Commentary: 'Camouflaging' in autistic people - reflection on Fombonne (2020)

Fombonne's (2020) editorial is a thought-provoking appraisal of the literature on 'camouflaging', whereby some autistic people mask or compensate for their autistic characteristics as an attempt to fit in and to cope with disabilities under neurotypical social norms. Fombonne (2020) highlights three issues of contention: (a) construct validity and measurement of camouflaging; (b) camouflaging as a reason for late autism diagnosis in adolescence/adulthood; and (c) camouflaging as a feature of the 'female autism phenotype'. Here, we argue that (a) establishing construct validity and measurement of different aspects of camouflaging is warranted; (b) subjective experiences are important for the differential diagnosis of autism in adolescence/adulthood; and (c) camouflaging is not necessarily a feature of autism in female individuals - nevertheless, taking into account sex and gender influences in development is crucial to understand behavioural manifestations of autism. Future research and clinical directions should involve clarification of associated constructs and measurements, demography, mechanisms, impact (including harms and benefits) and tailored support.

Practitioner Review: Pharmacological treatment of attention-deficit/hyperactivity disorder symptoms in children and youth with autism spectrum disorder: a systematic review and meta-analysis

BACKGROUND

Clinically significant attention-deficit/hyperactivity disorder (ADHD) symptoms are common and impairing in children and youth with autism spectrum disorder(ASD). The aim of this systematic review and meta-analysis was to (a) evaluate the efficacy and safety of pharmacotherapy for the treatment of ADHD symptoms in ASD and (b) distil findings for clinical translation.

METHODS

We searched electronic databases and clinical trial registries (1992 onwards). We selected randomized controlled trials conducted in participants <25 years of age, diagnosed with ASD that evaluated ADHD outcomes (hyperactivity/impulsivity and inattention) following treatment with stimulants (methylphenidate or amphetamines), atomoxetine, alpha-2 adrenergic receptor agonists, antipsychotics, tricyclic antidepressants, bupropion, modafinil, venlafaxine, or a combination, in comparison with placebo, any of the listed medications, or behavioral therapies. Data were pooled using a random-effects model.

RESULTS

Twenty-five studies (4 methylphenidate, 4 atomoxetine, 1 guanfacine, 14 antipsychotic, 1 venlafaxine, and 1 tianeptine) were included. Methylphenidate reduced hyperactivity (parent-rated: standardized mean difference [SMD] = -.63, 95%CI = -.95,-.30; teacher-rated: SMD = -.81, 95%CI = -1.43,-.19) and inattention (parent-rated: SMD = -.36, 95%CI = -.64,-.07; teacher-rated: SMD = -.30, 95%CI = -.49,-.11). Atomoxetine reduced inattention (parent-rated: SMD = -.54, 95%CI = -.98,-.09; teacher/investigator-rated: SMD = -0.38, 95%CI = -0.75, -0.01) and parent-rated hyperactivity (parent-rated: SMD = -.49, 95%CI = -.76,-.23; teacher-rated: SMD = -.43, 95%CI = -.92, .06). Indirect evidence for significant reductions in hyperactivity with second-generation antipsychotics was also found. Quality of evidence for all interventions was low/very low. Methylphenidate was associated with a nonsignificant elevated risk of dropout due to adverse events.

CONCLUSIONS

Direct pooled evidence supports the efficacy and tolerability of methylphenidate or atomoxetine for treatment of ADHD symptoms in children and youth with ASD. The current review highlights the efficacy of standard ADHD pharmacotherapy for treatment of ADHD symptoms in children and youth with ASD. Consideration of the benefits weighed against the limitations of safety/efficacy data and lack of data evaluating long-term continuation is undertaken to help guide clinical decision-making regarding treatment of co-occurring ADHD symptoms in children and youth with ASD.

Assessing and stabilizing atypical plasticity in autism spectrum disorder using rTMS: Results from a proof-of-principle study

OBJECTIVES

Emerging evidence implicates atypical plasticity in the neurophysiology of autism spectrum disorder (ASD). Specifically, autistic people demonstrated hyperplasticity in response to theta-burst stimulation (TBS). We hypothesized that autistic adults would display hyperplasticity to TBS and that repetitive transcranial magnetic stimulation (rTMS) - which potentiates brain inhibitory mechanisms - would 'stabilize' hyperplasticity.

