Research Publications

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Weight discrimination is associated with adverse outcomes, including eating disorder (ED) symptoms, but few longitudinal studies have investigated this relationship in early adolescence. We examined the prospective association of weight discrimination with ED symptoms one year later in early adolescents, and the extent to which this association was moderated by body mass index (BMI) percentile and sex.

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Childhood brain development involves dynamic remodeling shaped by genetic influences contributing to long-term neurodevelopmental variation. Here we report integrative analyses of over 8600 children, using 7 brain imaging-derived phenotype (IDP) modalities, polygenic scores (PGS) of 33 complex traits, and 266 cognitive and psychological phenotypes. Most brain IDPs show low-to-moderate SNP-based heritability, lower than typically observed in adults. Sparse generalized canonical correlation analysis reveals positive associations between cognitive-related PGS and structural MRI features (e.g., total grey matter and ventral diencephalon volumes) and N-back task-related activation, while PGS for ADHD, depression, and neuroticism showed negative associations. Cognitive PGS also correlates positively with diffusion MRI metrics (streamline counts, fractional anisotropy in subcortical-frontal tracts and inferior parietal-subcortical tracts), whereas health-risk PGS (e.g., BMI, ADHD) correlates negatively. This study delineates key gene-brain-behavior associations in preadolescence, providing a multivariate dissection of the polygenic architecture underlying neurodevelopment.

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Prior work suggests that living among people who share similar identities may be protective against psychosis, but the meaning of this association in the context of racialized residential segregation is not well understood. We investigated the effects of evenness and exposure residential segregation on persistent, distressing psychotic-like experiences (PLEs) in Black and White adolescents living in urban neighborhoods with high and low social cohesion in the United States. Data from the Adolescent Brain Cognitive Development Study were used (N = 5871), measuring evenness and exposure segregation in metropolitan statistical areas using the Dissimilarity Index (DI) and Exposure-Interaction Index (EII), respectively. Multi-level log binomial generalized estimating equations estimated the relative risk of PLEs by exposure to each domain of segregation. Evenness and exposure segregation were associated with risk of PLE (DI: aRR = 1.11, 95 % CI 1.06-1.17; EII: aRR = 0.82, 95 % CI 0.78-0.87). When both domains were present in the same model, the effect of evenness, but not exposure, was attenuated (DI: aRR = 0.98, 95 % CI 0.92-1.05; EII: aRR = 0.81, 95 % 0.75-0.88). These associations were not statistically significantly different for levels of race (p-values ranged 0.08-0.86) or neighborhood social cohesion (p-values ranged 0.16-0.56). Sensitivity analysis indicated the main effect was not altered by duration of exposure. Lower exposure to exposure domain segregation may be protective against risk of PLEs in young adolescents in urban areas. The association was similar in comparisons of Black-White racial groups and high-low neighborhood social cohesion groups.

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Adverse childhood experiences (ACEs) are linked with risky sexual behaviors. However, we do not know how various ACE dimensions influence adolescent sexual behavior, especially behaviors that are precursors to early sexual intercourse. Using the data from the Adolescent Brain and Cognitive Development Study, we conducted LCA on 13 ACE measures assessed at ages 9-11 and analyzed how these latent classes relate to romantic relationships and early non-coital sexual behaviors (kissing and touching) at ages 11-12. We identified six distinct classes: Low ACEs (48.4%), Material Hardship and Community Violence (19.2%), Parental Dysfunction (18.6%), Parental Dysfunction and Criminal Justice Involvement (6.5%), Community and Peer Violence, Material Hardship, and Parental Dysfunction (6.4%), and Household Violence, Parental Dysfunction and Child Abuse (0.6%). The last three classes exhibited a higher likelihood of engaging in romantic and early non-coital sexual behaviors than adolescents in the Low ACEs class. The diverse impacts of ACE patterns suggest we should implement trauma-informed early sexuality education programs.

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Distinguishing those at risk of making a suicide attempt from those who experience only suicidal ideations remains a significant clinical challenge. Longitudinal studies during early adolescence may provide insight into altered brain and behavioral developmental trajectories among those who develop suicide behaviors (SB). Here, we applied linear mixed effects regression models to several global brain volumes and psychiatric/behavioral measures from the Adolescent Brain Cognitive Development (ABCD) Study. We analyzed data from baseline up until the two-year follow-up, when participants were roughly 10 to 12 years of age. Individuals who had either ever endorsed or developed SB exhibited the greatest reductions in cortical gray brain matter volume. Those who developed SB exhibited the greatest increase in DSM5-depression scores and were the only group that maintained their levels of Behavioral Activation System (BAS) Fun-Seeking behaviors. Finally, we applied a Cross-Lagged Panel Modelling approach to the whole ABCD sample and found that baseline total cortical gray matter structure significantly predicted variation in BAS Fun-Seeking behaviors at the two-year follow-up, providing evidence supportive of a potential causal relationship between these two measures. Altogether, our findings suggest that differences in total cortical gray matter volume at 9-10 years of age may impact the development of behavioral approach systems. Altered development of behavioral approach systems and depressive symptoms distinguish youth who developed suicide behaviors during early adolescence.

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Background
Understanding attention deficit/hyperactivity disorder (ADHD) medication patterns is crucial for optimizing treatment outcomes. There are limited data on racial, ethnic, gender and socioeconomic treatment differences across longitudinal national samples.

Methods
Secondary data analysis of baseline through 3rd-year follow-up (2016–2020) data from the Adolescent Brain Cognitive Development Study (ABCD) (N = 11,875). Data were collected from 21 US sites, to reflect national demographic diversity. Complete case panel included 9708 children aged 9/10 at baseline and 12/13 at 3rd-year follow up. Sociodemographic factors (sex, race, ethnicity, household income), ADHD medication use (stimulants and non-stimulants), and ADHD severity were examined.

Results
By the 3rd-year follow-up, 13% of children used ADHD medications. Females were more likely to never have received medications compared to males (92% vs. 82%, odds ratio [OR] 2.34, 95% confidence interval [CI] 2.05–2.67, p < 0.001). Females exhibited lower mean ADHD severity scores, though the difference diminished over time. Asian (95% vs. 87%, OR 2.83, 95% CI 1.41–5.38, p < 0.001) and Hispanic children (90% vs. 86%, OR 1.39, 95% CI 1.17–1.64, p < 0.001) were more likely to have never received medications compared to White and non-Hispanic children. Black children were more likely to discontinue medications (9% vs. 5%, OR 1.84, 95% CI 1.45–2.33, p < 0.001) compared to White children, although this was not significant after adjusting for sociodemographic factors. Children in lower income households were more likely to have clinically significant ADHD but less likely to receive and remain on medications compared to those from higher income households.

Conclusions
Significant differences exist in ADHD medication use patterns among US children based on sex, race, ethnicity, and socioeconomic status. Addressing these differences is essential to ensure equitable access to treatment.

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Childhood family income is a powerful predictor of academic achievement and mental health. Here, we ask whether children living in poverty who succeed academically are subsequently protected from, or at risk for, internalizing symptoms. Prior research indicates that children in poverty with better academic performance tend to have higher temporal coupling between the Lateral Frontoparietal Network (LFPN) and Default Mode Network (DMN) than lower-performing children in poverty. An open question is whether higher LFPN-DMN coupling has maladaptive long-term consequences for mental health for this population. In this pre-registered longitudinal study, we analyzed data from 10,829 children (1931 in poverty) in the ABCD study across four time points (ages 9-13). Higher grades correlated with fewer internalizing symptoms concurrently; this association was more pronounced for children below poverty. Longitudinally, higher LFPN-DMN related to more internalizing symptoms two years later for children in poverty in particular. Thus, although higher academic performance was associated with better mental health outcomes for all children, the specific pattern of LFPN-DMN connectivity that supports academic resilience among children in poverty may be a risk factor for developing internalizing symptoms. These findings highlight the complex nature of academic resilience in the context of structural inequity.

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To compare brain MRI outcomes between children who play American football vs non-contact sport controls testing the hypotheses that history (primary) and duration (secondary) of football participation would be associated with differences in cortical thickness, subcortical volume, resting state functional connectivity, and white matter diffusivity.

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Impaired musical rhythm abilities and developmental speech-language related disorders are biologically and clinically intertwined. Prior work examining their relationship has primarily used small samples; here, we studied associations at population-scale by conducting the largest systematic epidemiological investigation to date (total N = 39,358). Based on existing theoretical frameworks, we predicted that rhythm impairment would be a significant risk factor for speech-language disorders in the general adult population. Findings were consistent across multiple independent datasets and rhythm subskills (including beat synchronization and rhythm discrimination), and aggregate meta-analyzed data showed that non-linguistic rhythm impairment is a modest but consistent risk factor for developmental speech, language, and reading disorders (OR = 1.33 [1.18 – 1.49]; p < .0001). Further, cross-trait polygenic score analyses (total N = 7180) indicated shared genetic architecture between musical rhythm and reading abilities, suggesting genetic pleiotropy between musicality and language-related phenotypes.

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Many mental health problems are neurodevelopmental in nature and have an onset during childhood. These disorders are associated with neural abnormalities, but it is unclear when these emerge and how this relates to the development of different mental health problems.

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Reading ability depends on multiple cognitive skills, including decoding and language comprehension, which can vary widely across individuals-even among those with similarly low reading performance. To better understand the brain basis of this variability, we used connectome-based predictive modeling (CPM) to identify large-scale functional connectivity patterns associated with reading and language skills in a population-based sample. Cross-sectional CPM models were trained using functional connectivity data from the Adolescent Brain and Cognitive Development study (n = 6894) and tested in two independent cohorts: the New Haven Lexinome Project and the Genes, Reading, and Dyslexia study (combined n = 136). Functional connectivity measures included both resting- and task-based scans. Reading and language were measured with psychometric tests of word reading and vocabulary, respectively. CPM models significantly predicted reading (r = .24) and language (r = .28) scores in the discovery sample and generalized to an external sample (rs = .23 and .19). Anatomically, the reading and language models showed significant overlap, with the medial frontal network emerging as most predictive in both. However, these models exhibited distinct generalization patterns to children with decoding versus language comprehension difficulties-classified using 20th percentile cutoffs-highlighting their neural specificity. Reading and language models included distinct connectivity signatures and generalized differently to children with decoding versus language comprehension difficulties. These findings demonstrate that although reading and language abilities are behaviorally related, they are supported by partially distinct neural architectures. Integrating behavioral and neuroimaging data may clarify specific brain-behavior relationships and inform more tailored interventions for children with reading and language difficulties.

