Evidence for latent classes of IQ in young children with autism spectrum disorder

Examining Phenotypical Heterogeneity and its Underlying Factors in Gesture Skills of Chinese Autistic Children: Clustering Analysis

PURPOSE

The heterogeneity of autism is well documented, but few studies have studied the heterogeneity of gesture production ability in autistic children. The present study aimed to identify subgroups of autistic children who displayed heterogeneous gesture production abilities and explore the underlying factors, including autism characteristics, intellectual ability, and language ability, that were associated with the heterogeneity.

METHODS

A total of 65 Chinese autistic children (mean age = 5;3) participated. Their autism characteristics and intellectual ability were assessed by standardized measurements. Language output and gesture production were captured from a parent-child interaction task.

RESULTS

We conducted a hierarchical cluster analysis and identified four distinct clusters. Cluster 1 and Cluster 2 both had low gesture production whereas Cluster 3 and Cluster 4 had high gesture production. Both Clusters 1 and 2 had relatively strong autism characteristics, in comparison to Clusters 3 and 4.

CONCLUSIONS

Our findings revealed that children with stronger autism characteristics may gesture less often than those with weaker characteristics. However, the relationship between language ability and intellectual ability and gesture production was not clear. These findings shed light on the directions of intervention on gesture production for autistic children, especially those with stronger autism characteristics.

Studies assessing domains pertaining to structural language in autism vary in reporting practices and approaches to assessment: A systematic review

LAY ABSTRACT

Under the Diagnostic and Statistical Manual of Mental Disorders (5th ed.), language impairment can co-occur with autism. It is not yet clear how research defines, reports, and characterizes structural language abilities of autistic individuals eligible for school-based special education services (aged 3-21 years) in the United States. In the United States, students typically must be formally diagnosed to be eligible for services and supports. However, the quality of diagnosis is only as good as the research evidence on which diagnosis depends. To evaluate evidence quality, we examined how studies of school-aged autistic individuals report assessments of language ability. This systematic review included 57 studies using English language age-referenced assessments used to measure structural language. Findings showed many differences across studies in how language abilities were measured and reported. Also, none of the studies fully reported the variables relevant to characterizing language impairment. Outcomes were similar across versions of the Diagnostic and Statistical Manual of Mental Disorders. Findings indicate that researchers and clinicians should pay attention to reporting diagnostic and grouping criteria. Carefully interpreting research evidence is critical for ensuring that diagnostic criteria and supports are representative of and accessible to autistic individuals and relevant parties.

Patterns of spontaneous neural activity associated with social communication abilities among infants and toddlers showing signs of autism

Early disruptions to social communication development, including delays in joint attention and language, are among the earliest markers of autism spectrum disorder (autism, henceforth). Although social communication differences are a core feature of autism, there is marked heterogeneity in social communication-related development among infants and toddlers exhibiting autism symptoms. Neural markers of individual differences in joint attention and language abilities may provide important insight into heterogeneity in autism symptom expression during infancy and toddlerhood. This study examined patterns of spontaneous electroencephalography (EEG) activity associated with joint attention and language skills in 70 community-referred 12- to 23-month-olds with autism symptoms and elevated scores on an autism diagnostic instrument. Data-driven cluster-based permutation analyses revealed significant positive associations between relative alpha power (6-9 Hz) and concurrent response to joint attention skills, receptive language, and expressive language abilities. Exploratory analyses also revealed significant negative associations between relative alpha power and measures of core autism features (i.e., social communication difficulties and restricted/repetitive behaviors). These findings shed light on the neural mechanisms underlying typical and atypical social communication development in emerging autism and provide a foundation for future work examining neural predictors of social communication growth and markers of intervention response.

Differences in regional brain structure in toddlers with autism are related to future language outcomes

Language and social symptoms improve with age in some autistic toddlers, but not in others, and such outcome differences are not clearly predictable from clinical scores alone. Here we aim to identify early-age brain alterations in autism that are prognostic of future language ability. Leveraging 372 longitudinal structural MRI scans from 166 autistic toddlers and 109 typical toddlers and controlling for brain size, we find that, compared to typical toddlers, autistic toddlers show differentially larger or thicker temporal and fusiform regions; smaller or thinner inferior frontal lobe and midline structures; larger callosal subregion volume; and smaller cerebellum. Most differences are replicated in an independent cohort of 75 toddlers. These brain alterations improve accuracy for predicting language outcome at 6-month follow-up beyond intake clinical and demographic variables. Temporal, fusiform, and inferior frontal alterations are related to autism symptom severity and cognitive impairments at early intake ages. Among autistic toddlers, brain alterations in social, language and face processing areas enhance the prediction of the child's future language ability.

Profiles of minimally verbal autistic children: Illuminating the neglected end of the spectrum

Heterogeneity among individuals on the autism spectrum is widely acknowledged as a barrier to develop effective interventions. Overcoming this challenge requires characterization of individual differences, especially for children that are minimally verbal and often excluded from research studies. Most studies that describe autistic subgroups identify a single minimally verbal verbal group based on a single identifying measure (e.g., ADOS module one or single item indicating absence of phrase speech). Determining personalized courses of intervention requires a more detailed understanding since a single intervention will not be effective for all who are minimally verbal. The present study identified comprehensive profiles of cognitive, language, and social communication skills within a large, diverse, group of minimally verbal children with autism. The analysis combined baseline data from two studies to yield a sample of 344 participants, who were 3 to 8 years old at the time of study onset, with 60% who identified as having a race/ethnicity other than White. Via latent profile analysis (LPA), a three-group model was identified as best fit to the data. Profile identification was dependent on a participant's combination of cognitive, expressive, and social communication characteristics, rather than a single domain. One group (n = 206) had global delays, while the other two groups (n = 95 and n = 43) had variable strengths in cognition and communication. Findings suggest that low-frequency/minimally verbal communicators with autism have heterogeneous characteristics that can be systematically organized.

Reduced covariation between brain morphometry and local spontaneous activity in young children with ASD

While disruptions in brain maturation in the first years of life in ASD are well documented, little is known about how the brain structure and function are related in young children with ASD compared to typically developing peers. We applied a multivariate pattern analysis to examine the covariation patterns between brain morphometry and local brain spontaneous activity in 38 toddlers and preschoolers with ASD and 31 typically developing children using T1-weighted structural MRI and resting-state fMRI data acquired during natural sleep. The results revealed significantly reduced brain structure-function correlations in ASD. The resultant brain structure and function composite indices were associated with age among typically developing children, but not among those with ASD, suggesting mistiming of typical brain maturational trajectories early in life in autism. Additionally, the brain function composite indices were associated with the overall developmental and adaptive behavior skills in the ASD group, highlighting the neurodevelopmental significance of early local brain activity in autism.

Community-based Agency Delivery of Parent-Child Interaction Therapy: Comparing Outcomes for Children with and Without Autism Spectrum Disorder and/or Developmental Delays

While externalizing behaviors are common among children with autism spectrum disorder (ASD), there is a shortage of specialist community-based clinicians to provide treatment. Parent-Child Interaction Therapy (PCIT), an intervention designed to reduce child disruptive behaviors, may be effective for families of children with ASD but has rarely been studied outside of university-based research settings. We examined the effectiveness of PCIT delivered for children with (N = 109) and without (N = 2,324) ASD/developmental delays (DD) across community-based agencies in Oregon. Findings revealed significant reductions in disruptive behavior and positive changes in the parent-child relationship in both groups. These findings support PCIT as an efficacious intervention for children with ASD/DD and demonstrate PCIT's promise in community-based agencies with non-specialized clinicians.

