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

Importance: Childhood is a crucial developmental phase for mental health and cognitive function, both of which are commonly affected in patients with psychiatric disorders. This neurodevelopmental trajectory is shaped by a complex interplay of genetic and environmental factors. While common genetic variants account for a large proportion of inherited genetic risk, rare genetic variations, particularly copy number variants (CNVs), play a significant role in the genetic architecture of neurodevelopmental disorders. Despite their importance, the relevance of CNVs to child psychopathology and cognitive function in the general population remains underexplored. Objective: Investigating CNV associations with dimensions of child psychopathology and cognitive functions. Design Setting and Participants: ABCD ® study focuses on a cohort of over 11,875 youth aged 9 to 10, recruited from 21 sites in the US, aiming to investigate the role of various factors, including brain, environment, and genetic factors, in the etiology of mental and physical health from middle childhood through early adulthood. Data analysis occurred from April 2023 to April 2024. Main Outcomes and Measures: In this study, we utilized PennCNV and QuantiSNP algorithms to identify duplications and deletions larger than 50Kb across a cohort of 11,088 individuals from the Adolescent Brain Cognitive Development ® study. CNVs meeting quality control standards were subjected to a genome-wide association scan to identify regions associated with quantitative measures of broad psychiatric symptom domains and cognitive outcomes. Additionally, a CNV risk score, reflecting the aggregated burden of genetic intolerance to inactivation and dosage sensitivity, was calculated to assess its impact on variability in overall and dimensional child psychiatric and cognitive phenotypes. Results: In a final sample of 8,564 individuals (mean age=9.9 years, 4,532 males) passing quality control, we identified 4,111 individuals carrying 5,760 autosomal CNVs. Our results revealed significant associations between specific CNVs and our phenotypes of interest, psychopathology and cognitive function. For instance, a duplication at 10q26.3 was associated with overall psychopathology, and somatic complaints in particular. Additionally, deletions at 1q12.1, along with duplications at 14q11.2 and 10q26.3, were linked to overall cognitive function, with particular contributions from fluid intelligence (14q11.2), working memory (10q26.3), and reading ability (14q11.2). Moreover, individuals carrying CNVs previously associated with neurodevelopmental disorders exhibited greater impairment in social functioning and cognitive performance across multiple domains, in particular working memory. Notably, a higher deletion CNV risk score was significantly correlated with increased overall psychopathology (especially in dimensions of social functioning, thought disorder, and attention) as well as cognitive impairment across various domains. Conclusions and Relevance: In summary, our findings shed light on the contributions of CNVs to interindividual variability in complex traits related to neurocognitive development and child psychopathology. Key Points: Question: Are copy number variants (CNVs) contributing to individualized variability in psychopathology outcomes and cognitive functions in children?Findings: Both regional CNVs at 1q12.1, 10q26.3 and 14q11.2 and global CNV burden accounted for the variance in dimensions of psychopathology, particularly for attention and social problems, as well as cognitive performance, especially for working memory and reading ability.Meaning: Our findings suggest that, in addition to common genetic variants, gene dosage changes confer genetic susceptibility to child psychopathology and cognitive development.

In-vivo whole-cortex marker of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth.

A balanced excitation-inhibition ratio (E/I ratio) is critical for healthy brain function. Normative development of cortex-wide E/I ratio remains unknown. Here we non-invasively estimate a putative marker of whole-cortex E/I ratio by fitting a large-scale biophysically-plausible circuit model to resting-state functional MRI (fMRI) data. We first confirm that our model generates realistic brain dynamics in the Human Connectome Project. Next, we show that the estimated E/I ratio marker is sensitive to the GABA-agonist benzodiazepine alprazolam during fMRI. Alprazolam-induced E/I changes are spatially consistent with positron emission tomography measurement of benzodiazepine receptor density. We then investigate the relationship between the E/I ratio marker and neurodevelopment. We find that the E/I ratio marker declines heterogeneously across the cerebral cortex during youth, with the greatest reduction occurring in sensorimotor systems relative to association systems. Importantly, among children with the same chronological age, a lower E/I ratio marker (especially in association cortex) is linked to better cognitive performance. This result is replicated across North American (8.2 to 23.0 years old) and Asian (7.2 to 7.9 years old) cohorts, suggesting that a more mature E/I ratio indexes improved cognition during normative development. Overall, our findings open the door to studying how disrupted E/I trajectories may lead to cognitive dysfunction in psychopathology that emerges during youth.

