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Perceived social support (PSS) has been related to physical and mental well-being in typically developing individuals, but systematic characterizations of PSS in autism spectrum disorder (ASD) are limited. We compared self-report ratings of the multidimensional scale of PSS (MSPSS) among age- and IQ-matched groups of adults (18-58 years) with cognitively high-functioning ASD (N = 41), or attention-deficit/hyperactivity disorder (ADHD; N = 69), and neurotypical controls (NC; N = 69). Accompanying group comparisons, we used machine learning random forest (RF) analyses to explore predictors among a range of psychopathological and socio-emotional variables. Relative to both ADHD and NC, adults with ASD showed lower MSPSS ratings, specifically for the friends subscale (MSPSS-f). Across ASD and ADHD, interindividual differences in autism severity, affective empathy, symptoms of anxiety related to social interactions, hyperactivity/impulsivity, and somatization best predicted MSPSS-f. These relationships did not differ between clinical groups. While group comparisons demonstrated greater impairment in individuals with ASD, analyzing individuals' characteristics revealed cross-diagnoses similarities in regard to their MSPSS-f relationships. This is consistent with the Research Domain Criteria framework, supporting a trans-diagnostic approach as on the path toward "precision medicine." Autism Res 2017, 10: 866-877. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

International audience; We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n = 35,584 total samples, 11,986 with ASD). Using an enhanced analytical framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate of 0.1 or less. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained to have severe neurodevelopmental delay, whereas 53 show higher frequencies in individuals ascertained to have ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In cells from the human cortex, expression of risk genes is enriched in excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory-inhibitory imbalance underlying ASD.

There is relatively little information about prospectively reported developmental milestones from caregivers of children who go on to be diagnosed with neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD). The current study examined rates of early skill attainment in 5-year-old children who participated in a comprehensive in-person assessment for NDDs in Hirosaki in Japan. Developmental milestone data were extracted from their Maternal and Child Health Handbook (MCHH), a booklet distributed to all pregnant women as part of universal health care. Seven hundred and twenty children underwent the assessment, among whom 455 received one or more NDD diagnoses (ASD: n = 124, non-ASD NDD: n = 331). Developmental skills were organized into four domains (motor, social interaction, communication, self-help), and the cumulative number of potential delays in each domain was calculated for each participant within three different age ranges (by 12 months, by 24 months, and by 36 months). Even by age 12 months, children with ASD/NDDs showed more potential delays across domains compared to those who received no NDD diagnosis. However, differences between those with ASD and those with non-ASD NDDs were not apparent until 24 months for social interaction and communication, and 36 months for self-help. These findings provide insights into specific behaviors that could be used to screen for ASD and other NDDs. In addition, the present study indicates the potential utility of the MCHH as a broadband screening tool to educate parents about what to look for in charting their child's early development. LAY SUMMARY: The present study examined prospectively charted developmental milestones from home-based records used as part of universal health care in 720 5-year-old children from Hirosaki, Japan. All children participated in a comprehensive evaluation to determine if they met criteria for a neurodevelopmental disorder (NDD), including autism spectrum disorder (ASD). Compared to those who received no NDD diagnosis, children with NDDs exhibited higher rates of potential delays across developmental domains, including social interaction, communication, and self-help. For some children, these delays were apparent before the age of 12 months. Differences between diagnostic groups became even more pronounced by 24 and 36 months, well before the average age of diagnosis. This suggests that home-based records can be useful tools to educate caregivers about what to look for in charting their child's early development and could assist with early screening efforts.

In this work, we propose deep latent space clustering for speaker diarization using generative adversarial network (GAN) backprojection with the help of an encoder network. The proposed diarization system is trained jointly with GAN loss, latent variable recovery loss, and a clustering-specific loss. It uses x-vector speaker embeddings at the input, while the latent variables are sampled from a combination of continuous random variables and discrete one-hot encoded variables using the original speaker labels. We benchmark our proposed system on the AMI meeting corpus, and two child-clinician interaction corpora (ADOS and BOSCC) from the autism diagnosis domain. ADOS and BOSCC contain diagnostic and treatment outcome sessions respectively obtained in clinical settings for verbal children and adolescents with autism. Experimental results show that our proposed system significantly outperform the state-of-the-art x-vector based diarization system on these databases. Further, we perform embedding fusion with x-vectors to achieve a relative DER improvement of 31%, 36% and 49% on AMI eval, ADOS and BOSCC corpora respectively, when compared to the x-vector baseline using oracle speech segmentation., Submitted to ICASSP 2020

Children with autism spectrum disorder (ASD) present with heterogeneous levels of abilities and deficits. The identification of subgroups within a specific age range could be useful for understanding prognosis and treatment planning. We applied Hierarchical Clustering on Principal Components (HCPC) with a sample of 188 preschoolers with ASD and identified three distinct subgroups based on multiple developmental and behavioral domains. Cluster 1 was characterized by relatively high cognitive, language and adaptive abilities, and relatively low levels of social symptoms, repetitive behaviors, and sensory issues within the sample. Cluster 2 was characterized by similarly high cognitive, language and adaptive abilities compared to Cluster 1, but more severe social deficits as well as repetitive and sensory behaviors. Finally, Cluster 3 was characterized by lower cognitive, language and adaptive abilities, and more severe social, repetitive, and sensory symptoms. These findings provide insights into how considering multiple developmental and behavioral domains and core autism symptoms simultaneously can distinguish subgroups of young children with ASD and provide more comprehensive developmental profiles. Moreover, the unique profile of children in Cluster 2 highlighted the usefulness of including different measures and informants when evaluating the abilities and deficits of preschoolers with ASD and the importance of understanding the relationships among different developmental and behavioral factors in this specific population. Autism Res 2020, 13: 796-809. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Children with autism exhibit a range of abilities and deficits in different developmental and behavioral areas, making it difficult to tailor treatment and predict outcomes. We identified three distinct subgroups among 188 preschoolers with autism spectrum disorder distinguished by the combination of measures from multiple developmental and behavioral domains. The findings revealed the importance of comprehensive profiling of the child's abilities and deficits to inform subgrouping within autism.

