Classifying Autism Spectrum Disorders by ADI-R: Subtypes or Severity Gradient?

Utilising Behavioural and Sensory Profiles and Associated Perinatal Factors to Identify Meaningful Subgroups in Autism Spectrum Disorder

The heterogeneity of autism spectrum disorder (ASD) clinically and aetiologically hinders intervention matching and prediction of outcomes. This study investigated if the behavioural, sensory, and perinatal factor profiles of autistic children could be used to identify distinct subgroups. Participants on the autism spectrum aged 2 to 17 years and their families were sourced via the Australian Autism Biobank (AAB). Latent class analysis was used to identify subgroups within this cohort, utilising twenty-six latent variables representing child's behavioural and sensory features and perinatal factors. Four distinct subgroups within the sample (n = 1168) distinguished by sensory and behavioural autism traits and exposure to perinatal determinants were identified. Class 2 and Class 4, which displayed the greatest behavioural and sensory impairment respectively, were associated with the highest perinatal factor exposure. Class 1, labelled "Most behavioural concerns and moderate sensory and behavioural skills concerns" had mixed exposure to perinatal determinants while Class 3, named "Least sensory and behavioural skills concerns" had the least perinatal determinant exposure, indicating a directly proportional correlation between severity of clinical features and perinatal factor exposure. Additionally, association between specific exposures such as maternal mental illness in Class 1 and significant behavioural concerns was recognised. Identifying distinct subgroups among autistic children can lead to development of targeted interventions and supports. Close monitoring of children exposed to specific perinatal determinants for developmental differences could assist early intervention and supports.

Identification of subgroups of children in the Australian Autism Biobank using latent class analysis

BACKGROUND

The identification of reproducible subtypes within autistic populations is a priority research area in the context of neurodevelopment, to pave the way for identification of biomarkers and targeted treatment recommendations. Few previous studies have considered medical comorbidity alongside behavioural, cognitive, and psychiatric data in subgrouping analyses. This study sought to determine whether differing behavioural, cognitive, medical, and psychiatric profiles could be used to distinguish subgroups of children on the autism spectrum in the Australian Autism Biobank (AAB).

METHODS

Latent profile analysis was used to identify subgroups of children on the autism spectrum within the AAB (n = 1151), utilising data on social communication profiles and restricted, repetitive, and stereotyped behaviours (RRBs), in addition to their cognitive, medical, and psychiatric profiles.

RESULTS

Our study identified four subgroups of children on the autism spectrum with differing profiles of autism traits and associated comorbidities. Two subgroups had more severe clinical and cognitive phenotype, suggesting higher support needs. For the 'Higher Support Needs with Prominent Language and Cognitive Challenges' subgroup, social communication, language and cognitive challenges were prominent, with prominent sensory seeking behaviours. The 'Higher Support Needs with Prominent Medical and Psychiatric and Comorbidity' subgroup had the highest mean scores of challenges relating to social communication and RRBs, with the highest probability of medical and psychiatric comorbidity, and cognitive scores similar to the overall group mean. Individuals within the 'Moderate Support Needs with Emotional Challenges' subgroup, had moderate mean scores of core traits of autism, and the highest probability of depression and/or suicidality. A fourth subgroup contained individuals with fewer challenges across domains (the 'Fewer Support Needs Group').

LIMITATIONS

Data utilised to identify subgroups within this study was cross-sectional as longitudinal data was not available.

CONCLUSIONS

Our findings support the holistic appraisal of support needs for children on the autism spectrum, with assessment of the impact of co-occurring medical and psychiatric conditions in addition to core autism traits, adaptive functioning, and cognitive functioning. Replication of our analysis in other cohorts of children on the autism spectrum is warranted, to assess whether the subgroup structure we identified is applicable in a broader context beyond our specific dataset.

Classifying children with ASD by service utilization and treatment type: A cluster analysis of a nationally representative United States survey

BACKGROUND

If there are patterns of the distribution of services and treatments across the population of people with ASD, these patterns should be based along clinical characteristics or other service needs and not sociodemographic characteristics unrelated to evidence-based care. We examined how individuals in a broad, nationally representative sample "grouped together" based on service utilization and services needed but not covered by insurance. By understanding various treatment patterns, clinicians, researchers, policymakers, and self-advocates and their families can better advocate for high-quality, evidence-based services to be provided equitably.

METHODS

Using the 2011 Survey of Pathways to Diagnosis and Services, a cluster analysis was performed to explore patterns in this population based on medication use, private services use, school-based service use, and services not covered by insurance. Differences in clusters were then explored through multinomial logistic regression.

RESULTS

Six clusters emerged, showing differences in the level of service/medication usage and insurance coverage. Differences across clusters were associated with the level of functional limitation and age at ASD diagnosis. Disparities by insurance type, functional limitation, and age at diagnosis exist among patterns of ASD service provision.

CONCLUSIONS

Our analysis showed that intervention for children with ASD can be across several scales - high and low users of services (both private and school-based), high and low users of medications, and high and low levels of reported non-covered services. The differences were clustered in multiple ways. Further research should incorporate longitudinal and nationally representative data to explore these relationships further.

Parenting children with autism spectrum disorder in the United Arab Emirates: Exploring perceptions towards using the picture exchange communication system to enhance the development of children with autism spectrum disorder

Background

Autism spectrum disorder (ASD) is an interplay between biological, social and environmental factors that impact the development of individuals. However, core characteristics are social, communication and behaviour challenges that restrict children’s participation in society. Consequently, there are discussions regarding the need for society to develop interventions that are geared towards promoting the participation of children with ASD in societies. While the Picture Exchange Communication System (PECS) helps lessen the biological characteristics of children with ASD, its impact has rarely been explored in non-western societies, such as the United Arab Emirates (UAE).

Objectives

The instant study’s purpose was to explore parents’ perceptions of the effectiveness of the PECS on the communicative, social and academic developments of children with ASD in UAE.

Method

The Perception Towards Picture Exchange Communication Scale (PTPECS) was developed to collect data from the participants. The newly developed tool was piloted and validated before being implemented. The participants included 73 caregivers of children with ASD in the UAE.

