Annual research review: re-thinking the classification of autism spectrum disorders

Three autism subtypes based on single-subject gray matter network revealed by semi-supervised machine learning

Autism spectrum disorder (ASD) is a heterogeneous, early-onset neurodevelopmental condition characterized by persistent impairments in social interaction and communication. This study aims to delineate ASD subtypes based on individual gray matter brain networks and provide new insights from a graph theory perspective. In this study, we extracted and normalized single-subject gray matter networks and calculated each network's topological properties. The heterogeneity through discriminative analysis (HYDRA) method was utilized to subtype all patients based on network properties. Next, we explored the differences among ASD subtypes in terms of network properties and clinical measures. Our investigation identified three distinct ASD subtypes. In the case-control study, these subtypes exhibited significant differences, particularly in the precentral gyrus, lingual gyrus, and middle frontal gyrus. In the case analysis, significant differences in global and nodal properties were observed between any two subtypes. Clinically, subtype 1 showed lower VIQ and PIQ compared to subtype 3, but exhibited higher scores in ADOS-Communication and ADOS-Total compared to subtype 2. The results highlight the distinct brain network properties and behaviors among different subtypes of male patients with ASD, providing valuable insights into the neural mechanisms underlying ASD heterogeneity.

Real-time coded measures in natural language samples capture change over time in minimally verbal autistic children

Prior research supports the use of natural language sampling (NLS) to assess the rate of speech utterances (URate) and the rate of conversational turns (CTRate) in minimally verbal (MV) autistic children. Bypassing time-consuming transcription, previous work demonstrated the ability to derive URate and CTRate using real-time coding methods and provided support for their strong psychometric properties. (1) Unexplored is how URate and CTRate using real-time coding methods capture change over time and (2) whether specific child factors predict changes in URate and CTRate in 50 MV autistic children (40 males; M = 75.54, SD = 16.45 (age in months)). A NLS was collected at Time 1 (T1) and Time 2 (T2) (4.5 months between T1 and T2) and coding was conducted in ELAN Linguistic Annotator software using a real-time coding approach to derive URate and CTRate. Findings from paired samples Wilcoxon tests revealed a significant increase in child URate (not examiner URate) and child and examiner CTRate from T1 to T2. Child chronological age, Mullen expressive language age equivalent scores, and URate and CTRate at T1 were predictive of URate and CTRate at T2. Findings support using NLS-derived real-time coded measures of URate and CTRate to efficiently capture change over time in MV autistic children. Identifying child factors that predict changes in URate and CTRate can help in the tailoring of goals to children's individual needs and strengths.

Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning

Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in neuropsychiatric and neurodegenerative disorders. Therefore, it has contributed to a better understanding of disease heterogeneity by identifying disease subtypes with different brain phenotypic measures. In this review, we first present a systematic literature overview of studies using machine learning and multimodal magnetic resonance imaging to unravel disease heterogeneity in various neuropsychiatric and neurodegenerative disorders, including Alzheimer's disease, schizophrenia, major depressive disorder, autism spectrum disorder, and multiple sclerosis, as well as their potential in a transdiagnostic framework, where neuroanatomical and neurobiological commonalities were assessed across diagnostic boundaries. Subsequently, we summarize relevant machine learning methodologies and their clinical interpretability. We discuss the potential clinical implications of the current findings and envision future research avenues. Finally, we discuss an emerging paradigm called dimensional neuroimaging endophenotypes. Dimensional neuroimaging endophenotypes dissects the neurobiological heterogeneity of neuropsychiatric and neurodegenerative disorders into low-dimensional yet informative, quantitative brain phenotypic representations, serving as robust intermediate phenotypes (i.e., endophenotypes), presumably reflecting the interplay of underlying genetic, lifestyle, and environmental processes associated with disease etiology.

Autism Severity and its Relationship to Disability

Autism severity is currently defined and measured based exclusively on the severity levels of the two core symptom domains: social-communication and restricted or repetitive patterns of behaviors and interests. Autistic individuals, however, are often diagnosed with other medical, developmental, and psychological co-occurring conditions. These additional challenges such as intellectual disability, limited expressive and/or receptive language, and anxiety disorders, can have a tremendous impact on the day-to-day lives of autistic individuals, for both their adaptive functioning as well as their sense of wellbeing. Furthermore, the initial presentation of core symptoms and their likelihood of changing over time are influenced by the presence of such co-occurring conditions. In order to truly understand how a person's autism impacts their life, both core symptoms as well as other challenges should be considered. This approach was recently taken by The Lancet Commission on the future of care and clinical research in autism, which proposed the term "profound autism" for a subgroup of individuals presenting with high core symptom severity, co-occurring intellectual disability, and little or no language, who require extensive long-term care. Considering other individual factors such as daily living skills, specific support needs and environmental resources would also enhance the evaluation of disability in autistic individuals. As currently employed in the assessment of intellectual disability, a multidimensional approach to autism could provide a more comprehensive system for classification of impairment. At present, however, there is no formal way to designate the combined effect of these different aspects of autism on a person's life. A comprehensive outlook that acknowledges impairments, capabilities, co-occurring conditions, and environmental factors would be useful for identifying subgroups of individuals as well as for determining individual needs and strengths in clinical assessments. Lay Summary: The severity of a person's autism is currently defined based on the severity of their core autism symptoms: impaired social-communication and the presence of restricted or repetitive patterns of behaviors and interests. But autistic people often face additional challenges such as intellectual disability, epilepsy, and anxiety disorder, that considerably impact their everyday life, wellbeing, and the need for support. A more complete view of autism severity, one that includes core symptoms as well as additional challenges, could help identify meaningful sub-groups of autistic individuals and could be useful in clinical care. Appeared originally in Autism Res 2023; 16:685-696.

Correlation Between Gaze Behaviors and Social Communication Skills of Young Autistic Children: A Meta-Analysis of Eye-Tracking Studies

This meta-analysis examined correlations between eye-tracking measures of gaze behaviors manifested during dynamic salient social stimuli and behavioral assessment measures of social communication skills of young autistic children. We employed a multilevel model with random effects to perform three separate meta-analyses for correlation between social communication skills and (a) all gaze behaviors, (b) gaze duration, and (c) gaze transition. Subsequently, we performed meta-regression to assess the role of four moderators, including age, continuum of naturalness of stimuli, gaze metric, and area of interest, on correlation effect sizes that were heterogeneous at the population level. A total of 111 correlation coefficients from 17 studies for 1132 young autistic children or children with high-likelihood for autism (Mage range = 6-95 months) were included in this meta-analysis. The correlation effect sizes for all three meta-analyses were significant, supporting the relation between improved gaze behaviors and better social communication skills. In addition, age, gaze metric, and area of interest were significant moderators. This suggests the importance of identifying meaningful gaze behaviors related to social communication skills and the increasingly influential role of gaze behaviors in shaping social communication skills as young autistic children progress through the early childhood stage. The continuum of naturalness of stimuli, however, was revealed to trend towards having a significant moderating effect. Lastly, it is important to note the evidence of potential publication bias. Our findings are discussed in the context of early identification and intervention and unraveling the complex nature of autism.

Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning

Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in neuropsychiatric and neurodegenerative disorders. Therefore, it has contributed to a better understanding of disease heterogeneity by identifying disease subtypes that present significant differences in various brain phenotypic measures. In this review, we first present a systematic literature overview of studies using machine learning and multimodal MRI to unravel disease heterogeneity in various neuropsychiatric and neurodegenerative disorders, including Alzheimer's disease, schizophrenia, major depressive disorder, autism spectrum disorder, multiple sclerosis, as well as their potential in transdiagnostic settings. Subsequently, we summarize relevant machine learning methodologies and discuss an emerging paradigm which we call dimensional neuroimaging endophenotype (DNE). DNE dissects the neurobiological heterogeneity of neuropsychiatric and neurodegenerative disorders into a low-dimensional yet informative, quantitative brain phenotypic representation, serving as a robust intermediate phenotype (i.e., endophenotype) largely reflecting underlying genetics and etiology. Finally, we discuss the potential clinical implications of the current findings and envision future research avenues.

Idiographic Coping Outcomes in Youth with Autism Spectrum Disorder and Co-Occurring Anxiety: Results from the TAASD Study

Versions of cognitive behavioral therapy (Coping Cat, CC; Behavioral Interventions for Anxiety in Children with Autism, BIACA) have shown efficacy in treating anxiety among youth with autism spectrum disorder. Measures of efficacy have been primarily nomothetic symptom severity assessments. The current study examined idiographic coping outcomes in the Treatment of Anxiety in Autism Spectrum Disorder study (N = 167). Longitudinal changes in coping with situations individualized to youth fears (Coping Questionnaire) were examined across CC, BIACA and treatment as usual (TAU) in a series of multilevel models. CC and BIACA produced significantly greater improvements than TAU in caregiver-reported coping. Youth report did not reflect significant differences. Results show the efficacy of CC and BIACA in improving idiographic caregiver-, but not youth-, reported youth coping.

The Selective Social Attention task in children with autism spectrum disorder: Results from the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) feasibility study

The Selective Social Attention (SSA) task is a brief eye-tracking task involving experimental conditions varying along socio-communicative axes. Traditionally the SSA has been used to probe socially-specific attentional patterns in infants and toddlers who develop autism spectrum disorder (ASD). This current work extends these findings to preschool and school-age children. Children 4- to 12-years-old with ASD (N = 23) and a typically-developing comparison group (TD; N = 25) completed the SSA task as well as standardized clinical assessments. Linear mixed models examined group and condition effects on two outcome variables: percent of time spent looking at the scene relative to scene presentation time (%Valid), and percent of time looking at the face relative to time spent looking at the scene (%Face). Age and IQ were included as covariates. Outcome variables' relationships to clinical data were assessed via correlation analysis. The ASD group, compared to the TD group, looked less at the scene and focused less on the actress' face during the most socially-engaging experimental conditions. Additionally, within the ASD group, %Face negatively correlated with SRS total T-scores with a particularly strong negative correlation with the Autistic Mannerism subscale T-score. These results highlight the extensibility of the SSA to older children with ASD, including replication of between-group differences previously seen in infants and toddlers, as well as its ability to capture meaningful clinical variation within the autism spectrum across a wide developmental span inclusive of preschool and school-aged children. The properties suggest that the SSA may have broad potential as a biomarker for ASD.

Neurotypical, but not autistic, adults might experience distress when looking at someone avoiding eye contact: A live face-to-face paradigm

LAY ABSTRACT

What is already known about the topic?Autistics are usually reported to share less eye contact than neurotypicals with their interlocutors. However, the reason why autistics might pay less attention to eyes looking at them is still unknown: some autistics express being hyper-aroused by this eye contact, while some eye-tracking studies suggest that eye contact is associated with hypo-arousal in autism.What this paper adds?This study is based on a highly controlled live face-to-face paradigm, combining a wearable eye-tracker (to study eye behaviours) with electrodermal activity sensors (to assess potential stress). We draw a nuanced picture of social attention in autism, as our autistic participants did not differ from our neurotypical group in their eye behaviours nor their skin conductance responses. However, we found that neurotypicals, compared to autistics, seemed to be much more distressed when their interlocutor did not gaze at them during the experiment.Implications for practice, research or policy:Our study encourages to consider social interaction difficulties in autism as a relational issue, instead as an individual deficit. This step might be first taken in research, by implementing paradigms sensitive to the experimenter's role and attitude.

The Construct Validity of the Childhood Joint Attention Rating Scale (C-JARS) in School-Aged Autistic Children

Preliminary evidence from the Childhood Joint Attention Rating Scale (C-JARS; Mundy et al., 2017) suggests symptoms related to diminished joint attention and the spontaneous sharing of experience with others can be assessed with a parent-report measure in children and adolescents with autism. This study was designed to expand on the previous study by examining the validity of both a Social Symptom (SS) and a Prosocial (PS) scale of the C-JARS in a study of school-aged autistic children (n  = 89) with and without co-occurring intellectual disability (ID), as well as an age matched neurotypical sample (n  = 62). Results indicated that both C-JARS scales were sensitive and specific with respect to identifying the diagnostic status of the children. In addition, the PS scale was sensitive to differences in cognitive abilities (IQ) and sex differences in the autism group. These results are consistent with the hypothesis that joint attention and spontaneous sharing of experience symptoms are not only characteristic of preschool children with autism but may also constitute a developmentally continuous dimension of the social phenotype of autism that can be measured in school-aged children.

Listener- Versus Speaker-Oriented Disfluencies in Autistic Adults: Insights From Wearable Eye-Tracking and Skin Conductance Within a Live Face-to-Face Paradigm

PURPOSE

Our study addresses three main questions: (a) Do autistics and neurotypicals produce different patterns of disfluencies, depending on the experimenter's direct versus averted gaze? (b) Are these patterns correlated to gender, skin conductance responses, fixations on the experimenter's face, alexithymia, or social anxiety scores? Lastly, (c) can eye-tracking and electrodermal activity data be used in distinguishing listener- versus speaker-oriented disfluencies?

METHOD

Within a live face-to-face paradigm combining a wearable eye-tracker with electrodermal activity sensors, 80 adults (40 autistics, 40 neurotypicals) defined words in front of an experimenter who was either staring at their eyes (direct gaze condition) or looking elsewhere (averted gaze condition).

RESULTS

Autistics produce less listener-oriented (uh, um) and more speaker-oriented (prolongations, breath) disfluencies than neurotypicals. In both groups, men produce less um than women. Both autistics' and neurotypicals' speech are influenced by whether their interlocutor systematically looks at them in the eyes or not, but their reactions go in opposite directions. Disfluencies seem to primarily be linguistic phenomena as experienced stress, social attention, alexithymia, and social anxiety scores do not influence any of the reported results. Finally, eye-tracking and electrodermal activity data suggest that laughter could be a listener-oriented disfluency.

CONCLUSIONS

This article studies disfluencies in a fine-grained way in autistic and neurotypical adults while controlling for social attention, experienced stress, and experimental condition (direct vs. averted gaze). It adds to current literature by (a) enlightening our knowledge of speech in autism, (b) opening new perspectives on disfluency patterns as important signals in social interaction, (c) addressing theoretical issues on the dichotomy between listener- and speaker-oriented disfluencies, and (d) considering understudied phenomena as potential disfluencies (e.g., laughter, breath).

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.23549550.

