Autistic Symptoms, Irritability, and Executive Dysfunctions: Symptom Dynamics from Multi-Network Models

Socio-cognitive difficulties in individuals with autism spectrum disorder (ASD) are heterogenuous and often co-occur with irritability symptoms, such as angry/grouchy mood and temper outbursts. However, the specific relations between individual symptoms are not well-represented in conventional methods analyzing aggregated autistic symptoms and ASD diagnosis. Moreover, the cognitive-behavioral mechanisms linking ASD to irritability are largely unknown. This study investigated the dynamics between autistic (Social Responsiveness Scale) and irritability (Affective Reactivity Index) symptoms and executive functions (Cambridge Neuropsychological Test Automated Battery) in a sample of children and adolescents with ASD, their unaffected siblings, and neurotypical peers (N = 345, aged 6-18 years, 78.6% male). Three complementary networks across the entire sample were computed: (1) Gaussian graphical network estimating the conditional correlations between symptom nodes; (2) Relative importance network computing relative influence between symptoms; (3) Bayesian directed acyclic graph estimating predictive directionality between symptoms. Networks revealed numerous partial correlations within autistic (rs = .07-.56) and irritability (rs = .01-.45) symptoms and executive functions (rs = -.83 to .67) but weak connections between clusters. This segregated pattern converged in all directed and supplementary networks. Plausible predictive paths were found between social communication difficulties to autism mannerisms and between "angry frequently" to "lose temper easily." Autistic and irritability symptoms are two relatively independent families of symptoms. It is unlikely that executive dysfunctions explain elevated irritability in ASD. Findings underscore the need for researching other mood and cognitive-behavioral bridge symptoms, which may inform individualized treatments for co-occurring irritability in ASD.

Emotion regulation and emotion dysregulation in children and adolescents with Autism Spectrum Disorder: A meta-analysis of evaluation and intervention studies

Children and adolescents with Autism Spectrum Disorder (ASD) often experience challenges in emotion regulation (ER) and emotion dysregulation (ED) which can interfere with their adaptive functioning. This study aimed to systematically review and meta-analyze the evidence on ER/ED in children and/or adolescents with ASD, examining its relationship with the following variables: internalizing and externalizing symptoms, cognitive function and social skills, and the effectiveness of non-pharmacological interventions addressing ER difficulties. Both electronic and manual searches were conducted to identify potential studies. Fifty-five studies were included in the meta-analysis. A statistically significant between-group difference was found, suggesting greater ER/ED challenges in the ASD group. Also, the ASD group showed more maladaptive ER strategies and fewer adaptive ER strategies compared to the non-ASD participants. Additionally, more severe ASD and poorer social skills were associated with greater ED and poorer ER skills, respectivelly. Furthermore, there was a significant correlation between internalizing symptomatology and both adaptive and maladaptive ER strategies. Studies of non-pharmacological interventions showed significant improvement in both ER and ED. These results imply that assessing ER/ED in children and adolescents with ASD should be part of the evaluation process, and it should also be a focal point for intervention in this population.

A deep connectome learning network using graph convolution for connectome-disease association study

Multivariate analysis approaches provide insights into the identification of phenotype associations in brain connectome data. In recent years, deep learning methods including convolutional neural network (CNN) and graph neural network (GNN), have shifted the development of connectome-wide association studies (CWAS) and made breakthroughs for connectome representation learning by leveraging deep embedded features. However, most existing studies remain limited by potentially ignoring the exploration of region-specific features, which play a key role in distinguishing brain disorders with high intra-class variations, such as autism spectrum disorder (ASD), and attention deficit hyperactivity disorder (ADHD). Here, we propose a multivariate distance-based connectome network (MDCN) that addresses the local specificity problem by efficient parcellation-wise learning, as well as associating population and parcellation dependencies to map individual differences. The approach incorporating an explainable method, parcellation-wise gradient and class activation map (p-GradCAM), is feasible for identifying individual patterns of interest and pinpointing connectome associations with diseases. We demonstrate the utility of our method on two largely aggregated multicenter public datasets by distinguishing ASD and ADHD from healthy controls and assessing their associations with underlying diseases. Extensive experiments have demonstrated the superiority of MDCN in classification and interpretation, where MDCN outperformed competitive state-of-the-art methods and achieved a high proportion of overlap with previous findings. As a CWAS-guided deep learning method, our proposed MDCN framework may narrow the bridge between deep learning and CWAS approaches, and provide new insights for connectome-wide association studies.