Results

The following non-parametric tests were conducted: Mann-Whitney U test, Kruskal-Wallis test, and spearman rho. The results revealed that the parents were generally positive about employing the PECS to support the development of their children with ASD. There was also a positive association between using the PECS and improving communication, learning and social skills in children with ASD.

Conclusion

It is imperative that educators and policymakers envisage parents as equal partners in providing rehabilitation services to children with ASD. Various implications, such as the need for continual engagement and empowering parents of children with ASD, are discussed.

Impaired Biological Motion Processing and Motor Skills in Adults with Autistic Traits

The present study explored the relationship between biological motion (BioM) processing, motor skills, and autistic traits within a non-clinical sample of 621 adults (18-73 years, 51.8% female). Results indicated that adults with greater autistic traits also endorsed difficulties associated with developmental coordination disorder (DCD) in childhood and adulthood. Traits associated with autism spectrum disorder and DCD were predictive of BioM processing abilities. The results also revealed sex differences in DCD, autistic traits, and BioM processing. Overall, these findings suggest that adults with greater autistic traits experience both deficits in motor activities as well as underlying motor perceptual abilities.

Altered Cytokine and BDNF Levels in Individuals with Autism Spectrum Disorders

Previous studies have shown that immunological factors are involved in the pathogenesis of autism spectrum disorders (ASDs). The present study examined whether immunological abnormalities are associated with cognitive and behavioral deficits in children with ASD and whether children with ASD show different immunological biomarkers and brain-derived neurotrophic factor BDNF levels than typically developing (TD) children. Sixteen children with TD and 18 children with ASD, aged 6–18 years, voluntarily participated in the study. Participants’ executive functions were measured using neuropsychological tests, and behavioral measures were measured using parent ratings. Immunological measures were assessed by measuring the participants’ blood serum levels of chemokine ligand 2 (CCL2) and chemokine ligand 5 (CCL5). Children with ASD showed greater deficits in cognitive functions as well as altered levels of immunological measures when compared to TD children, and their cognitive functions and behavioral deficits were significantly associated with increased CCL5 levels and decreased BDNF levels. These results provide evidence to support the notion that altered immune functions and neurotrophin deficiency are involved in the pathogenesis of ASD.

Sibling Adjustment and Sibling Relationships Associated with Clusters of Needs in Children with Autism: A Novel Methodological Approach

We tested a novel methodological approach to examine associations between characteristics of autistic children and outcomes for siblings. Cluster analysis was used to define five groups of children with autism (n = 168) based on autism symptoms, adaptive behavior, pro-social behavior, and behavior problems. Primary and secondary parent carers, and siblings themselves, reported on sibling relationship quality and psychological adjustment. Siblings of autistic children with a mild symptom profile, high levels of adaptive skills, but high internalizing and externalizing problems had the highest level of these problems themselves and more conflict in their relationship. Siblings of autistic children with the most complex support needs (adaptive skills deficits, severe autism symptoms) reported lower warmth relationships but not elevated internalizing and externalizing problems.

Virtual voice assistant applications improved expressive verbal abilities and social interactions in children with autism spectrum disorder: a Single-Subject experimental study

The use of interactive technologies has been demonstrated to enhance verbal and non-verbal communication, as well as the social interaction tendencies of children with Autism Spectrum Disorder (ASD). We examined effects of using Virtual Voice Assistant (VVAs) in children with ASD with respect to two outcomes: speech skills and social interaction skills. A single-case study included three children with ASD (4-11 years old) that utilized VVAs for three months. Pre- and post-intervention questionnaires and semi-structured interviews were used to measure the communication and social interaction skills of the participating children. Participant One, Two and Three showed improvement in the number of correct words produced the VVA intervention. All participants showed increases in social interactions in the intervention phase. Overall, the results showed that the VVAs had positive effects on the speech and social interaction skills of autistic children. The findings demonstrate that children with ASD may benefit from VVAs to improve their communication skills.

Environmental Influences Measured by Epigenetic Clock and Vulnerability Components at Birth Impact Clinical ASD Heterogeneity

Although Autism Spectrum Disorders (ASD) is recognized as being heavily influenced by genetic factors, the role of epigenetic and environmental factors is still being established. This study aimed to identify ASD vulnerability components based on familial history and intrauterine environmental stress exposure, explore possible vulnerability subgroups, access DNA methylation age acceleration (AA) as a proxy of stress exposure during life, and evaluate the association of ASD vulnerability components and AA to phenotypic severity measures. Principal Component Analysis (PCA) was used to search the vulnerability components from 67 mothers of autistic children. We found that PC1 had a higher correlation with psychosocial stress (maternal stress, maternal education, and social class), and PC2 had a higher correlation with biological factors (psychiatric family history and gestational complications). Comparing the methylome between above and below PC1 average subgroups we found 11,879 statistically significant differentially methylated probes (DMPs, p < 0.05). DMPs CpG sites were enriched in variably methylated regions (VMRs), most showing environmental and genetic influences. Hypermethylated probes presented higher rates in different regulatory regions associated with functional SNPs, indicating that the subgroups may have different affected regulatory regions and their liability to disease explained by common variations. Vulnerability components score moderated by epigenetic clock AA was associated with Vineland Total score (p = 0.0036, adjR² = 0.31), suggesting risk factors with stress burden can influence ASD phenotype.

Extracting Latent Subdimensions of Social Communication: A Cross-Measure Factor Analysis

OBJECTIVE

Social communication deficits associated with autism spectrum disorder (ASD) are commonly represented as a single behavioral domain. However, increased precision of measurement of social communication is needed to promote more nuanced phenotyping, both within the autism spectrum and across diagnostic boundaries.

METHOD

A large sample (N = 1,470) of 4- to 10-year-old children was aggregated from across 4 data sources, and then randomly split into testing and validation samples. A total of 57 selected social communication items from 3 widely used autism symptom measures (the Autism Diagnostic Observation Scale [ADOS], Autism Diagnostic Interview-Revised [ADI-R], and Social Responsiveness Scale [SRS]) were analyzed in the multi-trait/multi-method factor analysis framework. The selected model was then confirmed with the validation sample.

