposed method selects several resting-state functional magnetic resonance imaging connectivity markers as mediators for the relationship between adverse childhood events and the crystallized composite score in the NIH toolbox.

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Adolescence is a period in which mental health problems emerge. Research suggests that the COVID-19 lockdown may have worsened emotional and behavioral health.

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Canonical correlation analysis (CCA) and partial least squares correlation (PLS) detect linear associations between two data matrices by computing latent variables (LVs) having maximal correlation (CCA) or covariance (PLS). This study compared the similarity and generalizability of CCA- and PLS-derived brain-behavior relationships. Data were accessed from the baseline Adolescent Brain Cognitive Development (ABCD) dataset ( > 9,000, 9-11 years). The brain matrix consisted of cortical thickness estimates from the Desikan-Killiany atlas. Two phenotypic scales were examined separately as the behavioral matrix; the Child Behavioral Checklist (CBCL) subscale scores and NIH Toolbox performance scores. Resampling methods were used to assess significance and generalizability of LVs. LV for the CBCL brain relationships was found to be significant, yet not consistently stable or reproducible, across CCA and PLS models (singular value: CCA = .13, PLS = .39, < .001). LV for the NIH brain relationships showed similar relationships between CCA and PLS and was found to be stable and reproducible (singular value: CCA = .21, PLS = .43, < .001). The current study suggests that stability and reproducibility of brain-behavior relationships identified by CCA and PLS are influenced by the statistical characteristics of the phenotypic measure used when applied to a large population-based pediatric sample.

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Prenatal substance exposure (PSE) can lead to various harmful outcomes for the developing fetus and is linked to many emotional, behavioral, and cognitive difficulties later in life. Therefore, examination of the relationship between the development of associated brain structures and PSE is important for the development of more specific or new preventative methods.

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Neuroimaging-based prediction of neurocognitive measures is valuable for studying how the brain’s structure relates to cognitive function. However, the accuracy of prediction using popular linear regression models is relatively low. We propose a novel deep regression method, namely , that allows full supervision for contrastive learning in regression tasks using diffusion MRI tractography. TractoSCR performs supervised contrastive learning by using the absolute difference between continuous regression labels (i.e., neurocognitive scores) to determine positive and negative pairs. We apply TractoSCR to analyze a large-scale dataset including multi-site harmonized diffusion MRI and neurocognitive data from 8,735 participants in the Adolescent Brain Cognitive Development (ABCD) Study. We extract white matter microstructural measures using a fine parcellation of white matter tractography into fiber clusters. Using these measures, we predict three scores related to domains of higher-order cognition (general cognitive ability, executive function, and learning/memory). To identify important fiber clusters for prediction of these neurocognitive scores, we propose a permutation feature importance method for high-dimensional data. We find that TractoSCR obtains significantly higher accuracy of neurocognitive score prediction compared to other state-of-the-art methods. We find that the most predictive fiber clusters are predominantly located within the superficial white matter and projection tracts, particularly the superficial frontal white matter and striato-frontal connections. Overall, our results demonstrate the utility of contrastive representation learning methods for regression, and in particular for improving neuroimaging-based prediction of higher-order cognitive abilities. Our code will be available at: https://github.com/SlicerDMRI/TractoSCR.

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Neuroimaging has been widely adopted in psychiatric research, with hopes that these non-invasive methods will provide important clues to the underpinnings and prediction of various mental health symptoms and outcomes. However, the translational impact of neuroimaging has not yet reached its promise, despite the plethora of computational methods, tools, and datasets at our disposal. Some have lamented that too many psychiatric neuroimaging studies have been underpowered with respect to sample size. In this review, we encourage this discourse to shift from a focus on sheer increases in sample size to more thoughtful choices surrounding experimental study designs. We propose considerations at multiple decision points throughout the study design, data modeling and analysis process that may help researchers working in psychiatric neuroimaging boost power for their research questions of interest without necessarily increasing sample size. We also provide suggestions for leveraging multiple datasets to inform each other and strengthen our confidence in the generalization of findings to both population-level and clinical samples. Through a greater emphasis on improving the quality of brain-based and clinical measures rather than merely quantity, meaningful and potentially translational clinical associations with neuroimaging measures can be achieved with more modest sample sizes in psychiatry.

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The inequitable distribution of economic resources and exposure to adversity between racial groups contributes to mental health disparities within the United States. Consideration of the potential neurodevelopmental consequences, however, has been limited particularly for neurocircuitry known to regulate the emotional response to threat. Characterizing the consequences of inequity on threat neurocircuitry is critical for robust and generalizable neurobiological models of psychiatric illness. Here we use data from the Adolescent Brain and Cognitive Development Study 4.0 release to investigate the contributions of individual and neighborhood-level economic resources and exposure to discrimination. We investigate the potential appearance of race-related differences using both standard methods and through population-level normative modeling. We show that, in a sample of white and Black adolescents, racial inequities in socioeconomic factors largely contribute to the appearance of race-related differences in cortical thickness of threat neurocircuitry. The race-related differences are preserved through the use of population-level models and such models also preserve associations between cortical thickness and specific socioeconomic factors. The present findings highlight that such socioeconomic inequities largely underlie race-related differences in brain morphology. The present findings provide important new insight for the generation of generalizable neurobiological models of psychiatric illness.