A general exposome factor explains individual differences in functional brain network topography and cognition in youth.

Childhood environments are critical in shaping cognitive neurodevelopment. With the increasing availability of large-scale neuroimaging datasets with deep phenotyping of childhood environments, we can now build upon prior studies that have considered relationships between one or a handful of environmental and neuroimaging features at a time. Here, we characterize the combined effects of hundreds of inter-connected and co-occurring features of a child's environment ("exposome") and investigate associations with each child's unique, multidimensional pattern of functional brain network organization ("functional topography") and cognition. We apply data-driven computational models to measure the exposome and define personalized functional brain networks in pre-registered analyses. Across matched discovery (n=5139, 48.5% female) and replication (n=5137, 47.1% female) samples from the Adolescent Brain Cognitive Development study, the exposome was associated with current (ages 9-10) and future (ages 11-12) cognition. Changes in the exposome were also associated with changes in cognition after accounting for baseline scores. Cross-validated ridge regressions revealed that the exposome is reflected in functional topography and can predict performance across cognitive domains. Importantly, a single measure capturing a child's exposome could more accurately and parsimoniously predict cognition than a wealth of personalized neuroimaging data, highlighting the importance of children's complex, multidimensional environments in cognitive neurodevelopment.

Gray matter volume associations in youth with ADHD features of inattention and hyperactivity/impulsivity.

BACKGROUND: Prior research has shown smaller cortical and subcortical gray matter volumes among individuals with attention-deficit/hyperactivity disorder (ADHD). However, neuroimaging studies often do not differentiate between inattention and hyperactivity/impulsivity, which are distinct core features of ADHD. The present study uses an approach to disentangle overlapping variance to examine the neurostructural heterogeneity of inattention and hyperactivity/impulsivity dimensions. METHODS: We analyzed data from 10,692 9- to 10-year-old children from the Adolescent Brain Cognitive Development (ABCD) Study. Confirmatory factor analysis was used to derive factors representing inattentive and hyperactive/impulsive traits. We employed structural equation modeling to examine these factors' associations with gray matter volume while controlling for the shared variance between factors. RESULTS: Greater endorsement of inattentive traits was associated with smaller bilateral caudal anterior cingulate and left parahippocampal volumes. Greater endorsement of hyperactivity/impulsivity traits was associated with smaller bilateral caudate and left parahippocampal volumes. The results were similar when accounting for socioeconomic status, medication, and in-scanner motion. The magnitude of these findings increased when accounting for overall volume and intracranial volume, supporting a focal effect in our results. CONCLUSIONS: Inattentive and hyperactivity/impulsivity traits show common volume deficits in regions associated with visuospatial processing and memory while at the same time showing dissociable differences, with inattention showing differences in areas associated with attention and emotion regulation and hyperactivity/impulsivity associated with volume differences in motor activity regions. Uncovering such biological underpinnings within the broader disorder of ADHD allows us to refine our understanding of ADHD presentations.

Early life stress and functional network topology in children.

