Internet-Based Prevention of Re-Victimization for Youth with Care Experience (EMPOWER-YOUTH): Results of a Randomized Controlled Trial.

Traumatic experiences and maltreatment are highly prevalent among adolescents in foster or institutional care and have severe long-term effects on mental health. Childhood maltreatment increases the risk of revictimization. This study aimed to evaluate the efficacy of the internet-based prevention program EMPOWER YOUTH in reducing victimization experiences among youth with care experience. A total of 163 youth, that is, adolescents in foster or institutional care, adopted adolescents, or young care leavers aged 14 to 21 years (Mage = 17.68 years; SD = 2.11) were randomized to the six-module guided program or a wait-list control group. The primary endpoint was the decrease in victimization experiences at an 18-week follow-up. Secondary endpoints included risk perception, aggressive tendencies, empathy, prosocial behavior, depressiveness, post-traumatic stress symptoms, and loneliness. About half of the youth exhibited increased psychopathology. No significant interaction between time-point and group was found for victimization measures, though both groups saw a significant reduction over time (p = 0.012, ηp2 = 0.06; p = 0.017, ηp2 = 0.06). The intervention group showed a significant increase in perception of thrill-seeking and rebellious risks (p = 0.036, ηp2 = 0.04; p = 0.026, ηp2 = 0.05). While EMPOWER YOUTH effectively increased risk perception of thrill-seeking and rebellious behaviors, it should be considered an add-on to more intensive interventions for common mental health disorders in this vulnerable group, rather than a stand-alone online program.

[Digital Beacons of Hope? The Challenges and Potentials of Digital Health Applications for Children and Adolescents with Mental Disorders in Germany]. / Digitale Hoffnungsträger?

Digital Beacons of Hope? The Challenges and Potentials of Digital Health Applications for Children and Adolescents with Mental Disorders in Germany Abstract: With the Digital Healthcare Act, Germany has taken a decisive step toward promoting high-quality, evidence-based digital health applications (DiHAs). Presently, there is a significant gap in the provision of mental health services throughout Germany, particularly regarding children and adolescents and especially in the aftermath of the COVID-19 pandemic. DiHAs as low-threshold, location- and time-independent additional mental health services - may offer a way to address this situation. Particularly in the emerging generation of digital natives, there is a high demand for digital mental health services. However, despite the rapidly growing supply of DiHAs for adults, there is a lack of approved DiHAs for children and adolescents with mental disorders. Rather, the demand for care is left to the unregulated market of diverse internet- and mobile-based interventions; early studies have questioned the evidence base, safety, and quality. This discrepancy arises from various specific challenges and risks that reduce incentives to develop DiHAs for this particularly vulnerable target group, including (1) limited evidence, (2) high complexity in study execution, (3) high complexity in the development of applications, (4) poorly researched specific risks, and (5) high regulatory requirements. This article discusses these challenges and risks and outlines the perspectives for a high-quality, safe, and evidence-based digital mental healthcare for children and adolescents.

Lifetime victimization experiences, depressiveness, suicidality, and feelings of loneliness in youth in care.

BACKGROUND: Research has demonstrated the damaging effects of poly-victimization on the mental health of children and adolescents. However, few studies have been conducted in high-risk youth in care (Y-IC) samples. OBJECTIVE: The study examines the frequency of lifetime victimization and the association of poly-victimization and victimization types on depressiveness, suicidality, and feelings of loneliness among Y-IC. PARTICIPANTS AND SETTING: 164 participants aged 14 and 21 years (M = 17.39, SD = 1.95), who live in family-based care or residential care. METHODS: The Juvenile Victimization Questionnaire (JVQ) was used to assess lifetime victimization. The Patient Health Questionnaire (PHQ-9), and the Loneliness Scale-SOEP (LS-S) to measure depressiveness, suicidality, and loneliness. Hierarchical regression models were calculated. RESULTS: Participants reported on average 12.66 (SD = 6.58) victimization experiences. The female and diverse gender groups reported higher rates of victimization, loneliness, depressiveness, and suicidality than the males. Participants in residential care reported more victimizations and stronger feelings of loneliness than those in family-based care. Poly-victimization was not associated with any of these internalizing symptoms but peer victimization was significantly associated with depressiveness (ß = 0.23, p = .002) and loneliness (ß = 0.22, p = .006), sexual victimization with depressiveness (ß = 0.22, p = .004). CONCLUSION: Y-IC show high levels of victimization and internalizing symptoms, with higher burden on girls and youth living in residential care. Findings underscore the relevance of social exclusion experiences among peers within Y-IC. Interventions should address multiple forms of victimization, with a special focus on sexual and peer victimization.

