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

Multivariate associations between neuroanatomy and cognition in unmedicated and medicated individuals with schizophrenia

Previous studies that focused on univariate correlations between neuroanatomy and cognition in schizophrenia identified some inconsistent findings. Moreover, antipsychotic medication may impact the brain-behavior profiles in affected individuals. It remains unclear whether unmedicated and medicated individuals with schizophrenia would share common neuroanatomy-cognition associations. Therefore, we aimed to investigate multivariate neuroanatomy-cognition relationships in both groups. A sample of 59 drug-naïve individuals with first-episode schizophrenia (FES) and a sample of 115 antipsychotic-treated individuals with schizophrenia were finally included. Multivariate modeling was conducted in the two patient samples between multiple cognitive domains and neuroanatomic features, such as cortical thickness (CT), cortical surface area (CSA), and subcortical volume (SV). We observed distinct multivariate correlational patterns between the two samples of individuals with schizophrenia. In the FES sample, better performance in token motor, symbol coding, and verbal fluency tests was associated with greater thalamic volumes but lower CT in the prefrontal and anterior cingulate cortices. Two significant multivariate correlations were identified in antipsychotic-treated individuals: 1) worse verbal memory performance was related to smaller volumes for the most subcortical structures and smaller CSA mainly in the temporal regions and inferior parietal lobule; 2) a lower symbol coding test score was correlated with smaller CSA in the right parahippocampal gyrus but greater volume in the right caudate. These multivariate patterns were sample-specific and not confounded by imaging quality, illness duration, antipsychotic dose, or psychopathological symptoms. Our findings may help to understand the neurobiological basis of cognitive impairments and the development of cognition-targeted interventions.

Comparing the stability and reproducibility of brain-behavior relationships found using canonical correlation analysis and partial least squares within the ABCD sample

Canonical correlation analysis (CCA) and partial least squares correlation (PLS) detect linear associations between two data matrices by computing latent variables (LVs) having maximal correlation (CCA) or covariance (PLS). This study compared the similarity and generalizability of CCA- and PLS-derived brain-behavior relationships. Data were accessed from the baseline Adolescent Brain Cognitive Development (ABCD) dataset (N > 9,000, 9-11 years). The brain matrix consisted of cortical thickness estimates from the Desikan-Killiany atlas. Two phenotypic scales were examined separately as the behavioral matrix; the Child Behavioral Checklist (CBCL) subscale scores and NIH Toolbox performance scores. Resampling methods were used to assess significance and generalizability of LVs. LV1 for the CBCL brain relationships was found to be significant, yet not consistently stable or reproducible, across CCA and PLS models (singular value: CCA = .13, PLS = .39, p < .001). LV1 for the NIH brain relationships showed similar relationships between CCA and PLS and was found to be stable and reproducible (singular value: CCA = .21, PLS = .43, p < .001). The current study suggests that stability and reproducibility of brain-behavior relationships identified by CCA and PLS are influenced by the statistical characteristics of the phenotypic measure used when applied to a large population-based pediatric sample.

Multivariate association between psychosocial environment, behaviors, and brain functional networks in adolescent depression

BACKGROUND

Adolescent depression shows high clinical heterogeneity. Brain functional networks serve as a powerful tool for investigating neural mechanisms underlying depression profiles. A key challenge is to characterize how variation in brain functional organization links to behavioral features and psychosocial environmental influences.

METHODS

We recruited 80 adolescents with major depressive disorder (MDD) and 42 healthy controls (HCs). First, we estimated the differences in functional connectivity of resting-state networks (RSN) between the two groups. Then, we used sparse canonical correlation analysis to characterize patterns of associations between RSN connectivity and symptoms, cognition, and psychosocial environmental factors in MDD adolescents. Clustering analysis was applied to stratify patients into homogenous subtypes according to these brain-behavior-environment associations.

RESULTS

MDD adolescents showed significantly hyperconnectivity between the ventral attention and cingulo-opercular networks compared with HCs. We identified one reliable pattern of covariation between RSN connectivity and clinical/environmental features in MDD adolescents. In this pattern, psychosocial factors, especially the interpersonal and family relationships, were major contributors to variation in connectivity of salience, cingulo-opercular, ventral attention, subcortical and somatosensory-motor networks. Based on this association, we categorized patients into two subgroups which showed different environment and symptoms characteristics, and distinct connectivity alterations. These differences were covered up when the patients were taken as a whole group.

CONCLUSION

This study identified the environmental exposures associated with specific functional networks in MDD youths. Our findings emphasize the importance of the psychosocial context in assessing brain function alterations in adolescent depression and have the potential to promote targeted treatment and precise prevention.

Triple Interactions Between the Environment, Brain, and Behavior in Children: An ABCD Study

BACKGROUND

Environmental exposures play a crucial role in shaping children's behavioral development. However, the mechanisms by which these exposures interact with brain functional connectivity and influence behavior remain unexplored.

METHODS

We investigated the comprehensive environment-brain-behavior triple interactions through rigorous association, prediction, and mediation analyses, while adjusting for multiple confounders. Particularly, we examined the predictive power of brain functional network connectivity (FNC) and 41 environmental exposures for 23 behaviors related to cognitive ability and mental health in 7655 children selected from the Adolescent Brain Cognitive Development (ABCD) Study at both baseline and follow-up.

RESULTS

FNC demonstrated more predictability for cognitive abilities than for mental health, with cross-validation from the UK Biobank study (N = 20,852), highlighting the importance of thalamus and hippocampus in longitudinal prediction, while FNC+environment demonstrated more predictive power than FNC in both cross-sectional and longitudinal prediction of all behaviors, especially for mental health (r = 0.32-0.63). We found that family and neighborhood exposures were common critical environmental influencers on cognitive ability and mental health, which can be mediated by FNC significantly. Healthy perinatal development was a unique protective factor for higher cognitive ability, whereas sleep problems, family conflicts, and adverse school environments specifically increased risk of poor mental health.

CONCLUSIONS

This work revealed comprehensive environment-brain-behavior triple interactions based on the ABCD Study, identified cognitive control and default mode networks as the most predictive functional networks for a wide repertoire of behaviors, and underscored the long-lasting impact of critical environmental exposures on childhood development, in which sleep problems were the most prominent factors affecting mental health.

Voxelwise Multivariate Analysis of Brain-Psychosocial Associations in Adolescents Reveals 6 Latent Dimensions of Cognition and Psychopathology

BACKGROUND

Adolescence heralds the onset of considerable psychopathology, which may be conceptualized as an emergence of altered covariation between symptoms and brain measures. Multivariate methods can detect such modes of covariation or latent dimensions, but none specifically relating to psychopathology have yet been found using population-level structural brain data. Using voxelwise (instead of parcellated) brain data may strengthen latent dimensions' brain-psychosocial relationships, but this creates computational challenges.

METHODS

We obtained voxelwise gray matter density and psychosocial variables from the baseline (ages 9-10 years) Adolescent Brain Cognitive Development (ABCD) Study cohort (N = 11,288) and employed a state-of-the-art segmentation method, sparse partial least squares, and a rigorous machine learning framework to prevent overfitting.

RESULTS

We found 6 latent dimensions, 4 of which pertain specifically to mental health. The mental health dimensions were related to overeating, anorexia/internalizing, oppositional symptoms (all ps < .002) and attention-deficit/hyperactivity disorder symptoms (p = .03). Attention-deficit/hyperactivity disorder was related to increased and internalizing symptoms related to decreased gray matter density in dopaminergic and serotonergic midbrain areas, whereas oppositional symptoms were related to increased gray matter in a noradrenergic nucleus. Internalizing symptoms were related to increased and oppositional symptoms to reduced gray matter density in the insular, cingulate, and auditory cortices. Striatal regions featured strongly, with reduced caudate nucleus gray matter in attention-deficit/hyperactivity disorder and reduced putamen gray matter in oppositional/conduct problems. Voxelwise gray matter density generated stronger brain-psychosocial correlations than brain parcellations.