Brain networks are continuously modified throughout development, yet this plasticity can also make functional networks vulnerable to early life stress. Little is currently known about the effect of early life stress on the functional organization of the brain. The current study investigated the association between environmental stressors and network topology using data from the Adolescent Brain Cognitive DevelopmentSM (ABCD®) Study. Hierarchical modeling identified a general factor of environmental stress, representing the common variance across multiple stressors, as well as four subfactors including familial dynamics, interpersonal support, neighborhood SES deprivation, and urbanicity. Functional network topology metrics were obtained using graph theory at rest and during tasks of reward processing, inhibition, and affective working memory. The general factor of environmental stress was associated with less specialization of networks, represented by lower modularity at rest. Local metrics indicated that general environmental stress was also associated with less efficiency in the subcortical-cerebellar and visual networks while showing greater efficiency in the default mode network at rest. Subfactors of environmental stress were associated with differences in specialization and efficiency in select networks. The current study illustrates that a wide range of stressors in a child's environment are associated with differences in brain network topology.

Validation of the structured interview section of the penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT GOASSESS).

Large-scale studies and burdened clinical settings require precise, efficient measures that assess multiple domains of psychopathology. Computerized adaptive tests (CATs) can reduce administration time without compromising data quality. We examined feasibility and validity of an adaptive psychopathology measure, GOASSESS, in a clinical community-based sample (N = 315; ages 18-35) comprising three groups: healthy controls, psychosis, mood/anxiety disorders. Assessment duration was compared between the Full and CAT GOASSESS. External validity was tested by comparing how the CAT and Full versions related to demographic variables, study group, and socioeconomic status. The relationships between scale scores and criteria were statistically compared within a mixed-model framework to account for dependency between relationships. Convergent validity was assessed by comparing scores of the CAT and the Full GOASSESS using Pearson correlations. The CAT GOASSESS reduced interview duration by more than 90 % across study groups and preserved relationships to external criteria and demographic variables as the Full GOASSESS. All CAT GOASSESS scales could replace those of the Full instrument. Overall, the CAT GOASSESS showed acceptable psychometric properties and demonstrated feasibility by markedly reducing assessment time compared to the Full GOASSESS. The adaptive version could be used in large-scale studies or clinical settings for intake screening.

Mapping potential pathways from polygenic liability through brain structure to psychological problems across the transition to adolescence.

BACKGROUND: We used a polygenic score for externalizing behavior (extPGS) and structural MRI to examine potential pathways from genetic liability to conduct problems via the brain across the adolescent transition. METHODS: Three annual assessments of child conduct problems, attention-deficit/hyperactivity problems, and internalizing problems were conducted across across 9-13 years of age among 4,475 children of European ancestry in the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®). RESULTS: The extPGS predicted conduct problems in each wave (R2 = 2.0%-2.9%). Bifactor models revealed that the extPRS predicted variance specific to conduct problems (R2 = 1.7%-2.1%), but also variance that conduct problems shared with other measured problems (R2 = .8%-1.4%). Longitudinally, extPGS predicted levels of specific conduct problems (R2 = 2.0%), but not their slope of change across age. The extPGS was associated with total gray matter volume (TGMV; R2 = .4%) and lower TGMV predicted both specific conduct problems (R2 = 1.7%-2.1%) and the variance common to all problems in each wave (R2 = 1.6%-3.1%). A modest proportion of the polygenic liability specific to conduct problems in each wave was statistically mediated by TGMV. CONCLUSIONS: Across the adolescent transition, the extPGS predicted both variance specific to conduct problems and variance shared by all measured problems. The extPGS also was associated with TGMV, which robustly predicted conduct problems. Statistical mediation analyses suggested the hypothesis that polygenic variation influences individual differences in brain development that are related to the likelihood of conduct problems during the adolescent transition, justifying new research to test this causal hypothesis.

Development of an individualized risk calculator of treatment resistance in patients with first-episode psychosis (TRipCal) using automated machine learning: a 12-year follow-up study with clozapine prescription as a proxy indicator.