Profiling Autism and Attention Deficit Hyperactivity Disorder Traits in Children with SYNGAP1-Related Intellectual Disability

SYNGAP1-related ID is a genetic condition characterised by global developmental delay and epilepsy. Individuals with SYNGAP1-related ID also commonly show differences in attention and social communication/interaction and frequently receive additional diagnoses of Autism Spectrum Disorder (ASD) or Attention Deficit Hyperactivity Disorder (ADHD). We thus set out to quantify ASD and ADHD symptoms in children with this syndrome. To assess ASD and ADHD, parents and caregivers of a child with SYNGAP1-related ID (N = 34) or a typically developing control (N = 21) completed the Social Responsiveness Scale-2, the Social Communication Questionnaire with a subset of these also completing the Conners-3. We found that those with SYNGAP1-related ID demonstrated higher levels of autistic traits on both the SRS and SCQ than typically developing controls. On the SRS, those with SYNGAP1-related ID scored highest for restricted repetitive behaviours, and were least impaired in social awareness. On the Conners-3, those with SYNGAP1-related ID also showed a high prevalence of ADHD traits, with scores demonstrating difficulties with peer relations but relatively low occurrence of symptoms for DSM-5 conduct disorder and DSM-5 oppositional defiant disorder. Hierarchical clustering analysis highlighted distinct SYNGAP1-related ID subgroups for both ASD and ADHD traits. These findings provide further characterisation of the SYNGAP1-related ID behavioural phenotype, guiding diagnosis, assessment and potential interventions.

Comparison between the socio-educational profiles of children with verbal and non-verbal Autism Spectrum Disorder

PURPOSE

Compare the psychoeducational profiles of children with verbal and non-verbal Autism Spectrum Disorder (ASD).

METHODS

Cross-sectional study conducted with a sample of 30 children with a medical diagnosis of ASD (15 verbal and 15 non-verbal) aged 2-9 years. The Psychoeducational Profile-Revised (PEP-R) scale was applied to assess the children's development. The data were analyzed quantitatively and comparatively. Analysis of covariance (ANCOVA) was performed to evaluate the compatibility between the groups regarding the scores obtained in each PEP-R area, with chronological age as the covariate, and Student's t-Test was used for the independent samples (p≤0.001).

RESULTS

The scores in the different areas of the PEP-R were higher in the verbal group, with associations between language development and cognitive and social adaptive skills in the studied sample. Comparison between the groups showed a lower profile of the non-verbal group, with statistically significant differences in the areas of imitation, perception, gross and fine motor coordination, eye-hand coordination, cognitive performance, and verbal performance.

CONCLUSION

The goal of comparing the psychoeducational profiles of verbal and non-verbal ASD children was reached, and statistically significant differences were observed. The children with non-verbal ASD presented a lower psychoeducational profile compared with that of verbal ASD children. Further studies with larger samples, delimited age groups, and more specific tests in each developmental area are suggested.

Examining the validity of the use of ratio IQs in psychological assessments

Intelligence tests are amongst the most used psychological assessments, both in research and clinical settings. To avoid missing data points, for participants who cannot complete Intelligence tests normed for their age, ratio IQ scores (RIQ) are routinely computed and used as a proxy of IQ. Here, we use the case of autism to examine the validity of this widely used, yet never scientifically validated, practice. We examine the differences between standard full-scale IQ (FSIQ) and RIQ. Data was extracted from four databases in which age, FSIQ scores and subtests raw scores (from which RIQ scores could be calculated) were available for 16,751 autistic participants between 2 and 18 years old. The Intelligence tests included were the MSEL (N = 12,033), DAS-II early years (N = 1270), DAS-II school age (N = 2848), WISC-IV (N = 471) and WISC-V (N = 129). RIQs were computed for each participant as well as the discrepancy (DSC) between RIQ and FSIQ. We performed a multiple linear regression model to assess the effects of age and FSIQ on DSC for each IQ test. Participants at the extremes of the FSIQ distribution tended to have a greater DSC than participants with average FSIQ. Furthermore, age significantly predicted the DSC, with RIQ superior to FSIQ for younger participants while the opposite was found for older participants. Similar results were found in secondary analyses including typically developing children. These results question the validity of the RIQ as an alternative scoring method, especially for individuals at the extremes of the normal distribution, for whom RIQs are most often employed.

Different levels of visuospatial abilities linked to differential brain correlates underlying visual mental segmentation processes in autism

The neural underpinnings of enhanced locally oriented visual processing that are specific to autistics with a Wechsler's Block Design (BD) peak are largely unknown. Here, we investigated the brain correlates underlying visual segmentation associated with the well-established autistic superior visuospatial abilities in distinct subgroups using functional magnetic resonance imaging. This study included 31 male autistic adults (15 with (AUTp) and 16 without (AUTnp) a BD peak) and 28 male adults with typical development (TYP). Participants completed a computerized adapted BD task with models having low and high perceptual cohesiveness (PC). Despite similar behavioral performances, AUTp and AUTnp showed generally higher occipital activation compared with TYP participants. Compared with both AUTnp and TYP participants, the AUTp group showed enhanced task-related functional connectivity within posterior visuoperceptual regions and decreased functional connectivity between frontal and occipital-temporal regions. A diminished modulation in frontal and parietal regions in response to increased PC was also found in AUTp participants, suggesting heavier reliance on low-level processing of global figures. This study demonstrates that enhanced visual functioning is specific to a cognitive phenotypic subgroup of autistics with superior visuospatial abilities and reinforces the need to address autistic heterogeneity by good cognitive characterization of samples in future studies.

Relationship between quantitative digital behavioral features and clinical profiles in young autistic children

Early behavioral markers for autism include differences in social attention and orienting in response to one's name when called, and differences in body movements and motor abilities. More efficient, scalable, objective, and reliable measures of these behaviors could improve early screening for autism. This study evaluated whether objective and quantitative measures of autism-related behaviors elicited from an app (SenseToKnow) administered on a smartphone or tablet and measured via computer vision analysis (CVA) are correlated with standardized caregiver-report and clinician administered measures of autism-related behaviors and cognitive, language, and motor abilities. This is an essential step in establishing the concurrent validity of a digital phenotyping approach. In a sample of 485 toddlers, 43 of whom were diagnosed with autism, we found that CVA-based gaze variables related to social attention were associated with the level of autism-related behaviors. Two language-related behaviors measured via the app, attention to people during a conversation and responding to one's name being called, were associated with children's language skills. Finally, performance during a bubble popping game was associated with fine motor skills. These findings provide initial support for the concurrent validity of the SenseToKnow app and its potential utility in identifying clinical profiles associated with autism. Future research is needed to determine whether the app can be used as an autism screening tool, can reliably stratify autism-related behaviors, and measure changes in autism-related behaviors over time.