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Alcohol, the most consumed drug in the United States, is associated with various psychological disorders and abnormal personality traits. Despite extensive research on adolescent alcohol consumption, the impact of early alcohol sipping patterns on changes in personality and mental health over time remains unclear. There is also limited information on the latent trajectory of early alcohol sipping, beginning as young as 9-10 years old. The dorsal anterior cingulate cortex (dACC) is crucial for cognitive control and response inhibition. However, the role of the dACC remains unclear in the relationship between early alcohol sipping and mental health outcomes and personality traits over time.

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Obese adults are often reported to have smaller brain volumes than their non-obese peers. Whether this represents evidence of accelerations in obesity-driven atrophy or is instead a legacy of developmental differences established earlier in the lifespan remains unclear. This study aimed to investigate whether early-life differences in adiposity explain differences in numerous adult brain traits commonly attributed to mid-life obesity. We utilised a two-sample lifecourse Mendelian randomization study in 37,501 adults recruited to UK Biobank (UKB) imaging centers from 2014, with secondary analyses in 6,996 children assessed in the Adolescent Brain Cognitive Development Study (ABCD) recruited from 2018. Exposures were genetic variants for childhood (266 variants) and adult (470 variants) adiposity derived from a GWAS of 407,741 UKB participants. Primary outcomes were adult total brain volume; grey matter volume, thickness, and surface area; white matter volume and hyperintensities; and hippocampus, amygdala, and thalamus volumes at mean age 55 in UKB. Secondary outcomes were equivalent childhood measures collected at mean age 10 in ABCD. In UKB, individuals who were genetically-predicted to have had higher levels of adiposity in childhood were found to have multiple smaller adult brain volumes relative to intracranial volume (e.g. z-score difference in normalised brain volume per category increase in adiposity [95%CI] = -0.20 [-0.28, -0.12]; p = 4 × 10-6). These effect sizes remained essentially unchanged after accounting for birthweight or current adult obesity in multivariable models, whereas most observed adult effects attenuated towards null (e.g. adult z-score [95%CI] for total volume = 0.06 [-0.05,0.17]; p = 0.3). Observational analyses in ABCD showed a similar pattern of changes already present in those with a high BMI by age 10 (z-score [95%CI] = -0.10 [-0.13, -0.07]; p = 8 × 10-13), with follow-up genetic risk score analyses providing some evidence for a causal effect already at this early age. Sensitivity analyses revealed that many of these effects were likely due to the persistence of larger head sizes established in those who gained excess weight in childhood (childhood z-score [95%CI] for intracranial volume = 0.14 [0.05,0.23]; p = 0.002), rather than smaller brain sizes per se. Our data suggest that persistence of early-life developmental differences across the lifecourse may underlie numerous neuroimaging traits commonly attributed to obesity-related atrophy in later life.

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Transparency can build trust in the scientific process, but scientific findings can be undermined by poor and obscure data use and reporting practices. The purpose of this work is to report how data from the Adolescent Brain Cognitive Development (ABCD) Study has been used to date, and to provide practical recommendations on how to improve the transparency and reproducibility of findings.

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Evidence suggests that adolescents engage in less physical activity during the summer break. Less is known regarding physical activity during the summer months of the COVID-19 pandemic.

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To investigate relationships of breastfeeding duration with brain structure and adiposity markers in youth and how these relationships are modified by neighborhood socioeconomic environments (SEEs).

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Psychotic-like experiences (PLEs) during adolescence can lead to psychotic disorders. Digital media usage has been suggested to link to PLEs, but research is limited on how different types of screen exposure may differentially relate to PLEs over time. This study aimed to examine longitudinal associations between screen usage patterns and PLEs in adolescents.

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Cross-sectional studies in adults have demonstrated associations between early life adversity (ELA) and reduced hippocampal volume, but the timing of these effects is not clear. The present study sought to examine whether ELA predicts changes in hippocampal volume over time in a large sample of early adolescents.

