Editorial: Time to give up on Autism Spectrum Disorder?

Olink proteomics profiling platform reveals non-invasive inflammatory related protein biomarkers in autism spectrum disorder

Background

Owing to the lack of valid biomarkers, the diagnosis of autism spectrum disorder (ASD) diagnosis relies solely on the behavioral phenotypes of children. Several researchers have suggested an association between ASD and inflammation; however, the complex relationship between the two is unelucidated to date. Therefore, the current study aims to comprehensively identify novel circulating ASD inflammatory biomarkers.

Methods

Olink proteomics was applied to compare the plasma inflammation-related protein changes in a group of the healthy children (HC, n = 33) and another with ASD (n = 31). The areas under the receiver operating characteristic curves (AUCs) of the differentially expressed proteins (DEPs) were calculated. The functional analysis of the DEPs was performed using Gene Ontology and Kyoto Encyclopedia Genes and Genomes. Pearson correlation tests were used employed to analyze the correlation between the DEPs and clinical features.

Results

A total of 13 DEPs were significantly up-regulated in the ASD group compared with the HC group. The four proteins, namely, STAMBP, ST1A1, SIRT2, and MMP-10 demonstrated good diagnostic accuracy with the corresponding AUCs (95% confidence interval, CI) of 0.7218 (0.5946-0.8489), 0.7107 (0.5827-0.8387), 0.7016 (0.5713-0.8319), and 0.7006 (0.568-0.8332). Each panel of STAMBP and any other differential protein demonstrated a better classification performance [AUC values from 0.7147 (0.5858-0.8436, STAMBP/AXIN1) to 0.7681 (0.6496-0.8867, STAMBP/MMP-10)]. These DEP profiles were enriched in immune and inflammatory response pathways, including TNF and NOD-like receptor signaling pathways. The interaction between STAMBP and SIRT2 (R = 0.97, p = 8.52 × 10^-39) was found to be the most significant. In addition, several DEPs related to clinical features in patients with ASD, particularly AXIN1 (R = 0.36, p = 0.006), SIRT2 (R = 0.34, p = 0.010) and STAMBP (R = 0.34, p = 0.010), were positively correlated with age and parity, indicating that older age and higher parity may be the inflammation-related clinical factors in ASD.

Conclusion

Inflammation plays a crucial role in ASD, and the up-regulated inflammatory proteins may serve as potential early diagnostic biomarkers for ASD.

Should We Continue to Tell Autistic People that Their Brains are Different?

Autism is often considered to reflect categorically 'different brains'. Neuropsychological research on autism spectrum disorder (ASD) however, has struggled to define this difference, or derive clear-cut boundaries between autism and non-autism. Consequently, restructuring or disbanding the ASD diagnosis is becoming increasingly advocated within research. Nonetheless, autism now exists as a salient social construction, of which 'difference' is a key facet. Clinical and educational professionals must influence this cautiously, as changes to autism's social construction may counterproductively affect the quality of life of autistic people. This paper therefore reviews ASD's value as both neuropsychological and social constructs. Although lacking neuropsychological validity, the autism label may be beneficial for autistic self-identity, reduction of stigma, and administering support. Whilst a shift away from case-control ASD research is warranted, lay notions of 'different brains' may be preserved.

Loving Objects: Can Autism Explain Objectophilia?

Objectophilia (also known as objectum-sexuality) involves romantic and sexual attraction to specific objects. Objectophiles often develop deep and enduring emotional, romantic, and sexual relations with specific inanimate (concrete or abstract) objects such as trains, bridges, cars, or words. The determinants of objectophilia are poorly understood. The aim of this paper is to examine the determining factors of objectophilia. We examine four hypotheses about the determinants of objectophilia (pertaining to fetishism, synesthesia, cross-modal mental imagery, and autism) and argue that the most likely determining factors of objectophilia are the social and non-social features of autism. Future studies on the determinants of objectophilia could enhance our understanding and potentially lessen the marginalization experienced by objectophiles.