Remote Assessment: Origins, Benefits, and Concerns

Although guidelines surrounding COVID-19 have relaxed and school-aged students are no longer required to wear masks and social distance in schools, we have become, as a nation and as a society, more comfortable working from home, learning online, and using technology as a platform to communicate ubiquitously across ecological environments. In the school psychology community, we have also become more familiar with assessing students virtually, but at what cost? While there is research suggesting score equivalency between virtual and in-person assessment, score equivalency alone is not sufficient to validate a measure or an adaptation thereof. Furthermore, the majority of psychological measures on the market are normed for in-person administration. In this paper, we will not only review the pitfalls of reliability and validity but will also unpack the ethics of remote assessment as an equitable practice.

Multimodal interaction analysis of non-lexical vocalisations in low-verbal autistic children

This article analyses non-lexical vocalisations produced by low-verbal autistic children. Seven dyads of naturalistic interactions between non-autistic adults and low-verbal autistic children over five years old were analysed from a multimodal conversation analysis perspective. Data were extracted from an audio-visual corpus of interactions in institutional (school) and non-institutional settings (home). The data are in Brazilian Portuguese. The videos are visualised using the ELAN tool and transcribed. The analyses showed that in some cases participants did not reach a mutual understanding of the semantic meaning of non-lexical vocalisations, while in other cases, the meanings of vocalisations emerged between the participants in the multimodal process of sense-making in their embodied context. A microanalysis of where these vocalisations occurred and their multimodal aspects (linguistics, bodily, material, and spatial) suggests that: a) such occurrences are both initiated by the autistic child and responsive to the non-autistic interlocutor's turn; b) some vocalisations play an important role in the sequential organisation of the interaction, promoting the maintenance of intersubjective of low verbal children; and c) non-autistic adult interlocutors perform a varied set of actions, recycling, incorporating, retaking, assigning meaning, and repairing the non-lexical vocalisations produced by autistic children. The indexical analysis shows how communicative ecologies create meaning. This study thus contributes to our understanding of the interactional behaviour of these children and their interlocutors.

Assessment of Neuroanatomical Endophenotypes of Autism Spectrum Disorder and Association With Characteristics of Individuals With Schizophrenia and the General Population

Importance

Autism spectrum disorder (ASD) is associated with significant clinical, neuroanatomical, and genetic heterogeneity that limits precision diagnostics and treatment.

Objective

To assess distinct neuroanatomical dimensions of ASD using novel semisupervised machine learning methods and to test whether the dimensions can serve as endophenotypes also in non-ASD populations.

Design, Setting, and Participants

This cross-sectional study used imaging data from the publicly available Autism Brain Imaging Data Exchange (ABIDE) repositories as the discovery cohort. The ABIDE sample included individuals diagnosed with ASD aged between 16 and 64 years and age- and sex-match typically developing individuals. Validation cohorts included individuals with schizophrenia from the Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging (PHENOM) consortium and individuals from the UK Biobank to represent the general population. The multisite discovery cohort included 16 internationally distributed imaging sites. Analyses were performed between March 2021 and March 2022.

Main Outcomes and Measures

The trained semisupervised heterogeneity through discriminative analysis models were tested for reproducibility using extensive cross-validations. It was then applied to individuals from the PHENOM and the UK Biobank. It was hypothesized that neuroanatomical dimensions of ASD would display distinct clinical and genetic profiles and would be prominent also in non-ASD populations.

Results

Heterogeneity through discriminative analysis models trained on T1-weighted brain magnetic resonance images of 307 individuals with ASD (mean [SD] age, 25.4 [9.8] years; 273 [88.9%] male) and 362 typically developing control individuals (mean [SD] age, 25.8 [8.9] years; 309 [85.4%] male) revealed that a 3-dimensional scheme was optimal to capture the ASD neuroanatomy. The first dimension (A1: aginglike) was associated with smaller brain volume, lower cognitive function, and aging-related genetic variants (FOXO3; Z = 4.65; P = 1.62 × 10-6). The second dimension (A2: schizophrenialike) was characterized by enlarged subcortical volumes, antipsychotic medication use (Cohen d = 0.65; false discovery rate-adjusted P = .048), partially overlapping genetic, neuroanatomical characteristics to schizophrenia (n = 307), and significant genetic heritability estimates in the general population (n = 14 786; mean [SD] h2, 0.71 [0.04]; P < 1 × 10-4). The third dimension (A3: typical ASD) was distinguished by enlarged cortical volumes, high nonverbal cognitive performance, and biological pathways implicating brain development and abnormal apoptosis (mean [SD] β, 0.83 [0.02]; P = 4.22 × 10-6).

Conclusions and Relevance

This cross-sectional study discovered 3-dimensional endophenotypic representation that may elucidate the heterogeneous neurobiological underpinnings of ASD to support precision diagnostics. The significant correspondence between A2 and schizophrenia indicates a possibility of identifying common biological mechanisms across the 2 mental health diagnoses.

Do Savant Syndrome and Autism Spectrum Disorders Share Sex Differences? A Comprehensive Review

Savant syndrome was described before autism. However, they soon became closely associated, as many of their symptoms (intellectual disability, repetitive behaviors, alterations in social communication, and islets of abilities) overlap. Only a few women with autism have been diagnosed with savant syndrome. The theories or hypotheses that attempt to explain savant syndrome, which are common in autism, present differential treatment according to sex. We postulate that savant syndrome associated with autism as well as autism in general is underdiagnosed in women.

Changes in Autistic Symptoms and Adaptive Functioning of Children Receiving Early Behavioral Intervention in a Community Setting: A Latent Growth Curve Analysis

Despite showing effects in well-controlled studies, the extent to which early intensive behavioral intervention (EBI) produces positive changes in community-based settings remains uncertain. Thus, our study examined changes in autistic symptoms and adaptive functioning in 233 children with autism receiving EBI in a community setting. The results revealed nonlinear changes in adaptive functioning characterized by significant improvements during the intervention and a small linear decrease in autistic symptoms from baseline to follow-up. The intensity of intervention, initial age, IQ and autistic symptoms were associated either with progress during the intervention or maintenance during the follow-up. The next step to extend this line of research involves collecting detailed data about intervention strategies and implementation fidelity to produce concrete recommendations for practitioners.

IQ trajectories in autistic children through preadolescence

Background

We extended our study of trajectories of intellectual development of autistic individuals in early (mean age 3 years; T1), and middle childhood (mean age 5 years, 7 months; T2) into later middle childhood/preadolescence (mean age 11 years, 6 months; T3) in the longitudinal Autism Phenome Project cohort. Participants included 373 autistic children (115 females).

Methods

Multivariate latent class growth analysis was used to identify distinct IQ trajectory subgroups. Baseline and developmental course group differences and predictors of trajectory membership were assessed using linear mixed effects models with repeated measures with pairwise testing, multinomial logistic regression models, and sensitivity analyses.

Results

We isolated three IQ trajectories between T1 and T3 for autistic youth that were similar to those found in our prior work. These included a group with persistent intellectual disability (ID; 45%), a group with substantial increases in IQ (CHG; 39%), and a group with persistently average or above IQs (P-High; 16%). By T3, the groups did not differ in ADOS-2 calibrated severity scores (CSS), and there were no group differences between Vineland (VABS) communication scores in CHG and P-High. T1-T3 externalizing behaviors declined significantly for CHG, however, there were no significant T3 group differences between internalizing or externalizing symptoms. T1 correlates for CHG and P-High versus ID group membership included higher VABS communication and lower ADOS-2 CSS. A T1 to T2 increase in VABS communication scores and a decline in externalizing predicted CHG versus ID group membership at T3, while T1 to T2 improvement in VABS communication and reduction in ADOS-2 CSS predicted P-High versus ID group membership.