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The brain undergoes extensive development during late childhood and early adolescence. Cortical thinning is a prominent feature of this development, and some researchers have suggested that differences in cortical thickness may be related to internalizing symptoms, which typically increase during the same period. However, research has yielded inconclusive results. We utilized a new method that estimates the combined effect of individual differences in vertex-wise cortical thickness on internalizing symptoms. This approach allows for many small effects to be distributed across the cortex and avoids the necessity of correcting for multiple tests. Using a sample of 8763 children aged 8.9 to 11.1 from the ABCD study, we decomposed the total variation in caregiver-reported internalizing symptoms into differences in cortical thickness, additive genetics, and shared family environmental factors and unique environmental factors. Our results indicated that individual differences in cortical thickness accounted for less than 0.5% of the variation in internalizing symptoms. In contrast, the analysis revealed a substantial effect of additive genetics and family environmental factors on the different components of internalizing symptoms, ranging from 06% to 48% and from 0% to 34%, respectively. Overall, while this study found a minimal association between cortical thickness and internalizing symptoms, additive genetics, and familial environmental factors appear to be of importance for describing differences in internalizing symptoms in late childhood. RESEARCH HIGHLIGHTS: We utilized a new method for modelling the total contribution of vertex-wise individual differences in cortical thickness to internalizing symptoms in late childhood. The total contribution of individual differences in cortical thickness accounted for <0.5% of the variance in internalizing symptoms. Additive genetics and shared family environmental variation accounted for 17% and 34% of the variance in internalizing symptoms, respectively. Our results suggest that cortical thickness is not an important indicator for internalizing symptoms in childhood, whereas genetic and environmental differences have a substantial impact.

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Childhood externalizing psychopathology is heterogeneous. Symptom variability in conduct disorder (CD), oppositional defiant disorder (ODD), attention-deficit/hyperactivity disorder (ADHD), and callous-unemotional (CU) traits designate different subgroups of children with externalizing problems who have specific treatment needs. However, CD, ODD, ADHD, and CU traits are highly comorbid. Studies need to generate insights into shared versus unique risk mechanisms, including through the use of functional magnetic resonance imaging (fMRI). In this study, we tested whether symptoms of CD, ODD, ADHD, and CU traits were best represented within a bifactor framework, simultaneously modeling shared (i.e., general externalizing problems) and unique (i.e., symptom-specific) variance, or through a four-correlated factor or second-order factor model. Participants ( = 11,878, age, = 9 years) were from the Adolescent Brain and Cognitive Development Study. We used questionnaire and functional magnetic resonance imaging data (emotional N-back task) from the baseline assessment. A bifactor model specifying a general externalizing and specific CD, ODD, ADHD, and CU traits factors demonstrated the best fit. The four-correlated and second-order factor models both fit the data well and were retained for analyses. Across models, reduced right amygdala activity to fearful faces was associated with more general externalizing problems and reduced dorsolateral prefrontal cortex activity to fearful faces was associated with higher CU traits. ADHD scores were related to greater right nucleus accumbens activation to fearful and happy faces. Results give insights into risk mechanisms underlying comorbidity and heterogeneity within externalizing psychopathology. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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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.

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To investigate relationships among different physical health problems in a large, sociodemographically diverse sample of 9-to-10-year-old children and determine the extent to which perinatal health factors are associated with childhood physical health problems.

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Though research indicates that certain aspects of adverse neighborhood conditions may influence weight development in childhood and adolescence, it is unknown if the Child Opportunity Index (COI), a composite measure of 29 indicators of neighborhood conditions, is associated with weight outcomes in adolescence. We hypothesized that lower COI would be associated with higher overweight and obesity in cross-sectional and longitudinal modeling in a national sample of 9 year olds and 10 year olds and that this association would be different by sex.

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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.

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Previous work has found increased endorsement of psychotic-like experiences (PLEs) among marginalized racial and ethnic groups. According to social determinants frameworks, marginalized groups are at increased risk for exposure to socio-environmental risk factors, including systemic factors (e.g., poverty and poor housing conditions), and social stressors (e.g., discrimination). We examine the extent to which environmental risk factors and stress account for associations between racial/ethnic groups with PLEs.

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Persistence and distress distinguish more clinically significant psychotic-like experiences (PLEs) from those that are less likely to be associated with impairment and/or need for care. Identifying risk factors that differentiate clinically relevant PLEs early in development is important for improving our understanding of the etiopathogenesis of these experiences. Machine learning analyses examined the most important baseline factors distinguishing persistent distressing PLEs.

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Previous studies have linked adolescent motherhood to adverse neurodevelopmental outcomes in offspring, yet the sex-specific effect and underlying mechanisms remain unclear.

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To assess the prevalence of various media parenting practices and identify their associations with early adolescent screen time and problematic social media, video game, and mobile phone use.

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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.

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Neuroimaging is a popular method to map brain structural and functional patterns to complex human traits. Recently published observations cast doubt upon these prospects, particularly for prediction of cognitive traits from structural and resting state functional magnetic resonance imaging (MRI). We leverage baseline data from thousands of children in the Adolescent Brain Cognitive DevelopmentSM Study to inform the replication sample size required with univariate and multivariate methods across different imaging modalities to detect reproducible brain-behavior associations. We demonstrate that by applying multivariate methods to high-dimensional brain imaging data, we can capture lower dimensional patterns of structural and functional brain architecture that correlate robustly with cognitive phenotypes and are reproducible with only 41 individuals in the replication sample for working memory-related functional MRI, and ~ 100 subjects for structural and resting state MRI. Even with 100 random re-samplings of 100 subjects in discovery, prediction can be adequately powered with 66 subjects in replication for multivariate prediction of cognition with working memory task functional MRI. These results point to an important role for neuroimaging in translational neurodevelopmental research and showcase how findings in large samples can inform reproducible brain-behavior associations in small sample sizes that are at the heart of many research programs and grants.