About 15-40% of patients with schizophrenia are treatment resistance (TR) and require clozapine. Identifying individuals who have higher risk of development of TR early in the course of illness is important to provide personalized intervention. A total of 1400 patients with FEP enrolled in the early intervention for psychosis service or receiving the standard psychiatric service between July 1, 1998, and June 30, 2003, for the first time were included. Clozapine prescriptions until June 2015, as a proxy of TR, were obtained. Premorbid information, baseline characteristics, and monthly clinical information were retrieved systematically from the electronic clinical management system (CMS). Training and testing samples were established with random subsampling. An automated machine learning (autoML) approach was used to optimize the ML algorithm and hyperparameters selection to establish four probabilistic classification models (baseline, 12-month, 24-month, and 36-month information) of TR development. This study found 191 FEP patients (13.7%) who had ever been prescribed clozapine over the follow-up periods. The ML pipelines identified with autoML had an area under the receiver operating characteristic curve ranging from 0.676 (baseline information) to 0.774 (36-month information) in predicting future TR. Features of baseline information, including schizophrenia diagnosis and age of onset, and longitudinal clinical information including symptoms variability, relapse, and use of antipsychotics and anticholinergic medications were important predictors and were included in the risk calculator. The risk calculator for future TR development in FEP patients (TRipCal) developed in this study could support the continuous development of data-driven clinical tools to assist personalized interventions to prevent or postpone TR development in the early course of illness and reduce delay in clozapine initiation.

Validation of the cognitive section of the Penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT-CCNB).

BACKGROUND: The Penn Computerized Neurocognitive Battery is an efficient tool for assessing brain-behavior domains, and its efficiency was augmented via computerized adaptive testing (CAT). This battery requires validation in a separate sample to establish psychometric properties. METHODS: In a mixed community/clinical sample of N = 307 18-to-35-year-olds, we tested the relationships of the CAT tests with the full-form tests. We compared discriminability among recruitment groups (psychosis, mood, control) and examined how their scores relate to demographics. CAT-Full relationships were evaluated based on a minimum inter-test correlation of 0.70 or an inter-test correlation within at least 0.10 of the full-form correlation with a previous administration of the full battery. Differences in criterion relationships were tested via mixed models. RESULTS: Most tests (15/17) met the minimum criteria for replacing the full-form with the updated CAT version (mean r = 0.67; range = 0.53-0.80) when compared to relationships of the full-forms with previous administrations of the full-forms (mean r = 0.68; range = 0.50-0.85). Most (16/17) CAT-based relationships with diagnostics and other validity criteria were indistinguishable (interaction p > 0.05) from their full-form counterparts. CONCLUSIONS: The updated CNB shows psychometric properties acceptable for research. The full-forms of some tests should be retained due to insufficient time savings to justify the loss in precision.

Development of white matter fiber covariance networks supports executive function in youth.

During adolescence, the brain undergoes extensive changes in white matter structure that support cognition. Data-driven approaches applied to cortical surface properties have led the field to understand brain development as a spatially and temporally coordinated mechanism that follows hierarchically organized gradients of change. Although white matter development also appears asynchronous, previous studies have relied largely on anatomical tract-based atlases, precluding a direct assessment of how white matter structure is spatially and temporally coordinated. Harnessing advances in diffusion modeling and machine learning, we identified 14 data-driven patterns of covarying white matter structure in a large sample of youth. Fiber covariance networks aligned with known major tracts, while also capturing distinct patterns of spatial covariance across distributed white matter locations. Most networks showed age-related increases in fiber network properties, which were also related to developmental changes in executive function. This study delineates data-driven patterns of white matter development that support cognition.

Allostatic load in early adolescence: gene / environment contributions and relevance for mental health.

