Genome-wide detection of tandem DNA repeats that are expanded in autism.

Tandem DNA repeats vary in the size and sequence of each unit (motif). When expanded, these tandem DNA repeats have been associated with more than 40 monogenic disorders1. Their involvement in disorders with complex genetics is largely unknown, as is the extent of their heterogeneity. Here we investigated the genome-wide characteristics of tandem repeats that had motifs with a length of 2-20 base pairs in 17,231 genomes of families containing individuals with autism spectrum disorder (ASD)2,3 and population control individuals4. We found extensive polymorphism in the size and sequence of motifs. Many of the tandem repeat loci that we detected correlated with cytogenetic fragile sites. At 2,588 loci, gene-associated expansions of tandem repeats that were rare among population control individuals were significantly more prevalent among individuals with ASD than their siblings without ASD, particularly in exons and near splice junctions, and in genes related to the development of the nervous system and cardiovascular system or muscle. Rare tandem repeat expansions had a prevalence of 23.3% in children with ASD compared with 20.7% in children without ASD, which suggests that tandem repeat expansions make a collective contribution to the risk of ASD of 2.6%. These rare tandem repeat expansions included previously undescribed ASD-linked expansions in DMPK and FXN, which are associated with neuromuscular conditions, and in previously unknown loci such as FGF14 and CACNB1. Rare tandem repeat expansions were associated with lower IQ and adaptive ability. Our results show that tandem DNA repeat expansions contribute strongly to the genetic aetiology and phenotypic complexity of ASD.

Identifying novel data-driven subgroups in congenital heart disease using multi-modal measures of brain structure.

Individuals with congenital heart disease (CHD) have an increased risk of neurodevelopmental impairments. Given the hypothesized complexity linking genomics, atypical brain structure, cardiac diagnoses and their management, and neurodevelopmental outcomes, unsupervised methods may provide unique insight into neurodevelopmental variability in CHD. Using data from the Pediatric Cardiac Genomics Consortium Brain and Genes study, we identified data-driven subgroups of individuals with CHD from measures of brain structure. Using structural magnetic resonance imaging (MRI; N = 93; cortical thickness, cortical volume, and subcortical volume), we identified subgroups that differed primarily on cardiac anatomic lesion and language ability. In contrast, using diffusion MRI (N = 88; white matter connectivity strength), we identified subgroups that were characterized by differences in associations with rare genetic variants and visual-motor function. This work provides insight into the differential impacts of cardiac lesions and genomic variation on brain growth and architecture in patients with CHD, with potentially distinct effects on neurodevelopmental outcomes.

Dataset factors associated with age-related changes in brain structure and function in neurodevelopmental conditions.

With brain structure and function undergoing complex changes throughout childhood and adolescence, age is a critical consideration in neuroimaging studies, particularly for those of individuals with neurodevelopmental conditions. However, despite the increasing use of large, consortium-based datasets to examine brain structure and function in neurotypical and neurodivergent populations, it is unclear whether age-related changes are consistent between datasets and whether inconsistencies related to differences in sample characteristics, such as demographics and phenotypic features, exist. To address this, we built models of age-related changes of brain structure (regional cortical thickness and regional surface area; N = 1218) and function (resting-state functional connectivity strength; N = 1254) in two neurodiverse datasets: the Province of Ontario Neurodevelopmental Network and the Healthy Brain Network. We examined whether deviations from these models differed between the datasets, and explored whether these deviations were associated with demographic and clinical variables. We found significant differences between the two datasets for measures of cortical surface area and functional connectivity strength throughout the brain. For regional measures of cortical surface area, the patterns of differences were associated with race/ethnicity, while for functional connectivity strength, positive associations were observed with head motion. Our findings highlight that patterns of age-related changes in the brain may be influenced by demographic and phenotypic characteristics, and thus future studies should consider these when examining or controlling for age effects in analyses.

Gender diversity is correlated with dimensional neurodivergent traits but not categorical neurodevelopmental diagnoses in children.