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There is an imminent need to identify neural markers during preadolescence that are linked to developing depression during adolescence, especially among youth at elevated familial risk. However, longitudinal studies remain scarce and exhibit mixed findings. Here we aimed to elucidate functional connectivity (FC) patterns among preadolescents that interact with familial depression risk to predict depression two years later.

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Area deprivation index (ADI) has been shown to be associated with reduced hippocampal volume (HV) among youths. The social environment may interact with the association between ADI and HV.

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Racial discrimination is a psychosocial stressor associated with youths’ risk for psychiatric symptoms. Scarce data exist on the moderating role of amygdalar activation patterns among Black youths in the US.

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Background and aims
Poor cardiovascular health has been linked to a higher risk of cognitive decline in adults, however this relation is not well established among adolescents. The purpose of this analysis was to test the associations of cardiovascular health behaviors (diet, physical activity, nicotine use, and sleep health) and health indicators (body mass index, blood lipids, blood glucose, blood pressure) with adolescents’ brain development and executive and cognitive function.

Methods
We included 978 individuals from the Adolescent Brain and Cognitive Development (ABCD) Study who completed the year 2 follow-up assessment. Analysis was limited to those with complete data on cardiovascular health behaviors and health indicators which were used to compute composite cardiovascular health scores. Outcomes included estimates of general cognitive ability, executive function, and learning/memory through the NIH Toolbox neurocognitive battery, and MRI-derived brain morphometry. Associations were estimated by multilevel linear regression models using random effects.

Results
The mean (SD) age was 11.9 (0.2) years, 44.9% were girls, and 53.4% were white race/ethnicity. Individuals with more favorable cardiovascular health behaviors showed higher executive cognitive function scores (β = 0.170; CI 95%, 0.076 to 0.265; p = .001). Overall cardiovascular health was associated with a higher measure of executive cognitive function (β = 0.209; CI 95%, 0.067 to 0.351; p = .002) and total whole brain cortical volume (β = 480.1; CI 95%, 4.7 to 955.6; p = .003).

Conclusion
Our findings reveal positive associations between adolescents’ cardiovascular health behaviors and overall cardiovascular health with cognitive and executive function and brain cortical volume. Although our study is cross-sectional, the findings from a representative group of early adolescents add to the existing evidence suggesting a relationship between cardiovascular and brain health.

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Sociodemographic and lifestyle factors (sleep, physical activity, and sedentary behavior) may predict obesity risk in early adolescence; a critical period during the life course. Analyzing data from 2971 participants (M = 11.94, SD = 0.64 years) wearing Fitbit Charge HR 2 devices in the Adolescent Brain Cognitive Development (ABCD) Study, glass box machine learning models identified obesity predictors from Fitbit-derived measures of sleep, cardiovascular fitness, and sociodemographic status. Key predictors of obesity include identifying as Non-White race, low household income, later bedtime, short sleep duration, variable sleep timing, low daily step counts, and high heart rates (AUC = 0.726). Findings highlight the importance of inadequate sleep, physical inactivity, and socioeconomic disparities, for obesity risk. Results also show the clinical applicability of wearables for continuous monitoring of sleep and cardiovascular fitness in adolescents. Identifying the tipping points in the predictors of obesity risk can inform interventions and treatment strategies to reduce obesity rates in adolescents.

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Ambient air pollution is a neurotoxicant with hypothesized immune-related mechanisms. Adolescent brain structural and functional connectivity may be especially vulnerable to ambient pollution due to the refinement of large-scale brain networks during this period, which vary by sex and have important implications for cognitive, behavioral, and emotional functioning. In the current study we explored associations between air pollutants, immune markers, and structural and functional connectivity in early adolescence by leveraging cross-sectional sex-stratified data from the Adolescent Brain Cognitive Development℠ Study®.

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Air pollution exposure has been associated with adverse cognitive and mental health outcomes in children, adolescents, and adults, although youth may be particularly susceptible given ongoing brain development. However, the neurodevelopmental mechanisms underlying the associations among air pollution, cognition, and mental health remain unclear. We examined the impact of particulate matter (PM2.5) on resting-state functional connectivity (rsFC) of the default mode network (DMN) and three key attention networks: dorsal attention, ventral attention, and cingulo-opercular. Longitudinal changes in rsFC within/between networks were assessed from baseline (9-10 years) to the two-year follow-up (11-12 years) in 10,072 youth (M+SD=9.93+0.63 years; 49% female) from the Adolescent Brain Cognitive Development (ABCD®) study. Annual ambient PM2.5 concentrations from the 2016 calendar year were estimated using hybrid ensemble spatiotemporal models. RsFC was estimated using functional neuroimaging. Linear mixed models were used to test associations between PM2.5 and change in rsFC over time while adjusting for relevant covariates (e.g., age, sex, race/ethnicity, parental education, family income) and other air pollutants (O3, NO2). A PM2.5 x time interaction was significant for within-network rsFC of the DMN such that higher PM2.5 concentrations were associated with a smaller increase in rsFC over time. Further, significant PM2.5 x time interactions were observed for between-network rsFC of the DMN and all three attention networks, with varied directionality. PM2.5 exposure was associated with alterations in the development and equilibrium of the DMN-a network implicated in self-referential processing-and anti-correlated attention networks, which may impact trajectories of cognitive and mental health symptoms across adolescence.

