Functional brain connectivity predictors of prospective substance use initiation and their environmental correlates.

Background: Early substance use initiation (SUI) places youth at substantially higher risk for later substance use disorders. Furthermore, adolescence is a critical period for the maturation of brain networks, the pace and magnitude of which are susceptible to environmental influences and may shape risk for SUI. Methods: We examined whether patterns of functional brain connectivity during rest (rsFC), measured longitudinally in pre-and-early adolescence, can predict future SUI. In an independent sub-sample, we also tested whether these patterns are associated with key environmental factors, specifically neighborhood pollution and socioeconomic dimensions. We utilized data from the Adolescent Brain Cognitive Development (ABCD) Study®. SUI was defined as first-time use of at least one full dose of alcohol, nicotine, cannabis, or other drugs. We created a control group (N = 228) of participants without SUI who were matched with the SUI group (N = 233) on age, sex, race/ethnicity, and parental income and education. Results: Multivariate analysis showed that whole-brain rsFC prior to SUI during 9-10 and 11-12 years of age successfully differentiated the prospective SUI and control groups. This rsFC signature was expressed more at older ages in both groups, suggesting a pattern of accelerated maturation in the SUI group in the years prior to SUI. In an independent sub-sample (N = 2,854) and adjusted for family socioeconomic factors, expression of this rsFC pattern was associated with higher pollution, but not neighborhood disadvantage. Conclusion: Brain functional connectivity patterns in early adolescence that are linked to accelerated maturation and environmental exposures can predict future SUI in youth.

The link between daily affective complexity and anxiety is altered by oral contraceptive use.

Affective complexity - the unique ways in which individuals' emotions covary and differentiate - is an important aspect of internalizing problems. For instance, daily affective complexity has been linked to anxiety increases in women and to decreases in men. The mechanisms underlying this gender difference have not been widely investigated, but a role for ovarian hormones is likely. Research on oral contraceptives (OCs) provides promising insights into such mechanisms, as OCs suppress endogenous ovarian hormone production and vary in exogenous hormone formulations. Thus, the goal of this study was to examine links between daily affective complexity and internalizing problems in OC users (n = 84), focusing on dimensionally-assessed anxiety, and to investigate whether the links varied by pill formulation. Affective complexity was operationalized as number of factors for each person, as estimated by p-technique (i.e., person-specific factor analysis) of 75-day intensive longitudinal data. There was not a relation between affective complexity and anxiety in OC users, and this did not depend on OC pill formulation (i.e., estrogenic, progestational, or androgenic activities). Thus, OC use may blunt the relation between affective complexity and anxiety, as OC users had a relation in between the established positive relation for naturally cycling women and the inverse for men (despite a similar range of factors). Findings are consistent with a growing literature showing that OC use modulates stress and anxiety-linked processes, and suggest that gendered mechanisms underlying the relation between affective complexity and anxiety may be suppressed along with ovarian hormones in OC users.

100 days of Adolescence: Elucidating Externalizing Behaviors Through the Daily Assessment of Inhibitory Control.

Inhibitory control is a transdiagnostic risk factor for externalizing behaviors, particularly during adolescence. Despite advances in understanding links between inhibitory control and externalizing behaviors across youth on average, significant questions remain about how these links play out in the day-to-day lives of individual adolescents. The goals of the current study were to: (1) validate a novel 100-occasion measure of inhibitory control; (2) assess links between day-to-day fluctuations in inhibitory control and individual differences in externalizing behaviors; and (3) illustrate the potential of intensive longitudinal studies for person-specific analyses of adolescent externalizing behaviors. Participants were 106 youth (57.5% female, Mage = 13.34 years; SDage = 1.92) who completed a virtual baseline session followed by 100 daily surveys, including an adapted Stroop Color Word task designed to assess inhibitory control. Results suggested that the novel task was generally reliable and valid, and that inhibitory control fluctuated across days in ways that were meaningfully associated with individual differences in baseline impulsive behaviors. Results of illustrative personalized analyses suggested that inhibitory control had more influence in the daily networks of adolescents who used substances during the 100 days than in a matched set of adolescents who did not. This work marks a path forward in intensive longitudinal research by validating a novel inhibitory control measure, revealing that daily fluctuations in inhibitory control may be a unique construct broadly relevant to adolescent externalizing problems, and at the same time, highlighting that links between daily inhibitory control and impulsive behaviors are adolescent-specific.

