Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder:The ENIGMA adventure

International audienc

Brain imaging of the cortex in ADHD: a coordinated analysis of large-scale clinical and population-based samples

Objective: Neuroimaging studies show structural alterations of various brain regions in children and adults with attention deficit hyperactivity disorder (ADHD), although nonreplications are frequent. The authors sought to identify cortical characteristics related to ADHD using large-scale studies. Methods: Cortical thickness and surface area (based on the Desikan–Killiany atlas) were compared between case subjects with ADHD (N=2,246) and control subjects (N=1,934) for children, adolescents, and adults separately in ENIGMA-ADHD, a consortium of 36 centers. To assess familial effects on cortical measures, case subjects, unaffected siblings, and control subjects in the NeuroIMAGE study (N=506) were compared. Associations of the attention scale from the Child Behavior Checklist with cortical measures were determined in a pediatric population sample (Generation-R, N=2,707). Results: In the ENIGMA-ADHD sample, lower surface area values were found in children with ADHD, mainly in frontal, cingulate, and temporal regions; the largest significant effect was for total surface area (Cohen’s d=−0.21). Fusiform gyrus and temporal pole cortical thickness was also lower in children with ADHD. Neither surface area nor thickness differences were found in the adolescent or adult groups. Familial effects were seen for surface area in several regions. In an overlapping set of regions, surface area, but not thickness, was associated with attention problems in the Generation-R sample. Conclusions: Subtle differences in cortical surface area are widespread in children but not adolescents and adults with ADHD, confirming involvement of the frontal cortex and highlighting regions deserving further attention. Notably, the alterations behave like endophenotypes in families and are linked to ADHD symptoms in the population, extending evidence that ADHD behaves as a continuous trait in the population. Future longitudinal studies should clarify individual lifespan trajectories that lead to nonsignificant findings in adolescent and adult groups despite the presence of an ADHD diagnosis

Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets

Objective Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium. Methods We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries. Results There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen’s d from −0.18 to 0.18) and would not survive study-wide correction for multiple testing. Conclusion Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait

Subcortical brain volume, regional cortical thickness, and cortical surface area across disorders: findings from the ENIGMA ADHD, ASD, and OCD Working Groups

Objective Attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. We aimed to directly compare all three disorders. The ENIGMA consortium is ideally positioned to investigate structural brain alterations across these disorders. Methods Structural T1-weighted whole-brain MRI of controls (n=5,827) and 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. We examined subcortical volume, cortical thickness and 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 ICV for subcortical and surface area measures). Results We found no shared alterations among all three disorders, while shared alterations between any two disorders did not survive multiple comparisons correction. Children with ADHD compared to those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller ICV than controls and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared to adult controls and other clinical groups. No OCD-specific alterations across different age-groups and surface area alterations among all disorders in childhood and adulthood were observed. Conclusion Our findings suggest robust but subtle alterations across different age-groups among ADHD, ASD, and OCD. ADHD-specific ICV and hippocampal alterations in children and adolescents, and ASD-specific cortical thickness alterations in the frontal cortex in adults support previous work emphasizing neurodevelopmental alterations in these disorders

Exploring the knowledge contained in neuroimages: Statistical discriminant analysis and automatic segmentation of the most significant changes

Objective: The aim of this article is to propose an integrated framework for extracting and describing patterns of disorders from medical images using a combination of linear discriminant analysis and active contour models. Methods: A multivariate statistical methodology was first used to identify the most discriminating hyperplane separating two groups of images (from healthy controls and patients with schizophrenia) contained in the input data. After this, the present work makes explicit the differences found by the multivariate statistical method by subtracting the discriminant models of controls and patients, weighted by the pooled variance between the two groups. A variational level-set technique was used to segment clusters of these differences. We obtain a label of each anatomical change using the Talairach atlas. Results: In this work all the data was analysed simultaneously rather than assuming a priori regions of interest. As a consequence of this, by using active contour models, we were able to obtain regions of interest that were emergent from the data. The results were evaluated using, as gold standard, well-known facts about the neuroanatomical changes related to schizophrenia. Most of the items in the gold standard was covered in our result set. Conclusions: We argue that such investigation provides a suitable framework for characterising the high complexity of magnetic resonance images in schizophrenia as the results obtained indicate a high sensitivity rate with respect to the gold standard. (C) 2010 Elsevier B.V. All rights reserved.FAPESPSPCNPq, Brazi