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The influence of socioeconomic disparities and multidimensional stressors on youth tobacco and marijuana use is recognized; however, the extent of these effects varies among different racial groups. Understanding the racial differences in the factors influencing substance use is crucial for developing tailored interventions aimed at reducing disparities in tobacco and marijuana use among adolescents.

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During adolescence major shifts in sleep and circadian systems occur with a notable circadian phase delay. Yet, the circadian influence on pain during early adolescence is largely unknown. Using 2 years of data from the Adolescent Brain Cognitive Development study, we investigated the impact of chronotype on pain incidence, moderate-to-severe pain, and multiregion pain 1 year later in U.S. adolescents. Based on the Munich ChronoType Questionnaire, chronotype was calculated as the midpoint between sleep onset and offset on free days, corrected for sleep debt over the week. Adolescents reported pain presence over the past month, and if present, rated pain intensity (0-10 numerical rating scale; ≥ 4 defined as moderate-to-severe pain) and body site locations (Collaborative Health Outcomes Information Registry Body Map; ≥2 regions defined as multiregion pain). Three-level random intercept logistic regression models were specified for each pain outcome, adjusting for baseline sociodemographic and developmental characteristics. Among 5991 initially pain-free adolescents (mean age 12.0 years, SD 0.7), the mean chronotype was 3:59 am (SD 97 minutes), and the 1-year incidence of pain, moderate-to-severe pain, and multiregion pain was 24.4%, 15.2%, and 13.5%, respectively. Each hour later chronotype at baseline was associated with higher odds of developing any pain (odds ratio [OR] = 1.06, 95% confidence interval [CI] = 1.01, 1.11), moderate-to-severe pain (OR = 1.10, 95% CI = 1.05-1.17), and multiregion pain (OR = 1.08, 95% CI = 1.02-1.14) during 1-year follow-up. In this diverse U.S. adolescent sample, later chronotype predicted higher incidence of new-onset pain.

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Associations between brain and obesity are bidirectional: changes in brain structure and function underpin over-eating, while chronic adiposity leads to brain atrophy. Investigating brain-obesity interactions across the lifespan can help better understand these relationships. This study explores the interaction between obesity and cortical morphometry in children, young adults, adults, and older adults. We also investigate the genetic, neurochemical, and cognitive correlates of the brain-obesity associations. Our findings reveal a pattern of lower cortical thickness in fronto-temporal brain regions associated with obesity across all age cohorts and varying age-dependent patterns in the remaining brain regions. In adults and older adults, obesity correlates with neurochemical changes and expression of inflammatory and mitochondrial genes. In children and older adults, adiposity is associated with modifications in brain regions involved in emotional and attentional processes. Thus, obesity might originate from cognitive changes during early adolescence, leading to neurodegeneration in later life through mitochondrial and inflammatory mechanisms.

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Exposure to outdoor particulate matter (PM) represents a ubiquitous threat to human health, and particularly the neurotoxic effects of PM from multiple sources may disrupt neurodevelopment. Studies addressing neurodevelopmental implications of PM exposure have been limited by small, geographically limited samples and largely focus either on macroscale cortical morphology or postmortem histological staining and total PM mass. Here, we leverage residentially assigned exposure to six, data-driven sources of PM and neuroimaging data from the longitudinal Adolescent Brain Cognitive Development Study (ABCD Study®), collected from 21 different recruitment sites across the United States. To contribute an interpretable and actionable assessment of the role of air pollution in the developing brain, we identified alterations in cortical microstructure development associated with exposure to specific sources of PM using multivariate, partial least squares analyses. Specifically, average annual exposure (i.e., at ages 8-10 years) to PM from biomass burning was related to differences in neurite development across the cortex between 9 and 13 years of age.

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Underreporting of adolescent substance use is a known issue, with format of assessment (in-person vs. remote) a potentially important factor. We investigate whether being assessed remotely (via phone or videoconference) versus in-person affects youth report of substance use patterns, attitudes, and access, hypothesizing remote visits would garner higher levels of substance use reporting and more positive substance use attitudes. We used the Adolescent Brain and Cognitive Development [ABCD] Study data between 2021-2022 during the COVID-19 pandemic. Participants chose whether to complete assessments in-person (n=615; 49% female; mean=13.9; 57% White) or remotely (n=1,467; 49% female, mean=13.7; 49% White). Regressions predicted substance use patterns, attitudes, and access, by visit format, controlling for relevant sociodemographic factors. Effect sizes and standardized mean differences are presented. 17% of adolescent participants reported any level of substance use. Youth interviewed remotely reported more negative expectancies of alcohol and cannabis. In addition, those queried remotely were less likely to endorse use), sipping alcohol, eating cannabis), and reported less curiosity or intent to try alcohol, though these differences did not survive an adjustment for multiple testing. Effect sizes ranged from small to medium. Preliminary evidence suggests youth completing remote visits were more likely to disclose negative expectancies toward alcohol and cannabis. Effect sizes were modest, though 37 of 39 variables examined trended toward restricted reporting during remote sessions. Thus, format of substance use assessment should be controlled for, but balanced by other study needs (e.g., increasing accessibility of research to all sociodemographic groups).