Distinct personality profiles associated with disease risk and diagnostic status in eating disorders.

BACKGROUND: Personality traits have been associated with eating disorders (EDs) and comorbidities. However, it is unclear which personality profiles are premorbid risk rather than diagnostic markers. METHODS: We explored associations between personality and ED-related mental health symptoms using canonical correlation analyses. We investigated personality risk profiles in a longitudinal sample, associating personality at age 14 with onset of mental health symptoms at ages 16 or 19. Diagnostic markers were identified in a sample of young adults with anorexia nervosa (AN, n = 58) or bulimia nervosa (BN, n = 63) and healthy controls (n = 47). RESULTS: Two significant premorbid risk profiles were identified, successively explaining 7.93 % and 5.60 % of shared variance (Rc2). The first combined neuroticism (canonical loading, rs = 0.68), openness (rs = 0.32), impulsivity (rs = 0.29), and conscientiousness (rs = 0.27), with future onset of anxiety symptoms (rs = 0.87) and dieting (rs = 0.58). The other, combined lower agreeableness (rs = -0.60) and lower anxiety sensitivity (rs = -0.47), with future deliberate self-harm (rs = 0.76) and purging (rs = 0.55). Personality profiles associated with "core psychopathology" in both AN (Rc2 = 80.56 %) and BN diagnoses (Rc2 = 64.38 %) comprised hopelessness (rs = 0.95, 0.87) and neuroticism (rs = 0.93, 0.94). For BN, this profile also included impulsivity (rs = 0.60). Additionally, extraversion (rs = 0.41) was associated with lower depressive risk in BN. LIMITATIONS: The samples were not ethnically diverse. The clinical cohort included only females. There was non-random attrition in the longitudinal sample. CONCLUSIONS: The results suggest neuroticism and impulsivity as risk and diagnostic markers for EDs, with neuroticism and hopelessness as shared diagnostic markers. They may inform the design of more personalised prevention and intervention strategies.

Impaired flexible reward learning in ADHD patients is associated with blunted reinforcement sensitivity and neural signals in ventral striatum and parietal cortex.

Reward-based learning and decision-making are prime candidates to understand symptoms of attention deficit hyperactivity disorder (ADHD). However, only limited evidence is available regarding the neurocomputational underpinnings of the alterations seen in ADHD. This concerns flexible behavioral adaption in dynamically changing environments, which is challenging for individuals with ADHD. One previous study points to elevated choice switching in adolescent ADHD, which was accompanied by disrupted learning signals in medial prefrontal cortex. Here, we investigated young adults with ADHD (n = 17) as compared to age- and sex-matched controls (n = 17) using a probabilistic reversal learning experiment during functional magnetic resonance imaging (fMRI). The task requires continuous learning to guide flexible behavioral adaptation to changing reward contingencies. To disentangle the neurocomputational underpinnings of the behavioral data, we used reinforcement learning (RL) models, which informed the analysis of fMRI data. ADHD patients performed worse than controls particularly in trials before reversals, i.e., when reward contingencies were stable. This pattern resulted from 'noisy' choice switching regardless of previous feedback. RL modelling showed decreased reinforcement sensitivity and enhanced learning rates for negative feedback in ADHD patients. At the neural level, this was reflected in a diminished representation of choice probability in the left posterior parietal cortex in ADHD. Moreover, modelling showed a marginal reduction of learning about the unchosen option, which was paralleled by a marginal reduction in learning signals incorporating the unchosen option in the left ventral striatum. Taken together, we show that impaired flexible behavior in ADHD is due to excessive choice switching ('hyper-flexibility'), which can be detrimental or beneficial depending on the learning environment. Computationally, this resulted from blunted sensitivity to reinforcement of which we detected neural correlates in the attention-control network, specifically in the parietal cortex. These neurocomputational findings remain preliminary due to the relatively small sample size.

