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Using a novel trait-based measure, we examined genetic variants associated with obsessive-compulsive (OC) traits and tested whether OC traits and obsessive-compulsive disorder (OCD) shared genetic risk. We conducted a genome-wide association analysis (GWAS) of OC traits using the Toronto Obsessive-Compulsive Scale (TOCS) in 5018 unrelated Caucasian children and adolescents from the community (Spit for Science sample). We tested the hypothesis that genetic variants associated with OC traits from the community would be associated with clinical OCD using a meta-analysis of all currently available OCD cases. Shared genetic risk was examined between OC traits and OCD in the respective samples using polygenic risk score and genetic correlation analyses. A locus tagged by rs7856850 in an intron of PTPRD (protein tyrosine phosphatase δ) was significantly associated with OC traits at the genome-wide significance level (p = 2.48 × 10-8). rs7856850 was also associated with OCD in a meta-analysis of OCD case/control genome-wide datasets (p = 0.0069). The direction of effect was the same as in the community sample. Polygenic risk scores from OC traits were significantly associated with OCD in case/control datasets and vice versa (p's

No diagnostic biomarkers are available for obsessive-compulsive disorder (OCD). Here, we aimed to identify magnetic resonance imaging (MRI) biomarkers for OCD, using 46 data sets with 2304 OCD patients and 2068 healthy controls from the ENIGMA consortium. We performed machine learning analysis of regional measures of cortical thickness, surface area and subcortical volume and tested classification performance using cross-validation. Classification performance for OCD vs. controls using the complete sample with different classifiers and cross-validation strategies was poor. When models were validated on data from other sites, model performance did not exceed chance-level. In contrast, fair classification performance was achieved when patients were grouped according to their medication status. These results indicate that medication use is associated with substantial differences in brain anatomy that are widely distributed, and indicate that clinical heterogeneity contributes to the poor performance of structural MRI as a disease marker.

ObjectiveAttention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data.MethodsStructural T1-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures).ResultsNo shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood.ConclusionsThe study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.

BackgroundLateralized dysfunction has been suggested in obsessive-compulsive disorder (OCD). However, it is currently unclear whether OCD is characterized by abnormal patterns of brain structural asymmetry. Here we carried out what is by far the largest study of brain structural asymmetry in OCD.MethodsWe studied a collection of 16 pediatric datasets (501 patients with OCD and 439 healthy control subjects), as well as 30 adult datasets (1777 patients and 1654 control subjects) from the OCD Working Group within the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Consortium. Asymmetries of the volumes of subcortical structures, and of measures of regional cortical thickness and surface areas, were assessed based on T1-weighted magnetic resonance imaging scans, using harmonized image analysis and quality control protocols. We investigated possible alterations of brain asymmetry in patients with OCD. We also explored potential associations of asymmetry with specific aspects of the disorder and medication status.ResultsIn the pediatric datasets, the largest case-control differences were observed for volume asymmetry of the thalamus (more leftward; Cohen's d = 0.19) and the pallidum (less leftward; d = -0.21). Additional analyses suggested putative links between these asymmetry patterns and medication status, OCD severity, or anxiety and depression comorbidities. No significant case-control differences were found in the adult datasets.ConclusionsThe results suggest subtle changes of the average asymmetry of subcortical structures in pediatric OCD, which are not detectable in adults with the disorder. These findings may reflect altered neurodevelopmental processes in OCD.

Objective: Brain imaging communities focusing on different diseases have increasingly started to collaborate and to pool data to perform well-powered meta- and mega-analyses. Some methodologists claim that a one-stage individual-participant data (IPD) mega-analysis can be superior to a two-stage aggregated data meta-analysis, since more detailed computations can be performed in a mega-analysis. Before definitive conclusions regarding the performance of either method can be drawn, it is necessary to critically evaluate the methodology of, and results obtained by, meta- and mega-analyses. Methods: Here, we compare the inverse variance weighted random-effect meta-analysis model with a multiple linear regression mega-analysis model, as well as with a linear mixed-effects random-intercept mega-analysis model, using data from 38 cohorts including 3,665 participants of the ENIGMA-OCD consortium. We assessed the effect sizes and standard errors, and the fit of the models, to evaluate the performance of the different methods. Results: The mega-analytical models showed lower standard errors and narrower confidence intervals than the meta-analysis. Similar standard errors and confidence intervals were found for the linear regression and linear mixed-effects random-intercept models. Moreover, the linear mixed-effects random-intercept models showed better fit indices compared to linear regression mega-analytical models. Conclusions: Our findings indicate that results obtained by meta- and mega-analysis differ, in favor of the latter. In multi-center studies with a moderate amount of variation between cohorts, a linear mixed-effects random-intercept mega-analytical framework appears to be the better approach to investigate structural neuroimaging data.