Autism severity and its relationship to disability

Autism severity is currently defined and measured based exclusively on the severity levels of the two core symptom domains: social-communication and restricted or repetitive patterns of behaviors and interests. Autistic individuals, however, are often diagnosed with other medical, developmental, and psychological co-occurring conditions. These additional challenges such as intellectual disability, limited expressive and/or receptive language, and anxiety disorders, can have a tremendous impact on the day-to-day lives of autistic individuals, for both their adaptive functioning as well as their sense of wellbeing. Furthermore, the initial presentation of core symptoms and their likelihood of changing over time are influenced by the presence of such co-occurring conditions. In order to truly understand how a person's autism impacts their life, both core symptoms as well as other challenges should be considered. This approach was recently taken byThe Lancet Commission on the future of care and clinical research in autism, which proposed the term "profound autism" for a subgroup of individuals presenting with high core symptom severity, co-occurring intellectual disability, and little or no language, who require extensive long-term care. Considering other individual factors such as daily living skills, specific support needs and environmental resources would also enhance the evaluation of disability in autistic individuals. As currently employed in the assessment of intellectual disability, a multidimensional approach to autism could provide a more comprehensive system for classification of impairment. At present, however, there is no formal way to designate the combined effect of these different aspects of autism on a person's life. A comprehensive outlook that acknowledges impairments, capabilities, co-occurring conditions, and environmental factors would be useful for identifying subgroups of individuals as well as for determining individual needs and strengths in clinical assessments.

Research on social attention in autism and the challenges of the research domain criteria (RDoC) framework

The fuzzy nature of categories of psychopathology, such as autism, leads to significant research challenges. Alternatively, focusing research on the study of a common set of important and well-defined psychological constructs across psychiatric conditions may make the fundamental etiological processes of psychopathology easier to discern and treat (Cuthbert, 2022). The development of the research domain criteria (RDoC) framework is designed to guide this new research approach (Insel et al., 2010). However, progress in research may be expected to continually refine and reorganize the understanding of the specifics of these mental processes (Cuthbert & Insel, 2013). Moreover, knowledge gleaned from the study of both normative and atypical development can be mutually informative in the evolution of our understanding of these fundamental processes. A case in point is the study of social attention. This Autism 101 commentary provides an educational summary of research over the last few decades indicates that social attention is major construct in the study of human social-cognitive development, autism and other forms of psychopathology. The commentary also describes how this research can inform the Social Process dimension of the RDoC framework.

“Realizing the problem wasn’t necessarily me”: the meaning of childhood adversity and resilience in the lives of autistic adults

Purpose

Methods

Results

Conclusion

Accounting for motion in resting-state fMRI: What part of the spectrum are we characterizing in autism spectrum disorder?

The exclusion of high-motion participants can reduce the impact of motion in functional Magnetic Resonance Imaging (fMRI) data. However, the exclusion of high-motion participants may change the distribution of clinically relevant variables in the study sample, and the resulting sample may not be representative of the population. Our goals are two-fold: 1) to document the biases introduced by common motion exclusion practices in functional connectivity research and 2) to introduce a framework to address these biases by treating excluded scans as a missing data problem. We use a study of autism spectrum disorder in children without an intellectual disability to illustrate the problem and the potential solution. We aggregated data from 545 children (8-13 years old) who participated in resting-state fMRI studies at Kennedy Krieger Institute (173 autistic and 372 typically developing) between 2007 and 2020. We found that autistic children were more likely to be excluded than typically developing children, with 28.5% and 16.1% of autistic and typically developing children excluded, respectively, using a lenient criterion and 81.0% and 60.1% with a stricter criterion. The resulting sample of autistic children with usable data tended to be older, have milder social deficits, better motor control, and higher intellectual ability than the original sample. These measures were also related to functional connectivity strength among children with usable data. This suggests that the generalizability of previous studies reporting naïve analyses (i.e., based only on participants with usable data) may be limited by the selection of older children with less severe clinical profiles because these children are better able to remain still during an rs-fMRI scan. We adapt doubly robust targeted minimum loss based estimation with an ensemble of machine learning algorithms to address these data losses and the resulting biases. The proposed approach selects more edges that differ in functional connectivity between autistic and typically developing children than the naïve approach, supporting this as a promising solution to improve the study of heterogeneous populations in which motion is common.

The Potential of AR Solutions for Behavioral Learning: A Scoping Review

In recent years, educational researchers and practitioners have become increasingly interested in new technologies for teaching and learning, including augmented reality (AR). The literature has already highlighted the benefit of AR in enhancing learners’ outcomes in natural sciences, with a limited number of studies exploring the support of AR in social sciences. Specifically, there have been a number of systematic and scoping reviews in the AR field, but no peer-reviewed review studies on the contribution of AR within interventions aimed at teaching or training behavioral skills have been published to date. In addition, most AR research focuses on technological or development issues. However, limited studies have explored how technology affects social experiences and, in particular, the impact of using AR on social behavior. To address these research gaps, a scoping review was conducted to identify and analyze studies on the use of AR within interventions to teach behavioral skills. These studies were conducted across several intervention settings. In addition to this research question, the review reports an investigation of the literature regarding the impact of AR technology on social behavior. The state of the art of AR solutions designed for interventions in behavioral teaching and learning is presented, with an emphasis on educational and clinical settings. Moreover, some relevant dimensions of the impact of AR on social behavior are discussed in more detail. Limitations of the reviewed AR solutions and implications for future research and development efforts are finally discussed.

Sex Differences in Autism Spectrum Disorder: Diagnostic, Neurobiological, and Behavioral Features

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder with a worldwide prevalence of about 1%, characterized by impairments in social interaction, communication, repetitive patterns of behaviors, and can be associated with hyper- or hypo-reactivity of sensory stimulation and cognitive disability. ASD comorbid features include internalizing and externalizing symptoms such as anxiety, depression, hyperactivity, and attention problems. The precise etiology of ASD is still unknown and it is undoubted that the disorder is linked to some extent to both genetic and environmental factors. It is also well-documented and known that one of the most striking and consistent finding in ASD is the higher prevalence in males compared to females, with around 70% of ASD cases described being males. The present review looked into the most significant studies that attempted to investigate differences in ASD males and females thus trying to shade some light on the peculiar characteristics of this prevalence in terms of diagnosis, imaging, major autistic-like behavior and sex-dependent uniqueness. The study also discussed sex differences found in animal models of ASD, to provide a possible explanation of the neurological mechanisms underpinning the different presentation of autistic symptoms in males and females.

The Altered Pattern of the Functional Connectome Related to Pathological Biomarkers in Individuals for Autism Spectrum Disorder Identification

Objective

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder characterized by the development of multiple symptoms, with incidences rapidly increasing worldwide. An important step in the early diagnosis of ASD is to identify informative biomarkers. Currently, the use of functional brain network (FBN) is deemed important for extracting data on brain imaging biomarkers. Unfortunately, most existing studies have reported the utilization of the information from the connection to train the classifier; such an approach ignores the topological information and, in turn, limits its performance. Thus, effective utilization of the FBN provides insights for improving the diagnostic performance.

Methods

We propose the combination of the information derived from both FBN and its corresponding graph theory measurements to identify and distinguish ASD from normal controls (NCs). Specifically, a multi-kernel support vector machine (MK-SVM) was used to combine multiple types of information.

Results

The experimental results illustrate that the combination of information from multiple connectome features (i.e., functional connections and graph measurements) can provide a superior identification performance with an area under the receiver operating characteristic curve (ROC) of 0.9191 and an accuracy of 82.60%. Furthermore, the graph theoretical analysis illustrates that the significant nodal graph measurements and consensus connections exists mostly in the salience network (SN), default mode network (DMN), attention network, frontoparietal network, and social network.