RESULTS

The 4-substantive factor model, with 3 orthogonal method factors, was selected using the testing sample based on fit indices and then confirmed with the validation sample. Two of the factors, "Basic Social Communication Skills" and "Interaction Quality," were similar to those identified in a previous analysis of the ADOS, Module 3. Two additional factors, "Peer Interaction and Modification of Behavior" and "Social Initiation and Affiliation," also emerged. Factor scores showed nominal correlations with age and verbal IQ.

CONCLUSION

Identification of subdimensions could inform the creation of better conceptual models of social communication impairments, including mapping of how the cascading effects of social communication deficits unfold in ASD versus other disorders. Especially if extended to include both older and younger age cohorts and individuals with more varying developmental levels, these efforts could inform phenotype-based exploration for biological and genetic mechanisms by pinpointing specific mechanisms that contribute to various types of social communication deficits.

Examining Phenotypical Heterogeneity in Language Abilities in Chinese-Speaking Children with Autism: A Naturalistic Sampling Approach

Phenotypical heterogeneity in language abilities is a hallmark of autism but remains poorly understood. The present study collected naturalistic language samples from parent-child interactions. We quantified verbal abilities (mean length of utterance, tokens, types) of 50 Chinese-speaking children (M = 5; 6) and stratified subgroups based on their autism traits, IQ, and language abilities. Using hierarchical cluster analysis, four groups were identified. Group 1, the least affected group, had mild autism, the highest IQ, and the strongest verbal abilities. Group 2, the severely affected group, had the lowest IQ, most severe autism symptoms, and weakest verbal abilities. Group 3 and Group 4 displayed average levels of verbal abilities and IQ. These findings may characterize the heterogeneous profiles of verbal abilities in Chinese-speaking children.

Subgroups of Children with Autism Spectrum Disorder without Intellectual Disability: A Longitudinal Examination of Executive and Socio-Adaptive Behaviors in Adolescence

Within the autistic spectrum, there is remarkable variability in the etiology, presentation, and treatment response. This prospective study was designed to identify, through cluster analysis, subgroups of individuals with ASD without intellectual disability (ID) based on the severity of the core symptoms in childhood. The secondary aim was to explore whether these subgroups and a group with typical development (TD) differ in cognitive, adaptive, and social aspects measured in adolescence. The sample at baseline was comprised of 52 children with ASD without ID and 37 children with TD, aged 7-11. Among the ASD group, three clusters were identified. Cluster 1 (40%), 'high severity', presented high symptom severity on the DSM-5 criteria and the Social Communication Questionnaire. Cluster 2 (34%) showed 'moderate severity' on most of the scores. Cluster 3 (25%) corresponded to 'low severity', showing moderate social impairment and low restrictive, repetitive patterns of behavior, interests and activities. At 5-year follow-up, 45 adolescents with ASD without ID and 27 adolescents with TD were assessed. All clusters had significantly more difficulties in EF, ToM, socialization and adaptive behavior compared to TD. Social and adaptive trajectories between the ASD subgroups were relatively different; Cluster 3 showed poorer socialization and daily living skills than the other two subgroups. These findings highlight the importance of fully assessing social, cognitive, and adaptive profiles to develop care plans tailored to specific needs.

Imbalanced social-communicative and restricted repetitive behavior subtypes of autism spectrum disorder exhibit different neural circuitry

Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97-99%) out-of-sample SC = RRB, SC > RRB, and RRB > SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry.

Validation strategies for subtypes in psychiatry: A systematic review of research on autism spectrum disorder

Heterogeneity within autism spectrum disorder (ASD) is recognized as a challenge to both biological and psychological research, as well as clinical practice. To reduce unexplained heterogeneity, subtyping techniques are often used to establish more homogeneous subtypes based on metrics of similarity and dissimilarity between people. We review the ASD literature to create a systematic overview of the subtyping procedures and subtype validation techniques that are used in this field. We conducted a systematic review of 156 articles (2001-June 2020) that subtyped participants (range N of studies = 17-20,658), of which some or all had an ASD diagnosis. We found a large diversity in (parametric and non-parametric) methods and (biological, psychological, demographic) variables used to establish subtypes. The majority of studies validated their subtype results using variables that were measured concurrently, but were not included in the subtyping procedure. Other investigations into subtypes' validity were rarer. In order to advance clinical research and the theoretical and clinical usefulness of identified subtypes, we propose a structured approach and present the SUbtyping VAlidation Checklist (SUVAC), a checklist for validating subtyping results.

Ageing and heterogeneity regarding autism spectrum conditions: a protocol paper of an accelerated longitudinal study

INTRODUCTION

Autism spectrum conditions (ASC) develop early in life and are thought to last a lifetime. However, ASC research has two major knowledge gaps that hinder progression in understanding the concept of ASC and in providing proper support for autistic adults: (1) the majority of knowledge about ASC mainly stems from childhood studies so little is known about older autistic adults and (2) while it is broadly recognised that ASC is a heterogeneous condition, we do not yet understand the differences in trajectories leading to their future outcome. We aim to fill both knowledge gaps.

METHODS AND ANALYSIS

A multistage overlapping cohort design assessing (cognitive) ageing in ASC is designed to obtain an accelerated longitudinal data set. Data, including a multitude of questionnaires, diagnostics and cognitive tests, are collected over four waves within a 10-year time frame. This will provide information regarding actual changes in quality of life, co-occurring health conditions and cognition as well as the possibility to test external validity and temporal stability in newly formed behavioural subtypes. Participants consist of three groups of adults aged 20-90 years: (1) with a clinical diagnosis of ASC, (2) with a clinical diagnosis of attention deficit hyperactivity disorder (ADHD) but no ASC, (3) no ASC/ADHD (ie, comparison group). The sample size differs between waves and instruments. Detailed analysis plans will be preregistered in AsPredicted or at the Open Science Framework.

ETHICS AND DISSEMINATION

Ethical approval for this study was obtained from the ethical review board of the Department of Psychology of the University of Amsterdam (wave 1 2011-PN-1952 and 2013-PN-2668, wave 2 2015-BC-4270, waves 3 and 4 2018-BC-9285). In line with the funding policies of the grant organisation funding this study, future papers will be published open access.