Socioeconomic resources in youth are linked to divergent patterns of network integration and segregation across the brain's transmodal axis.

Socioeconomic resources (SER) calibrate the developing brain to the current context, which can confer or attenuate risk for psychopathology across the lifespan. Recent multivariate work indicates that SER levels powerfully influence intrinsic functional connectivity patterns across the entire brain. Nevertheless, the neurobiological meaning of these widespread alterations remains poorly understood, despite its translational promise for early risk identification, targeted intervention, and policy reform. In the present study, we leverage the resources of graph theory to precisely characterize multivariate and univariate associations between household SER and the functional integration and segregation (i.e., participation coefficient, within-module degree) of brain regions across major cognitive, affective, and sensorimotor systems during the resting state in 5,821 youth (ages 9-10 years) from the Adolescent Brain Cognitive Development (ABCD) Study. First, we establish that decomposing the brain into profiles of integration and segregation captures more than half of the multivariate association between SER and functional connectivity with greater parsimony (100-fold reduction in number of features) and interpretability. Second, we show that the topological effects of SER are not uniform across the brain; rather, higher SER levels are related to greater integration of somatomotor and subcortical systems, but greater segregation of default mode, orbitofrontal, and cerebellar systems. Finally, we demonstrate that the effects of SER are spatially patterned along the unimodal-transmodal gradient of brain organization. These findings provide critical interpretive context for the established and widespread effects of SER on brain organization, indicating that SER levels differentially configure the intrinsic functional architecture of developing unimodal and transmodal systems. This study highlights both sensorimotor and higher-order networks that may serve as neural markers of environmental stress and opportunity, and which may guide efforts to scaffold healthy neurobehavioral development among disadvantaged communities of youth.

Generalizable prediction of childhood ADHD symptoms from neurocognitive testing and youth characteristics.

Childhood attention-deficit/hyperactivity disorder (ADHD) symptoms are believed to result from disrupted neurocognitive development. However, evidence for the clinical and predictive value of neurocognitive assessments in this context has been mixed, and there have been no large-scale efforts to quantify their potential for use in generalizable models that predict individuals' ADHD symptoms in new data. Using data drawn from the Adolescent Brain Cognitive Development Study (ABCD), a consortium that recruited a diverse sample of over 10,000 youth (ages 9-10 at baseline) across 21 U.S. sites, we develop and test cross-validated machine learning models for predicting youths' ADHD symptoms using neurocognitive abilities, demographics, and child and family characteristics. Models used baseline demographic and biometric measures, geocoded neighborhood data, youth reports of child and family characteristics, and neurocognitive tests to predict parent- and teacher-reported ADHD symptoms at the 1-year and 2-year follow-up time points. Predictive models explained 15-20% of the variance in 1-year ADHD symptoms for ABCD Study sites that were left out of the model-fitting process and 12-13% of the variance in 2-year ADHD symptoms. Models displayed high generalizability across study sites and trivial loss of predictive power when transferred from training data to left-out data. Features from multiple domains contributed meaningfully to prediction, including neurocognition, sex, self-reported impulsivity, parental monitoring, and screen time. This work quantifies the information value of neurocognitive abilities and other child characteristics for predicting ADHD symptoms and provides a foundational method for predicting individual youths' symptoms in new data across contexts.

Neighborhood air pollution is negatively associated with neurocognitive maturation in early adolescence.