CONCLUSIONS

Voxelwise brain data strengthen latent dimensions of brain-psychosocial covariation, and sparse multivariate methods increase their psychopathological specificity. Internalizing and externalizing symptoms are associated with opposite gray matter changes in similar cortical and subcortical areas.

Identification of a Composite Latent Dimension of Reward and Impulsivity Across Clinical, Behavioral, and Neurobiological Domains Among Youth

BACKGROUND

Individual differences in reward processing are central to heightened risk-taking behaviors during adolescence, but there is inconsistent evidence for the relationship between risk-taking phenotypes and the neural substrates of these behaviors.

METHODS

Here, we identify latent features of reward in an attempt to provide a unifying framework linking together aspects of the brain and behavior during early adolescence using a multivariate pattern learning approach. Data (N = 8295; n male = 4190; n female = 4105) were acquired as part of the Adolescent Brain Cognitive Development (ABCD) Study and included neuroimaging (regional neural activity responses during reward anticipation) and behavioral (e.g., impulsivity measures, delay discounting) variables.

RESULTS

We revealed a single latent dimension of reward driven by shared covariation between striatal, thalamic, and anterior cingulate responses during reward anticipation, negative urgency, and delay discounting behaviors. Expression of these latent features differed among adolescents with attention-deficit/hyperactivity disorder and disruptive behavior disorder, compared with those without, and higher expression of these latent features was negatively associated with multiple dimensions of executive function and cognition.

CONCLUSIONS

These results suggest that cross-domain patterns of anticipatory reward processing linked to negative features of impulsivity exist in both the brain and in behavior during early adolescence and that these are representative of 2 commonly diagnosed reward-related psychiatric disorders, attention-deficit/hyperactivity disorder and disruptive behavior disorder. Furthermore, they provide an explicit baseline from which multivariate developmental trajectories of reward processes may be tracked in later waves of the ABCD Study and other developmental cohorts.

A Shared Multivariate Brain-Behavior Relationship in a Transdiagnostic Sample of Adolescents

BACKGROUND

Internalizing and externalizing psychopathology typically present in early childhood and can have negative implications on general functioning and quality of life. Prior work has linked increased psychopathology symptoms with altered brain structure. Multivariate analysis such as partial least squares correlation can help identify patterns of covariation between brain regions and psychopathology symptoms. This study examined the relationship between gray matter volume (GMV) and psychopathology symptoms in adolescents with various psychiatric diagnoses.

METHODS

Structural magnetic resonance imaging data were collected from 490 participants with various internalizing and externalizing diagnoses (197 female/293 male; age = 14.68 ± 2.35 years; IQ = 104.05 ± 13.11). Cortical and subcortical volumes were parcellated using the Desikan-Killiany atlas. Partial least squares correlation was used to identify multivariate linear relationships between GMV and the Strength and Difficulties Questionnaire difficulties domains (emotional, peer, conduct, and hyperactivity issues). Resampling approaches were used to determine significance (permutation test), stability (bootstrap resampling), and reproducibility (split-half resampling) of identified relationships.

RESULTS

We found a significant, stable, and largely reproducible dimension that linked lower Strength and Difficulties Questionnaire scores (less impairment) across all difficulties domains with greater widespread GMV (singular value = 1.17, accounts for 87.1% of the covariance; p < .001). This dimension emphasized the relationship between lower conduct problems and greater GMV in frontotemporal regions.

CONCLUSIONS

Our results indicate that the most significant and stable brain-behavior relationship in a transdiagnostic sample is a domain-general relationship, linking lower psychopathology symptom scores to greater global GMV. This finding suggests that a shared brain-behavior relationship may be present across adolescents with and without clinically significant psychopathology symptoms.

Leveraging multivariate approaches to advance the science of early-life adversity

Since the landmark Adverse Childhood Experiences (ACEs) study, adversity research has expanded to more precisely account for the multifaceted nature of adverse experiences. The complex data structures and interrelated nature of adversity data require robust multivariate statistical methods, and recent methodological and statistical innovations have facilitated advancements in research on childhood adversity. Here, we provide an overview of a subset of multivariate methods that we believe hold particular promise for advancing the field's understanding of early-life adversity, and discuss how these approaches can be practically applied to explore different research questions. This review covers data-driven or unsupervised approaches (including dimensionality reduction and person-centered clustering/subtype identification) as well as supervised/prediction-based approaches (including linear and tree-based models and neural networks). For each, we highlight studies that have effectively applied the method to provide novel insight into early-life adversity. Taken together, we hope this review serves as a resource to adversity researchers looking to expand upon the cumulative approach described in the original ACEs study, thereby advancing the field's understanding of the complexity of adversity and related developmental consequences.

Reconfiguration of Structural and Functional Connectivity Coupling in Patient Subgroups With Adolescent Depression

Importance

Adolescent major depressive disorder (MDD) is associated with serious adverse implications for brain development and higher rates of self-injury and suicide, raising concerns about its neurobiological mechanisms in clinical neuroscience. However, most previous studies regarding the brain alterations in adolescent MDD focused on single-modal images or analyzed images of different modalities separately, ignoring the potential role of aberrant interactions between brain structure and function in the psychopathology.

Objective

To examine alterations of structural and functional connectivity (SC-FC) coupling in adolescent MDD by integrating both diffusion magnetic resonance imaging (MRI) and resting-state functional MRI data.

Design, Setting, and Participants

This cross-sectional study recruited participants aged 10 to 18 years from January 2, 2020, to December 28, 2021. Patients with first-episode MDD were recruited from the outpatient psychiatry clinics at The First Affiliated Hospital of Chongqing Medical University. Healthy controls were recruited by local media advertisement from the general population in Chongqing, China. The sample was divided into 5 subgroup pairs according to different environmental stressors and clinical characteristics. Data were analyzed from January 10, 2022, to February 20, 2023.

Main Outcomes and Measures

The SC-FC coupling was calculated for each brain region of each participant using whole-brain SC and FC. Primary analyses included the group differences in SC-FC coupling and clinical symptom associations between SC-FC coupling and participants with adolescent MDD and healthy controls. Secondary analyses included differences among 5 types of MDD subgroups: with or without suicide attempt, with or without nonsuicidal self-injury behavior, with or without major life events, with or without childhood trauma, and with or without school bullying.

Results

Final analyses examined SC-FC coupling of 168 participants with adolescent MDD (mean [mean absolute deviation (MAD)] age, 16.0 [1.7] years; 124 females [73.8%]) and 101 healthy controls (mean [MAD] age, 15.1 [2.4] years; 61 females [60.4%]). Adolescent MDD showed increased SC-FC coupling in the visual network, default mode network, and insula (Cohen d ranged from 0.365 to 0.581; false discovery rate [FDR]-corrected P < .05). Some subgroup-specific alterations were identified via subgroup analyses, particularly involving parahippocampal coupling decrease in participants with suicide attempt (partial η2 = 0.069; 90% CI, 0.025-0.121; FDR-corrected P = .007) and frontal-limbic coupling increase in participants with major life events (partial η2 ranged from 0.046 to 0.068; FDR-corrected P < .05).