Phenotypic Subtyping and Re-analyses of Existing Transcriptomic Data from Autistic Probands in Simplex Families Reveal Differentially Expressed and ASD Trait-Associated Genes

Autism spectrum disorder (ASD) describes a collection of neurodevelopmental disorders characterized by core symptoms that include social communication deficits and repetitive, stereotyped behaviors often coupled with restricted interests. Primary challenges to understanding and treating ASD are the genetic and phenotypic heterogeneity of cases that complicates all omics analyses as well as a lack of information on relationships among genes, pathways, and autistic traits. In this study, we re-analyze existing transcriptomic data from simplex families by subtyping individuals with ASD according to multivariate cluster analyses of clinical ADI-R scores that encompass a broad range of behavioral symptoms. We also correlate multiple ASD traits, such as deficits in verbal and non-verbal communication, play and social skills, ritualistic behaviors, and savant skills, with expression profiles using Weighted Gene Correlation Network Analyses (WGCNA). Our results show that subtyping greatly enhances the ability to identify differentially expressed genes involved in specific canonical pathways and biological functions associated with ASD within each phenotypic subgroup. Moreover, using WGCNA, we identify gene modules that correlate significantly with specific ASD traits. Network prediction analyses of the genes in these modules reveal canonical pathways as well as neurological functions and disorders relevant to the pathobiology of ASD. Finally, we compare the WGCNA-derived data on autistic traits in simplex families with analogous data from multiplex families using transcriptomic data from our previous studies. The comparison reveals overlapping trait-associated pathways as well as upstream regulators of the module-associated genes that may serve as useful targets for a precision medicine approach to ASD.

Fractionating autism based on neuroanatomical normative modeling

Autism is a complex neurodevelopmental condition with substantial phenotypic, biological, and etiologic heterogeneity. It remains a challenge to identify biomarkers to stratify autism into replicable cognitive or biological subtypes. Here, we aim to introduce a novel methodological framework for parsing neuroanatomical subtypes within a large cohort of individuals with autism. We used cortical thickness (CT) in a large and well-characterized sample of 316 participants with autism (88 female, age mean: 17.2 ± 5.7) and 206 with neurotypical development (79 female, age mean: 17.5 ± 6.1) aged 6-31 years across six sites from the EU-AIMS multi-center Longitudinal European Autism Project. Five biologically based putative subtypes were derived using normative modeling of CT and spectral clustering. Three of these clusters showed relatively widespread decreased CT and two showed relatively increased CT. These subtypes showed morphometric differences from one another, providing a potential explanation for inconsistent case-control findings in autism, and loaded differentially and more strongly onto symptoms and polygenic risk, indicating a dilution of clinical effects across heterogeneous cohorts. Our results provide an important step towards parsing the heterogeneous neurobiology of autism.

Differences in Language Ability and Emotional-Behavioral Problems according to Symptom Severity in Children with Autism Spectrum Disorder

PURPOSE

The aim of this study was to investigate differences in language ability and emotional-behavioral problems according to the severity of social communication impairments (SCI) and restricted and repetitive behaviors (RRB) in children with autism spectrum disorders (ASD).

MATERIALS AND METHODS

We grouped 113 children with ASD aged 3-12 years according to the severity of SCI and RRB, and investigated language differences and emotional-behavioral problems among the severity groups. If differences in language abilities between the groups were observed, they were further subdivided to examine possible predictors of both receptive and expressive language abilities.

RESULTS

In cluster analyses using subdomains of the Autism Diagnostic Interview-revised, severe SCI individuals showed lower language ability than their milder counterparts, while RRB showed no differences. Receptive and expressive language in the severe SCI group was negatively predicted by social communication and social motivation, respectively. The severe RRB group showed significantly higher levels of anxiety/distress, somatic complaints, thought problems, attention problems, and aggressive behavior, while the severe SCI group was reported to be more withdrawn.

CONCLUSION

The results of this study suggest that the severity of SCI greatly affects language ability. In children with severe SCI, social communication and social motivation negatively predicted receptive language and expressive language, respectively. Children with severe RRB may have more emotional-behavioral problems that require active intervention.

Patterns of autism symptoms: hidden structure in the ADOS and ADI-R instruments

We simultaneously revisited the Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule (ADOS) with a comprehensive data-analytics strategy. Here, the combination of pattern-analysis algorithms and extensive data resources (n = 266 patients aged 7-49 years) allowed identifying coherent clinical constellations in and across ADI-R and ADOS assessments widespread in clinical practice. Our clustering approach revealed low- and high-severity patient groups, as well as a group scoring high only in the ADI-R domains, providing quantitative contours for the widely assumed autism subtypes. Sparse regression approaches uncovered the most clinically predictive questionnaire domains. The social and communication domains of the ADI-R showed convincing performance to predict the patients' symptom severity. Finally, we explored the relative importance of each of the ADI-R and ADOS domains conditioning on age, sex, and fluid IQ in our sample. The collective results suggest that (i) identifying autism subtypes and severity for a given individual may be most manifested in the ADI-R social and communication domains, (ii) the ADI-R might be a more appropriate tool to accurately capture symptom severity, and (iii) the ADOS domains were more relevant than the ADI-R domains to capture sex differences.

Applying Item Response Theory Modeling to Identify Social (Pragmatic) Communication Disorder

Purpose No diagnostic tools exist for identifying social (pragmatic) communication disorder (SPCD), a new Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition category for individuals with social communication deficits but not the repetitive, restricted behaviors and interests (RRBIs) that would qualify them for a diagnosis of autism spectrum disorder (ASD). We explored the value of items from a widely used screening measure of ASD for distinguishing SPCD from typical controls (TC; Aim 1) and from ASD (Aim 2). Method We applied item response theory (IRT) modeling to Social Communication Questionnaire-Lifetime (Rutter, Bailey, & Lord, 2003) records available in the National Database for Autism Research. We defined records from putative SPCD (n = 54), ASD (n = 278), and TC (n = 274) groups retrospectively, based on National Database for Autism Research classifications and Autism Diagnostic Interview-Revised responses. After assessing model assumptions, estimating model parameters, and measuring model fit, we identified items in the social communication and RRBI domains that were maximally informative in differentiating the groups. Results IRT modeling identified a set of seven social communication items that distinguished SPCD from TC with sensitivity and specificity > 80%. A set of five RRBI items was less successful in distinguishing SPCD from ASD (sensitivity and specificity < 70%). Conclusion The IRT modeling approach and the Social Communication Questionnaire-Lifetime item sets it identified may be useful in efforts to construct screening and diagnostic measures for SPCD.