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 will be helpful for research in many populations, but will be particularly crucial for detecting incremental changes in youth with neurodevelopmental disorders, who may gain skills but still lag substantially behind same-aged peers. While study designs and statistical methods are under development to try to account for slow and/or non-linear, but potentially meaningful, improvements,(1) there is a dearth of measures designed to capture both growth and loss of social-communication skills. This opinion piece outlines the argument for such a measure, as well as primary issues to consider in its development.

In advance of the 2019 INSAR Conference in Montreal, Quebec, Canada, I asked the members of the Autism Research Editorial Board and the Associate Editors to write short (approximately 300 word) mini‐commentaries on what they considered to be the current gaps in research on autism spectrum disorder. The responses and styles were diverse and reflect research gaps ranging from basic biology to treatment trials to services for transition to adulthood. They reflect thoughts from countries around the world. While each of the contributions was done entirely independently, it is interesting how the theme of heterogeneity is found in many of them. There is also increasing concern over the lack of research on socioeconomic and cultural factors related to the diagnosis and treatment of autism spectrum disorder. We hope that these comments will provide food for thought.

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

In the present study, we examined how unstructured (e.g., spending time with friends or co-workers) and structured (e.g., attending social events at a place of workshop, sports teams) social participation changed from before to after high school for youth with autism spectrum disorders (ASD), as well as the longitudinal and concurrent relations between social participation and internalizing symptoms. Participants included 36 families of youth with ASD who were all in their last year of high school at the first time point of data collection, and who were out of high school for an average of 9 months at the second time point. Social participation and internalizing symptoms were determined using parental report. There was no average change in the amount of unstructured social participation after high school exit, although substantial individual variability was observed. Participation in structured social activities significantly declined after high school exit. Youth who had more structured social participation while in high school were significantly more likely to have gains in their unstructured social participation after high school exit. Turning to relationships between internalizing and social activities, more internalizing symptoms while youth with ASD were in high school significantly predicted increasing social isolation after high school exit (both in terms of structured and unstructured activities). Results point to the likely need for additional supports during the transition to adulthood for youth with ASD who have internalizing problems. Autism Res 2016. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 663-672. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

The cost associated with incorporating standardized observational assessments and diagnostic interviews in large-scale epidemiologic studies of autism spectrum disorders (ASD) risk factors can be substantial. Streamlined approaches for confirming ASD case status would benefit these studies. We conducted a multi-site, cross-sectional criterion validity study in a convenience sample of 382 three-year olds scheduled for neurodevelopmental evaluation. ASD case classification as determined by three novel assessment instruments (the Early Video-guided Autism Screener E-VAS; the Autism Symptom Interview, ASI; the Screening Tool for Autism in Toddlers Expanded, STAT-E) each designed to be administered in less than 30 minutes by lay staff, was compared to ADOS scores and DSM-based diagnostic assessment from a qualified clinician. Sensitivity and specificity of each instrument alone and in combination were estimated. Alternative cutpoints were identified under different criteria and two-stage cross validation was used to avoid overfitting. Findings were interpreted in the context of a large, prospective pregnancy cohort study utilizing a two-stage approach to case identification. Under initial cutpoints, sensitivity ranged from 0.63 to 0.92 and specificity from 0.35 to 0.70. Cutpoints giving equal weight to sensitivity and specificity resulted in sensitivity estimates ranging from 0.45 to 0.83 and specificity ranging from 0.49 to 0.86. Several strategies were well-suited for application as a second-stage case-confirmation. These included the STAT-E alone and the parallel administration of both the E-VAS and the ASI. Use of more streamlined methods of case-confirmation in large-scale prospective cohort epidemiologic investigations of ASD risk factors appears feasible. Autism Res 2017, 10: 485-501. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

This study reports on the initial validation of the Autism Symptom Interview (ASI), School-Age, a brief (15-20 min) phone interview derived from questions from the Autism Diagnostic Interview-Revised (ADI-R). The ASI, School-Age was administered by interviewers with minimal training to parents of children ages 5 to 12 who had all been previously identified with (or referred for assessment of) ASD or another neurodevelopmental disorder. Children then underwent a comprehensive assessment to determine a best-estimate clinical diagnosis of ASD (n = 159) or non-ASD (e.g. language disorder, intellectual disability, ADHD; n = 130). Clinicians who conducted the assessments were blind to ASI results. ROC analyses compared ASI scores to clinical diagnosis. Due to the small number of participants with non-ASD diagnoses who were classified as nonverbal (i.e. not yet using phrases on a daily basis), it was not possible to assess sensitivity and specificity of the nonverbal algorithm in this sample. The verbal algorithm yielded a sensitivity of 0.87 (95% CI = 0.81-0.92) and a specificity of 0.62 (95% CI = 0.53-0.70). When used in conjunction with the Autism Diagnostic Observation Schedule (ADOS), sensitivity and specificity were 0.82 (95% CI = 0.74-0.88) and 0.92 (95% CI = 0.86-0.96), respectively. Internal consistency and test-retest reliability were both excellent. Particularly for verbal school age children, the ASI may serve as a useful tool to more quickly ascertain or classify children with ASD for research or clinical triaging purposes. Additional data collection is underway to determine the utility of the ASI in children who are younger and/or nonverbal. Autism Res 2017, 10: 78-88. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Autism Spectrum Disorder (ASD or autism) is a heterogeneous neurodevelopmental disorder. We are now at a critical juncture in autism research where we have the knowledge base and expertise to begin to think about studies that view heterogeneity, not as 'statistical noise' that can be 'accounted for' using data-reduction techniques (such as group trajectories), but rather as 'informative variance' that can help form a more precise and dynamic picture of autism. In this Editorial we coin a new term and introduce the concept of 'chronogeneity' for the study of autism heterogeneity in relation to the dimension of time (chrono). Using examples of ongoing research and analytical advances we build the case for the potential utility of the concept of 'chronogeneity' and argue that a refined approach to the longitudinal investigation of autism (and other neurodevelopmental disorders) may move us closer to more precise and adaptive models of care for the children and youth affected by these disorders.