Conclusions and Relevance

Results of this cross-sectional study suggest increased SC-FC coupling in adolescent MDD, especially involving hub regions of the default mode network, visual network, and insula. The findings enrich knowledge of the aberrant brain SC-FC coupling in the psychopathology of adolescent MDD, underscoring the vulnerability of frontal-limbic SC-FC coupling to external stressors and the parahippocampal coupling in shaping future-minded behavior.

Lifestyle Factors Counteract the Neurodevelopmental Impact of Genetic Risk for Accelerated Brain Aging in Adolescence

BACKGROUND

The transition from childhood to adolescence is characterized by enhanced neural plasticity and a consequent susceptibility to both beneficial and adverse aspects of one's milieu.

METHODS

To understand the implications of the interplay between protective and risk-enhancing factors, we analyzed longitudinal data from the Adolescent Brain Cognitive Development (ABCD) Study (n = 834; 394 female). We probed the maturational correlates of positive lifestyle variables (friendships, parental warmth, school engagement, physical exercise, healthy nutrition) and genetic vulnerability to neuropsychiatric disorders (major depressive disorder, Alzheimer's disease, anxiety disorders, bipolar disorder, schizophrenia) and sought to further elucidate their implications for psychological well-being.

RESULTS

Genetic risk factors and lifestyle buffers showed divergent relationships with later attentional and interpersonal problems. These effects were mediated by distinguishable functional neurodevelopmental deviations spanning the limbic, default mode, visual, and control systems. More specifically, greater genetic vulnerability was associated with alterations in the normative maturation of areas rich in dopamine (D2), glutamate, and serotonin receptors and of areas with stronger expression of astrocytic and microglial genes, a molecular signature implicated in the brain disorders discussed here. Greater availability of lifestyle buffers predicted deviations in the normative functional development of higher density GABAergic (gamma-aminobutyric acidergic) receptor regions. The two profiles of neurodevelopmental alterations showed complementary roles in protection against psychopathology, which varied with environmental stress levels.

CONCLUSIONS

Our results underscore the importance of educational involvement and healthy nutrition in attenuating the neurodevelopmental sequelae of genetic risk factors. They also underscore the importance of characterizing early-life biomarkers associated with adult-onset pathologies.

Multivariate patterns of brain functional connectome associated with COVID-19-related negative affect symptoms

Severe mental health problems with the representation of negative affect symptoms (NAS) have been increasingly reported during the coronavirus disease 2019 (COVID-19) pandemic. This study aimed to explore the multivariate patterns of brain functional connectome predicting COVID-19-related NAS. This cohort study encompassed a group of university students to undergo neuroimaging scans before the pandemic, and we re-contacted participants for 1-year follow-up COVID-related NAS evaluations during the pandemic. Regularized canonical correlation analysis was used to identify connectome-based dimensions of NAS to compute pairs of canonical variates. The predictive ability of identified functional connectome to NAS dimensional scores was examined with a nested cross-validation. Two dimensions (i.e. mode stress and mode anxiety) were related to distinct patterns of brain functional connectome (r2 = 0.911, PFDR = 0.048; r2 = 0.901, PFDR = 0.037, respectively). Mode anxiety was characterized by high loadings in connectivity between affective network (AFN) and visual network (VN), while connectivity of the default mode network with dorsal attention network (DAN) were remarkably prominent in mode stress. Connectivity patterns within the DAN and between DAN and VN, ventral attention network, and AFN was common for both dimensions. The identified functional connectome can reliably predict mode stress (r = 0.37, MAE = 5.1, p < 0.001) and mode anxiety (r = 0.28, MAE = 5.4, p = 0.005) in the cross-validation. Our findings provide new insight into multivariate dimensions of COVID-related NAS, which may have implications for developing network-based biomarkers in psychological interventions for vulnerable individuals in the pandemic.

Covariation of preadult environmental exposures, adult brain imaging phenotypes, and adult personality traits

Exposure to preadult environmental exposures may have long-lasting effects on mental health by affecting the maturation of the brain and personality, two traits that interact throughout the developmental process. However, environment-brain-personality covariation patterns and their mediation relationships remain unclear. In 4297 healthy participants (aged 18-30 years), we combined sparse multiple canonical correlation analysis with independent component analysis to identify the three-way covariation patterns of 59 preadult environmental exposures, 760 adult brain imaging phenotypes, and five personality traits, and found two robust environment-brain-personality covariation models with sex specificity. One model linked greater stress and less support to weaker functional connectivity and activity in the default mode network, stronger activity in subcortical nuclei, greater thickness and volume in the occipital, parietal and temporal cortices, and lower agreeableness, consciousness and extraversion as well as higher neuroticism. The other model linked higher urbanicity and better socioeconomic status to stronger functional connectivity and activity in the sensorimotor network, smaller volume and surface area and weaker functional connectivity and activity in the medial prefrontal cortex, lower white matter integrity, and higher openness to experience. We also conducted mediation analyses to explore the potential bidirectional mediation relationships between adult brain imaging phenotypes and personality traits with the influence of preadult environmental exposures and found both environment-brain-personality and environment-personality-brain pathways. We finally performed moderated mediation analyses to test the potential interactions between macro- and microenvironmental exposures and found that one category of exposure moderated the mediation pathways of another category of exposure. These results improve our understanding of the effects of preadult environmental exposures on the adult brain and personality traits and may facilitate the design of targeted interventions to improve mental health by reducing the impact of adverse environmental exposures.

Screen media activity in youth: A critical review of mental health and neuroscience findings

This review has two primary objectives: (1) to offer a balanced examination of recent findings on the relationship between screen media activity (SMA) in young individuals and outcomes such as sleep patterns, mood disturbances, anxiety-related concerns, and cognitive processes; and (2) to introduce a novel multi-level system model that integrates these findings, resolves contradictions in the literature, and guides future studies in examining key covariates affecting the SMA-mental health relationship. Key findings include: (1) Several meta-analyses reveal a significant association between SMA and mental health issues, particularly anxiety and depression, including specific negative effects linked to prolonged screen time; (2) substantial evidence indicates that SMA has both immediate and long-term impacts on sleep duration and quality; (3) the relationship between SMA and cognitive functioning is complex, with mixed findings showing both positive and negative associations; and (4) the multifaceted relationship between SMA and various aspects of adolescent life is influenced by a wide range of environmental and contextual factors. SMA in youth is best understood within a complex system encompassing individual, caregiver, school, peer, and environmental factors, as framed by Bronfenbrenner's ecological systems theory, which identifies five interrelated systems (microsystem, mesosystem, exosystem, macrosystem, and chronosystem) that influence development across both proximal and distal levels of the environment. This model provides a framework for future research to examine these interactions, considering moderating factors, and to develop targeted interventions that can mitigate potential adverse effects of SMA on mental well-being.

Whole Person Modeling: a transdisciplinary approach to mental health research

The growing global burden of mental illness has prompted calls for innovative research strategies. Theoretical models of mental health include complex contributions of biological, psychosocial, experiential, and other environmental influences. Accordingly, neuropsychiatric research has self-organized into largely isolated disciplines working to decode each individual contribution. However, research directly modeling objective biological measurements in combination with cognitive, psychological, demographic, or other environmental measurements is only now beginning to proliferate. This review aims to (1) to describe the landscape of modern mental health research and current movement towards integrative study, (2) to provide a concrete framework for quantitative integrative research, which we call Whole Person Modeling, (3) to explore existing and emerging techniques and methods used in Whole Person Modeling, and (4) to discuss our observations about the scarcity, potential value, and untested aspects of highly transdisciplinary research in general. Whole Person Modeling studies have the potential to provide a better understanding of multilevel phenomena, deliver more accurate diagnostic and prognostic tests to aid in clinical decision making, and test long standing theoretical models of mental illness. Some current barriers to progress include challenges with interdisciplinary communication and collaboration, systemic cultural barriers to transdisciplinary career paths, technical challenges in model specification, bias, and data harmonization, and gaps in transdisciplinary educational programs. We hope to ease anxiety in the field surrounding the often mysterious and intimidating world of transdisciplinary, data-driven mental health research and provide a useful orientation for students or highly specialized researchers who are new to this area.