Conclusions

Autistic youth exhibit consistent IQ developmental trajectories from early childhood through preadolescence. Factors associated with trajectory group membership may provide clues about prognosis, and the need for treatments that improve adaptive communication and externalizing symptoms.

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.

A convergent structure-function substrate of cognitive imbalances in autism

BACKGROUND

Autism spectrum disorder (ASD) is a common neurodevelopmental diagnosis showing substantial phenotypic heterogeneity. A leading example can be found in verbal and nonverbal cognitive skills, which vary from elevated to impaired compared with neurotypical individuals. Moreover, deficits in verbal profiles often coexist with normal or superior performance in the nonverbal domain.

METHODS

To study brain substrates underlying cognitive imbalance in ASD, we capitalized categorical and dimensional IQ profiling as well as multimodal neuroimaging.

RESULTS

IQ analyses revealed a marked verbal to nonverbal IQ imbalance in ASD across 2 datasets (Dataset-1: 155 ASD, 151 controls; Dataset-2: 270 ASD, 490 controls). Neuroimaging analysis in Dataset-1 revealed a structure-function substrate of cognitive imbalance, characterized by atypical cortical thickening and altered functional integration of language networks alongside sensory and higher cognitive areas.

CONCLUSION

Although verbal and nonverbal intelligence have been considered as specifiers unrelated to autism diagnosis, our results indicate that intelligence disparities are accentuated in ASD and reflected by a consistent structure-function substrate affecting multiple brain networks. Our findings motivate the incorporation of cognitive imbalances in future autism research, which may help to parse the phenotypic heterogeneity and inform intervention-oriented subtyping in ASD.

Language, Social, and Face Regions Are Affected in Toddlers with Autism and Predictive of Language Outcome

Identifying prognostic early brain alterations is crucial for autism spectrum disorder (ASD). Leveraging structural MRI data from 166 ASD and 109 typical developing (TD) toddlers and controlling for brain size, we found that, compared to TD, ASD toddlers showed larger or thicker lateral temporal regions; smaller or thinner frontal lobe and midline structures; larger callosal subregion volume; and smaller cerebellum. Most of these differences were replicated in an independent cohort of 38 ASD and 37 TD toddlers. Moreover, the identified brain alterations were related to ASD symptom severity and cognitive impairments at intake, and, remarkably, they improved the accuracy for predicting later language outcome beyond intake clinical and demographic variables. In summary, brain regions involved in language, social, and face processing were altered in ASD toddlers. These early-age brain alterations may be the result of dysregulation in multiple neural processes and stages and are promising prognostic biomarkers for future language ability.

Measuring the association between behavioural services and outcomes in young children with autism spectrum disorder

BACKGROUND

Children with autism spectrum disorder (ASD) receive a wide range of services.

AIMS

To examine the association between behavioural services received by children with ASD between ages 2 and 5 years and outcomes during primary school years.

METHODS

A total of 414 preschool-aged children diagnosed with ASD were enrolled at five Canadian sites and were assessed within four months of diagnosis (T1), six months later (T2), 12 months later (T3), at school entry (T4), and then annually (T5-T8) to 11 years of age. The association between the receipt of behavioural services during T1 to T3 and T8 outcomes related to adaptive behaviour and behavioural problems was modelled using linear regressions adjusted for immigrant status, family income, child's age at diagnosis, site, sex assigned at birth, and baseline (T1) outcome.

RESULTS

Children who received behavioural services during at least one time period from T1 to T3 did not have significantly different outcomes at T8 than children who did not receive any behavioural services.

IMPLICATIONS

Pre-school use of behavioural services was not found to affect outcomes during later childhood. Numerous challenges accompany studies of the association between pre-school service use and later outcomes in a heterogeneous ASD sample. Recommendations for study design are provided.

The global prevalence of autism spectrum disorder: A three-level meta-analysis

Autism spectrum disorder (ASD) is one the most disabling developmental disorders, imposing an extremely high economic burden. Obtaining as accurate prevalence estimates as possible is crucial to guide governments in planning policies for identification and intervention for individuals with ASD and their relatives. The precision of prevalence estimates can be heightened by summative analyses of the data collected around the world. To that end, we conducted a three-level mixed-effects meta-analysis. A systematic search of the Web of Science, PubMed, EMBASE, and PsycINFO databases from 2000 up to 13 July 2020 was performed, and reference lists of previous reviews and existing databases of prevalence studies were screened. Overall, 79 studies were included in the analysis of ASD and 59-in the analysis of previously existing relevant diagnoses: 30 for Autistic Disorder (AD), 15 for Asperger Syndrome (AS), and 14 for Atypical Autism (AA) and Pervasive Developmental Disorder - Not Otherwise Specified (PDD-NOS); these research reports covered the period from 1994 to 2019. Pooled prevalence estimates were 0.72% (95% CI = 0.61-0.85) for ASD, 0.25% (95% CI = 0.18-0.33) for AD, 0.13% (95% CI = 0.07-0.20) for AS, and 0.18% (95% CI = 0.10-0.28) for the combined group of AA and PDD-NOS. Estimates were higher (1) for the studies that used records-review surveillance rather than other designs; (2) in North America compared with other geographical regions; and (3) in high-income compared with lower-income countries. The highest prevalence estimates were registered in the USA. There was an increase in autism prevalence estimates over time. The prevalence was also significantly higher for children aged between 6 and 12 years compared to children under the age of 5 and over the age of 13 years.

SYSTEMATIC REVIEW REGISTRATION

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42019131525, identifier CRD42019131525.

Findings of a Multidisciplinary Assessment of Children Referred for Possible Neurodevelopmental Disorders: Insights from a Retrospective Chart Review Study

Children with ASD have a wide spectrum of functional deficits in multiple neurodevelopmental domains. A multidisciplinary team assessment (MDT) is required to assess those deficits to help construct a multimodal intervention plan. This is a retrospective chart review of the assessment for children who were referred for an assessment of potential neurodevelopmental disorders. We reviewed 221 participants' charts from January 2019 to January 2020. The mean age of the children was 7.95 ± 3.69, while the mean age of the fathers and mothers was 37.31 ± 8.57 and 31.95 ± 6.93, respectively. Consanguinity was as high as 37.9% for the referred children with developmental delay who were first-degree related, and 13.2% of the parents were second-degree relatives. Approximately 26.6% of children had a family history of mental illness in first-degree relatives. ASD was the most commonly reported diagnosis post-assessment, and ADHD was the most common reported comorbidity at 64.3% and 88.5%, respectively. The MDT findings showed that 58% of children required moderate or higher assistance with toileting, 79.2% were unable to answer yes/no questions, and 86.8% were unable to understand "wh" questions. Only 26% of the nonverbal children had average IQ testing results, and 31% of verbal children did. In conclusion, the mean age of the children when assessed was above that recommended for early screening and intervention. An increased paternal and maternal age was noticeable. Consanguinity and a family history of mental disorders in first-degree relatives were high, attesting to a possible genetic risk.