Diagnostic procedures for ASD (autism spectrum disorder) involve semi-naturalistic interactions between the child and a clinician. Computational methods to analyze these sessions require an end-to-end speech and language processing pipeline that go from raw audio to clinically-meaningful behavioral features. An important component of this pipeline is the ability to automatically detect who is speaking when i.e., perform child-adult speaker classification. This binary classification task is often confounded due to variability associated with the participants' speech and background conditions. Further, scarcity of training data often restricts direct application of conventional deep learning methods. In this work, we address two major sources of variability - age of the child and data source collection location - using domain adversarial learning which does not require labeled target domain data. We use two methods, generative adversarial training with inverted label loss and gradient reversal layer to learn speaker embeddings invariant to the above sources of variability, and analyze different conditions under which the proposed techniques improve over conventional learning methods. Using a large corpus of ADOS-2 (autism diagnostic observation schedule, 2nd edition) sessions, we demonstrate upto 13.45% and 6.44% relative improvements over conventional learning methods., Comment: Submitted to ICASSP 2020

We present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n=35,584 total samples, 11,986 with ASD). Using an enhanced Bayesian framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate ≤ 0.1. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained for severe neurodevelopmental delay, while 53 show higher frequencies in individuals ascertained for ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most of the risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In human cortex single-cell gene expression data, expression of risk genes is enriched in both excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory/inhibitory imbalance underlying ASD.

SummaryWe present the largest exome sequencing study of autism spectrum disorder (ASD) to date (n=35,584 total samples, 11,986 with ASD). Using an enhanced Bayesian framework to integrate de novo and case-control rare variation, we identify 102 risk genes at a false discovery rate ≤ 0.1. Of these genes, 49 show higher frequencies of disruptive de novo variants in individuals ascertained for severe neurodevelopmental delay, while 53 show higher frequencies in individuals ascertained for ASD; comparing ASD cases with mutations in these groups reveals phenotypic differences. Expressed early in brain development, most of the risk genes have roles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelopmental and neurophysiological changes), and 13 fall within loci recurrently hit by copy number variants. In human cortex single-cell gene expression data, expression of risk genes is enriched in both excitatory and inhibitory neuronal lineages, consistent with multiple paths to an excitatory/inhibitory imbalance underlying ASD.

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Analysis of de novo CNVs (dnCNVs) from the full Simons Simplex Collection (SSC) (N = 2,591 families) replicates prior findings of strong association with autism spectrum disorders (ASDs) and confirms six risk loci (1q21.1, 3q29, 7q11.23, 16p11.2, 15q11.2-13, and 22q11.2). The addition of published CNV data from the Autism Genome Project (AGP) and exome sequencing data from the SSC and the Autism Sequencing Consortium (ASC) shows that genes within small de novo deletions, but not within large dnCNVs, significantly overlap the high-effect risk genes identified by sequencing. Alternatively, large dnCNVs are found likely to contain multiple modest-effect risk genes. Overall, we find strong evidence that de novo mutations are associated with ASD apart from the risk for intellectual disability. Extending the transmission and de novo association test (TADA) to include small de novo deletions reveals 71 ASD risk loci, including 6 CNV regions (noted above) and 65 risk genes (FDR ≤ 0.1). Through analysis of de novo mutations in autism spectrum disorder (ASD), Sanders et al. find that small deletions, but not large deletions/duplications, contain one critical gene. Combining CNV and sequencing data, they identify 6 loci and 65 genes associated with ASD.

The Child Behavior Checklist (CBCL) has been proposed for screening of autism spectrum disorders (ASD) in clinical settings. Given the already widespread use of the CBCL, this could have great implications for clinical practice. This study examined the utility of CBCL profiles in differentiating children with ASD from children with other clinical disorders. Participants were 226 children with ASD and 163 children with attention-deficit/hyperactivity disorder, intellectual disability, language disorders, or emotional disorders, aged 2-13 years. Diagnosis was based on comprehensive clinical evaluation including well-validated diagnostic instruments for ASD and cognitive testing. Discriminative validity of CBCL profiles proposed for ASD screening was examined with area under the curve (AUC) scores, sensitivity, and specificity. The CBCL profiles showed low discriminative accuracy for ASD (AUC 0.59-0.70). Meeting cutoffs proposed for ASD was associated with general emotional/behavioral problems (EBP; mood problems/aggressive behavior), both in children with and without ASD. Cutoff adjustment depending on EBP-level was associated with improved discriminative accuracy for school-age children. However, the rate of false positives remained high in children with clinical levels of EBP. The results indicate that use of the CBCL profiles for ASD-specific screening would likely result in a large number of misclassifications. Although taking EBP-level into account was associated with improved discriminative accuracy for ASD, acceptable specificity could only be achieved for school-age children with below clinical levels of EBP. Further research should explore the potential of using the EBP adjustment strategy to improve the screening efficiency of other more ASD-specific instruments.

