The Network Structure of Irritability and Aggression in Individuals with Autism Spectrum Disorder

Network structure of phasic and tonic irritability in adults: A Bayesian Gaussian graphical model

BACKGROUND

Tonic (i.e., irritable mood) and phasic (i.e., temper outbursts) irritability are distinct constructs in childhood, yet there has been little work investigating their relations in adulthood. In particular, no study has examined the relations between these symptoms in the daily lives of adults. The present study seeks to address these gaps by applying a Bayesian Gaussian graphical model to daily diary data of tonic and phasic irritability in adults.

METHOD

A total of 122 participants (Mage = 34.94 [SD = 12.3] years, 52 % female) completed up to 18 days of daily diary, with questions on both tonic and phasic irritability. Contemporaneous, temporal, and between-person networks were constructed using 5 items of tonic and 11 items of phasic irritability. Predictability, centrality, density, and network loadings were also calculated.

RESULTS

Five main findings emerged. First, phasic and tonic irritability were connected in our contemporaneous and temporal networks but distinct in our between-person network. Second, phasic irritability symptoms demonstrated the most importance and influence across networks. Third, tonic irritability symptoms best connected the two subnetworks. Fourth, phasic irritability symptoms appeared to have the potential to be more responsive to interventions. Fifth, tonic irritability demonstrated robust associations with daily functional impairment.

CONCLUSIONS

Tonic and phasic irritability symptoms demonstrate unique associations in the daily lives of adults. Future work should examine the differential potential of these symptoms to respond to targeted interventions.

Similarities and differences in core symptoms of problematic smartphone use among Chinese students enrolled in grades 4 to 9: A large national cross-sectional study

Children and adolescents are highly susceptible to problematic smartphone usage. We employed network analysis to explore the similarities and differences in the core symptoms of problematic smartphone use across grades 4-9, using a large nationwide sample. This study included 8552 children and adolescents (Mage = 12.98, SD=1.51) who met the critical value for problematic smartphone use. The results showed that the core symptoms of problematic smartphone use exhibit both similarities and differences between grades 4 and 9. 'Withdrawal symptoms' and 'preoccupation symptoms' were the stable core symptoms of problematic smartphone use across grades 4 to 9, suggesting that problematic smartphone use begin to appear from earlier grades, such as grade 4. 'Feel impatient and fretful', 'never give up' and 'always thinking about' were the core symptoms in grades 4 and 5. 'Longer than I had intended' and 'hard to concentrate' emerged as additional core symptoms in grade 6, with the intensity indicators peaking in grades 8 and 9, suggesting that the issue of problematic smartphone use among Chinese children and adolescents has become intensified and intricate. Symptoms of problematic smartphone use vary across grades and exhibit both continuity and stage specificity. Consequently, to address this issue, the formulation of intervention measures should comprehensively consider both the grade levels and symptoms.

Sleep disturbance and other co-occurring conditions in autistic children: A network approach to understanding their inter-relationships

Autistic children frequently have one or more co-occurring psychological, behavioral, or medical conditions. We examined relationships between child behaviors, sleep, adaptive behavior, autistic traits, mental health conditions, and health in autistic children using network analysis. Network analysis is hypothesis generating and can inform our understanding of relationships between multiple conditions and behaviors, directing the development of transdiagnostic treatments for co-occurring conditions. Participants were two child cohorts from the Autism Treatment Network registry: ages 2-5 years (n = 2372) and 6-17 years (n = 1553). Least absolute-shrinkage and selection operator (LASSO) regularized partial correlation network analysis was performed in the 2-5 years cohort (35 items) and the 6-17 years cohort (36 items). The Spinglass algorithm determined communities within each network. Two-step expected influence (EI2) determined the importance of network variables. The most influential network items were sleep difficulties (2 items) and aggressive behaviors for young children and aggressive behaviors, social problems, and anxious/depressed behavior for older children. Five communities were found for younger children and seven for older children. Of the top three most important bridge variables, night-waking/parasomnias and anxious/depressed behavior were in both age-groups, and somatic complaints and sleep initiation/duration were in younger and older cohorts respectively. Despite cohort differences, sleep disturbances were prominent in all networks, indicating they are a transdiagnostic feature across many clinical conditions, and thus a target for intervention and monitoring. Aggressive behavior was influential in the partial correlation networks, indicating a potential red flag for clinical monitoring. Other items of strong network importance may also be intervention targets or screening flags.

