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.

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.

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

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.

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.

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.

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.

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.

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).

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.

Sex effects on structural maturation of the limbic system and outcomes on emotional regulation during adolescence.

Though adolescence is a time of emerging sex differences in emotions, sex-related differences in the anatomy of the maturing brain has been under-explored over this period. The aim of this study was to investigate whether puberty and sexual differentiation in brain maturation could explain emotional differences between girls and boys during adolescence. We adapted a dedicated longitudinal pipeline to process structural and diffusion images from 335 typically developing adolescents between 14 and 16 years.

Identification of neurobehavioural symptom groups based on shared brain mechanisms.

Most psychopathological disorders develop in adolescence. The biological basis for this development is poorly understood. To enhance diagnostic characterization and develop improved targeted interventions, it is critical to identify behavioural symptom groups that share neural substrates.

Heavy drinking in adolescents is associated with change in brainstem microstructure and reward sensitivity.

Heavy drinker adolescents: altered brainstem microstructure.

Pubertal maturation and sex effects on the default-mode network connectivity implicated in mood dysregulation.

This study examines the effects of puberty and sex on the intrinsic functional connectivity (iFC) of brain networks, with a focus on the default-mode network (DMN). Consistently implicated in depressive disorders, the DMN's function may interact with puberty and sex in the development of these disorders, whose onsets peak in adolescence, and which show strong sex disproportionality (females > males). The main question concerns how the DMN evolves with puberty as a function of sex.

Early Variations in White Matter Microstructure and Depression Outcome in Adolescents With Subthreshold Depression.

Objective: White matter microstructure alterations have recently been associated with depressive episodes during adolescence, but it is unknown whether they predate depression. The authors investigated whether subthreshold depression in adolescence is associated with white matter microstructure variations and whether they relate to depression outcome.

Method: Adolescents with subthreshold depression (N=96) and healthy control subjects (N=336) drawn from a community-based cohort were compared using diffusion tensor imaging and whole brain tract-based spatial statistics (TBSS) at age 14 to assess white matter microstructure.

Distinct brain structure and behavior related to ADHD and conduct disorder traits.

Attention-Deficit/Hyperactivity Disorder (ADHD) and conduct disorder (CD) exemplify top-down dysregulation conditions that show a large comorbidity and shared genetics. At the same time, they entail two different types of symptomology involving mainly non-emotional or emotional dysregulation. Few studies have tried to separate the specific biology underlying these two dimensions.

Ventromedial Prefrontal Volume in Adolescence Predicts Hyperactive/Inattentive Symptoms in Adulthood.

Youths with attention-deficit/hyperactivity disorder symptomatology often exhibit residual inattention and/or hyperactivity in adulthood; however, this is not true for all individuals. We recently reported that dimensional, multi-informant ratings of hyperactive/inattentive symptoms are associated with ventromedial prefrontal cortex (vmPFC) structure. Herein, we investigate the degree to which vmPFC structure during adolescence predicts hyperactive/inattentive symptomatology at 5-year follow-up.

Extending the Construct Network of Trait Disinhibition to the Neuroimaging Domain: Validation of a Bridging Scale for Use in the European IMAGEN Project.

Trait disinhibition, a clinical-liability construct, has well-established correlates in the diagnostic, self-rating, task-behavioral, and brain potential response domains. Recently, studies have begun to test for neuroimaging correlates of this liability factor, but more work of this type using larger data sets is needed to clarify its brain bases. The current study details the development and validation of a scale measure of trait disinhibition composed of questionnaire items available in the IMAGEN project, a large-scale longitudinal study of factors contributing to substance abuse that includes clinical interview, self-report personality, task-behavioral, neuroimaging, and genomic measures.

The contribution of parent and youth information to identify mental health disorders or problems in adolescents.

Background: Discrepancies between multiple informants often create considerable uncertainties in delivering services to youth. The present study assessed the ability of the parent and youth scales of the Strength and Difficulties Questionnaire (SDQ) to predict mental health problems/disorders across several mental health domains as validated against two contrasting indices of validity for psychopathology derived from the Development and Well Being Assessment (DAWBA): (1) an empirically derived computer algorithm and (2) expert based ICD-10 diagnoses.

Methods: Ordinal and logistic regressions were used to predict any problems/disorders, emotional problems/disorders and behavioural problems/disorders in a community sample (n = 252) and in a clinic sample (n = 95).

Inattention and Reaction Time Variability Are Linked to Ventromedial Prefrontal Volume in Adolescents.

Background: Neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) have most commonly reported volumetric abnormalities in the basal ganglia, cerebellum, and prefrontal cortices. Few studies have examined the relationship between ADHD symptomatology and brain structure in population-based samples. We investigated the relationship between dimensional measures of ADHD symptomatology, brain structure, and reaction time variability-an index of lapses in attention.

Neural correlates of three types of negative life events during angry face processing in adolescents.

Negative life events (NLE) contribute to anxiety and depression disorders, but their relationship with brain functioning in adolescence has rarely been studied. We hypothesized that neural response to social threat would relate to NLE in the frontal-limbic emotional regions. Participants (N = 685) were drawn from the Imagen database of 14-year-old community adolescents recruited in schools.

Effective Mental Health Screening in Adolescents: Should We Collect Data from Youth, Parents or Both?

Youth- and parent-rated screening measures derived from the Strengths and Difficulties Questionnaire (SDQ) and Development and Well-Being Assessment (DAWBA) were compared on their psychometric properties as predictors of caseness in adolescence (mean age 14). Successful screening was judged firstly against the likelihood of having an ICD-10 psychiatric diagnosis and secondly by the ability to discriminate between community (N = 252) and clinical (N = 86) samples (sample status). Both, SDQ and DAWBA measures adequately predicted the presence of an ICD-10 disorder as well as sample status.

Subthreshold depression and regional brain volumes in young community adolescents.

Objective: Neuroimaging findings have been reported in regions of the brain associated with emotion in both adults and adolescents with depression, but few studies have investigated whether such brain alterations can be detected in adolescents with subthreshold depression, a condition at risk for major depressive disorder. In this study, we searched for differences in brain structure at age 14 years in adolescents with subthreshold depression and their relation to depression at age 16 years.

Method: High-resolution structural magnetic resonance imaging was used to assess adolescents with self-reported subthreshold depression (n = 119) and healthy control adolescents (n = 461), all recruited from a community-based sample.