This article provides a selective review of advances in scientific knowledge about autism spectrum disorder (ASD), using DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, fifth edition) diagnostic criteria as a framework for the discussion. We review literature that prompted changes to the organization of ASD symptoms and diagnostic subtypes in DSM-IV, and we examine the rationale for new DSM-5 specifiers, modifiers, and severity ratings as well as the introduction of the diagnosis of social (pragmatic) communication disorder. Our goal is to summarize and critically consider the contribution of clinical psychology research, along with that of other disciplines, to the current conceptualization of ASD.

OBJECTIVE: Aside from features associated with risk of neurogenetic syndromes in general (e.g., cognitive impairment), limited progress has been made in identifying phenotype-genotype relationships in autism spectrum disorder (ASD). The objective of this study was to extend work in the Simons Simplex Collection by comparing the phenotypic profiles of ASD probands with or without identified de novo loss of function mutations or copy number variants in high-confidence ASD-associated genes or loci.METHOD: Analyses preemptively accounted for documented differences in sex and IQ in affected individuals with de novo mutations by matching probands with and without these genetic events on sex, IQ, and age before comparing them on multiple behavioral domains.RESULTS: Children with de novo mutations (N=112) had a greater likelihood of motor delay during early development (later age at walking), but they were less impaired on certain measures of ASD core symptoms (parent-rated social communication abnormalities and clinician-rated diagnostic certainty about ASD) in later childhood. These children also showed relative strengths in verbal and language abilities, including a smaller discrepancy between nonverbal and verbal IQ and a greater likelihood of having achieved fluent language (i.e., regular use of complex sentences).CONCLUSIONS: Children with ASD with de novo mutations may exhibit a "muted" symptom profile with respect to social communication and language deficits relative to those with ASD with no identified genetic abnormalities. Such findings suggest that examining early milestone differences and standardized testing results may be helpful in etiologic efforts, and potentially in clinical differentiation of various subtypes of ASD, but only if developmental and demographic variables are properly accounted for first.

Nonverbal IQ (NVIQ) was examined in 84 individuals with autism spectrum disorder (ASD) followed from age 2 to 19. Most adults who scored in the range of intellectual disability also received scores below 70 as children, and the majority of adults with scores in the average range had scored in this range by age 3. However, within the lower ranges of ability, actual scores declined from age 2 to 19, likely due in part to limitations of appropriate tests. Use of Vineland-II daily living skills scores in place of NVIQ did not statistically improve the correspondence between age 2 and age 19 scores. Clinicians and researchers should use caution when making comparisons based on exact scores or specific ability ranges within or across individuals with ASD of different ages.

The aim of this study was to examine the association between depressive symptoms and several psychosocial constructs (insight into autism symptoms, rumination, desire for social interaction, and satisfaction with social support) that may play a role in the development or maintenance of depression in verbally fluent adolescents and adults with ASD. Participants included 50 individuals with ASD and verbal IQ ≥ 70, aged 16–35 (sample size varied by measure). Elevated depressive symptoms on the Beck Depression Inventory, 2nd edition (BDI-II), were associated with greater self-perceived, autism-related impairments (n = 48), greater rumination (n = 21), and lower perceived social support (n = 37). Rumination tended to moderate the association between self-perceived autism symptoms and BDI-II scores (n = 21), and was significantly associated with ASD-related insistence on sameness behaviors (n = 18). An unexpected relationship between depressive features and social participation and motivation will need to be clarified by longitudinal research. These and similar findings contribute to our understanding of the phenomenology of depression in ASD, which is critical to the development of practical prevention and treatment. Autism Res 2014, 7: 381–391. © 2014 International Society for Autism Research, Wiley Periodicals, Inc.

This study examines whether sensory differences can be used to classify meaningful subgroups of children with autism spectrum disorder (ASD). Caregivers of children with ASD aged 2–10 years (n = 228) completed the Short Sensory Profile. Model-based cluster analysis was used to extract sensory subtypes. The relationship of these subtypes to age, gender, autism symptom severity, and nonverbal intelligence quotient (IQ) was further explored. Four distinct sensory subtypes were identified: (a) sensory adaptive; (b) taste smell sensitive; (c) postural inattentive; and (d) generalized sensory difference. The sensory subtypes differ from each other on two dimensions: (a) the severity of reported sensory differences; and (b) the focus of differences across auditory, taste, smell, vestibular and proprioceptive domains. Examination of the clinical features of each subtype reveals two possible mechanisms of sensory disturbance in autism: (a) sensory hyperreactivity; and (b) difficulties with multisensory processing. Further, the sensory subtypes are not well explained by other variables such as age, gender, IQ, and autism symptom severity. We conclude that classification of children using sensory differences offers a promising method by which to identify phenotypes in ASD. Sensory-based phenotypes may be useful in identifying behavioral features responsive to specific interventions thereby improving intervention effectiveness. Further validation of the sensory-based phenotypes by establishing neural and physiological correlates is recommended. Autism Res 2014, 7: 322–333. © 2014 International Society for Autism Research, Wiley Periodicals, Inc.

Objectives Approximately 4% of children who are deaf or hard of hearing have co-occurring autism spectrum disorder (ASD). Making an additional diagnosis of ASD in this population can be challenging, given the complexities of determining whether speech/language and social delays can be accounted for by their hearing loss, or whether these delays might be indicative of a comorbid ASD diagnosis. This exploratory study described a population of 24 children with the dual diagnosis of ASD and hearing loss. Methods Children completed a comprehensive ASD evaluation using standardized autism diagnostic instruments (Autism Diagnostic Observation Schedule, language and psychological testing). Children with permanent hearing loss who had a developmental evaluation between 2001 and 2011 and were diagnosed with an ASD based on the results of that evaluation were included. Information on communication modality, language and cognitive abilities was collected. Results The median age of diagnosis was 14 months (range 1–71) for hearing loss and 66.5 months (range 33–106) for ASD. Only 25% (n = 6) children were diagnosed with ASD ≤48 months of age and 46% by ≤6 years. Twelve (50%) children were diagnosed with ASD, 11 were diagnosed with pervasive developmental disorder not otherwise specified and 1 child had Asperger's. Most (67%) had profound degree of hearing loss. Fourteen (58%) children had received a cochlear implant, while 3 children had no amplification for hearing loss. Nine (38%) of the 24 children used speech as their mode of communication (oral communicators). Conclusions Communication delays in children who are deaf or hard of hearing are a serious matter and should not be assumed to be a direct consequence of the hearing loss. Children who received cochlear implants completed a multidisciplinary evaluation including a developmental pediatrician, which may have provided closer monitoring of speech and language progression and subsequently an earlier ASD diagnosis. Because children who are deaf or hard of hearing with ASD are challenging to evaluate, they may receive a diagnosis of ASD at older ages.