Conclusion

This work provides insights into potential neuroimaging biomarkers that may be used for the diagnosis of ASD and offers a new perspective for the exploration of the brain pathophysiology of ASD through machine learning.

Sex- and age-related differences in autistic behaviours in children with neurofibromatosis type 1

This study investigated sex and age differences in autistic behaviours in children with neurofibromatosis type 1 (NF1) who scored within the clinical range on the Social Responsiveness Scale - Second Edition (T score ≥ 60). Thirty-four males and 28 females (3-16 years) were assessed with the Autism Diagnostic Observation Schedule - Second Edition and Autism Diagnostic Interview - Revised. Across both measures, males exhibited greater social communication deficits relative to females. Age-related abatement of social communication difficulties was observed for males but not females. Conversely, no sex differences were found for restricted/repetitive behaviours, which were stable over time for both males and females. The findings are discussed within the context of broader neurodevelopmental considerations that are common in NF1.

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.

The Bidirectional Social-Cognitive Mechanisms of the Social-Attention Symptoms of Autism

Differences in social attention development begin to be apparent in the 6th to 12th month of development in children with Autism Spectrum Disorder (ASD) and theoretically reflect important elements of its neurodevelopmental endophenotype. This paper examines alternative conceptual views of these early social attention symptoms and hypotheses about the mechanisms involved in their development. One model emphasizes mechanism involved in the spontaneous allocation of attention to faces, or social orienting. Alternatively, another model emphasizes mechanisms involved in the coordination of attention with other people, or joint attention, and the socially bi-directional nature of its development. This model raises the possibility that atypical responses of children to the attention or the gaze of a social partner directed toward themselves may be as important in the development of social attention symptoms as differences in the development of social orienting. Another model holds that symptoms of social attention may be important to early development, but may not impact older individuals with ASD. The alterative model is that the social attention symptoms in infancy (social orienting and joint attention), and social cognitive symptoms in childhood and adulthood share common neurodevelopmental substrates. Therefore, differences in early social attention and later social cognition constitute a developmentally continuous axis of symptom presentation in ASD. However, symptoms in older individuals may be best measured with in vivo measures of efficiency of social attention and social cognition in social interactions rather than the accuracy of response on analog tests used in measures with younger children. Finally, a third model suggests that the social attention symptoms may not truly be a symptom of ASD. Rather, they may be best conceptualized as stemming from differences domain general attention and motivation mechanisms. The alternative argued for here that infant social attention symptoms meet all the criteria of a unique dimension of the phenotype of ASD and the bi-directional phenomena involved in social attention cannot be fully explained in terms of domain general aspects of attention development.

Evidence from Characteristics and Comorbidities Suggesting That Asperger Syndrome Is a Subtype of Autism Spectrum Disorder

The current version of the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders (DSM-V) does not consider Asperger syndrome a diagnostic category. This study was undertaken to see if there is evidence that this diagnosis should be reinstated. An online survey was conducted to examine symptoms and behaviors associated with the current diagnostic criteria of autism spectrum disorders (ASD) (DSM-V), and those associated with Asperger syndrome based on the previous version (DSM-IV-TR). The study also examined other characteristics historically associated with autism, as well as impairments often reported in infancy/young childhood and medical comorbidities frequently associated with autism. The sample included 251 individuals who had received a diagnosis of Asperger syndrome and 1888 who were diagnosed with autism or ASD. Numerous similarities and differences were found between the two groups. The findings are discussed in relation to reestablishing Asperger syndrome as a valid diagnostic category as well as a subtype of ASD.

The Diagnosis of Autism: From Kanner to DSM-III to DSM-5 and Beyond

In this paper we review the impact of DSM-III and its successors on the field of autism-both in terms of clinical work and research. We summarize the events leading up to the inclusion of autism as a "new" official diagnostic category in DSM-III, the subsequent revisions of the DSM, and the impact of the official recognition of autism on research. We discuss the uses of categorical vs. dimensional approaches and the continuing tensions around broad vs. narrow views of autism. We also note some areas of current controversy and directions for the future.

Inter and intra-limb coordination variability during walking in adolescents with autism spectrum disorder

BACKGROUND

Autism spectrum disorder, a neurodevelopmental disorder, is difficult to characterize from a gait biomechanics perspective, possibly due to increased inter and intra-individual variability. Previous research illustrates increased gait variability in young children with autism, but assessments in older adolescents or at varying speeds are unavailable. The purpose of this study was to determine if adolescents with autism demonstrate increased intra-limb and inter-limb coordination variability during walking compared to age, sex, and body mass index matched controls.

METHODS

Seventeen adolescents with autism (age 13-18 years) and seventeen matched controls performed walking at two matched speeds: self-selected of adolescents with autism and at 1.3 m/s. Modified vector coding was used to determine the patterns of movement for foot-shank, left/right thigh, and contralateral thigh-arm coupling. Coordination variability, a measure of cycle-to-cycle variability, was determined across the full stride. Mixed-model analyses of variance were used to determine if group by speed interactions and/or main effects existed for coordination variability.

FINDINGS

A significant interaction existed for foot-shank variability (p = 0.039). Adolescents with autism had greater variability at self-selected speeds (p = 0.018), but not at 1.3 m/s (p = 0.593) compared to controls. Thigh-thigh coordination was greater for adolescents with ASD compared to controls at both speeds (p = 0.021). Variability was decreased at 1.3 m/s for both foot-shank (p = 0.016) and thigh-thigh (p = 0.021) coupling.

INTERPRETATION

This study illustrates that adolescents with autism perform walking with increased coordination variability at both proximal and distal segments. Thus, it is likely intra-individual variability drives the disparity of movement patterns in this population.

Stereotypies in the Autism Spectrum Disorder: Can We Rely on an Ethological Model?

BACKGROUND

Stereotypic behaviour can be defined as a clear behavioural pattern where a specific function or target cannot be identified, although it delays on time. Nonetheless, repetitive and stereotypical behaviours play a key role in both animal and human behaviour. Similar behaviours are observed across species, in typical human developmental phases, and in some neuropsychiatric conditions, such as Autism Spectrum Disorder (ASD) and Intellectual Disability. This evidence led to the spread of animal models of repetitive behaviours to better understand the neurobiological mechanisms underlying these dysfunctional behaviours and to gain better insight into their role and origin within ASD and other disorders. This, in turn, could lead to new treatments of those disorders in humans.

METHOD

This paper maps the literature on repetitive behaviours in animal models of ASD, in order to improve understanding of stereotypies in persons with ASD in terms of characterization, pathophysiology, genomic and anatomical factors.

RESULTS

Literature mapping confirmed that phylogenic approach and animal models may help to improve understanding and differentiation of stereotypies in ASD. Some repetitive behaviours appear to be interconnected and mediated by common genomic and anatomical factors across species, mainly by alterations of basal ganglia circuitry. A new distinction between stereotypies and autotypies should be considered.

CONCLUSIONS

Phylogenic approach and studies on animal models may support clinical issues related to stereotypies in persons with ASD and provide new insights in classification, pathogenesis, and management.

Co-activation pattern alterations in autism spectrum disorder-A volume-wise hierarchical clustering fMRI study

INTRODUCTION

There has been a growing effort to characterize the time-varying functional connectivity of resting state (RS) fMRI brain networks (RSNs). Although voxel-wise connectivity studies have examined different sliding window lengths, nonsequential volume-wise approaches have been less common.