Background: Allostatic load is the cumulative "wear and tear" on the body due to chronic adversity. We aimed to test poly-environmental (exposomic) and polygenic contributions to allostatic load and their combined contribution to early adolescent mental health. Methods: We analyzed data on N = 5,035 diverse youth (mean age 12) from the Adolescent Brain Cognitive Development Study (ABCD). Using dimensionality reduction method, we calculated and overall allostatic load score (AL) using body mass index [BMI], waist circumference, blood pressure, blood glycemia, blood cholesterol, and salivary DHEA. Childhood exposomic risk was quantified using multi-level environmental exposures before age 11. Genetic risk was quantified using polygenic risk scores (PRS) for metabolic system susceptibility (type 2 diabetes [T2D]) and stress-related psychiatric disease (major depressive disorder [MDD]). We used linear mixed effects models to test main, additive, and interactive effects of exposomic and polygenic risk (independent variables) on AL (dependent variable). Mediation models tested the mediating role of AL on the pathway from exposomic and polygenic risk to youth mental health. Models adjusted for demographics and genetic principal components. Results: We observed disparities in AL with non-Hispanic White youth having significantly lower AL compared to Hispanic and Non-Hispanic Black youth. In the diverse sample, childhood exposomic burden was associated with AL in adolescence (beta=0.25, 95%CI 0.22-0.29, P<.001). In European ancestry participants (n=2,928), polygenic risk of both T2D and depression was associated with AL (T2D-PRS beta=0.11, 95%CI 0.07-0.14, P<.001; MDD-PRS beta=0.05, 95%CI 0.02-0.09, P=.003). Both polygenic scores showed significant interaction with exposomic risk such that, with greater polygenic risk, the association between exposome and AL was stronger. AL partly mediated the pathway to youth mental health from exposomic risk and from MDD-PRS, and fully mediated the pathway from T2D-PRS. Conclusions: AL can be quantified in youth using anthropometric and biological measures and is mapped to exposomic and polygenic risk. Main and interactive environmental and genetic effects support a diathesis-stress model. Findings suggest that both environmental and genetic risk be considered when modeling stress-related health conditions.

A pattern of cognitive resource disruptions in childhood psychopathology.

The Hurst exponent (H) isolated in fractal analyses of neuroimaging time series is implicated broadly in cognition. Within this literature, H is associated with multiple mental disorders, suggesting that H is transdimensionally associated with psychopathology. Here, we unify these results and demonstrate a pattern of decreased H with increased general psychopathology and attention-deficit/hyperactivity factor scores during a working memory task in 1,839 children. This pattern predicts current and future cognitive performance in children and some psychopathology in 703 adults. This pattern also defines psychological and functional axes associating psychopathology with an imbalance in resource allocation between fronto-parietal and sensorimotor regions, driven by reduced resource allocation to fronto-parietal regions. This suggests the hypothesis that impaired working memory function in psychopathology follows from a reduced cognitive resource pool and a reduction in resources allocated to the task at hand.

High executive functioning is associated with reduced posttraumatic stress after trauma exposure among male U.S. military personnel.

Introduction: Evidence suggests that executive function (EF) may play a key role in development of PTSD, possibly influenced by factors such as trauma type and timing. Since EF can be improved through intervention, it may be an important target for promoting resilience to trauma exposure. However, more research is needed to understand the relation between trauma exposure, EF, and PTSD. The goal of this study was to improve understanding of EF as a potential antecedent or protective factor for the development of PTSD among military personnel. Method: In a cohort of U.S. Marines and Navy personnel (N = 1,373), the current study tested the association between exposure to traumatic events (pre-deployment and during deployment) and PTSD severity, and whether EF moderated these associations. Three types of pre-deployment trauma exposure were examined: cumulative exposure, which included total number of events participants endorsed as having happened to them, witnessed, or learned about; direct exposure, which included total number of events participants endorsed as having happened to them; and interpersonal exposure, which included total number of interpersonally traumatic events participants' endorsed. EF was measured using the Penn Computerized Neurocognitive Battery. Results: EF was associated with less PTSD symptom severity at pre-deployment, even when adjusting for trauma exposure, alcohol use, traumatic brain injury, and number of years in the military. EF also moderated the relation between cumulative trauma exposure and interpersonal trauma exposure and PTSD, with higher EF linked to a 20 and 33% reduction in expected point increase in PTSD symptoms with cumulative and interpersonal trauma exposure, respectively. Finally, higher pre-deployment EF was associated with reduced PTSD symptom severity at post-deployment, independent of deployment-related trauma exposure and adjusting for pre-deployment PTSD. Conclusion: Our results suggest that EF plays a significant, if small role in the development of PTSD symptoms after trauma exposure among military personnel. These findings provide important considerations for future research and intervention and prevention, specifically, incorporating a focus on improving EF in PTSD treatment.