METHODS

Using a randomized, cross-over design, plasticity was assessed using TBS in the left motor cortex (M1) in 31 autistic adults and 30 sex-, intelligence quotient-, and age-matched controls. Autistic adults (n = 29) were further randomized (1:1) to receive a single session of active (n = 14) or sham (n = 15) rTMS (6000 pulses at 20 Hz) over left M1 and plasticity was reassessed on the next day following rTMS.

RESULTS

Both long-term potentiation (LTP) and long-term depression (LTD) were significantly increased in the ASD group, indicating hyperplasticity. Active, but not sham rTMS, attenuated LTD in autistic adults.

CONCLUSIONS

We provided further evidence for the presence of brain hyperplasticity in ASD. To our knowledge, this is the first study to show preliminary evidence that an excessive LTD in ASD can be 'stabilized' using rTMS. Such 'stabilizing' effect of rTMS on LTP was not observed, likely due to small sample size or a more specific 'attenuating' effect of rTMS on LTD, compared to LTP.

SIGNIFICANCE

These findings indicate atypical brain inhibitory mechanisms behind hyperplasticity in ASD. Utilizing a larger sample, future replication studies could investigate therapeutic opportunities of 'mechanism-driven' rTMS.

Cortical Gyrification Morphology in Individuals with ASD and ADHD across the Lifespan: A Systematic Review and Meta-Analysis

Autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) are common neurodevelopmental disorders (NDDs) that may impact brain maturation. A number of studies have examined cortical gyrification morphology in both NDDs. Here we review and when possible pool their results to better understand the shared and potentially disorder-specific gyrification features. We searched MEDLINE, PsycINFO, and EMBASE databases, and 24 and 10 studies met the criteria to be included in the systematic review and meta-analysis portions, respectively. Meta-analysis of local Gyrification Index (lGI) findings across ASD studies was conducted with SDM software adapted for surface-based morphometry studies. Meta-regressions were used to explore effects of age, sex, and sample size on gyrification differences. There were no significant differences in gyrification across groups. Qualitative synthesis of remaining ASD studies highlighted heterogeneity in findings. Large-scale ADHD studies reported no differences in gyrification between cases and controls suggesting that, similar to ASD, there is currently no evidence of differences in gyrification morphology compared with controls. Larger, longitudinal studies are needed to further clarify the effects of age, sex, and IQ on cortical gyrification in these NDDs.

Quantitative and Qualitative Sex Modulations in the Brain Anatomy of Autism

BACKGROUND

Sex-based neurobiological heterogeneity in autism is poorly understood. Research is disproportionately biased to males, leading to an unwarranted presumption that autism neurobiology is the same across sexes. Previous neuroimaging studies using amalgamated multicenter datasets to increase autistic female samples are characterized by large statistical noise.

METHODS

We used a better-powered dataset of 1183 scans of 839 individuals-299 (467 scans) autistic males, 74 (102 scans) autistic females, 240 (334 scans) control males, and 226 (280 scans) control females-to test two whole-brain models of overall/global sex modulations on autism neuroanatomy, by summary measures computed across the brain: the local magnitude model, in which the same brain regions/circuitries are involved across sexes but effect sizes are larger in females, indicating quantitative sex modulation; and spatial dissimilarity model, in which the neuroanatomy differs spatially between sexes, indicating qualitative sex modulation. The male and female autism groups were matched on age, IQ, and autism symptoms. Autism brain features were defined by comparisons with same-sex control individuals.

RESULTS

Across five metrics (cortical thickness, surface area, volume, mean absolute curvature, and subcortical volume), we found no evidence supporting the local magnitude model. We found indicators supporting the spatial dissimilarity model on cortical mean absolute curvature and subcortical volume, but not on other metrics.

CONCLUSIONS

The overall/global autism neuroanatomy in females and males does not simply differ quantitatively in the same brain regions/circuitries. They may differ qualitatively in spatial involvement in cortical curvature and subcortical volume. The neuroanatomy of autism may be partly sex specific. Sex stratification to inform autism preclinical/clinical research is needed to identify sex-informed neurodevelopmental targets.