Mapping the Heterogeneous Brain Structural Phenotype of Autism Spectrum Disorder Using the Normative Model

BACKGROUND

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by substantial clinical and biological heterogeneity. Quantitative and individualized metrics for delineating the heterogeneity of brain structure in ASD are still lacking. Likewise, the extent to which brain structural metrics of ASD deviate from typical development (TD) and whether deviations can be used for parsing brain structural phenotypes of ASD is unclear.

METHODS

T1-weighted magnetic resonance imaging data from the Autism Brain Imaging Data Exchange (ABIDE) II (n_TD = 564) were used to generate a normative model to map brain structure deviations of ABIDE I subjects (n_TD = 560, n_ASD = 496). Voxel-based morphometry was used to compute gray matter volume. Non-negative matrix factorization was employed to decompose the gray matter matrix into 6 factors and weights. These weights were used for normative modeling to estimate the factor deviations. Then, clustering analysis was used to identify ASD subtypes.

RESULTS

Compared with TD, ASD showed increased weights and deviations in 5 factors. Three subtypes with distinct neuroanatomical deviation patterns were identified. ASD subtype 1 and subtype 3 showed positive deviations, whereas ASD subtype 2 showed negative deviations. Distinct clinical manifestations in social communication deficits were identified among the three subtypes.

CONCLUSIONS

Our findings suggest that individuals with ASD have heterogeneous deviation patterns in brain structure. The results highlight the need to test for subtypes in neuroimaging studies of ASD. This study also presents a framework for understanding neuroanatomical heterogeneity in this increasingly prevalent neurodevelopmental disorder.

Autism Spectrum Disorder and IQ - A Complex Interplay

Autism spectrum disorder (ASD) is characterized as a very heterogeneous child-onset disorder, whose heterogeneity is partly determined by differences in intelligence quotient (IQ). Older epidemiological studies suggested that the IQ-related spectrum tends to be skewed to the left, i.e., a larger proportion of individuals with ASD have below average intelligence, while only few individuals with ASD may have an IQ above average. This picture changed over time with broadening the spectrum view. Within the present perspective article, we discuss discrepancies in IQ profiles between epidemiological and clinical studies and identify potential underlying aspects, for example, the influence of external factors such as sample biases or differences in availability of autism health services. Additionally, we discuss the validity and reciprocal influences of ASD diagnostics and IQ measurement. We put the impact of these factors for diagnostic as well as care and support situations of patients into perspective and want to encourage further research to contribute to the conceptualization of "autism" more comprehensively including the IQ as well as to examine broader (life) circumstances, interacting factors and diagnostic requirements of given diagnoses in childhood as compared to adulthood.

Abilities and Disabilities-Applying Machine Learning to Disentangle the Role of Intelligence in Diagnosing Autism Spectrum Disorders

Objective

Although autism spectrum disorder (ASD) is a relatively common, well-known but heterogeneous neuropsychiatric disorder, specific knowledge about characteristics of this heterogeneity is scarce. There is consensus that IQ contributes to this heterogeneity as well as complicates diagnostics and treatment planning. In this study, we assessed the accuracy of the Autism Diagnostic Observation Schedule (ADOS/2) in the whole and IQ-defined subsamples, and analyzed if the ADOS/2 accuracy may be increased by the application of machine learning (ML) algorithms that processed additional information including the IQ level.

Methods

The study included 1,084 individuals: 440 individuals with ASD (with a mean IQ level of 3.3 ± 1.5) and 644 individuals without ASD (with a mean IQ level of 3.2 ± 1.2). We applied and analyzed Random Forest (RF) and Decision Tree (DT) to the ADOS/2 data, compared their accuracy to ADOS/2 cutoff algorithms, and examined most relevant items to distinguish between ASD and Non-ASD. In sum, we included 49 individual features, independently of the applied ADOS module.

Results

In DT analyses, we observed that for the decision ASD/Non-ASD, solely one to four items are sufficient to differentiate between groups with high accuracy. In addition, in sub-cohorts of individuals with (a) below (IQ level ≥4)/ID and (b) above average intelligence (IQ level ≤ 2), the ADOS/2 cutoff showed reduced accuracy. This reduced accuracy results in (a) a three times higher risk of false-positive diagnoses or (b) a 1.7 higher risk for false-negative diagnoses; both errors could be significantly decreased by the application of the alternative ML algorithms.

Conclusions

Using ML algorithms showed that a small set of ADOS/2 items could help clinicians to more accurately detect ASD in clinical practice across all IQ levels and to increase diagnostic accuracy especially in individuals with below and above average IQ level.

Features that best define the heterogeneity and homogeneity of autism in preschool-age children: A multisite case-control analysis replicated across two independent samples

The heterogeneous nature of children with symptoms of autism spectrum disorder (ASD) makes it difficult to identify risk factors and effective treatment options. We sought to identify behavioral and developmental features that best define the heterogeneity and homogeneity in 2-5-year-old children classified with ASD and subthreshold ASD characteristics. Children were enrolled in a multisite case-control study of ASD. Detailed behavioral and developmental data were gathered by maternal telephone interview, parent-administered questionnaires, child cognitive evaluation, and ASD diagnostic measures. Participants with a positive ASD screen score or prior ASD diagnosis were referred for comprehensive evaluation. Children in the ASD group met study criteria based on this evaluation; children who did not meet study criteria were categorized as having subthreshold ASD characteristics. There were 1480 children classified as ASD (81.6% boys) and 594 children classified as having subthreshold ASD characteristics (70.2% boys) in the sample. Factors associated with dysregulation (e.g., aggression, anxiety/depression, sleep problems) followed by developmental abilities (e.g., expressive and receptive language skills) most contributed to heterogeneity in both groups of children. Atypical sensory response contributed to homogeneity in children classified as ASD but not those with subthreshold characteristics. These findings suggest that dysregulation and developmental abilities are clinical features that can impact functioning in children with ASD and other DD, and that documenting these features in pediatric records may help meet the needs of the individual child. Sensory dysfunction could be considered a core feature of ASD and thus used to inform more targeted screening, evaluation, treatment, and research efforts. LAY SUMMARY: The diverse nature of autism spectrum disorder (ASD) makes it difficult to find risk factors and treatment options. We identified the most dissimilar and most similar symptom(s) in children classified as ASD and as having subthreshold ASD characteristics. Factors associated with dysregulation and developmental abilities contributed to diversity in both groups of children. Sensory dysfunction was the most common symptom in children with ASD but not those with subthreshold characteristics. Findings can inform clinical practice and research.

Two neuroanatomical subtypes of males with autism spectrum disorder revealed using semi-supervised machine learning

Background

Clinical and etiological varieties remain major obstacles to decompose heterogeneity in autism spectrum disorders (ASD). Recently, neuroimaging raised new hope to identify neurosubtypes of ASD for further understanding the biological mechanisms behind the disorder.