Autism Symptoms in Children and Young Adults With Fragile X Syndrome, Angelman Syndrome, Tuberous Sclerosis Complex, and Neurofibromatosis Type 1: A Cross-Syndrome Comparison

OBJECTIVE

The etiology of autism spectrum disorder (ASD) remains unclear, due to genetic heterogeneity and heterogeneity in symptoms across individuals. This study compares ASD symptomatology between monogenetic syndromes with a high ASD prevalence, in order to reveal syndrome specific vulnerabilities and to clarify how genetic variations affect ASD symptom presentation.

METHODS

We assessed ASD symptom severity in children and young adults (aged 0-28 years) with Fragile X Syndrome (FXS, n = 60), Angelman Syndrome (AS, n = 91), Neurofibromatosis Type 1 (NF1, n = 279) and Tuberous Sclerosis Complex (TSC, n = 110), using the Autism Diagnostic Observation Schedule and Social Responsiveness Scale. Assessments were part of routine clinical care at the ENCORE expertise center in Rotterdam, the Netherlands. First, we compared the syndrome groups on the ASD classification prevalence and ASD severity scores. Then, we compared individuals in our syndrome groups with an ASD classification to a non-syndromic ASD group (nsASD, n = 335), on both ASD severity scores and ASD symptom profiles. Severity scores were compared using MANCOVAs with IQ and gender as covariates.

RESULTS

Overall, ASD severity scores were highest for the FXS group and lowest for the NF1 group. Compared to nsASD, individuals with an ASD classification in our syndrome groups showed less problems on the instruments' social domains. We found a relative strength in the AS group on the social cognition, communication and motivation domains and a relative challenge in creativity; a relative strength of the NF1 group on the restricted interests and repetitive behavior scale; and a relative challenge in the FXS and TSC groups on the restricted interests and repetitive behavior domain.

CONCLUSION

The syndrome-specific strengths and challenges we found provide a frame of reference to evaluate an individual's symptoms relative to the larger syndromic population and to guide treatment decisions. Our findings support the need for personalized care and a dimensional, symptom-based diagnostic approach, in contrast to a dichotomous ASD diagnosis used as a prerequisite for access to healthcare services. Similarities in ASD symptom profiles between AS and FXS, and between NF1 and TSC may reflect similarities in their neurobiology. Deep phenotyping studies are required to link neurobiological markers to ASD symptomatology.

Rethinking Our Concepts and Assumptions About Autism

Autism is a clinical consensus diagnosis made based on behavioral symptoms of early developmental difficulties in domains of social-communication (SC) and restricted repetitive behaviors (RRB). Many readily assume that alongside being optimal for separating individuals based on SC and RRB behavioral domains, that the label should also be highly useful for explaining differential biology, outcomes, and treatment (BOT) responses. However, we also now take for granted the fact that the autism population is vastly heterogeneous at multiple scales, from genome to phenome. In the face of such multi-scale heterogeneity, here we argue that the concept of autism along with the assumptions that surround it require some rethinking. While we should retain the diagnosis for all the good it can do in real-world circumstances, we also call for the allowance of multiple other possible definitions that are better tailored to be highly useful for other translational end goals, such as explaining differential BOT responses.

From Research to Practice: Toward the Examination of Combined Interventions for Autism Spectrum Disorders

The use of biological (i.e., medications) in conjunction with applied behavior analysis is relatively common among people with ASD, yet research examining its benefit is scarce. This paper provides a brief overview of the existing literature on the combined interventions, including promising developments, and examines the existing barriers that hinder research in this area, including the heavy reliance on RCTs. Recommendations for possible solutions, including the creation of health homes, are provided in order to move toward a more integrated approach.

Theories of Autism and Autism Treatment from the DSM III Through the Present and Beyond: Impact on Research and Practice

The purely descriptive definition of autism introduced by the DSM III in 1980 marked a departure from previous DSM editions, which mixed phenomenological descriptions with psychoanalytic theories of etiology. This provided a blank slate upon which a variety of novel theories emerged to conceptualize autism and its treatment in the following four decades. In this article we examine the contribution of these different theoretical orientations with a focus on their impact on research and practice, areas of overlap and conflict between current theories, and their relevance in the context of the evolving landscape of scientific knowledge and societal views of autism.