This chapter examines negative peer experiences (e.g., peer victimization, being ignored or excluded, and direct and indirect rejection) in adolescents with autism spectrum disorders (ASD). Discussion is concentrated on adolescents with higher cognitive and language abilities, with a focus on providing insights and suggestions for the next phase of studies that will inform interventions targeting negative experiences in this group. The chapter describes negative peer experiences in terms of nomenclature, general findings, and important issues for adolescents with ASD; identifies common methodological issues with previous studies on this topic; presents a study on the impact of peer victimization in adolescents with ASD using obese adolescents as a comparison group; and finally, provides suggestions for advancing research in this topic area.

The majority of adolescents with ASD spend a significant amount of the school day in general education settings; yet, many of these students exhibit problems at school. The current manuscript examined whether specific types of peer victimization were associated with a range of educational outcomes. Participants from study 1 included parents of 1221 adolescents from the Interactive Autism Network. Study 2 included 54 adolescent males and one of their parents that were recruited from a clinic registry. Both studies found that all types of victimization were associated with educational outcomes. These findings indicate that, in addition to improving overall well-being of students with ASD, reducing peer victimization could have positive effects on educational performance of these students.

Perceived social support (PSS) has been related to physical and mental well-being in typically developing individuals, but systematic characterizations of PSS in autism spectrum disorder (ASD) are limited. We compared self-report ratings of the multidimensional scale of PSS (MSPSS) among age- and IQ-matched groups of adults (18-58 years) with cognitively high-functioning ASD (N = 41), or attention-deficit/hyperactivity disorder (ADHD; N = 69), and neurotypical controls (NC; N = 69). Accompanying group comparisons, we used machine learning random forest (RF) analyses to explore predictors among a range of psychopathological and socio-emotional variables. Relative to both ADHD and NC, adults with ASD showed lower MSPSS ratings, specifically for the friends subscale (MSPSS-f). Across ASD and ADHD, interindividual differences in autism severity, affective empathy, symptoms of anxiety related to social interactions, hyperactivity/impulsivity, and somatization best predicted MSPSS-f. These relationships did not differ between clinical groups. While group comparisons demonstrated greater impairment in individuals with ASD, analyzing individuals' characteristics revealed cross-diagnoses similarities in regard to their MSPSS-f relationships. This is consistent with the Research Domain Criteria framework, supporting a trans-diagnostic approach as on the path toward "precision medicine." Autism Res 2017, 10: 866-877. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Background Minimally verbal (MV) children with autism spectrum disorder (ASD) are often assumed to be profoundly cognitively impaired and excluded from analyses due to challenges completing standardized testing protocols. A literature aimed at increasing understanding of this subgroup is emerging; however, the many methods used to define MV status make it difficult to compare studies. Understanding how different instruments and definitions used to identify MV children affect sample composition is critical to advance research on this understudied clinical population. Method The MV status of 1,470 school-aged children was defined using five instruments commonly used in ASD research. MV sample composition was compared across instruments. Analyses examined the proportion of overlap across MV subgroups and the extent to which child characteristics varied across MV subgroups defined using different definitions or combinations of measures. Results A total of 257 children were classified as MV on at least one instrument. Proportion of overlap between definitions ranged from 3% to 100%. The stringency of definition (i.e. few-to-no vs. some words) was associated with differences in cognitive and adaptive functioning; more stringent definitions yielded greater consistency of MV status across instruments. Cognitive abilities ranged from profoundly impaired to average intelligence; 16% had NVIQ ≥ 70. Approximately half exhibited verbal skills commensurate with nonverbal cognitive ability, whereas half had verbal abilities significantly lower than their estimated NVIQ. Conclusions Future studies of MV children must carefully consider the methods used to identify their sample, acknowledging that definitions including children with ‘some words’ may yield larger samples with a wider range of language and cognitive abilities. Broadly defined MV samples may be particularly important to delineate factors interfering with language development in the subgroup of children whose expressive impairments are considerably below their estimated nonverbal cognitive abilities.