Identification of biological mechanisms underlying a multidimensional ASD phenotype using machine learning

The complex genetic architecture of Autism Spectrum Disorder (ASD) and its heterogeneous phenotype makes molecular diagnosis and patient prognosis challenging tasks. To establish more precise genotype-phenotype correlations in ASD, we developed a novel machine-learning integrative approach, which seeks to delineate associations between patients' clinical profiles and disrupted biological processes, inferred from their copy number variants (CNVs) that span brain genes. Clustering analysis of the relevant clinical measures from 2446 ASD cases in the Autism Genome Project identified two distinct phenotypic subgroups. Patients in these clusters differed significantly in ADOS-defined severity, adaptive behavior profiles, intellectual ability, and verbal status, the latter contributing the most for cluster stability and cohesion. Functional enrichment analysis of brain genes disrupted by CNVs in these ASD cases identified 15 statistically significant biological processes, including cell adhesion, neural development, cognition, and polyubiquitination, in line with previous ASD findings. A Naive Bayes classifier, generated to predict the ASD phenotypic clusters from disrupted biological processes, achieved predictions with a high precision (0.82) but low recall (0.39), for a subset of patients with higher biological Information Content scores. This study shows that milder and more severe clinical presentations can have distinct underlying biological mechanisms. It further highlights how machine-learning approaches can reduce clinical heterogeneity by using multidimensional clinical measures, and establishes genotype-phenotype correlations in ASD. However, predictions are strongly dependent on patient's information content. Findings are therefore a first step toward the translation of genetic information into clinically useful applications, and emphasize the need for larger datasets with very complete clinical and biological information.

Exploring the profiles of children with autism spectrum disorder: association with family factors

This study aimed to identify different profiles of children with autism spectrum disorder (ASD) without intellectual disability (ID) and maternal factors characteristic of these profiles. Participants were 89 children between 7 and 11 years old and their mothers, distributed in two groups, 52 children with ASD and 37 with typical development (TD). Based on the children's adaptive, behavioral, and pragmatic manifestations, three clusters were obtained in the ASD group. Children with the most serious difficulties in all the domains assessed were assigned to Cluster 1, whereas the children in Cluster 3 were characterized by relatively minor problems. Cluster 2 comprised children with moderate difficulties in the different domains. Compared to the TD group, group 1, with 'Serious Difficulties', and group 2, with 'Moderate Difficulties', showed significant differences on all the variables evaluated. Group 3, 'Slight Difficulties', was only significantly differentiated from the group with TD on ASD and attention deficit hyperactivity disorder (ADHD) symptoms, pragmatic competence, and applied theory of mind. Therefore, it was outlined as the purest group and basically manifested core ASD symptoms. In addition, mothers of children in the 'Serious Difficulties' group showed higher stress levels and less use of emotional and instrumental support and acceptance strategies, as well as more mental health problems, than mothers of children in the 'Slight Difficulties' group. The results support the need to assess the presentation of other possible problems in ASD children without ID, and design interventions for parents who may be at risk of experiencing higher levels of stress and have fewer coping strategies.

The Impact of Inhaled Ambient Ultrafine Particulate Matter on Developing Brain: Potential Importance of Elemental Contaminants

Epidemiological studies report associations between air pollution (AP) exposures and several neurodevelopmental disorders including autism, attention deficit disorder, and cognitive delays. Our studies in mice of postnatal (human third trimester brain equivalent) exposures to concentrated ambient ultrafine particles (CAPs) provide biological plausibility for these associations, producing numerous neuropathological and behavioral features of these disorders, including male-biased vulnerability. These findings raise questions about the specific components of AP that underlie its neurotoxicity, which our studies suggest could involve trace elements as candidate neurotoxicants. X-ray fluorescence analyses of CAP chamber filters confirm contamination of AP exposures by multiple elements, including iron (Fe) and sulfur (S). Correspondingly, laser ablation inductively coupled plasma mass spectrometry of brains of male mice indicates marked postexposure elevations of Fe and S and other elements. Elevations of brain Fe and S in particular are consistent with potential ferroptotic, oxidative stress, and altered antioxidant capacity-based mechanisms of CAPs-induced neurotoxicity, supported by observations of increased serum oxidized glutathione and increased neuronal cell death in nucleus accumbens with no corresponding significant increase in caspase-3, in male brains following postnatal CAP exposures. Understanding the role of trace element contaminants of particulate matter AP as a source of neurotoxicity is critical for public health protection.

Big data approaches to decomposing heterogeneity across the autism spectrum

Autism is a diagnostic label based on behavior. While the diagnostic criteria attempt to maximize clinical consensus, it also masks a wide degree of heterogeneity between and within individuals at multiple levels of analysis. Understanding this multi-level heterogeneity is of high clinical and translational importance. Here we present organizing principles to frame research examining multi-level heterogeneity in autism. Theoretical concepts such as 'spectrum' or 'autisms' reflect non-mutually exclusive explanations regarding continuous/dimensional or categorical/qualitative variation between and within individuals. However, common practices of small sample size studies and case-control models are suboptimal for tackling heterogeneity. Big data are an important ingredient for furthering our understanding of heterogeneity in autism. In addition to being 'feature-rich', big data should be both 'broad' (i.e., large sample size) and 'deep' (i.e., multiple levels of data collected on the same individuals). These characteristics increase the likelihood that the study results are more generalizable and facilitate evaluation of the utility of different models of heterogeneity. A model's utility can be measured by its ability to explain clinically or mechanistically important phenomena, and also by explaining how variability manifests across different levels of analysis. The directionality for explaining variability across levels can be bottom-up or top-down, and should include the importance of development for characterizing changes within individuals. While progress can be made with 'supervised' models built upon a priori or theoretically predicted distinctions or dimensions of importance, it will become increasingly important to complement such work with unsupervised data-driven discoveries that leverage unknown and multivariate distinctions within big data. A better understanding of how to model heterogeneity between autistic people will facilitate progress towards precision medicine for symptoms that cause suffering, and person-centered support.