The ability to maintain focus and process task-relevant information continues developing during adolescence, but the specific physical environmental factors that influence this development remain poorly characterized. One candidate factor is air pollution. Evidence suggests that small particulate matter and NO2 concentrations in the air may negatively impact cognitive development in childhood. We assessed the relationship between neighborhood air pollution and the changes in performance on the n-back task, a test of attention and working memory, in the Adolescent Brain Cognitive Development (ABCD) Study's baseline (ages 9-10) and two-year-follow-up releases (Y2, ages 11-12; n = 5,256). In the behavioral domain, multiple linear regression showed that developmental change in n-back task performance was negatively associated with neighborhood air pollution (ß = -.044, t = -3.11, p = .002), adjusted for covariates capturing baseline cognitive performance of the child, their parental income and education, family conflicts, and their neighborhood's population density, crime rate, perceived safety, and Area Deprivation Index (ADI). The strength of the adjusted association for air pollution was similar to parental income, family conflict, and neighborhood ADI. In the neuroimaging domain, we evaluated a previously published youth cognitive composite Connectome-based Predictive Model (ccCPM), and again found that decreased developmental change in the strength of the ccCPM from pre- to early adolescence was associated with neighborhood air pollution (ß = -.110, t = -2.69, p = .007), adjusted for the covariates mentioned above and head motion. Finally, we found that the developmental change in ccCPM strength was predictive of the developmental change in n-back performance (r = .157, p < .001), and there was an indirect-only mediation where the effect of air pollution on change in n-back performance was mediated by the change in the ccCPM strength (ßindirect effect = -.013, p = .029). In conclusion, neighborhood air pollution is associated with lags in the maturation of youth cognitive performance and decreased strengthening of the brain networks supporting cognitive abilities over time.

A cognitive process modeling framework for the ABCD study stop-signal task.

The Adolescent Brain Cognitive Development (ABCD) Study is a longitudinal neuroimaging study of unprecedented scale that is in the process of following over 11,000 youth from middle childhood though age 20. However, a design feature of the study's stop-signal task violates "context independence", an assumption critical to current non-parametric methods for estimating stop-signal reaction time (SSRT), a key measure of inhibitory ability in the study. This has led some experts to call for the task to be changed and for previously collected data to be used with caution. We present a cognitive process modeling framework, the RDEX-ABCD model, that provides a parsimonious explanation for the impact of this design feature on "go" stimulus processing and successfully accounts for key behavioral trends in the ABCD data. Simulation studies using this model suggest that failing to account for the context independence violations in the ABCD design can lead to erroneous inferences in several realistic scenarios. However, we demonstrate that RDEX-ABCD effectively addresses these violations and can be used to accurately measure SSRT along with an array of additional mechanistic parameters of interest (e.g., attention to the stop signal, cognitive efficiency), advancing investigators' ability to draw valid and nuanced inferences from ABCD data. AVAILABILITY OF DATA AND MATERIALS: Data from the ABCD Study are available through the NIH Data Archive (NDA): nda.nih.gov/abcd. Code for all analyses featured in this study is openly available on the Open Science Framework (OSF): osf.io/2h8a7/.

Benefits and challenges of using logistic regression to assess neuropsychological performance validity: Evidence from a simulation study.

Logistic regression (LR) is recognized as a promising method for making decisions about neuropsychological performance validity by integrating information across multiple measures. However, this method has yet to be widely adopted in clinical practice, likely because several open questions remain about its utility relative to simpler methods, its effectiveness across different clinical contexts, and its feasibility at sample sizes common in the field. The current study addresses these questions by assessing classification performance of logistic regression and alternative methods across an array of simulated data sets.We simulated scores of valid and invalid performers on 6 tests designed to mimic the psychometric and distributional properties of real performance validity measures. Out-of-sample predictive performance of LR and a commonly used alternative ("vote counting") was assessed across different base rates, validity measure properties, and sample sizes.LR improved classification accuracy by 2%-12% across simulation conditions, primarily by improving sensitivity. False positives and negatives can be further reduced when LR predictions are interpreted as continuous, rather than binary. LR made robust predictions at sample sizes feasible for neuropsychology research (N = 307) and when as few as 2 tests with good psychometric properties were used.Although training and test data sets of at least several hundred individuals may be required to develop and evaluate LR models for use in clinical practice, LR promises to be an efficient and powerful tool for improving judgements about performance validity. We offer several recommendations for model development and LR interpretation in a clinical setting.

The influence of autoregressive relation strength and search strategy on directionality recovery in group iterative multiple model estimation.