BACKGROUND: Gender clinic and single-item questionnaire-based data report increased co-occurrence of gender diversity and neurodevelopmental conditions. The nuances of these associations are under-studied. We used a transdiagnostic approach, combining categorical and dimensional characterization of neurodiversity, to further the understanding of its associations with gender diversity in identity and expression in children. METHODS: Data from 291 children (Autism N = 104, ADHD N = 104, Autism + ADHD N = 17, neurotypical N = 66) aged 4-12 years enrolled in the Province of Ontario Neurodevelopmental Network were analyzed. Gender diversity was measured multi-dimensionally using a well-validated parent-report instrument, the Gender Identity Questionnaire for Children (GIQC). We used gamma regression models to determine the significant correlates of gender diversity among age, puberty, sex-assigned-at-birth, categorical neurodevelopmental diagnoses, and dimensional neurodivergent traits (using the Social Communication Questionnaire and the Strengths and Weaknesses of ADHD Symptoms and Normal Behavior Rating Scales). Internalizing and externalizing problems were included as covariates. RESULTS: Neither a categorical diagnosis of autism nor ADHD significantly correlated with current GIQC-derived scores. Instead, higher early-childhood dimensional autistic social-communication traits correlated with higher current overall gender incongruence (as defined by GIQC-14 score). This correlation was potentially moderated by sex-assigned-at-birth: greater early-childhood autistic social-communication traits were associated with higher current overall gender incongruence in assigned-males-at-birth, but not assigned-females-at-birth. For fine-grained gender diversity domains, greater autistic restricted-repetitive behavior traits were associated with greater diversity in gender identity across sexes-assigned-at-birth; greater autistic social-communication traits were associated with lower stereotypical male expression across sexes-assigned-at-birth. CONCLUSIONS: Dimensional autistic traits, rather than ADHD traits or categorical neurodevelopmental diagnoses, were associated with gender diversity domains across neurodivergent and neurotypical children. The association between early-childhood autistic social-communication traits and overall current gender diversity was most evident in assigned-males-at-birth. Nuanced interrelationships between neurodivergence and gender diversity should be better understood to clarify developmental links and to offer tailored support for neurodivergent and gender-diverse populations.

The Phenotypic variability of 16p11.2 distal BP2-BP3 deletion in a transgenerational family and in neurodevelopmentally ascertained samples.

BACKGROUND: We present genomic and phenotypic findings of a transgenerational family consisting of three male offspring, each with a maternally inherited distal 220 kb deletion at locus 16p11.2 (BP2-BP3). Genomic analysis of all family members was prompted by a diagnosis of autism spectrum disorder (ASD) in the eldest child, who also presented with a low body mass index. METHODS: All male offspring underwent extensive neuropsychiatric evaluation. Both parents were also assessed for social functioning and cognition. The family underwent whole-genome sequencing. Further data curation was undertaken from samples ascertained for neurodevelopmental disorders and congenital abnormalities. RESULTS: On medical examination, both the second and third-born male offspring presented with obesity. The second-born male offspring met research diagnostic criteria for ASD at 8 years of age and presented with mild attention deficits. The third-born male offspring was only noted as having motor deficits and received a diagnosis of developmental coordination disorder. Other than the 16p11.2 distal deletion, no additional contributing variants of clinical significance were observed. The mother was clinically evaluated and noted as having a broader autism phenotype. CONCLUSION: In this family, the phenotypes observed are most likely caused by the 16p11.2 distal deletion. The lack of other overt pathogenic mutations identified by genomic sequencing reinforces the variable expressivity that should be heeded in a clinical setting. Importantly, distal 16p11.2 deletions can present with a highly variable phenotype even within a single family. Our additional data curation provides further evidence on the variable clinical presentation among those with pathogenetic 16p11.2 (BP2-BP3) mutations.

Predictors of Depressive Symptoms in Autistic Youth-A Longitudinal Study From the Province of Ontario Neurodevelopmental Disorders (POND) Network: Prédicteurs des symptômes dépressifs chez les jeunes autistes-une étude longitudinale du Réseau des troubles neurodéveloppementaux de la province de l'Ontario (réseau POND).

