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.

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.

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.

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.

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.

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.

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.

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.

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

Heavy drinker adolescents: altered brainstem microstructure.

The cortical-cerebellar circuit is vulnerable to heavy drinking (HD) in adults. We hypothesized early microstructural modifications of the pons/midbrain region, containing core structures of the reward system, in HD adolescents. Thirty-two otherwise symptom-free HDs at age 14 (HD14) and 24 abstainers becoming HDs at age 16 (HD16) were identified in the community with the Alcohol Use Disorders Identification Test (AUDIT) and compared with abstainers. The monetary incentive delay (MID) task assessed reward-sensitive performance. Voxelwise statistics of diffusion tensor imaging (DTI) values in the thalamo-ponto-mesencephalic region were obtained using tract-based spatial statistics. Projections between the ventral tegmental area (VTA) and the nucleus accumbens (NAcc) were identified by probabilistic tractography. Lower fraction of anisotropy and higher radial diffusivity (RD) values were detected in the upper dorsal pons of HD14 adolescents, and a trend for higher RD in HD16, compared with abstainers. When expecting reward, HD14 had higher MID task success scores than abstainers, and success scores were higher with a lower number of tracts in all adolescents. In symptom-free community adolescents, a region of lower white matter (WM) integrity in the pons at age 14 was associated with current HD and predicted HD at age 16. HD was related to reward sensitivity.

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. It has also been suggested that both types of conditions consist of extreme cases in the general population where the symptoms are widely distributed. Here we test whether brain structure is specifically associated to ADHD or CD symptoms in a general population of adolescents (n = 1093) being part of the IMAGEN project. Both ADHD symptoms and CD symptoms were related to similar and overlapping MRI findings of a smaller structure in prefrontal and anterior cingulate cortex. However, our regions of interest (ROI) approach indicated that gray matter volume (GMV) and surface area (SA) in dorsolateral/dorsomedial prefrontal cortex and caudal anterior cingulate cortex were negatively associated to ADHD symptoms when controlling for CD symptoms while rostral anterior cingulate cortex GMV was negatively associated to CD symptoms when controlling for ADHD symptoms. The structural findings were mirrored in performance of neuropsychological tests dependent on prefrontal and anterior cingulate regions, showing that while performance on the Stop Signal test was specifically related to the ADHD trait, delayed discounting and working memory were related to both ADHD and CD traits. These results point towards a partially domain specific and dimensional capacity in different top-down regulatory systems associated with ADHD and CD symptoms.

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. We used voxel-based and Regions of Interest approaches to explore sex and puberty effects on brain and behavioral changes during adolescence. Sexual differences in brain maturation were characterized by amygdala and hippocampal volume increase in boys and decrease in girls. These changes were mediating the sexual differences in positive emotional regulation as illustrated by positive attributes increase in boys and decrease in girls. Moreover, the differential maturation rates between the limbic system and the prefrontal cortex highlighted the delayed maturation in boys compared to girls. This is the first study to show the sex effects on the differential cortico/subcortical maturation rates and the interaction between sex and puberty in the limbic system maturation related to positive attributes, reported as being protective from emotional disorders.

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. We ran analyses to find relationships between behavioural symptoms and neuroimaging measures of brain structure and function in adolescence. We found two symptom groups, consisting of anxiety/depression and executive dysfunction symptoms, respectively, that correlated with distinct sets of brain regions and inter-regional connections, measured by structural and functional neuroimaging modalities. We found that the neural correlates of these symptom groups were present before behavioural symptoms had developed. These neural correlates showed case-control differences in corresponding psychiatric disorders, depression and attention deficit hyperactivity disorder in independent clinical samples. By characterizing behavioural symptom groups based on shared neural mechanisms, our results provide a framework for developing a classification system for psychiatric illness that is based on quantitative neurobehavioural measures.

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. These effects are expected to involve within- and between-network iFC, particularly, the salience and the central-executive networks, consistent with the Triple-Network Model. Resting-state scans of an adolescent community sample (n = 304, male/female: 157/147; mean/std age: 14.6/0.41 years), from the IMAGEN database, were analyzed using the AFNI software suite and a data reduction strategy for the effects of puberty and sex. Three midline regions (medial prefrontal, pregenual anterior cingulate, and posterior cingulate), within the DMN and consistently implicated in mood disorders, were selected as seeds. Within- and between-network clusters of the DMN iFC changed with pubertal maturation differently in boys and girls (puberty-X-sex). Specifically, pubertal maturation predicted weaker iFC in girls and stronger iFC in boys. Finally, iFC was stronger in boys than girls independently of puberty. Brain-behavior associations indicated that lower connectivity of the anterior cingulate seed predicted higher internalizing symptoms at 2-year follow-up. In conclusion, weaker iFC of the anterior DMN may signal disconnections among circuits supporting mood regulation, conferring risk for internalizing disorders.