Unified structural equation modeling (uSEM) implemented in the group iterative multiple model estimation (GIMME) framework has recently been widely used for characterizing within-person network dynamics of behavioral and functional neuroimaging variables. Previous studies have established that GIMME accurately recovers the presence of relations between variables. However, recovery of relation directionality is less consistent, which is concerning given the importance of directionality estimates for many research questions. There is evidence that strong autoregressive relations may aid directionality recovery and indirect evidence that a novel version of GIMME allowing for multiple solutions could improve recovery when such relations are weak, but it remains unclear how these strategies perform under a range of study conditions. Using comprehensive simulations that varied the strength of autoregressive relations among other factors, this study evaluated the directionality recovery of two GIMME search strategies: (a) estimating autoregressive relations by default in the null model (GIMME-AR) and (b) generating multiple solution paths (GIMME-MS). Both strategies recovered directionality best-and were roughly equivalent in performance-when autoregressive relations were strong (e.g., ß = .60). When they were weak (ß ≤ .10), GIMME-MS displayed an advantage, although overall directionality recovery was modest. Analyses of empirical data in which autoregressive relations were characteristically strong (resting state functional MRI) versus weak (daily diary) mirrored simulation results and confirmed that these strategies can disagree on directionality when autoregressive relations are weak. Findings have important implications for psychological and neuroimaging applications of uSEM/GIMME and suggest specific scenarios in which researchers might or might not be confident in directionality results. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Socioeconomic resources are associated with distributed alterations of the brain's intrinsic functional architecture in youth.

Little is known about how exposure to limited socioeconomic resources (SER) in childhood gets "under the skin" to shape brain development, especially using rigorous whole-brain multivariate methods in large, adequately powered samples. The present study examined resting state functional connectivity patterns from 5821 youth in the Adolescent Brain Cognitive Development (ABCD) study, employing multivariate methods across three levels: whole-brain, network-wise, and connection-wise. Across all three levels, SER was associated with widespread alterations across the connectome. However, critically, we found that parental education was the primary driver of neural associations with SER. These parental education associations with the developing connectome exhibited notable concentrations in somatosensory and subcortical regions, and they were partially accounted for by home enrichment activities, child's cognitive abilities, and child's grades, indicating interwoven links between parental education, child stimulation, and child cognitive performance. These results add a new data-driven, multivariate perspective on links between household SER and the child's developing functional connectome.

The role of parenting in the intergenerational transmission of executive functioning: A genetically informed approach.

Deficits in executive functioning both run in families and serve as a transdiagnostic risk factor for psychopathology. The present study employed twin modeling to examine parenting as an environmental pathway underlying the intergenerational transmission of executive functioning in an at-risk community sample of children and adolescents (N = 354 pairs, 167 monozygotic). Using structural equation modeling of multi-informant reports of parenting and a multi-method measure of child executive functioning, we found that better parent executive functioning related to less harsh, warmer parenting, which in turn related to better child executive functioning. Second, we assessed the etiology of executive functioning via the nuclear twin family model, finding large non-shared environmental effects (E = .69) and low-to-moderate heritability (A = .22). We did not find evidence of shared environmental effects or passive genotype-environment correlation. Third, a bivariate twin model revealed significant shared environmental overlap between both warm and harsh parenting and child executive functioning (which may indicate either passive genotype-environment correlation or environmental mediation), and non-shared environmental overlap between only harsh parenting and child executive functioning (indicating an effect of harsh parenting separable from genetic confounds). In summary, genetics contribute to the intergenerational transmission of executive functioning, with environmental mechanisms, including harsh parenting, also making unique contributions.

Sex Moderates Reward- and Loss-Related Neural Correlates of Triarchic-Model Traits and Antisocial Behavior.

Abnormalities in responses to reward and loss are implicated in the etiology of antisocial behavior and psychopathic traits. While there is evidence for sex differences in neural response to reward and loss, it remains unclear how sex differences may moderate links between these neural responses and the phenotypic expression of antisocial behavior and psychopathic traits. This study examined sex differences in associations of neural response to reward and loss with antisocial personality symptoms and psychopathic traits. Functional neuroimaging data were collected during a monetary incentive delay task from 158 participants. Among males, during loss anticipation, activation in the left nucleus accumbens was negatively associated with antisocial behavior. Among females, during loss feedback, activation in the left nucleus accumbens and left amygdala was negatively associated with antisocial behavior. These results suggest that phenotypic sex differences in psychopathic traits and antisocial behavior may in part be attributable to different etiological pathways.

Reciprocal associations between implicit attitudes and drinking in emerging adulthood.