OBJECTIVE: The objective of this study was to identify longitudinal predictors of depressive symptoms in autistic children and youth. METHODS: Participants were youth with a diagnosis of autism who were part of the Province of Ontario Neurodevelopmental Disorders Network longitudinal substudy. Depressive symptoms were assessed using the child behaviour checklist (CBCL) affective problems subscale. Univariate and multivariable logistic regression models were used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between clinical and demographic characteristics at baseline (T1) and clinically elevated depressive symptoms (CEDS) approximately 4 years later (T2). RESULTS: The mean age of participants (n = 75) at T1 was 9.8 years (SD = 2.7) and at T2 was 14.1 years (SD = 2.8). A total of 37% and 35% of participants had CEDS at T1 and T2, respectively. Additionally, 24% of participants had CEDS at both T1 and T2. T1 characteristics associated with T2 CEDS were: loneliness (OR = 3.0, 95% CI, 1.1 to 8.8), self-harm (OR = 4.0, 95% CI, 1.1 to 16.9), suicidal ideation (OR = 3.9, 95% CI, 1.0 to 16.5), more social and adaptive skills (OR = 0.3, 95% CI, 0.1 to 0.9), elevated restricted and repetitive behaviours (OR = 3.8, 95% CI, 1.3 to 11.6), psychotropic medication use (OR = 3.0, 95% CI, 1.1 to 8.4), attention-deficient/hyperactivity disorder (OR = 2.8, 95% CI, 1.1 to 7.8), and T1 CEDS (OR = 8.8, 95% CI, 3.1 to 27.0) (uncorrected for multiple comparisons). Associations persisted after adjusting for age and intelligence quotient (IQ) differences. Age, sex, IQ, teasing/bullying on the CBCL, family psychiatric history and family income were not associated with T2 CEDS. CONCLUSION: Our results highlight both high prevalence and high potential for the persistence of depressive symptoms in autism and emphasize the importance of early support to address loneliness and social participation.

Study assessing risk factors for depression in autistic youthPlain Language SummaryObjectiveThe goal of this study was to find risk factors for depression in autistic youth.MethodsThe study included autistic youth who were part of the Province of Ontario Neurodevelopmental Disorders Network. Symptoms of depression were identified using mental health surveys and screening tools completed by parents. We studied 75 youth over two time points, to understand what factors might predict greater depression risk.ResultsThe average age of our study population at the first visit was 10 years old, and 14 years old at the second visit. Our study found that 37% of participants had elevated symptoms of depression at the first visit, and 35% at the second visit. Factors associated with future depressive symptoms included: loneliness, self-harm, suicidal ideation, high levels of restrictive/repetitive behaviours, depressive symptoms at the first visit, and ADHD. Factors that protected against depressive symptoms included high levels of social skills.ConclusionOur results show high levels of depressive symptoms among autistic youth, and the potential for this to persist over time in this population. Our findings emphasize the importance of early supports to address loneliness and social participation.

Sex and intelligence quotient differences in age of diagnosis among youth with attention-deficit hyperactivity disorder.

OBJECTIVES: Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental condition and is characterized by inattention, hyperactivity, and impulsivity. Research suggests that some populations, such as females and individuals with high intelligence quotients may be a risk for late ADHD diagnosis and subsequent treatment. Our goal is to advance our understanding of ADHD diagnosis, by examining (1) how child sex and cognitive abilities together are related to the age of diagnosis and (2) whether symptom presentation, current internalizing and externalizing symptoms, and demographic factors are related to age of diagnosis. METHODS: Our analyses contained children who completed the required tests (N = 568) from a pre-existing dataset of 1380 children with ADHD from the Province of Ontario Neurodevelopmental Disorders (POND) Network (pond-network.ca). First, we conducted a moderation analysis with sex as the predictor, cognitive abilities as the moderator, and age of diagnosis as the outcome. Second, we conducted correlation analyses examining how symptom presentation, current internalizing and externalizing symptoms, and demographic factors are related to age of diagnosis. RESULTS: Higher IQ was related to a later age of diagnosis. Higher hyperactive-impulsive symptoms and externalizing symptoms were related to an earlier age of diagnosis. Internalizing symptoms were trend associated with a later age of diagnosis in girls. Higher socioeconomic status and non-White maternal ethnicity were related to later age of diagnosis. CONCLUSIONS: IQ, sex, ADHD symptomology, internalizing symptoms, externalizing symptoms, and socio-demographic factors affect the age of diagnosis.