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Pain, sleep disturbances, and substance use are common in adolescence, with research indicating that genetic and environmental factors account for variation in each of these behavioral and health outcomes. Moreover, pain, sleep disturbances, and substance use often co-occur during adolescence. However, research has not examined whether there is genetic and/or environmental covariation across these constructs in early adolescence or in diverse samples. To address these gaps, we examined genetic and environmental covariation in pain, sleep disturbances, and substance use intent in early adolescence.

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This study assesses the relation between screen time, problematic media use behaviors, and clinical concerns (internalizing and externalizing problems) and suicidal ideation and non-suicidal self-injury within race/ethnicity and sex in the Adolescent Brain Cognitive Development (ABCD) Study (youth aged 11 to 12; = 10,052). Understanding behaviors around screens (problematic media use), rather than focusing on screen time alone is useful in guiding clinical recommendations. In this analysis, regression models indicated that problematic media use consistently predicted clinical concerns with a larger effect size than screen media use. When examining how problematic media use and screen media use related to clinical concerns along domains of race/ethnicity and sex, problematic media use was a more consistent predictor of clinical concerns than screen media use for almost every race/ethnicity (except American Indian/Alaska Native participants). Problematic media use was also a consistent predictor of clinical concerns for both males and females, with some difference in screen media use predictors. This study has implications for the utility of assessing screen media use in research on clinical concerns in youth, and further suggests that researchers and clinicians should consider behaviors around screens in addition to screen time itself when assessing for impact on mental health.

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Intrinsic brain dynamics play a fundamental role in cognitive function, but their development is incompletely understood. We investigated pubertal changes in temporal fluctuations of intrinsic network topologies (focusing on the strongest connections and coordination patterns) and signals, in an early longitudinal sample from the Adolescent Brain Cognitive Development (ABCD) study, with resting-state fMRI ( = 4,099 at baseline; = 3,376 at follow-up [median age = 10.0 (1.1) and 12.0 (1.1) years; = 2,116 with both assessments]). Reproducible, inverse associations between low-frequency signal and topological fluctuations were estimated ( < 0.05, = -0.20 to -0.02, 95% confidence interval (CI) = [-0.23, -0.001]). Signal (but not topological) fluctuations increased in somatomotor and prefrontal areas with pubertal stage ( < 0.03, = 0.06-0.07, 95% CI = [0.03, 0.11]), but decreased in orbitofrontal, insular, and cingulate cortices, as well as cerebellum, hippocampus, amygdala, and thalamus ( < 0.05, = -0.09 to -0.03, 95% CI = [-0.15, -0.001]). Higher temporal signal and topological variability in spatially distributed regions were estimated in girls. In racial/ethnic minorities, several associations between signal and topological fluctuations were in the opposite direction of those in the entire sample, suggesting potential racial differences. Our findings indicate that during puberty, intrinsic signal dynamics change significantly in developed and developing brain regions, but their strongest coordination patterns may already be sufficiently developed and remain temporally consistent.

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The intersecting roles of immigrant status and socioeconomic status (SES) have not been a focal area for research in adolescent sleep. This study examined sleep disparities among early adolescents from immigrant and nonimmigrant families and whether SES moderated sleep disparities by immigrant status.

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Background
Although perceived threats in a child’s social environment, including in the family, school, and neighborhood, are known to increase risk for adolescent psychopathology, the underlying biological mechanisms remain unclear. To investigate, we examined whether perceived social threats were associated with the functional connectivity of large-scale cortical networks in early adolescence, and whether such connectivity differences mediated the development of subsequent mental health problems in youth.

Methods
Structural equation models were used to analyze data from 8,690 youth (50% female, 45% non-White, age 9–10 years) drawn from the large-scale, nationwide Adolescent Brain Cognitive Development study that has 21 clinical and research sites across the United States. Data were collected from 2016 to 2018.

Results
Consistent with Social Safety Theory, perceived social threats were prospectively associated with mental health problems both 6 months (standardized ) and 30 months () later. Perceived social threats predicted altered connectivity patterns within and between the default mode (DMN), dorsal attention (DAN), frontoparietal (FPN), and cingulo-opercular (CON) networks. In turn, hypoconnectivity within the DMN and FPN – and higher (i.e., less negative) connectivity between DMN-DAN, DMN-CON, and FPN-CON – mediated the association between perceived social threats and subsequent mental health problems.

Conclusions
Perceiving social threats in various environments may alter neural connectivity and increase the risk of psychopathology in youth. Therefore, parenting, educational, and community-based interventions that bolster social safety may be helpful.

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Externalizing behaviors in children, such as aggression, hyperactivity, and defiance, are influenced by complex interplays between genetic predispositions and environmental factors, particularly parental behaviors. Unraveling these intricate causal relationships can benefit from the use of robust data-driven methods.

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Psychological health issues resulting from emotional dysregulation such as anxiety and depression following pediatric concussion are a public health concern, but the underlying mechanisms remain unclear. Puberty opens a window of vulnerability for emotion dysregulation and a link between pediatric concussion and hormonal deficits has been reported. We investigated the association between pubertal hormones and psychological health in children with and without concussion history.

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A key challenge in predicting a person’s state of mind is that there are a wide range of contributing factors that each have a subtle, yet significant, influence on mental health. We applied data mining techniques to identify the most important risk factors for predicting current symptoms and longitudinal outcomes from the Adolescent Brain Cognitive Developmental study (n = 11,552). Our results consistently revealed that social conflicts were the strongest predictors of psychopathology, especially family fighting and reputational damage between peers. Sex-differences also emerged as a critical factor for predicting long-term mental health outcomes. Neuroimaging derived metrics were consistently the least informative. While these findings provide novel insight into the developmental origins of psychopathology, our best performing models could only explain up to 40% of the variation between individuals. Future research is needed to obtain a more complete understanding of all the factors that meaningfully contribute to mental health.

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Diagnostic criteria from the fifth edition of the does not fully address behavioral and clinical heterogeneity inherent to attention-deficit/hyperactivity disorder (ADHD); however, temperament-based profiles may help explain biological heterogeneity within the disorder. Temperament profiles have been defined and replicated among youths with ADHD and have demonstrated unique patterns of resting-state functional connectivity within a small sample. Two temperament profiles were identified by Kozlowski et al. in the Adolescent Brain Cognitive Development Study, and in the present study, we sought to replicate and validate documented resting-state patterns. Functional connectivity between bilateral amygdalae and 12 Gordon networks was compared between profiles and typically developing (TD) youths. Surgent youths demonstrated stronger right amygdala-dorsal attention network connectivity (β = 0.0434) and right amygdala-retrosplenial temporal network connectivity (β = 0.0442) compared with TD youths. Irritable youths demonstrated unique connectivity patterns compared with TD and surgent youths; however, effects did not survive correction for multiple comparisons. Findings provide support for future research examining temperament profiles among ADHD youths.

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Despite the evidence that sexual orientation can be fluid during early adolescence, there is a lack of research examining how sexual orientation self-identification evolves during this period. This study aims to explore age-specific patterns and trends in sexual orientation self-identification among a demographically diverse sample of U.S. adolescents.

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Identifying brain-based correlates of risk for future depression and anxiety severity in youth could improve prevention and treatment efforts. We tested whether connectome-based predictive modeling (CPM) based on resting-state functional connectivity (FC) at baseline: (a) predicts future depression and anxiety severity during childhood and (b) generalizes to adolescence. We used two independent, longitudinal datasets including children from the Adolescent Brain Cognitive Development (ABCD) study and adolescents from the Boston Adolescent Neuroimaging of Depression and Anxiety (BANDA). ABCD included a cohort of 11,875 children ages 9-11 years old, and BANDA enrolled 215 adolescents ages 14-17 years, of which ~70% reported a depressive or anxiety disorder. CPM with internal (within ABCD) and external validation (from ABCD to BANDA) used baseline whole-brain FC to predict depression and anxiety severity at a 1-year follow-up assessment. ABCD-derived functional connections, which we term “Symptoms Network”, were validated within BANDA to test model applicability in adolescence, which is a peak period for the emergence of internalizing disorders. Participants with complete data were included from ABCD (n = 3,718, 52.9% girls, ages 10.0 ± 0.6) and BANDA (n = 150, 61.3% girls, ages 15.4 ± 0.9). In ABCD, we found that FC predicted 1-year follow-up symptoms severity ( = 0.058, = 0.040), measured with the Child Behavior Checklist Anxious/Depressed subscale. External validation in BANDA indicated that the Symptoms Network predicted 1-year follow-up symptoms severity ( = 0.222, = 0.007), measured with the Revised Child Depression and Anxiety Scale -transformed total score. In both ABCD and BANDA, FC enhanced the prediction of future symptom severity beyond baseline clinical and demographic information (baseline severity, sex, and age), including when correcting for mean head motion. The ABCD-derived connections included contributions from somatomotor, attentional, and subcortical regions and were characterized by heterogeneous FC within adolescents, where the same region pairs were characterized by positive FC for some participants but by negative FC for others. In conclusion, FC may provide inroads for early identification of internalizing symptoms, which could inform preventative-intervention approaches prior to the emergence of affective disorders during a critical period of neuromaturation. However, the small effect sizes and heterogeneity in results underscore the challenges of employing brain-based biomarkers for clinical applications and emphasize the need for individualized approaches for understanding neurodevelopment and mental health.