Social Cognitive Performance in Schizophrenia Spectrum Disorders Compared With Autism Spectrum Disorder: A Systematic Review, Meta-analysis, and Meta-regression

IMPORTANCE

Schizophrenia spectrum disorders (SSDs) and autism spectrum disorder (ASD) both feature social cognitive deficits; however, these disorders historically have been examined separately using a range of tests and subdomain focus and at different time points in the life span. Moving beyond diagnostic categories and characterizing social cognitive deficits can enhance understanding of shared pathways across these disorders.

OBJECTIVE

To investigate how deficits in social cognitive domains diverge or overlap between SSDs and ASD based on the extant literature.

DATA SOURCES

Literature searches were conducted in MEDLINE, PsycInfo, Embase, and Web of Science from database inception until July 26, 2020.

STUDY SELECTION

Original research articles were selected that reported performance-based measures of social cognition in both SSDs and ASD samples. Selected articles also had to be published in English and use International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, DSM-IV, or more recent diagnostic criteria.

DATA EXTRACTION AND SYNTHESIS

This systematic review and meta-analysis was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-analyses and Meta-analysis of Observational Studies in Epidemiology reporting guidelines, including data extraction and quality assessment using a modified version of the Newcastle-Ottawa Scale. Data were pooled using a random-effects model.

MAIN OUTCOMES AND MEASURES

Effect sizes were calculated as Hedges g (SSDs vs ASD). The primary outcomes were performance on emotion processing tasks, theory of mind (ToM) tasks, and the Reading the Mind in the Eyes Test (RMET) in SSDs compared with ASD. Meta-regressions were performed for age difference, publication year, quality assessment scores, and antipsychotic medication use.

RESULTS

Of the 4175 screened articles, 36 studies directly comparing social cognitive performance in individuals with SSDs vs ASD were included in the qualitative analysis (n = 1212 for SSDs groups and n = 1109 for ASD groups), and 33 studies were included in the quantitative analyses (n = 1113 for SSDs groups and n = 1015 for ASD groups). Most study participants were male (number of studies [k] = 36, 72% [878 of 1212] in SSDs groups and 82% [907 of 1109] in ASD groups), and age (k = 35) was older in SSDs groups (mean [SD], 28.4 [9.5] years) than in ASD groups (mean [SD], 23.3 [7.6] years). Included studies highlighted the prevalence of small, male-predominant samples and a paucity of cross-disorder clinical measures. The meta-analyses revealed no statistically significant differences between SSDs and ASD on emotion processing measures (k = 15; g = 0.12 [95% CI, -0.07 to 0.30]; P = .21; I2 = 51.0%; 1 outlier excluded), ToM measures (k = 17; g = -0.01 [95% CI, -0.21 to 0.19]; P = .92; I2 = 56.5%; 1 outlier excluded), or the RMET (k = 13; g = 0.25 [95% CI, -0.04 to 0.53]; P = .10; I2 = 75.3%). However, SSDs vs ASD performance differences between studies were statistically significantly heterogeneous, which was only minimally explained by potential moderators.

CONCLUSIONS AND RELEVANCE

In this analysis, similar levels of social cognitive impairment were present, on average, in individuals with SSDs and ASD. Cross-disorder studies of social cognition, including larger samples, consensus batteries, and consistent reporting of measures, as well as data across multiple levels of analysis, are needed to help identify subgroups within and across disorders that may be more homogeneous in etiology and treatment response.

Visuomotor Activation of Inhibition-Processing in Pediatric Obsessive Compulsive Disorder: A Magnetoencephalography Study

Background: Response inhibition engages the cortico-striato-thalamo-cortical (CSTC) circuit, which has been implicated in children, and youth with obsessive compulsive disorder (OCD). This study explored whether CSTC engagement during response inhibition, measured using magnetoencephalography (MEG), differed in a sample of medication-naïve youth with OCD, compared to typically developing controls (TDC). Methods: Data was analyzed in 17 medication-naïve children and youth with OCD (11.7 ± 2.2 SD years) and 13 TDC (12.6 ± 2.2 SD years). MEG was used to localize and characterize neural activity during a Go/No-Go task. Task performance on Go/No-Go conditions and regional differences in amplitude of activity during Go and No-Go condition between OCD vs. TDC were examined using two-sample t-tests. Post-hoc analysis with Bayesian t-tests was used to estimate the certainty of outcomes. Results: No differences in Go/No-Go performance were found between OCD and TDC groups. In response to the visual cue presented during the Go condition, participants with OCD showed significantly increased amplitude of activity in the primary motor (MI) cortex compared to TDC. In addition, significantly reduced amplitude of PCu was found following successful stopping to No-Go cues in OCD vs. TDC during No-Go task performance. Bayesian t-tests indicated high probability and large effect sizes for the differences in MI and PCu amplitude found between groups. Conclusion: Our preliminary study in a small medication-naïve sample extends previous work indicating intact response inhibition in pediatric OCD. While altered neural response in the current study was found during response inhibition performance in OCD, differences localized to regions outside of the CSTC. Our findings suggest that additional imaging research in medication-naïve samples is needed to clarify regional differences associated with OCD vs. influenced by medication effects, and suggest that MEG may be sensitive to detecting such differences.

Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

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.

Physical health of autistic girls and women: a scoping review

Background

There is a growing recognition of sex and gender influences in autism. Increasingly, studies include comparisons between sexes or genders, but few have focused on clarifying the characteristics of autistic girls’/women’s physical health.

Methods

A scoping review was conducted to determine what is currently known about the physical health of autistic girls/women. We screened 1112 unique articles, with 40 studies meeting the inclusion criteria. We used a convergent iterative process to synthesize this content into broad thematic areas.

Results

Autistic girls/women experience more overall physical health challenges compared to non-autistic girls/women and to autistic boys/men. Emerging evidence suggests increased prevalence of epilepsy in autistic girls/women compared to non-autistic girls/women and to autistic boys/men. The literature also suggests increased endocrine and reproductive health conditions in autistic girls/women compared to non-autistic girls/women. Findings regarding gastrointestinal, metabolic, nutritional, and immune-related conditions are preliminary and inconsistent.

Limitations

The literature has substantial heterogeneity in how physical health conditions were assessed and reported. Further, our explicit focus on physical health may have constrained the ability to examine interactions between mental and physical health. The widely differing research aims and methodologies make it difficult to reach definitive conclusions. Nevertheless, in keeping with the goals of a scoping review, we were able to identify key themes to guide future research.

Conclusions

The emerging literature suggests that autistic girls/women have heightened rates of physical health challenges compared to non-autistic girls/women and to autistic boys/men. Clinicians should seek to provide holistic care that includes a focus on physical health and develop a women’s health lens when providing clinical care to autistic girls/women.

Structural neuroimaging biomarkers for obsessive-compulsive disorder in the ENIGMA-OCD consortium: medication matters

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.

Sex Differences in Variability of Brain Structure Across the Lifespan

Several brain disorders exhibit sex differences in onset, presentation, and prevalence. Increased understanding of the neurobiology of sex-based differences in variability across the lifespan can provide insight into both disease vulnerability and resilience. In n = 3069 participants, from 8 to 95 years of age, we found widespread greater variability in males compared with females in cortical surface area and global and subcortical volumes for discrete brain regions. In contrast, variance in cortical thickness was similar for males and females. These findings were supported by multivariate analysis accounting for structural covariance, and present and stable across the lifespan. Additionally, we examined variability among brain regions by sex. We found significant age-by-sex interactions across neuroimaging metrics, whereby in very early life males had reduced among-region variability compared with females, while in very late life this was reversed. Overall, our findings of greater regional variability, but less among-region variability in males in early life may aid our understanding of sex-based risk for neurodevelopmental disorders. In contrast, our findings in late life may provide a potential sex-based risk mechanism for dementia.

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. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data.

METHODS

Structural 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).

RESULTS

No 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.

CONCLUSIONS

The 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.

Coping, fostering resilience, and driving care innovation for autistic people and their families during the COVID-19 pandemic and beyond

The new coronavirus disease (COVID-19) pandemic is changing how society operates. Environmental changes, disrupted routines, and reduced access to services and social networks will have a unique impact on autistic individuals and their families and will contribute to significant deterioration in some. Access to support is crucial to address vulnerability factors, guide adjustments in home environments, and apply mitigation strategies to improve coping. The current crisis highlights that our regular care systems are not sufficient to meet the needs of the autism communities. In many parts of the world, people have shifted to online school and increased use of remote delivery of healthcare and autism supports. Access to these services needs to be increased to mitigate the negative impact of COVID-19 and future epidemics/pandemics. The rapid expansion in the use of telehealth platforms can have a positive impact on both care and research. It can help to address key priorities for the autism communities including long waitlists for assessment and care, access to services in remote locations, and restricted hours of service. However, system-level changes are urgently needed to ensure equitable access and flexible care models, especially for families and individuals who are socioeconomically disadvantaged. COVID-19 mandates the use of technology to support a broader range of care options and better meet the diverse needs of autistic people and their families. It behooves us to use this crisis as an opportunity to foster resilience not only for a given individual or their family, but also the system: to drive enduring and autism-friendly changes in healthcare, social systems, and the broader socio-ecological contexts.