Systematic comparisons of different quality control approaches applied to three large pediatric neuroimaging datasets.

INTRODUCTION: Poor quality T1-weighted brain scans systematically affect the calculation of brain measures. Removing the influence of such scans requires identifying and excluding scans with noise and artefacts through a quality control (QC) procedure. While QC is critical for brain imaging analyses, it is not yet clear whether different QC approaches lead to the exclusion of the same participants. Further, the removal of poor-quality scans may unintentionally introduce a sampling bias by excluding the subset of participants who are younger and/or feature greater clinical impairment. This study had two aims: (1) examine whether different QC approaches applied to T1-weighted scans would exclude the same participants, and (2) examine how exclusion of poor-quality scans impacts specific demographic, clinical and brain measure characteristics between excluded and included participants in three large pediatric neuroimaging samples. METHODS: We used T1-weighted, resting-state fMRI, demographic and clinical data from the Province of Ontario Neurodevelopmental Disorders network (Aim 1: n = 553, Aim 2: n = 465), the Healthy Brain Network (Aim 1: n = 1051, Aim 2: n = 558), and the Philadelphia Neurodevelopmental Cohort (Aim 1: n = 1087; Aim 2: n = 619). Four different QC approaches were applied to T1-weighted MRI (visual QC, metric QC, automated QC, fMRI-derived QC). We used tetrachoric correlation and inter-rater reliability analyses to examine whether different QC approaches excluded the same participants. We examined differences in age, mental health symptoms, everyday/adaptive functioning, IQ and structural MRI-derived brain indices between participants that were included versus excluded following each QC approach. RESULTS: Dataset-specific findings revealed mixed results with respect to overlap of QC exclusion. However, in POND and HBN, we found a moderate level of overlap between visual and automated QC approaches (rtet=0.52-0.59). Implementation of QC excluded younger participants, and tended to exclude those with lower IQ, and lower everyday/adaptive functioning scores across several approaches in a dataset-specific manner. Across nearly all datasets and QC approaches examined, excluded participants had lower estimates of cortical thickness and subcortical volume, but this effect did not differ by QC approach. CONCLUSION: The results of this study provide insight into the influence of QC decisions on structural pediatric imaging analyses. While different QC approaches exclude different subsets of participants, the variation of influence of different QC approaches on clinical and brain metrics is minimal in large datasets. Overall, implementation of QC tends to exclude participants who are younger, and those who have more cognitive and functional impairment. Given that automated QC is standardized and can reduce between-study differences, the results of this study support the potential to use automated QC for large pediatric neuroimaging datasets.

Mutations in trpγ, the homologue of TRPC6 autism candidate gene, causes autism-like behavioral deficits in Drosophila.

Autism Spectrum Disorder (ASD) is characterized by impaired social communication, restricted interests, and repetitive and stereotyped behaviors. The TRPC6 (transient receptor potential channel 6) represents an ASD candidate gene under an oligogenic/multifactorial model based on the initial description and cellular characterization of an individual with ASD bearing a de novo heterozygous mutation disrupting TRPC6, together with the enrichment of disruptive TRPC6 variants in ASD cases as compared to controls. Here, we perform a clinical re-evaluation of the initial non-verbal patient, and also present eight newly reported individuals ascertained for ASD and bearing predicted loss-of-function mutations in TRPC6. In order to understand the consequences of mutations in TRPC6 on nervous system function, we used the fruit fly, Drosophila melanogaster, to show that null mutations in transient receptor gamma (trpγ; the fly gene most similar to TRPC6), cause a number of behavioral defects that mirror features seen in ASD patients, including deficits in social interactions (based on courtship behavior), impaired sleep homeostasis (without affecting the circadian control of sleep), hyperactivity in both young and old flies, and defects in learning and memory. Some defects, most notably in sleep, differed in severity between males and females and became normal with age. Interestingly, hyperforin, a TRPC6 agonist and the primary active component of the St. John's wort antidepressant, attenuated many of the deficits expressed by trpγ mutant flies. In summary, our results provide further evidence that the TRPC6 gene is a risk factor for ASD. In addition, they show that the behavioral defects caused by mutations in TRPC6 can be modeled in Drosophila, thereby establishing a paradigm to examine the impact of mutations in other candidate genes.

