Autism in DSM-5: progress and challenges

Machine Learning Differentiation of Autism Spectrum Sub-Classifications

PURPOSE

Disorders on the autism spectrum have characteristics that can manifest as difficulties with communication, executive functioning, daily living, and more. These challenges can be mitigated with early identification. However, diagnostic criteria has changed from DSM-IV to DSM-5, which can make diagnosing a disorder on the autism spectrum complex. We evaluated machine learning to classify individuals as having one of three disorders of the autism spectrum under DSM-IV, or as non-spectrum.

METHODS

We employed machine learning to analyze retrospective data from 38,560 individuals. Inputs encompassed clinical, demographic, and assessment data.

RESULTS

The algorithm achieved AUROCs ranging from 0.863 to 0.980. The model correctly classified 80.5% individuals; 12.6% of individuals from this dataset were misclassified with another disorder on the autism spectrum.

CONCLUSION

Machine learning can classify individuals as having a disorder on the autism spectrum or as non-spectrum using minimal data inputs.

Spontaneous instrumental approach-avoidance learning in social contexts in autism

BACKGROUND

Individuals with Autism Spectrum Condition (ASC) are characterized by atypicalities in social interactions, compared to Typically Developing individuals (TD). The social motivation theory posits that these difficulties stem from diminished anticipation, reception, and/or learning from social rewards. Although learning from socioemotional outcomes is core to the theory, studies to date have been sparse and inconsistent. This possibly arises from a combination of theoretical, methodological and sample-related issues. Here, we assessed participants' ability to develop a spontaneous preference for actions that lead to desirable socioemotional outcomes (approaching/avoiding of happy/angry individuals, respectively), in an ecologically valid social scenario. We expected that learning abilities would be impaired in ASC individuals, particularly in response to affiliative social feedback.

METHOD

We ran an online social reinforcement learning task, on two large online cohorts with (n = 274) and without (n = 290) ASC, matched for gender, age and education. Participants had to indicate where they would sit in a waiting room. Each seat was associated with different probabilities of approaching/avoiding emotional individuals. Importantly, the task was implicit, as participants were not instructed to learn, and emotional expressions were never mentioned. We applied both categorical analyses contrasting the ASC and TD groups and dimensional factor analysis on affective questionnaires.

RESULTS

Contrary to our hypothesis, participants showed spontaneous learning from socioemotional outcomes, regardless of their diagnostic group. Yet, when accounting for dimensional variations in autistic traits, as well as depression and anxiety, two main findings emerged among females who failed to develop explicit learning strategies: (1) autism severity in ASC correlated with reduced learning to approach happy individuals; (2) anxiety-depression severity across both ASC and TD participants correlated with reduced learning to approach/avoid happy/angry individuals, respectively.

CONCLUSIONS

Implicit spontaneous learning from socioemotional outcomes is not generally impaired in autism but may be specifically associated with autism severity in females with ASC, when they do not have an explicit strategy for adapting to their social environment. Clinical diagnosis and intervention ought to take into account individual differences in their full complexity, including the presence of co-morbid anxiety and depression, when dealing with social atypicalities in autism.

Caregivers' Assessment of the Sensory Processing Patterns Exhibited by Children with Autism in the Gulf Region

This study explored the nature, prevalence, and developmental profiles of sensory processing disorders among children with autism spectrum disorder (ASD). The participants comprised 119 children with ASD and 30 typically developing children and their parents. The Child Sensory Profile-2 was used to assess the children's sensory processing characteristics. The children with ASD exhibited elevated sensory processing difficulties. Deficits were observed in all the sensory modalities among the children with ASD, except the visual processing modality. Age-related improvements were observed in most sensory processing domains, although non-significant differences were noted in three domains. These findings should enhance understanding of the sensory challenges faced by children with ASD and contribute to the development of individually tailored, targeted, and age-specific therapeutic interventions.

Executive Function Assessment in 2-Year-Olds Born Preterm

OBJECTIVE

 Our objective was to investigate the executive function and its relationship with gestational age, sex, maternal education, and neurodevelopmental outcome at 2 years corrected age in children born preterm.

METHOD

 Executive function was assessed by means of the Multisearch Multilocation Task (MSML), Reversed Categorization Task (RevCat), and Snack Delay Task (SDT). Infant and maternal characteristics were gathered from the child's record. The developmental outcome was measured by the Bayley Scales and a multidisciplinary risk evaluation for autism.

RESULTS

 The executive function battery was completed by 97 children. The majority were able to successfully complete the MSML and SDT but failed RevCat. The lower the gestational age and the maternal education, the lower the executive function scores. Better cognition and motor function, as well as low autism risk, were associated with better executive function scores. Executive function was not related to sex.

INTERPRETATION

 This cohort study provides evidence that it is feasible to assess executive function in 2-year-olds born preterm. Executive function is related to gestational age and maternal education and is positively correlated with behavioral outcome. Therefore, executive functions can be a valuable target for early intervention, resulting in improvements in neurodevelopmental outcomes in children born preterm.

Compassion focused therapy for self-stigma and shame in autism: a single case pre-experimental study

Introduction

Exposure to public stigma can lead to the internalization of autism-related stigma (i.e., self-stigma), associated with negative health, occupational and social outcomes. Importantly, self-stigma is linked to shame and social isolation. Although elevated self-stigma has been reported in autistic adults, to the best of our knowledge, interventions designed to target this issue are lacking. Compassion is an effective way to reduce the emotional correlates of self-stigma (i.e., shame) and their impacts on mental health. However, no study has investigated whether compassion focused therapy (CFT) can effectively reduce self-stigma in autistic adults. The present study aims at investigating whether and how self-compassion improvement following CFT may reduce self-stigma and shame in an autistic individual.

Methods

A single case pre-experimental design (SCED) was used with weekly repeated measures during four phases: (i) pure baseline without any intervention (A), (ii) case conceptualization (A'), (iii) intervention (B) where CFT was delivered, (iv) follow-up without intervention (FU). The participant is a 46-year-old autistic man with high self-stigma and shame. Self-report measures of self-compassion and self-stigma and a daily idiographic measure of shame were used.