Prenatal environment is associated with the pace of cortical network development over the first three years of life

Environmental influences on brain structure and function during early development have been well-characterized. In pre-registered analyses, we test the theory that socioeconomic status (SES) is associated with differences in trajectories of intrinsic brain network development from birth to three years (n = 261). Prenatal SES is associated with developmental increases in cortical network segregation, with neonates and toddlers from lower-SES backgrounds showing a steeper increase in cortical network segregation with age, consistent with accelerated network development. Associations between SES and cortical network segregation occur at the local scale and conform to a sensorimotor-association hierarchy of cortical organization. SES-associated differences in cortical network segregation are associated with language abilities at two years, such that lower segregation is associated with improved language abilities. These results yield key insight into the timing and directionality of associations between the early environment and trajectories of cortical development.

Neurobiological Clusters Are Associated With Trajectories of Overall Psychopathology in Youth

BACKGROUND

Integrating multiple neuroimaging modalities to identify clusters of individuals and then associating these clusters with psychopathology is a promising approach for understanding neurobiological mechanisms that underlie psychopathology and the extent to which these features are associated with clinical symptoms.

METHODS

We leveraged neuroimaging data from T1-weighted, diffusion-weighted, and resting-state functional magnetic resonance images from the Adolescent Brain Cognitive Development (ABCD) Study (N = 8035) and used similarity network fusion and spectral clustering to identify subgroups of participants. We examined neuroimaging measures as a function of clustering profiles using 1, 2, or 3 imaging modalities (i.e., data combinations), calculated the stability of the clustering assignment in each respective data combination, and compared the consistency of clusters across different data combinations. We then compared the extent to which clusters were associated with overall psychopathology at the baseline assessment and at 2 yearly follow-up visits.

RESULTS

Each data combination resulted in optimal clusters ranging from 2 to 4 subgroups for each data combination. Clusters were stable across subsampling of the ABCD Study cohort. Widespread structural measures (surface area, fractional anisotropy, and mean diffusivity) were important features contributing to clustering across different data combinations. Five of the seven data combinations were associated with overall psychopathology, both at baseline and over time (d = 0.08-0.41). Generally, lower global cortical volume and surface area, widespread reduced fractional anisotropy, and increased radial diffusivity were associated with increased overall psychopathology.

CONCLUSIONS

Profiles constructed from neuroimaging data combinations are associated with concurrent and future psychopathology trajectories.

General and Specific Factors of Environmental Stress and Their Associations With Brain Structure and Dimensions of Psychopathology

Background

Early-life stressors can adversely affect the developing brain. While hierarchical modeling has established the existence of a general factor of psychopathology, no studies have modeled a general factor of environmental stress and related this factor to brain development. Using a large sample of children from the ABCD (Adolescent Brain Cognitive Development) Study, the current study aimed to identify general and specific factors of environmental stress and test their associations with brain structure and psychopathology.

Methods

In a sample of 11,878 children, bifactor modeling and higher-order (second-order) modeling identified general and specific factors of environmental stress: family dynamics, interpersonal support, neighborhood socioeconomic status deprivation, and urbanicity. Structural equation modeling was performed to examine associations between these factors and regional gray matter volume (GMV) and cortical thickness as well as general and specific factors of psychopathology.

Results

The general environmental stress factor was associated with globally smaller cortical and subcortical GMV as well as thinner cortices across widespread regions. Family dynamics and neighborhood socioeconomic status deprivation were associated with smaller GMV in focal regions. Urbanicity was associated with larger cortical and subcortical GMV and thicker cortices in frontotemporal regions. The environmental factors were associated with psychopathology in the expected directions. The general factors of environmental stress and psychopathology were both predictors of smaller GMV in children, while remaining distinct from each other.

Conclusions

This study reveals a unifying model of environmental influences that illustrates the inherent organization of environmental stressors and their relationship to brain structure and psychopathology.

Adolescent neurodevelopment and psychopathology: The interplay between adversity exposure and genetic risk for accelerated brain ageing

In adulthood, stress exposure and genetic risk heighten psychological vulnerability by accelerating neurobiological senescence. To investigate whether molecular and brain network maturation processes play a similar role in adolescence, we analysed genetic, as well as longitudinal task neuroimaging (inhibitory control, incentive processing) and early life adversity (i.e., material deprivation, violence) data from the Adolescent Brain and Cognitive Development study (N = 980, age range: 9-13 years). Genetic risk was estimated separately for Major Depressive Disorder (MDD) and Alzheimer's Disease (AD), two pathologies linked to stress exposure and allegedly sharing a causal connection (MDD-to-AD). Adversity and genetic risk for MDD/AD jointly predicted functional network segregation patterns suggestive of accelerated (GABA-linked) visual/attentional, but delayed (dopamine [D2]/glutamate [GLU5R]-linked) somatomotor/association system development. A positive relationship between brain maturation and psychopathology emerged only among the less vulnerable adolescents, thereby implying that normatively maladaptive neurodevelopmental alterations could foster adjustment among the more exposed and genetically more stress susceptible youths. Transcriptomic analyses suggested that sensitivity to stress may underpin the joint neurodevelopmental effect of adversity and genetic risk for MDD/AD, in line with the proposed role of negative emotionality as a precursor to AD, likely to account for the alleged causal impact of MDD on dementia onset.

Comparing the stability and reproducibility of brain-behaviour relationships found using Canonical Correlation Analysis and Partial Least Squares within the ABCD Sample

Introduction

Canonical Correlation Analysis (CCA) and Partial Least Squares Correlation (PLS) detect associations between two data matrices based on computing a linear combination between the two matrices (called latent variables; LVs). These LVs maximize correlation (CCA) and covariance (PLS). These different maximization criteria may render one approach more stable and reproducible than the other when working with brain and behavioural data at the population-level. This study compared the LVs which emerged from CCA and PLS analyses of brain-behaviour relationships from the Adolescent Brain Cognitive Development (ABCD) dataset and examined their stability and reproducibility.

Methods

Structural T1-weighted imaging and behavioural data were accessed from the baseline Adolescent Brain Cognitive Development dataset (N > 9000, ages = 9-11 years). The brain matrix consisted of cortical thickness estimates in different cortical regions. The behavioural matrix consisted of 11 subscale scores from the parent-reported Child Behavioral Checklist (CBCL) or 7 cognitive performance measures from the NIH Toolbox. CCA and PLS models were separately applied to the brain-CBCL analysis and brain-cognition analysis. A permutation test was used to assess whether identified LVs were statistically significant. A series of resampling statistical methods were used to assess stability and reproducibility of the LVs.

Results

When examining the relationship between cortical thickness and CBCL scores, the first LV was found to be significant across both CCA and PLS models (singular value: CCA = .13, PLS = .39, p < .001). LV1 from the CCA model found that covariation of CBCL scores was linked to covariation of cortical thickness. LV1 from the PLS model identified decreased cortical thickness linked to lower CBCL scores. There was limited evidence of stability or reproducibility of LV1 for both CCA and PLS. When examining the relationship between cortical thickness and cognitive performance, there were 6 significant LVs for both CCA and PLS (p < .01). The first LV showed similar relationships between CCA and PLS and was found to be stable and reproducible (singular value: CCA = .21, PLS = .43, p < .001).