Coping, fostering resilience, and driving care innovation for autistic people and their families during the COVID-19 pandemic and beyond

The new coronavirus disease (COVID-19) pandemic is changing how society operates. Environmental changes, disrupted routines, and reduced access to services and social networks will have a unique impact on autistic individuals and their families and will contribute to significant deterioration in some. Access to support is crucial to address vulnerability factors, guide adjustments in home environments, and apply mitigation strategies to improve coping. The current crisis highlights that our regular care systems are not sufficient to meet the needs of the autism communities. In many parts of the world, people have shifted to online school and increased use of remote delivery of healthcare and autism supports. Access to these services needs to be increased to mitigate the negative impact of COVID-19 and future epidemics/pandemics. The rapid expansion in the use of telehealth platforms can have a positive impact on both care and research. It can help to address key priorities for the autism communities including long waitlists for assessment and care, access to services in remote locations, and restricted hours of service. However, system-level changes are urgently needed to ensure equitable access and flexible care models, especially for families and individuals who are socioeconomically disadvantaged. COVID-19 mandates the use of technology to support a broader range of care options and better meet the diverse needs of autistic people and their families. It behooves us to use this crisis as an opportunity to foster resilience not only for a given individual or their family, but also the system: to drive enduring and autism-friendly changes in healthcare, social systems, and the broader socio-ecological contexts.

Neuroimaging Heterogeneity in Psychosis: Neurobiological Underpinnings and Opportunities for Prognostic and Therapeutic Innovation

Heterogeneity in symptom presentation, outcomes, and treatment response has long been problematic for researchers aiming to identify biological markers of schizophrenia or psychosis. However, there is increasing recognition that there may likely be no such general illness markers, which is consistent with the notion of a group of schizophrenia(s) that may have both shared and unique neurobiological pathways. Instead, strategies aiming to capitalize on or leverage such heterogeneity may help uncover neurobiological pathways that may then be used to stratify groups of patients for prognostic purposes or for therapeutic trials. A shift toward larger sample sizes with adequate statistical power to overcome small effect sizes and disentangle the shared variance among different brain-imaging or behavioral variables has become a priority for the field. In addition, recognition that two individuals with the same clinical diagnosis may be more different from each other (at brain, genetic, and behavioral levels) than from another individual in a different disorder or nonclinical control group-coupled with computational advances-has catapulted data-driven efforts forward. Emerging challenges for this new approach include longitudinal stability of new subgroups, demonstration of validity, and replicability. The "litmus test" will be whether computational approaches that are successfully identifying groups of patients who share features in common, more than current DSM diagnostic constructs, also provide better prognostic accuracy over time and in addition lead to enhancements in treatment response and outcomes. These are the factors that matter most to patients, families, providers, and payers.

Mapping Cortical and Subcortical Asymmetry in Obsessive-Compulsive Disorder: Findings From the ENIGMA Consortium

BACKGROUND

Lateralized 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.

METHODS

We 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.

RESULTS

In 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.

CONCLUSIONS

The 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.

Greater Individual Variability in Functional Brain Activity during Working Memory Performance in young people with Autism and Executive Function Impairment

BACKGROUND

Individuals with autism spectrum disorder (ASD) often present with executive functioning (EF) deficits, including spatial working memory (SWM) impairment, which impedes real-world functioning. The present study examined task-related brain activity, connectivity and individual variability in fMRI-measured neural response during an SWM task in older youth and young adults with autism and clinically significant EF impairment.

METHODS

Neuroimaging was analyzed in 29 individuals with ASD without intellectual disability who had clinically significant EF impairment on the Behavior Rating Inventory of Executive Function, and 20 typically developing controls (participant age range=16-34). An SWM N-Back task was performed during fMRI. SWM activity (2-Back vs. 0-Back) and task-related dorsolateral prefrontal cortex (DLPFC) connectivity was examined within and between groups. Variability of neural response during SWM was also examined.