Methods

In this study, brain structural MRI data and clinical measures of 221 male subjects with ASD and 257 healthy controls were selected from 7 independent sites from the Autism Brain Image Data Exchange database (ABIDE). Heterogeneity through discriminative analysis (HYDRA), a recently-proposed semi-supervised clustering method was utilized to divide individuals with ASD into several neurosubtypes by regional volumetric measures of gray matter, white matter, and cerebrospinal fluid. Voxel-wise volume, clinical measures, dynamic resting-state functional magnetic resonance imaging (R-fMRI) measures among different neurosubtypes of ASD were explored. In addition, support vector machine (SVM) model was applied to test whether the neurosubtyping of ASD could improve diagnostic accuracy of ASD.

Results

Two neurosubtypes of ASD with different voxel-wise volumetric patterns were revealed. The full-scale intelligence quotient (IQ), verbal IQ, Autism Diagnostic Observation Schedule (ADOS) total scores and ADOS severity scores were significantly different between the two neurosubtypes, the total intracranial volume was correlated with performance IQ in Subtype 1 and was correlated with ADOS communication score and ADOS social score in Subtype 2. Compared with Subtype 2, Subtype 1 showed lower dynamic R-fMRI measures, lower dynamic functional architecture stability, higher mean and lower standard deviation (SD) of concordance among dynamic R-fMRI measures in cerebellum. In addition, classification accuracies between ASD neurosubtypes and healthy controls were significantly improved compared with classification accuracy between entire ASD group and healthy controls.

Limitations

The present study excluded female subjects and left-handed subjects, which limited the ability to investigate the associations between these factors and the heterogeneity of ASD.

Conclusions

The two distinct neuroanatomical subtypes of ASD validated by other data modalities not only adds reliability of the result, but also bridges from brain phenomenology to clinical behavior. The current neurosubtypes of ASD could facilitate understanding the neuropathology of this disorder and could be potentially used to improve clinical decision-making process and optimize treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13229-022-00489-3.

Early communication development in infants and toddlers with Fragile X syndrome

BACKGROUND AND AIMS

Individuals with fragile X syndrome (FXS) characteristically struggle with language and communication throughout the life course, but there is limited research on the development of communication before 24 months. The purpose of this study is to describe the early communication of infants and toddlers with FXS using the Communication and Symbolic Behavior Scales-Caregiver Questionnaire (CSBS-CQ), a standardized communication screening measure, as compared to the reported normative data of the CSBS-CQ and identify the percentage of infants and toddlers who scored within the range of concern. Documenting how children with FXS perform on screening measures can provide a quick snapshot of skills to help clinicians determine the need for services.

METHODS

Participants were 22 infants and toddlers with FXS between 6 and 29 months. Performance on the CSBS-CQ was compared to the measure's normative data. The CSBS-CQ was completed by mothers, and children were administered the Mullen Scales of Early Learning. Because co-occurring autism is common in FXS, the presence of autism was determined using a clinical best estimate procedure.

RESULTS

Overall and within the domains and subdomains of the CSBS-CQ, infants and toddlers with FXS had significantly lower scores than the normative data. Further, 68.2% of our sample was in the range of concern for their overall communication score. The presence of autism led to consistently lower scores, and more infants and toddlers with FXS + autism scored within the range of concern.

CONCLUSIONS

Our findings suggest that delays in early communication are evident in comparison to typically developing norms before 24 months. These findings also emphasize that infants and toddlers with FXS would likely benefit from early language intervention given that 68.2% of our sample was in the range of concern for their overall communication score.

IMPLICATIONS

Early identification and developmental monitoring of children with FXS will help to determine concerns in communication and other domains of development. While early communication broadly may not be an early indicator of autism in FXS, some specific skills, such as eye gaze, may serve as such an indicator. Screening measures, like the CSBS-CQ, may help monitor both early communication impairments and autism symptoms. Infants and toddlers with FXS, regardless of autism status, will benefit from early language interventions.

Latent Structure of Combined Autistic and ADHD Symptoms in Clinical and General Population Samples: A Scoping Review

Background: Many phenotypic studies have estimated the degree of comorbidity between Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD), but few have examined the latent, or unobserved, structure of combined ASD and ADHD symptoms. This is an important perquisite toward better understanding the overlap between ASD and ADHD. Methods: We conducted a scoping review of studies that examined the factor or latent class structure of ASD and ADHD symptoms within the same clinical or general population sample. Results: Eight studies met final inclusion criteria. Four factor analysis studies found that ASD and ADHD domains loaded separately and one found that some ASD and ADHD domains loaded together. In the three latent class studies, there were evidence of profiles with high levels of co-occurring ASD and ADHD symptoms. Conclusions: Our scoping review provides some evidence of phenotypic overlap between ASD and ADHD at the latent, or unobserved, level, particularly when using a "person-centered" (latent class analysis) vs. a "variable-centered" (factor analysis) approach.

Assessing global developmental delay across instruments in minimally verbal preschool autistic children: The importance of a multi-method and multi-informant approach

Intellectual assessment in preschool autistic children bears many challenges, particularly for those who have lower language and/or cognitive abilities. These challenges often result in underestimation of their potential or exclusion from research studies. Understanding how different instruments and definitions used to identify autistic preschool children with global developmental delay (GDD) affect sample composition is critical to advance research on this understudied clinical population. This study set out to examine the extent to which using different instruments to define GDD affects sample composition and whether different definitions affect resultant cognitive and adaptive profiles. Data from the Mullen Scales of Early Learning and the Vineland Adaptive Behavior Scales-Second Edition, a parent-report tool, were analyzed in a sample of 64 autistic and 73 neurotypical children (28-69 months). Our results highlight that cognitive assessment alone should not be used in clinical or research practices to infer a comorbid diagnosis of GDD, as it might lead to underestimating autistic children's potential. Instead, using both adaptive and cognitive levels as a stratification method to create subgroups of children with and without GDD might be a promising approach to adequately differentiate them, with less risk of underestimating them.

Imputing cognitive impairment in SPARK, a large autism cohort

Diverse large cohorts are necessary for dissecting subtypes of autism, and intellectual disability is one of the most robust endophenotypes for analysis. However, current cognitive assessment methods are not feasible at scale. We developed five commonly used machine learning models to predict cognitive impairment (FSIQ<80 and FSIQ<70) and FSIQ scores among 521 children with autism using parent-reported online surveys in SPARK, and evaluated them in an independent set (n = 1346) with a missing data rate up to 70%. We assessed accuracy, sensitivity, and specificity by comparing predicted cognitive levels against clinical IQ data. The elastic-net model has good performance (AUC = 0.876, sensitivity = 0.772, specificity = 0.803) using 129 predictive features to impute cognitive impairment (FSIQ<80). Top-ranked predictive features included parent-reported language and cognitive levels, age at autism diagnosis, and history of services. Prediction of FSIQ<70 and FSIQ scores also showed good performance. We show cognitive levels can be imputed with high accuracy for children with autism, using commonly collected parent-reported data and standardized surveys. The current model offers a method for large-scale autism studies seeking estimates of cognitive ability when standardized psychometric testing is not feasible. LAY SUMMARY: Children with autism who have more severe learning challenges or cognitive impairment have different needs that are important to consider in research studies. When children in our study were missing standardized cognitive testing scores, we were able to use machine learning with other information to correctly "guess" when they have cognitive impairment about 80% of the time. We can use this information in research in the future to develop more appropriate treatments for children with autism and cognitive impairment.

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.