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ADHD can impair children’s functioning. Socioeconomic and sociodemographic factors present barriers to treatment access and lead to disparate outcomes in children with ADHD. The purpose of this study was to describe trajectories of functional outcomes and ADHD symptom counts across 3 years and explore the moderating effects of income and race/ethnicity on these trajectories among U.S. children with ADHD.

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To examine whether pediatric mild traumatic brain injury (mTBI) is associated with differences in neurocognitive functioning among children.

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Cognitive control refers to a set of mental processes that enable individuals to flexibly and adaptively engage in goal-directed behavior. Adolescence is characterized by the emergence and subsequent rapid development of adult-like cognitive control abilities, and as such, there is great interest in understanding the neural basis of this maturational process. The goal of the present study was to investigate how the resting-state and task-based functional connectivity (FC) patterns of two brain networks implicated in control processes, the fronto-parietal network (FPN) and the cingulo-opercular network (CON), contribute to individual differences in the cognitive control abilities of young adolescents. Specifically, we examined whether the FPN and the CON play distinct roles in the implementation of control as evidenced by unique associations with individual differences in cognitive control. We further investigated whether coordinated processing between the FPN and the CON supports the successful engagement of cognitive control. We explored these issues in a large sample (n = 3,719) of 9-10 year olds drawn from the Adolescent Brain Cognitive Development℠ Study. Our results provide evidence that youth with higher levels of cognitive control showed more isolation of the FPN from other networks, while the CON showed greater flexibility in its connectivity with other networks across rest and task. We additionally demonstrate that individuals with higher levels of cognitive control exhibit greater differentiation between the FPN and the CON. Together, these findings support developmental theories highlighting the importance of neural processing within and across the FPN and the CON during adolescence.

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Caffeine is the most commonly used substance during gaming sessions. Despite health guidelines to avoid caffeine before adulthood, many adolescents use caffeine to compensate for lost sleep or prolong wakefulness to enhance gaming performance. The relationship between gaming and sleep is well-established, but the role of caffeine has been under-explored. This study investigated the potential mediating effect of caffeine use on the relationship between gaming duration/problems and sleep duration/difficulties in young adolescents.

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To advance our understanding of sleep among sexual-minority (SM) youth using actigraphy and to assess sleep as a buffer against minority stress (i.e., discrimination) for SM youth.

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The current study examined how early smartphone ownership impacts parent-child informant discrepancy of youth internalizing problems during the transition to adolescence. We used four waves of longitudinal data (Years 1-4) from the Adolescent Brain Cognitive Development (ABCD; Baseline = 11,878; White = 52.0%, Hispanic = 20.3%, Black = 15.0%, Asian = 2.1%, Other = 10.5%; Female = 47.8%). Across the full sample, significant parent-child informant discrepancy, such that parents underestimated child reports, appeared at Year 2 ( = 12.0) and increased across the remainder of the study ( = -0.21, = .042, < .001, 95%CI [-.29, -.23]). Further, multi-group models indicated that significant parent-child informant discrepancy emerged in the years following initial smartphone acquisition, whereas youth who remained non smartphone owners did not demonstrate such a pattern. Moreover, this discrepancy grew with additional years of smartphone ownership. This study contributes to the ongoing discourse on adolescent smartphone use and mental health by documenting a novel, longitudinally observed risk to timely parental detection of mental health problems by early smartphone ownership.

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A family history of depression is a well-documented risk factor for offspring psychopathology. However, the genetic mechanisms underlying the intergenerational transmission of depression remain unclear. We used genetic, family history, and diagnostic data from 11,875 9-10 year-old children from the Adolescent Brain Cognitive Development study. We estimated and investigated the children’s polygenic scores (PGSs) for 30 distinct traits and their association with a family history of depression (including grandparents and parents) and the children’s overall psychopathology through logistic regression analyses. We assessed the role of polygenic risk for psychiatric disorders in mediating the transmission of depression from one generation to the next. Among 11,875 multi-ancestry children, 8111 participants had matching phenotypic and genotypic data (3832 female [47.2%]; mean (SD) age, 9.5 (0.5) years), including 6151 [71.4%] of European-ancestry). Greater PGSs for depression (estimate = 0.129, 95% CI = 0.070-0.187) and bipolar disorder (estimate = 0.109, 95% CI = 0.051-0.168) were significantly associated with higher family history of depression (Bonferroni-corrected P < 0.05). Depression PGS was the only PGS that significantly associated with both family risk and offspring’s psychopathology, and robustly mediated the impact of family history of depression on several youth psychopathologies including anxiety disorders, suicidal ideation, and any psychiatric disorder (proportions mediated 1.39-5.87% of the total effect on psychopathology; FDR-corrected P < 0.05). These findings suggest that increased polygenic risk for depression partially mediates the associations between family risk for depression and offspring psychopathology, showing a genetic basis for intergenerational transmission of depression. Future approaches that combine assessments of family risk with polygenic profiles may offer a more accurate method for identifying children at elevated risk.

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Increases in impulsivity and negative affect (e.g., neuroticism) are common during adolescence and are both associated with risk for alcohol-use initiation and other risk behaviors. Whole-brain functional connectivity approaches-when coupled with appropriate cross-validation-enable identification of complex neural networks subserving individual differences in dimensional traits (hereafter referred to as ‘neural signatures’). Here, we analyzed functional connectivity data acquired at age 19 from individuals enrolled in a multisite European study of adolescent development (N ~ 1100) using connectome-based predictive modeling. Network anatomies of these dimensional phenotypes were compared with one another and with a previously identified alcohol-use risk network to identify shared and unique neural mechanisms. Models accurately predicted both impulsivity and neuroticism (r’s ~ 0.17-0.19, p’s < 0.05), and successfully generalized to an external sample. The impulsivity network was predominantly characterized by motor/sensory-related connections. By contrast, the neural signature of neuroticism was relatively more distributed across multiple canonical networks, including motor/sensory, default mode, subcortical, frontoparietal and cerebellar networks. Very few connections were common to both impulsivity and neuroticism networks. Moreover, while ~10-20% of the connections from each trait overlapped with the alcohol-use risk network, these connections were distinct between the two traits. This study for the first time identifies functional connectivity signatures of two common risk factors for alcohol-use in youth-impulsivity and neuroticism. Consistent with current equifinality-based conceptions of development, few connections predicted both impulsivity and neuroticism, indicating that the neural signatures of these two traits are relatively distinct despite both being implicated in alcohol-use risk and a wide array of behaviors.

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Previous studies have demonstrated that children with high irritability are at increased risk for suicidal ideations and behaviors. However, they have mostly relied on teacher reports and shown mixed findings regarding sex differences. We aimed to identify developmental trajectories of childhood irritability, test their direct and indirect (through psychopathology) associations with adolescent suicidal ideations and behaviors, and examine whether these associations differed by sex.

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Functional network connectivity (FNC) among large-scale brain networks-including the default mode (DMN), frontoparietal (FPN), and salience (SN) networks-have been increasingly implicated in transdiagnostic features of mental health disorders. In this study, we examined FNC patterns among the DMN, FPN, SN, and nine additional large-scale networks using resting-state functional MRI (rs-fMRI) data from 7760 adolescents (ages 10-13) from the Adolescent Brain Cognitive Development (ABCD) study. We investigated whether altered connectivity among these networks was associated with symptoms of social anxiety, as reported by caregivers at the two-year follow-up visit. Bayesian multiple regression revealed small, positive associations between social anxiety symptoms and FNC between the SN and cingulo-opercular network (β = 0.038, 95 % HDI = [0.003, 0.073]), the SN and retrosplenial temporal network (β = 0.031, 95 % HDI = [0.001, 0.061]), and the DMN and dorsal attention network (β = 0.046, 95 % HDI = [0.008, 0.085]). Female sex was also associated with greater social anxiety (β = 0.073, 95 % HDI = [0.026, 0.119]). These results highlight specific patterns of FNC that may serve as early neurobiological markers of social anxiety during adolescent development, offering insight into the network-level mechanisms that underlie risk for social anxiety in youth. SIGNIFICANCE STATEMENT: By analyzing resting-state fMRI data from 7760 adolescents, we identified small, positive effects of salience network-cingulo-opercular network and salience network-retrosplenial temporal network connectivity on social anxiety, and a small, positive effect of default mode network-dorsal attention network connectivity. These findings highlight the role of salience and default mode network dynamics in shaping adolescent social anxiety risk. With growing interest in transdiagnostic approaches to mental health, our results provide novel evidence that network-level variations can represent a core risk factor for social anxiety during early adolescence. This work suggests that functional network connectivity could yield clinically relevant biomarkers for early identification and targeted interventions for social anxiety in adolescence.

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During puberty, sex-specific processes shape distinct mental health outcomes. However, research on puberty and psychosis has been limited, and the findings are conflicting.

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To examine associations between low cognitive-performance and regional-and network-level brain changes at ages 9-10 in very-preterm, moderately-preterm, and full-term children, and explore whether these alterations predict ASD/ADHD symptoms at age 12.

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Adolescent neuroimaging studies of sex differences in the human brain predominantly examine average differences between males and females. This focus on mean differences without probing relative distributions and similarities may contribute to both conflation and overestimation of sex differences and sexual dimorphism in the developing human brain. We aimed to characterize the variance in brain macro- and micro-structure in early adolescence as it pertains to sex at birth using a large sample of 9-11-year-olds from the Adolescent Brain Cognitive Development (ABCD) Study (N = 7,723). For global and regional estimates of gray and white matter volume, cortical thickness, and white matter microstructure (i.e., fractional anisotropy and mean diffusivity), we examined: within- and between-sex variance, overlap between male and female distributions, inhomogeneity of variance, effect size, and CLES. We examined these sex differences using both unadjusted (raw) brain estimates and residualized brain estimates from mixed-effects modeling (adjusted) to account for variance better attributed to age, pubertal development, socioeconomic status, race, ethnicity, MRI scanner manufacturer, and total brain volume, where applicable. Contrary to the popular view of the brain as sexually dimorphic, we found high similarity and low difference between sexes in all regional measurements of brain structure examined after accounting for other sources of variance. However, the sex difference for adjusted total brain volume (TBV) had a medium effect size and a 71.9% probability that a randomly chosen male adolescent would have a larger brain than a randomly chosen female adolescent. All cortical and subcortical volumes showed significant inhomogeneity of variance between sexes, whereas a minority of brain regions showed significant sex differences in variance for cortical thickness, white matter volume, fractional anisotropy, and mean diffusivity. Previously reported sex differences in early adolescent regional human brain volume may, therefore, be driven by disparities in variance, rather than binary, sex-based phenotypes. This study builds upon previous findings illustrating the importance of considering variance when examining sex differences in brain structure.