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An extensive literature shows that race information can impact cognitive performance. Two key findings include an attentional bias to Black racial cues in U.S. samples and diminished recognition of other-race faces compared to same-race faces in predominantly White adult samples. Yet face stimuli are increasingly used in psychological research often unrelated to race (Conley et al., 2018) or without consideration for how race information may influence cognitive performance, especially among developmental participants from different racial groups. In the current study we used open-access data from the Adolescent Brain Cognitive Development (ABCD) Study® 4.0.1 release to test for developmentally similar other- and same-race effects of Black and White face stimuli on attention, working memory, and recognition memory in 9- and 10-year-old Black and White children (n=5,659) living in the U.S. Black and White children showed better performance when attending to Black versus White faces. We also show an advantage in recognition memory of same-race compared to other-race faces in White children that did not generalize to Black children. Together the findings highlight how race information, even when irrelevant to an experiment, may indirectly lead to misinterpretation of group differences in cognitive performance in children of different racial backgrounds.

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There are numerous studies examining differences in the experience of disorders and symptoms of psychopathology in adolescents across racial or ethnic groups and sex. Though there is substantial research exploring potential factors that may influence these differences, few studies have considered the potential contribution of measurement properties to these differences. Therefore, this study examined whether there are differences across racial or ethnic groups and sex in the measurement of psychopathology, assessed in mother-reported behavior of 9-11 year old youth from the Adolescent Brain Cognitive Development study sample using updated Child Behavior Checklist scales (CBCL; Achenbach & Rescorla, 2001). Tests of measurement invariance of the CBCL utilized the higher order factor structure identified by Michelini et al. (2019) using this same Adolescent Brain Cognitive Development cohort. The dimensions include internalizing, somatoform, detachment, externalizing, and neurodevelopmental problems. The configural model had a good-to-excellent fit on all subscales of the CBCL across racial or ethnic groups and sex. The metric and scalar models fit just as well as the configural models, indicating that the scales are measuring the same constructs across racial or ethnic groups and sex and are not influenced by measurement properties of items on the CBCL, although some high-severity response options were not endorsed for youth in all racial or ethnic groups. These findings support the use of the CBCL in research examining psychopathology in racially or ethnically diverse samples of youth. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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To examine whether adverse parental legal system involvement (incarceration, arrest) was associated with suicide risk, accounting for other adverse childhood experiences, and whether there was a moderating relationship between positive childhood experiences (PCEs) and parental legal system involvement in suicide risk.

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To investigate the prevalence and sociodemographic associations of online dating in a demographically diverse U.S. national cohort of early adolescents.

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Academic performance plays a crucial role in long-term educational attainment and occupational function. Chronotype refers to an individual’s daily tendencies for times for waking, activity, and sleep. Social jetlag reflects the mismatch between an individual’s chronotype and their social schedule. Because school typically starts early in the morning, later chronotype is often associated with daytime sleepiness, insufficient sleep, and poor academic performance. However, the relationship between academic performance, chronotype, and social jetlag has not been extensively examined in large samples like the Adolescent Brain Cognitive Development (ABCD) study. We hypothesized that greater social jetlag would predict poorer cognitive and academic performance. Year 2 (ages 11-14) cross-sectional data from the ABCD cohort ( = 6,890 adolescents) were used to evaluate academic performance (i.e. self-reported past year grades), NIH Toolbox cognitive performance measures, chronotype, and social jetlag from the Munich Chronotype Questionnaire. We found that later chronotype and greater social jetlag predicted poorer cognitive and academic performance with small effect sizes. Our findings emphasize the importance of individual differences in chronotype and social jetlag when designing class schedules, as aligning school activities with student optimal sleep-wake times may contribute to improved academic performance.

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According to the Physical Activity Guidelines Advisory Committee Scientific Report, limited evidence is available on sedentary behaviors (screen time) and their joint associations with physical activity (steps) for cardiovascular health in adolescence. The objective of this study was to identify joint associations of screen time and physical activity categories with cardiovascular disease (CVD) risk factors (blood pressure, hemoglobin A1c, cholesterol) in adolescence.