Conclusion

CCA and PLS identify different brain-behaviour relationships with limited stability and reproducibility when examining the relationship between cortical thickness and parent-reported behavioural measures. However, both methods identified relatively similar brain-behaviour relationships that were stable and reproducible when examining the relationship between cortical thickness and cognitive performance. The results of the current study suggest that stability and reproducibility of brain-behaviour relationships identified by CCA and PLS are influenced by characteristics of the analyzed sample and the included behavioural measurements when applied to a large pediatric dataset.

Neuroimaging profiling identifies distinct brain maturational subtypes of youth with mood and anxiety disorders

Mood and anxiety disorders typically begin in adolescence and have overlapping clinical features but marked inter-individual variation in clinical presentation. The use of multimodal neuroimaging data may offer novel insights into the underlying brain mechanisms. We applied Heterogeneity Through Discriminative Analysis (HYDRA) to measures of regional brain morphometry, neurite density, and intracortical myelination to identify subtypes of youth, aged 9-10 years, with mood and anxiety disorders (N = 1931) compared to typically developing youth (N = 2823). We identified three subtypes that were robust to permutation testing and sample composition. Subtype 1 evidenced a pattern of imbalanced cortical-subcortical maturation compared to the typically developing group, with subcortical regions lagging behind prefrontal cortical thinning and myelination and greater cortical surface expansion globally. Subtype 2 displayed a pattern of delayed cortical maturation indicated by higher cortical thickness and lower cortical surface area expansion and myelination compared to the typically developing group. Subtype 3 showed evidence of atypical brain maturation involving globally lower cortical thickness and surface coupled with higher myelination and neural density. Subtype 1 had superior cognitive function in contrast to the other two subtypes that underperformed compared to the typically developing group. Higher levels of parental psychopathology, family conflict, and social adversity were common to all subtypes, with subtype 3 having the highest burden of adverse exposures. These analyses comprehensively characterize pre-adolescent mood and anxiety disorders, the biopsychosocial context in which they arise, and lay the foundation for the examination of the longitudinal evolution of the subtypes identified as the study sample transitions through adolescence.

Shared pattern of impaired social communication and cognitive ability in the youth brain across diagnostic boundaries

BACKGROUND

Abnormalities in brain structure are shared across diagnostic categories. Given the high rate of comorbidity, the interplay of relevant behavioural factors may also cross these classic boundaries.

METHODS

We aimed to detect brain-based dimensions of behavioural factors using canonical correlation and independent component analysis in a clinical youth sample (n = 1732, 64 % male, age: 5-21 years).

RESULTS

We identified two correlated patterns of brain structure and behavioural factors. The first mode reflected physical and cognitive maturation (r = 0.92, p = .005). The second mode reflected lower cognitive ability, poorer social skills, and psychological difficulties (r = 0.92, p = .006). Elevated scores on the second mode were a common feature across all diagnostic boundaries and linked to the number of comorbid diagnoses independently of age. Critically, this brain pattern predicted normative cognitive deviations in an independent population-based sample (n = 1253, 54 % female, age: 8-21 years), supporting the generalisability and external validity of the reported brain-behaviour relationships.

CONCLUSIONS

These results reveal dimensions of brain-behaviour associations across diagnostic boundaries, highlighting potent disorder-general patterns as the most prominent. In addition to providing biologically informed patterns of relevant behavioural factors for mental illness, this contributes to a growing body of evidence in favour of transdiagnostic approaches to prevention and intervention.

The Role of School Environment in Brain Structure, Connectivity, and Mental Health in Children: A Multimodal Investigation

BACKGROUND

Much work has been dedicated to understanding the effects of adverse home environments on brain development. While the school social and learning environment plays a role in child development, little work has been done to investigate the impact of the school environment on the developing brain. The goal of the present study was to examine associations between the school environment, brain structure and connectivity, and mental health.

METHODS

In this preregistered study we investigated these questions in a large sample of adolescents (9-10 years of age) from the Adolescent Brain Cognitive Development (ABCD) Study. We examined the association between school environment and gray matter (n = 10,435) and white matter (n = 10,770) structure and functional connectivity (n = 9528). We then investigated multivariate relationships between school-associated brain measures and mental health.

RESULTS

School environment was associated with connectivity of the auditory and retrosplenial temporal network as well as of higher-order cognitive networks like the cingulo-opercular, default mode, ventral attention, and frontoparietal networks. Multivariate analyses revealed that connectivity of the cingulo-opercular and default mode networks was also associated with mental health.

CONCLUSIONS

Findings shed light on the neural mechanisms through which favorable school environments may contribute to positive mental health outcomes in children. Our findings have implications for interventions targeted at promoting positive youth functioning through improving school environments.

Mapping gene by early life stress interactions on child subcortical brain structures: A genome-wide prospective study

Background

Although it is well-established that both genetics and the environment influence brain development, they are typically examined separately. Here, we aimed to prospectively investigate the interactive effects of genetic variants-from a genome-wide approach-and early life stress (ELS) on child subcortical brain structures, and their association with subsequent mental health problems.

Method

Primary analyses were conducted using data from the Generation R Study (N = 2257), including genotype and cumulative prenatal and postnatal ELS scores (encompassing life events, contextual risk, parental risk, interpersonal risk, direct victimisation). Neuroimaging data were collected at age 10 years, including intracranial and subcortical brain volumes (accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus). Genome-wide association and genome-wide-by-environment interaction analyses (GWEIS, run separately for prenatal/postnatal ELS) were conducted for eight brain outcomes (i.e., 24 genome-wide analyses) in the Generation R Study (discovery). Polygenic scores (PGS) using the resulting weights were calculated in an independent (target) cohort (adolescent brain cognitive development Study; N = 10,751), to validate associations with corresponding subcortical volumes and examine links to later mother-reported internalising and externalising problems.

Results

One GWEIS-prenatal stress locus was associated with caudate volume (rs139505895, mapping onto PRSS12 and NDST3) and two GWEIS-postnatal stress loci with the accumbens (rs2397823 and rs3130008, mapping onto CUTA, SYNGAP1, and TABP). Functional annotation revealed that these genes play a role in neuronal plasticity and synaptic function, and have been implicated in neuro-developmental phenotypes, for example, intellectual disability, autism, and schizophrenia. None of these associations survived a more stringent correction for multiple testing across all analysis sets. In the validation sample, all PGS_genotype were associated with their respective brain volumes, but no PGS_GxE associated with any subcortical volume. None of the PGS associated with internalising or externalising problems.

Conclusions

This study lends novel suggestive insights into gene-environment interplay on the developing brain as well as pointing to promising candidate loci for future replication and mechanistic studies.

Canonical Correlation Analysis and Partial Least Squares for Identifying Brain-Behavior Associations: A Tutorial and a Comparative Study

Canonical correlation analysis (CCA) and partial least squares (PLS) are powerful multivariate methods for capturing associations across 2 modalities of data (e.g., brain and behavior). However, when the sample size is similar to or smaller than the number of variables in the data, standard CCA and PLS models may overfit, i.e., find spurious associations that generalize poorly to new data. Dimensionality reduction and regularized extensions of CCA and PLS have been proposed to address this problem, yet most studies using these approaches have some limitations. This work gives a theoretical and practical introduction into the most common CCA/PLS models and their regularized variants. We examine the limitations of standard CCA and PLS when the sample size is similar to or smaller than the number of variables. We discuss how dimensionality reduction and regularization techniques address this problem and explain their main advantages and disadvantages. We highlight crucial aspects of the CCA/PLS analysis framework, including optimizing the hyperparameters of the model and testing the identified associations for statistical significance. We apply the described CCA/PLS models to simulated data and real data from the Human Connectome Project and Alzheimer's Disease Neuroimaging Initiative (both of n > 500). We use both low- and high-dimensionality versions of these data (i.e., ratios between sample size and variables in the range of ∼1-10 and ∼0.1-0.01, respectively) to demonstrate the impact of data dimensionality on the models. Finally, we summarize the key lessons of the tutorial.