Examining overlap and homogeneity in ASD, ADHD, and OCD: a data-driven, diagnosis-agnostic approach

The validity of diagnostic labels of autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and obsessive compulsive disorder (OCD) is an open question given the mounting evidence that these categories may not correspond to conditions with distinct etiologies, biologies, or phenotypes. The objective of this study was to determine the agreement between existing diagnostic labels and groups discovered based on a data-driven, diagnosis-agnostic approach integrating cortical neuroanatomy and core-domain phenotype features. A machine learning pipeline, called bagged-multiview clustering, was designed to discover homogeneous subgroups by integrating cortical thickness data and measures of core-domain phenotypic features of ASD, ADHD, and OCD. This study was conducted using data from the Province of Ontario Neurodevelopmental Disorders (POND) Network, a multi-center study in Ontario, Canada. Participants (n = 226) included children between the ages of 6 and 18 with a diagnosis of ASD (n = 112, median [IQR] age = 11.7[4.8], 21% female), ADHD (n = 58, median [IQR] age = 10.2[3.3], 14% female), or OCD (n = 34, median [IQR] age = 12.1[4.2], 38% female), as well as typically developing controls (n = 22, median [IQR] age = 11.0[3.8], 55% female). The diagnosis-agnostic groups were significantly different than each other in phenotypic characteristics (SCQ: χ²(9) = 111.21, p < 0.0001; SWAN: χ²(9) = 142.44, p < 0.0001) as well as cortical thickness in 75 regions of the brain. The analyses revealed disagreement between existing diagnostic labels and the diagnosis-agnostic homogeneous groups (normalized mutual information < 0.20). Our results did not support the validity of existing diagnostic labels of ASD, ADHD, and OCD as distinct entities with respect to phenotype and cortical morphology.

Big data approaches to decomposing heterogeneity across the autism spectrum

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

Increased facial asymmetry in autism spectrum conditions is associated with symptom presentation

A key research priority in the study of autism spectrum conditions (ASC) is the discovery of biological markers that may help to identify and elucidate etiologically distinct subgroups. One physical marker that has received increasing research attention is facial structure. Although there remains little consensus in the field, findings relating to greater facial asymmetry (FA) in ASC exhibit some consistency. As there is growing recognition of the importance of replicatory studies in ASC research, the aim of this study was to investigate the replicability of increased FA in autistic children compared to nonautistic peers. Using three-dimensional photogrammetry, this study examined FA in 84 autistic children, 110 typically developing children with no family history of the condition, and 49 full siblings of autistic children. In support of previous literature, significantly greater depth-wise FA was identified in autistic children relative to the two comparison groups. As a further investigation, increased lateral FA in autistic children was found to be associated with greater severity of ASC symptoms on the Autism Diagnostic Observation Schedule, second edition, specifically related to repetitive and restrictive behaviors. These outcomes provide an important and independent replication of increased FA in ASC, as well as a novel contribution to the field. Having confirmed the direction and areas of increased FA in ASC, these findings could motivate a search for potential underlying brain dysmorphogenesis. Autism Res 2019, 12: 1774-1783. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: This study looked at the amount of facial asymmetry (FA) in autistic children compared to typically developing children and children who have siblings with autism. The study found that autistic children, compared to the other two groups, had greater FA, and that increased FA was related to greater severity of autistic symptoms. The face and brain grow together during the earliest stages of development, and so findings of facial differences in autism might inform future studies of early brain differences associated with the condition.

ASD Comorbidity in Fragile X Syndrome: Symptom Profile and Predictors of Symptom Severity in Adolescent and Young Adult Males

Many males with FXS meet criteria for ASD. This study was designed to (1) describe ASD symptoms in adolescent and young adult males with FXS (n = 44) and (2) evaluate the contributions to ASD severity of cognitive, language, and psychiatric factors, as well as FMRP (the protein deficient in FXS). A few ASD symptoms on the ADOS-2 were universal in the sample. There was less impairment in restricted and repetitive behaviors (RRB) than in the social affective (SA) domain. The best predictor of overall ASD severity and SA severity was expressive syntactic ability. RRB severity was best predicted by the psychiatric factors. Implications for clinical practice and for understanding the ASD comorbidity in FXS are discussed.