Results

There was a large increase in self-compassion between pure baseline (A) and the intervention phase (A'B) (Tau-U = 0.99), maintained at follow-up. Similarly, there was a moderate decrease of self-stigma (Tau-U = 0.32). In contrast, when we compared the whole baseline phase AA' (i.e., considering the conceptualisation phase as baseline) to the intervention (B), there was no change in self-stigma (Tau-U = -0.09). There was no change in self-stigma between the intervention (B) and follow-up (Tau-U = -0.19). There was a moderate decrease in daily shame reports between the baseline (AA') and the intervention (B) (Tau-U = 0.31) and a moderate decrease between the pure baseline (A) and intervention phase (A'B) (Tau-U = 0.51).

Conclusion

CFT was feasible for this autistic client and our results show that CFT led to the improvement of self-compassion. Changes on self-stigma measures were moderate. Self-stigma may need more time to change. Because self-stigma is involved in poorer social functioning and mental health in autistic adults, our results are promising and suggesting conducting more large-scale studies on CFT in autistic adults.

Systematic bibliometric and visualized analysis of research hotspots and trends in artificial intelligence in autism spectrum disorder

Background

Artificial intelligence (AI) has been the subject of studies in autism spectrum disorder (ASD) and may affect its identification, diagnosis, intervention, and other medical practices in the future. Although previous studies have used bibliometric techniques to analyze and investigate AI, there has been little research on the adoption of AI in ASD. This study aimed to explore the broad applications and research frontiers of AI used in ASD.

Methods

Citation data were retrieved from the Web of Science Core Collection (WoSCC) database to assess the extent to which AI is used in ASD. CiteSpace.5.8. R3 and VOSviewer, two online tools for literature metrology analysis, were used to analyze the data.

Results

A total of 776 publications from 291 countries and regions were analyzed; of these, 256 publications were from the United States and 173 publications were from China, and England had the largest centrality of 0.33; Stanford University had the highest H-index of 17; and the largest cluster label of co-cited references was machine learning. In addition, keywords with a high number of occurrences in this field were autism spectrum disorder (295), children (255), classification (156) and diagnosis (77). The burst keywords from 2021 to 2023 were infants and feature selection, and from 2022 to 2023, the burst keyword was corpus callosum.

Conclusion

This research provides a systematic analysis of the literature concerning AI used in ASD, presenting an overall demonstration in this field. In this area, the United States and China have the largest number of publications, England has the greatest influence, and Stanford University is the most influential. In addition, the research on AI used in ASD mostly focuses on classification and diagnosis, and "infants, feature selection, and corpus callosum are at the forefront, providing directions for future research. However, the use of AI technologies to identify ASD will require further research.

Buspirone in Autism Spectrum Disorder: A Systematic Review

The aim of this systematic review is to appraise the current evidence on the efficacy and safety of buspirone in core symptoms of autism spectrum disorder (ASD), co-occurring anxiety, and other associated symptoms. Major medical literature databases were searched for randomized controlled trials (RCTs), open-label trials, and any other relevant studies or clinical trials reporting on pediatric (age < 18 years) patients with ASD treated with buspirone for any reason. A total of 310 abstracts were screened, and six clinical trials were selected for inclusion. Out of these six clinical trials, two were RCTs (n =166 and 40), two open-label trials (n= 26 and 4), and one cross-over study (n = 1). We also included one retrospective chart review (n=31). Meta-analysis was not performed due to a lack of homogeneity in the two RCTs. Although most of the studies reported improved overall symptoms, they had different outcome measures. The quality of evidence available is low, and there is a need for higher-power studies in the future. Most studies suggested that buspirone was well tolerated and safe in pediatric patients with ASD. Based on the data, there is insufficient evidence to make conclusive recommendations on buspirone for improvement in core symptoms of ASD or cooccurring anxiety, irritability, or hyperactivity symptoms in the pediatric population. Given there are limited approved therapies for co-occurring anxiety, buspirone could be used as a safe off-label option due to the lack of behavioral activation and any serious adverse reactions.

Effect of Longitudinal Practice in Real and Virtual Environments on Motor Performance, Physical Activity and Enjoyment in People with Autism Spectrum Disorder: A Prospective Randomized Crossover Controlled Trial

(1) Background: People with ASD commonly present difficulty performing motor skills and a decline in physical activity (PA) level and low enjoyment of PA. We aimed to evaluate whether longitudinal practice of an activity in virtual and real environments improves motor performance and whether this improvement is transferred to a subsequent practice when changing the environment, promoting PA and providing enjoyment; (2) Methods: People with ASD, aged between 10 and 16 years, were included and distributed randomly into two opposite sequences. The participants performed a 10 session protocol, with five sessions practicing in each environment (virtual or real). Heart rate measurement was carried out and an enjoyment scale was applied; (3) Results: 22 participants concluded the protocol. Sequence A (virtual first) presented an improvement in accuracy and precision and transferred this when changing environment; they also had a greater change in heart rate reserve. The majority of participants reported "fun" and "great fun" levels for enjoyment; (4) Conclusions: The virtual reality activity presented a higher level of difficulty, with greater gains in terms of transference to the real environment. Considering PA, our task provided very light to light activity and the majority of participants enjoyed the task.

Development of a phenotype ontology for autism spectrum disorder by natural language processing on electronic health records

BACKGROUND

Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by restricted, repetitive behavior, and impaired social communication and interactions. However, significant challenges remain in diagnosing and subtyping ASD due in part to the lack of a validated, standardized vocabulary to characterize clinical phenotypic presentation of ASD. Although the human phenotype ontology (HPO) plays an important role in delineating nuanced phenotypes for rare genetic diseases, it is inadequate to capture characteristic of behavioral and psychiatric phenotypes for individuals with ASD. There is a clear need, therefore, for a well-established phenotype terminology set that can assist in characterization of ASD phenotypes from patients' clinical narratives.

METHODS

To address this challenge, we used natural language processing (NLP) techniques to identify and curate ASD phenotypic terms from high-quality unstructured clinical notes in the electronic health record (EHR) on 8499 individuals with ASD, 8177 individuals with non-ASD psychiatric disorders, and 8482 individuals without a documented psychiatric disorder. We further performed dimensional reduction clustering analysis to subgroup individuals with ASD, using nonnegative matrix factorization method.

