Explore the vast range of titles available.

This large cross-sectional study examined the impact of COVID-19 emergency measures on child/adolescent mental health for children/adolescents with and without pre-existing psychiatric diagnoses. Using adapted measures from the CRISIS questionnaire, parents of children aged 6–18 (N = 1013; 56% male; 62% pre-existing psychiatric diagnosis) and self-reporting children/adolescents aged 10–18 (N = 385) indicated changes in mental health across six domains: depression, anxiety, irritability, attention, hyperactivity, and obsessions/compulsions. Changes in anxiety, irritability, and hyperactivity were calculated for children aged 2–5 years using the Strengths and Difficulties Questionnaire. COVID-19 exposure, compliance with emergency measures, COVID-19 economic concerns, and stress from social isolation were measured with the CRISIS questionnaire. Prevalence of change in mental health status was estimated for each domain; multinomial logistic regression was used to determine variables associated with mental health status change in each domain. Depending on the age group, 67–70% of children/adolescents experienced deterioration in at least one mental health domain; however, 19–31% of children/adolescents experienced improvement in at least one domain. Children/adolescents without and with psychiatric diagnoses tended to experience deterioration during the first wave of COVID-19. Rates of deterioration were higher in those with a pre-exiting diagnosis. The rate of deterioration was variable across different age groups and pre-existing psychiatric diagnostic groups: depression 37–56%, anxiety 31–50%, irritability 40–66%, attention 40–56%, hyperactivity 23–56%, obsessions/compulsions 13–30%. Greater stress from social isolation was associated with deterioration in all mental health domains (all ORs 11.12–55.24). The impact of pre-existing psychiatric diagnosis was heterogenous, associated with deterioration in depression, irritability, hyperactivity, obsession/compulsions for some children (ORs 1.96–2.23) but also with improvement in depression, anxiety, and irritability for other children (ORs 2.13–3.12). Economic concerns were associated with improvement in anxiety, attention, and obsessions/compulsions (ORs 3.97–5.57). Children/adolescents with and without pre-existing psychiatric diagnoses reported deterioration. Deterioration was associated with increased stress from social isolation. Enhancing social interactions for children/adolescents will be an important mitigation strategy for current and future COVID-19 waves.

Neurodevelopmental conditions can be associated with decreased health-related quality of life; however, the predictors of these outcomes remain largely unknown. We characterized the predictors of health-related quality of life (HRQoL) in a sample of neurodiverse children and youth. We used a cross-sectional subsample from the Province of Ontario Neurodevelopmental Disorders Network (POND) consisting of those children and young people in the POND dataset with complete study data (total n = 615; 31% female; age: 11.28 years ± 2.84 years). Using a structural equation model, we investigated the effects of demographics (age, sex, socioeconomic status), core features (Social Communication Questionnaire, Toronto Obsessive Compulsive Scale, Strengths and Weaknesses of attention deficit/hyperactivity disorder (ADHD)-symptoms and Normal Behavior), co-occurring symptoms (Child Behaviour Checklist), and adaptive functioning (Adaptive Behaviour Assessment System) on HRQoL (KINDL). A total of 615 participants had complete data for this study (autism = 135, ADHD = 273, subthreshold ADHD = 7, obsessive–compulsive disorder (OCD) = 38, sub-threshold OCD = 1, neurotypical = 161). Of these participants, 190 (31%) identified as female, and 425 (69%) identified as male. The mean age was 11.28 years ± 2.84 years. Health-related quality of life was negatively associated with co-occurring symptoms (B = − 0.6, SE = 0.20, CI (− 0.95, − 0.19), p = 0.004)) and age (B = − 0.1, SE = 0.04, CI (− 0.19, − 0.01), p = 0.037). Fewer co-occurring symptoms were associated with higher socioeconomic status (B = − 0.5, SE = − 0.05, CI (− 0.58, − 0.37), p < 0.001). This study used a cross-sectional design. Given that one’s experiences, needs, supports, and environment and thus HrQoL may change significantly over the lifespan and a longitudinal analysis of predictors is needed to capture these changes. Future studies with more diverse participant groups are needed. These results demonstrate the importance of behavioural and sociodemographic characteristics on health-related quality of life across neurodevelopmental conditions.

Autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and obsessive-compulsive disorder (OCD) have been associated with difficulties recognizing and responding to social cues. Neuroimaging studies have begun to map the social brain; however, the specific neural substrates contributing to social deficits in neurodevelopmental disorders remain unclear. Three hundred and twelve children underwent structural magnetic resonance imaging of the brain (controls = 32, OCD = 44, ADHD = 77, ASD = 159; mean age = 11). Their social deficits were quantified on the Social Communication Questionnaire (SCQ) and the Reading the Mind in the Eyes Test (RMET). Multivariable regression models were used to examine the structural neuroimaging correlates of social deficits, with both a region of interest and a whole-brain vertex-wise approach. For the region of interest analysis, social brain regions were grouped into three networks: (1) lateral mentalization (e.g., temporal–parietal junction), (2) frontal cognitive (e.g., orbitofrontal cortex), and (3) subcortical affective (e.g., limbic system) regions. Overall, social communication deficits on the SCQ were associated with thinner cortices in the left lateral regions and the right insula, and decreased volume in the ventral striatum, across diagnostic groups (p = 0.006 to <0.0001). Smaller subcortical volumes were associated with more severe social deficits on the SCQ in ASD and ADHD, and less severe deficits in OCD. On the RMET, larger amygdala/hippocampal volumes were associated with fewer deficits across groups. Overall, patterns of associations were similar in ASD and ADHD, supporting a common underlying biology and the blurring of the diagnostic boundaries between these disorders.

Introduction The amygdala subnuclei regulate emotional processing and are widely implicated in social cognitive impairments often seen in children with autism spectrum disorder (ASD). Dysregulated amygdala development has been reported in young children with ASD; less is known about amygdala maturation in later adolescence, a sensitive window for social skill development. Methods The macrostructural development of the amygdala subnuclei was assessed at two time points in a longitudinal magnetic resonance imaging (MRI) study of adolescents with ASD (n = 23) and typically‐developing adolescents (n = 15) . In adolescents with ASD, amygdala subnuclei growth was assessed in relation to ASD symptomatology based on standardized diagnostic assessments. Participants were scanned with MRI at median age of 12 years and returned for a second scan at a median age of 15 years. The volumes of nine amygdala subnuclei were extracted using an automatic segmentation algorithm. Results When examining the longitudinal data acquired across two time points, adolescents with ASD had larger basolateral amygdala (BLA) nuclei volumes compared to typically developing adolescents (B = 46.8, p = 0.04). When examining ASD symptomatology in relation to the growth of the amygdala subnuclei, reciprocal social interaction scores on the ADI‐R were positively associated with increased growth of the BLA nuclei (B = 8.3, p < 0.001). Growth in the medial nucleus negatively predicted the communication (B = −46.9, p = 0.02) and social (B = −47.7, p < 0.001) domains on the ADOS‐G. Growth in the right cortical nucleus (B = 26.14, p = 0.02) positively predicted ADOS‐G social scores. Central nucleus maturation (B = 29.9, p = 0.02) was associated with the repetitive behaviors domain on the ADOS‐G. Conclusions Larger BLA volumes in adolescents with ASD may reflect underlying alterations in cellular density previously reported in post‐mortem studies. Furthermore, findings demonstrate an association between regional growth in amygdala subnuclei volumes and ASD symptomatology. Improved understanding of the developmental trajectories of the amygdala subnuclei may aid in identifying key windows for interventions, particularly for social communication, in adolescents with ASD. Amygdala subnuclei maturation was examined in adolescents with and without ASD. The volumes of the BLA nuclei were larger in adolescents with ASD compared to controls. BLA, cortical, and medial nuclei predicted social and/or communication skills. Larger central nuclei volumes positively predicted repetitive behaviors.

