Autistic Spectrum Disorder symptoms in children and adolescents with Attention-deficit/hyperactivity disorder: a meta-analytical review - Corrigendum

Management of sleep disorders in autism spectrum disorder with co-occurring attention-deficit hyperactivity disorder: update for clinicians

AIMS

To update and examine available literature germane to the recognition, assessment and treatment of comorbid autism spectrum disorder (ASD), attention-deficit hyperactivity disorder (ADHD) and sleep disruption, with a predominant focus on children, adolescents and emerging adults.

BACKGROUND

Considerable overlaps exist among ASD, ADHD and sleep disruption. Literature and guidance for clinicians, administrators, policy makers and families have been limited, as such deliberations were rarely considered until 2013.

METHOD

This narrative review of the literature addressing sleep disruption issues among those with ASD, ADHD and comorbid ASD and ADHD involved searching multiple databases and use of reverse citations up to the end of September 2022. Emphasis is placed on secondary sources and relevant data for clinical practice.

RESULTS

Complex clinical presentations of ASD/ADHD/sleep disruption are frequently encountered in clinical practice. Prior to 2013, prevalence, clinical presentation, pathophysiology, prognosis, other sleep-related factors and interventions were determined separately for each disorder, often with overlapping objective and subjective methods employed in the process. High percentages of ADHD and ASD patients have both disorders and sleep disruption. Here, the extant literature is integrated to provide a multidimensional understanding of the relevant issues and insights, allowing enhanced awareness and better care of this complex clinical population. Database limitations are considered.

CONCLUSIONS

Assessment of ASD symptomatology in youth with ADHD, and the reverse, in cases with disrupted sleep is critical to address the special challenges for case formulation and treatment. Evidence-based approaches to treatment planning and multi-treatment modalities should consider combining psychosocial and biological interventions to address the complexities of each case.

The Relationship Between Cortical Thickness and Executive Function Measures in Children With and Without ADHD

OBJECTIVE

Attention Deficit Hyperactivity Disorder (ADHD) is characterized by inattention, hyperactivity, and impulsivity; however, other executive function dysregulation is common, including inhibition and working memory. This study aims to identify CT differences based on executive function performance in individuals with and without ADHD.

METHODS

Data for this study was acquired from the Adolescent Brain and Cognitive Development (ABCD) database (61 ADHD, and 61 age and sex matched controls). General linear models were used to assess relationships between measures, CT, and diagnosis.

RESULTS

We found a significant relation between CT and working memory scores in the right precentral area. Additionally, we found significant interactions between CT, diagnosis, and measure outcome in the Flanker assessment (in the left fusiform area) and the attention score of the CBCL (in the right precentral region).

CONCLUSION

This suggests that there may be different relationships that exist between CT and executive function in children with ADHD.

Identifying Replicable Subgroups in Neurodevelopmental Conditions Using Resting-State Functional Magnetic Resonance Imaging Data

Importance

Neurodevelopmental conditions, such as autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and obsessive-compulsive disorder (OCD), have highly heterogeneous and overlapping phenotypes and neurobiology. Data-driven approaches are beginning to identify homogeneous transdiagnostic subgroups of children; however, findings have yet to be replicated in independently collected data sets, a necessity for translation into clinical settings.

Objective

To identify subgroups of children with and without neurodevelopmental conditions with shared functional brain characteristics using data from 2 large, independent data sets.

Design, Setting, and Participants

This case-control study used data from the Province of Ontario Neurodevelopmental (POND) network (study recruitment began June 2012 and is ongoing; data were extracted April 2021) and the Healthy Brain Network (HBN; study recruitment began May 2015 and is ongoing; data were extracted November 2020). POND and HBN data are collected from institutions across Ontario and New York, respectively. Participants who had diagnoses of ASD, ADHD, and OCD or were typically developing (TD); were aged between 5 and 19 years; and successfully completed the resting-state and anatomical neuroimaging protocol were included in the current study.

Main Outcomes and Measures

The analyses consisted of a data-driven clustering procedure on measures derived from each participant's resting-state functional connectome, performed independently on each data set. Differences between each pair of leaves in the resulting clustering decision trees in the demographic and clinical characteristics were tested.

Results

Overall, 551 children and adolescents were included from each data set. POND included 164 participants with ADHD; 217 with ASD; 60 with OCD; and 110 with TD (median [IQR] age, 11.87 [9.51-14.76] years; 393 [71.2%] male participants; 20 [3.6%] Black, 28 [5.1%] Latino, and 299 [54.2%] White participants) and HBN included 374 participants with ADHD; 66 with ASD; 11 with OCD; and 100 with TD (median [IQR] age, 11.50 [9.22-14.20] years; 390 [70.8%] male participants; 82 [14.9%] Black, 57 [10.3%] Hispanic, and 257 [46.6%] White participants). In both data sets, subgroups with similar biology that differed significantly in intelligence as well as hyperactivity and impulsivity problems were identified, yet these groups showed no consistent alignment with current diagnostic categories. For example, there was a significant difference in Strengths and Weaknesses ADHD Symptoms and Normal Behavior Hyperactivity/Impulsivity subscale (SWAN-HI) between 2 subgroups in the POND data (C and D), with subgroup D having increased hyperactivity and impulsivity traits compared with subgroup C (median [IQR], 2.50 [0.00-7.00] vs 1.00 [0.00-5.00]; U = 1.19 × 104; P = .01; η2 = 0.02). A significant difference in SWAN-HI scores between subgroups g and d in the HBN data was also observed (median [IQR], 1.00 [0.00-4.00] vs 0.00 [0.00-2.00]; corrected P = .02). There were no differences in the proportion of each diagnosis between the subgroups in either data set.