RESULTS

Through a note-processing pipeline that includes several steps of state-of-the-art NLP approaches, we identified 3336 ASD terms linking to 1943 unique medical concepts, which represents among the largest ASD terminology set to date. The extracted ASD terms were further organized in a formal ontology structure similar to the HPO. Clustering analysis showed that these terms could be used in a diagnostic pipeline to differentiate individuals with ASD from individuals with other psychiatric disorders.

CONCLUSION

Our ASD phenotype ontology can assist clinicians and researchers in characterizing individuals with ASD, facilitating automated diagnosis, and subtyping individuals with ASD to facilitate personalized therapeutic decision-making.

Autism Spectrum Disorder Diagnostic Criteria Changes and Impacts on the Diagnostic Scales-Utility of the 2nd and 3rd Versions of the Gilliam Autism Rating Scale (GARS)

There is joint agreement among professionals internationally on the importance of diagnosing autism spectrum disorders (ASD) in the early stages of the emergence of symptoms. Criteria changes for the diagnosis of ASD need updated versions of the scale to make the diagnosis feasible. This study aimed to evaluate the level of overlap between two different versions of the Gilliam Autism Rating Scale (GARS-2 and GARS-3), which have been updated based on changes in DSM-IV and DSM-5 on a Kurdish sample of individuals at risk of having ASD and Intellectual Disability, referred to the Bahoz center in the Kurdistan Region of Iraq. A group of 148 cases with ASD and developmental disabilities (DD) was evaluated using the 2nd and 3rd versions of the GARS scale to understand the level of cases that confirm an ASD diagnosis in both scales. Ninety-six individuals (65%) scored about the cut-off score for being diagnosed with ASD based on the GARS-2, and 137 individuals (93%) scored above the cut-off score based on the GARS-3. Moreover, keeping updated and meeting the changing demand of standardization and cultural suitability of the updating scales is a challenge. This challenge is due to the shortage of infrastructure sources and lack of established professionals in low- and middle-income countries (LMICs). Findings indicated that GARS-3, updated based on the DSM-5, tends to diagnose children with accompanying diagnoses and different levels of symptoms severity of ASD at different age levels. Further studies are needed to help professionals and policymakers in low- and middle-income countries understand the updated versions of the available scales and depend on the older version, which must be considered cautiously.

Cognitive deficits in children with autism spectrum disorders: Toward an integrative approach combining social and non-social cognition

Autism spectrum disorder (ASD) is associated with neurocognitive impairment, including executive dysfunctioning and social cognition (SC) deficits. Cognitive remediation (CR) is a behavioral training-based intervention aiming to improve cognitive processes. Its first use in psychiatry interested patients with schizophrenia, in whom promising results have been shown. Integrated CR programs targeting both social and non-social cognition have demonstrated to be effective in improving both cognitive domains and functional outcomes. CR studies in children and adolescents with ASD are still new, those regarding CR approaches combining social and executive functioning remediation are scares. One study examining the efficacy of cognitive enhancement therapy (CET) for improving cognitive abilities in ADS adults, showed significant differential increases in neurocognitive function and large social-cognitive improvements. Therefore, taking into account the overlap between ASD and schizophrenia, and considering the close link between executive functions (EF) and SC, we suggest that integrative approach in ASD could result in better outcomes. The present perspective aimed to highlight cognitive remediation (CR) programs contributions in ASD (especially in children and adolescents), and to discuss the value of combining social and non-social programs.

Deep learning for neuroimaging-based diagnosis and rehabilitation of Autism Spectrum Disorder: A review

Accurate diagnosis of Autism Spectrum Disorder (ASD) followed by effective rehabilitation is essential for the management of this disorder. Artificial intelligence (AI) techniques can aid physicians to apply automatic diagnosis and rehabilitation procedures. AI techniques comprise traditional machine learning (ML) approaches and deep learning (DL) techniques. Conventional ML methods employ various feature extraction and classification techniques, but in DL, the process of feature extraction and classification is accomplished intelligently and integrally. DL methods for diagnosis of ASD have been focused on neuroimaging-based approaches. Neuroimaging techniques are non-invasive disease markers potentially useful for ASD diagnosis. Structural and functional neuroimaging techniques provide physicians substantial information about the structure (anatomy and structural connectivity) and function (activity and functional connectivity) of the brain. Due to the intricate structure and function of the brain, proposing optimum procedures for ASD diagnosis with neuroimaging data without exploiting powerful AI techniques like DL may be challenging. In this paper, studies conducted with the aid of DL networks to distinguish ASD are investigated. Rehabilitation tools provided for supporting ASD patients utilizing DL networks are also assessed. Finally, we will present important challenges in the automated detection and rehabilitation of ASD and propose some future works.

Resources, Problems and Challenges of Autism Spectrum Disorder Diagnosis and Support System in Poland

The article refers to resources, problems and challenges of autism diagnosis and support system in Poland. The resources include: the increasing number of specialists, diagnostic and therapeutic centres, well-established course of education for people working with youths, standardised and normalised diagnostic tools. The diagnostic process is not without some areas in need of our focus: the tendency of some specialists to make unauthorised diagnosis, overshadowing; underestimation of comorbidity of ASD with other disorders. The challenges refer to introducing an effective system of monitoring the services provided in form of certification and control in order to prevent their abuse, initiating category of temporary diagnosis; paying more attention on individual's resources, better cooperation among specialists, teachers and families, developing and unifying diagnostic standards.

Exploring an e-learning community's response to the language and terminology use in autism from two massive open online courses on autism education and technology use

LAY ABSTRACT

Within the neurodiversity movement, one recent divergence is in the semantic choice of language when describing autism, as members of the autism and autistic community preferred to use identity-first language (autistic person), whereas professionals were more likely to use person-first language (person with autism). This study explored 803 e-learners' responses from their comments across two massive open online courses on autism education held between 2017 and 2019. Learners agreed that autistic individuals should guide others on which terminology to use when describing autism, and although identity-first language acknowledges autism as part of an individual's identity, it can also conjure up negative stereotypes and be stigmatising. Although family, friends and professionals highlighted that the diagnostic label is a way to facilitate understanding across stakeholder groups and help autistic individuals gain access to support, autistic self-advocates found the process of disclosing autism as a form of disability to conflict with their sense of identity, and broader terms such as 'autism spectrum' failed to capture individual strengths and weaknesses. Semantic language choices may matter less as long as the person's difficulties are clearly acknowledged, with adaptations made to meet their specific needs. Adding to a growing body of literature on terminology use in autism research and practice, we highlight that language used when describing autism should follow the autistic individual's lead, with the primary focus on communicating an individual's strengths and difficulties, to foster a sense of positive autism identity and inclusivity, and enable access to appropriate support.