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.

Predictors of irritability in pediatric autistic populations: a scoping review

Introduction

Autism is characterized by social communication differences and repetitive behaviors, affecting 1%-2% of children. Irritability is a disabling condition affecting 19%-80% of autistic children. While extensive research has focused on interventions to reduce irritability symptoms, the underlying correlates remain poorly understood. To address this, we conducted a scoping review of the literature examining factors contributing to irritability in pediatric autistic populations.

Methods

A literature search of Embase, MEDLINE, PubMed, PsycINFO, and Web of Science was conducted in addition to manually retrieved papers from Google Scholar. Studies underwent title and abstract screening by one reviewer and full-text screening by two reviewers; disagreements were resolved through deliberation. The remaining studies underwent data extraction. The review was conducted using the PRISMA-ScR checklist.

Results

The search yielded 48 studies meeting the inclusion criteria. Correlates of irritability were categorized into eight themes: demographics/environmental, autism features, mental health, language, cognition, and function, neurobiological, physical health, physiological, and multidimensional factors. Findings revealed mixed associations with demographic factors, consistent positive associations with sensory differences and mental health symptoms, and varying associations with cognitive abilities and physical health factors. Neurobiological and physiological correlates were less explored.

Conclusion

This review revealed a significant gap in understanding sociodemographic, phenotypic, and neurobiological and physiological correlates of irritability in autism. There was also a significant gap in understanding the multi-dimensional irritability correlates. Positive associations between irritability and sensory differences and mental health symptoms suggest potential avenues for investigation of non-medication interventions.

Network analysis of trait aggression among community youths and juvenile offenders

OBJECTIVE

The mainstream view in trait aggression research has regarded the structure as representing the latent cause of the cognitions, emotions, and behaviors that supposedly reflect its nature. Under network perspective, trait aggression is not a latent cause of its features but a dynamic system of interacting elements. The current study uses network theory to explain the structure of relationships between trait aggression features in juvenile offenders and their peers.

METHODS

Network analysis was applied to investigate the dynamic system of trait aggression operationalized by the Buss-Perry Aggression Questionnaire in a sample of community youths (Mage = 17.46, N = 715) and juvenile offenders (Mage = 18.36, N = 834).

RESULTS

The facet level networks showed that anger is a particularly effective mechanism for activating all other traits. In addition, anger was more strongly associated with physical aggression and the overall network strength was greater in juvenile delinquency networks than in their peers. The item level networks revealed that A4 and A6 exhibited the highest predictability and strength centrality in both samples. Also, the Bayesian network indicated that these two items were positioned at the highest level in the model. There are similarities and differences between juvenile delinquents and community adolescents in trait aggression.

CONCLUSION

Trait aggression was primarily activated by difficulty controlling one's temper and feeling like a powder keg.

The interrelationship between sleep disturbance symptoms and aggression before and after the campus closure of the COVID-19 pandemic: insight from a cross-lagged panel network model

Background

The COVID-19 pandemic is detrimental to sleep quality and increases aggression among college students. Nevertheless, relevant studies were rare. Hence, we collected longitudinal data during and post-campus closure in the current study to investigate the relationship between sleep disturbance and aggression.

Methods

Data from 665 college students (59.2% females, Meanage = 19.01, SD age = 1.25) were collected before (wave 1) and after (wave 2) the campus closure of COVID-19. All participants were asked to fill out the Buss-Perry Aggression Questionnaire and the Youth Self-Rating Insomnia Scale. Two symptom networks and a cross-lagged panel network were formed and tested.