Hoarding behavior and its association with mental health and functioning in a large youth sample.

Hoarding behavior is prevalent in children and adolescents, yet clinicians do not routinely inquire about it and youth may not spontaneously report it due to stigma. It is unknown whether hoarding behavior, over and above obsessive-compulsive symptoms (OCS), is associated with major clinical factors in a general youth population. This observational study included N = 7054 youth who were not seeking help for mental health problems (ages 11-21, 54% female) and completed a structured interview that included evaluation of hoarding behavior and OCS, as a part of the Philadelphia Neurodevelopmental Cohort between November 2009 and December 2011. We employed regression models with hoarding behavior and OCS (any/none) as independent variables, and continuous (linear regression) or binary (logistic regression) mental health measures as dependent variables. All models covaried for age, sex, race, and socioeconomic status. A total of 374 participants endorsed HB (5.3%), most of which reported additional OCS (n = 317). When accounting for OCS presence, hoarding behavior was associated with greater dimensional psychopathology burden (i.e., higher P-factor) (ß = 0.19, p < .001), and with poorer functioning (i.e., lower score on the child global assessment scale) (ß = - 0.07, p < .001). The results were consistent when modeling psychopathology using binary variables. The results remained significant in sensitivity analyses accounting for count of endorsed OCS and excluding participants who met criteria for obsessive-compulsive disorder (n = 210). These results suggest that hoarding behavior among youth is associated with poorer mental health and functioning, independent of OCS. Brief hoarding-behavior assessments in clinical settings may prove useful given hoarding behavior's stigma and detrimental health associations.

Evaluation of a new intrinsic and extrinsic motivation scale in youth with psychosis spectrum symptoms.

BACKGROUND: Impairment in intrinsic motivation (IM), the drive to satisfy internal desires like mastery, may play a key role in disability in psychosis. However, we have limited knowledge regarding relative impairments in IM compared to extrinsic motivation (EM) or general motivation (GM), in part due to limitations in existing measures. METHODS: Here we address this gap using a novel Trait Intrinsic and Extrinsic Motivation self-report scale in a sample of n = 243 participants including those with schizophrenia, psychosis-risk, and healthy controls. Each of the 7 IM and 6 EM items used a 7-point Likert scale assessing endorsement of dispositional statements. Bifactor analyses of these items yielded distinct IM, EM, and GM factor scores. Convergent and discriminant validity were examined in relation to General Causality Orientation Scale (GCOS-CP) and Quality of Life 3-item IM measure (QLS-IM). Utility was assessed in relation to psychosis-spectrum (PS) status and CAINS clinical amotivation. RESULTS: IM and EM showed acceptable inter-item consistency (IM: α = 0.88; EM: α = 0.66); the bifactor model exhibited fit that varied from good to borderline to inadequate depending on the specific fit metric (SRMR = 0.038, CFI = 0.94, RMSEA = 0.106 ± 0.014). IM scores correlated with established IM measures: GCOS-CP Autonomy (rho = 0.38, p < 0.01) and QLS-IM (rho = 0.29, p < 0.01). Supporting discriminant validity, IM did not correlate with GCOS-CP Control (rho = -0.14, p > 0.05). Two-year stability in an available longitudinal subset (n = 35) was strong (IM: rho = 0.64, p < 0.01; EM: rho = 0.55, p < 0.01). Trait IM was lower in PS youth (t = 4.24, p < 0.01), and correlated with clinical amotivation (rho = -0.36, p < 0.01); EM did not show significant clinical associations. CONCLUSIONS: These results demonstrate the clinical relevance of IM in psychosis risk. They also provide preliminary support for the reliability, validity and utility of this new Trait IM-EM scale, which addresses a measurement gap and can facilitate identification of neurobehavioral and clinical correlates of IM deficits.