Implications of Applying "Clinically Significant Impairment" to Autism Assessment: Commentary on Six Problems Encountered in Clinical Practice

The addition of 'clinically significant impairment' (American Psychiatric Association, Diagnostic and statistical manual of mental disorders, Author, 2013) to the diagnostic criteria for autism in DSM-5 attempts to establish a threshold for the condition. However, the increased prominence of the neurodiversity paradigm and social model of disability runs counter to the idea that characteristics of autism are fundamentally impairing. Consequently, diagnostic criteria for autism are becoming misaligned with the contemporary views of 'disorder' and 'disability'. In this commentary, we outline six clinical issues that arise from this misalignment during diagnostic assessment for autism, and the tension this creates in making diagnostic decisions. We conclude by considering ways the 'clinically significant impairment' criterion could be changed, and the implications this would have on clinical practice, and the concept of autism.

Autism Spectrum Disorder: Investigating Predictive Adaptive Behavior Skill Deficits in Young Children

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental disorder that consists of difficulties with social communication and language, as well as the presence of restricted and repetitive behaviors. These deficits tend to present in early childhood and usually lead to impairments in functioning across various settings. Moreover, these deficits have been shown to negatively impact adaptive behavior and functioning. Thus, early diagnosis and intervention is vital for future success within this population. The purpose of this study was to further examine the subscales that comprise the adaptive behavior section of the Bayley®-III to determine which of the ten subscales are predictive of ASD in young children (i.e., ≤ three years of age). A retrospective file review of 273 children participating in Kentucky's early intervention program, First Steps, was completed. The children ranged in age from 18 to 35 months. A binary logistic regression was used to assess the subscales that comprise the adaptive behavior of the section of the Bayley®-III to determine which of the ten subscales are predictive of ASD in young children (i.e., ≤ three years of age). The results indicated that individual lower raw scores in communication, community use, functional preacademics, home living, health and safety, leisure, self-care, self-direction, and social subscales were predictive of an autism diagnosis.

Gender Differences in Psychological Symptoms and Psychotherapeutic Processes in Japanese Children

Gender differences have been documented in the prevalence of psychological symptoms. Tic disorders and autism spectrum disorder (ASD) are more common in male clinical samples, while selective mutism and trichotillomania are more common in female clinical samples. In a review of 84 published case studies of Japanese children, this study explored gender differences in the prevalence of four categories of symptoms and expressions made in therapy for tics, selective mutism, autism spectrum disorder (ASD), and trichotillomania. Case studies were evaluated using both qualitative coding and statistical analysis. The findings were mostly consistent with epidemiological surveys and empirical research on adults. The gender differences in symptom prevalence and their expression could be summarized as differences in more direct aggression for boys versus indirect aggression for girls. The objective and progress in the therapy were to control impulsive energy for boys and to express energy for girls.

Common and unique multimodal covarying patterns in autism spectrum disorder subtypes

BACKGROUND

The heterogeneity inherent in autism spectrum disorder (ASD) presents a substantial challenge to diagnosis and precision treatment. Heterogeneity across biological etiologies, genetics, neural systems, neurocognitive attributes and clinical subtypes or phenotypes has been observed across individuals with ASD.

METHODS

In this study, we aim to investigate the heterogeneity in ASD from a multimodal brain imaging perspective. The Autism Diagnostic Observation Schedule (ADOS) was used as a reference to guide functional and structural MRI fusion. DSM-IV-TR diagnosed Asperger's disorder (n = 79), pervasive developmental disorder-not otherwise specified [PDD-NOS] (n = 58) and Autistic disorder (n = 92) from ABIDE II were used as discovery cohort, and ABIDE I (n = 400) was used for replication.

RESULTS

Dorsolateral prefrontal cortex and superior/middle temporal cortex are the primary common functional-structural covarying cortical brain areas shared among Asperger's, PDD-NOS and Autistic subgroups. Key differences among the three subtypes are negative functional features within subcortical brain areas, including negative putamen-parahippocampus fractional amplitude of low-frequency fluctuations (fALFF) unique to the Asperger's subtype; negative fALFF in anterior cingulate cortex unique to PDD-NOS subtype; and negative thalamus-amygdala-caudate fALFF unique to the Autistic subtype. Furthermore, each subtype-specific brain pattern is correlated with different ADOS subdomains, with social interaction as the common subdomain. The identified subtype-specific patterns are only predictive for ASD symptoms manifested in the corresponding subtypes, but not the other subtypes.

CONCLUSIONS

Although ASD has a common neural basis with core deficits linked to social interaction, each ASD subtype is strongly linked to unique brain systems and subdomain symptoms, which may help to better understand the underlying mechanisms of ASD heterogeneity from a multimodal neuroimaging perspective.

LIMITATIONS

This study is male based, which cannot be generalized to the female or the general ASD population.

[Validity of the Scale of Pervasive Developmental Disorder in a Clinical Sample of Adults with Intellectual Disability]

OBJECTIVES

The study assesses the diagnostic validity of the Scale of Pervasive Developmental Disorder in Mentally Retarded Persons (PDD-MRS).

METHODS

Unblinded conduct of PDD-MRS in a clinical psychiatric sample of adults with intellectual disability (ID; N = 109) and suspect of autism.

RESULTS

For a cut-off-score of 10, sensitivity was 89 %, specificity 62 % and the Area Under the Curve (AUC) 0.83. The total score was independent of age, gender and level of ID. However the diagnostic validity was better balanced in adults with mild to moderate ID (sensitivity/specificity: 85 %/73 %) compared to those with severe to profound ID (93 %/42 %). The SEAS-M total score was correlated with various ASD screening measures (r = .3-.6), while no correlation was found for scales assessing challenging behavior.

CONCLUSION

To conclude, the PDD-MRS is a screening instrument for diagnosing autism in adults with mild to moderate ID. Knowledge of the PDD-MRS results within the consensus conference may have led to an overestimation of its diagnostic validity.