Deviations from normative brain white and gray matter structure are associated with psychopathology in youth

Combining imaging modalities and metrics that are sensitive to various aspects of brain structure and maturation may help identify individuals that show deviations in relation to same-aged peers, and thus benefit early-risk-assessment for mental disorders. We used one timepoint multimodal brain imaging, cognitive, and questionnaire data from 1280 eight- to twenty-one-year-olds from the Philadelphia Neurodevelopmental Cohort. We estimated age-related gray and white matter properties and estimated individual deviation scores using normative modeling. Next, we tested for associations between the estimated deviation scores, and with psychopathology domain scores and cognition. More negative deviations in DTI-based fractional anisotropy (FA) and the first principal eigenvalue of the diffusion tensor (L1) were associated with higher scores on psychosis positive and prodromal symptoms and general psychopathology. A more negative deviation in cortical thickness (CT) was associated with a higher general psychopathology score. Negative deviations in global FA, surface area, L1 and CT were also associated with poorer cognitive performance. No robust associations were found between the deviation scores based on CT and DTI. The low correlations between the different multimodal magnetic resonance imaging-based deviation scores suggest that psychopathological burden in adolescence can be mapped onto partly distinct neurobiological features.

Longitudinal Assessments of Neurocognitive Performance and Brain Structure Associated With Initiation of Tobacco Use in Children, 2016 to 2021

IMPORTANCE

The landscape of tobacco use is changing. However, information about the association between early-age tobacco use and cognitive performances is limited, especially for emerging tobacco products such as electronic cigarettes (e-cigarettes).

OBJECTIVE

To assess the association between early-age initiation of tobacco use and cognitive performances measured by the National Institutes of Health (NIH) Toolbox Cognitive Battery and to examine whether initiation is associated with differences in brain morphometry.

DESIGN, SETTING, AND PARTICIPANTS

This observational cohort study examined the longitudinal associations of initiation of tobacco use with neurocognition using multivariate linear mixed models. Children aged 9 to 10 years from 21 US sites were enrolled in wave 1 (October 1, 2016, to October 31, 2018 [n = 11 729]) and the 2-year follow-up (August 1, 2018, to January 31, 2021 [n = 10 081]) of the Adolescent Brain Cognitive Development (ABCD) Study.

EXPOSURES

Ever use (vs none) of any tobacco products at wave 1, including e-cigarettes, cigarettes, cigars, smokeless tobacco, hookah, pipes, and nicotine replacement.

MAIN OUTCOMES AND MEASURES

Neurocognition measured by the NIH Toolbox Cognition Battery and morphometric measures of brain structure and region of interest analysis for the cortex from structural magnetic resonance imaging.

RESULTS

Among 11 729 participants at wave 1 (mean [SE] age, 9.9 [0.6] years; 47.9% girls and 52.1% boys; 20.3% Hispanic; 14.9% non-Hispanic Black; and 52.1% non-Hispanic White), 116 children reported ever use of tobacco products. Controlling for confounders, tobacco ever users vs nonusers exhibited lower scores in the Picture Vocabulary Tests at wave 1 (b [SE] = -2.9 [0.6]; P < .001) and 2-year follow-up (b [SE] = -3.0 [0.7]; P < .001). The crystalized cognition composite score was lower among tobacco ever users than nonusers both at wave 1 (b [SE] = -2.4 [0.5]; P < .001) and 2-year follow-up (b [SE] = -2.7 [0.8]; P = .005). In structural magnetic resonance imaging, the whole-brain measures in cortical area and volume were significantly lower among tobacco users than nonusers, including cortical area (b [SE] = -5014.8 [1739.8] mm2; P = .004) at wave 1 and cortical volume at wave 1 (b [SE] = -174 621.0 [5857.7] mm3; P = .003) and follow-up (b [SE] = -21 790.8 [7043.9] mm3; P = .002). Further region of interest analysis revealed smaller cortical area and volume in multiple regions across frontal, parietal, and temporal lobes at both waves.

CONCLUSIONS AND RELEVANCE

In this cohort study, initiating tobacco use in late childhood was associated with inferior cognitive performance and reduced brain structure with sustained effects at 2-year follow-up. These findings suggest that youths vulnerable to e-cigarettes and tobacco products should be treated as a priority population in tobacco prevention.

Multivariate, Transgenerational Associations of the COVID-19 Pandemic Across Minoritized and Marginalized Communities

IMPORTANCE

The experienced consequences of the COVID-19 pandemic have diverged across individuals, families, and communities, resulting in inequity within a host of factors. There is a gap of quantitative evidence about the transgenerational impacts of these experiences and factors.

OBJECTIVE

To identify baseline predictors of COVID-19 experiences, as defined by child and parent report, using a multivariate pattern-learning framework from the Adolescent Brain and Cognitive Development (ABCD) cohort.

DESIGN, SETTING, AND PARTICIPANTS

ABCD is an ongoing prospective longitudinal study of child and adolescent development in the United States including 11 875 youths, enrolled at age 9 to 10 years. Using nationally collected longitudinal profiling data from 9267 families, a multivariate pattern-learning strategy was developed to identify factor combinations associated with transgenerational costs of the ongoing COVID-19 pandemic. ABCD data (release 3.0) collected from 2016 to 2020 and released between 2019 and 2021 were analyzed in combination with ABCD COVID-19 rapid response data from the first 3 collection points (May-August 2020).

EXPOSURES

Social distancing and other response measures imposed by COVID-19, including school closures and shutdown of many childhood recreational activities.

MAIN OUTCOMES AND MEASURES

Mid-COVID-19 experiences as defined by the ABCD's parent and child COVID-19 assessments.

RESULTS

Deep profiles from 9267 youth (5681 female [47.8%]; mean [SD] age, 119.0 [7.5] months) and their caregivers were quantitatively examined. Enabled by a pattern-learning analysis, social determinants of inequity, including family structure, socioeconomic status, and the experience of racism, were found to be primarily associated with transgenerational impacts of COVID-19, above and beyond other candidate predictors such as preexisting medical or psychiatric conditions. Pooling information across more than 17 000 baseline pre-COVID-19 family indicators and more than 280 measures of day-to-day COVID-19 experiences, non-White (ie, families who reported being Asian, Black, Hispanic, other, or a combination of those choices) and/or Spanish-speaking families were found to have decreased resources (mode 1, canonical vector weight [CVW] = 0.19; rank 5 of 281), escalated likelihoods of financial worry (mode 1, CVW = -0.20; rank 4), and food insecurity (mode 1, CVW = 0.21; rank 2), yet were more likely to have parent-child discussions regarding COVID-19-associated health and prevention issues, such as handwashing (mode 1, CVW = 0.14; rank 9), conserving food or other items (mode 1, CVW = 0.21; rank 1), protecting elderly individuals (mode 1, CVW = 0.11; rank 21), and isolating from others (mode 1, CVW = 0.11; rank 23). In contrast, White families (mode 1, CVW = -0.07; rank 3), those with higher pre-COVID-19 income (mode 1, CVW = -0.07; rank 5), and presence of a parent with a postgraduate degree (mode 1, CVW = -0.06; rank 14) experienced reduced COVID-19-associated impact. In turn, children from families experiencing reduced COVID-19 impacts reported longer nighttime sleep durations (mode 1, CVW = 0.13; rank 14), less difficulties with remote learning (mode 2, CVW = 0.14; rank 7), and decreased worry about the impact of COVID-19 on their family's financial stability (mode 1, CVW = 0.134; rank 13).