Prevalence and Characteristics of Autism Spectrum Disorder Among Spanish School-Age Children

The present study aims to assess the prevalence of autism spectrum disorder (ASD) in preschool and school-age children following a two-phase procedure. The screening phase was performed on a sample of 5555 children taking into account parent and teacher information. The individual assessment included the ADI-R, ADOS-2 and Wechsler scales. The estimated prevalence was 1.55% in preschoolers and 1.00% in school-age children. Between 1.84 and 2.59% of the children exhibited subclinical diagnosis. The male-to-female ratio was around 4:1. Most of the children exhibited mild and moderate nuclear symptoms, and the girls showed less severe communication problems. Previous diagnosis was found in 62-71% of the children. Prevalence estimates are close to the 1% international ratings and much higher than previous national reports suggested.

Behavioral characteristics of autism spectrum disorder in very preterm birth children

Background

Lower gestational age may increase autism spectrum disorder (ASD) vulnerability; however, the incidence of ASD diagnosis through a direct assessment on every very preterm birth child on the population base remains unclear. Moreover, the behavioral characteristics of preterm birth ASD are unknown.

Methods

Every very preterm birth child (gestational age < 32 weeks; birth weight < 1500 g) who was discharged from neonatal intensive care units in Southern Taiwan and prospectively followed to 5 years of age was evaluated using the Autism Diagnostic Observation Schedule (ADOS) and the Autism Diagnostic Interview-Revised (ADI-R). The term birth (gestational age > 37 weeks) ASD children characterized by ADOS and ADI-R were group matched to the preterm birth ASD by age at examination for comparison. ADOS severity scores were calculated by the Mann-Whitney U test and ADI-R by multivariate analysis of variance and canonical discriminant analysis.

Results

Two hundred forty-six (87%) of the 283 very preterm survivors were followed prospectively to 5 years of age. Nineteen (7.7%) of the 246 children fulfilled the diagnostic criteria of ASD. After excluding 1 patient with cerebral palsy and profound mental disability, 18 preterm ASD children were compared with 44 term birth ASD children. The two ASD groups were comparable for age at examination, gender, and intelligence quotient. The two groups showed comparable ADOS severity scores in social affect deficits, restricted repetitive behaviors, and total score, but had differences in qualitative abnormalities in reciprocal social interaction (Wilks lambda F value = 6.2, P < 0.001) of ADI-R. Compared to term birth ASD children, preterm birth ASD children exhibited worse nonverbal behaviors that regulate social interaction (OR 2.59, 95% CI 1.41-4.73, P = 0.002) but more favorable peer relationships (OR 0.58, 95% CI 0.38-0.90, P = 0.01) and socioemotional reciprocity (OR 0.55, 95% CI 0.33-0.92, P = 0.02). In contrast to the heterogeneous severity of social reciprocity in the term ASD group, the behavioral characteristics of the preterm ASD group showed a homogeneous reciprocal social interaction pattern.

Conclusions

The 5-year incidence rate of ASD was high in very preterm birth children. Preterm birth ASD exhibited a specific behavioral phenotype of reciprocal social interaction.

Comprehensive Analysis of Rare Variants of 101 Autism-Linked Genes in a Hungarian Cohort of Autism Spectrum Disorder Patients

Background

Autism spectrum disorder (ASD) is genetically and phenotypically heterogeneous. Former genetic studies suggested that both common and rare genetic variants play a role in the etiology. In this study, we aimed to analyze rare variants detected by next generation sequencing (NGS) in an autism cohort from Hungary.

Methods

We investigated the yield of NGS panel sequencing of an unselected ASD cohort (N = 174 ) for the detection of ASD associated syndromes. Besides, we analyzed rare variants in a common disease-rare variant framework and performed rare variant burden analysis and gene enrichment analysis in phenotype based clusters.

Results

We have diagnosed 13 molecularly proven syndromic autism cases. Strongest indicators of syndromic autism were intellectual disability, epilepsy or other neurological plus symptoms. Rare variant analysis on a cohort level confirmed the association of five genes with autism (AUTS2, NHS, NSD1, SLC9A9, and VPS13). We found no correlation between rare variant burden and number of minor malformation or autism severity. We identified four phenotypic clusters, but no specific gene was enriched in a given cluster.

Conclusion

Our study indicates that NGS panel gene sequencing can be useful, where the clinical picture suggests a clinically defined syndromic autism. In this group, targeted panel sequencing may provide reasonable diagnostic yield. Unselected NGS panel screening in the clinic remains controversial, because of uncertain utility, and difficulties of the variant interpretation. However, the detected rare variants may still significantly influence autism risk and subphenotypes in a polygenic model, but to detect the effects of these variants larger cohorts are needed.

Extreme enhancement or depletion of serotonin transporter function and serotonin availability in autism spectrum disorder

A variety of human and animal studies support the hypothesis that serotonin (5-hydroxytryptamine or 5-HT) system dysfunction is a contributing factor to the development of autism in some patients. However, many questions remain about how developmental manipulation of various components that influence 5-HT signaling (5-HT synthesis, transport, metabolism) persistently impair social behaviors. This review will summarize key aspects of central 5-HT function important for normal brain development, and review evidence implicating perinatal disruptions in 5-HT signaling in the pathophysiology of autism spectrum disorder. We discuss the importance, and relative dearth, of studies that explore the possible correlation to autism in the interactions between important intrinsic and extrinsic factors that may disrupt 5-HT homeostasis during development. In particular, we focus on exposure to 5-HT transport altering mechanisms such as selective serotonin-reuptake inhibitors or genetic polymorphisms in primary or auxiliary transporters of 5-HT, and how they relate to neurological stores of serotonin and its precursors. A deeper understanding of the many mechanisms by which 5-HT signaling can be disrupted, alone and in concert, may contribute to an improved understanding of the etiologies and heterogeneous nature of this disorder. We postulate that extreme bidirectional perturbations of these factors during development likely compound or synergize to facilitate enduring neurochemical changes resulting in insufficient or excessive 5-HT signaling, that could underlie the persistent behavioral characteristics of autism spectrum disorder.