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Sleep problems are common in adolescence and are associated with poorer mental and physical health. Parental factors may be associated with adolescent sleep, providing potential targets for sleep health interventions. Whether these associations are mediated through emotional regulation and screen use and whether they vary by adolescent sex remain unclear.

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Adverse childhood experiences (ACEs) are common and account for more than 25% of psychiatric disorders in youths, but the underlying neurobiological mechanisms associated with risk and resilience among children exposed to ACEs are poorly understood.

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Neighborhood adversity links to mental health and cognitive outcomes, but little is known about structural factors that may buffer these links. The current study addresses this gap by assessing the role of protective factors in the association of neighborhood deprivation, threat, and segregation with psychopathology symptoms and cognitive outcomes. Linear mixed models were run in ABCD sample participants (n = 5812) to test associations of neighborhood Area Deprivation Index (ADI; deprivation), crime (threat), and dissimilarity and interaction index (segregation) with attention difficulties, internalizing and externalizing symptoms, psychotic-like experiences (PLEs), and fluid and crystallized cognitive performance. School environment, neighborhood education child opportunity index, neighborhood cohesion, and green space were tested as moderators of the association of neighborhood adversity with outcomes. Higher neighborhood educational resources buffered the association of neighborhood deprivation with crystallized cognitive performance. The association of higher neighborhood crime with externalizing symptoms was weaker for youth in less supportive school environments. Further, higher neighborhood segregation was associated with internalizing symptoms more strongly for youth with more neighborhood educational resources. Taken together, results suggest adverse neighborhood environments are associated with higher psychopathology symptoms and lower cognitive performance. Access of neighborhood educational resources could buffer links of neighborhood deprivation and cognitive performance. While evidence of protective links was not widespread, studying these patterns is necessary for understanding possible environmental contributors to mental health and cognitive function. A video abstract of this article can be viewed at https://www.youtube.com/watch?v=dpGkdPkPiSw. SUMMARY: Adverse neighborhood environments were associated with higher psychopathology symptoms and lower cognitive performance, independent of individual socioeconomic status. Higher neighborhood educational resources buffered links of neighborhood deprivation with crystallized cognitive performance; deprivation was more strongly associated with lower crystallized cognition for youth with lower neighborhood educational resources. While evidence of protective links was not widespread, understanding these patterns is necessary for informing structural prevention and intervention targets for mental health and cognition.

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Sports participation benefits children but increases the risk of mild traumatic brain injury (mTBI) and orthopedic injury (OI). This study examines risks of mTBI vs. OI associated with specific sports and benefits of sports participation.

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Socioeconomic determinants of health impact childhood development and adult health outcomes. One key aspect is the physical environment and neighborhood where children live and grow. Emerging evidence suggests that neighborhood deprivation, often measured by the Area Deprivation Index (ADI), may influence neurodevelopment, but longitudinal and multimodal neuroimaging analyses remain limited.

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Prodromal symptoms of mania in children are predictive of the later development of bipolar disorder; yet, the neurostructural correlates of these early symptoms remain poorly understood. This study aimed to investigate the association between prodromal mania symptoms and brain structure in a large cohort of children.

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This study tested whether measurement of the Familism scale of the Mexican American Cultural Values Scale (comprising Support, Obligations, and Referent subscales) was invariant across parent and youth reporters in early adolescence and examined whether reporter discrepancies predicted youth functioning across substance use, problem behavior, academic, peer, and family domains 1 year later. The sample comprised 2410 multi-ethnic Hispanic/Latino/a youth (M = 12.87 years; 48% female) and their parents from the Adolescent Brain Cognitive Development (ABCD) Study. At least partial metric invariance was established for Support and Obligations subscales, suggesting associations between mean levels of these subscales with other measures can be meaningfully compared by parent and youth reporters. However, the Referent subscale and Total Familism scale demonstrated only configural invariance, meaning their structure was similar across reporters, but item loadings, latent means, and associations with other measures were not comparable. Reporter discrepancies in Support and Obligations did not account for unique variance in any indicator of youth functioning beyond the main effects of parent and youth Support and Obligations, both of which were associated with adaptive youth outcomes. Both parent and youth reports on the Familism scale of the Mexican American Cultural Values Scale have demonstrated reliability and validity in previous work, but our tests of measurement invariance suggest only the Support and Obligations subscales, but not the Referent or Familism scales, can be meaningfully compared across parent and youth reporters. This work has important implications for the assessment of familism in early adolescence and its role for youth well-being.

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Disadvantaged socioeconomic status (SES) is associated with elevated internalizing symptoms in adolescents and is potentially mediated by accelerated pubertal development. Neighborhood SES may have distinct effects beyond family influences, interacting with family SES to shape adolescents’ development. The present study examines the combined effects of family and neighborhood SES on pubertal development trajectory and internalizing symptoms and explores the mediating role of pubertal trajectory. This study included 5560 early adolescents (46.51% female; aged 9-10 years at baseline; M = 9.48; SD = 0.51) from the Adolescent Brain Cognitive Development (ABCD) study across four annual assessments. Three pubertal development trajectories were identified: “early-onset with slow progression”, “late-onset with rapid catch-up”, and “late-onset with slow catch-up”. The results revealed that accelerated pubertal trajectories mediated the association between multilevel SES disparities and internalizing symptoms. For adolescents from high-SES families, high neighborhood SES reduced the likelihood of early-onset and rapid catch-up trajectories, which were linked to fewer internalizing symptoms. However, for adolescents from low-SES families, higher neighborhood SES increased the likelihood of early-onset and rapid catch-up trajectories, which were associated with more internalizing symptoms. Sex differences were observed, with neighborhood SES predicting pubertal trajectories in males but not in females, and the rapid catch-up trajectory was associated with fewer anxious/depressed symptoms in males but more internalizing symptoms in females. This study emphasizes the crucial role of family and neighborhood SES disparities in shaping adolescent pubertal development, which in turn affects internalizing symptoms.

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Internalizing problems (e.g., anxiety and depression) are associated with a wide range of adverse outcomes. While some predictors of internalizing problems are known (e.g., their frequent co-occurrence with neurodevelopmental (ND) conditions), the biological markers of internalizing problems are not well understood. Here, we used deep learning, a powerful tool for identifying complex and multi-dimensional brain-behaviour relationships, to predict cross-sectional and worsening longitudinal trajectories of internalizing problems. Data were extracted from four large-scale datasets: the Adolescent Brain Cognitive Development study, the Healthy Brain Network, the Human Connectome Project Development study, and the Province of Ontario Neurodevelopmental network. We developed deep learning models that used measures of brain structure (thickness, surface area, and volume) to (a) predict clinically significant internalizing problems cross-sectionally (N = 14,523); and (b) predict subsequent worsening trajectories (using the reliable change index) of internalizing problems (N = 10,540) longitudinally. A stratified cross-validation scheme was used to tune, train, and test the models, which were evaluated using the area under the receiving operating characteristic curve (AUC). The cross-sectional model performed well across the sample, reaching an AUC of 0.80 [95% CI: 0.71, 0.88]. For the longitudinal model, while performance was sub-optimal for predicting worsening trajectories in a sample of the general population (AUC = 0.66 [0.65, 0.67]), good performance was achieved in a small, external test set of primarily ND conditions (AUC = 0.80 [0.78, 0.81]), as well as across all ND conditions (AUC = 0.73 [0.70, 0.76]). Deep learning with features of brain structure is a promising avenue for biomarkers of internalizing problems, particularly for individuals who have a higher likelihood of experiencing difficulties.

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Low socio-economic status, male sex, and body mass index (BMI) are known risk factors for high sugar sweetened beverage (SSB) consumption in adolescents. The present analysis aimed to predict SSB intake based on known risk factors and resting-state functional magnetic resonance (rsfMRI) connectivity from the Adolescent Brain Cognitive Development study.

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Research has linked early intercourse and romantic relationships to increased depressive symptoms, especially for female adolescents. However, less is known about the ways in which early noncoital sexual behaviors are associated with mental health. Thus, this study examined whether early kissing, sexual touching, and romantic relationships were associated with depressive symptoms, and whether these associations differed for male, female, and nonbinary adolescents.

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Perceived racial discrimination during childhood and adolescence is a critical social determinant of health disparities. However, few scales measure perceived racial discrimination in these age groups, and even fewer are validated with robust psychometric properties or demonstrate measurement invariance across racial and ethnic or sex groups.

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Youth whose parents have depression histories are at elevated risk for psychopathology. Familial depression-related patterns of neurodevelopment and environmental stress (e.g., family conflict) likely contribute to heightened risk. However, knowledge remains limited due to few studies, small sample sizes, and cross-sectional designs. We sought to identify how neural circuitry, familial risk for depression, and family conflict interact during preadolescence to predict adolescent psychopathology.

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The Adolescent Brain Cognitive Development (ABCD) Study® has significant potential to reveal the nature, causes, context, and consequences of pubertal development in diverse American youth. Optimal use of the data requires thoughtful consideration of puberty: how it is likely to affect psychological and neural development, and its measurement. We examined how ABCD puberty data have been used, and the relative advantages of two measures derived from the Pubertal Development Scale: the categorical measure provided in data releases and a continuous measure widely used outside ABCD.