Background Atypical reactions to the sensory environment are often reported in autistic individuals, with a high degree of variability across the sensory modalities. These sensory differences have been shown to promote challenging behaviours and distress in autistic individuals and are predictive of other functions including motor, social, and cognitive abilities. Preliminary research suggests that specific sensory differences may cluster together within individuals creating discrete sensory phenotypes. However, the manner in which these sensory differences cluster, and whether the resulting phenotypes are associated with specific cognitive and social challenges is unclear. Methods Short sensory profile data from 599 autistic children and adults between the ages of 1 and 21 years were subjected to a K-means cluster analysis. Analysis of variances compared age, adaptive behaviour, and traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder across the resultant clusters. Results A five-cluster model was found to minimize error variance and produce five sensory phenotypes: (1) sensory adaptive, (2) generalized sensory differences, (3) taste and smell sensitivity, (4) under-responsive and sensation seeking, and (5) movement difficulties with low energy. Age, adaptive behaviour, and traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder were found to differ significantly across the five phenotypes. Limitations The results were based on parent-report measures of sensory processing, adaptive behaviour, traits associated with autism, attention-deficit and hyperactivity disorder, and obsessive and compulsive disorder, which may limit the generalizability of the findings. Further, not all measures are standardized, or psychometrically validated with an autism population. Autistic individuals with an intellectual disability were underrepresented in this sample. Further, as these data were obtained from established records from a large provincial database, not all measures were completed for all individuals. Conclusions These findings suggest that sensory difficulties in autistic individuals can be clustered into sensory phenotypes, and that these phenotypes are associated with behavioural differences. Given the large degree of heterogeneity in sensory difficulties seen in the autistic population, these sensory phenotypes represent an effective way to parse that heterogeneity and create phenotypes that may aid in the development of effective treatments and interventions for sensory difficulties.

•Overall, there are differences in the participants excluded from four different quality control approaches across three pediatric datasets.•In clinically enriched samples, the greatest correspondence of excluded participants was between automated and visual quality control procedures.•Implementing quality control led to the exclusion of younger participants and those with greater clinical impairments.•Specific QC approach implemented did not lead to measurable differences in clinical or brain metric characteristics. 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. 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. 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. 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.

The purpose of the current study was to assess the penetrance of NRXN1 deletions. We compared the prevalence and genomic extent of NRXN1 deletions identified among 19,263 clinically referred cases to that of 15,264 controls. The burden of additional clinically relevant copy-number variations (CNVs) was used as a proxy to estimate the relative penetrance of NRXN1 deletions. We identified 41 (0.21%) previously unreported exonic NRXN1 deletions ascertained for developmental delay/intellectual disability that were significantly greater than in controls (odds ratio (OR) = 8.14; 95% confidence interval (CI): 2.91–22.72; P < 0.0001). Ten (22.7%) of these had a second clinically relevant CNV. Subjects with a deletion near the 3ʹ end of NRXN1 were significantly more likely to have a second rare CNV than subjects with a 5ʹ NRXN1 deletion (OR = 7.47; 95% CI: 2.36–23.61; P = 0.0006). The prevalence of intronic NRXN1 deletions was not statistically different between cases and controls (P = 0.618). The majority (63.2%) of intronic NRXN1 deletion cases had a second rare CNV at a prevalence twice as high as that for exonic NRXN1 deletion cases (P = 0.0035). The results support the importance of exons near the 5ʹ end of NRXN1 in the expression of neurodevelopmental disorders. Intronic NRXN1 deletions do not appear to substantially increase the risk for clinical phenotypes.