Ethical Advocacy Across the Autism Spectrum: Beyond Partial Representation

Recent debates within the autism advocacy community have raised difficult questions about who can credibly act as a representative of a particular population and what responsibilities that role entails. We attempt to answer these questions by defending a set of evaluative criteria that can be used to assess the legitimacy of advocacy organizations and other nonelectoral representatives. With these criteria in hand, we identify a form of misrepresentation common but not unique to autism advocacy, which we refer to as partial representation. Partial representation occurs when an actor claims to represent a particular group of people but appropriately engages with only a subset of that group. After highlighting symbolic and substantive harms associated with partial representation, we propose several strategies for overcoming it.

Autism as Representative of Disability

Pediatricians care for many children with autism spectrum disorder who demonstrate a wide range of abilities and needs. This population is vulnerable because of lags in diagnosis, difficulty accessing services, overlooked medical conditions, behavioral difficulties during medical visits, parental stress, bullying, comorbid mental health issues, and variable transitional care moving from adolescence to young adulthood. Comprehensive care includes earlier recognition of symptoms with timely referral to early intervention services. It includes primary pediatricians partnering with the family, developmental pediatricians, and other specialists to reduce the vulnerabilities by medical advocacy, family education, and appropriate behavior intervention to improve functioning.

Gut Microbiota Dysbiosis Associated With Altered Production of Short Chain Fatty Acids in Children With Neurodevelopmental Disorders

While gut microbiota dysbiosis has been linked with autism, its role in the etiology of other neurodevelopmental disorders (NDD) is largely underexplored. To our knowledge this is the first study to evaluate gut microbiota diversity and composition in 36 children from the Republic of Serbia diagnosed with NDD and 28 healthy children. The results revealed an increased incidence of potentially harmful bacteria, closely related to Clostridium species, in the NDD patient group compared to the Control group: Desulfotomaculum guttoideum (P < 0.01), Intestinibacter bartlettii (P < 0.05), and Romboutsia ilealis (P < 0.001). On the other hand, significantly lower diversity of common commensal bacteria in the NDD group of patients was noticed. Enterococcus faecalis (P < 0.05), Enterococcus gallinarum (P < 0.01), Streptococcus pasteurianus (P < 0.05), Lactobacillus rhamnosus (P < 0.01) and Bifidobacteria sp. were detected in lower numbers of patients or were even absent in some NDD patients. In addition, butyrate-producing bacteria Faecalibacterium prausnitzii (P < 0.01), Butyricicoccus pullicaecorum (P < 0.05), and Eubacterium rectale (P = 0.07) were less frequent in the NDD patient group. In line with that, the levels of fecal short chain fatty acids (SCFAs) were determined. Although significant differences in SCFA levels were not detected between NDD patients and the Control group, a positive correlation was noted between number of rDNA amplicons obtained with universal primers and level of propionic acid, as well as a trend for levels of total SCFAs and butyric acid in the Control group. This correlation is lost in the NDD patient group, indicating that NDD patients' microbiota differs from the microbiota of healthy children in the presence or number of strong SCFA-producing bacteria. According to a range-weighted richness index it was observed that microbial diversity was significantly lower in the NDD patient group. Our study reveals that the intestinal microbiota from NDD patients differs from the microbiota of healthy children. It is hypothesized that early life microbiome might have an impact on GI disturbances and accompanied behavioral problems frequently observed in patients with a broad spectrum of NDD.

Adaptation of Diagnosis from Autism Spectrum Disorder to Social Communication Disorder in Adolescents with ADHD

Here, we describe a case in which an original diagnosis of Attention Deficit Hyperactivity Disorder (ADHD) and Asperger's syndrome was later adapted to social communication disorder, to meet the new guidelines. First, separate diagnostic labels of autism disorder, Asperger's disorder, and PDD-NOS have been replaced by one umbrella term "autism spectrum disorder". Second, the new DSM-5 criteria are more stringent than the old criteria. For example, observation of a higher number of symptoms is necessary to meet the criteria, such as restricted interests and repetitive behaviors. Third, the communication and social interaction domains are combined into one, titled "social/communication deficits." Finally, requirement of a delay in language development is no longer necessary to establish a diagnosis of autism.

Persistent homology analysis of brain transcriptome data in autism

Persistent homology methods have found applications in the analysis of multiple types of biological data, particularly imaging data or data with a spatial and/or temporal component. However, few studies have assessed the use of persistent homology for the analysis of gene expression data. Here we apply persistent homology methods to investigate the global properties of gene expression in post-mortem brain tissue (cerebral cortex) of individuals with autism spectrum disorders (ASD) and matched controls. We observe a significant difference in the geometry of inter-sample relationships between autism and healthy controls as measured by the sum of the death times of zero-dimensional components and the Euler characteristic. This observation is replicated across two distinct datasets, and we interpret it as evidence for an increased heterogeneity of gene expression in autism. We also assessed the topology of gene-level point clouds and did not observe significant differences between ASD and control transcriptomes, suggesting that the overall transcriptome organization is similar in ASD and healthy cerebral cortex. Overall, our study provides a novel framework for persistent homology analyses of gene expression data for genetically complex disorders.

Accuracy of the Childhood Autism Rating Scale: a systematic review and meta-analysis

AIM

To assess the accuracy of the Childhood Autism Rating Scale (CARS) through systematic review and meta-analysis.

METHOD

Studies that provided quantitative values for the reliability and validity for all versions of CARS were searched through MEDLINE, CINAHL, PsycINFO, Embase, and OpenDissertations.

RESULTS

A total of 24 studies with 4433 participants were included in our analysis. Meta-analysis showed that the summary Cronbach's alpha regarding a team of physicians and psychologists or others subgroup, derived from six studies (952 participants), was considered to be acceptable at 0.90 (95% confidence interval, 0.87-0.92) with moderate heterogeneity. Analysis of two 'low risk of bias' studies on the criterion validity for CARS with a cut-off of 30 and DSM-IV resulted in sensitivity of 0.86 and 0.71 and specificity of 0.79 and 0.75.

INTERPRETATION

Through the results of the current systematic review and meta-analysis, the internal consistency can be considered to be acceptable for a team of physicians and psychologists or others subgroup. In terms of the criterion validity, the sensitivity was thought to be acceptable although the specificity was not, suggesting that CARS should be used along with other confirmatory tools.