In the present study, we examined how unstructured (e.g., spending time with friends or co-workers) and structured (e.g., attending social events at a place of workshop, sports teams) social participation changed from before to after high school for youth with autism spectrum disorders (ASD), as well as the longitudinal and concurrent relations between social participation and internalizing symptoms. Participants included 36 families of youth with ASD who were all in their last year of high school at the first time point of data collection, and who were out of high school for an average of 9 months at the second time point. Social participation and internalizing symptoms were determined using parental report. There was no average change in the amount of unstructured social participation after high school exit, although substantial individual variability was observed. Participation in structured social activities significantly declined after high school exit. Youth who had more structured social participation while in high school were significantly more likely to have gains in their unstructured social participation after high school exit. Turning to relationships between internalizing and social activities, more internalizing symptoms while youth with ASD were in high school significantly predicted increasing social isolation after high school exit (both in terms of structured and unstructured activities). Results point to the likely need for additional supports during the transition to adulthood for youth with ASD who have internalizing problems. Autism Res 2016. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 663-672. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Elevated anxiety symptoms are one of the most common forms of psychopathology to co-occur with autism spectrum disorders (ASDs). The purpose of this study was to explore the association between anxiety and ASD symptoms, particularly the degree to which the relationship is explained by insistence on sameness (IS) behaviors and/or cognitive ability. The sample included 1429 individuals aged 5:8-18:0 years who participated in the Simons Simplex Collection, a genetic consortium study of ASD. Child Behavior Checklist Anxiety Problems T-scores and Autism Diagnostic Interview-Revised "IS" item raw totals were treated as both categorical and continuous measures of anxiety and IS, respectively. Chronological age, verbal intelligence quotient (IQ), and a variety of ASD phenotype-related and other behavioral variables were assessed for potential association with anxiety and IS. Anxiety and IS continuous variables were minimally, although significantly, associated with each other and with chronological age and verbal IQ. Neither anxiety nor IS was associated with other core autism diagnostic scores. Anxiety was associated with a variety of other psychiatric and behavioral symptoms in ASD, including irritability, attention problems, and aggression, while IS was not. Anxiety and IS appear to function as distinct constructs, each with a wide range of expression in children with ASD across age and IQ levels. Thus, both variables could be of use in ASD behavioral research or in dimensional approaches to genetic exploration. Unlike IS, however, anxiety is related to non-ASD-specific behavioral symptoms.

Research suggests that restricted and repetitive behaviors (RRBs) can be subdivided into repetitive sensory motor (RSM) and insistence on Sameness (IS) behaviors. However, because the majority of previous studies have used the Autism Diagnostic Interview-Revised (ADI-R), it is not clear whether these subcategories reflect the actual organization of RRBs in ASD. Using data from the Simons Simplex Collection (n=1825), we examined the association between scores on the ADI-R and the Repetitive Behavior Scale-Revised (RBS-R). Analyses supported the construct validity of RSM and IS subcategories. As in previous studies, IS behaviors showed no relationship with IQ. These findings support the continued use of RRB subcategories, particularly IS behaviors, as a means of creating more behaviorally homogeneous subgroups of children with ASD.

Objective: Substantial revisions to the DSM-IV criteria for autism spectrum disorders (ASDs) have been proposed in efforts to increase diagnostic sensitivity and specificity. This study evaluated the proposed DSM5criteriaforthesinglediagnosticcategoryof autism spectrum disorder in children with DSM-IV diagnoses of pervasive developmental disorders (PDDs) and non-PDD diagnoses. Method: Three data sets included 4,453 children with DSM-IV clinical PDD diagnoses and 690 with non-PDD diagnoses (e.g., language disorder). Items from a parent report measure of ASD symptoms (Autism Diagnostic Interview–Revised) and clinical observation instrument (Autism Diagnostic Observation Schedule) were matched to DSM-5 criteria and used to evaluate the sensitivity and specificity of the proposed DSM-5 criteria and current DSM-IV criteria when compared with clinical diagnoses. Results: Based on just parent data, the proposed DSM-5 criteria identified 91% of children with clinical DSM-IV PDD diagnoses. Sensitivity remained high in specifi cs ubgroups, including girls and children under 4. The specificity of DSM-5 ASD was 0.53 overall, while the specificity of DSM-IV ranged from 0.24, for clinically diagnosed PDD not otherwise specified (PDD-NOS), to 0.53, for autistic disorder. When data were required from both parent and clinical observation, the specificity of the DSM-5 criteria increased to 0.63. Conclusions: These results suggest that most children with DSM-IV PDD diagnoses would remain eligible for an ASD diagnosis under the proposed DSM-5 criteria. Compared with the DSM-IV criteria for Asperger’s disorder and PDD-NOS, the DSM-5 ASD criteria have greater specificity, particularly when abnormalities are evident from both parents and clinical observation. (Am J Psychiatry 2012; 169:1056–1064)

Background: The Social Responsiveness Scale (SRS) is a parent-completed screening questionnaire often used to measure autism spectrum disorders (ASD) severity. Although child characteristics are known to influence scores from other ASD-symptom measures, as well as parent-questionnaires more broadly, there has been limited consideration of how non-ASD-specific factors may affect interpretation of SRS scores. Previous studies have explored effects of behavior problems on SRS specificity, but have not addressed influences on the use of the SRS as a quantitative measure of ASD-symptoms. Method: Raw scores (SRS-Raw) from parent-completed SRS were analyzed for 2,368 probands with ASD and 1,913 unaffected siblings. Regression analyses were used to assess associations between SRS scores and demographic, language, cognitive, and behavior measures. Results: For probands, higher SRS-Raw were associated with greater non-ASD behavior problems, higher age, and more impaired language and cognitive skills, as well as scores from other parent report measures of social development and ASD-symptoms. For unaffected siblings, having more behavior problems predicted higher SRS-Raw; male gender, younger age, and poorer adaptive social and expressive communication skills also showed small, but significant effects. Conclusions: When using the SRS as a quantitative phenotype measure, the influence of behavior problems, age, and expressive language or cognitive level on scores must be considered. If effects of non-ASD-specific factors are not addressed, SRS scores are more appropriately interpreted as indicating general levels of impairment, than as severity of ASDspecific symptoms or social impairment. Additional research is needed to consider how these factors influence the SRS’ sensitivity and specificity in large, clinical samples including individuals with disorders other than ASD. Keywords: Social Responsiveness Scale, autism spectrum disorder, behavior problems, age, language level.

Scores on the autism spectrum quotient (AQ) were examined in 65 adults with ASD. Maternal reports of symptoms were collected simultaneously using the autism diagnostic interview-revised (ADI-R) and the Vineland Screener. A slightly revised AQ administration procedure was used to accommodate adults with below average IQ. AQ scores were lower than in the original validation study, with only 11 adults (17%) scoring above the proposed diagnostic cut-off and 24 (27%) exceeding the screening cut-off. Adults with higher IQs endorsed more symptoms than those with below average intelligence, but even when analyses were restricted to the 39 adults with at least average IQ, only 44% met the screening cut-off. AQ scores were not significantly correlated with ADI-R or Vineland scores.