Results

Hostility has the highest centrality in the symptom network both in waves 1 and 2, and it bridges sleep disturbance and aggression. "Easily be woken" - "wake up too early" and "wake up with tired" - "function hindrance" are two important symptom associations in networks of waves 1 and 2. All symptoms except "difficulty in falling asleep" and "easily be woken" ameliorated after closure. Moreover, "physical aggression" and "hostility" can trigger other symptoms in wave 2.

Conclusion

As the first study about aggression and sleep disturbance in the background of COVID-19, we provide valuable information about the relationship between sleep disturbance and aggression on the symptom dimension.

Examining Sensitivity to Developmental Changes on the Behavioral Inflexibility Scale

PURPOSE

The study objective was to determine if the validated Behavioral Inflexibility Scale (BIS) is sensitive to the detection of developmental changes in inflexibility in a sample of autistic children.

METHODS

Parents of autistic children (n = 146, 3-17 years) completed the BIS at two time points, one year apart, to examine change.

RESULTS

The findings indicate the BIS is sensitive to the detection of developmental changes and that child-level variables are not associated with those changes. Children's Time 1 BIS scores predicted children's severity on an independent outcome measure. Finally, a relationship between total services children were receiving and change in BIS scores over time was not found.

CONCLUSION

The findings suggest the BIS is a reasonable candidate for consideration as an outcome measure.

Identification of hippocampal area CA2 in hamster and vole brain

Prairie voles (Microtus ochrogaster) and Syrian, or golden, hamsters (Mesocricetus auratus) are closely related to mice (Mus musculus) and rats (Rattus norvegicus, for example) and are commonly used in studies of social behavior including social interaction, social memory, and aggression. The CA2 region of the hippocampus is known to play a key role in social memory and aggression in mice and responds to social stimuli in rats, likely owing to its high expression of oxytocin and vasopressin 1b receptors. However, CA2 has yet to be identified and characterized in hamsters or voles. In this study, we sought to determine whether CA2 could be identified molecularly in vole and hamster. To do this, we used immunofluorescence with primary antibodies raised against known molecular markers of CA2 in mice and rats to stain hippocampal sections from voles and hamsters in parallel with those from mice. Here, we report that, like in mouse and rat, staining for many CA2 proteins in vole and hamster hippocampus reveals a population of neurons that express regulator of G protein signaling 14 (RGS14), Purkinje cell protein 4 (PCP4) and striatal-enriched protein tyrosine phosphatase (STEP), which together delineate the borders with CA3 and CA1. These cells were located at the distal end of the mossy fiber projections, marked by the presence of Zinc Transporter 3 (ZnT-3) and calbindin in all three species. In addition to staining the mossy fibers, calbindin also labeled a layer of CA1 pyramidal cells in mouse and hamster but not in vole. However, Wolframin ER transmembrane glycoprotein (WFS1) immunofluorescence, which marks all CA1 neurons, was present in all three species and abutted the distal end of CA2, marked by RGS14 immunofluorescence. Staining for two stress hormone receptors-the glucocorticoid (GR) and mineralocorticoid (MR) receptors-was also similar in all three species, with GR staining found primarily in CA1 and MR staining enriched in CA2. Interestingly, although perineuronal nets (PNNs) are known to surround CA2 cells in mouse and rat, we found that staining for PNNs differed across species in that both CA2 and CA3 showed staining in voles and primarily CA3 in hamsters with only some neurons in proximal CA2 showing staining. These results demonstrate that, like in mouse, CA2 in voles and hamsters can be molecularly distinguished from neighboring CA1 and CA3 areas, but PNN staining is less useful for identifying CA2 in the latter two species. These findings reveal commonalities across species in molecular profile of CA2, which will facilitate future studies of CA2 in these species. Yet to be determined is how differences in PNNs might relate to differences in social behavior across species.