Machine learning models for diagnosis and risk prediction in eating disorders, depression, and alcohol use disorder.

This study uses machine learning models to uncover diagnostic and risk prediction markers for eating disorders (EDs), major depressive disorder (MDD), and alcohol use disorder (AUD). Utilizing case-control samples (ages 18-25 years) and a longitudinal population-based sample (n=1,851), the models, incorporating diverse data domains, achieved high accuracy in classifying EDs, MDD, and AUD from healthy controls. The area under the receiver operating characteristic curves (AUC-ROC [95% CI]) reached 0.92 [0.86-0.97] for AN and 0.91 [0.85-0.96] for BN, without relying on body mass index as a predictor. The classification accuracies for MDD (0.91 [0.88-0.94]) and AUD (0.80 [0.74-0.85]) were also high. Each data domain emerged as accurate classifiers individually, with personality distinguishing AN, BN, and their controls with AUC-ROCs ranging from 0.77 to 0.89. The models demonstrated high transdiagnostic potential, as those trained for EDs were also accurate in classifying AUD and MDD from healthy controls, and vice versa (AUC-ROCs, 0.75-0.93). Shared predictors, such as neuroticism, hopelessness, and symptoms of attention-deficit/hyperactivity disorder, were identified as reliable classifiers. For risk prediction in the longitudinal population sample, the models exhibited moderate performance (AUC-ROCs, 0.64-0.71), highlighting the potential of combining multi-domain data for precise diagnostic and risk prediction applications in psychiatry.

Differing impact of the COVID-19 pandemic on youth mental health: combined population and clinical study.

BACKGROUND: Identifying youths most at risk to COVID-19-related mental illness is essential for the development of effective targeted interventions. AIMS: To compare trajectories of mental health throughout the pandemic in youth with and without prior mental illness and identify those most at risk of COVID-19-related mental illness. METHOD: Data were collected from individuals aged 18-26 years (N = 669) from two existing cohorts: IMAGEN, a population-based cohort; and ESTRA/STRATIFY, clinical cohorts of individuals with pre-existing diagnoses of mental disorders. Repeated COVID-19 surveys and standardised mental health assessments were used to compare trajectories of mental health symptoms from before the pandemic through to the second lockdown. RESULTS: Mental health trajectories differed significantly between cohorts. In the population cohort, depression and eating disorder symptoms increased by 33.9% (95% CI 31.78-36.57) and 15.6% (95% CI 15.39-15.68) during the pandemic, respectively. By contrast, these remained high over time in the clinical cohort. Conversely, trajectories of alcohol misuse were similar in both cohorts, decreasing continuously (a 15.2% decrease) during the pandemic. Pre-pandemic symptom severity predicted the observed mental health trajectories in the population cohort. Surprisingly, being relatively healthy predicted increases in depression and eating disorder symptoms and in body mass index. By contrast, those initially at higher risk for depression or eating disorders reported a lasting decrease. CONCLUSIONS: Healthier young people may be at greater risk of developing depressive or eating disorder symptoms during the COVID-19 pandemic. Targeted mental health interventions considering prior diagnostic risk may be warranted to help young people cope with the challenges of psychosocial stress and reduce the associated healthcare burden.

A shared neural basis underlying psychiatric comorbidity.

Recent studies proposed a general psychopathology factor underlying common comorbidities among psychiatric disorders. However, its neurobiological mechanisms and generalizability remain elusive. In this study, we used a large longitudinal neuroimaging cohort from adolescence to young adulthood (IMAGEN) to define a neuropsychopathological (NP) factor across externalizing and internalizing symptoms using multitask connectomes. We demonstrate that this NP factor might represent a unified, genetically determined, delayed development of the prefrontal cortex that further leads to poor executive function. We also show this NP factor to be reproducible in multiple developmental periods, from preadolescence to early adulthood, and generalizable to the resting-state connectome and clinical samples (the ADHD-200 Sample and the Stratify Project). In conclusion, we identify a reproducible and general neural basis underlying symptoms of multiple mental health disorders, bridging multidimensional evidence from behavioral, neuroimaging and genetic substrates. These findings may help to develop new therapeutic interventions for psychiatric comorbidities.