Functional connectivity-based subtypes of individuals with and without autism spectrum disorder

Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder, characterized by impairments in social communication and restricted, repetitive behaviors. Neuroimaging studies have shown complex patterns and functional connectivity (FC) in ASD, with no clear consensus on brain-behavior relationships or shared patterns of FC with typically developing controls. Here, we used a dimensional approach to characterize two distinct clusters of FC patterns across both ASD participants and controls using k-means clustering. Using multivariate statistical analyses, a categorical approach was taken to characterize differences in FC between subtypes and between diagnostic groups. One subtype was defined by increased FC within resting-state networks and decreased FC across networks compared with the other subtype. A separate FC pattern distinguished ASD from controls, particularly within default mode, cingulo-opercular, sensorimotor, and occipital networks. There was no significant interaction between subtypes and diagnostic groups. Finally, a dimensional analysis of FC patterns with behavioral measures of IQ, social responsiveness, and ASD severity showed unique brain-behavior relations in each subtype and a continuum of brain-behavior relations from ASD to controls within one subtype. These results demonstrate that distinct clusters of FC patterns exist across ASD and controls, and that FC subtypes can reveal unique information about brain-behavior relationships.

“Autistic people”? Who do you mean?

Jaswal & Akhtar (J&A) offer evidence against lack of social motivation in “autistic people,” providing no further phenotypic details as to the autism spectrum disorder (ASD) subgroups that they refer to. I will argue that given the extensive behavioral and neurobiological heterogeneity among people who receive the diagnosis, reference to “autistic people” is misleading. As a consequence, J&A's claims are difficult to interpret.

Developmental changes of cortical white-gray contrast as predictors of autism diagnosis and severity

Recent studies suggest that both cortical gray and white-matter microstructural characteristics are distinct for subjects with autism. There is a lack of evidence regarding how these characteristics change in a developmental context. We analysed a longitudinal/cross-sectional dataset of 402 magnetic resonance imaging (MRI) scans (171 subjects with autism and 231 with typical development) from the Autism Brain Imaging Data Exchange, cohorts I-II (ABIDE-I-II). In the longitudinal sample, we computed the rate of change in the white-gray contrast, a measure which has been related to age and cognitive performance, at the boundary of the cerebral cortex. Then, we devised an analogous metric for the cross-sectional sample of the ABIDE dataset to measure age-related differences in cortical contrast. Further, we developed a probabilistic model to predict the diagnostic group in the longitudinal sample of the cortical contrast change data, using results obtained from the cross-sectional sample. In both subsets, we observed a similar overall pattern of greater decrease within the autistic population in intensity contrast for most cortical regions (81%), with occasional increases, mostly in primary sensory regions. This pattern correlated well with raw and calibrated behavioural scores. The prediction results show 76% accuracy for the whole-cortex diagnostic prediction and 86% accuracy in prediction using the motor system alone. Our results support a contrast change analysis strategy that appears sensitive in predicting diagnostic outcome and symptom severity in autism spectrum disorder, and is readily extensible to other MRI-based studies of neurodevelopmental cohorts.