Subtly altered topological asymmetry of brain structural covariance networks in autism spectrum disorder across 43 datasets from the ENIGMA consortium.

Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls, affecting widespread cortical regions. The possible impacts of these regional alterations in terms of structural network effects have not previously been characterized. Inter-regional morphological covariance analysis can capture network connectivity between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1455 individuals with ASD and 1560 controls, across 43 independent datasets of the ENIGMA consortium's ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered average asymmetry of networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, involving higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve executive functions, language-related and sensorimotor processes. These findings provide a network-level characterization of altered left-right brain asymmetry in ASD, based on a large combined sample. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.

Cortical Gyrification Morphology in ASD and ADHD: Implication for Further Similarities or Disorder-Specific Features?

Shared etiological pathways are suggested in ASD and ADHD given high rates of comorbidity, phenotypic overlap and shared genetic susceptibility. Given the peak of cortical gyrification expansion and emergence of ASD and ADHD symptomology in early development, we investigated gyrification morphology in 539 children and adolescents (6-17 years of age) with ASD (n=197) and ADHD (n=96) compared to typically developing controls (n=246) using the local Gyrification Index (lGI) to provide insight into contributing etiopathological factors in these two disorders. We also examined IQ effects and functional implications of gyrification by exploring the relation between lGI and ASD and ADHD symptomatology beyond diagnosis. General Linear Models yielded no group differences in lGI, and across groups, we identified an age-related decrease of lGI and greater lGI in females compared to males. No diagnosis-by-age interactions were found. Accounting for IQ variability in the model (n=484) yielded similar results. No significant associations were found between lGI and social communication deficits, repetitive and restricted behaviours, inattention or adaptive functioning. By examining both disorders and controls using shared methodology, we found no evidence of atypicality in gyrification as measured by the lGI in these conditions.

Stepping up to COVID-19: A Clinical Trial of a Telepsychology Positive Parenting Program Targeting Behavior Problems in Children With Neurological Risk.

OBJECTIVE: To evaluate the feasibility, acceptability, and preliminary efficacy of a stepped-care parenting program implemented during COVID-19 among families of behaviorally at-risk children with neurological or neurodevelopmental disorders aged 3-9 years. METHODS: Stepped-care I-InTERACT-North increased psychological support across 3 steps, matched to family needs: (1) guided self-help (podcast), (2) brief support, and (3) longer-term parent support. The intervention was provided by clinicians at The Hospital for Sick Children. Recruitment occurred via hospital and research cohort referral. A single-arm trial using a pragmatic prospective pre-post mixed-method design was utilized to assess accrual, engagement, acceptability, and preliminary efficacy. RESULTS: Over 15 months, 68 families enrolled (83% consent rate) and 56 families completed stepped-care (Step 1 = 56; Step 2 = 39; Step 3 = 28), with high adherence across Steps (100%, 98%, and 93%, respectively). Parents reported high acceptability, reflected in themes surrounding accessibility, comprehension, effectiveness, and targeted care. Positive parenting skill increases were documented, and robust improvement in child behavior problems was apparent upon Step 3 completion (p =.001, d = .390). Stepped-care was as effective as traditional delivery, while improving consent and completion rates within a pandemic context. CONCLUSIONS: This stepped-care telepsychology parenting program provides a compelling intervention model to address significant gaps in accessible mental health intervention while simultaneously balancing the need for efficient service. Findings inform program scalability beyond COVID-19 and emphasize the value of stepped-care intervention in delivering and monitoring mental health treatment.

The Distinction Between Social Connectedness and Support When Examining Depressive Symptoms Among Children and Adolescents During the COVID-19 Pandemic.