Anxiety onset in adolescents: a machine-learning prediction.

Recent longitudinal studies in youth have reported MRI correlates of prospective anxiety symptoms during adolescence, a vulnerable period for the onset of anxiety disorders. However, their predictive value has not been established. Individual prediction through machine-learning algorithms might help bridge the gap to clinical relevance. A voting classifier with Random Forest, Support Vector Machine and Logistic Regression algorithms was used to evaluate the predictive pertinence of gray matter volumes of interest and psychometric scores in the detection of prospective clinical anxiety. Participants with clinical anxiety at age 18-23 (N = 156) were investigated at age 14 along with healthy controls (N = 424). Shapley values were extracted for in-depth interpretation of feature importance. Prospective prediction of pooled anxiety disorders relied mostly on psychometric features and achieved moderate performance (area under the receiver operating curve = 0.68), while generalized anxiety disorder (GAD) prediction achieved similar performance. MRI regional volumes did not improve the prediction performance of prospective pooled anxiety disorders with respect to psychometric features alone, but they improved the prediction performance of GAD, with the caudate and pallidum volumes being among the most contributing features. To conclude, in non-anxious 14 year old adolescents, future clinical anxiety onset 4-8 years later could be individually predicted. Psychometric features such as neuroticism, hopelessness and emotional symptoms were the main contributors to pooled anxiety disorders prediction. Neuroanatomical data, such as caudate and pallidum volume, proved valuable for GAD and should be included in prospective clinical anxiety prediction in adolescents.

Chronotype, Longitudinal Volumetric Brain Variations Throughout Adolescence, and Depressive Symptom Development.

OBJECTIVE: Adolescence is a critical period for circadian rhythm, with a strong shift toward eveningness around age 14. Also, eveningness in adolescence has been found to predict later onset of depressive symptoms. However, no previous study has investigated structural variations associated with chronotype in early adolescence and how this adds to the development of depressive symptoms. METHOD: Assessment of 128 community-based adolescents (51% girls) at age 14 and 19 years was performed. Using whole-brain voxel-based morphometry, baseline (at age 14) regional gray matter volumes (GMVs), follow-up (at age 19) regional GMVs, and longitudinal changes (between 14 and 19) associated with Morningness/Eveningness Scale in Children score and sleep habits at baseline were measured. The association of GMV with depressive symptoms at 19 years was studied, and the role of potential clinical and genetic factors as mediators and moderators was assessed. RESULTS: Higher eveningness was associated with larger GMV in the right medial prefrontal cortex at ages 14 and 19 in the whole sample. GMV in this region related to depressive symptoms at age 19 in catechol-O-methyltransferase (COMT) Val/Val, but not in Met COMT, carriers. Larger GMV also was observed in the right fusiform gyrus at age 14, which was explained by later wake-up time during weekends. CONCLUSION: In adolescence, eveningness and its related sleep habits correlated with distinct developmental patterns. Eveningness was specifically associated with GMV changes in the medial prefrontal cortex; this could serve as a brain vulnerability factor for later self-reported depressive symptoms in COMT Val/Val carriers.

Global and Regional Structural Differences and Prediction of Autistic Traits during Adolescence.

BACKGROUND: Autistic traits are commonly viewed as dimensional in nature, and as continuously distributed in the general population. In this respect, the identification of predictive values of markers such as subtle autism-related alterations in brain morphology for parameter values of autistic traits could increase our understanding of this dimensional occasion. However, currently, very little is known about how these traits correspond to alterations in brain morphology in typically developing individuals, particularly during a time period where changes due to brain development processes do not provide a bias. Therefore, in the present study, we analyzed brain volume, cortical thickness (CT) and surface area (SA) in a cohort of 14-15-year-old adolescents (N = 285, female: N = 162) and tested their predictive value for autistic traits, assessed with the social responsiveness scale (SRS) two years later at the age of 16-17 years, using a regression-based approach. We found that autistic traits were significantly predicted by volumetric changes in the amygdala (r = 0.181), cerebellum (r = 0.128) and hippocampus (r = -0.181, r = -0.203), both in boys and girls. Moreover, the CT of the superior frontal region was negatively correlated (r = -0.144) with SRS scores. Furthermore, we observed a significant association between the SRS total score and smaller left putamen volume, specifically in boys (r = -0.217), but not in girls. Our findings suggest that neural correlates of autistic traits also seem to lie on a continuum in the general population, are determined by limbic-striatal neuroanatomical brain areas, and are partly dependent on sex. As we imaged adolescents from a large population-based cohort within a small age range, these data may help to increase the understanding of autistic-like occasions in otherwise typically developing individuals.