Children and adolescents with neurodevelopmental disorders show cognitive heterogeneity and require a person-centered approach

We aimed to identify patterns of cognitive differences and characterize subgroups of Mexican children and adolescents with three neurodevelopmental disorders (NDD): intellectual disability (ID), autism spectrum disorders (ASD) and attention deficit/hyperactivity disorder (ADHD). The sample included 74 children and adolescents 6–15 years; 34% had ID, ASD or ADHD, 47% had ID in comorbidity with ASD, ADHD or both, 11% had ASD + ADHD, 8% were children without NDD. We applied WISC-IV, Autism Diagnostic Interview-Revised, Mini-International Neuropsychiatric Structured Interview, Child Behavior Checklist, and UNICEF Child Functioning Module. We evaluated the normality of the WISC-IV sub-scales using the Shapiro-Francia test, then conducted a latent class analysis and assessed inter-class differences in terms of household, parent and child characteristics. The following four-class solution best fit the data: “Lower Cognitive Profile” (LCP), “Lower Working Memory” (LWM), “Higher Working Memory” (HWM), “Higher Cognitive Profile” (HCP). LCP included most of the children with ID, who had a low Working Memory (WM) index score. LWM included mainly children with ASD or ID + ADHD; their Perceptual Reasoning (PR) and Processing Speed (PS) index scores were much higher than those for Verbal Comprehension (VC) and WM. HWM included children with ASD or ADHD; their scores for PR, PS and VC were high with lower WM (although higher than for LWM). HCP included children without NDD and with ASD or ADHD or both and had the highest scores on all indices. Children with NDD show cognitive heterogeneity and thus require individualized treatment plans.

Update about "minimally verbal" children with autism spectrum disorder

OBJECTIVE

To review clinical and neurobiological features of minimally verbal children with autism spectrum disorder.

DATA SOURCE

We carried out a narrative review using the PubMed database. We considered the following search terms combined through the Boolean operator "AND": "autism spectrum disorder"; "minimally verbal."

DATA SYNTHESIS

To date, there is no shared definition of minimally verbal children with autism spectrum disorder. The heterogeneity in intellectual functioning and in linguistic abilities among these individuals suggests there is no single mechanism underlying their difficulties in learning to speak. However, the reasons why these children do not speak and the biological markers that can identify them are still unknown. Language impairment in these children can lead to several unfavorable consequences, including behavior problems (such as self-aggression, hetero-aggression, and property destruction), poorer daily living and social skills. Psychiatric comorbidities (including attention deficit/hyperactivity disorder, specific phobias, and compulsions) consist in a serious problem related to the lack of verbal language in individuals with autism spectrum disorder. Although in the literature there are very few evidence-based results, several findings suggest that an alternative and augmentative communication intervention, creating an extra-verbal communication channel, may be effective in these individuals.

CONCLUSIONS

The exact definition, clinical characteristics, associated disorders, etiology, and treatment of minimally verbal subjects with autism spectrum disorder must still be further studied and understood.

Brief Report: Unexpected Bilingualism: A Case of a Russian Child With ASD

Some children with autism spectrum disorders (ASD) demonstrate unusual islets of abilities or "splinter skills" that represent relative strengths in their development. In this paper we present a clinical case of an 11-year-old Russian boy with ASD who spontaneously acquired the English language. While the child demonstrated language deficits in both English and Russian, the discrepancy between the languages was paradoxical given the lack of exposure to English language. This case study brings into question the importance of a language environment for children with ASD. Alternative pathway to language acquisition is discussed. We hypothesize that that incidental second language acquisition in children with ASD resulting from media exposure could become more frequent with the availability of the Internet.

Attention to intentional versus incidental pointing gestures in young autistic children: An eye-tracking study

Whereas a reduced tendency to follow pointing gestures is described as an early sign of autism, the literature on response to joint attention indicates that autistic children perform better when a point is added to other social cues such as eye gaze. The purpose of this study was to explore pointing processing in autism when it is the only available cue and to investigate whether autistic children discriminate intentional pointing gestures from incidental pointing gestures. Eye movements of 58 autistic children (48 male) and 61 typically developing children (36 male) aged 3-5 years were recorded as the children were watching videos of a person uttering a pseudoword and pointing intentionally with one hand and incidentally with the other hand. After 3 s, two different potential referents for the pseudoword gradually emerged in both pointed-at corners. In comparison with typically developing children, autistic children's fixations were significantly farther away from both pointed-at zones. Upon hearing a novel word, typically developing children shifted their visual attention toward the zone pointed intentionally. This trend did not emerge in the group of autistic children regardless of their level of vocabulary. Autistic children, independently of their level of language, pay little attention to pointing when no other social cues are available and fail to discriminate intentional pointing gestures from incidental ones. They seem to grasp neither the spatial nor the social value of pointing.

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.

Prerequisite Skills in Cognitive Testing: Innovations in theory and recommendations for practice

Testing cognitive skill development is important for diagnostic, prognostic, and monitoring purposes, especially for young children and individuals with neurodevelopmental disorders. Developmental tests have been created for infants and toddlers, while traditional IQ tests are often employed beginning in the later preschool period. However, IQ tests rely on developmental skills that are rapidly changing during early childhood. Here, we introduce the idea of prerequisite skills in developmental domains, which are discrete skills required for, but not explicitly tested by, traditional IQ tests. Focusing on general cognition, particularly among children with a chronological or mental age under 4 years, may fail to capture important nuances in skill development. New skill-based assessments are needed in general, and in particular for categorization, which is foundational to higher-order cognitive skills. Novel measures quantifying categorization skills would provide a more sensitive measure of development for young children and older individuals with low developmental levels.

A Monte Carlo evaluation of growth mixture modeling

Growth mixture modeling (GMM) and its variants, which group individuals based on similar longitudinal growth trajectories, are quite popular in developmental and clinical science. However, research addressing the validity of GMM-identified latent subgroupings is limited. This Monte Carlo simulation tests the efficiency of GMM in identifying known subgroups (k = 1-4) across various combinations of distributional characteristics, including skew, kurtosis, sample size, intercept effect size, patterns of growth (none, linear, quadratic, exponential), and proportions of observations within each group. In total, 1,955 combinations of distributional parameters were examined, each with 1,000 replications (1,955,000 simulations). Using standard fit indices, GMM often identified the wrong number of groups. When one group was simulated with varying skew and kurtosis, GMM often identified multiple groups. When two groups were simulated, GMM performed well only when one group had steep growth (whether linear, quadratic, or exponential). When three to four groups were simulated, GMM was effective primarily when intercept effect sizes and sample sizes were large, an uncommon state of affairs in real-world applications. When conditions were less ideal, GMM often underestimated the correct number of groups when the true number was between two and four. Results suggest caution in interpreting GMM results, which sometimes get reified in the literature.

Identifying Subgroups of Toddlers with DSM-5 Autism Spectrum Disorder Based on Core Symptoms

The objective of this study was to identify subgroups of toddlers with DSM-5 ASD based on core ASD symptoms using a person-based analytical framework. This is a retrospective study of 500 toddlers (mean age 26 months, 79% male) with DSM-5 ASD. Data were analyzed using latent class analyses in which profiles were formed based on ASD symptomatology. Social communication (SC) symptoms favored a three-class solution, while restricted/repetitive behaviors (RRBs) favored a two-class solution. Classes with higher consistency of SC deficits were younger, with lower developmental functioning. The class with more RRBs was older, with higher functioning. If confirmed in other populations, these classes may more precisely characterize subgroups within the heterogeneous group of toddlers at time of ASD diagnosis.