BACKGROUND: Implicit alcohol attitudes are considered important in the etiology of drinking, and theory posits reciprocal associations between them. Research testing reciprocal associations between implicit attitudes (using the Implicit Association Task, IAT) and drinking is limited by a failure to consider multiple processes influencing performance on the IAT and to disaggregate within- and between-person effects. The current study addressed these limitations by using a diffusion model to analyze IAT data and Latent Curve Models with Structured Residuals to test reciprocal associations. METHODS: The sample included 314 emerging adults from the community (52% female; predominantly non-Hispanic Caucasian (76%) or African American (15%)) assessed annually for three years. Differences between IAT conditions in the drift rate parameter of the EZ-diffusion model (vΔ) were used as an alternative to traditional response-time-based indices from the IAT (d-scores). Differences in drift rate have been found to index implicit attitudes effectively. RESULTS: Within-person reciprocal associations were supported, but between-person associations were not. Positive implicit alcohol attitudes (vΔ) were prospectively associated with heavy drinking, which was positively associated with subsequent positive implicit alcohol attitudes. CONCLUSIONS: We found that positive implicit alcohol attitudes and heavy drinking reinforce each other in a negative cascade within individuals. The results highlight the importance of disaggregating within- and between-person prospective effects when testing dual process models and suggest that the diffusion model may be a fruitful approach to enhance the construct validity of IAT assessed implicit attitudes.

Neural heterogeneity underlying late adolescent motivational processing is linked to individual differences in behavioral sensation seeking.

Adolescent risk-taking, including sensation seeking (SS), is often attributed to developmental changes in connectivity among brain regions implicated in cognitive control and reward processing. Despite considerable scientific and popular interest in this neurodevelopmental framework, there are few empirical investigations of adolescent functional connectivity, let alone examinations of its links to SS behavior. The studies that have been done focus on mean-based approaches and leave unanswered questions about individual differences in neurodevelopment and behavior. The goal of this paper is to take a person-specific approach to the study of adolescent functional connectivity during a continuous motivational state, and to examine links between connectivity and self-reported SS behavior in 104 adolescents (MAge  = 19.3; SDAge  = 1.3). Using Group Iterative Multiple Model Estimation (GIMME), person-specific connectivity during two neuroimaging runs of a monetary incentive delay task was estimated among 12 a priori brain regions of interest representing reward, cognitive, and salience networks. Two data-driven subgroups were detected, a finding that was consistent between both neuroimaging runs, but associations with SS were only found in the first run, potentially reflecting neural habituation in the second run. Specifically, the subgroup that had unique connections between reward-related regions had greater SS and showed a distinctive relation between connectivity strength in the reward regions and SS. These findings provide novel evidence for heterogeneity in adolescent brain-behavior relations by showing that subsets of adolescents have unique associations between neural motivational processing and SS. Findings have broader implications for future work on reward processing, as they demonstrate that brain-behavior relations may attenuate across runs.

Computational modeling reveals strategic and developmental differences in the behavioral impact of reward across adolescence.

Studies of reward effects on behavior in adolescence typically rely on performance metrics that confound myriad cognitive and non-cognitive processes, making it challenging to determine which process is impacted by reward. The present longitudinal study applied the diffusion decision model to a reward task to isolate the influence of reward on response caution from influences of processing and motor speed. Participants completed three annual assessments from early to middle adolescence (N = 387, 55% female, Mage  = 12.1 at Wave 1; Mage  = 13.1 at Wave 2, Mage  = 14.1 at Wave 3) and three annual assessments in late adolescence (Mages  = 17.8, 18.9, 19.9). At each assessment, participants completed a two-choice reaction time task under conditions of no-reward and a block in which points were awarded for speeded accuracy. Reward reduced response caution at all waves, as expected, but had a greater impact as teens moved from early to middle adolescence. Simulations to identify optimal response caution showed that teens were overly cautious in early adolescence but became too focused on speed over accuracy by middle adolescence. By late adolescence, participants adopted response styles that maximized reward. Further, response style was associated with both internalizing and externalizing symptoms in early-to-middle adolescence, providing evidence for the construct validity of a diffusion model approach in this developmental period.

Brain-wide functional connectivity patterns support general cognitive ability and mediate effects of socioeconomic status in youth.