Associations between parental broader autism phenotype and child autism spectrum disorder phenotype in the Study to Explore Early Development

The autism spectrum disorder phenotype varies by social and communication ability and co-occurring developmental, behavioral, and medical conditions. Etiology is also diverse, with myriad potential genetic origins and environmental risk factors. Examining the influence of parental broader autism phenotype-a set of sub-clinical characteristics of autism spectrum disorder-on child autism spectrum disorder phenotypes may help reduce heterogeneity in potential genetic predisposition for autism spectrum disorder. We assessed the associations between parental broader autism phenotype and child phenotype among children of age 30-68 months enrolled in the Study to Explore Early Development (N = 707). Child autism spectrum disorder phenotype was defined by a replication of latent classes derived from multiple developmental and behavioral measures: Mild Language Delay with Cognitive Rigidity, Mild Language and Motor Delay with Dysregulation (e.g. anxiety/depression), General Developmental Delay, and Significant Developmental Delay with Repetitive Motor Behaviors. Scores on the Social Responsiveness Scale-Adult measured parent broader autism phenotype. Broader autism phenotype in at least one parent was associated with a child having increased odds of being classified as mild language and motor delay with dysregulation compared to significant developmental delay with repetitive motor behaviors (odds ratio: 2.44; 95% confidence interval: 1.16, 5.09). Children of parents with broader autism phenotype were more likely to have a phenotype qualitatively similar to broader autism phenotype presentation; this may have implications for etiologic research.

Review of cluster analysis of phenotypic data in Autism Spectrum Disorders: distinct subtypes or a severity gradient model?

Background: Individuals with autism spectrum disorder (ASD) form a heterogeneous group, posing a challenge for clinical definition. Additional problems regarding the diverse clinical presentation arise from changes in diagnostic criteria according to the latest Diagnostic and Statistical Manual of Mental Disorders (DSM-5), with exclusion of individuals who met earlier criteria or inclusion of more than previously. Objectives: To investigate studies that have attempted to reduce the heterogeneity of ASD based on cluster analysis of phenotypic data and to clarify whether ASD should be interpreted as 'a unitary spectrum,' with a severity gradient, or defined by distinct subtypes. This will allow better understanding of the disorder with implications for its treatment and prognosis. Methods: A literature search was made through PubMed, Researchgate and Google Scholar for studies of ASD populations. In addition, reference lists from identified studies were reviewed. Results: Only 10 studies were found that dealt with the heterogeneity of ASD and its different subtypes, based on the review prerequisites. Most of the studies appear to support the existence of subtypes within ASD, but it remains unclear whether these are considered as different specific subtypes with characteristic profiles of symptoms or as a part of a severity gradient across symptom domains. Conclusions: Drawing definitive conclusions from the published studies about the nature of ASD is difficult, due to the fundamental methodological differences among the studies and their inconsistent findings. This review shed light on a number of discrepancies regarding the current classification of ASD. However, future research will be necessary to provide a more definite answer on the question of a definition based on separate diagnostic subtypes or on a severity gradient by including larger samples that are followed longitudinal and by applying better diagnostic system and choosing the appropriate variables.

Parsing brain structural heterogeneity in males with autism spectrum disorder reveals distinct clinical subtypes

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with considerable neuroanatomical heterogeneity. Thus, how and to what extent the brains of individuals with ASD differ from each other is still unclear. In this study, brain structural MRI data from 356 right-handed, male subjects with ASD and 403 right-handed male healthy controls were selected from the Autism Brain Image Data Exchange database (age range 5-35 years old). Voxel-based morphometry preprocessing steps were conducted to compute the gray matter volume maps for each subject. Individual neuroanatomical difference patterns for each ASD individual were calculated. A data-driven clustering method was next utilized to stratify individuals with ASD into several subtypes. Whole-brain functional connectivity and clinical severity were compared among individuals within the ASD subtypes identified. A searchlight analysis was applied to determine whether subtyping ASD could improve the classification accuracy between ASD and healthy controls. Three ASD subtypes with distinct neuroanatomical difference patterns were revealed. Different degrees of clinical severity and atypical brain functional connectivity patterns were observed among these three subtypes. By dividing ASD into three subtypes, the classification accuracy between subjects of two out of the three subtypes and healthy controls was improved. The current study confirms that ASD is not a disorder with a uniform neuroanatomical signature. Understanding neuroanatomical heterogeneity in ASD could help to explain divergent patterns of clinical severity and outcomes.

Broader autism phenotype in parents of children with autism: a systematic review of percentage estimates

The broader autism phenotype (BAP) is a collection of sub-diagnostic autistic traits more common in families of individuals with autism spectrum disorder (ASD) than in the general population. BAP is a latent construct that can be defined using different domains, measured using multiple instruments, and reported using different techniques. Therefore, estimates of BAP may vary greatly across studies. Our objective was to systematically review studies that reported occurrence of BAP in parents of children with ASD in order to quantify and describe heterogeneity in estimates. We systematically searched PubMed and Scopus using PRISMA guidelines for studies quantifying percentage of parents of children with ASD who had BAP We identified 41 studies that measured BAP in parents of children with ASD. These studies used eight different instruments, four different forms of data collection, and had a wide range of sample sizes (N=4 to N=3299). Percentage with BAP ranged from 2.6% to 80%. BAP was more prevalent in fathers than mothers. Parental BAP may be an important tool for parsing heterogeneity in ASD etiology and for developing parent-mediated ASD interventions. However, the variety in measurement instruments and variability in study samples limits our ability to synthesize estimates. To improve measurement of BAP and increase consistency across studies, universal methods should be accepted and adopted across studies. A more consistent approach to BAP measurement may enable efficient etiologic research that can be meta-analyzed and may allow for a larger evidence base that can be used to account for BAP when developing parent-mediated interventions.

