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Importance: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood., Objective: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia., Design, Setting, and Participants: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244., Main Outcomes and Measures: Interregional profiles of group difference in cortical thickness between cases and controls., Results: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders., Conclusions and Relevance: In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.

This paper presents a novel approach for classifying obsessive-compulsive disorder (OCD) in adolescents from resting-state fMRI data. Currently, the state-of-the-art for diagnosing OCD in youth involves interviews with adolescent patients and their parents by an experienced clinician, symptom rating scales based on Diagnostic and Statistical Manual of Mental Disorders (DSM), and behavioral observation. Discovering signal processing and network-based biomarkers from functional magnetic resonance imaging (fMRI) scans of patients has the potential to assist clinicians in their diagnostic assessments of adolescents suffering from OCD. This paper investigates the clinical diagnostic utility of a set of univariate, bivariate and multivariate features extracted from resting-state fMRI using an information-theoretic approach in 15 adolescents with OCD and 13 matched healthy controls. Results indicate that an information-theoretic approach based on sub-graph entropy is capable of classifying OCD vs. healthy subjects with high accuracy. Mean time-series were extracted from 85 brain regions and were used to calculate Shannon wavelet entropy, Pearson correlation matrix, network features and sub-graph entropy. In addition, two special cases of sub-graph entropy, namely node and edge entropy, were investigated to identify important brain regions and edges from OCD patients. A leave-one-out cross-validation method was used for the final predictor performance. The proposed methodology using differential sub-graph (edge) entropy achieved an accuracy of 0.89 with specificity 1 and sensitivity 0.80 using leave-one-out cross-validation with in-fold feature ranking and selection. The high classification accuracy indicates the predictive power of the sub-network as well as edge entropy metric., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: Foundational knowledge on neural circuitry underlying pediatric obsessive-compulsive disorder (OCD) and how it changes during standard treatment is needed to provide the basis for conceptualization and development of novel targeted treatments. This study explored the effects of sertraline, a selective serotonin reuptake inhibitor, on resting-state functional connectivity in cortico-striatal-thalamic-cortical circuits in pediatric OCD., Method: Medication-free youths with OCD (n = 14) and healthy controls (n = 14) were examined at baseline and 12 weeks with resting-state functional magnetic resonance imaging. Between scan sessions, participants with OCD received 12 weeks of sertraline. For each scan, seed-based whole-brain resting-state functional connectivity analyses were conducted with 6 striatal seeds. Analysis of variance examined the interaction between group and time on striatal connectivity, including cluster-based thresholding to correct for multiple tests. Connectivity changes within circuits identified in group analyses were correlated with clinical change., Results: Two significant group-by-time effects in the OCD group showed increased striatal connectivity from baseline to 12 weeks compared with controls. Circuits demonstrating this pattern included the right putamen with the left frontal cortex and insula and the left putamen with the left frontal cortex and pre- and post-central cortices. Increase in connectivity in the left putamen circuit was significantly correlated with clinical improvement on the Children's Yale-Brown Obsessive-Compulsive Scale score (r = -0.58, p = .03)., Conclusion: Sertraline appears to affect specific striatal-based circuits in pediatric OCD, and these changes in part could account for clinical improvement. Future work is needed to confirm these preliminary findings, which would facilitate identification of circuit-based targets for novel treatment development., Clinical Trial Registration Information: Effects of Sertraline on Brain Connectivity in Adolescents with OCD; https://clinicaltrials.gov/; NCT02797808., (Copyright © 2018 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)