General cognitive ability (GCA) is an individual difference dimension linked to important academic, occupational, and health-related outcomes and its development is strongly linked to differences in socioeconomic status (SES). Complex abilities of the human brain are realized through interconnections among distributed brain regions, but brain-wide connectivity patterns associated with GCA in youth, and the influence of SES on these connectivity patterns, are poorly understood. The present study examined functional connectomes from 5937 9- and 10-year-olds in the Adolescent Brain Cognitive Development (ABCD) multi-site study. Using multivariate predictive modeling methods, we identified whole-brain functional connectivity patterns linked to GCA. In leave-one-site-out cross-validation, we found these connectivity patterns exhibited strong and statistically reliable generalization at 19 out of 19 held-out sites accounting for 18.0% of the variance in GCA scores (cross-validated partial η2). GCA-related connections were remarkably dispersed across brain networks: across 120 sets of connections linking pairs of large-scale networks, significantly elevated GCA-related connectivity was found in 110 of them, and differences in levels of GCA-related connectivity across brain networks were notably modest. Consistent with prior work, socioeconomic status was a strong predictor of GCA in this sample, and we found that distributed GCA-related brain connectivity patterns significantly statistically mediated this relationship (mean proportion mediated: 15.6%, p < 2 × 10-16). These results demonstrate that socioeconomic status and GCA are related to broad and diffuse differences in functional connectivity architecture during early adolescence, potentially suggesting a mechanism through which socioeconomic status influences cognitive development.

Little evidence for sex or ovarian hormone influences on affective variability.

Women were historically excluded from research participation partly due to the assumption that ovarian hormone fluctuations lead to variation, especially in emotion, that could not be experimentally controlled. Although challenged in principle and practice, relevant empirical data are limited by single measurement occasions. The current paper fills this knowledge gap using data from a 75-day intensive longitudinal study. Three indices of daily affective variability-volatility, emotional inertia, and cyclicity-were evaluated using Bayesian inferential methods in 142 men, naturally cycling women, and women using three different oral contraceptive formulations (that "stabilize" hormone fluctuations). Results provided more evidence for similarities between men and women-and between naturally cycling women and oral contraceptive users-than for differences. Even if differences exist, effects are likely small. Thus, there is little indication that ovarian hormones influence affective variability in women to a greater extent than the biopsychosocial factors that influence daily emotion in men.

The General Factor of Psychopathology in the Adolescent Brain Cognitive Development (ABCD) Study: A Comparison of Alternative Modeling Approaches.

Many models of psychopathology include a single general factor of psychopathology (GFP) or "p factor" to account for covariation across symptoms. The Adolescent Brain Cognitive Development (ABCD) Study provides a rich opportunity to study the development of the GFP. However, a variety of approaches for modeling the GFP have emerged, raising questions about how modeling choices impact estimated GFP scores. We used the ABCD baseline assessment (ages 9-10 years-old; N=11,875) of the parent-rated Child Behavior Checklist (CBCL) to examine the implications of modeling the GFP using items versus scales; using a priori CBCL scales versus data-driven dimensions; and using bifactor, higher-order, or single-factor models. Children's rank-ordering on the GFP was stable across models, with GFP scores similarly related to criterion variables. Results suggest that while theoretical debates about modeling the GFP continue, the practical implications of these choices for rank-ordering children and assessing external associations will often be modest.

Heterogeneity Within Youth With Childhood-Onset Conduct Disorder in the ABCD Study.

The purpose of this study was to examine if personality traits can be used to characterize subgroups of youth diagnosed with childhood-onset conduct disorder (CD). Participants were 11,552 youth from the Adolescent Brain Cognitive Development study. Data used in this report came from doi: 10.15154/1504041 (M age 9.92; 45.3% female, 49.6% white, 19.0% Hispanic). A subset of this sample (n = 365) met criteria for CD. Latent profile analyses (LPA) were performed on this subgroup (n = 365) to define profiles of individuals with CD based on self-report measures of impulsivity, punishment sensitivity, reward response, and callous-unemotional traits. Follow up analyses determined if these groups differed on clinically relevant variables including psychopathology, environmental risk factors, social risk factors, and neurocognitive functioning. Participants with a CD diagnosis scored significantly higher on psychological, environmental, social, and neurocognitive risk factors. The LPA revealed three unique profiles, which differed significantly on liability for broad psychopathology and domain-specific liability for externalizing psychopathology but were largely matched on environmental and social risk factors. These unique configurations provide a useful way to further parse clinically relevant subgroups within youth who meet criteria for childhood-onset CD, setting the stage for prospective longitudinal research using these latent profiles to better understand the development of youth with childhood-onset CD.