CONCLUSIONS AND RELEVANCE

The findings of this study indicate that community-level, transgenerational intervention strategies may be needed to combat the disproportionate burden of pandemics on minoritized and marginalized racial and ethnic populations.

Linking interindividual variability in brain structure to behaviour

What are the brain structural correlates of interindividual differences in behaviour? More than a decade ago, advances in structural MRI opened promising new avenues to address this question. The initial wave of research then progressively led to substantial conceptual and methodological shifts, and a replication crisis unveiled the limitations of traditional approaches, which involved searching for associations between local measurements of neuroanatomy and behavioural variables in small samples of healthy individuals. Given these methodological issues and growing scepticism regarding the idea of one-to-one mapping of psychological constructs to brain regions, new perspectives emerged. These not only embrace the multivariate nature of brain structure-behaviour relationships and promote generalizability but also embrace the representation of the relationships between brain structure and behavioural data by latent dimensions of interindividual variability. Here, we examine the past and present of the study of brain structure-behaviour associations in healthy populations and address current challenges and open questions for future investigations.

School Climate, Cortical Structure, and Socioemotional Functioning: Associations across Family Income Levels

School climates are important for children's socioemotional development and may also serve as protective factors in the context of adversity. Nevertheless, little is known about the potential neural mechanisms of such associations, as there has been limited research concerning the relation between school climate and brain structure, particularly for brain regions relevant for mental health and socioemotional functioning. Moreover, it remains unclear whether the role of school climate differs depending on children's socioeconomic status. We addressed these questions in baseline data for 9- to 10-year-olds from the Adolescent Brain and Cognitive Development study (analytic sample for socioemotional outcomes, n = 8,887), conducted at 21 sites across the United States. Cortical thickness, cortical surface area, and subcortical volume were derived from T1-weighted brain magnetic resonance imaging. School climate was measured by youth report, and socioemotional functioning was measured by both youth and parent report. A positive school climate and higher family income were associated with lower internalizing and externalizing symptoms, with no evidence of moderation. There were no associations between school climate and cortical thickness or subcortical volume, although family income was positively associated with hippocampal volume. For cortical surface area, however, there was both a positive association with family income and moderation: There was an interaction between school climate and income for total cortical surface area and locally in the lateral orbitofrontal cortex. In all cases, there was an unexpected negative association between school climate and cortical surface area in the lower-income group. Consequently, although the school climate appears to be related to better socioemotional function for all youth, findings suggest that the association between a positive school environment and brain structure only emerges in the context of socioeconomic stress and adversity. Longitudinal data are needed to understand the role of these neural differences in socioemotional functioning over time.

Measurement matters: An individual differences examination of family socioeconomic factors, latent dimensions of children's experiences, and resting state functional brain connectivity in the ABCD sample

The variation in experiences between high and low-socioeconomic status contexts are posited to play a crucial role in shaping the developing brain and may explain differences in child outcomes. Yet, examinations of SES and brain development have largely been limited to distal proxies of these experiences (e.g., income comparisons). The current study sought to disentangle the effects of multiple socioeconomic indices and dimensions of more proximal experiences on resting-state functional connectivity (rsFC) in a sample of 7834 youth (aged 9-10 years) from the Adolescent Brain Cognitive Development (ABCD) study. We applied moderated nonlinear factor analysis (MNLFA) to establish measurement invariance among three latent environmental dimensions of experience (material/economic deprivation, caregiver social support, and psychosocial threat). Results revealed measurement biases as a function of child age, sex, racial group, family income, and parental education, which were statistically adjusted in the final MNLFA scores. Mixed-effects models demonstrated that socioeconomic indices and psychosocial threat differentially predicted variation in frontolimbic networks, and threat statistically moderated the association between income and connectivity between the dorsal and ventral attention networks. Findings illuminate the importance of reducing measurement biases to gain a more socioculturally-valid understanding of the complex and nuanced links between socioeconomic context, children's experiences, and neurodevelopment.

Neural Signatures of Data-Driven Psychopathology Dimensions at the Transition to Adolescence

Background

One of the challenges in human neuroscience is to uncover associations between brain organization and psychopathology in order to better understand the biological underpinnings of mental disorders. Here, we aimed to characterize the neural correlates of psychopathology dimensions obtained using two conceptually different data-driven approaches.

Methods

Dimensions of psychopathology that were either maximally dissociable or correlated were respectively extracted by independent component analysis (ICA) and exploratory factor analysis (EFA) applied to the Childhood Behavior Checklist items from 9- to 10-year-olds (n = 9983; 47.8% female, 50.8% white) participating in the Adolescent Brain Cognitive Development study. The patterns of brain morphometry, white matter integrity and resting-state connectivity associated with each dimension were identified using kernel-based regularized least squares and compared between dimensions using Spearman’s correlation coefficient.

Results

ICA identified three psychopathology dimensions, representing opposition–disinhibition, cognitive dyscontrol, and negative affect, with distinct brain correlates. Opposition–disinhibition was negatively associated with cortical surface area, cognitive dyscontrol was negatively associated with anatomical and functional dysconnectivity while negative affect did not show discernable associations with any neuroimaging measure. EFA identified three dimensions representing broad externalizing, neurodevelopmental, and broad Internalizing problems with partially overlapping brain correlates. All EFA-derived dimensions were negatively associated with cortical surface area, whereas measures of functional and structural connectivity were associated only with the neurodevelopmental dimension.

Conclusions

This study highlights the importance of cortical surface area and global connectivity for psychopathology in preadolescents and provides evidence for dissociable psychopathology dimensions with distinct brain correlates.

Multivariate patterns of brain-behavior associations across the adult lifespan

The nature of brain-behavior covariations with increasing age is poorly understood. In the current study, we used a multivariate approach to investigate the covariation between behavioral-health variables and brain features across adulthood. We recruited healthy adults aged 20–73 years-old (29 younger, mean age = 25.6 years; 30 older, mean age = 62.5 years), and collected structural and functional MRI (s/fMRI) during a resting-state and three tasks. From the sMRI, we extracted cortical thickness and subcortical volumes; from the fMRI, we extracted activation peaks and functional network connectivity (FNC) for each task. We conducted canonical correlation analyses between behavioral-health variables and the sMRI, or the fMRI variables, across all participants. We found significant covariations for both types of neuroimaging phenotypes (ps = 0.0004) across all individuals, with cognitive capacity and age being the largest opposite contributors. We further identified different variables contributing to the models across phenotypes and age groups. Particularly, we found behavior was associated with different neuroimaging patterns between the younger and older groups. Higher cognitive capacity was supported by activation and FNC within the executive networks in the younger adults, while it was supported by the visual networks’ FNC in the older adults. This study highlights how the brain-behavior covariations vary across adulthood and provides further support that cognitive performance relies on regional recruitment that differs between older and younger individuals.

An update on the assessment of culture and environment in the ABCD Study®: Emerging literature and protocol updates over three measurement waves

Advances in our understanding of risk and resilience factors in adolescent brain health and development increasingly demand a broad set of assessment tools that consider a youth's peer, family, school, neighborhood, and cultural contexts in addition to neurobiological, genetic, and biomedical information. The Culture and Environment (CE) Workgroup (WG) of the Adolescent Brain Cognitive Development (ABCD) Study curates these important components of the protocol throughout ten years of planned data collection. In this report, the CE WG presents an update on the evolution of the ABCD Study® CE protocol since study inception (Zucker et al., 2018), as well as emerging findings that include CE measures. Background and measurement characteristics of instruments present in the study since baseline have already been described in our 2018 report, and therefore are only briefly described here. New measures introduced since baseline are described in more detail. Descriptive statistics on all measures are presented based on a total sample of 11,000+ youth and their caregivers assessed at baseline and the following two years. Psychometric properties of the measures, including longitudinal aspects of the data, are reported, along with considerations for future measurement waves. The CE WG ABCD® components are an essential part of the overall protocol that permits characterization of the unique cultural and social environment within which each developing brain is transactionally embedded.