In the absence of molecular biomarkers that can be used to diagnose ASD, current diagnostic tools depend upon clinical assessments of behavior. Research efforts with human subjects have successfully utilized standardized diagnostic instruments, which include clinician interviews with parents and direct observation of the children themselves [Risi et al., 2006]. However, because clinical instruments are semi-structured and rely heavily on dynamic social processes and clinical skill, scores from these measures do not necessarily lend themselves directly to experimental investigations into the causes of ASD. Studies of the neurobiology of autism require experimental animal models. Mice are particularly useful for elucidating genetic and toxicological contributions to impairments in social function [Halladay et al., 2009]. Behavioral tests have been developed that are relevant to autism [Crawley, 2004, 2007], including measures of repetitive behaviors [Lewis, Tanimura, Lee, & Bodfish, 2007; Moy et al., 2008], social behavior [Brodkin, 2007; Lijam et al., 1997; Moretti, Bouwknecht, Teague, Paylor, & Zoghbi, 2005], and vocal communication [D'Amato et al., 2005; Panksepp et al., 2007; Scattoni et al., 2008]. Advances also include development of high-throughput measures of mouse sociability that can be used to reliably compare inbred mouse strains [Moy et al., 2008; Nadler et al., 2004], as well as measures of social reward [Panksepp & Lahvis, 2007] and empathy [Chen, Panksepp, & Lahvis, 2009; Langford et al., 2006]. With continued generation of mouse gene-targeted mice that are directly relevant to genetic linkages in ASD, there remains an urgent need to utilize a full suite of mouse behavioral tests that allows for a comprehensive assessment of the spectrum of social difficulties relevant to ASD. Using impairments in shared affect as an example, this paper explores potential avenues for collaboration between clinical and basic scientists, within an amply considered translational framework.

This study examined how restricted and repetitive behaviors and interests (RRBs) developed over time in a sample of children with autism spectrum disorders (ASD). One hundred ninety-two children referred for a diagnosis of autism at age 2, and 22 children with nonspectrum development disorders were evaluated with a battery of cognitive and diagnostic measures at age 2 and subsequently at ages 3, 5, and 9. Factor analysis of the RRB items on the Autism Diagnostic Interview–Revised revealed two RRB factors at each wave of data collection, one comprising “repetitive sensorimotor” (RSM) behaviors and the other “insistence on sameness” (IS) behaviors. For children with ASD, RSM scores remained relatively high over time, indicating consistent severity, whereas IS scores started low and increased over time, indicating worsening. Having a higher nonverbal intelligence (NVIQ) at age 2 was associated with milder concurrent RSM behaviors and with improvement in these behaviors over time. There was no relationship between NVIQ at age 2 and IS behaviors. However, milder social/communicative impairment, at age 2 was associated with more severe concurrent IS behaviors. Trajectory analysis revealed considerable heterogeneity in patterns of change over time for both kinds of behaviors. These findings are discussed in terms of their implications for our understanding of RRBs in ASD and other disorders, making prognoses about how RRBs will develop in children with ASD as they get older, and using RRBs to identify ASD phenotypes in genetic studies.

The Autism Diagnostic Observation Schedule (ADOS; Lord et al., J Autism Dev Disord, 30(3):205-223, 2000) is widely accepted as a "gold standard" diagnostic instrument, but it is of restricted utility with very young children. The purpose of the current project was to modify the ADOS for use in children under 30 months of age. A modified ADOS, the ADOS Toddler Module (or Module T), was used in 360 evaluations. Participants included 182 children with best estimate diagnoses of ASD, non-spectrum developmental delay or typical development. A final set of protocol and algorithm items was selected based on their ability to discriminate the diagnostic groups. The traditional algorithm "cutoffs" approach yielded high sensitivity and specificity, and a new range of concern approach was proposed.

Background Machine learning (ML) provides novel opportunities for human behavior research and clinical translation, yet its application can have noted pitfalls (Bone et al., 2015). In this work, we fastidiously utilize ML to derive autism spectrum disorder (ASD) instrument algorithms in an attempt to improve upon widely used ASD screening and diagnostic tools. Methods The data consisted of Autism Diagnostic Interview-Revised (ADI-R) and Social Responsiveness Scale (SRS) scores for 1,264 verbal individuals with ASD and 462 verbal individuals with non-ASD developmental or psychiatric disorders, split at age 10. Algorithms were created via a robust ML classifier, support vector machine, while targeting best-estimate clinical diagnosis of ASD versus non-ASD. Parameter settings were tuned in multiple levels of cross-validation. Results The created algorithms were more effective (higher performing) than the current algorithms, were tunable (sensitivity and specificity can be differentially weighted), and were more efficient (achieving near-peak performance with five or fewer codes). Results from ML-based fusion of ADI-R and SRS are reported. We present a screener algorithm for below (above) age 10 that reached 89.2% (86.7%) sensitivity and 59.0% (53.4%) specificity with only five behavioral codes. Conclusions ML is useful for creating robust, customizable instrument algorithms. In a unique dataset comprised of controls with other difficulties, our findings highlight the limitations of current caregiver-report instruments and indicate possible avenues for improving ASD screening and diagnostic tools.