The role of reduced expression of fragile X mental retardation protein in neurons and increased expression in astrocytes in idiopathic and syndromic autism (duplications 15q11.2-q13)

Fragile X syndrome (FXS), caused by lack of fragile X mental retardation protein (FMRP), is associated with a high prevalence of autism. The deficit of FMRP reported in idiopathic autism suggests a mechanistic overlap between FXS and autism. The overall goal of this study is to detect neuropathological commonalities of FMRP deficits in the brains of people with idiopathic autism and with syndromic autism caused by dup15q11.2-q13 (dup15). This study tests the hypothesis based on our preliminary data that both idiopathic and syndromic autism are associated with brain region-specific deficits of neuronal FMRP and structural changes of the affected neurons. This immunocytochemical study revealed neuronal FMRP deficits and shrinkage of deficient neurons in the cerebral cortex, subcortical structures, and cerebellum in subjects with idiopathic and dup(15)/autism. Neuronal FMRP deficit coexists with surprising infiltration of the brains of autistic children and adults with FMRP-positive astrocytes known to be typical only for the fetal and short postnatal periods. In the examined autistic subjects, these astrocytes selectively infiltrate the border between white and gray matter in the cerebral and cerebellar cortex, the molecular layer of the cortex, part of the amygdala and thalamus, central cerebellar white matter, and dentate nucleus. Astrocyte pathology results in an additional local loss of FMRP in neurons and their shrinkage. Neuronal deficit of FMRP and shrinkage of affected neurons in structures free of FMRP-positive astrocytes and regions infiltrated with FMRP-expressing astrocytes appear to reflect mechanistic, neuropathological, and functional commonalities of FMRP abnormalities in FXS and autism spectrum disorder. Autism Res 2018, 11: 1316-1331. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Immunocytochemistry reveals a deficit of fragile X mental retardation protein (FMRP) in neurons of cortical and subcortical brain structures but increased FMRP expression in astrocytes infiltrating gray and white matter. The detected shrinkage of FMRP-deficient neurons may provide a mechanistic explanation of reported neuronal structural and functional changes in autism. This study contributes to growing evidence of mechanistic commonalities between fragile X syndrome and autism spectrum disorder.

RDoC-based categorization of amygdala functions and its implications in autism

Confusion endures as to the exact role of the amygdala in relation to autism. To help resolve this we turned to the NIMH's Research Domain Criteria (RDoC) which provides a classification schema that identifies different categories of behaviors that can turn pathologic in mental health disorders, e.g. autism. While RDoC incorporates all the known neurobiological substrates for each domain, this review will focus primarily on the amygdala. We first consider the amygdala from an anatomical, historical, and developmental perspective. Next, we examine the different domains and constructs of RDoC that the amygdala is involved in: Negative Valence Systems, Positive Valence Systems, Cognitive Systems, Social Processes, and Arousal and Regulatory Systems. Then the evidence for a dysfunctional amygdala in autism is presented with a focus on alterations in development, prenatal valproic acid exposure as a model for ASD, and changes in the oxytocin system therein. Finally, a synthesis of RDoC, the amygdala, and autism is offered, emphasizing the task of disambiguation and suggestions for future research.

Advances, challenges, and promises in pediatric neuroimaging of neurodevelopmental disorders

Recent years have witnessed the proliferation of neuroimaging studies of neurodevelopmental disorders (NDDs), particularly of children with autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and Tourette's syndrome (TS). Neuroimaging offers immense potential in understanding the biology of these disorders, and how it relates to clinical symptoms. Neuroimaging techniques, in the long run, may help identify neurobiological markers to assist clinical diagnosis and treatment. However, methodological challenges have affected the progress of clinical neuroimaging. This paper reviews the methodological challenges involved in imaging children with NDDs. Specific topics include correcting for head motion, normalization using pediatric brain templates, accounting for psychotropic medication use, delineating complex developmental trajectories, and overcoming smaller sample sizes. The potential of neuroimaging-based biomarkers and the utility of implementing neuroimaging in a clinical setting are also discussed. Data-sharing approaches, technological advances, and an increase in the number of longitudinal, prospective studies are recommended as future directions. Significant advances have been made already, and future decades will continue to see innovative progress in neuroimaging research endeavors of NDDs.