WHAT THIS PAPER ADDS

The Childhood Autism Rating Scale can be considered as a supplementary diagnostic tool for autism spectrum disorder.

Autism spectrum disorder

Sources of data

This article is based on key recent published literature including international guidelines and relevant reviews and meta-analyses. Authors have also supplemented this material with their own clinical experience.

Areas of agreement

There is an agreement that autism spectrum disorder (ASD) have a strong hereditary component. There is also a consensus that the reported prevalence estimates have increased in the last 5 years. There is strong support for using the broader spectrum disorder conceptualization of the DSM-5.

Areas of controversy

Higher public awareness of ASD has generated several controversial theories of causation. We review a number of environmental risk factors receiving media attention including: vaccines, mercury, heavy metal exposure and Selective Serotonin Uptake Inhibitors (SSRIs). Popular yet controversial treatment interventions are discussed. Early diagnostic screening tools are also addressed.

Growing points

There is increasing scientific interest in identifying biomarkers of autism with potential for early diagnosis, prognostic indicators and predictive treatment responses. We review evidence from genetics, neuroimaging and eye tracking as candidate biomarkers.

Area timely for developing research

Family studies point to a strong hereditary component in the aetiology of autism. However these studies have not established 100% concordance rates, suggesting a role for environmental factors. The gene-environment interplay has not received enough attention in scientific research. This represents an important new avenue for research in ASD.

Recognising autism: a latent transition analysis of parental reports of child autistic spectrum disorder 'red flag' traits before and after age 3

PURPOSE

It has been proposed that parents should be educated about child autistic spectrum disorder (ASD) 'red flag' traits to help professionals identify and address concerning behaviours as early as possible. This study aimed to empirically demonstrate that established/recognised 'red flag' traits in the first 3 years of life would reliably predict ASD risk severity in later childhood, associated with established ASD risk correlates and mirroring functioning diagnostic categories.

METHODS

Using retrospective parental report data from the Mental Health of Children and Young People in Great Britain survey (N = 7977), latent class analysis (LCA) and a quasi -latent transition analysis were used to (1) identify profiles of variation in parent reports of child 'red flag' traits before and after age 3 and (2) model transitions in risk from 3 years and below to ≥ 3 years, respectively, per the 'optimal outcome' model.

RESULTS

Three distinct classes, each characterised by variation in parent 'red flag' trait reporting were identified for the '≤ 3 years of age' and the '≥ 3 years of age' data. Both LCA class profiles comprised groups of children characterised by low, medium and high ASD risk. Dose-response effects for a number of recognised ASD correlates across the low, moderate and high risk '≥ 3 years of age' classes seemed to validate older classes in terms of ASD relevance. Over 54% of children characterised by the highest levels of ASD 'red flag' trait probability at 3 years and below (2% of sample), also populated the high-risk class evidenced in the '≥ 3 years of age' LCA.

CONCLUSIONS

Retrospective parental reports of child ASD 'red flag' traits ≤ 3 years of age were reliable indicators of ASD risk in later childhood.

California Autism Prevalence Trends from 1931 to 2014 and Comparison to National ASD Data from IDEA and ADDM

Time trends in U.S. autism prevalence from three ongoing datasets [Individuals with Disabilities Education Act, Autism and Developmental Disabilities Monitoring Network, and California Department of Developmental Services (CDDS)] are calculated using two different methods: (1) constant-age tracking of 8 year-olds and (2) age-resolved snapshots. The data are consistent across methods in showing a strong upward trend over time. The prevalence of autism in the CDDS dataset, the longest of the three data records, increased from 0.001% in the cohort born in 1931 to 1.2% among 5 year-olds born in 2012. This increase began around ~ 1940 at a rate that has gradually accelerated over time, including notable change points around birth years 1980, 1990 and, most recently, 2007.

The Use of Multi-parametric Biomarker Profiles May Increase the Accuracy of ASD Prediction

Effective biomarkers are urgently needed to facilitate early diagnosis of autism spectrum disorder (ASD), permitting early intervention, and consequently improving prognosis. In this study, we evaluate the usefulness of nine biomarkers and their association (combination) in predicting ASD onset and development. Data were analyzed using multiple independent mathematical and statistical approaches to verify the suitability of obtained results as predictive parameters. All biomarkers tested appeared useful in predicting ASD, particularly vitamin E, glutathione-S-transferase, and dopamine. Combining biomarkers into profiles improved the accuracy of ASD prediction but still failed to distinguish between participants with severe versus mild or moderate ASD. Library-based identification was effective in predicting the occurrence of disease. Due to the small sample size and wide participant age variation in this study, we conclude that the use of multi-parametric biomarker profiles directly related to autism phenotype may help predict the disease occurrence more accurately, but studies using larger, more age-homogeneous populations are needed to corroborate our findings.

A Prospective Study of the Concordance of DSM-IV and DSM-5 Diagnostic Criteria for Autism Spectrum Disorder

The transition from DSM-IV to DSM-5 criteria for autism spectrum disorder (ASD) sparked considerable concern about the potential implications of these changes. This study was designed to address limitations of prior studies by prospectively examining the concordance of DSM-IV and final DSM-5 criteria on a consecutive sample of 439 children referred for autism diagnostic evaluations. Concordance and discordance were assessed using a consistent diagnostic battery. DSM-5 criteria demonstrated excellent overall specificity and good sensitivity relative to DSM-IV criteria. Sensitivity and specificity were strongest for children meeting DSM-IV criteria for autistic disorder, but poor for those meeting criteria for Asperger's disorder and pervasive developmental disorder. Higher IQ, older age, female sex, and less pronounced ASD symptoms were associated with greater discordance.

Factors associated with DSM-5 severity level ratings for autism spectrum disorder

The newest edition of the Diagnostic and Statistical Manual of Mental Disorders (5th ed., DSM-5) introduced substantial changes to the diagnostic criteria for autism spectrum disorder, including new severity level ratings for social communication and restricted and repetitive behavior domains. The purpose of this study was to evaluate the use of these new severity ratings and to examine their relation to other measures of severity and clinical features. Participants included 248 children with autism spectrum disorder who received diagnostic evaluations at one of six Autism Treatment Network sites. Higher severity ratings in both domains were associated with younger age, lower intelligence quotient, and greater Autism Diagnostic Observation Schedule-Second Edition domain-specific symptom severity. Greater restricted and repetitive behavior severity was associated with higher parent-reported stereotyped behaviors. Severity ratings were not associated with emotional or behavioral problems. The new DSM-5 severity ratings in both domains were significantly associated with behavioral observations of autism severity but not with measures of other behavioral or emotional symptoms. However, the strong associations between intelligence quotient and DSM-5 severity ratings in both domains suggest that clinicians may be including cognitive functioning in their overall determination of severity. Further research is needed to examine clinician decision-making and interpretation of these specifiers.