Objectives: The clinical presentation of pediatric obsessive-compulsive disorder (OCD) is heterogeneous, which is a stumbling block to understanding pathophysiology and to developing new treatments. A major shift in psychiatry, embodied in the Research Domain Criteria (RDoC) initiative of National Institute of Mental Health, recognizes the pitfalls of categorizing mental illnesses using diagnostic criteria. Instead, RDoC encourages researchers to use a dimensional approach, focusing on narrower domains of psychopathology to characterize brain-behavior relationships. Our aim in this multidisciplinary pilot study was to use computer vision tools to record OCD behaviors and to cross-validate these behavioral markers with standard clinical measures., Methods: Eighteen youths with OCD and 21 healthy controls completed tasks in an innovation laboratory (free arrangement of objects, hand washing, arrangement of objects on contrasting carpets). Tasks were video-recorded. Videos were coded by blind raters for OCD-related behaviors. Children's Yale-Brown Obsessive Compulsive Scale (CY-BOCS) and other scales were administered. We compared video-recorded measures of behavior in OCD versus healthy controls and correlated video measures and clinical measures of OCD., Results: Behavioral measures on the videos were significantly correlated with specific CY-BOCS dimension scores. During the free arrangement task, more time spent ordering objects and more moves of objects were both significantly associated with higher CY-BOCS ordering/repeating dimension scores. Longer duration of hand washing was significantly correlated with higher scores on CY-BOCS ordering/repeating and forbidden thoughts dimensions. During arrangement of objects on contrasting carpets, more moves and more adjustment of objects were significantly associated with higher CY-BOCS ordering/repeating dimension scores., Conclusion: Preliminary data suggest that measurement of behavior using video recording is a valid approach for quantifying OCD psychopathology. This methodology could serve as a new tool for investigating OCD using an RDoC approach. This objective, novel behavioral measurement technique may benefit both researchers and clinicians in assessing pediatric OCD and in identifying new behavioral markers of OCD. Clinical Trial Registry: Development of an Instrument That Monitors Behaviors Associated With OCD. NCT02866422. http://clinicaltrials.gov.

Obssesive-compulsive disorder (OCD) is a serious mental illness that affects the overall quality of the patients' daily lives. Accurate diagnosis of this disorder is a primary step towards effective treatment. Diagnosing OCD is a lengthy procedure that involves interviews, symptom rating scales and behavioral observation as well as the experience of a clinician. Discovering signal processing and network based biomarkers from functional magnetic resonance scans of patients may greatly assist the clinicians in their diagnostic assessments. In this paper, we explore the use of Pearson's correlation scores and network based features to predict if a subject has OCD. We extracted mean time series from 112 brain regions and decomposed them to 5-frequency bands. The mean time courses were used to calculate the Pearson's correlation matrix and network based features for each band. Minimum redundancy maximum relevance feature selection method is applied to the Pearson's correlation matrix and network based features from each frequency band to select the best features for the final predictor. A leave-one-out cross validation method is used for the final predictor performance. Our proposed methodology achieves 80% accuracy (23 out of 29 subjects classified correctly) with 81% sensitivity(13 out of 16 OCD subjects identified correctly) and 77% specificity (10 out of 13 controls identified correctly) using leave-one-out with in-fold feature ranking and selection. The most discriminating feature bands are 0.06-0.11 Hz for Pearson's correlation and 0.03-0.06 Hz for network based features. The high classification accuracy indicates the predictive power of the network features as well as carefully chosen Pearson's correlation values.

Neuroimaging research has implicated abnormalities in cortico-striatal-thalamic-cortical (CSTC) circuitry in pediatric obsessive-compulsive disorder (OCD). In this study, resting-state functional magnetic resonance imaging (R-fMRI) was used to investigate functional connectivity in the CSTC circuitry in adolescents with OCD. Imaging was obtained with the Human Connectome Project (HCP) scanner using newly developed pulse sequences which allow for higher spatial and temporal resolution. Fifteen adolescents with OCD and 13 age- and gender-matched healthy controls (ages 12-19) underwent R-fMRI on the 3T HCP scanner. Twenty-four minutes of resting-state scans (two consecutive 12-min scans) were acquired. We investigated functional connectivity of the striatum using a seed-based, whole brain approach with anatomically-defined seeds placed in the bilateral caudate, putamen, and nucleus accumbens. Adolescents with OCD compared with controls exhibited significantly lower functional connectivity between the left putamen and a single cluster of right-sided cortical areas including parts of the orbitofrontal cortex, inferior frontal gyrus, insula, and operculum. Preliminary findings suggest that impaired striatal connectivity in adolescents with OCD in part falls within the predicted CSTC network, and also involves impaired connections between a key CSTC network region (i.e., putamen) and key regions in the salience network (i.e., insula/operculum). The relevance of impaired putamen-insula/operculum connectivity in OCD is discussed., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)