Switching from oral risperidone to flexibly dosed oral paliperidone extended-release: core symptoms, satisfaction, and quality of life in patients with stable but symptomatic schizophrenia: the RISPALI study

Objective:The purpose of this prospective study was to evaluate the effects of switching from oral risperidone to flexibly dosed oral paliperidone extended-release (ER) in Brazilian adults with schizophrenia because of lack of efficacy, intolerability, or nonadherence after a minimum trial of 30 days on adequate (labeled) doses of oral risperidone, according to individual clinical judgment.Research design and methods:Subjects with Positive and Negative Syndrome Scale total scores above 78, and/or intolerable adverse effects, with risperidone received open-label paliperidone ER 3 to 12 mg daily for 26 (main phase) to 52 (extension phase) weeks.Clinical trial registration:Clinicaltrials.gov identifier: NCT01010776.Results:The intent-to-treat (efficacy) populations comprised 213 subjects in the main phase and 159 in the extension phase. of 213 subjects with baseline and post-baseline efficacy data, 154 (72.3%) switched from risperidone to paliperidone ER because of a lack of efficacy and 59 (27.7%) because of tolerability issues, according to individual clinical judgment. Paliperidone ER significantly (p < 0.0500) improved a broad spectrum of efficacy endpoints from baseline, as early as the first post-baseline visit (Visit 2; 4 weeks) and persisting through 26 to 52 weeks. On most efficacy endpoints, function improved from baseline to the first post-baseline visit (week 4) and remained significantly improved compared to baseline at each visit for paliperidone ER treatment, at weeks 8, 13, 26, 39, 26, and 52; data are reported herein mainly for 26 and 52 weeks compared to baseline. Significant improvements from baseline were observed for the Positive and Negative Syndrome Scale total score and subscale scores (each p < 0.0001 at 26 and 52 weeks vs. baseline); and personal and social functioning (p < 0.0001 at 26 and 52 weeks). Paliperidone ER also significantly improved health-related quality of life (Short-Form 36) from baseline, particularly on the Mental Component Summary (p = 0.0011 at 26 weeks and p = 0.0019 at 52 weeks). Treatment with paliperidone ER also significantly improved (vs. baseline) sleep quality (according to decreases on the Pittsburgh Sleep Quality Index; p < 0.0001 at each visit vs. baseline) and disease severity (Clinical Global Impression-Severity; p < 0.0001 at each visit vs. baseline). Paliperidone ER was well tolerated. Adverse events occurring in at least 10% of subjects in either phase were insomnia (14.9% in the main phase and 8.8% in the extension phase); increased body weight (10.7% and 12.6%, respectively); and anxiety (10.7% and 2.5%). Most of these adverse events were: 1) rated as mild or moderate; 2) did not prompt interventions such as paliperidone ER dose adjustment or interruption; and 3) decreased in frequency from the main to the extension phase.Conclusions:Oral paliperidone ER is a rational treatment alternative for patients with schizophrenia whose antipsychotic regimens are switched because of unsuccessful treatment with oral risperidone according to individual clinical judgment. Study limitations included the open-label study design, lack of placebo, and use of subjective clinical judgment to determine lack of efficacy, intolerability, or nonadherence with oral risperidone.Janssen-Cilag Farmaceutica Ltda., São Paulo, BrazilFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Janssen-CilagNovartisRocheEMS Pharmaceuticals, BrazilMoksha8Eli LillyBristol-Myers SquibbServierLundbeckQuintilesTevaCPPSSUniv São Paulo, Sch Med, Dept & Inst Psychiat, BR-05403010 São Paulo, BrazilUniv São Paulo, Sch Med, Lab Neurosci LIM27, BR-05403010 São Paulo, BrazilUniv Fed Goias, Dept Psychiat, Goiania, Go, BrazilUniversidade Federal de São Paulo, Dept Psychiat, São Paulo, BrazilInst Psychiat Prof Andro Teixeira Lima, Sorocaba, SP, BrazilCtr Psychiat & Res SR, Ctr Psychiat & Res, Rio de Janeiro, BrazilUniv Fed Bahia, Dept Neurosci & Mental Hlth, Salvador, BA, BrazilInst Social Secur Civil Servants Minas Gerais IPS, Dept Psychiat, Belo Horizonte, MG, BrazilHosp Bom Retiro, Curitiba, Parana, BrazilFac Med Marilia, Marilia, SP, BrazilUniv São Paulo, Inst Psychiat, BR-05403010 São Paulo, BrazilUniv Southern Santa Catarina, Neurosci Lab, Criciuma, SC, BrazilUniv Southern Santa Catarina, Natl Inst Translat Med INCT TM, Criciuma, SC, BrazilUniv Fed Parana, Fac Med, BR-80060000 Curitiba, Parana, BrazilFac Med ABC, Santo Andre, SP, BrazilJanssen Cilag Farmaceut Ltda, São Paulo, BrazilUniv Fed Rio de Janeiro, Inst Psychiat, BR-21941 Rio de Janeiro, BrazilUniversidade Federal de São Paulo, Dept Psychiat, São Paulo, BrazilWeb of Scienc