RESULTS

During SWM performance both groups activated the expected networks, and no group differences in network activation or task-related DLPFC-connectivity were found. However, greater individual variability in the pattern of SWM activity was found in the ASD versus the typically developing control group.

CONCLUSIONS

While there were no group differences in SWM task-evoked activity or connectivity, fronto-parietal network engagement was found to be more variable/idiosyncratic in ASD. Our results suggest that the fronto-parietal network may be shifted or sub-optimally engaged during SWM performance in participants with ASD with clinically significant EF impairment, with implications for developing targeted interventions for this subgroup.

In Vivo Imaging of Gray Matter Microstructure in Major Psychiatric Disorders: Opportunities for Clinical Translation

Postmortem studies reveal that individuals with major neuropsychiatric disorders such as schizophrenia and autism spectrum disorder have gray matter microstructural abnormalities. These include abnormalities in neuropil organization, expression of proteins supporting neuritic and synaptic integrity, and myelination. Genetic and postmortem studies suggest that these changes may be causally linked to the pathogenesis of these disorders. Advances in diffusion-weighted magnetic resonance image (dMRI) acquisition techniques and biophysical modeling allow for the quantification of gray matter microstructure in vivo. While several biophysical models for imaging microstructural properties are available, one in particular, neurite orientation dispersion and density imaging (NODDI), holds great promise for clinical applications. NODDI can be applied to both gray and white matter and requires only a single extra shell beyond a standard dMRI acquisition. Since its development only a few years ago, the NODDI algorithm has been used to characterize gray matter microstructure in schizophrenia, Alzheimer's disease, healthy aging, and development. These investigations have shown that microstructural findings in vivo, using NODDI, align with postmortem findings. Not only do NODDI and other advanced dMRI-based modeling methods provide a window into the brain previously only available postmortem, but they may be more sensitive to certain brain changes than conventional magnetic resonance imaging approaches. This opens up exciting new possibilities for clinicians to more rapidly detect disease signatures and allows earlier intervention in the course of the disease. Given that neurites and gray matter microstructure have the capacity to rapidly remodel, these novel dMRI-based methods represent an opportunity to noninvasively monitor neuroplastic changes posttherapy within much shorter time scales.

Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions.

Treatment of Executive Function Deficits in autism spectrum disorder with repetitive transcranial magnetic stimulation: A double-blind, sham-controlled, pilot trial

Background:

In youth and young adults with autism spectrum disorder (ASD), executive function (EF) deficits may be a promising treatment target with potential impact on everyday functioning.

Objective:

To conduct a pilot randomized, double-blind, parallel, controlled trial evaluating repetitive transcranial magnetic stimulation (rTMS) for EF deficits in ASD.

Method:

In Toronto, Ontario (November 2014 to June 2017), a 20-session, 4-week course of 20 Hz rTMS targeting dorsolateral prefrontal cortex (DLPFC) (90%RMT) was compared to sham stimulation in 16—35 year-olds with ASD (28 male/12 female), without intellectual disability, who had impaired everyday EF performance (n = 20 active/n = 20 sham). Outcome measures evaluated protocol feasibility and clinical effects of active vs. sham rTMS on EF performance. The moderating effect of baseline functioning was explored.

Results:

Of eligible participants, 95% were enrolled and 95% of randomized participants completed the protocol. Adverse events across treatment arms were mild-to-moderate. There was no significant difference between active vs. sham rTMS on EF performance. Baseline adaptive functioning moderated the effect of rTMS, such that participants with lower baseline functioning experienced significant EF improvement in the active vs. sham group.

Conclusions:

Our pilot RCT demonstrated the feasibility and acceptability of using high frequency rTMS targeting DLPFC in youth and young adults with autism. No evidence for efficacy of active versus sham rTMS on EF performance was found. However, we found promising preliminary evidence of EF performance improvement following active versus sham rTMS in participants with ASD with more severe adaptive functioning deficits. Future work could focus on examining efficacy of rTMS in this higher-need population.