METHODS

Inspired by earlier co-activation pattern (CAP) studies, we applied hierarchical clustering (HC) to classify the image volumes of the RS-fMRI data on 28 adolescents with autism spectrum disorder (ASD) and their 27 typically developing (TD) controls. We compared the distribution of the ASD and TD groups' volumes in CAPs as well as their voxel-wise means. For simplification purposes, we conducted a group independent component analysis to extract 14 major RSNs. The RSNs' average z-scores enabled us to meaningfully regroup the RSNs and estimate the percentage of voxels within each RSN for which there was a significant group difference. These results were jointly interpreted to find global group-specific patterns.

RESULTS

We found similar brain state proportions in 58 CAPs (clustering interval from 2 to 30). However, in many CAPs, the voxel-wise means differed significantly within a matrix of 14 RSNs. The rest-activated default mode-positive and default mode-negative brain state properties vary considerably in both groups over time. This division was seen clearly when the volumes were partitioned into two CAPs and then further examined along the HC dendrogram of the diversifying brain CAPs. The ASD group network activations followed a more heterogeneous distribution and some networks maintained higher baselines; throughout the brain deactivation state, the ASD participants had reduced deactivation in 12/14 networks. During default mode-negative CAPs, the ASD group showed simultaneous visual network and either dorsal attention or default mode network overactivation.

CONCLUSION

Nonsequential volume gathering into CAPs and the comparison of voxel-wise signal changes provide a complementary perspective to connectivity and an alternative to sliding window analysis.

Role of Pediatrician in Early Risk Evaluation, Diagnosis and Management of Children with Autism Spectrum Disorders

The article discusses recent ideas about autism: classification approaches, incidence, etiology and pathogenesis, clinical manifestations and diagnosis, comorbid medical conditions, early detection approaches and medical care for children with autism spectrum disorders. The focus is on the information needed for pediatricians in their practice to provide effective medical care for children with neurodevelopmental disorders.

Near-point Findings in Children with Autism Spectrum Disorder and in Typical Peers

SIGNIFICANCE

Clinicians can better diagnose and manage vision problems of autism spectrum disorder (ASD) children by establishing a standard of care for this population. Results also reinforce the importance of a comprehensive binocular vision evaluation in all patients with ASD.

PURPOSE

The purposes of this study were to compare near-point and ocular motility test findings in ASD children and typically developing (TD) peers and to compare findings among ASD children by level of verbal communication.

METHODS

Sixty-one children and adolescents (ASD, 34; TD, 27) aged 9 to 17 years completed an eye examination protocol including tests of distance and near phoria, near point of convergence, near fusional convergence and divergence, accommodative response, and Northeastern State University College of Optometry oculomotor testing. Testing was completed through refractive correction. Parents of ASD children provided information regarding subjects' verbal communication level (nonverbal, uses short words, verbal).

RESULTS

Distance phoria did not differ significantly between groups. Near phoria of ASD subjects was more exophoric (difference, 2.8 prism diopters). Mean near point of convergence break and recovery were 7.0 and 8.02 cm, respectively, in ASD subjects and 2.19 and 3.99 cm in TD subjects. Near fusional divergence and convergence showed no significant difference. Autism spectrum disorder subjects had significantly poorer stereoacuity (P < .0001) and, on Northeastern State University College of Optometry Oculomotor Testing, reduced fixation, poorer accuracy and stamina/ability, and increased head and body movement. Monocular estimation method retinoscopy results did not differ significantly between ASD and TD subjects. No significant differences in phoria, near point of convergence, and near fusional divergence or convergence were observed between ASD subgroups (nonverbal, uses short words, verbal).

CONCLUSIONS

Autism spectrum disorder children are more likely to show receded near point of convergence, poor fixation, inaccurate saccades, erratic pursuits, and exophoric posture. These differences occur, regardless of reported verbal communication level.

Taxonomy and utility in the diagnostic classification of mental disorders

OBJECTIVE

One strategy for improving the clinical utility of mental health diagnostic systems is to better align them with how clinicians conceptualize psychopathology in practice. This approach was used in International Classification of Diseases 11th Revision (ICD-11) development, but its underlying assumption-a link between taxonomic "fit" and clinical utility-remains untested.

METHODS

Using data from global mental health clinician samples (combined N = 5404), we investigated the association between taxonomic fit and clinical utility in mental disorder categories.

RESULTS

The overall association between fit and utility was positive (r = 0.19) but statistically not different from zero (95% confidence interval [CI]: -0.06, 0.43) in this small sample (N = 39 ICD/DSM categories). However, a positive association became clear after correcting for outliers (r = 0.34 [0.05, 0.58] or higher). Further insights were apparent for specific diagnoses given their locations in the scatterplot.

CONCLUSIONS

Results suggest a positive link between taxonomic fit and clinical utility in mental disorder diagnoses, highlighting future research directions.

Autismus-Spektrum-Störungen: von der Früherfassung zu Intervention und Begleitung

Autismus-Spektrum-Störungen zeigen eine Prävalenz von 1 %. Die unterschiedlich stark ausgeprägte, soziale Interaktions- und Kommunikationsstörung ist gekennzeichnet durch eingeschränkte Fähigkeit, sich sprachlich und nichtsprachlich auf andere Menschen einzustellen. Weitere Kernsymptome sind repetitive und stereotype Verhaltens- und Interessenmuster.

Symptome einer Autismus-Spektrum-Störung zeigen sich überwiegend bereits während des Kleinkindalters und persistieren meist über die Lebensspanne in unterschiedlicher Phänomenologie und unterschiedlichem Ausprägungsgrad.

Wichtige abzugrenzende, aber auch begleitende Störungen bei jungen Kindern sind: kognitive Entwicklungsstörungen, Aufmerksamkeitsdefizit- und Hyperaktivitätssyndrom und Sprachstörungen.

Früherkennung ist häufig bereits im zweiten Lebensjahr möglich. Evidenzbasierte, effektive Frühinterventionsmodelle existieren, sind aktuell aber im deutschsprachigen Raum noch nicht flächendeckend verfügbar.

Angesichts der hohen Belastung für Familie und Umfeld ist ein kompetentes ärztliches Case Management mit Vernetzung zu Systempartnern aus Bildungs- und Sozialwesen notwendig.

How do minimally verbal children and adolescents with autism spectrum disorder use communicative gestures to complement their spoken language abilities?

BACKGROUND AND AIMS

Prior work has examined how children and adolescents with autism spectrum disorder who are minimally verbal use their spoken language abilities during interactions with others. However, social communication includes other aspects beyond speech. To our knowledge, no studies have examined how minimally verbal children and adolescents with autism spectrum disorder are using their gestural communication during social interactions. Such work can provide important insights into how gestures may complement their spoken language abilities.

METHODS

Fifty minimally verbal children and adolescents with autism spectrum disorder participated (M _age = 12.41 years; 38 males). Gestural communication was coded from the Autism Diagnostic Observation Schedule. Children (n = 25) and adolescents (n = 25) were compared on their production of gestures, gesture-speech combinations, and communicative functions. Communicative functions were also assessed by the type of communication modality: gesture, speech, and gesture-speech to examine the range of communicative functions across different modalities of communication. To explore the role gestures may play the relation between speech utterances and gestural production was investigated.