Phenotypically driven subgroups of ASD display distinct metabolomic profiles

Autism Spectrum Disorder (ASD) is a heterogeneous condition that includes a broad range of characteristics and associated comorbidities; however, the biology underlying the variability in phenotypes is not well understood. As ASD impacts approximately 1 in 100 children globally, there is an urgent need to better understand the biological mechanisms that contribute to features of ASD. In this study, we leveraged rich phenotypic and diagnostic information related to ASD in 2001 individuals aged 4 to 17 years from the Simons Simplex Collection to derive phenotypically driven subgroups and investigate their respective metabolomes. We performed hierarchical clustering on 40 phenotypes spanning four ASD clinical domains, resulting in three subgroups with distinct phenotype patterns. Using global plasma metabolomic profiling generated by ultrahigh-performance liquid chromatography mass spectrometry, we characterized the metabolome of individuals in each subgroup to interrogate underlying biology related to the subgroups. Subgroup 1 included children with the least maladaptive behavioral traits (N = 862); global decreases in lipid metabolites and concomitant increases in amino acid and nucleotide pathways were observed for children in this subgroup. Subgroup 2 included children with the highest degree of challenges across all phenotype domains (N = 631), and their metabolome profiles demonstrated aberrant metabolism of membrane lipids and increases in lipid oxidation products. Subgroup 3 included children with maladaptive behaviors and co-occurring conditions that showed the highest IQ scores (N = 508); these individuals had increases in sphingolipid metabolites and fatty acid byproducts. Overall, these findings indicated distinct metabolic patterns within ASD subgroups, which may reflect the biological mechanisms giving rise to specific patterns of ASD characteristics. Our results may have important clinical applications relevant to personalized medicine approaches towards managing ASD symptoms.

Health-related risky behaviors in Chinese adolescents with autism: a cross-sectional study

BACKGROUND

Health-related risky behaviors (HRB) generally refer to behaviors that have a negative influence on health and quality of life. HRB in adolescents with autism have not been well understood so far. We aim to explore health-related risky behaviors and their risk factors with autistic adolescents.

METHODS

In this study, 150 adolescents with autism and 150 neurotypical adolescents were enrolled. Participants in both groups completed the Adolescent Health-Related Risky Behavior Inventory (AHRBI). Autism Spectrum Screening Questionnaire (ASSQ), Wechsler Intelligence Scale, Theory of Mind (ToM) Test, Zung Self-rating Anxiety Scale (SAS), Zung Self-rating Depression Scale (SDS), and Self-Esteem Scale (SES) were also assessed in the autism group to explore risk factors.

RESULTS

The results showed that the total score of AHRBI and scores of "aggression and violence (AV)", "suicide or self-injury (SS)", "health-compromising behavior (HCB)", and "unprotected sex (US)" subscales in the autism group were significantly higher than those in the control group (Z value = - 4.58 ~ - 2.26, all P < 0.05). Anxiety, depression, low self-esteem, low IQ score, low ToM test score, increasing age, and communication disorder were found as risk factors for health-related risky behaviors in autistic adolescents.

CONCLUSIONS

Adolescents with autism have more health-related risky behaviors than neurotypical adolescents. We should pay attention to the emotional state, self-esteem, cognitive function, and verbal communication levels of autistic adolescent with health-related risky behaviors.