Diagnostic Utility of the ADI-R and DSM-5 in the Assessment of Latino Children and Adolescents

Latino children in the US are systematically underdiagnosed with Autism Spectrum Disorder (ASD); therefore, it is important that recent changes to the diagnostic process do not exacerbate this pattern of under-identification. Previous research has found that the Autism Diagnostic Interview-Revised (ADI-R) algorithm, based on the Diagnostic and Statistical Manual of Mental Disorder, Fourth Edition, Text Revision (DSM-IV-TR), has limitations with Latino children of Spanish speaking parents. We evaluated whether an ADI-R algorithm based on the new DSM-5 classification for ASD would be more sensitive in identifying Latino children of Spanish speaking parents who have a clinical diagnosis of ASD. Findings suggest that the DSM-5 algorithm shows better sensitivity than the DSM-IV-TR algorithm for Latino children.

Validation of autism spectrum disorder diagnoses recorded in the Clinical Practice Research Datalink, 1990-2014

Background

Prior studies have reported that the validity of autism spectrum disorder (ASD) diagnoses recorded in the Clinical Practice Research Datalink (CPRD) was high; however, diagnostic criteria and screening practices have changed since the last study was published in 2004.

Objectives

1) To calculate the positive predictive value (PPV) of ASD diagnoses recorded in the CPRD compared to original medical records and 2) to describe characteristics of cases and use of clinical codes that support the ASD diagnosis as recorded in the electronic data by general practitioners over time.

Methods

We identified children with a code for ASD (autism spectrum disorder, autism, Asperger’s, or pervasive developmental disorder) in the CPRD from 1990 to 2014. We evaluated presence of codes in the electronic medical record indicating the presence of developmental delay, speech delay, behavioral problems, and other supporting clinical codes (e.g., therapy, referrals, etc.). We also evaluated changes in recording of these clinical codes over time. We compared the information present in the electronic medical record to original medical records for a sample of cases and calculated PPVs of ASD diagnoses recorded in the CPRD.

Results

We identified 2154 children with a code for ASD. The mean age at diagnosis was 5.8 years, and 84% of cases were male. The majority (78.4%) had 1 ASD diagnosis code in their electronic medical record. Approximately half of the cases had a code indicating behavioral problem, developmental delay, or speech delay, and 24.7% had a code indicating specialist referral or visit. After review of original medical records, the PPV of ASD diagnoses recorded in the CPRD was 91.9%.

Conclusion

The results of this study suggest that ASD diagnoses recorded in the CPRD are reliable and can be used with confidence to study ASD.

An evaluation of the clinical application of the DSM-5 for the diagnosis of autism spectrum disorder

INTRODUCTION

The changes to the diagnostic criteria for autism spectrum disorder (ASD) in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) were met with much controversy by researchers, clinicians, and families of individuals with ASD. The goal of this paper is to review the literature on the impact of these changes. Areas covered: This paper reviews the major changes to diagnostic criteria from DSM-IV-TR to DSM-5. It emphasizes how these changes are hypothesized to impact prevalence rates, as well as trends in characteristics of individuals who would have met previous criteria for ASD but no longer qualify for a diagnosis under DSM-5. Policy issues such as access to services and research considerations are also briefly reviewed. Expert commentary: Researchers have found that the DSM-5 diagnostic criteria for ASD may significantly impact which children receive diagnoses, which in turn affects access to services that address impairments characteristic of this disorder. Despite the fact that the DSM-5 has now been in use for four years, fewer recent studies were identified than was expected. Future research should continue to focus on the impact of changes in criteria, as well as on translational scientific advances across disciplines.

Language Ability Predicts Cortical Structure and Covariance in Boys with Autism Spectrum Disorder

There is significant clinical heterogeneity in language and communication abilities of individuals with Autism Spectrum Disorders (ASD). However, no consistent pathology regarding the relationship of these abilities to brain structure has emerged. Recent developments in anatomical correlation-based approaches to map structural covariance networks (SCNs), combined with detailed behavioral characterization, offer an alternative for studying these relationships. In this study, such an approach was used to study the integrity of SCNs of cortical thickness and surface area associated with language and communication, in 46 high-functioning, school-age children with ASD compared with 50 matched, typically developing controls (all males) with IQ > 75. Findings showed that there was alteration of cortical structure and disruption of fronto-temporal cortical covariance in ASD compared with controls. Furthermore, in an analysis of a subset of ASD participants, alterations in both cortical structure and covariance were modulated by structural language ability of the participants, but not communicative function. These findings indicate that structural language abilities are related to altered fronto-temporal cortical covariance in ASD, much more than symptom severity or cognitive ability. They also support the importance of better characterizing ASD samples while studying brain structure and for better understanding individual differences in language and communication abilities in ASD.

An Overview of Autism Spectrum Disorder, Heterogeneity and Treatment Options

Since the documented observations of Kanner in 1943, there has been great debate about the diagnoses, the sub-types, and the diagnostic threshold that relates to what is now known as autism spectrum disorder (ASD). Reflecting this complicated history, there has been continual refinement from DSM-III with 'Infantile Autism' to the current DSM-V diagnosis. The disorder is now widely accepted as a complex, pervasive, heterogeneous condition with multiple etiologies, sub-types, and developmental trajectories. Diagnosis remains based on observation of atypical behaviors, with criteria of persistent deficits in social communication and restricted and repetitive patterns of behavior. This review provides a broad overview of the history, prevalence, etiology, clinical presentation, and heterogeneity of ASD. Factors contributing to heterogeneity, including genetic variability, comorbidity, and gender are reviewed. We then explore current evidence-based pharmacological and behavioral treatments for ASD and highlight the complexities of conducting clinical trials that evaluate therapeutic efficacy in ASD populations. Finally, we discuss the potential of a new wave of research examining objective biomarkers to facilitate the evaluation of sub-typing, diagnosis, and treatment response in ASD.