Measuring the Diagnostic Features of Social (Pragmatic) Communication Disorder: An Exploratory Study

PURPOSE

The Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition introduced a new neurodevelopmental disorder, social (pragmatic) communication disorder (SPCD), that is characterized by deficits in 4 areas of communication. Although descriptions of these areas are provided, no assessment tools for SPCD are recommended. The purpose of this study was to examine the extent to which items from measurement tools commonly used in assessing pragmatic language impairment and related disorders might be useful in assessing the characteristics of social communication that define SPCD in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition.

METHOD

Based on a literature search, 594 items from assessment tools commonly used to measure social communication abilities in people with pragmatic language impairment were identified. The first author judged whether each item reflected 1, more than 1, or none of the 4 SPCD diagnostic characteristics. After a brief training process, 5 second raters independently mapped subsets of items to the 6 categories. We calculated the percentage of agreement and Cohen's kappa for each pair of raters in assigning items to categories.

RESULTS

Percentages of agreement ranged from 76% to 82%, and Cohen's kappa values ranged from .69 to .76, indicating substantial agreement. Sources and item numbers for the 206 items that both raters assigned to the same SPCD feature are provided.

CONCLUSIONS

These items may provide guidance in assessing SPCD and in designing standardized screening and diagnostic measures for SPCD.

Factors influencing the severity of behavioral phenotype in autism spectrum disorders: Implications for research

The phenotypic heterogeneity of Autism Spectrum Disorders (ASD) presents particular research challenges in the assessment of symptom severity, while the standardized Autism Diagnostic Observation Schedule (ADOS) scores present a severity metric, namely calibrated severity scores (CSS) that are relatively impervious to individual characteristics. To date, no studies have examined the convergent validity of CSS in Chinese sample populations. The present study investigated the validity of the ADOS-CSS using a sample of 321 children aged 2-18 years with ASD, and developed upon existing literature examining the influence of non-ASD-specific characteristics on other types of measures including Autism Diagnostic Interview-Revised (ADI-R), Social Responsiveness Scale (SRS), and Vineland Adaptive Behavior Scales (VABS). As expected, the findings revealed that the CSS were less influenced than ADOS-RAW scores by the demographic and developmental-level variables. Moreover, compared to the ADOS-CSS, the ADI-R, SRS and VABS were still strongly correlated with confounding factors, such as chronological age, intelligence quotients, and language-level. The results of this study corroborate the utilization of CSS as a more valid indicator of ASD severity than raw scores from ADOS and other instruments.

A Biomarker Characterizing Neurodevelopment with applications in Autism

Despite great advances in neuroscience and genetic studies, our understanding of neurodevelopmental disorders is still quite limited. An important reason is not having objective psychiatric clinical tests. Here we propose a quantitative neurodevelopment assessment by studying natural movement outputs. Movement is central to behaviors: It involves complex coordination, temporal alterations, and precise dynamic controls. We carefully analyzed the continuous movement output data, collected with high definition electromagnetic sensors at millisecond time scales. We unraveled new metrics containing striking physiological information that was unseen neither by using traditional motion assessments nor by naked eye observations. Our putative biomarker leads to precise individualized classifications. It illustrates clear differences between Autism Spectrum Disorder (ASD) subjects from mature typical developing (TD) individuals. It provides an ASD complementary quantitative classification, which closely agrees with the clinicaly assessed functioning levels in the spectrum. It also illustrates TD potential age-related neurodevelopmental trajectories. Applying our movement biomarker to the parents of the ASD individuals studied in the cohort also shows a novel potential familial signature ASD tie. This paper proposes a putative behavioral biomarker to characterize the level of neurodevelopment with high predicting power, as illustrated in ASD subjects as an example.

Resources available for autism research in the big data era: a systematic review

Recently, there has been a move encouraged by many stakeholders towards generating big, open data in many areas of research. One area where big, open data is particularly valuable is in research relating to complex heterogeneous disorders such as Autism Spectrum Disorder (ASD). The inconsistencies of findings and the great heterogeneity of ASD necessitate the use of big and open data to tackle important challenges such as understanding and defining the heterogeneity and potential subtypes of ASD. To this end, a number of initiatives have been established that aim to develop big and/or open data resources for autism research. In order to provide a useful data reference for autism researchers, a systematic search for ASD data resources was conducted using the Scopus database, the Google search engine, and the pages on 'recommended repositories' by key journals, and the findings were translated into a comprehensive list focused on ASD data. The aim of this review is to systematically search for all available ASD data resources providing the following data types: phenotypic, neuroimaging, human brain connectivity matrices, human brain statistical maps, biospecimens, and ASD participant recruitment. A total of 33 resources were found containing different types of data from varying numbers of participants. Description of the data available from each data resource, and links to each resource is provided. Moreover, key implications are addressed and underrepresented areas of data are identified.

Relationship between adipic acid concentration and the core symptoms of autism spectrum disorders

Dicarboxylic acids are an important source of information about metabolism and potential physiopathological alterations in children with autism spectrum disorders (ASDs). We measured the concentration between dicarboxylic adipic and suberic acids in children with an ASD and typically-developing (TD) children and analyzed any relationships between the severity of the core symptoms of ASDs and other clinical features (drugs, supplements, drugs, or diet). The core symptoms of autism were evaluated using the DSM-IV criteria, and adipic acid and suberic acid were measured in urine samples. Overall, no increase in the concentration of adipic acid in children with ASDs compared to TD children, however when considering vitamin B supplementation in ASD there were significantly increased level of urinary adipic acid in children with an ASD not taking vitamin B supplementation compared to supplemented children or to TD children. No significant difference were observed in suberic acid. Interestingly, the increase in adipic acid concentration was significantly and indirectly correlated with the severity of the deficit in socialization and communication skills in children with an ASD. Therefore, therapeutic treatments aimed at decreasing adipic acid concentration might not be beneficial for treating the core symptoms of ASDs.