Multivariate analytical approaches for investigating brain-behavior relationships.

Background: Many studies of brain-behavior relationships rely on univariate approaches where each variable of interest is tested independently, which does not allow for the simultaneous investigation of multiple correlated variables. Alternatively, multivariate approaches allow for examining relationships between psychopathology and neural substrates simultaneously. There are multiple multivariate methods to choose from that each have assumptions which can affect the results; however, many studies employ one method without a clear justification for its selection. Additionally, there are few studies illustrating how differences between methods manifest in examining brain-behavior relationships. The purpose of this study was to exemplify how the choice of multivariate approach can change brain-behavior interpretations. Method: We used data from 9,027 9- to 10-year-old children from the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®) to examine brain-behavior relationships with three commonly used multivariate approaches: canonical correlation analysis (CCA), partial least squares correlation (PLSC), and partial least squares regression (PLSR). We examined the associations between psychopathology dimensions including general psychopathology, attention-deficit/hyperactivity symptoms, conduct problems, and internalizing symptoms with regional brain volumes. Results: The results of CCA, PLSC, and PLSR showed both consistencies and differences in the relationship between psychopathology symptoms and brain structure. The leading significant component yielded by each method demonstrated similar patterns of associations between regional brain volumes and psychopathology symptoms. However, the additional significant components yielded by each method demonstrated differential brain-behavior patterns that were not consistent across methods. Conclusion: Here we show that CCA, PLSC, and PLSR yield slightly different interpretations regarding the relationship between child psychopathology and brain volume. In demonstrating the divergence between these approaches, we exemplify the importance of carefully considering the method's underlying assumptions when choosing a multivariate approach to delineate brain-behavior relationships.

Atypical Functional Network Properties and Associated Dimensions of Child Psychopathology During Rest and Task Performance.

Background: When brain networks deviate from typical development, this is thought to contribute to varying forms of psychopathology. However, research has been limited by the reliance on discrete diagnostic categories that overlook the potential for psychological comorbidity and the dimensional nature of symptoms. Methods: This study examined the topology of functional networks in association with 4 bifactor-defined psychopathology dimensions-general psychopathology, internalizing symptoms, conduct problems, and attention-deficit/hyperactivity disorder symptoms-via the Child Behavior Checklist in a sample of 3568 children from the ABCD (Adolescent Brain Cognitive Development) Study. Local and global graph theory metrics were calculated at rest and during tasks of reward processing, inhibition, and working memory. Results: Greater attention-deficit/hyperactivity disorder symptoms were associated with reduced modularity across rest and tasks as well as reduced local efficiency in motor networks at rest. Results survived sensitivity analyses for medication and socioeconomic status. Greater conduct problem symptoms were associated with reduced modularity on working memory and reward processing tasks; however, these results did not persist after sensitivity analyses. General psychopathology and internalizing symptoms showed no significant network associations. Conclusions: Our findings suggest reduced efficiency in topology in those with greater attention-deficit/hyperactivity disorder symptoms across 4 critical cognitive states, with conduct problems also showing network deficits, although less consistently. This may suggest that modularity deficits are a neurobiological marker of externalizing behavior in children. Such specificity has not been demonstrated before using graph theory metrics and has the potential to redefine our understanding of network deficits in children with psychopathology symptoms.

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.

Development of Iron Status Measures during Youth: Associations with Sex, Neighborhood Socioeconomic Status, Cognitive Performance, and Brain Structure.