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Perinatal insults (e.g., obstetric complications, substance exposure) are increasing in prevalence and confer risk for psychotic-like experiences in offspring, contributing to a growing public health burden. Perinatal insults often co-occur, creating methodological challenges in understanding their impacts on psychosis-spectrum phenotypes. Data-driven approaches to organizing perinatal insults and testing their longitudinal effects on psychotic-like experiences in youth increases ecological validity and translational utility. Using data from 11,417 youth ages 9-14 across five years of the Adolescent Brain Cognitive Development (ABCD) Study, data-driven dimensions of perinatal insults were derived through exploratory factor analysis of thirty-one perinatal insults. Latent growth modeling tested the effect of perinatal insult dimensions on trajectories (baseline, rate-of-change, year-four severity) of distressing psychotic-like experiences. Six dimensions of perinatal insults were observed (substance exposure, obstetric complications, birth complications, postnatal challenges, parental age, medical needs). Substance exposure (β = 0.42, 95% CI [0.20, 0.63]), obstetric complications (β = 0.34, 95% CI [0.08, 0.61]), and parental age (β = 1.00, 95% CI [0.76, 1.22]) were associated with elevated baseline psychotic-like experiences. Perinatal insult dimensions were not associated with increasing rates-of-change in psychotic-like experiences. Medical needs (β = -0.12, 95% CI [-0.20, -0.05]) and parental age (β = -0.11, 95% CI [-0.18, -0.03]) were associated with steeper declines in psychotic-like experiences. Perinatal insult dimensions remained associated with elevated psychotic-like experiences at year-four. Data-driven dimensions of perinatal insults are associated with stably elevated psychotic-like experience trajectories across early adolescence. Given the role of psychotic-like experiences in later psychopathology and functioning, early identification of at-risk offspring is critical in reducing the public health burden of these exposures.

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Females who experience menarche early have elevated risk for dysmenorrhea; yet, other puberty features precede menarche. Using data from the Adolescent Brain Cognitive Development Study®, pubertal timing was estimated via random effects linear growth curves of pubertal status indicators excluding menarche for postmenarcheal females with no ( = 1083), mild ( = 1239), or severe ( = 266) dysmenorrhea. Early pubertal timing increased odds for dysmenorrhea by 22-31%, making it a novel marker for dysmenorrhea risk.

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Not everyone is equally likely to experience mental illness. What is the contribution of an individual’s genetic background and experiences of childhood adversity to that likelihood? And how do these risk factors interact at the level of the brain? This study explores these questions by investigating the relationship between genetic liability for mental illness, childhood adversity, and cortico-limbic connectivity in a large developmental sample drawn from the ABCD cohort (N = 6535). Canonical Correlation Analysis – a multivariate data-reduction technique – revealed two genetic dimensions of mental illness from the polygenic risk scores for ADHD, Anxiety, Depression, and Psychosis. The first dimension represented liability for broad psychopathology which was positively correlated with adversity. The second dimension represented neurodevelopmental-specific risk which negatively interacted with adversity, suggesting that neurodevelopmental symptoms may arise from unique combinations of genetic and environmental factors that differ from other symptom domains. Next, we investigated the cortico-limbic signature of adversity and genetic liability using Partial Least Squares. We found that the neural correlates of adversity broadly mirrored those of genetic liability, with adversity capturing most of the shared variance. These novel findings suggest that genetic and environmental risk overlap in the neural connections that underlie mental health symptomatology.

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In longitudinal research with adolescents and adults, one-third of individuals who report self-injurious thoughts and behaviors (SITBs) fail to report this history in the future. However, there is limited information regarding this phenomenon in children. This study examined the prevalence, correlates, and developmental shifts of inconsistent reporting of SITBs in children using data from the Adolescent Brain Cognitive Development study baseline (BL, ages 9-10), Year 1 (Y1), and Year 2 (Y2) assessments. Lifetime SITBs were assessed annually using a computerized clinical interview. Reporting consistency was calculated for 1-year intervals in two partially overlapping cohorts (BL-Y1, = 1,350; Y1-Y2, = 1,086). Logistic regressions modeled BL sociodemographic, clinical, and neurocognitive correlates with inconsistent reporting from BL to Y1. Developmental differences in inconsistency were assessed by comparing rates between BL-Y1 and Y1-Y2. At Y1, 67% of SITB reporters from BL did not endorse past SITBs (inconsistency range = 67%-80% across SITBs). Less severe clinical symptoms (e.g., parent-reported youth psychopathology, longitudinal SITB reports), younger age, and lower general neurocognitive performance were significantly associated with higher odds of inconsistent reporting of SITBs. Inconsistency in nonsuicidal self-injury reporting was significantly lower from Y1 to Y2 (73%) compared to BL-Y1 (80%). In late childhood, inconsistency in reported SITBs is the norm and may hinder accurate risk assessment for youth. These patterns may be associated with lower clinical severity and neurocognitive and developmental immaturity. Further examination is needed to better understand features associated with inconsistent reporting (e.g., forgetting, reconceptualizing, or nondisclosure) to inform suicide risk assessments. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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Adolescence marks a critical window wherein individual differences in brain structure may influence the emergence of alcohol use behaviors. The orbitofrontal cortex (OFC), a region involved in reward processing and behavioral regulation, may play a key role in shaping early responses to alcohol. This study examined whether smaller OFC volume at ages 9-10 predicted likelihood of experiencing subjective effects of alcohol by ages 13-14. Participants (N = 206; 57 % female) were drawn from the Adolescent Brain Cognitive Development Study. Baseline medial and lateral OFC volumes were used. Subjective response to alcohol was measured during follow-up using a binary outcome (1 = any effect, 0 = no effects). Mixed-effects logistic regression models tested the association between OFC and alcohol response, adjusting for sex, parental education, race/ethnicity, intracranial volume, and site. Smaller left medial OFC at Baseline was significantly associated with greater odds of reporting subjective effects (OR = 1.70, p = .026). Youth who reported subjective effects also consumed more alcohol in the past year (p < .001), but did not differ in their alcohol expectancies. Among those reporting subjective effects, OFC volume was not significantly associated with the amount or frequency of alcohol use. These findings suggest that smaller OFC volume may not reflect pharmacological sensitivity per se, but instead relate to early drinking behavior sufficient to elicit noticeable effects. This may reflect underlying impulsivity-related traits or altered neurodevelopmental trajectories that predispose youth to early and potentially riskier patterns of alcohol use. Results underscore the potential value of identifying structural brain markers that contribute to individual vulnerability for alcohol use during adolescence.

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Racial discrimination has been linked with pubertal development among Black and Latinx American youth. The direction of effects, however, is poorly understood. We examined bidirectional associations between exposure to racial discrimination and pubertal development among Black and Latinx boys and girls from age 9 to age 11.

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Major Depression (MD) is a prevalent, disabling and life-limiting condition. The neurobiological associations of genetic risk for MD remain under-explored in large samples, with no comprehensive mega-analysis conducted to date. Our study analysed data from 11 separate studies, encompassing 50,975 participants from the ENIGMA Major Depressive Disorder Working Group. We developed highly consistent genetic and neuroimaging protocols and applied these throughout all participating studies, together with rigorous genetic methods to remove overlap between the polygenic risk scores (PRS) training and testing samples. Elevated PRS for MD correlated with lower intracranial volume and lower global measure of cortical surface area (β = -0.017, p = 1.97 × 10; β = -0.013, p = 4.5 × 10; pFDR < 3.62 × 10). The most significant cortical association was observed in the surface area of the frontal lobe (β = -0.011, p = 2.85 × 10, pFDR = 1.42 × 10), particularly in the left medial orbito-frontal gyrus (β = -0.021, p = 9.48 × 10, pFDR = 1.25 × 10). In subcortical regions, lower volumes of the thalamus, hippocampus, and pallidum correlated with higher PRS of MD (β ranged from -0.011 to -0.015, p ranged from 0.002-1.73 × 10, pFDR < 0.006). In a subsample of young individuals only (<25 years old, N = 5570), although there were no FDR-significant findings, directions of effects were highly consistent between the analyses of cortical surface areas in youth and the full sample (71.2% in the same direction, exact binomial test p-value = 7.56 × 10). Subsequent Mendelian randomisation analysis revealed potentially causal effects of smaller left hippocampal volume on higher liability for MD (Inverse variance weighted analysis β = -0.064, p = 8.04 × 10, pFDR = 0.04). Our findings represent an example of how extensive international collaborations can significantly advance our neurogenetic understanding of MD and give insights to avenues for early interventions in those at high risk for developing MD.

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Physical Activity (PA) is important for mental, physical, and brain health. Adolescence is marked by increased engagement in risky substance use (SU) behaviors, which can negatively affect brain development. This study aims to determine if PA influences SU experimentation and initiation among adolescents. We predicted higher levels of PA would be associated with less SU, with a larger effect in more vigorous compared to light PA. A sample of 2541 participants from the Adolescent Brain Cognitive Development (ABCD) Study provided three weeks of Fitbit-measured PA data at the 2-year follow-up, and SU outcomes at the 3- and 4-year follow-up. SU outcomes of experimentation (i.e., sip/puff/try of alcohol, nicotine, or cannabis) and initiation (i.e., full drink of alcohol, more than a puff/try of nicotine or cannabis, or anything else) were examined dichotomously (i.e., yes/no). Logistic regression analyses were conducted, controlling for demographics, externalizing, and depressive symptoms endorsed on Child Behavior Checklist (CBCL). Total PA was associated with 24 % decreased odds in SU initiation (OR 0.82, 95 % CI 0.69-0.99,  < .05). After examining PA intensities more closely, light PA predicted 26 % decreased odds of SU initiation (OR 0.73, 95 % CI 0.61-0.88, p = .001). No significant associations emerged between PA and experimentation, or moderate and vigorous PA and initiation. More engagement in total and light PA reduced the odds of SU initiation, suggesting that low-intensity activity, not moderate or vigorous PA, may provide protection against adolescent SU. Future research should examine underlying mechanisms and contextual factors that account for these results.