Background Theory of mind (ToM) is fundamental for social interactions, allowing individuals to appreciate that others have their own mental states. Children and youth with neurodevelopmental conditions (e.g., autism, attention-deficit hyperactivity disorder (ADHD), and obsessive-compulsive disorder (OCD)) often show differences in ToM abilities compared to their neurotypical (NT) peers. Given the phenotypic heterogeneity and overlap associated with these conditions, this motivates a transdiagnostic investigation of ToM across neurodevelopmental conditions. Methods Five hundred and fifty-five participants (5–22 years; 193 ADHD, 189 autism, 33 OCD, and 140 NT) were recruited via the Province of Ontario Neurodevelopmental Disorders network. To measure ToM, participants completed the Social Attribution Task (SAT), where participants attribute social stories to videos of moving shapes. The Animation Index (ability to attribute social stories to the videos) and Pertinence Index (how pertinent the attributions are) were calculated from the descriptions. Three analyses were performed: (1) a case-control analysis, comparing the SAT indices amongst the diagnostic groups, (2) a univariate dimensional analysis, examining associations with phenotypic variables (e.g., full-scale IQ, verbal IQ, and social communication difficulties), (3) and a multivariate analysis (partial least squares) that identifies a latent space that describes the associations between the SAT and phenotypic measures. Results There were no between-group differences in the Animation Index, but the Pertinence Index was significantly lower in autism compared to the other diagnostic categories. Phenotypic variables (full-scale IQ, verbal IQ, and social communication difficulties) were found to be significantly associated with SAT performance across groups, and explained more variance than the diagnostic categories. In the multivariate analysis, the phenotypic variables contributed more strongly to the identified latent component compared to the diagnostic categories. Limitations The verbal requirement of the SAT limited the inclusion of non-verbal participants, while the overall cognitive demand limited the participation of those with lower IQs. Additionally, our OCD group was significantly smaller than the other groups, which may have limited our ability to detect OCD-specific effects. Conclusions In a large sample, we found that transdiagnostic measures, such as IQ and social communication difficulties, are related to SAT abilities across neurodivergent and neurotypical children and youth and better describe differences in SAT performance compared to the individual diagnostic categories. Although poorer performance on ToM tasks has been classically associated with autism, this study highlights that transdiagnostic, phenotypic variables are a stronger predictor of SAT performance than diagnostic group.

Background Autism and attention deficit hyperactivity disorder (ADHD) are two highly heterogeneous neurodevelopmental conditions with variable underlying neurobiology. Imaging studies have yielded varied results, and it is now clear that there is unlikely to be one characteristic neuroanatomical profile of either condition. Parsing this heterogeneity could allow us to identify more homogeneous subgroups, either within or across conditions, which may be more clinically informative. This has been a pivotal goal for neurodevelopmental research using both clinical and neuroanatomical features, though results thus far have again been inconsistent with regards to the number and characteristics of subgroups. Methods Here, we use population modelling to cluster a multi-site dataset based on global and regional centile scores of cortical thickness, surface area and grey matter volume. We use HYDRA, a novel semi-supervised machine learning algorithm which clusters based on differences to controls and compare its performance to a traditional clustering approach. Results We identified distinct subgroups within autism and ADHD, as well as across diagnosis, often with opposite neuroanatomical alterations relatively to controls. These subgroups were characterised by different combinations of increased or decreased patterns of morphometrics. We did not find significant clinical differences across subgroups. Limitations Crucially, however, the number of subgroups and their membership differed vastly depending on chosen features and the algorithm used, highlighting the impact and importance of careful method selection. Conclusions We highlight the importance of examining heterogeneity in autism and ADHD and demonstrate that population modelling is a useful tool to study subgrouping in autism and ADHD. We identified subgroups with distinct patterns of alterations relative to controls but note that these results rely heavily on the algorithm used and encourage detailed reporting of methods and features used in future studies.

Parent and child mental health has suffered during the pandemic and transition phase. Structured and shared parenting may be intervention targets beneficial to families who are struggling with parent or child mental health challenges. First, we investigated associations between structured and shared parenting and parent depression symptoms. Second, we investigated associations between structured and shared parenting and depression, hyperactivity/inattention and irritability symptoms in children. A total of 1027 parents in two-parent households (4797 observations total; 85.1% mothers) completed online surveys about themselves and their children (aged 2-18 years) from April 2020 to July 2022. Structured parenting and shared parenting responsibilities were assessed from April 2020 to November 2021. Symptoms of parent depression, child depression, child hyperactivity and inattention, child irritability, and child emotional and conduct problems were assessed repeatedly (one to 14 times; median of four times) from April 2020 to July 2022. Parents who reported higher levels of shared parenting responsibilities had lower depression symptoms ( = -0.09 to -0.32, all < 0.01) longitudinally. Parents who reported higher levels of shared parenting responsibilities had children with fewer emotional problems (ages 2-5 years; = -0.07, < 0.05), fewer conduct problems (ages 2-5 years; = -0.09, < 0.01) and less irritability (ages 13-18 years; = -0.27, < 0.001) longitudinally. Structured parenting was associated with fewer conduct problems (ages 2-5 years; = -0.05, < 0.05). Shared parenting is beneficial for parent and child mental health, even under chaotic or inflexible life conditions. Structured parenting is beneficial for younger children.