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Anxiety and depression in children and adolescents warrant special attention as a public health concern given their devastating and long-term effects on development and mental health. Multiple factors, ranging from genetic vulnerabilities to environmental stressors, influence the risk for the disorders. This study aimed to understand how environmental factors and genomics affect children and adolescents anxiety and depression across three cohorts: Adolescent Brain and Cognitive Development Study (US, age of 9-10; N=11,875), Consortium on Vulnerability to Externalizing Disorders and Addictions (INDIA, age of 6-17; N=4,326) and IMAGEN (EUROPE, age of 14; N=1888). We performed data harmonization and identified the environmental impact on anxiety/depression using a linear mixed-effect model, recursive feature elimination regression, and the LASSO regression model. Subsequently, genome-wide association analyses with consideration of significant environmental factors were performed for all three cohorts by mega-analysis and meta-analysis, followed by functional annotations. The results showed that multiple environmental factors contributed to the risk of anxiety and depression during development, where early life stress and school support index had the most significant and consistent impact across all three cohorts. In both meta, and mega-analysis, SNP rs79878474 in chr11p15 emerged as a particularly promising candidate associated with anxiety and depression, despite not reaching genomic significance. Gene set analysis on the common genes mapped from top promising SNPs of both meta and mega analyses found significant enrichment in regions of chr11p15 and chr3q26, in the function of potassium channels and insulin secretion, in particular Kv3, Kir-6.2, SUR potassium channels encoded by the KCNC1, KCNJ11, and ABCCC8 genes respectively, in chr11p15. Tissue enrichment analysis showed significant enrichment in the small intestine, and a trend of enrichment in the cerebellum. Our findings provide evidences of consistent environmental impact from early life stress and school support index on anxiety and depression during development and also highlight the genetic association between mutations in potassium channels, which support the stress-depression connection via hypothalamic-pituitary-adrenal axis, along with the potential modulating role of potassium channels.

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The association between body mass index (BMI) and binge-eating disorder (BED) is well-established. However, data on the extent to which BMI is associated with progression from binge-eating behavior into BED among adolescents are limited, which was the aim of this investigation. Participants were 9,964 U.S. adolescents from the Adolescent Brain Cognitive Development (ABCD) Study, aged 9-13 at the time of study enrollment. A computerized parent-reported assessment was used to establish adolescents’ binge-eating behaviors and BED. Cox proportional hazards models adjusting for sociodemographic covariates were used to examine prospective associations between BMI and likelihood of BED onset among a) adolescents with binge-eating behavior, and b) adolescents with no binge-eating behavior. Of 975 adolescents who met study criteria for binge-eating behavior, 89 (9.1%) subsequently met study criteria for BED. Of 8,989 adolescents with no binge-eating behavior, 82 (0.9%) subsequently met study criteria for BED. BMI percentile was significantly associated with the likelihood of BED onset in participants with [ adjusted HR =1.03 (1.00, 1.06)] and participants without [adjusted HR =1.05 (1.03, 1.07)] binge-eating behavior. Results were also significant when examining BMI as a dichotomous predictor (above and below 85 percentile) among those with [adjusted HR =2.60 (1.00, 6.68) and those without [adjusted HR =6.01 (3.90, 11.10)] binge-eating behavior. Overall, results indicate that elevated BMI is prospectively associated with a greater risk for BED onset among U.S. adolescents with or without binge-eating behavior. Adolescents with a higher BMI may benefit from screening for binge eating, and prevention/early intervention strategies to mitigate the risk for developing BED.

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Adolescent depression is characterized by diverse symptom trajectories over time and has a strong genetic influence. Research has determined genetic overlap between depression and other psychiatric conditions; investigating the shared genetic architecture of heterogeneous depression trajectories is crucial for understanding disease etiology, prediction, and early intervention.

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Children tend to endorse psychotic-like experiences (PLEs) at higher rates than adults, although little is known about how specific symptom endorsement changes across the span of development. Here we take an observational approach to examine trends in PLE endorsement by age in two non-clinical samples: one of school-aged children and another of late adolescents and early adults.

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Patients and healthcare professionals overestimate the risks of using antidepressants during pregnancy. According to current literature, approximately half of people stop taking an anti-depressant medication when they become pregnant. Discontinuing antidepressants during pregnancy increases risks of postnatal relapses. Factors like socioeconomic status, education, and planned pregnancies play a role in the decision to continue antidepressant medication, which can worsen disparities in maternal and child health. Our aim was to identify the sociodemographic factors associated with antidepressant continuation after awareness of pregnancy.

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Impulsivity undergoes a normative developmental trajectory from childhood to adulthood and is thought to be driven by maturation of brain structure. However, few large-scale studies have assessed associations between impulsivity, brain structure, and genetic susceptibility in children. In 9112 children ages 9-10 from the ABCD study, we explored relationships among impulsivity (UPPS-P impulsive behavior scale; delay discounting), brain structure (cortical thickness (CT), cortical volume (CV), and cortical area (CA)), and polygenic scores for externalizing behavior (PGS). Both higher UPPS-P total scores and more severe delay-discounting had widespread, low-magnitude associations with smaller CA in frontal and temporal regions. No associations were seen between impulsivity and CV or CT. Additionally, higher PGS was associated with both higher UPPS-P scores and with smaller CA and CV in frontal and temporal regions, but in non-overlapping cortical regions, underscoring the complex interplay between genetics and brain structure in influencing impulsivity. These findings indicate that, within large-scale population data, CA is significantly yet weakly associated with each of these impulsivity measures and with polygenic risk for externalizing behaviors, but in distinct brain regions. Future work should longitudinally assess these associations through adolescence, and examine associated functional outcomes, such as future substance use and psychopathology.