Human Self-Domestication and the Evolution of Pragmatics

As proposed for the emergence of modern languages, we argue that modern uses of languages (pragmatics) also evolved gradually in our species under the effects of human self-domestication, with three key aspects involved in a complex feedback loop: (a) a reduction in reactive aggression, (b) the sophistication of language structure (with emerging grammars initially facilitating the transition from physical aggression to verbal aggression); and (c) the potentiation of pragmatic principles governing conversation, including, but not limited to, turn-taking and inferential abilities. Our core hypothesis is that the reduction in reactive aggression, one of the key factors in self-domestication processes, enabled us to fully exploit our cognitive and interactional potential as applied to linguistic exchanges, and ultimately to evolve a specific form of communication governed by persuasive reciprocity-a trait of human conversation characterized by both competition and cooperation. In turn, both early crude forms of language, well suited for verbal aggression/insult, and later more sophisticated forms of language, well suited for persuasive reciprocity, significantly contributed to the resolution and reduction of (physical) aggression, thus having a return effect on the self-domestication processes. Supporting evidence for our proposal, as well as grounds for further testing, comes mainly from the consideration of cognitive disorders, which typically simultaneously present abnormal features of self-domestication (including aggressive behavior) and problems with pragmatics and social functioning. While various approaches to language evolution typically reduce it to a single factor, our approach considers language evolution as a multifactorial process, with each player acting upon the other, engaging in an intense mutually reinforcing feedback loop. Moreover, we see language evolution as a gradual process, continuous with the pre-linguistic cognitive abilities, which were engaged in a positive feedback loop with linguistic innovations, and where gene-culture co-evolution and cultural niche construction were the main driving forces.

Equine-Assisted Interventions (EAIs) for Children with Autism Spectrum Disorders (ASD): Behavioural and Physiological Indices of Stress in Domestic Horses (Equus caballus) during Riding Sessions

Equine-assisted interventions (EAIs) are well-known complementary practices combining physical activity with emotional/cognitive stimulation. They are especially suited for children with autism spectrum disorders (ASD) who need a high degree of physical and psychological enrichment. Even though EAIs have become a common practice, stress responses in horses interacting with individuals that can manifest inappropriate behaviours, such as ASD children, have not been thoroughly investigated. Our multicentre study aimed to investigate behavioural and physiological indices of stress in horses involved in EAI standardised sessions with children with ASD compared to typically developing (TD) children. A controlled within-subject design with repeated measurements involving 19 horses and 38 children was adopted. Stress-related behaviours, heart rate, heart rate variability, and eye temperature were recorded during the riding sessions. Moreover, blood samples were collected from horses before and after each session to monitor changes in blood adrenocorticotropic hormone (ACTH), cortisol, and catecholamines. Results indicate that, in general, stress responses in horses involved in EAIs did not differ as a function of the horse being ridden by children with ASD or TD. A lower sympathetic tone in horses involved in ASD sessions was found, while in the mounting and dismounting phases, horses displayed behavioural signs of stress, independently from children's behaviour. We conclude that professionals working in EAI should increase their awareness of animal welfare and refine riding practices, taking into account horse's needs.

Testing the Latent Structure of the Autism Spectrum Quotient in a Sub-clinical Sample of University Students Using Factor Mixture Modelling

In the present study, factor mixture models (FMMs) were used to examine the latent structure underlying the Autism-Spectrum Quotient (AQ) among a sample of 633 undergraduate students. FMM represents a combination of latent-class, person-centered approaches and common-factor, variable-centered approaches to modeling population heterogeneity. Findings suggest the presence of either two or six latent classes with distinct profiles across the set of 50 AQ items. In addition, within each class, individuals can be further differentiated according to their scores on five latent factors. These results suggest the presence of phenotypical heterogeneity at the sub-clinical level in addition to that which is known to exist at the clinical level.

Network Analysis of Internet Addiction Symptoms Among a Clinical Sample of Japanese Adolescents with Autism Spectrum Disorder

In the present study, we employed network analysis that conceptualizes internet addiction (IA) as a complex network of mutually influencing symptoms in 108 adolescents with autism spectrum disorder (ASD) to examine the network architecture of IA symptoms and identify central/influential symptoms. Our analysis revealed that defensive and secretive behaviors and concealment of internet use were identified as central symptoms in this population, suggesting that mitigating these symptoms potentially prevent the development and/or maintenance of IA in adolescents with ASD. Providing adolescents and their caregivers with psychoeducation on the role of central symptoms above in IA can be a salient intervention. Doing so may facilitate nonconflicting conversations between them about adolescents' internet use and promote more healthy adolescents' internet use behavior.