Evidence for similar structural brain anomalies in youth and adult attention-deficit/hyperactivity disorder: a machine learning analysis

Attention-deficit/hyperactivity disorder (ADHD) affects 5% of children world-wide. Of these, two-thirds continue to have impairing symptoms of ADHD into adulthood. Although a large literature implicates structural brain differences of the disorder, it is not clear if adults with ADHD have similar neuroanatomical differences as those seen in children with recent reports from the large ENIGMA-ADHD consortium finding structural differences for children but not for adults. This paper uses deep learning neural network classification models to determine if there are neuroanatomical changes in the brains of children with ADHD that are also observed for adult ADHD, and vice versa. We found that structural MRI data can significantly separate ADHD from control participants for both children and adults. Consistent with the prior reports from ENIGMA-ADHD, prediction performance and effect sizes were better for the child than the adult samples. The model trained on adult samples significantly predicted ADHD in the child sample, suggesting that our model learned anatomical features that are common to ADHD in childhood and adulthood. These results support the continuity of ADHD’s brain differences from childhood to adulthood. In addition, our work demonstrates a novel use of neural network classification models to test hypotheses about developmental continuity.publishedVersio

Evidence for similar structural brain anomalies in youth and adult attention-deficit/hyperactivity disorder:a machine learning analysis

Attention-deficit/hyperactivity disorder (ADHD) affects 5% of children world-wide. Of these, two-thirds continue to have impairing symptoms of ADHD into adulthood. Although a large literature implicates structural brain differences of the disorder, it is not clear if adults with ADHD have similar neuroanatomical differences as those seen in children with recent reports from the large ENIGMA-ADHD consortium finding structural differences for children but not for adults. This paper uses deep learning neural network classification models to determine if there are neuroanatomical changes in the brains of children with ADHD that are also observed for adult ADHD, and vice versa. We found that structural MRI data can significantly separate ADHD from control participants for both children and adults. Consistent with the prior reports from ENIGMA-ADHD, prediction performance and effect sizes were better for the child than the adult samples. The model trained on adult samples significantly predicted ADHD in the child sample, suggesting that our model learned anatomical features that are common to ADHD in childhood and adulthood. These results support the continuity of ADHD’s brain differences from childhood to adulthood. In addition, our work demonstrates a novel use of neural network classification models to test hypotheses about developmental continuity

Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets

Objective Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium. Methods We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries. Results There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen’s d from −0.18 to 0.18) and would not survive study-wide correction for multiple testing. Conclusion Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait

Evidence for similar structural brain anomalies in youth and adult attention-deficit/hyperactivity disorder: a machine learning analysis

Attention-deficit/hyperactivity disorder (ADHD) affects 5% of children world-wide. Of these, two-thirds continue to have impairing symptoms of ADHD into adulthood. Although a large literature implicates structural brain differences of the disorder, it is not clear if adults with ADHD have similar neuroanatomical differences as those seen in children with recent reports from the large ENIGMA-ADHD consortium finding structural differences for children but not for adults. This paper uses deep learning neural network classification models to determine if there are neuroanatomical changes in the brains of children with ADHD that are also observed for adult ADHD, and vice versa. We found that structural MRI data can significantly separate ADHD from control participants for both children and adults. Consistent with the prior reports from ENIGMA-ADHD, prediction performance and effect sizes were better for the child than the adult samples. The model trained on adult samples significantly predicted ADHD in the child sample, suggesting that our model learned anatomical features that are common to ADHD in childhood and adulthood. These results support the continuity of ADHD’s brain differences from childhood to adulthood. In addition, our work demonstrates a novel use of neural network classification models to test hypotheses about developmental continuity