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In past decades, the positive role of self-control in students’ academic success has attracted plenty of scholarly attention. However, fewer studies have examined the link between adolescents’ neural development of the inhibitory control system and their academic achievement, especially using a longitudinal approach. Moreover, less is known about the role of parents in this link. Using large-scale longitudinal data from the Adolescent Brain Cognitive Development (ABCD) study (N = 9574; mean age = 9.94 years at baseline, SD = .63; 50% girls), the current study took an integrative biopsychosocial approach to explore the longitudinal link between early adolescents’ fronto-striatal connectivity and their academic achievement, with attention to the moderating role of parental warmth. Results showed that weaker intrinsic connectivity between the frontoparietal network and the striatum was associated with early adolescents’ worse academic achievement over 2 years during early adolescence. Notably, parental warmth moderated the association between fronto-striatal connectivity and academic achievement, such that weaker fronto-striatal connectivity was only predictive of worse academic achievement among early adolescents who experienced low levels of parental warmth. Taken together, the findings demonstrate weaker fronto-striatal connectivity as a risk factor for early adolescents’ academic development and highlight parental warmth as a protective factor for academic development among those with weaker connectivity within the inhibitory control system.

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The prevalence, pathophysiology, and long-term outcomes of COVID-19 (post-acute sequelae of SARS-CoV-2 [PASC] or “Long COVID”) in children and young adults remain unknown. Studies must address the urgent need to define PASC, its mechanisms, and potential treatment targets in children and young adults.

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Cannabidiol (CBD) is rising in popularity, including as a potential medicinal product. Yet data on use of commercial CBD for medicinal or health reasons in adolescents are lacking. In this study we aim to detail characteristics of adolescents given commercial CBD for health reasons (health CBD [hCBD]) and to investigate predictors of use. The Adolescent Brain Cognitive Development (ABCD) Study is a population-based cohort study following U.S. healthy, community-based adolescents annually, with data from 2018 to 2022 (11- to 15-year-olds; =11,189). Participants and caregivers completed questionnaires, including whether adolescents were given CBD with parent or doctor’s permission. Participants reported past-month pain, attention problems, externalizing symptoms, internalizing symptoms, and total mental health problems. Caregivers reported youth sociodemographics, sleep problems, whether the youth had mental health treatment or sought medical treatment, and rules about recreational cannabis use. We describe youth given hCBD, and run generalized estimating equations predicting odd ratios (ORs) and 95% confidence intervals of adolescents given hCBD by mental health, physical health, or sociodemographics of factors. Of the 11,189 participants across up to three waves of data, 48% were female. Mean age across waves was 12.8 years old (SD=1). In total, 307 (2.8%) were given hCBD. Common administration methods were oil (42%), topical (31%), and edibles (29%). Increased hCBD odds were associated with being older (OR=1.32 [1.17-1.49]), White (relative to Black, OR=05.97 [2.81-12.65] or Hispanic, OR=1.82 [1.17-2.82]), parents with some college (relative to no high school diploma, OR=3.55 [1.09-11.6]), internalizing symptoms (OR=1.81 [1.13-2.91]), mental health treatment (OR=1.76 [1.3-2.38]), pain (OR=1.38 [1.09-1.76]), medical treatment (OR=1.39 [1.08-1.79]), and sleep problems (OR=1.69 [1.27-2.25]). Rules against recreational cannabis decreased odds of hCBD (OR=1.75 [1.30-2.36]). Findings indicate some healthy adolescents are given hCBD, and predictors of use include mental and physical health concerns, being White, older, and parents with some college education. Providers should ask if their youth patients are being given CBD medicinally, and transparently discuss potential benefits, consequences, and unknowns of CBD.

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Among 3614 youth who were 9 to 12 years old and initially did not have overweight or obesity (12% [n = 385] developed overweight or obesity), we examined the natural progression of weight gain and brain structure development during a 2-year period with a high risk for obesity (e.g., pre- and early adolescence) to determine the following: 1) whether variation in maturational trajectories of the brain regions contributes to weight gain; and/or 2) whether weight gain contributes to altered brain development.

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To assess the association between transgender or gender-questioning identity and screen use (recreational screen time and problematic screen use) in a demographically diverse national sample of early adolescents in the U.S.

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The purpose of the study was to investigate the association between discrimination by multiple sources (i.e., teachers, students, and other adults) and early adolescents’ behavioral problems (i.e., internalizing, externalizing, and attention problems), also considering the protective role of parental warmth in this association.

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