Background Children with attention deficit/hyperactivity disorder (ADHD) often present with social difficulties, though the extent to which these clearly overlap with symptoms of autism spectrum disorder (ASD) is not well understood. Methods We explored parent-reported and directly-observed ASD symptoms on the Autism Diagnostic Interview-Revised (ADI-R) and the Autism Diagnostic Observation Schedule (ADOS) in children referred to ASD-specialty clinics who received diagnoses of either ADHD (n = 48) or ASD (n = 164). Results Of the ADHD sample, 21 % met ASD cut-offs on the ADOS and 30 % met ASD cut-offs on all domains of the ADI-R. Four social communication ADOS items (Quality of Social Overtures, Unusual Eye Contact, Facial Expressions Directed to Examiner, and Amount of Reciprocal Social Communication) adequately differentiated the groups while none of the items on the ADI-R met the criteria for adequate discrimination. Conclusions Results of this work highlight the challenges that clinicians and researchers face when distinguishing ASD from other disorders in verbally fluent, school-age children.

OBJECTIVE: Delayed onset of independent walking is common in intellectual disability (ID). However, in children with autism spectrum disorders (ASD), delayed walking has not been reported as frequently, despite the high rate of concurrent ID in ASD. This study directly examined the relationship between delayed walking and severity of ID in children with ASD versus other non-ASD diagnoses. METHOD Participants were 1185 individuals (ASD, n = 903; non-ASD, n = 282) who received an assessment at age 4 to 12 years (6.89 ± 2.25) that yielded an estimate of nonverbal IQ (NVIQ) and retrospectively reported age of walking from the Autism Diagnostic Interview–Revised. The relationship between diagnostic group and delayed walking (defined as occurring at ≥16 months) as a function of NVIQ was explored using the Cox proportional hazards model. RESULTS: Children with ASD were less likely to exhibit delayed walking than those with non-ASD diagnoses, and this difference was larger at lower levels of NVIQ (P = .002). For example, rates of delayed walking for ASD and non-ASD were 13% and 19%, respectively, in those with NVIQ >85 but 31% and 60% in children with NVIQ CONCLUSIONS: Although lower IQ scores were associated with increased rates of late walking in both ASD and non-ASD groups, children with low IQ were more likely to show delayed walking in the absence of ASD. This raises the possibility of separate etiological pathways to ID in children with and without ASD.

This study reports on the initial validation of the Autism Symptom Interview (ASI), School-Age, a brief (15-20 min) phone interview derived from questions from the Autism Diagnostic Interview-Revised (ADI-R). The ASI, School-Age was administered by interviewers with minimal training to parents of children ages 5 to 12 who had all been previously identified with (or referred for assessment of) ASD or another neurodevelopmental disorder. Children then underwent a comprehensive assessment to determine a best-estimate clinical diagnosis of ASD (n = 159) or non-ASD (e.g. language disorder, intellectual disability, ADHD; n = 130). Clinicians who conducted the assessments were blind to ASI results. ROC analyses compared ASI scores to clinical diagnosis. Due to the small number of participants with non-ASD diagnoses who were classified as nonverbal (i.e. not yet using phrases on a daily basis), it was not possible to assess sensitivity and specificity of the nonverbal algorithm in this sample. The verbal algorithm yielded a sensitivity of 0.87 (95% CI = 0.81-0.92) and a specificity of 0.62 (95% CI = 0.53-0.70). When used in conjunction with the Autism Diagnostic Observation Schedule (ADOS), sensitivity and specificity were 0.82 (95% CI = 0.74-0.88) and 0.92 (95% CI = 0.86-0.96), respectively. Internal consistency and test-retest reliability were both excellent. Particularly for verbal school age children, the ASI may serve as a useful tool to more quickly ascertain or classify children with ASD for research or clinical triaging purposes. Additional data collection is underway to determine the utility of the ASI in children who are younger and/or nonverbal. Autism Res 2017, 10: 78-88. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Numerous studies of Autism Spectrum Disorder have attempted to link behavioral phenotypes to genetic findings. Reliance on cross-sectional behavioral data in samples that span wide age ranges may have limited this endeavor because ASD behaviors are not static within individuals across development. This study uses quantitative methods to describe specific aspects of changes in autism-related and more general behaviors in order to yield trajectories that could be used in place of single time-point data as behavioral phenotypes in neurobiological studies of both Autism Spectrum Disorders and overlapping conditions. Building on previous analyses, we examined trajectories of parent-reported social-communication deficits, social adaptive functioning, and two types of repetitive behaviors, repetitive sensory motor (RSM) behaviors and insistence on sameness (IS) behaviors, in a relatively large sample of participants referred for possible autism at age 2 years and followed into young adulthood (n=85). A strength of this sample was the diverse range of outcomes, including young adults with intellectual disability and persistent autism related difficulties, those with IQs in the borderline or average range who continued to experience functional impairment related to Autism Spectrum Disorders, and a small group of young adults (n=8) with IQs in the average range who were judged to be functioning socially and adaptively at age-appropriate levels at age 19 years, despite a previous childhood diagnosis of autism.

This study investigated the incidence and determinants of remarriage and cohabitation among a sample of 35 widowed parents of school-aged children. Data from a U. S. longitudinal study of parentally bereaved children, with surviving parents of mean age 41, revealed—by contrast with prior findings and general lore—that virtually half (47. 5%) of the widows and widowers were either remarried or in substantial cohabitation relationships within five years post-death. Contrary to previous findings, there were no differences in remarriage rates between men and women. Other factors expected to influence the likelihood of remarriages, such as number and age of children, did not; income change pre–post death was a determinant for widows, as was widow's age within this relatively young sample of widows. There was a trend for surviving parents who exhibited fewer symptoms of psychopathology (on the BSI) at the initial Wave I assessment to more likely be remarried or cohabiting at Wave II than those exhibiting higher levels of psychopathology at the initial assessment. Possible interpretations of the divergence between prior reports or assumptions and these data are noted, as is the importance of studying the role of surviving parent remarriage and/or cohabitation(s) intrinsically, and correspondingly, their effects upon parentally bereaved children.