Altered gut microbiota correlates with behavioral problems but not gastrointestinal symptoms in individuals with autism

BACKGROUND

Despite inconsistent results across studies, emerging evidence suggests that the microbial micro-environment may be associated with autism spectrum disorder (ASD). Geographical and cultural factors highly impact microbial profiles, and there is a shortage of data from East Asian populations. This study aimed to comprehensively characterize microbial profiles in an East Asian sample and explore whether gut microbiota contributes to clinical symptoms, emotional/behavioral problems, and GI symptoms in ASD.

METHODS

We assessed 82 boys and young men with ASD and 31 typically developing controls (TDC), aged 6-25 years. We analyzed the stool sample of all participants with 16S V3-V4 rRNA sequencing and correlated its profile with GI symptoms, autistic symptoms, and emotional/behavioral problems.

RESULTS

Autistic individuals, compared to TDC, had worse GI symptoms. There were no group differences in alpha diversity of species richness estimates (Shannon-wiener and Simpson diversity indices). Participants with ASD had an increased relative abundance of Fusobacterium, Ruminococcus torques group (at the genus level), and Bacteroides plebeius DSM 17135 (at the species level), while a decreased relative abundance of Ruminococcaceae UCG 013, Ervsipelotrichaceae UCG 003, Parasutterella, Clostridium sensu stricto 1, Turicibacter (at the genus level), and Clostridium spiroforme DSM 1552 and Intestinimonas butyriciproducens (at the species level). Altered taxonomic diversity in ASD significantly correlated with autistic symptoms, thought problems, delinquent behaviors, self dysregulation, and somatic complaints. We did not find an association between gut symptoms and gut microbial dysbiosis.

CONCLUSIONS

Our findings suggest that altered microbiota are associated with behavioral phenotypes but not GI symptoms in ASD. The function of the identified microbial profiles mainly involves the immune pathway, supporting the hypothesis of a complex relationship between altered microbiome, immune dysregulation, and ASD that may advance the discovery of molecular biomarkers for ASD.

Differential neural correlates underlying mental rotation processes in two distinct cognitive profiles in autism

Enhanced visuospatial abilities characterize the cognitive profile of a subgroup of autistics. However, the neural correlates underlying such cognitive strengths are largely unknown. Using functional magnetic resonance imaging (fMRI), we investigated the neural underpinnings of superior visuospatial functioning in different autistic subgroups. Twenty-seven autistic adults, including 13 with a Wechsler's Block Design peak (AUTp) and 14 without (AUTnp), and 23 typically developed adults (TYP) performed a classic mental rotation task. As expected, AUTp participants were faster at the task compared to TYP. At the neural level, AUTp participants showed enhanced bilateral parietal and occipital activation, stronger occipito-parietal and fronto-occipital connectivity, and diminished fronto-parietal connectivity compared to TYP. On the other hand, AUTnp participants presented greater activation in right and anterior regions compared to AUTp. In addition, reduced connectivity between occipital and parietal regions was observed in AUTnp compared to AUTp and TYP participants. A greater reliance on posterior regions is typically reported in the autism literature. Our results suggest that this commonly reported finding may be specific to a subgroup of autistic individuals with enhanced visuospatial functioning. Moreover, this study demonstrated that increased occipito-frontal synchronization was associated with superior visuospatial abilities in autism. This finding contradicts the long-range under-connectivity hypothesis in autism. Finally, given the relationship between distinct cognitive profiles in autism and our observed differences in brain functioning, future studies should provide an adequate characterization of the autistic subgroups in their research. The main limitations are small sample sizes and the inclusion of male-only participants.

Altered synaptic protein expression, aberrant spine morphology, and impaired spatial memory in Dlgap2 mutant mice, a genetic model of autism spectrum disorder

A microdeletion of approximately 2.4 Mb at the 8p23 terminal region has been identified in a Taiwanese autistic boy. Among the products transcribed/translated from genes mapped in this region, the reduction of DLGAP2, a postsynaptic scaffold protein, might be involved in the pathogenesis of autism spectrum disorder (ASD). DLGAP2 protein was detected in the hippocampus yet abolished in homozygous Dlgap2 knockout (Dlgap2 KO) mice. In this study, we characterized the hippocampal phenotypes in Dlgap2 mutant mice. Dlgap2 KO mice exhibited impaired spatial memory, indicating poor hippocampal function in the absence of DLGAP2. Aberrant expressions of postsynaptic proteins, including PSD95, SHANK3, HOMER1, GluN2A, GluR2, mGluR1, mGluR5, βCAMKII, ERK1/2, ARC, BDNF, were noticed in Dlgap2 mutant mice. Further, the spine density was increased in Dlgap2 KO mice, while the ratio of mushroom-type spines was decreased. We also observed a thinner postsynaptic density thickness in Dlgap2 KO mice at the ultrastructural level. These structural changes found in the hippocampus of Dlgap2 KO mice might be linked to impaired hippocampus-related cognitive functions such as spatial memory. Mice with Dlgap2 deficiency, showing signs of intellectual disability, a common co-occurring condition in patients with ASD, could be a promising animal model which may advance our understanding of ASD.