Internet-Based Prevention Program of Victimization for Youth in Care and Care Leavers (EMPOWER YOUTH): Protocol for a Randomized Controlled Trial.

BACKGROUND: The global estimate of the number of children in institutional care is around 5 million, with around 1 million of these children living in Europe. In Germany, about 75,000 children and adolescents find themselves in the foster care system and about 93,000 additional children and adolescents are living in institutions. Traumatic experiences and neglect in childhood are highly prevalent among these youth in care and are related to severe long-term effects. Childhood maltreatment and abuse can increase the risk of future victimization experiences. Although youth in care are at risk of victimization or revictimization, no specific evidence-based prevention program has been designed to address these specific needs. OBJECTIVE: This study aims to evaluate the efficacy of a newly developed 6-module internet-based prevention program of victimization for youth in care, named EMPOWER YOUTH. METHODS: In a randomized controlled trial, the intervention group will be compared to a waiting-list control group with an unblinded 1:1 allocation ratio. Assessments will take place before randomization (baseline) and at follow-up 18 weeks after baseline (ie, 12 weeks after finishing the last module of the program). The primary endpoint is the number of victimization, and online and offline bullying experiences (composite score) at the 18-week follow-up. Secondary endpoints are risk-taking behavior, aggressive tendencies, empathy, prosocial behavior, depressiveness, and loneliness at follow-up. The expected outcome requires a sample size of 156 subjects to achieve a power of 80%. Assuming a 30% dropout rate at follow-up, we require 225 participants to be allocated to the trial. Participants are youth in care, that is, adolescents in foster care, adopted adolescents, or young care leavers aged 14 to 21 years. RESULTS: Ethical approval was granted by the Ethics Committee of the Medical School Berlin in March 2021 (MSB-2021/55). Recruitment started in September 2021 and is planned until November 2022. The results are expected to be published in January 2023. CONCLUSIONS: Given the increased likelihood for future victimization experiences among youth in care, there is a strong need for a low-threshold intervention specifically for this high-risk age group. There are no existing nationwide mental health programs exclusively for youth in care in Germany. TRIAL REGISTRATION: German Clinical Trials Register DRKS00024749; https://tinyurl.com/tjaahayw. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/34706.

Randomized controlled trial of cognitive remediation therapy in adolescent inpatients with anorexia nervosa: Neuropsychological outcomes.

OBJECTIVE: Neuropsychological dysfunction exists in anorexia nervosa (AN). Cognitive Remediation Therapy (CRT), mainly evaluated in adults with AN, targets these impairments. METHODS: Adolescent inpatients (age = 11-17 years) with AN were randomized to 5 weeks of either 10 sessions of individually delivered CRT or non-specific cognitive-training (NSCT). Co-primary outcomes included cognitive domain 'flexibility' [composite score of Wisconsin Card Sorting Test (WSCT) and Trail Making Test (TMT-4)] and 'central coherence' [composite score of Central Coherence Index (CCI) and Group Embedded Figures Test (GEFT)] at end of treatment (FU1). Secondary outcomes included individual test scores and self-reported everyday-life flexibility at FU1 and at 6-months post-treatment (FU2). Independent sample t-tests, Pearson chi-square-tests and mixed models for repeated measures (MMRM) analyses were conducted. RESULTS: In 56 females (age = 15.1 ± 1.5 years), CRT was not superior to NSCT at FU1 regarding 'flexibility' (p = 0.768) or 'central coherence' (p = 0.354), nor at FU2 (p = 0.507; p = 0.624) (effect sizes = 0.02-0.26). Both groups improved over time in central coherence (CCI p = 0.001; GEFT p < 0.001), self-reported flexibility (p = 0.002) and WCST (p = 0.18), but not TMT-4 (p = 0.286). NSCT was superior to CRT regarding self-reported planning/organisation ability at FU1 (p < 0.001) and FU2 (p = 0.003). CONCLUSIONS: CRT was not superior to NSCT in adolescent inpatients with AN. More randomized controlled studies are needed.