Conclusions and Relevance

The findings of this study suggest that homogeneity in the neurobiology of neurodevelopmental conditions transcends diagnostic boundaries and is instead associated with behavioral characteristics. This work takes an important step toward translating neurobiological subgroups into clinical settings by being the first to replicate our findings in independently collected data sets.

Do shapes have feelings? Social attribution in children with autism spectrum disorder and attention-deficit/hyperactivity disorder

Theory of mind (ToM) deficits are common in children with neurodevelopmental disorders (NDDs), such as autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD), which contribute to their social and cognitive difficulties. The social attribution task (SAT) involves geometrical shapes moving in patterns that depict social interactions and is known to recruit brain regions from the classic ToM network. To better understand ToM in ASD and ADHD children, we examined the neural correlates using the SAT and functional magnetic resonance imaging (fMRI) in a cohort of 200 children: ASD (N = 76), ADHD (N = 74) and typically developing (TD; N = 50) (4-19 years). In the scanner, participants were presented with SAT videos corresponding to social help, social threat, and random conditions. Contrasting social vs. random, the ASD compared with TD children showed atypical activation in ToM brain areas-the middle temporal and anterior cingulate gyri. In the social help vs. social threat condition, atypical activation of the bilateral middle cingulate and right supramarginal and superior temporal gyri was shared across the NDD children, with between-diagnosis differences only being observed in the right fusiform. Data-driven subgrouping identified two distinct subgroups spanning all groups that differed in both their clinical characteristics and brain-behaviour relations with ToM ability.

The Co-existence of ADHD With Autism in Saudi Children: An Analysis Using Next-Generation DNA Sequencing

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders. Several studies have confirmed the co-existence of other neuropsychiatric disorders with ADHD. Out of 106 individuals suspected to have ADHD, eight Saudi Arabian pediatric patients were diagnosed with ADHD using a dual assessment procedure based on highly significant scores from the international criteria for diagnosis; (full form DMS) DSM-5. Then, these patients were examined for the co-existence of autism and ADHD using different international diagnostic protocols. Four patients with combined ADHD and autism and four ADHD patients without autism were examined for the presence of genetic variants. Six variants (chr1:98165091, chr6:32029183, chr6:32035603, chr6:32064098, chr8:2909992, chr16:84213434) were identified in 75% of the patients with ADHD and autism, indicating that these genes may have a possible role in causing autism. Five variants (The chr2:116525960, chr15:68624396, chr15:91452595, chr15:92647645, and chr16:82673047) may increase to the severity of ADHD. This study recommends screening these eleven variants in ADHD cases and their relevant controls to confirm the prevalence in the Saudi population. It is recommended that future studies examine the 11 variants in detail.

Emotional face processing across neurodevelopmental disorders: a dynamic faces study in children with autism spectrum disorder, attention deficit hyperactivity disorder and obsessive-compulsive disorder

Autism spectrum disorder (ASD) is classically associated with poor face processing skills, yet evidence suggests that those with obsessive-compulsive disorder (OCD) and attention deficit hyperactivity disorder (ADHD) also have difficulties understanding emotions. We determined the neural underpinnings of dynamic emotional face processing across these three clinical paediatric groups, including developmental trajectories, compared with typically developing (TD) controls. We studied 279 children, 5-19 years of age but 57 were excluded due to excessive motion in fMRI, leaving 222: 87 ASD, 44 ADHD, 42 OCD and 49 TD. Groups were sex- and age-matched. Dynamic faces (happy, angry) and dynamic flowers were presented in 18 pseudo-randomized blocks while fMRI data were collected with a 3T MRI. Group-by-age interactions and group difference contrasts were analysed for the faces vs. flowers and between happy and angry faces. TD children demonstrated different activity patterns across the four contrasts; these patterns were more limited and distinct for the NDDs. Processing happy and angry faces compared to flowers yielded similar activation in occipital regions in the NDDs compared to TDs. Processing happy compared to angry faces showed an age by group interaction in the superior frontal gyrus, increasing with age for ASD and OCD, decreasing for TDs. Children with ASD, ADHD and OCD differentiated less between dynamic faces and dynamic flowers, with most of the effects seen in the occipital and temporal regions, suggesting that emotional difficulties shared in NDDs may be partly attributed to shared atypical visual information processing.