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Extensive neuroimaging research in temporal lobe epilepsy with hippocampal sclerosis (TLE-HS) has identified brain atrophy as a disease phenotype. While it is also related to a complex genetic architecture, the transition from genetic risk factors to brain vulnerabilities remains unclear. Using a population-based approach, we examined the associations between epilepsy-related polygenic risk for HS (PRS-HS) and brain structure in healthy developing children, assessed their relation to brain network architecture, and evaluated its correspondence with case-control findings in TLE-HS diagnosed patients relative to healthy individuals We used genome-wide genotyping and structural T1-weighted magnetic resonance imaging (MRI) of 3,826 neurotypical children from the Adolescent Brain Cognitive Development (ABCD) study. Surface-based linear models related PRS-HS to cortical thickness measures, and subsequently contextualized findings with structural and functional network architecture based on epicentre mapping approaches. Imaging-genetic associations were then correlated to atrophy and disease epicentres in 785 patients with TLE-HS relative to 1,512 healthy controls aggregated across multiple sites. Higher PRS-HS was associated with decreases in cortical thickness across temporo-parietal as well as fronto-central regions of neurotypical children. These imaging-genetic effects were anchored to the connectivity profiles of distinct functional and structural epicentres. Compared with disease-related alterations from a separate epilepsy cohort, regional and network correlates of PRS-HS strongly mirrored cortical atrophy and disease epicentres observed in patients with TLE-HS, and highly replicable across different studies. Findings were consistent when using statistical models controlling for spatial autocorrelations and robust to variations in analytic methods. Capitalizing on recent imaging-genetic initiatives, our study provides novel insights into the genetic underpinnings of structural alterations in TLE-HS, revealing common morphological and network pathways between genetic vulnerability and disease mechanisms. These signatures offer a foundation for early risk stratification and personalized interventions targeting genetic profiles in epilepsy.

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The global prevalence of cannabis use during pregnancy is increasing, driven by perceived therapeutic benefits and greater societal acceptance. Concurrently, the psychoactive potency of cannabis products has risen significantly, due to increase in concentrations of Tetrahydrocannabinol (THC) from 5% to 30%. THC crosses the placenta, disrupts the endocannabinoid system critical for neurodevelopment, and accumulates in fetal tissues. THC is transferred into breast milk, with breastfed infants receiving ~2.5% of the maternal dose, raising concerns regarding neurodevelopmental consequences. An increasing number of studies and metanalysis have demonstrated association of prenatal cannabis exposure with low birth weight, preterm birth, neonatal intensive care unit admission, and reduced Apgar scores. Longitudinal studies show brain alterations in offspring, affecting memory, attention, and executive function. The inability to conduct randomized controlled trials due to ethical constraints necessitates reliance on observational studies, underscoring the need for rigorous longitudinal research to delineate causality.

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As an increasing realization, many behavioral relationships are interwoven with inherent variations in human populations. Presently, there is no clarity in the biomedical community on which sources of population variation are most dominant. The recent advent of population-scale cohorts like the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®) are now offering unprecedented depth and width of phenotype profiling that potentially explains interfamily differences. Here, we leveraged a deep learning framework (conditional variational autoencoder) on the totality of the ABCD Study® phenome (8,902 candidate phenotypes in 11,875 participants) to identify and characterize major sources of population stratification. 80% of the top 5 sources of explanatory stratifications were driven by distinct combinations of 202 available socioeconomic status (SES) measures; each in conjunction with a unique set of non-overlapping social and environmental factors. Several sources of variation across this cohort flagged geographies marked by material poverty interlocked with mental health and behavioral correlates. Deprivation emerged in another top stratification in relation to urbanicity and its ties to immigrant and racial and ethnic minoritized groups. Conversely, two other major sources of population variation were both driven by indicators of privilege: one highlighted measures of access to educational opportunity and income tied to healthy home environments and good behavior, the other profiled individuals of European ancestry leading advantaged lifestyles in desirable neighborhoods in terms of location and air quality. Overall, the disclosed social stratifications underscore the importance of treating SES as a multidimensional construct and recognizing its ties into social determinants of health.

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Functional connectivity is frequently used to assess dynamic brain functioning and predict individual differences in behavioral outcomes, such as psychopathology. Inferences from functional connectivity analyses typically rely on group-averaged model statistics. However, heterogeneity between individuals may lead to group-level models that poorly reflect each individual. Poor individual-level precision may limit the ability to make individual-level predictions, which is necessary for key goals such as clinical translation. This registered report examined between-person heterogeneity in resting-state functional connectivity strength patterns by assessing similarity between group- and individual-level connectivity models in the Adolescent Brain Cognitive Development study. Using intraclass correlation coefficients, we found that a group-averaged region-of-interest-based connectivity model was a poor reflection of every individual. In contrast, a group-averaged model of between- and within-network connectivity was a good representation of most individuals. We then examined how individual-level distinctness from the group moderated predictive performance of several clinical and neurocognitive scales. Hypotheses that group-to-individual dissimilarity would worsen behavioral prediction were not supported with primary clinical outcomes. The little psychopathology reported in this sample was a notable limitation. In contrast, lower similarity to the group worsened prediction of performance on the pattern comparison test, providing minor support for hypotheses. Overall, results suggest that region-of-interest-based functional connectivity networks are highly heterogeneous and group-based models are inappropriate for individual-level inferences, but that network-based connectivity is largely similar across individuals. Additionally, we provide minor evidence of the impacts of heterogeneity on prediction that future studies should build on.

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Pain in youth is a growing public health concern. While research suggests pervasive differences in brain morphology with pain in adulthood, this relationship is less studied in adolescence. To address this gap, the present study explored pain-related associations with gray matter volume across 82 brain regions in a community sample of 7712 youth (mean age = 11.96) by comparing structural brain measures between those with (n = 2668; 34.6%) and without (n = 5044; 65.4%) past-month pain and examining associations with a continuous latent pain factor composed of average pain ratings, worst pain ratings, and pain limitations. Results showed no significant morphological differences between groups with and without past-month pain. Among participants reporting pain, average pain limitations were generally low, despite varied pain intensity, duration, and number of pain locations. Within this group, higher latent pain scores were associated with lower gray matter volume in six cortical regions (bilateral precentral, right postcentral, right inferior parietal, left supramarginal and left lateral occipital gyri; all p < 0.05). However, in secondary analyses adjusting for total intracranial volume (ICV), only the result in the right inferior parietal gyrus remained significant, suggesting this region may represent a more robust and regionally specific correlate of pain, independent of global brain effects. Together, these findings suggest that heightened pain experiences are related to lower gray matter volume in predominantly sensorimotor and parietal regions. Future work exploring the temporal dynamics of these morphological differences is needed to clarify their clinical implications. PERSPECTIVE: This article describes an association between lower gray matter volume in primarily sensorimotor and parietal areas and higher pain scores among youth reporting past-month pain (n = 2668) in a nonclinical community sample (n = 7712). The findings contribute to the understanding of neurobiological correlates of adolescent pain and pain-related neurodevelopmental patterns.

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Psychotic-like experiences (PLEs) may arise from genetic and environmental risk leading to worsening cognitive and morphometry metrics over time, which in turn lead to worsening PLEs. Analyses used three waves of unique longitudinal Adolescent Brain Cognitive Development Study data (ages 9-13) to test whether changes in cognition and global morphometry metrics attenuate associations between genetic and environmental risk with persistent distressing PLEs. Multigroup univariate latent growth models examined three waves of cognitive metrics and global morphometry separately for three PLE groups: persistent distressing PLEs (n=356), transient distressing PLEs (n=408), and low-level PLEs (n=7901). Persistent distressing PLEs showed greater decreases (i.e., more negative slopes) of cognition and morphometry metrics over time compared to those in low-level PLE groups. Analyses also provided novel evidence for extant theories that worsening cognition and global morphometry metrics may partially account for associations between environmental risk with persistent distressing PLEs.

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Humans and nonhuman primate studies suggest that timing and tempo of cortical development varies neuroanatomically along a sensorimotor-to-association (S-A) axis. Prior human studies have reported a principal S-A axis across various modalities but largely rely on cross-sectional samples with wide age-ranges. Here, we investigate developmental changes and individual variability in cortical organization along the S-A axis between the ages of 9-13 years using a large, longitudinal sample (N = 2487-3747, 46-50% female) from the Adolescent Brain Cognitive Development Study (ABCD Study®). This work assesses multiple aspects of neurodevelopment indexed by changes in cortical thickness, cortical microarchitecture, and resting-state low-frequency oscillations. First, we evaluated S-A organization in age-related changes and then, computed individual-level S-A alignment in brain changes and assessing differences therein due to age, sex, and puberty. Varying degrees of linear and quadratic age-related brain changes were identified along the S-A axis. Yet, these patterns of cortical development were overshadowed by considerable individual variability in S-A alignment. Even within individuals, there was little correspondence between S-A patterning across the different aspects of neurodevelopment investigated (i.e., cortical morphology, microarchitecture, function). Some of the individual variation in developmental patterning of cortical morphology and microarchitecture was explained by age, sex, and pubertal development. Altogether, this work contextualizes prior findings that regional age differences do progress along an S-A axis at a group level, while highlighting broad variation in developmental change between individuals and between aspects of cortical development, in part due to sex and puberty. Understanding normative patterns of adolescent brain change, and individual variability therein, is crucial for disentangling healthy and abnormal development. We used longitudinal human neuroimaging data to study several aspects of neurodevelopment during early adolescence and assessed their organization along a sensorimotor-to-association (S-A) axis across the cerebral cortex. Age differences in brain changes were linear and curvilinear along this S-A axis. However, individual-level sensorimotor-association alignment varied considerably, driven in part by differences in sex and pubertal development.