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.

Supporting Minimally Verbal Autistic Girls with Intellectual Disabilities Through Puberty: Perspectives of Parents and Educators

Limited research has examined puberty in autistic girls, yet alone those who are minimally verbal and with additional intellectual disabilities. In this study, ten parents and ten educators were interviewed about their views and experiences of supporting these girls through puberty. Results demonstrated that many parents had concerns prior to the onset of puberty in these girls. Yet, for most girls, experiences of puberty were felt to be positive, with the girls coping well with changes that they were experiencing (e.g. menstruation, breast development and developing body hair). Thematic analysis of interview data highlighted three main themes: a range of individual experiences and needs; the importance of promoting dignity and respect; and identifying ways to support these girls through puberty.

The definition and measurement of heterogeneity

Heterogeneity is an important concept in psychiatric research and science more broadly. It negatively impacts effect size estimates under case-control paradigms, and it exposes important flaws in our existing categorical nosology. Yet, our field has no precise definition of heterogeneity proper. We tend to quantify heterogeneity by measuring associated correlates such as entropy or variance: practices which are akin to accepting the radius of a sphere as a measure of its volume. Under a definition of heterogeneity as the degree to which a system deviates from perfect conformity, this paper argues that its proper measure roughly corresponds to the size of a system's event/sample space, and has units known as numbers equivalent. We arrive at this conclusion through focused review of more than 100 years of (re)discoveries of indices by ecologists, economists, statistical physicists, and others. In parallel, we review psychiatric approaches for quantifying heterogeneity, including but not limited to studies of symptom heterogeneity, microbiome biodiversity, cluster-counting, and time-series analyses. We argue that using numbers equivalent heterogeneity measures could improve the interpretability and synthesis of psychiatric research on heterogeneity. However, significant limitations must be overcome for these measures-largely developed for economic and ecological research-to be useful in modern translational psychiatric science.

A preliminary investigation assessing the basic digital capabilities of minimally verbal children on the autism spectrum with intellectual disability

Purpose

Children with Autism Spectrum Disorder (ASD) can demonstrate a preference for using digital technologies which can represent a relative strength within the autism community. Such a strength would have implications for digitally mediated interventions and support for autism. However, research to date has not developed a methodology for assessing the capabilities of minimally verbal children on the autism spectrum with intellectual disability (ID) to use digital technology.

Design/methodology/approach

Six minimally verbal children with ASD and ID undertook an accessible assessment that identified what capabilities for interacting with a digital tablet device they could and could not demonstrate. Twelve brief assessments were demonstrated, including turning on the device, adjusting the volume, operating the camera, touching, tilting and rotating the screen.

Findings

Participants could be assessed on their digital capabilities. In this study, participants could largely touch and swipe the screen effectively and leave the app, but could not tilt and rotate the screen nor turn on the digital tablet device.

Research limitations/implications

While the numbers were small, the findings indicate that the digital capabilities of this group can usefully be assessed. Future research can use such assessments to highlight how intervention effectiveness and support can be enhanced by matching the digital capacities of minimally verbal children with ASD and ID to technological support. This is a preliminary study and a greater understanding of children’s prior experiences with technology will better inform how and which digital capabilities develop.

Originality/value

This is the first study to assess a range of basic capabilities for using digital tablet devices in minimally verbal children with ASD and ID.

Dimensions over categories: a meta-analysis of taxometric research

Taxometric procedures have been used extensively to investigate whether individual differences in personality and psychopathology are latently dimensional or categorical ('taxonic'). We report the first meta-analysis of taxometric research, examining 317 findings drawn from 183 articles that employed an index of the comparative fit of observed data to dimensional and taxonic data simulations. Findings supporting dimensional models outnumbered those supporting taxonic models five to one. There were systematic differences among 17 construct domains in support for the two models, but psychopathology was no more likely to generate taxonic findings than normal variation (i.e. individual differences in personality, response styles, gender, and sexuality). No content domain showed aggregate support for the taxonic model. Six variables - alcohol use disorder, intermittent explosive disorder, problem gambling, autism, suicide risk, and pedophilia - emerged as the most plausible taxon candidates based on a preponderance of independently replicated findings. We also compared the 317 meta-analyzed findings to 185 additional taxometric findings from 96 articles that did not employ the comparative fit index. Studies that used the index were 4.88 times more likely to generate dimensional findings than those that did not after controlling for construct domain, implying that many taxonic findings obtained before the popularization of simulation-based techniques are spurious. The meta-analytic findings support the conclusion that the great majority of psychological differences between people are latently continuous, and that psychopathology is no exception.

Reconciling Dimensional and Categorical Models of Autism Heterogeneity: A Brain Connectomics and Behavioral Study

BACKGROUND

Heterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide individuals with ASD into nonoverlapping (categorical) subgroups. However, continuous interindividual variation in ASD suggests that there is a need for a dimensional approach.

METHODS

A Bayesian model was employed to decompose resting-state functional connectivity (RSFC) of individuals with ASD into multiple abnormal RSFC patterns, i.e., categorical subtypes, henceforth referred to as "factors." Importantly, the model allowed each individual to express one or more factors to varying degrees (dimensional subtyping). The model was applied to 306 individuals with ASD (5.2-57 years of age) from two multisite repositories. Post hoc analyses associated factors with symptoms and demographics.

RESULTS

Analyses yielded three factors with dissociable whole-brain hypo- and hyper-RSFC patterns. Most participants expressed multiple (categorical) factors, suggestive of a mosaic of subtypes within individuals. All factors shared abnormal RSFC involving the default mode network, but the directionality (hypo- or hyper-RSFC) differed across factors. Factor 1 was associated with core ASD symptoms. Factors 1 and 2 were associated with distinct comorbid symptoms. Older male participants preferentially expressed factor 3. Factors were robust across control analyses and were not associated with IQ or head motion.

CONCLUSIONS

There exist at least three ASD factors with dissociable whole-brain RSFC patterns, behaviors, and demographics. Heterogeneous default mode network hypo- and hyper-RSFC across the factors might explain previously reported inconsistencies. The factors differentiated between core ASD and comorbid symptoms-a less appreciated domain of heterogeneity in ASD. These factors are coexpressed in individuals with ASD with different degrees, thus reconciling categorical and dimensional perspectives of ASD heterogeneity.

Developmental Trajectories of Adaptive Behavior From Toddlerhood to Middle Childhood in Autism Spectrum Disorder

Longitudinal growth modeling was utilized to examine adaptive behavior over eight years across the three time points (i.e., ages 2-10). Seventy-six parents completed the Vineland Adaptive Behavior Scales interviews of adaptive behavior. Child participants completed standardized developmental testing and an executive function task in toddlerhood and the Autism Diagnostic Observation Schedule across all time points. Growth models were specified for communication, daily living skills, and socialization domains of adaptive behavior. Mental age in toddlerhood was a significant predictor of trajectories of communication, daily living skills, and socialization. Executive function and autism severity were significant predictors of socialization. Findings suggest executive function as a potential target for promoting the growth of adaptive behavior skills in addition to autism symptomology.