Longitudinal Trajectory of the Link Between Ventral Striatum and Depression in Adolescence.

OBJECTIVE: Research in adolescent depression has found aberrant intrinsic functional connectivity (iFC) among the ventral striatum (VS) and several brain regions implicated in reward processing. The present study probes this question by taking advantage of the availability of data from a large youth cohort, the IMAGEN Consortium. METHODS: iFC data from 303 adolescents (48% of them female) were used to examine associations of VS connectivity at baseline (at age 14) with depressive disorders at baseline and at 2-year (N=250) and 4-year (N=219) follow-ups. Eleven regions of interest, key nodes of the reward system, were used to probe the reward network and calculate the connectivity strength of the VS within this network (VS connectivityrw). The main analyses assessed associations of VS connectivityrw with depressive disorders, anhedonia, and low mood using logistic regression. Autoregressive models accounting for carryover effects over time were conducted to further evaluate these brain-behavior associations. RESULTS: Higher right VS connectivityrw was associated with higher probability of depressive disorders at baseline (odds ratio=2.65, 95% CI=1.40, 5.05). This finding was confirmed in the autoregressive model, adjusting for carryover effects of the depressive disorders across the three time points. VS connectivityrw was not predictive of depressive disorders at follow-up assessments. Longitudinal associations between VS connectivityrw and anhedonia emerged in the structural equation model: left VS connectivityrw was associated with anhedonia at 2 years (odds ratio=2.20, 95% CI=1.54, 3.14), and right VS connectivityrw was linked to anhedonia at 4 years (odds ratio=1.87, 95% CI=1.09, 3.21). VS connectivityrw did not predict low mood at any time point in the structural equation model. CONCLUSIONS: The connectivity strength of the VS within the reward network showed distinct patterns of association with depressive disorders and anhedonia from mid to late adolescence, suggesting that the role of this circuitry in depression changes with age. This study replicates, in an independent sample, the association between the VS and depression previously reported in younger adolescents. The findings suggest a role of VS connectivityrw in anhedonia but not in low mood.

Predicting Depression Onset in Young People Based on Clinical, Cognitive, Environmental, and Neurobiological Data.

BACKGROUND: Adolescent onset of depression is associated with long-lasting negative consequences. Identifying adolescents at risk for developing depression would enable the monitoring of risk factors and the development of early intervention strategies. Using machine learning to combine several risk factors from multiple modalities might allow prediction of depression onset at the individual level. METHODS: A subsample of a multisite longitudinal study in adolescents, the IMAGEN study, was used to predict future (subthreshold) major depressive disorder onset in healthy adolescents. Based on 2-year and 5-year follow-up data, participants were grouped into the following: 1) those developing a diagnosis of major depressive disorder or subthreshold major depressive disorder and 2) healthy control subjects. Baseline measurements of 145 variables from different modalities (clinical, cognitive, environmental, and structural magnetic resonance imaging) at age 14 years were used as input to penalized logistic regression (with different levels of penalization) to predict depression onset in a training dataset (n = 407). The features contributing the highest to the prediction were validated in an independent hold-out sample (three independent IMAGEN sites; n = 137). RESULTS: The area under the receiver operating characteristic curve for predicting depression onset ranged between 0.70 and 0.72 in the training dataset. Baseline severity of depressive symptoms, female sex, neuroticism, stressful life events, and surface area of the supramarginal gyrus contributed most to the predictive model and predicted onset of depression, with an area under the receiver operating characteristic curve between 0.68 and 0.72 in the independent validation sample. CONCLUSIONS: This study showed that depression onset in adolescents can be predicted based on a combination multimodal data of clinical characteristics, life events, personality traits, and brain structure variables.

Linked patterns of biological and environmental covariation with brain structure in adolescence: a population-based longitudinal study.