Human Embryonic Stem Cells in the Treatment of Autism: A Case Series

Background: Autism spectrum disorder is a neurodevelopmental disorder accompanied by weak immune system and neuroinflammation. Multiple factors contribute to etiology of autism spectrum disorder including genetic disorders, environmental substances/toxins, imbalanced immune system, encephalitis, and viral infections. Autism spectrum disorder is an incurable disease; however, it can be managed by educational and medical interventions. Human embryonic stem cell therapy has been shown to improve blood perfusion in the brain; thus, this therapy may be effective in improving motor skills, social skills, and cognition in patients with autism spectrum disorder. Method: Three pediatric patients with autism spectrum disorder were administered human embryonic stem cell therapy. Their treatment plan comprised 3 to 4 therapy sessions (T1, T2, T3, T4) that were 4 to 6 weeks in length, with 4- to 8-month gap phases separating each therapy session. Results: The patients showed improvements in eye coordination, writing, balancing, cognition, and speech and showed reduced hypersensitivity to noises and smells. Conclusion: The use of human embryonic stem cell therapy may be a safe and effective treatment for patients with autism spectrum disorder. Studies with larger sample sizes are needed to support the use of human embryonic stem cell therapy in this patient population.

Searching for convergent pathways in autism spectrum disorders: insights from human brain transcriptome studies

Autism spectrum disorder (ASD) is one of the most heritable neuropsychiatric conditions. The complex genetic landscape of the disorder includes both common and rare variants at hundreds of genetic loci. This marked heterogeneity has thus far hampered efforts to develop genetic diagnostic panels and targeted pharmacological therapies. Here, we give an overview of the current literature on the genetic basis of ASD, and review recent human brain transcriptome studies and their role in identifying convergent pathways downstream of the heterogeneous genetic variants. We also discuss emerging evidence on the involvement of non-coding genomic regions and non-coding RNAs in ASD.

Verbal Thinking and Inner Speech Use in Autism Spectrum Disorder

The extent to which cognition is verbally mediated in neurotypical individuals is the subject of debate in cognitive neuropsychology, as well as philosophy and psychology. Studying "verbal thinking" in developmental/neuropsychological disorders provides a valuable opportunity to inform theory building, as well as clinical practice. In this paper, we provide a comprehensive, critical review of such studies among individuals with autism spectrum disorder (ASD). ASD involves severe social-communication deficits and limitations in cognitive/behavioural flexibility. The prevailing view in the field is that neither cognition nor behaviour is mediated verbally in ASD, and that this contributes to diagnostic features. However, our review suggests that, on the contrary, most studies to date actually find that among people with ASD cognitive task performance is either a) mediated verbally in a typical fashion, or b) not mediated verbally, but at no obvious cost to overall task performance. Overall though, these studies have methodological limitations and thus clear-cut conclusions are not possible at this stage. The aim of the review is to take stock of existing empirical findings, as well as to help develop the directions for future research that will resolve the many outstanding issues in this field.

ASD Symptom Severity in Adolescence of Individuals Diagnosed with PDD-NOS in Childhood: Stability and the Relation with Psychiatric Comorbidity and Societal Participation

The current 7-year follow-up study investigated: (1) the stability of ASD severity, and (2) associations of ASD severity in adolescence with (a) childhood and concurrent psychiatric comorbidity, and (b) concurrent societal functioning. The Autism Diagnostic Observation Schedule (ADOS) and the Diagnostic Interview Schedule for Children were administered in childhood (ages 6-12) and in adolescence (ages 12-20) to 72 individuals with a pervasive developmental disorder-not otherwise specified (PDD-NOS). ADOS calibrated severity scores showed a large stability (r = .51). Psychiatric comorbidity in childhood and adolescence were not associated with ASD severity in adolescence. Mental health care use (87 %) and special education needs were high (71 %). Reevaluation of ASD severity and psychiatric comorbidity later in life seem useful when PDD-NOS is diagnosed in childhood.

The New DSM-5 Impairment Criterion: A Challenge to Early Autism Spectrum Disorder Diagnosis?

The possible effect of the DSM-5 impairment criterion on diagnosing autism spectrum disorder (ASD) in young children was examined in 127 children aged 20-47 months with a DSM-IV-TR clinical consensus diagnosis of ASD. The composite score of the Vineland Adaptive Behavior Scales (VABS) served as a proxy for the DSM-5 impairment criterion. When applying a mild level of impairment (cutoff: 1 SD below the mean on the VABS), 88 % of the cases fulfilled the impairment criterion. Sixty-nine percent fulfilled the impairment criterion at a moderate level (1.5 SDs) and 33 % at a severe level (2 SDs). Findings indicate that a strict application of the new DSM-5 impairment criterion might compromise early diagnosis of ASD.

The Effects of DSM-5 Criteria on Number of Individuals Diagnosed with Autism Spectrum Disorder: A Systematic Review

A growing body of research has raised concerns about the number of individuals diagnosed with autism spectrum disorder (ASD) according to DSM-IV-TR who may no longer qualify for diagnoses under the new DSM-5 criteria, published in May 2013. The current study systematically reviews 25 articles evaluating samples according to both DSM-IV-TR and DSM-5 ASD criteria. Consistent with previous reviews, the majority of included studies indicated between 50 and 75% of individuals will maintain diagnoses. We conducted visual analyses of subgroups using harvest plots and found the greatest decreases among high-functioning populations with IQs over 70 and/or previous diagnoses of PDD-NOS or Asperger's disorder. We discuss the potential research and clinical implications of reduced numbers of individuals diagnosed with ASD.

Heterogeneity within adult day services: a focus on centers that serve younger adults with intellectual and developmental disabilities

As the population of younger adults with intellectual and developmental disabilities continues to grow, adult day services is positioned to be a key provider of community-based care and support. In this article, researchers examine how adult day centers that serve younger adults with intellectual and developmental disabilities differ from centers that serve older and mixed age groups. One-way analyses of variance and post hoc analyses of 490 adult day services centers (N = 490) revealed significant differences in terms of participant, staffing, and organizational characteristics. These findings have important implications for service providers, researchers, and policy makers.