ObjectiveBrain imaging studies of structural abnormalities in OCD have yielded inconsistent results, partly because of limited statistical power, clinical heterogeneity, and methodological differences. The authors conducted meta- and mega-analyses comprising the largest study of cortical morphometry in OCD ever undertaken.MethodT1-weighted MRI scans of 1,905 OCD patients and 1,760 healthy controls from 27 sites worldwide were processed locally using FreeSurfer to assess cortical thickness and surface area. Effect sizes for differences between patients and controls, and associations with clinical characteristics, were calculated using linear regression models controlling for age, sex, site, and intracranial volume.ResultsIn adult OCD patients versus controls, we found a significantly lower surface area for the transverse temporal cortex and a thinner inferior parietal cortex. Medicated adult OCD patients also showed thinner cortices throughout the brain. In pediatric OCD patients compared with controls, we found significantly thinner inferior and superior parietal cortices, but none of the regions analyzed showed significant differences in surface area. However, medicated pediatric OCD patients had lower surface area in frontal regions. Cohen's d effect sizes varied from -0.10 to -0.33.ConclusionsThe parietal cortex was consistently implicated in both adults and children with OCD. More widespread cortical thickness abnormalities were found in medicated adult OCD patients, and more pronounced surface area deficits (mainly in frontal regions) were found in medicated pediatric OCD patients. These cortical measures represent distinct morphological features and may be differentially affected during different stages of development and illness, and possibly moderated by disease profile and medication.

Anxiety disorders are associated with abnormalities in amygdala function and prefrontal cortex-amygdala connectivity. The majority of functional magnetic resonance imaging studies have examined mean group differences in amygdala activation or connectivity in children and adolescents with anxiety disorders relative to controls, but emerging evidence suggests that abnormalities in amygdala function are dependent on the timing of the task and may vary across the course of a scanning session. The goal of the present study was to extend our knowledge of the dynamics of amygdala dysfunction by examining whether changes in amygdala activation and connectivity over scanning differ in pediatric anxiety disorder patients relative to typically developing controls during an emotion processing task. Examining changes in activation over time allows for a comparison of how brain function differs during initial exposure to novel stimuli versus more prolonged exposure. Participants included 34 anxiety disorder patients and 19 controls 7 to 19 years old. Participants performed an emotional face-matching task during functional magnetic resonance imaging scanning, and the task was divided into thirds in order to examine change in activation over time. Results demonstrated that patients exhibited an abnormal pattern of amygdala activation characterized by an initially heightened amygdala response relative to controls at the beginning of scanning, followed by significant decreases in activation over time. In addition, controls evidenced greater context-modulated prefrontal cortex-amygdala connectivity during the beginning of scanning relative to patients. These results indicate that differences in emotion processing between the groups vary from initial exposure to novel stimuli relative to more prolonged exposure. Implications are discussed regarding how this pattern of neural activation may relate to altered early-occurring or anticipatory emotion-regulation strategies and maladaptive later-occurring strategies in children and adolescents with anxiety disorders.

BackgroundPediatric and adult anxiety disorder patients exhibit attention bias to threat and difficulty disengaging attention away from threat. Cognitive frameworks suggest that these patterns are associated with hyperactivation of regions associated with detecting threat, such as the amygdala, and hypoactivation of regions associated with regulating attention, including the lateral prefrontal cortex and rostral anterior cingulate cortex (rACC). The aim of the present study was to examine the neural correlates of these processes in children and adolescents with anxiety disorders.MethodsParticipants with an anxiety disorder 7 to 19 years old (n = 34) and typically developing controls (n = 35) underwent fMRI scanning. During scanning, they completed a task with conditions that manipulated whether participants were instructed to match emotional faces (direct emotion processing) or match shapes in the context of emotional face distractors (attentional control).ResultsResults revealed a significant difference in rACC activation during shape versus face matching, with controls evidencing greater rACC activation relative to patients.ConclusionsThis study identifies abnormalities in rACC activation as a potential neural mediator associated with pediatric anxiety disorders, which can inform frameworks for understanding their development and treatment.

The current study examined concurrent relationships between children's self-regulation, measured behaviorally and by parent-report, and children's internalizing and externalizing symptoms. The aim was to distinguish which components of self-regulation (attention vs. inhibitory control, "hot" vs. "cool" regulation) best predict dimensional symptomatology and clinical disorders in young children. The participants were 120 children, ages 4–8 years old. Results showed that greater parent-reported attention was associated with fewer internalizing and externalizing symptoms. Behaviorally-measured hot inhibitory control related to fewer internalizing symptoms, whereas parent-reported inhibitory control related to fewer externalizing symptoms. Similar patterns emerged for clinical diagnoses, with parent-rated attention most strongly predicting disorders across domains. Results support prior evidence implicating self-regulatory deficits in externalizing problems, while also demonstrating that components of self-regulation are impaired with internalizing symptoms. Further, different sub-components of self-regulation relate to different dimensions of psychopathology in children. Interventions should target these areas in children at-risk for disorders. [ABSTRACT FROM AUTHOR]