Linking irritability and functional brain networks: A transdiagnostic case for expanding consideration of development and environment in RDoC

The National Institute of Mental Health Research Domain Criteria (RDoC) framework promotes the dimensional and transdiagnostic operationalization of psychopathology, but consideration of the neurodevelopmental foundations of mental health problems requires deeper examination. Irritability, the dispositional tendency to angry emotion that has both mood and behavioral elements, is dimensional, transdiagnostic, and observable early in life-a promising target for the identification of early neural indicators or risk factors for psychopathology. Here, we examine functional brain networks linked to irritability from preschool to adulthood and discuss how development and early experience may influence these neural substrates. Functional connectivity measured with fMRI varies according to irritability and indicates the atypical coordination of several functional networks involved in emotion generation, emotion perception, attention, internalization, and cognitive control. We lay out an agenda to improve our understanding and detection of atypical brain:behavior patterns through advances in the characterization of both functional networks and irritability as well as the consideration and operationalization of developmental and early life environmental influences on this pathway.

High Depression Symptoms and Burnout Levels Among Parents of Children with Autism Spectrum Disorders: A Multi-Center, Cross-Sectional, Case-Control Study

The diagnosis of autism spectrum disorder (ASD) in a child affects family processes, increases parenting stress and marital conflicts, and may lead to parental psychopathology. It may also affect the prognosis for their children. The aim of this study is to determine depression and burnout levels as well as their predictors among parents of children with ASD compared with those of healthy children. We also sought to evaluate rate of complementary and alternative medicine (CAM) interventions among parents and explore the associations of this phenomenon in an exploratory fashion. 145 children with ASD and 127 control children were enrolled along with their mothers and fathers. Beck Depression Inventory and Maslach Burnout Inventory were used to evaluate parents' depression symptoms and burnout levels. Symptoms of children with ASDs were evaluated according to the Childhood Autism Rating Scale by the clinicians. Family, child and CAM variables were screened by means of a sociodemographic data form. Descriptive, bivariate and correlation analyses were used in statistical evaluations. Predictors of burnout were evaluated with multiple regression analysis. Burnout and depression levels among parents of children with ASD were significantly elevated compared to controls. Burnout levels of mothers were significantly elevated compared to fathers while depression scores of fathers were significantly elevated compared to mothers. Maternal burnout was significantly predicted by presence of functional speech in child while paternal burnout was significantly predicted by paternal vocation. Maternal depression was associated with paternal depression, lack of speech in child and attendance of child to special education services. Paternal depression was associated with autistic symptom severity and maternal depression. More than half the parents sought CAM interventions. Education level did not affect search for CAM interventions while both maternal and paternal psychopathology and presence of epilepsy among children increased use of CAM methods. Psychological support should be provided to both mothers and fathers of a child receiving a diagnosis of ASD. Addressing parents' burnout and stress levels and facilitating their negotiation of knowledge on etiology and treatments for ASD may be beneficial for the family unit as a whole.

Association of self-regulation with white matter correlates in boys with and without autism spectrum disorder

Previous studies demonstrated distinct neural correlates underpinning impaired self-regulation (dysregulation) between individuals with autism spectrum disorder (ASD) and typically developing controls (TDC). However, the impacts of dysregulation on white matter (WM) microstructural property in ASD and TDC remain unclear. Diffusion spectrum imaging was acquired in 59 ASD and 62 TDC boys. We investigated the relationship between participants’ dysregulation levels and microstructural property of 76 WM tracts in a multivariate analysis (canonical correlation analysis), across diagnostic groups. A single mode of brain-behavior co-variation was identified: participants were spread along a single axis linking diagnosis, dysregulation, diagnosis-by-dysregulation interaction, and intelligence to a specific WM property pattern. This mode corresponds to diagnosis-distinct correlates underpinning dysregulation, which showed higher generalized fractional anisotropy (GFA) associated with less dysregulation in ASD but greater dysregulation in TDC, in the tracts connecting limbic and emotion regulation systems. Moreover, higher GFA of the tracts implicated in memory, attention, sensorimotor processing, and perception associated with less dysregulation in TDC but worse dysregulation in ASD. No shared WM correlates of dysregulation between ASD and TDC were identified. Corresponding to previous studies, we demonstrated that ASD and TDC have broad distinct white matter microstructural property underpinning self-regulation.