Adolescence is a period of major brain reorganization shaped by biologically timed and by environmental factors. We sought to discover linked patterns of covariation between brain structural development and a wide array of these factors by leveraging data from the IMAGEN study, a longitudinal population-based cohort of adolescents. Brain structural measures and a comprehensive array of non-imaging features (relating to demographic, anthropometric, and psychosocial characteristics) were available on 1476 IMAGEN participants aged 14 years and from a subsample reassessed at age 19 years (n = 714). We applied sparse canonical correlation analyses (sCCA) to the cross-sectional and longitudinal data to extract modes with maximum covariation between neuroimaging and non-imaging measures. Separate sCCAs for cortical thickness, cortical surface area and subcortical volumes confirmed that each imaging phenotype was correlated with non-imaging features (sCCA r range: 0.30-0.65, all PFDR < 0.001). Total intracranial volume and global measures of cortical thickness and surface area had the highest canonical cross-loadings (|ρ| = 0.31-0.61). Age, physical growth and sex had the highest association with adolescent brain structure (|ρ| = 0.24-0.62); at baseline, further significant positive associations were noted for cognitive measures while negative associations were observed at both time points for prenatal parental smoking, life events, and negative affect and substance use in youth (|ρ| = 0.10-0.23). Sex, physical growth and age are the dominant influences on adolescent brain development. We highlight the persistent negative influences of prenatal parental smoking and youth substance use as they are modifiable and of relevance for public health initiatives.

Development of Disordered Eating Behaviors and Comorbid Depressive Symptoms in Adolescence: Neural and Psychopathological Predictors.

BACKGROUND: Eating disorders are common in adolescence and are devastating and strongly comorbid with other psychiatric disorders. Yet little is known about their etiology, knowing which would aid in developing effective preventive measures. METHODS: Longitudinal assessments of disordered eating behaviors (DEBs)-binge-eating, purging, and dieting-and comorbid psychopathology were measured in 1386 adolescents from the IMAGEN study. Development of DEBs and associated mental health problems was investigated by comparing participants who reported symptoms at ages 16 or 19 years, but not at age 14 years, with asymptomatic control participants. Voxel-based morphometry and psychopathological differences at age 14 were investigated to identify risk factors for the development of DEBs and associated mental health problems. RESULTS: DEBs and depressive symptoms developed together. Emotional and behavioral problems, including symptoms of attention-deficit/hyperactivity disorder and conduct disorder, predated their development. Alterations in frontostriatal brain areas also predated the development of DEBs and depressive symptoms. Specifically, development of binge-eating was predicted by higher gray matter volumes in the right putamen/globus pallidus at age 14. Conversely, development of purging and depressive symptoms was predicted by lower volumes in the medial orbitofrontal, dorsomedial, and dorsolateral prefrontal cortices. Lower gray matter volumes in the orbitofrontal and anterior cingulate cortices mediated the relationship between attention-deficit/hyperactivity disorder and conduct disorder symptoms and future purging and depressive symptoms. CONCLUSIONS: These findings suggest that alterations in frontal brain circuits are part of the shared etiology among eating disorders, attention-deficit/hyperactivity disorder, conduct disorder, and depression and highlight the importance of a transdiagnostic approach to treating these conditions.

Association of Genetic and Phenotypic Assessments With Onset of Disordered Eating Behaviors and Comorbid Mental Health Problems Among Adolescents.