Developmental change in look durations predicts later effortful control in toddlers at familial risk for ASD

BACKGROUND

Difficulties with executive functioning (EF) are common in individuals with a range of developmental disorders, including autism spectrum disorder (ASD). Interventions that target underlying mechanisms of EF early in development could be broadly beneficial, but require infant markers of such mechanisms in order to be feasible. Prospective studies of infants at high familial risk (HR) for ASD have revealed a surprising tendency for HR toddlers to show longer epochs of attention to faces than low-risk (LR) controls. In typical development, decreases in look durations towards the end of the first year of life are driven by the development of executive attention-a foundational component of EF. Here, we test the hypothesis that prolonged attention to visual stimuli (including faces) in HR toddlers reflects early differences in the development of executive attention.

METHODS

In a longitudinal prospective study, we used eye-tracking to record HR and LR infants' looking behaviour to social and non-social visual stimuli at ages 9 and 15 months. At age 3 years, we assessed children with a battery of clinical research measures and collected parental report of effortful control (EC)-a temperament trait closely associated with EF and similarly contingent on executive attention.

RESULTS

Consistent with previous studies, we found an attenuated reduction in peak look durations to faces between 9 and 15 months for the HR group compared with the LR group, and lower EC amongst the HR-ASD group. In line with our hypothesis, change in peak look duration to faces between 9 and 15 months was negatively associated with EC at age 3.

CONCLUSIONS

We suggest that for HR toddlers, disruption to the early development of executive attention results in an attenuated reduction in looking time to faces. Effects may be more apparent for faces due to early biases to orient towards them; further, attention difficulties may interact with earlier emerging differences in social information processing. Our finding that prolonged attention to faces may be an early indicator of disruption to the executive attention system is of potential value in screening for infants at risk for later EF difficulties and for evaluation of intervention outcomes.

Facilitating Autism Research

Early autism research focused on behavior and cognition. In recent decades, the pace of research has accelerated, and advances in imaging and genetics have allowed the accumulation of biological data. Nevertheless, a coherent picture of the syndrome at either phenotypic or biological level has not emerged. We see two fundamental obstacles to progress in basic understanding of autism. First, the two defining features (impairment in social interactions and communication, and restricted, repetitive behaviors and interests) are historically seen as integrally related. Others hold that these two major traits are fractionable and must be studied independently, casting doubt on autism as a coherent syndrome. Second, despite much recent research on brain structure and function, environmental factors, and genetics/genomics, findings on the biological level have not generally aligned well with those on the phenotypic level. In the first two sections, we explore these challenges, and in the third section, we review approaches that may facilitate progress, such as (1) including in studies all individuals defined by social impairment without regard to repetitive behaviors, (2) forming narrowly defined subtypes by thorough characterization on specific features, both diagnostic and non-diagnostic, (3) focusing on characteristics that may be relatively robust to environmental influence, (4) studying children as early as possible, minimizing environmental influence, and including longitudinal course as an important part of the phenotype, (5) subtyping by environmental risk factors, (6) distinguishing between what participants can do and what they typically do, and (7) aggregating large data sets across sites. (JINS, 2017, 23, 903-915).

Hypermasculinised facial morphology in boys and girls with Autism Spectrum Disorder and its association with symptomatology

Elevated prenatal testosterone exposure has been associated with Autism Spectrum Disorder (ASD) and facial masculinity. By employing three-dimensional (3D) photogrammetry, the current study investigated whether prepubescent boys and girls with ASD present increased facial masculinity compared to typically-developing controls. There were two phases to this research. 3D facial images were obtained from a normative sample of 48 boys and 53 girls (3.01-12.44 years old) to determine typical facial masculinity/femininity. The sexually dimorphic features were used to create a continuous 'gender score', indexing degree of facial masculinity. Gender scores based on 3D facial images were then compared for 54 autistic and 54 control boys (3.01-12.52 years old), and also for 20 autistic and 60 control girls (4.24-11.78 years). For each sex, increased facial masculinity was observed in the ASD group relative to control group. Further analyses revealed that increased facial masculinity in the ASD group correlated with more social-communication difficulties based on the Social Affect score derived from the Autism Diagnostic Observation Scale-Generic (ADOS-G). There was no association between facial masculinity and the derived Restricted and Repetitive Behaviours score. This is the first study demonstrating facial hypermasculinisation in ASD and its relationship to social-communication difficulties in prepubescent children.