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Machine learning (ML) has significantly transformed biomedical research, leading to a growing interest in model development to advance classification accuracy in various clinical applications. However, this progress raises essential questions regarding how to rigorously compare the accuracy of different ML models. In this study, we highlight the practical challenges in quantifying the statistical significance of accuracy differences between two neuroimaging-based classification models when cross-validation (CV) is performed. Specifically, we propose an unbiased framework to assess the impact of CV setups (e.g., the number of folds) on the statistical significance. We apply this framework to three publicly available neuroimaging datasets to re-emphasize known flaws in current computation of p-values for comparing model accuracies. We further demonstrate that the likelihood of detecting significant differences among models varies substantially with the intrinsic properties of the data, testing procedures, and CV configurations of choice. Given that many of the above factors do not typically fall into the evaluation criteria of ML-based biomedical studies, we argue that such variability can potentially lead to p-hacking and inconsistent conclusions on model improvement. The obtained results from this study underscore that more rigorous practices in model comparison are urgently needed in order to mitigate the reproducibility crisis in biomedical ML research.

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Non-suicidal self-injury (NSSI) is common in adolescence and is strongly associated with depressive disorders (DDs), necessitating targeted screening and interventions for NSSI among depressed adolescents. This study aimed to build longitudinal predictive models to identify psychosocial factors distinguishing depressed adolescents who begin engaging in NSSI from those who do not and to compare these predictors with those in youth without DDs.

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To investigate the neurodevelopmental associations of moderate to late preterm (MLP) birth during late childhood.

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Impulsivity, often operationalized as delay discounting (DD) and as impulsive personality traits via the UPPS-P scales, is a key transdiagnostic construct across psychiatric disorders. Recent genome-wide association studies (GWAS) have studied the genetic basis of impulsivity in adults, but it remains unclear how similar the genetic architecture of DD is in children. The present study conducted GWAS of DD and impulsivity traits in 5548 children (ages 9-10 years old) of genetically inferred European ancestry from the Adolescent Brain Cognitive Development (ABCD) Study. Heritability estimates for DD (h = 0.20, S.E. = 0.10) and UPPS-P subscales (h = 0.08-0.11 S.E. = 0.05) were comparable to adult estimates. Genetic correlations between adult and child impulsivity were modest (r = 0.28-0.46), with positive urgency showing the strongest correlation (r = 0.83). While no genome-wide significant associations were identified, the top associated variants were mapped to genes previously linked to smoking initiation (rs3820908; p = 6.5 × 10) and UPPS-P Lack of Premeditation (rs17292179; p = 4.2 × 10). Polygenic score (PGS) associations were used to compare the genetic signals in children with those reported in adults. Adult PGSs for DD and positive and negative urgency indicators explained small but significant variance in the respective child impulsivity phenotypes (0.36%-0.44%, p < 7.5 × 10). Additionally, UPPS-P indices were broadly associated with PGSs derived from adult externalizing (0.42%-1.02%) and ADHD (0.23%-0.79%). This first GWAS of impulsivity in children offers a developmentally informed comparison of genetic influences, revealing both similarities and differences by developmental stage.

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Many communities in the United States are delaying school start times to improve youth sleep. Racial disparities exist in sleep. The extent to which school start times are associated with racial disparities in sleep is unclear, especially in early adolescent populations that are not the focus of research on school start times. This study examined the associations between school start times and actigraphy-assessed sleep, including duration, onset, and offset times among a national sample of racially diverse early adolescents.

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The present study examined the longitudinal, bidirectional associations between early adolescents’ electronic media use and family conflict across 3 years using data from the ABCD study (T1; = 11,787). Findings indicated that more overall electronic media use was related to later increases in family conflict, whereas the reverse association was not supported. Further analyses examined associations by unique types of electronic media. Social electronic media use at T1 in girls was related to less family conflict at T2, yet more family conflict at later timepoints. These findings suggest that more overall electronic media use promotes later conflict throughout early adolescence and that girls’ use of social types of media may be especially disruptive in families as they progress through early adolescence. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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Persistent and/or distressing psychotic-like experiences (PLEs) during adolescence are associated with poorer subsequent psychiatric outcomes. Modifiable lifestyle factors (such as sleep quality or regular exercise) may improve mental health outcomes; however, it is unknown how lifestyle factors are linked to trajectories of PLEs.

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Adolescence is a pivotal stage for brain development and a critical window for the emergence and transition of self-injury thoughts and behaviours (SITBs). However, the genetic and neurobiological mechanisms underlying SITBs transition during this developmental period are poorly understood.

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Although moderate-to-vigorous physical activity (MVPA) is a widely used construct in physical activity (PA) research, the lack of standardized assessment methods- particularly with the growing use of consumer-grade wearable activity trackers- poses challenges for comparability. Consumer-grade devices tend to rely on heart rate (HR)-based estimation methods to classify PA intensity, which contrasts with traditional research-grade accelerometers that use count- or raw-acceleration metrics. Comparability issues are particularly salient across individuals with varying weight status. In this commentary, we discuss systematic discrepancies between HR-based (relative intensity) and acceleration-based (absolute intensity) classifications of MVPA among individuals with differing weight statuses. Using Fitbit data from the Adolescent Brain Cognitive Development Study, we illustrate how HR-based PA intensity classification may indicate higher MVPA in youth with greater adiposity despite lower step counts and light PA levels. We highlight implications for research design, public health surveillance, messaging, policy, and interventions. We also call for greater transparency, standardized methodologies, and integrative measurement approaches to ensure more accurate assessment of PA behavior.

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The long-term impact of prenatal substance exposure (PSE) on obesity remains inconclusive. Few studies have explored the trajectories of Tri-Ponderal Mass Index (TMI), despite its greater accuracy and reliability in assessing adolescent adiposity. The aim of this study was to examine adiposity trajectories assessed by TMI from pre- to early adolescence and the influence of PSE on these patterns.

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Substance use has been associated with differences in adult brain morphology; however, it is unclear whether these differences precede or are a result of substance use substance use. We investigated the impact of polygenic risk scores (PRSs) for cannabis use disorder (CUD) and general substance use and substance use disorder liability (SU/SUD) on brain morphology in drug-naïve adolescents. Baseline data were used from 1874 European-descent participants (ages 9-11) comprising 222, 328 and 387 pairs of MZ twins, DZ twins, and Non-Twin Siblings, respectively, in the Adolescent Brain Cognitive Development Study. We fitted multivariate twin models to estimate the putative effects of CUD, SU/SUD, and brain region-specific PRSs. These models assessed their influence on six subcortical and two cortical phenotypes. PRS for CUD and SU/SUD were created based on GWAS conducted by Johnson et al. (Lancet Psychiatry 7:1032, 2020) and Hatoum et al. (Nat Ment Health 1:210-223, 2023), respectively. When decomposing variance in each brain region of interest (ROI), we used the corresponding ROI-specific PRS. Brain morphometry in drug-naive subjects was unrelated to CUD PRS. The variance explained in each ROI by its corresponding PRS ranged from 0.8 to 4.4%. The SU/SUD PRS showed marginally significant effects (0.2-0.4%) on cortical surface area and nucleus accumbens volume, but overall effect sizes were small. This study failed to reject the null hypothesis of no association between genetic risk for substance use and brain morphometry among baseline drug-naive adolescents. Genetic risk for CUD was not associated with brain morphometry among drug-naive adolescents, but a weak association with general addiction and substance use risk (SU/SUD) particularly in nucleus accumbens volume and total cortical surface area, was observed.

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The neighborhood context is increasingly recognized as a significant determinant of health. Advances in geospatial analysis and neuroimaging have facilitated an emerging field of research investigating how neighborhood conditions influence brain development. We conducted a systematic review, identifying 37 studies that examined associations between neighborhood conditions and brain structure in children and adolescents. We highlight key findings and research gaps across multiple domains of neighborhood conditions – socioeconomic status, demographic composition, social environment, built environment, physical environment, and health resources. Our review suggests that adverse neighborhood socioeconomic conditions are linked to structural brain differences, including reduced brain volume and white matter, and smaller surface areas. Additionally, observed race-related disparities in brain structures may be partially explained by residence in low-resourced neighborhoods, underscoring the role of structural inequities in shaping neurodevelopment. The majority of studies relied on the Adolescent Brain Cognitive Development Study dataset, limiting the generalizability of findings. Critically, neighborhood conditions beyond socioeconomic status remain understudied, offering opportunities for future research to examine how positive conditions (e.g., social cohesion, greenspace, health resources) may foster neurodevelopment. This review emphasizes the urgent need for policies to reduce structural inequities while leveraging protective neighborhood conditions to promote equity and youth neurodevelopment.

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The human cortex exhibits remarkable morphometric similarity between regions; however, the form and extent of lifespan network remodeling remain unknown. Here, we show the spatiotemporal maturation of morphometric brain networks, using multimodal neuroimaging data from 33,937 healthy participants aged 0-80 years. Global architecture matures from birth to early adulthood through enhanced modularity and small worldness. Early development features cytoarchitecturally distinct remodeling: sensory cortices exhibit increased morphometric differentiation, paralimbic cortices show increased morphometric similarity, and association cortices retain stable hub roles. Morphology-function coupling peaks in early adolescence and then decreases, supporting protracted functional maturation. These growth patterns of morphometric networks are correlated with gene expression related to synaptic signaling, neurodevelopment, and metabolism. Normative models based on morphometric networks identify person-specific, connectivity-phenotypic deviations in 1,202 patients with brain disorders. These data provide a blueprint for elucidating the principle of cortical network reconfiguration and a benchmark for quantifying interindividual network variations.