Importance: Eating disorders are serious mental disorders with increasing prevalence. Without early identification and treatment, eating disorders may run a long-term course. Objective: To characterize any associations among disordered eating behaviors (DEBs) and other mental health disorders and to identify early associations with the development of symptoms over time. Design, Setting, and Participants: This multicenter, population-based, longitudinal cohort study used data from baseline (collected in 2010), follow-up 1 (collected in 2012), and follow-up 2 (collected in 2015) of the IMAGEN Study, which included adolescents recruited from 8 European sites. The present study assessed data from 1623 healthy adolescents, aged 14 years at baseline, recruited from high schools. Data analyses were performed from January 2018 to September 2019. Main Outcomes and Measures: Body mass index (BMI), mental health symptoms, substance use behaviors, and personality variables were investigated as time-varying associations of DEBs (dieting, binge eating, and purging) or change in BMI over time. Polygenic risk scores were calculated to investigate genetic contributions associated with BMI, attention-deficit/hyperactivity disorder (ADHD) and neuroticism to DEBs. Results: In this cohort study of 1623 adolescents (829 girls [51.1%]) recruited at a mean (SD) age of 14.5 (0.4) years and followed up at ages 16 and 19 years, 278 adolescents (17.1%) reported binge eating, 334 adolescents (20.6%) reported purging, and 356 adolescents (21.9%) reported dieting at 14, 16, or 19 years. Among the precursors of DEBs, high BMI was associated with future dieting (OR, 3.44; 95% CI, 2.09-5.65). High levels of neuroticism (OR, 1.04; 95% CI, 1.01-1.06), conduct problems (OR, 1.41; 95% CI, 1.17-1.69), and deliberate self-harm (OR, 2.18; 95% CI, 1.37-3.45) were associated with future binge eating. Low agreeableness (OR, 0.95; 95% CI, 0.92-0.97), deliberate self-harm (OR, 2.59; 95% CI, 1.69-3.95), conduct problems (OR, 1.42; 95% CI, 1.20-1.68), alcohol misuse (OR, 1.31; 95% CI, 1.10-1.54), and drug abuse (OR, 2.91; 95% CI, 1.78-4.74) were associated with future purging. Polygenetic risk scores for BMI were associated with dieting (at 14 years: OR, 1.27; lower bound 95% CI, 1.08; at 16 years: OR, 1.38; lower bound 95% CI, 1.17); ADHD, with purging (at 16 years: OR, 1.25; lower bound 95% CI, 1.08; at 19 years, OR, 1.23; lower bound 95% CI, 1.06); and neuroticism, with binge eating (at 14 years: OR, 1.32; lower bound 95% CI, 1.11; at 16 years: OR, 1.24; lower bound 95% CI, 1.06), highlighting distinct etiologic overlaps between these traits. The DEBs predated other mental health problems, with dieting at 14 years associated with future symptoms of depression (OR, 2.53; 95% CI, 1.56-4.10), generalized anxiety (OR, 2.27; 95% CI, 1.14-4.51), deliberate self-harm (OR, 2.10; 95% CI, 1.51-4.24), emotional problems (OR, 1.24; 95% CI, 1.08-1.43), and smoking (OR, 2.16; 95% CI, 1.36-3.48). Purging at 14 years was also associated with future depression (OR, 2.87; 95% CI, 1.69-5.01) and anxiety (OR, 2.48; 95% CI, 1.49-4.12) symptoms. Conclusions and Relevance: The findings of this study delineate temporal associations and shared etiologies among DEBs and other mental health disorders and emphasize the potential of genetic and phenotypical assessments of obesity, behavioral disorders, and neuroticism to improve early and differential diagnosis of eating disorders.

Cognitive and brain development is independently influenced by socioeconomic status and polygenic scores for educational attainment.

Genetic factors and socioeconomic status (SES) inequalities play a large role in educational attainment, and both have been associated with variations in brain structure and cognition. However, genetics and SES are correlated, and no prior study has assessed their neural associations independently. Here we used a polygenic score for educational attainment (EduYears-PGS), as well as SES, in a longitudinal study of 551 adolescents to tease apart genetic and environmental associations with brain development and cognition. Subjects received a structural MRI scan at ages 14 and 19. At both time points, they performed three working memory (WM) tasks. SES and EduYears-PGS were correlated (r = 0.27) and had both common and independent associations with brain structure and cognition. Specifically, lower SES was related to less total cortical surface area and lower WM. EduYears-PGS was also related to total cortical surface area, but in addition had a regional association with surface area in the right parietal lobe, a region related to nonverbal cognitive functions, including mathematics, spatial cognition, and WM. SES, but not EduYears-PGS, was related to a change in total cortical surface area from age 14 to 19. This study demonstrates a regional association of EduYears-PGS and the independent prediction of SES with cognitive function and brain development. It suggests that the SES inequalities, in particular parental education, are related to global aspects of cortical development, and exert a persistent influence on brain development during adolescence.