Clinical trial registration:

Repetitive Transcranial Magnetic Stimulation (rTMS) for Executive Function Deficits in Autism Spectrum Disorder and Effects on Brain Structure: A Pilot Study; https://clinicaltrials.gov/ct2/show/NCT02311751?term=ameis&rank=1; NCT02311751. The trial was funded by: an American Academy of Child and Adolescent Psychiatry (AACAP) Pilot Research Award, the Innovation Fund from the Alternate Funding Plan of the Academic Health Sciences Centres of Ontario, and an Ontario Mental Health Foundation (OMHF) Project A Grant and New Investigator Fellowship.

Tracking Inhibitory Control in Youth With ADHD: A Multi-Modal Neuroimaging Approach

BACKGROUND

A decreased ability to inhibit a speeded motor response is a well-studied deficit in Attention Deficit Hyperactivity Disorder (ADHD), and has been proposed as an endophenotype. Inhibitory control has been assessed reliably with the Stop Signal Task (SST) and is associated with prior documented differences in regional brain function using f-MRI. Here, we advance on these findings by examining their structural connectivity and white matter integrity with the goal of identifying a network underlying a core cognitive deficit in ADHD.

METHODS

Healthy controls (N=16) and youth diagnosed with ADHD (N=60) were recruited through the Province of Ontario Neurodevelopmental Disorders Network (POND) and the Hospital for Sick Children. An f-MRI activation difference map was co-registered with each participant's white matter imaging data, representing the specific network nodes where ADHD youth diverged significantly from controls while performing the SST. Probabilistic tractography was applied from these nodes, and white matter integrity indices such as fractional anisotropy (FA) within the tracts of interest were contrasted between the groups and correlated with SST output measures, including the measure of inhibitory control, the stop signal reaction time (SSRT).

RESULTS

The tracts that connected the network nodes belonged primarily to the inferior fronto-occipital fasciculus (IFOF) and cingulum. ADHD subjects showed trend differences in FA compared to controls between right inferior frontal gyrus (IFG) and right superior temporal gyrus (P= 0.09), right IFG and right posterior cingulate (P= 0.01), right anterior cingulate to posterior cingulate (p= 0.08), and between left middle temporal gyrus (BA 39) and left posterior cingulate (P=0.02). A trend correlation was found between radial diffusivity within IFG to STG white matter (IFOF) and SSRT.

CONCLUSIONS

We identified potential white matter tracts related to deficient inhibitory control, elucidating the brain mechanisms of an important cognitive deficit in ADHD. These findings could be integrated into future endophenotypic biomarker studies, incorporating altogether brain structure, function, and behavior for future studies of ADHD and other psychiatric conditions that exhibit this deficit.

Prevalence of co-occurring mental health diagnoses in the autism population: a systematic review and meta-analysis

BACKGROUND

Co-occurring mental health or psychiatric conditions are common in autism, impairing quality of life. Reported prevalences of co-occurring mental health or psychiatric conditions in people with autism range widely. Improved prevalence estimates and identification of moderators are needed to enhance recognition and care, and to guide future research.

METHODS

In this systematic review and meta-analysis, we searched MEDLINE, Embase, PsycINFO, Scopus, Web of Science, and grey literature for publications between Jan 1, 1993, and Feb 1, 2019, in English or French, that reported original research using an observational design on the prevalence of co-occurring mental health conditions in people with autism and reported confirmed clinical diagnoses of the co-occurring conditions and autism using DSM or ICD criteria. For co-occurring mental health conditions reported with at least 15 datapoints (studies), we assessed risk of bias and we determined pooled estimates of prevalence for different co-occurring conditions in autism using random-effects models, and descriptively compared these with prevalence estimates for the general population from the literature (post hoc). We investigated heterogeneity in prevalence estimates using random-effects meta-regression models. This systematic review is registered with PROSPERO, CRD42018103176.

FINDINGS

Of 9746 unique studies identified, 432 were selected for full-text review. 100 studies were eligible for inclusion in our qualitative synthesis, of which 96 were included in our meta-analyses. 11 categories of co-occurring conditions were investigated, of which eight conditions were included in the meta-analyses and three were descriptively synthesised (ie, trauma and stressor-related disorders, substance-related and addictive disorders, and gender dysphoria). From our meta-analyses, we found overall pooled prevalence estimates of 28% (95% CI 25-32) for attention-deficit hyperactivity disorder; 20% (17-23) for anxiety disorders; 13% (9-17) for sleep-wake disorders; 12% (10-15) for disruptive, impulse-control, and conduct disorders; 11% (9-13) for depressive disorders; 9% (7-10) for obsessive-compulsive disorder; 5% (3-6) for bipolar disorders; and 4% (3-5) for schizophrenia spectrum disorders. Estimates in clinical sample-based studies were higher than in population-based and registry-based studies, and these estimates were mostly higher than those in the general population (post hoc). Age, gender, intellectual functioning, and country of study were associated with heterogeneity in prevalence estimates, yet remaining heterogeneity not explained was still substantial (all I² >95%).