RESULTS

Analyses revealed that (1) minimally verbal children and adolescents with autism spectrum disorder did not differ in their total number of gestures. The most frequently produced gesture across children and adolescents was a reach gesture, followed by a point gesture (deictic gesture), and then conventional gestures. However, adolescents produced more gesture-speech combinations (reinforcing gesture-speech combinations) and displayed a wider range of communicative functions. (2) Overlap was found in the types of communicative functions expressed across different communication modalities. However, requests were conveyed via gesture more frequently compared to speech or gesture-speech. In contrast, dis/agree/acknowledging and responding to a question posed by the conversational partner was expressed more frequently via speech compared to gesture or gesture-speech. (3) The total number of gestures was negatively associated with total speech utterances after controlling for chronological age, receptive communication ability, and nonverbal IQ.

CONCLUSIONS

Adolescents may be employing different communication strategies to maintain the conversational exchange and to further clarify the message they want to convey to the conversational partner. Although overlap occurred in communicative functions across gesture, speech, and gesture-speech, nuanced differences emerged in how often they were expressed across different modalities of communication. Given their speech production abilities, gestures may play a compensatory role for some individuals with autism spectrum disorder who are minimally verbal.

IMPLICATIONS

Findings underscore the importance of assessing multiple modalities of communication to provide a fuller picture of their social communication abilities. Our results identified specific communicative strengths and areas for growth that can be targeted and expanded upon within gesture and speech to optimize social communication development.

How well are DSM-5 diagnostic criteria for ASD represented in standardized diagnostic instruments?

Five years after the publication of DSM-5 in 2013, three widely used diagnostic instruments have published algorithms designed to represent its (sub-)criteria for Autism Spectrum Disorder (ASD) in children and adolescents. This study aimed to: (1) establish the content validity of these three DSM-5-adapted algorithms, and (2) identify problems with the operationalization of DSM-5 diagnostic criteria in measurable and observable behaviors. Algorithm items of the Autism Diagnostic Observation Schedule-Second Edition (ADOS-2), Developmental, Dimensional and Diagnostic Interview (3di) and Diagnostic Interview for Social and Communication Disorders-11th edition (DISCO-11) were mapped onto DSM-5 sub-criteria. The development and decision-making rules integrated in their algorithms were then compared with DSM-5. Results demonstrated significant variability in the number and nature of sub-criteria covered by the ADOS-2, 3di and DISCO-11. In addition to differences in the development of algorithms and cut-off scores, instruments also differed in the extent to which they follow DSM-5 decision-making rules for diagnostic classification. We conclude that such differences in interpretation of DSM-5 criteria provide a challenge for symptom operationalization which will be most effectively overcome by consensus, testing and reformulation.

Circumscribed Interest Modulates Attention to Eyes in Boys With and Without Autism Spectrum Disorder

Children with autism spectrum disorder (ASD) exhibit abnormal visual attention, such as diminished attention to eyes and enhanced attention to high-autism-interest objects. We tested whether high-autism-interest objects would modulate the attention to eyes in boys with ASD and typically developing (TD) boys. Twenty-two ASD and 22 TD children were presented simultaneously with human eyes and high/low-autism-interest objects (HAI/LAI) while their eye movements were recorded. We found that visual preference for eyes was influenced by competing objects in children with and without ASD. Specifically, both children with and without ASD showed reduced overall and first looking preference when eyes were paired with HAI objects relative to LAI objects. Children with ASD also showed reduced sustained viewing preference to the eyes after first looking at the eyes and late looking preference to the eyes after first looking at the objects in the HAI condition than the LAI condition, but these effects were absent in the TD group. Our study not only helps us understand some factors that impact attention to eyes, but also has implications for interventions aiming at improving eye contact in children with ASD.

Heart Rate Variability in Children With Autism Spectrum Disorder and Associations With Medication and Symptom Severity

Decreased heart rate variability (HRV) is considered a common marker of autonomic dysfunction that contributes to poor health outcomes. While some studies have suggested that children with autism spectrum disorder (ASD) show reduced HRV, research is yet to consider whether this may be associated with medication use and symptom severity. This study examined the relationship between resting state HRV, medication use and symptom severity in children diagnosed with ASD. Children with ASD (N = 86), aged between 3 and 12 years (M = 8.09), were compared to 44 neurotypical children of similar age (M = 7.15). Laboratory assessment of HRV involved 5 min of non-invasive baseline electrocardiogram assessments while participants viewed an age-appropriate non-verbal animated video. Time-domain and frequency-domain HRV measures were analyzed. ASD symptom severity was assessed using the Autism Diagnostic Observation Schedule-Second Edition (ADOS-2) and Social Responsiveness Scale (SRS-2). Results indicated that children with ASD exhibited reduced resting HRV relative to neurotypical children. Subsequent analyses within the ASD group suggested that this group difference was greater in children who were taking psychotropic medication (N = 36). Our data also provides tentative evidence of a relationship between HRV and social impairment symptoms in children with ASD, with more severe repetitive behaviors (as measured by the ADOS-2) associated with decreased resting HRV. Overall, these findings suggest that HRV may be atypical in children with ASD and suggest the importance of exploring HRV as a risk factor for cardiovascular health in this group. LAY SUMMARY: Cardiac activity, such as heart rate variability (HRV), can provide insight into the autonomic nervous system. This study reports on the association between resting-state HRV and autonomic nervous system activity in young children with autism spectrum disorder (ASD) compared to neurotypical children. These results may help us understand what underlies autonomic nervous system dysfunction and the potential pathophysiological mechanisms leading to increased cardiovascular risk in ASD.

An initial examination of the psychometric properties of the Diagnostic Instrument for Social and Communication Disorders (DISCO-11) in a clinical sample of children with a diagnosis of Autism spectrum disorder

INTRODUCTION

The diagnostic interview for social and communication disorders (DISCO - 11; Wing 2006), is a semi-structured, interview-based instrument used in the diagnosis of children with autism spectrum disorder (ASD). This paper explores the psychometric properties of the DISCO-11 used in a specialist Paediatric clinical setting. Two key research questions were examined; (1) Does the factor structure of the DISCO-11 reflect the diagnostic and statistical manual 5th edition (DSM-5, American Psychiatric Association [APA], 2013) dyad of impairment in ASD? (2) Is there evidence of diagnostic stability over time using the DISCO?

METHODS

Review assessments of 65 children with ASD were carried out using standardised measures including the DISCO-11 and the autism diagnostic observation schedule.

RESULTS

The results revealed two factors resembling the DSM-5 algorithms, as used in DISCO-11, which were named as social-communication, and restricted and repetitive behaviours. The reliability, for the overall DISCO score was good (Cronbach's alpha = 0.78). The social communication and social interaction subscale showed good reliability (Cronbach's Alpha = 0.77) as did the restricted and repetitive patterns of behaviour, interests or activities subscale (Cronbach's Alpha = 0.74). Acceptable internal reliability was found for the overall DISCO score and the subscales of social communication and social interaction and the restricted and repetitive patterns of behaviour, interests or activities. Test-retest showed good stability of diagnosis over time.

DISCUSSION

This study supports that the DISCO-11 shows potential as a valid and reliable instrument that can be used both for clinical and research purposes.

Visual Search for Circumscribed Interests in Autism Is Similar to That of Neurotypical Individuals

Intense interests are a core symptom of autism spectrum disorders (ASD) and can be all-encompassing for affected individuals. This observation raises the hypothesis that intense interests in ASD are related to pervasive changes in visual processing for objects within that category, including visual search. We assayed visual processing with two novel tasks, targeting category search and exemplar search. For each task, three kinds of stimuli were used: faces, houses, and images personalized to each participant’s interest. 25 children and adults with ASD were compared to 25 neurotypical (NT) children and adults. We found no differences in either visual search task between ASD and NT controls for interests. Thus, pervasive alterations in perception are not likely to account for ASD behavioral symptoms.