Pubertal timing and functional neurodevelopmental alterations independently mediate the effect of family conflict on adolescent psychopathology

This study tested the hypothesis that early life adversity (ELA) heightens psychopathology risk by concurrently altering pubertal and neurodevelopmental timing, and associated gene transcription signatures. Analyses focused on threat- (family conflict/neighbourhood crime) and deprivation-related ELAs (parental inattentiveness/unmet material needs), using longitudinal data from 1514 biologically unrelated youths in the Adolescent Brain and Cognitive Development (ABCD) study. Typical developmental changes in white matter microstructure corresponded to widespread BOLD signal variability (BOLDsv) increases (linked to cell communication and biosynthesis genes) and region-specific task-related BOLDsv increases/decreases (linked to signal transduction, immune and external environmental response genes). Increasing resting-state (RS), but decreasing task-related BOLDsv predicted normative functional network segregation. Family conflict was the strongest concurrent and prospective contributor to psychopathology, while material deprivation constituted an additive risk factor. ELA-linked psychopathology was predicted by higher Time 1 threat-evoked BOLDSV (associated with axonal development, myelination, cell differentiation and signal transduction genes), reduced Time 2 RS BOLDsv (associated with cell metabolism and attention genes) and greater Time 1 to Time 2 control/attention network segregation. Earlier pubertal timing and neurodevelopmental alterations independently mediated ELA effects on psychopathology. Our results underscore the differential roles of the immediate and wider external environment(s) in concurrent and longer-term ELA consequences.

Widespread attenuating changes in brain connectivity associated with the general factor of psychopathology in 9- and 10-year olds

Convergent research identifies a general factor ("P factor") that confers transdiagnostic risk for psychopathology. Large-scale networks are key organizational units of the human brain. However, studies of altered network connectivity patterns associated with the P factor are limited, especially in early adolescence when most mental disorders are first emerging. We studied 11,875 9- and 10-year olds from the Adolescent Brain and Cognitive Development (ABCD) study, of whom 6593 had high-quality resting-state scans. Network contingency analysis was used to identify altered interconnections associated with the P factor among 16 large-scale networks. These connectivity changes were then further characterized with quadrant analysis that quantified the directionality of P factor effects in relation to neurotypical patterns of positive versus negative connectivity across connections. The results showed that the P factor was associated with altered connectivity across 28 network cells (i.e., sets of connections linking pairs of networks); pPERMUTATION values < 0.05 FDR-corrected for multiple comparisons. Higher P factor scores were associated with hypoconnectivity within default network and hyperconnectivity between default network and multiple control networks. Among connections within these 28 significant cells, the P factor was predominantly associated with "attenuating" effects (67%; pPERMUTATION < 0.0002), i.e., reduced connectivity at neurotypically positive connections and increased connectivity at neurotypically negative connections. These results demonstrate that the general factor of psychopathology produces attenuating changes across multiple networks including default network, involved in spontaneous responses, and control networks involved in cognitive control. Moreover, they clarify mechanisms of transdiagnostic risk for psychopathology and invite further research into developmental causes of distributed attenuated connectivity.

Neurodevelopment of the association cortices: Patterns, mechanisms, and implications for psychopathology

The human brain undergoes a prolonged period of cortical development that spans multiple decades. During childhood and adolescence, cortical development progresses from lower-order, primary and unimodal cortices with sensory and motor functions to higher-order, transmodal association cortices subserving executive, socioemotional, and mentalizing functions. The spatiotemporal patterning of cortical maturation thus proceeds in a hierarchical manner, conforming to an evolutionarily rooted, sensorimotor-to-association axis of cortical organization. This developmental program has been characterized by data derived from multimodal human neuroimaging and is linked to the hierarchical unfolding of plasticity-related neurobiological events. Critically, this developmental program serves to enhance feature variation between lower-order and higher-order regions, thus endowing the brain's association cortices with unique functional properties. However, accumulating evidence suggests that protracted plasticity within late-maturing association cortices, which represents a defining feature of the human developmental program, also confers risk for diverse developmental psychopathologies.

DNA Methylation and Resting Brain Function Mediate the Association between Childhood Urbanicity and Better Speed of Processing

Urbanicity has been suggested to affect cognition, but the underlying mechanism remains unknown. We examined whether epigenetic modification (DNA methylation, DNAm), and brain white matter fiber integrity (fractional anisotropy, FA) or local spontaneous brain function activity (regional homogeneity, ReHo) play roles in the association between childhood urbanicity and cognition based on 497 healthy Chinese adults. We found significant correlation between childhood urbanicity and better cognitive performance. Multiset canonical correlation analysis (mCCA) identified an intercorrelated DNAm-FA-ReHo triplet, which showed significant pairwise correlations (DNAm-FA: Bonferroni-adjusted P, P_bon = 4.99E−03, rho = 0.216; DNAm-ReHo: P_bon = 4.08E−03, rho = 0.239; ReHo-FA: P_bon = 1.68E−06, rho = 0.328). Causal mediation analysis revealed that 1) ReHo mediated 10.86% childhood urbanicity effects on the speed of processing and 2) childhood urbanicity alters ReHo through DNA methylation in the cadherin and Wnt signaling pathways (mediated effect: 48.55%). The mediation effect of increased ReHo in the superior temporal gyrus underlying urbanicity impact on a better speed of processing was further validated in an independent cohort. Our work suggests a mediation role for ReHo, particularly increased brain activity in the superior temporal gyrus, in the urbanicity-associated speed of processing.

Associations Between Neighborhood Disadvantage, Resting-State Functional Connectivity, and Behavior in the Adolescent Brain Cognitive Development Study: The Moderating Role of Positive Family and School Environments

BACKGROUND

Neighborhood disadvantage has consistently been associated with mental health and cognitive function, in addition to alterations in brain function and connectivity. However, positive environmental influences may buffer these effects. The aim of this study was to examine the association between neighborhood disadvantage and resting-state functional connectivity (rsFC), the moderating role of positive parenting and school environment, and relationships between disadvantage-associated rsFC patterns and mental health and cognition.

METHODS

In this preregistered study, we tested this hypothesis in a large sample of 7618 children (aged 9-10 years) from the Adolescent Brain Cognitive Development (ABCD) study. Specifically, we analyzed the relationship between neighborhood disadvantage and system-level FC. We also tested whether positive family and school environmental factors and sex moderated effects. Finally, we investigated multivariate relationships between disadvantage-associated rsFC patterns and cognition and mental health.

RESULTS

Disadvantage was associated with widespread alterations in FC across both higher-order (e.g., default mode network and dorsal attention network) and sensorimotor functional systems, some of which were moderated by positive environments. Implicated connections showed multivariate associations with behavior, whereby disadvantage-associated rsFC was generally associated with worse cognition and mental health. Disadvantage-associated connections also predicted variation in cognitive scores using machine learning models.

CONCLUSIONS

Our findings shed light on potential mechanisms (i.e., alteration of neural circuitry) through which neighborhood disadvantage may affect youth cognition and mental well-being. This work highlights the importance of positive family and school environments in mitigating some of these effects.