INTERPRETATION

Co-occurring mental health conditions are more prevalent in the autism population than in the general population. Careful assessment of mental health is an essential component of care for all people on the autism spectrum and should be integrated into clinical practice.

FUNDING

Academic Scholars Awards, Department of Psychiatry, University of Toronto; O'Brien Scholars Program, Slaight Family Child and Youth Mental Health Innovation Fund, and The Catherine and Maxwell Meighen Foundation via the Centre for Addiction and Mental Health Foundation.

BDNF-Dependent Effects on Amygdala-Cortical Circuitry and Depression Risk in Children and Youth

The brain-derived neurotrophic factor (BDNF) is critical for brain development, and the functional BDNF Val66Met polymorphism is implicated in risk for mood disorders. The objective of this study was to determine how the Val66Met polymorphism influences amygdala-cortical connectivity during neurodevelopment and assess the relevance for mood disorders. Age- and sex-specific effects of the BDNF Val66Met polymorphism on amygdala-cortical connectivity were assessed by examining covariance of amygdala volumes with thickness throughout the cortex in a sample of Caucasian youths ages 8-22 that were part of the Philadelphia Neurodevelopmental Cohort (n = 339). Follow-up analyses assessed corresponding BDNF genotype effects on resting-state functional connectivity (n = 186) and the association between BDNF genotype and major depressive disorder (MDD) (n = 2749). In adolescents, amygdala-cortical covariance was significantly stronger in Met allele carriers compared with Val/Val homozygotes in amygdala-cortical networks implicated in depression; these differences were driven by females. In follow-up analyses, the Met allele was also associated with stronger resting-state functional connectivity in adolescents and increased likelihood of MDD in adolescent females. The BDNF Val66Met polymorphism may confer risk for mood disorders in females through effects on amygdala-cortical connectivity during adolescence, coinciding with a period in the lifespan when onset of depression often occurs, more commonly in females.

Developmentally divergent sexual dimorphism in the cortico-striatal-thalamic-cortical psychosis risk pathway

Structural and functional cortico-striatal-thalamic-cortical (CSTC) circuit abnormalities have been observed in schizophrenia and the clinical high-risk state. However, this circuit is sexually dimorphic and changes across neurodevelopment. We examined effects of sex and age on structural and functional properties of the CSTC circuit in a large sample of youth with and without psychosis spectrum symptoms (PSS) from the Philadelphia Neurodevelopmental Cohort. T1-weighted and resting-state functional MRI scans were collected on a 3T Siemens scanner, in addition to participants' cognitive and psychopathology data. After quality control, the total sample (aged 11-21) was n = 1095 (males = 485, females = 610). Structural subdivisions of the striatum and thalamus were identified using the MAGeT Brain segmentation tool. Functional seeds were segmented based on brain network connectivity. Interaction effects among PSS group, sex, and age on striatum, thalamus, and subdivision volumes were examined. A similar model was used to test effects on functional connectivity of the CSTC circuit. A sex by PSS group interaction was identified, whereby PSS males had higher volumes and PSS females had lower volumes in striatal and thalamic subdivisions. Reduced functional striato-cortical connectivity was found in PSS youth, primarily driven by males, whereby younger male PSS youth also exhibited thalamo-cortical hypo-connectivity (compared to non-PSS youth), vs. striato-cortical hyper-connectivity in older male PSS youth (compared to non-PSS youth). Youth with PSS demonstrate sex and age-dependent differences in striatal and thalamic subdivision structure and functional connectivity. Further efforts at biomarker discovery and early therapeutic intervention targeting the CSTC circuit in psychosis should consider effects of sex and age.

An Empirical Comparison of Meta- and Mega-Analysis With Data From the ENIGMA Obsessive-Compulsive Disorder Working Group

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.