Childhood depression is associated with significant social and functional impairment, suicide risk, and persistence throughout adulthood. Recent evidence demonstrates that social connectedness and social support may serve as protective factors against the development of depression. The current study aimed to examine the effect of change in social connectedness and social support on depressive symptoms among children and adolescents during the COVID-19 pandemic. Hierarchical regression was performed. Results indicated that parent-reported measures of change in social connectedness were inversely associated with depressive symptom severity, and could significantly predict future depressive symptom severity. In contrast, parent-reported measures of social support (i.e., from family and friends) did not significantly predict future depressive symptom severity. The presence of a pre-COVID psychiatric and/or neurodevelopmental diagnosis and baseline depressive symptom severity were also important factors associated with future depressive symptom severity. The findings suggest that an awareness of the presence of social supports (i.e., family or friends) is not sufficient for children to feel connected, but rather the mechanisms of social relationships are crucial. As our approach to public health restrictions evolves, the risk transmission of COVID-19 should be carefully balanced with the risks associated with decreased connectedness among youth.

Examining the effect of chronic intranasal oxytocin administration on the neuroanatomy and behavior of three autism-related mouse models.

Although initially showing great potential, oxytocin treatment has encountered a translational hurdle in its promise of treating the social deficits of autism. Some debate surrounds the ability of oxytocin to successfully enter the brain, and therefore modify neuroanatomy. Moreover, given the heterogeneous nature of autism, treatment will only amerliorate symptoms in a subset of patients. Therefore, to determine whether oxytocin changes brain circuitry, and whether it does so variably, depending on genotype, we implemented a large randomized, blinded, placebo-controlled, preclinical study on chronic intranasal oxytocin treatment in three different mouse models related to autism with a focus on using neuroanatomical phenotypes to assess and subset treatment response. Intranasal oxytocin (0.6IU) was administered daily, for 28 days, starting at 5 weeks of age to the 16p11.2 deletion, Shank3 (exon 4-9) knockout, and Fmr1 knockout mouse models. Given the sensitivity of structural magnetic resonance imaging (MRI) to the neurological effects of interventions like drugs, along with many other advantages, the mice underwent in vivo longitudinal and high-resolution ex vivo imaging with MRI. The scans included three in vivo T1weighted, 90 um isotropic resolution scans and a T2-weighted, 3D fast spin echo with 40um isotropic resolution ex vivo scan to assess the changes in neuroanatomy using established automated image registration and deformation based morphometry approaches in response to oxytocin treatment. The behavior of the mice was assessed in multiple domains, including social behaviours and repetitive behaviours, among others. Treatment effect on the neuroanatomy did not reach significance, although the pattern of trending effects was promising. No significant effect of treatment was found on social behavior in any of the strains, although a significant effect of treatment was found in the Fmr1 mouse, with treatment normalizing a grooming deficit. No other treatment effect on behavior was observed that survived multiple comparisons correction. Overall, chronic treatment with oxytocin had limited effects on the three mouse models related to autism, and no promising pattern of response susceptibility emerged.

Amygdala subnuclei volumes and anxiety behaviors in children and adolescents with autism spectrum disorder, attention deficit hyperactivity disorder, and obsessive-compulsive disorder.

Alterations in the structural maturation of the amygdala subnuclei volumes are associated with anxiety behaviors in adults and children with neurodevelopmental and associated disorders. This study investigated the relationship between amygdala subnuclei volumes and anxiety in 233 children and adolescents (mean age = 11.02 years; standard deviation = 3.17) with autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), and children with obsessive compulsive disorder (OCD), as well as typically developing (TD) children. Parents completed the Child Behavior Checklist (CBCL), and the children underwent structural MRI at 3 T. FreeSurfer software was used to automatically segment the amygdala subnuclei. A general linear model revealed that children and adolescents with ASD, ADHD, and OCD had higher anxiety scores compared to TD children (p < .001). A subsequent interaction analysis revealed that children with ASD (B = 0.09, p < .0001) and children with OCD (B = 0.1, p < .0001) who had high anxiety had larger right central nuclei volumes compared with TD children. Similar results were obtained for the right anterior amygdaloid area. Amygdala subnuclei volumes may be key to identifying children with neurodevelopmental disorders or those with OCD who are at high risk for anxiety. Findings may inform the development of targeted behavioral interventions to address anxiety behaviors and to assess the downstream effects of such interventions.

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

Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses.

Obsessive-compulsive disorder in children and youth: neurocognitive function in clinic and community samples.