Affording autism an early brain development re-definition

The national priority to advance early detection and intervention for children with autism spectrum disorder (ASD) has not reduced the late age of ASD diagnosis in the US over several consecutive Centers for Disease Control and Prevention (CDC) surveillance cohorts, with traditionally under-served populations accessing diagnosis later still. In this review, we explore a potential perceptual barrier to this enterprise which views ASD in terms that are contradicted by current science, and which may have its origins in the current definition of the condition and in its historical associations. To address this perceptual barrier, we propose a re-definition of ASD in early brain development terms, with a view to revisit the world of opportunities afforded by current science to optimize children's outcomes despite the risks that they are born with. This view is presented here to counter outdated notions that potentially devastating disability is determined the moment a child is born, and that these burdens are inevitable, with opportunities for improvement being constrained to only alleviation of symptoms or limited improvements in adaptive skills. The impetus for this piece is the concern that such views of complex neurodevelopmental conditions, such as ASD, can become self-fulfilling science and policy, in ways that are diametrically opposed to what we currently know, and are learning every day, of how genetic risk becomes, or not, instantiated as lifetime disabilities.

Autism Spectrum Disorder Symptoms are Associated with Connectivity Between Large-Scale Neural Networks and Brain Regions Involved in Social Processing

The neurobiology of autism spectrum disorder remains poorly understood. The present study addresses this knowledge gap by examining the relationship between functional brain connectivity and Autism Diagnostic Observation Schedule (ADOS) scores using publicly available data from the Autism Brain Imaging Data Exchange (ABIDE) database (N = 107). This relationship was tested across all brain voxels, without a priori assumptions, using a novel statistical approach. ADOS scores were primarily associated with decreased connectivity to right temporoparietal junction, right anterior insula, and left fusiform gyrus (p < 0.05, corrected). Seven large-scale brain networks influenced these associations. Findings largely encompassed brain regions involved in processing socially relevant information, highlighting the importance of these processes in autism spectrum disorder.

Psychiatric comorbidities in Asperger syndrome are related with polygenic overlap and differ from other Autism subtypes

There is great phenotypic heterogeneity within autism spectrum disorders (ASD), which has led to question their classification into a single diagnostic category. The study of the common genetic variation in ASD has suggested a greater contribution of other psychiatric conditions in Asperger syndrome (AS) than in the rest of the DSM-IV ASD subtypes (Non_AS). Here, using available genetic data from previously performed genome-wide association studies (GWAS), we aimed to study the genetic overlap between five of the most related disorders (schizophrenia (SCZ), major depression disorder (MDD), attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorders (OCD) and anxiety (ANX)), and AS, comparing it with the overlap in Non_AS subtypes. A Spanish cohort of autism trios (N = 371) was exome sequenced as part of the Autism Sequencing Consortium (ASC) and 241 trios were extensively characterized to be diagnosed with AS following DSM-IV and Gillberg's criteria (N = 39) or not (N = 202). Following exome imputation, polygenic risk scores (PRS) were calculated for ASD, SCZ, ADHD, MDD, ANX, and OCD (from available summary data from Psychiatric Genomic Consortium (PGC) repository) in the Spanish trios' cohort. By using polygenic transmission disequilibrium test (pTDT), we reported that risk for SCZ (P_scz= 0.008, corrected-P_SCZ = 0.0409), ADHD (P_ADHD = 0.021, corrected-P_ADHD = 0.0301), and MDD (P_MDD = 0.039, corrected-P_MDD = 0.0501) is over-transmitted to children with AS but not to Non_AS. Indeed, agnostic clustering procedure with deviation values from pTDT tests suggested two differentiated clusters of subjects, one of which is significantly enriched in AS (P = 0.025). Subsequent analysis with S-Predixcan, a recently developed software to predict gene expression from genotype data, revealed a clear pattern of correlation between cortical gene expression in ADHD and AS (P < 0.001) and a similar strong correlation pattern between MDD and AS, but also extendable to another non-brain tissue such as lung (P < 0.001). Altogether, these results support the idea of AS being qualitatively distinct from Non_AS autism and consistently evidence the genetic overlap between AS and ADHD, MDD, or SCZ.

Toward Neurosubtypes in Autism

There is a consensus that substantial heterogeneity underlies the neurobiology of autism spectrum disorder (ASD). As such, it has become increasingly clear that a dissection of variation at the molecular, cellular, and brain network domains is a prerequisite for identifying biomarkers. Neuroimaging has been widely used to characterize atypical brain patterns in ASD, although findings have varied across studies. This is due, at least in part, to a failure to account for neurobiological heterogeneity. Here, we summarize emerging data-driven efforts to delineate more homogeneous ASD subgroups at the level of brain structure and function-that is, neurosubtyping. We break this pursuit into key methodological steps: the selection of diagnostic samples, neuroimaging features, algorithms, and validation approaches. Although preliminary and methodologically diverse, current studies generally agree that at least 2 to 4 distinct ASD neurosubtypes may exist. Their identification improved symptom prediction and diagnostic label accuracy above and beyond group average comparisons. Yet, this nascent literature has shed light onto challenges and gaps. These include 1) the need for wider and more deeply transdiagnostic samples collected while minimizing artifacts (e.g., head motion), 2) quantitative and unbiased methods for feature selection and multimodal fusion, 3) greater emphasis on algorithms' ability to capture hybrid dimensional and categorical models of ASD, and 4) systematic independent replications and validations that integrate different units of analyses across multiple scales. Solutions aimed to address these challenges and gaps are discussed for future avenues leading toward a comprehensive understanding of the mechanisms underlying ASD heterogeneity.

Oral Health Status of Children with Autism in Central Italy

Children with autism spectrum disorder (ASD) have significantly higher prevalence and caries severity compared to the average population. Knowledge about the oral health indices of children with this mental disorder is key to designing efficient plans of intervention. This paper reports the results of a study on the oral health status of children with ASD in central Italy. This is the first study of this type in Italy. The sample consists of 229 autistic children aged between 5 and 14 years, attending the Unit of Special Needs Policlinico Umberto I in Rome. Each patient received an intraoral examination to investigate decayed, missing, and filled teeth as well as periodontal status. Information on demographic attributes, dietary habits, medical history, and child’s cooperativeness at the first visit was also recorded. Of the participants, 79.26% presented signs of gingivitis and about 90% of them had plaque. Caries prevalence was 66.38%. The average of the total number of decayed, missing, and filled teeth in the permanent and primary dentition was 2.91. Among the factors considered, only dietary habits and the periodontal indices showed statistically significant association with caries prevalence and caries severity. Despite the selection bias, that prevents us to interpret the results presented as epidemiological evidence, our study suggests that children with ASD in central Italy represent a population at risk.