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Childhood behavioral problems are associated with significant long-term consequences, yet the underlying cognitive mechanisms remain poorly understood. In this study, we employed computational modeling alongside traditional reaction time (RT) measures to investigate cognitive control during a flanker task. We evaluated the predictive utility of these methods in explaining variance across eight transdiagnostic symptom domains in late childhood (mean age = 10.0 years; n = 10,343) from the Adolescent Brain Cognitive Development study. We compared simultaneous regression models across congruent and incongruent conditions using an RT-only model and a drift-diffusion model (DDM) that incorporated boundary separation, bias, drift rate, and non-decision time parameters. Results from the RT-only models indicated that slower reaction times across both task conditions were associated with higher scores on most symptom subscales, suggesting more behavioral problems. For both task conditions, DDM regressions accounted for more total variance across symptom domains compared to RT models. Additionally, DDM regressions demonstrated that impoverished evidence accumulation emerged as a shared feature of both internalizing and externalizing behaviors, while reductions in non-decision time, indicative of increased impulsiveness, were unique to rule-breaking and aggressive behaviors. These findings suggest that different aspects of cognitive control are associated with specific behavioral problems in children, rather than just overall response speed. Present results provide new insights into cognitive control dynamics and suggest that targeting ineffective cognitive control could be crucial for the prevention and intervention of childhood psychopathology.

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The purpose of this study was to: 1) examine the co-occurrence of household and community adverse childhood experiences (ACEs) among preadolescent youth using latent class analysis (LCA), and 2) examine the association of ACE latent clusters to clinical-range scores on the Child Behavior Checklist (CBCL). Data came from the baseline and year 1 survey of the Adolescent Brain Cognitive Development (ABCD) Study with 10,915 youth recruited from school-based catchment areas in the United States. We used LCA to examine 6 types of household adversity and 7 types of community adversity, including 4 types of discrimination. We identified 5 latent classes of household/community ACEs. The class with high levels of household and community ACEs together was most strongly associated with clinical-range CBCL scores in adjusted models. Assessing adversity comprehensively may improve identification of youth with elevated risk for behavioral symptoms, who are greatest in need of intervention.

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Early life stress (ELS) is associated with an increased risk of substance use in adolescence. The interaction of puberty with neurodevelopment during adolescence increases the sensitivity of the brain to both sex and stress hormones. This sensitivity may result in sex-specific pathways from ELS to adolescent alcohol use initiation. The current study examines the effect of ELS on alcohol initiation by age 13 via pubertal mediators, separated by sex and adjusted for the independent effects of age.

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Our genetic makeup, together with environmental and social influences, shape our brain’s development. Yet, the imaging-genetics field has struggled to integrate all these modalities to investigate the interplay between genetic blueprint, brain architecture, environment, human health and daily living skills. Here we interrogate the Adolescent Brain Cognitive Development (ABCD) cohort to outline the effects of rare high-effect genetic variants on brain architecture and their corresponding implications on cognitive, behavioural, psychosocial and socioeconomic traits. We design a holistic pattern-learning framework that quantitatively dissects the impacts of copy number variations (CNVs) on brain structure and 938 behavioural variables spanning 20 categories in 7,338 adolescents. Our results reveal associations between genetic alterations, higher-order brain networks and specific parameters of the family wellbeing, including increased parental and child stress, anxiety and depression, or neighbourhood dynamics such as decreased safety. We thus find effects extending beyond the impairment of cognitive ability or language capacity which have been previously reported. Our investigation spotlights the interplay between genetic variation and subjective life quality in adolescents and their families.

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Fluid and crystallized intelligence are acknowledged as distinct facets of cognitive ability during brain development, but the specific neural substrates and molecular mechanisms underlying them remain unclear. This study used a sample comprising 7471 young adolescents (mean age 9.87 ± 0.62 years) from the ABCD cohort to elucidate the differential neural correlates of fluid and crystallized intelligence. Our findings indicated that micro-level brain MRI phenotypes such as water diffusivity were closely associated with fluid intelligence, whereas macro-level brain MRI phenotypes such as gray matter cortical thickness were indicative of crystallized intelligence. We further investigated the molecular mechanisms underlying fluid and crystallized intelligence by correlating the characteristic MRI markers with spatial transcriptome profiles and PET imaging. Results showed that fluid intelligence had significant associations with serotonin and glutamate system, while crystallized intelligence was related to serotonin, dopamine and acetylcholine system. Furthermore, we examined the impacts of lifestyle factors on these two forms of intelligence and how the molecular pathways mediated these impacts. Our investigation suggested that physical activities, screen use and sleep duration influenced fluid intelligence mainly through mGlu5 receptors and crystallized intelligence through 5HT1a and D2 receptors. In conclusion, these findings illustrated a distinct neural basis between fluid and crystallized intelligence from the perspectives of neuroimaging, neurotransmitters, and lifestyles in young adolescents.

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Maternal tobacco use during pregnancy (MTDP) remains a global and domestic public health issue. This study seeks to investigate the long-term impact of MTDP on brain morphology during late childhood and early adolescence using the Adolescent Brain Cognitive Development (ABCD) dataset. Children aged 9-10 were enrolled using the ABCD school selection probability sample method for national representation. Participants and their parents or guardians underwent interviews and surveys, and children underwent Magnetic Resonance Imaging (MRI) at baseline and 2-year follow-up. Morphometric brain measures of cortical thickness and sulcal depth across 34 regions of interest on T1-weighted MRI images were analyzed. Of 11,448 at baseline, 1,607 children fell into the MTDP group. Intracranial volume (p<0.001), total cortical surface area, and volume (p<0.0001) were significantly lower among MTDP children (vs. control) at both waves 1 and 2. A sustained difference was found in mean cortical thickness at the parahippocampal gyrus as well as sulcal depth at the isthmus cingulate, parahippocampal, lateral occipital, and lingual gyri. Several regions of interest demonstrated differences in the cortical thickness and sulcal depth at single time points. An association between MTDP and long-term outcomes of regional morphometric differences in cortical thickness and sulcal depth on MRI was found at both baseline among 9-10 years old and at 2-year follow-ups. Taken together with NIH cognitive testing from the same population comparison, the results suggest longstanding cognitive deficits corresponding to specific brain regions.

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A pervasive dilemma in brain-wide association studies (BWAS) is whether to prioritize functional magnetic resonance imaging (fMRI) scan time or sample size. We derive a theoretical model showing that individual-level phenotypic prediction accuracy increases with sample size and total scan duration (sample size × scan time per participant). The model explains empirical prediction accuracies well across 76 phenotypes from nine resting-fMRI and task-fMRI datasets (R = 0.89), spanning diverse scanners, acquisitions, racial groups, disorders and ages. For scans of ≤20 min, accuracy increases linearly with the logarithm of the total scan duration, suggesting that sample size and scan time are initially interchangeable. However, sample size is ultimately more important. Nevertheless, when accounting for the overhead costs of each participant (such as recruitment), longer scans can be substantially cheaper than larger sample size for improving prediction performance. To achieve high prediction performance, 10 min scans are cost inefficient. In most scenarios, the optimal scan time is at least 20 min. On average, 30 min scans are the most cost-effective, yielding 22% savings over 10 min scans. Overshooting the optimal scan time is cheaper than undershooting it, so we recommend a scan time of at least 30 min. Compared with resting-state whole-brain BWAS, the most cost-effective scan time is shorter for task-fMRI and longer for subcortical-to-whole-brain BWAS. In contrast to standard power calculations, our results suggest that jointly optimizing sample size and scan time can boost prediction accuracy while cutting costs. Our empirical reference is available online for future study design ( https://thomasyeolab.github.io/OptimalScanTimeCalculator/index.html ).

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Suicide is one of the leading causes of death among youth worldwide, yet existing studies that aimed to predict the first onset of suicidal thoughts or behaviors (STB) included a limited number of data modalities, and/or focused on adult populations. We aimed to prospectively predict first-onset STB across four-year follow-ups in adolescents using (1) an existing STB history classification model that was previously applied to baseline data, and (2) a new machine learning model with 195 biopsychosocial features.

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Various multilevel, multidomain factors at the individual-, family-, and environmental-level, and changes in neurobiology have been associated with the likelihood of developing alcohol use disorder (AUD) or binge drinking later in life. Prior studies have examined only limited subsets of these factors, typically focusing on cross-sectional associations with alcohol initiation, binge drinking, or AUD rather than exploring longitudinal alcohol use trajectories. Our study addresses these gaps by applying machine learning methods to a comprehensive set of multilevel, multidomain factors and multimodal brain imaging features (including brain structure and functional connectivity) to prospectively predict early alcohol sipping trajectories. Using data from the Adolescent Brain Cognitive Development Study, we identified functional connectivity features and multilevel factors that distinguish youth with an increasing alcohol sipping trajectory from those who initially experimented with alcohol but reduced their consumption over time. Moreover, structural and functional features predicted differences between youth who increasingly sipped over time and those who did not engage in alcohol experimentation. Interactions between age, socioeconomical status and positive attitudes towards drinking could predict a pattern of increasing alcohol sipping over time. These trends could inform how individual, family, environmental and neurobiological factors impact the development of different alcohol sipping trajectories over time.

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Sleep disturbances and mental health challenges often arise during adolescence, with a greater prevalence among females and individuals experiencing obesity. In this study, we examined the intricate relationships between sleep problems, obesity, and biological sex, and their combined relationship with well-being in a large, diverse cohort of US adolescents.

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Psychiatric conditions, known for their hereditary nature, exert significant impacts on various life domains. Leveraging this heritability, we examine the relations between genetic susceptibility to major psychiatric disorders and the multifaceted aspects of quality of life in two population-based cohorts, the Adolescent Brain Cognitive Development (ABCD) study (N = 3909 preadolescent children) and the UK Biobank (N = 269,293 adults). Genetic susceptibility to seven major psychiatric disorders was quantified by polygenic scores derived from extensive genome-wide association studies (N = 21,000-413,000). Pervasive associations were found between genetic risk for all seven major psychiatric disorders investigated and age-relevant real-life quality of life indices, with varied patterns of associations for different life domains. We especially highlight the role of genetic risks for ADHD and major depressive disorders. Our findings emphasize the continuous nature of psychiatric traits, extending their influence on daily life experiences and societal functioning beyond symptomatology and diagnostic classifications.

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