BACKGROUND: Neurocognitive impairments are common in OCD, although not well studied in children and youth with the disorder. METHOD: Using the stop-signal task (SST), we measured response inhibition (stop-signal reaction time-SSRT), sustained attention (reaction time variability-RTV), reaction time (RT), and performance monitoring (post-error slowing-PES) in OCD cases and controls from two samples of children and youth. A Clinic OCD group (n = 171, aged 7-17 years) was recruited from a specialty clinic after rigorous assessment. A typically developing (Clinic TD, n = 157) group was enlisted through advertisement. A community OCD sample (Community OCD, n = 147) and controls (Community TD n = 13,832, aged 6-17 years) were recruited at a science museum. We also identified a community group with high OCD traits without an OCD diagnosis (Community High Trait; n = 125). RESULTS: Clinic OCD participants had longer SSRT and greater RTV than Clinic TD. These effects were greater in younger OCD participants and, for SSRT, in those on medication for OCD. The Community OCD group did not differ from Controls but was similar to the Clinic OCD group in ADHD and ASD comorbidity and medication usage. The Community High Trait group had longer SSRT and atypical PES suggesting that symptom severity predicts neurocognitive function. No group differences were found in RT. CONCLUSIONS: In the largest study of neurocognitive performance in children with OCD to date, we found impaired response inhibition and sustained attention in OCD participants in comparison to typically developing peers. Performance was worse in younger OCD participants. In the community sample, participants with high OCD trait scores but no OCD diagnosis had impaired response inhibition and error processing, suggesting that OCD might be under-recognized.

Characterizing the ASD-ADHD phenotype: measurement structure and invariance in a clinical sample.

BACKGROUND: Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) have considerable overlap, supporting the need for a dimensional framework that examines neurodevelopmental domains which cross traditional diagnostic boundaries. In the following study, we use factor analysis to deconstruct the ASD-ADHD phenotype into its underlying phenotypic domains and test for measurement invariance across adaptive functioning, age, gender and ASD/ADHD clinical diagnoses. METHODS: Participants included children and youth (aged 3-20 years) with a clinical diagnosis of ASD (n = 727) or ADHD (n = 770) for a total of 1,497 participants. Parents of these children completed the Social Communication Questionnaire (SCQ), a measure of autism symptoms, and the Strengths and Weaknesses of ADHD and Normal Behaviour (SWAN) questionnaire, a measure of ADHD symptoms. An exploratory factor analysis (EFA) was performed on combined SCQ and SWAN items. This was followed by a confirmatory factor analysis (CFA) and tests of measurement invariance. RESULTS: EFA revealed a four-factor solution (inattention, hyperactivity/impulsivity, social-communication, and restricted, repetitive, behaviours and interests (RRBI)) and a CFA confirmed good model fit. This solution also showed good model fit across subgroups of interest. CONCLUSIONS: Our study shows that a combined ASD-ADHD phenotype is characterized by two latent ASD domains (social communication and RRBIs) and two latent ADHD domains (inattention and hyperactivity/impulsivity). We established measurement invariance of the derived measurement model across adaptive functioning, age, gender and ASD/ADHD diagnoses.

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.

Cross-Diagnosis Structural Correlates of Autistic-Like Social Communication Differences.

Social communication differences are seen in autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and obsessive-compulsive disorder (OCD), but the brain mechanisms contributing to these differences remain largely unknown. To address this gap, we used a data-driven and diagnosis-agnostic approach to discover brain correlates of social communication differences in ASD, ADHD, and OCD, and subgroups of individuals who share similar patterns of brain-behavior associations. A machine learning pipeline (regression clustering) was used to discover the pattern of association between structural brain measures (volume, surface area, and cortical thickness) and social communication abilities. Participants (n = 416) included children with a diagnosis of ASD (n = 192, age = 12.0[5.6], 19% female), ADHD (n = 109, age = 11.1[4.1], 18% female), or OCD (n = 50, age = 12.3[4.2], 42% female), and typically developing controls (n = 65, age = 11.6[7.1], 48% female). The analyses revealed (1) associations with social communication abilities in distributed cortical and subcortical networks implicated in social behaviors, language, attention, memory, and executive functions, and (2) three data-driven, diagnosis-agnostic subgroups based on the patterns of association in the above networks. Our results suggest that different brain networks may contribute to social communication differences in subgroups that are not diagnosis-specific.