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. Using a construct-rating and psychometric refinement approach, a scale was developed that evidenced: (a) positive relations with interview-assessed psychopathology in the IMAGEN sample, both concurrently and prospectively and (b) positive associations with scale measures of disinhibition and reported psychopathology, and a robust negative correlation with P3 brain response, in a separate adult sample ( Mage = 19.5). These findings demonstrate that a common scale measure can index this construct from adolescence through to early adulthood, and set the stage for systematic work directed at identifying neural and genetic biomarkers of this key liability construct using existing and future data from the IMAGEN project.

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. Structural equation modeling was used to test the extent to which adolescent vmPFC volume predicts hyperactive/inattentive symptomatology 5 years later in early adulthood. 1104 participants (M = 14.52 years, standard deviation = 0.42; 583 females) possessed hyperactive/inattentive symptom data at 5-year follow-up, as well as quality controlled neuroimaging data and complete psychometric data at baseline. Self-reports of hyperactive/inattentive symptomatology were obtained during adolescence and at 5-year follow-up using the Strengths and Difficulties Questionnaire (SDQ). At baseline and 5-year follow-up, a hyperactive/inattentive latent variable was derived from items on the SDQ. Baseline vmPFC volume predicted adult hyperactive/inattentive symptomatology (standardized coefficient = -0.274, P < 0.001) while controlling for baseline hyperactive/inattentive symptomatology. These results are the first to reveal relations between adolescent brain structure and adult hyperactive/inattentive symptomatology, and suggest that early structural development of the vmPFC may be consequential for the subsequent expression of hyperactive/inattentive symptoms.

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. They were followed up at age 16 to assess depression. Probabilistic tractography was used to reconstruct white matter streamlines spreading from the regions identified in the TBSS analysis and along bundles implicated in emotion regulation, the uncinate fasciculus and the cingulum. The authors searched for mediating effects of white matter microstructure on the relationship between baseline subthreshold depression and depression at follow-up, and then explored the specificity of the findings. RESULTS: Lower fractional anisotropy (FA) and higher radial diffusivity were found in the anterior corpus callosum in the adolescents with subthreshold depression. Tractography analysis showed that they also had lower FA in the right cingulum streamlines, along with lower FA and higher mean diffusivity in tracts connecting the corpus callosum to the anterior cingulate cortex. The relation between subthreshold depression at baseline and depression at follow-up was mediated by FA values in the latter tracts, and lower FA values in those tracts distinctively predicted higher individual risk for depression. CONCLUSIONS: Early FA variations in tracts projecting from the corpus callosum to the anterior cingulate cortex may denote a higher risk of transition to depression in adolescents.

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). RESULTS: The findings were strikingly similar in both samples. Parent and youth SDQ scales were related to any problem/disorder. Youth SDQ symptom and impact had the strongest association with emotional problems/disorder and parent SDQ symptom score were most strongly related to behavioural problems/disorders. Both the SDQ total and the impact scores significantly predicted emotional problems/disorders in males whereas this was the case only for the total SDQ score in females. CONCLUSION: The present study confirms and expands previous findings on parent and youth informant validity. Clinicians should include both parent and youth for identifying any mental health problems/disorders, youth information for detecting emotional problems/disorders, and parent information to detect behavioural problems/disorders. Not only symptom scores but also impact measures may be useful to detect emotional problems/disorders, particularly in male youth.

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. We also tested for associations between brain structural correlates of ADHD symptomatology and maps of dopaminergic gene expression. METHODS: Psychopathology and imaging data were available for 1538 youths. Parent ratings of ADHD symptoms were obtained using the Development and Well-Being Assessment and the Strengths and Difficulties Questionnaire (SDQ). Self-reports of ADHD symptoms were assessed using the youth version of the SDQ. Reaction time variability was available in a subset of participants. For each measure, whole-brain voxelwise regressions with gray matter volume were calculated. RESULTS: Parent ratings of ADHD symptoms (Development and Well-Being Assessment and SDQ), adolescent self-reports of ADHD symptoms on the SDQ, and reaction time variability were each negatively associated with gray matter volume in an overlapping region of the ventromedial prefrontal cortex. Maps of DRD1 and DRD2 gene expression were associated with brain structural correlates of ADHD symptomatology. CONCLUSIONS: This is the first study to reveal relationships between ventromedial prefrontal cortex structure and multi-informant measures of ADHD symptoms in a large population-based sample of adolescents. Our results indicate that ventromedial prefrontal cortex structure is a biomarker for ADHD symptomatology. These findings extend previous research implicating the default mode network and dopaminergic dysfunction in ADHD.