BACKGROUND: Iron is essential to brain function, and iron deficiency during youth may adversely impact neurodevelopment. Understanding the developmental time course of iron status and its association with neurocognitive functioning is important for identifying windows for intervention. OBJECTIVES: This study aimed to characterize developmental change in iron status and understand its association with cognitive performance and brain structure during adolescence using data from a large pediatric health network. METHODS: This study included a cross-sectional sample of 4899 participants (2178 males; aged 8-22 y at the time of participation, M [SD] = 14.24 [3.7]) who were recruited from the Children's Hospital of Philadelphia network. Prospectively collected research data were enriched with electronic medical record data that included hematological measures related to iron status, including serum hemoglobin, ferritin, and transferrin (33,015 total samples). At the time of participation, cognitive performance was assessed using the Penn Computerized Neurocognitive Battery, and brain white matter integrity was assessed using diffusion-weighted MRI in a subset of individuals. RESULTS: Developmental trajectories were characterized for all metrics and revealed that sex differences emerged after menarche such that females had reduced iron status relative to males [all R2partial > 0.008; all false discovery rates (FDRs) < 0.05]. Higher socioeconomic status was associated with higher hemoglobin concentrations throughout development (R2partial = 0.005; FDR < 0.001), and the association was greatest during adolescence. Higher hemoglobin concentrations were associated with better cognitive performance during adolescence (R2partial = 0.02; FDR < 0.001) and mediated the association between sex and cognition (mediation effect = -0.107; 95% CI: -0.191, -0.02). Higher hemoglobin concentration was also associated with greater brain white matter integrity in the neuroimaging subsample (R2partial = 0.06, FDR = 0.028). CONCLUSIONS: Iron status evolves during youth and is lowest in females and individuals of low socioeconomic status during adolescence. Diminished iron status during adolescence has consequences for neurocognition, suggesting that this critical period of neurodevelopment may be an important window for intervention that has the potential to reduce health disparities in at-risk populations.

Psychosis brain subtypes validated in first-episode cohorts and related to illness remission: results from the PHENOM consortium.

Using machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups-a 'lower brain volume' subgroup (SG1) and an 'higher striatal volume' subgroup (SG2) with otherwise normal brain structure. In this study, we investigated whether the MRI signatures of these subgroups were also already present at the time of the first-episode of psychosis (FEP) and whether they were related to clinical presentation and clinical remission over 1-, 3-, and 5-years. We included 572 FEP and 424 healthy controls (HC) from 4 sites (Sao Paulo, Santander, London, Melbourne) of the PHENOM consortium. Our prior MRI subgrouping models (671 participants; USA, Germany, and China) were applied to both FEP and HC. Participants were assigned into 1 of 4 categories: subgroup 1 (SG1), subgroup 2 (SG2), no subgroup membership ('None'), and mixed SG1 + SG2 subgroups ('Mixed'). Voxel-wise analyses characterized SG1 and SG2 subgroups. Supervised machine learning analyses characterized baseline and remission signatures related to SG1 and SG2 membership. The two dominant patterns of 'lower brain volume' in SG1 and 'higher striatal volume' (with otherwise normal neuromorphology) in SG2 were identified already at the first episode of psychosis. SG1 had a significantly higher proportion of FEP (32%) vs. HC (19%) than SG2 (FEP, 21%; HC, 23%). Clinical multivariate signatures separated the SG1 and SG2 subgroups (balanced accuracy = 64%; p < 0.0001), with SG2 showing higher education but also greater positive psychosis symptoms at first presentation, and an association with symptom remission at 1-year, 5-year, and when timepoints were combined. Neuromorphological subtypes of schizophrenia are already evident at illness onset, separated by distinct clinical presentations, and differentially associated with subsequent remission. These results suggest that the subgroups may be underlying risk phenotypes that could be targeted in future treatment trials and are critical to consider when interpreting neuroimaging literature.