Alterations of functional connectivities associated with autism spectrum disorder symptom severity: a multi-site study using multivariate pattern analysis

Autism spectrum disorder (ASD) is a highly heterogeneous neurodevelopmental disorder. The estimation of ASD severity is very important in clinical practice due to providing a more elaborate diagnosis. Although several studies have revealed some resting-state functional connectivities (RSFCs) that are related to the ASD severity, they have all been based on small-sample data and local RSFCs. The aim of the present study is to adopt multivariate pattern analysis to investigate a subset of connectivities among whole-brain RSFCs that are more contributive to ASD severity estimation based on large-sample data. Regression estimation shows a Pearson correlation value of 0.5 between the estimated and observed severity, with a mean absolute error of 1.41. The results provide obvious evidence that some RSFCs undergo notable alterations with the severity of ASD. More importantly, these selected RSFCs have an abnormality in the connection modes of the inter-network and intra-network connections. In addition, these selected abnormal RSFCs are mainly associated with the sensorimotor network, the default mode network, and inter-hemispheric connectivities, while exhibiting significant left hemisphere lateralization. Overall, this study indicates that some RSFCs suffer from abnormal alterations in patients with ASD, providing additional evidence of large-scale functional network alterations in ASD.

A clustering approach for autistic trait classification

Machine learning (ML) techniques can be utilized by physicians, clinicians, as well as other users, to discover Autism Spectrum Disorder (ASD) symptoms based on historical cases and controls to enhance autism screening efficiency and accuracy. The aim of this study is to improve the performance of detecting ASD traits by reducing data dimensionality and eliminating redundancy in the autism dataset. To achieve this, a new semi-supervised ML framework approach called Clustering-based Autistic Trait Classification (CATC) is proposed that uses a clustering technique and that validates classifiers using classification techniques. The proposed method identifies potential autism cases based on their similarity traits as opposed to a scoring function used by many ASD screening tools. Empirical results on different datasets involving children, adolescents, and adults were verified and compared to other common machine learning classification techniques. The results showed that CATC offers classifiers with higher predictive accuracy, sensitivity, and specificity rates than those of other intelligent classification approaches such as Artificial Neural Network (ANN), Random Forest, Random Trees, and Rule Induction. These classifiers are useful as they are exploited by diagnosticians and other stakeholders involved in ASD screening.

Characterizing autonomic response to arousing visual-auditory multi-modal task in Autism Spectrum Disorder (ASD)

Sensory abnormalities are widespread in Autism Spectrum Disorder (ASD). However, their definition is still quite subjective and vague. Here we propose a novel approach for characterization of Autonomic Nervous System responses to sensory stimulation based on electrocardiogram (ECG) assessment. In particular, we develop a preliminary study where autonomic responses of both autistic (ASD = 5) and neurotypical (NT = 5) participants have been evaluated in terms of changes in responsiveness to repeated stimuli. Autonomic control has been estimated via high-frequency heart rate variability (HF-HRV) and low-frequency HRV (LF-HRV). Results show significant differences among groups for the HRV measures (p value = 0.0158), supported by expected changes of HF (p value = 0.0079) and LF (p value = 0.0079) trends over stimulations. We thus conclude that an overall decrease in autonomic arousal can give important insights for devising new habituation metrics in NT and ASD individuals.

Somatosensory Discrimination in People With Autism Spectrum Disorder: A Scoping Review

IMPORTANCE

Sensory symptoms in people with autism spectrum disorder (ASD) are commonly reported by researchers. However, an often overlooked sensory aspect of ASD is sensory discrimination in general, and somatosensory discrimination in particular.

OBJECTIVE

To examine what has and what has not yet been learned concerning the somatosensory discrimination abilities of people with ASD and to reveal gaps warranting further research.

DESIGN

Scoping review of clinical studies published 1995-2017 located through searches of PsycNET, PubMed, ERIC, and Google Scholar. Inclusion criteria were English-language peer-reviewed studies with (1) participants diagnosed with ASD, (2) a specific somatosensory discrimination measure, and (3) a comparison group. No age or intellectual exclusion criteria were established; studies were excluded if they were theoretical or descriptive, did not incorporate a control group, focused only on neurology or genetics, or used simple threshold detection measures or somatosensory measures integrated with other measures. The final search yielded 12 comparative articles discussing tactile and proprioceptive discrimination in people with ASD.

RESULTS

Overall, most results showed atypical somatosensory discrimination in people with ASD, especially among young children. The relationship between sensory discrimination abilities and other sensory symptoms and ASD symptoms is briefly discussed.

CONCLUSIONS AND RELEVANCE

Heterogeneous findings concerning somatosensory discrimination in people with ASD shed light on underlying mechanisms of these disorders and can contribute to improvement of occupational therapy intervention for this population.

WHAT THIS ARTICLE ADDS

The occupational therapy evaluation of people with ASD can benefit from addressing somatosensory discrimination and its contribution to other clinical symptoms. This type of assessment can help improve intervention strategies for people with ASD by promoting a focus on the effect of discrimination deficits on daily function.

A Machine Learning Approach to Reveal the NeuroPhenotypes of Autisms

Although much research has been undertaken, the spatial patterns, developmental course, and sexual dimorphism of brain structure associated with autism remains enigmatic. One of the difficulties in investigating differences between the sexes in autism is the small sample sizes of available imaging datasets with mixed sex. Thus, the majority of the investigations have involved male samples, with females somewhat overlooked. This paper deploys machine learning on partial least squares feature extraction to reveal differences in regional brain structure between individuals with autism and typically developing participants. A four-class classification problem (sex and condition) is specified, with theoretical restrictions based on the evaluation of a novel upper bound in the resubstitution estimate. These conditions were imposed on the classifier complexity and feature space dimension to assure generalizable results from the training set to test samples. Accuracies above [Formula: see text] on gray and white matter tissues estimated from voxel-based morphometry (VBM) features are obtained in a sample of equal-sized high-functioning male and female adults with and without autism ([Formula: see text], [Formula: see text]/group). The proposed learning machine revealed how autism is modulated by biological sex using a low-dimensional feature space extracted from VBM. In addition, a spatial overlap analysis on reference maps partially corroborated predictions of the “extreme male brain” theory of autism, in sexual dimorphic areas.

Autism aging

Many people perceive autism spectrum disorder (ASD) as a childhood disorder, yet ASD is a lifelong condition. Although little is known about the mental and physical health issues of aging individuals with ASD, there are increasing numbers of older adults being diagnosed with ASD. Although there has been a recent "call to action" (to address lack of knowledge and the dearth of services and programs for aging individuals with autism, the authors think it is also important for those who are involved in educational programs related to gerontology and geriatrics settings to be aware of "autism aging." This term conceptualizes the demographics, person and contextual factors, and intellectual awareness of the trends and patterns of ASD as a life course challenge and opportunity for well-being and quality of life. The purposes of this article are to (1) provide a general overview of autism issues and to examine several dimensions of ASD in the context of the emergent and relevant scholarship in the adult and aging domain, (2) propose how to address the "gap" in the literature on autism and aging in terms of a conceptual model and by improving the methodology, and (3) to discuss the implications of these dimensions for educators in gerontology and geriatrics, and for those professionals who work in clinical and health care services. It is the goal of the authors to have this article represent a general introduction to ASD and to be a part of the foundation for educational awareness for educators in gerontology and geriatrics.

The Need for a Developmentally Based Measure of Social Communication Skills

The ability to demonstrate and quantify changes in social communication skills has been hindered by a lack of existing measures with appropriate standardization and psychometric properties. Such a measure would be helpful for research in many populations but would be particularly crucial for detecting incremental changes in youth with neurodevelopmental disorders who might gain skills but still lag substantially behind same-age peers. Although study designs and statistical methods are under development to try to account for slow and/or nonlinear, but potentially meaningful, improvements,¹ there is a dearth of measures designed to capture growth and loss of social communication skills. This opinion piece outlines the argument for such a measure and the primary issues to consider in its development.