Large Autism Spectrum Disorders Research Articles

A genome-first study of sex chromosome aneuploidies provides evidence of Y chromosome dosage effects on autism risk

A female protective effect has long been postulated as the primary explanation for the four-fold increase of autism spectrum disorder (ASD) diagnoses in males versus females. However, genetic and epidemiological investigations of this hypothesis have so far failed to explain the large difference in ASD prevalence between the sexes. To address this knowledge gap, we examined sex chromosome aneuploidy in a large ASD case-control cohort to evaluate the relationship between X and Y chromosome dosage and ASD risk. From these data, we modeled three relationships between sex chromosome dosage and ASD risk: the extra Y effect, the extra X effect, and sex chromosome haploinsufficiency. We found that the extra Y effect increased ASD risk significantly more than the extra X effect. Among females, we observed a large association between 45, X and ASD, confirming sex chromosome haploinsufficiency as a strong ASD risk factor. These results provide a framework for understanding the relationship between X and Y chromosome dosage on ASD, which may inform future research investigating genomic contributors to the observed sex difference.

Autism spectrum disorder and brain volume link through a set of mTOR-related genes.

Larger than average head and brain sizes are often observed in individuals with autism spectrum disorders (ASDs). ASD and brain volume are both highly heritable, with multiple genetic variants contributing. However, it is unclear whether ASD and brain volume share any genetic mechanisms. Genes from the mammalian target of rapamycin (mTOR) pathway influence brain volume, and variants are found in rare genetic syndromes that include ASD features. Here we investigated whether variants in mTOR-related genes are also associated with ASD and if they constitute a genetic link between large brains and ASD. We extended our analyses between large heads (macrocephaly) and rare de novo mTOR-related variants in an intellectual disability cohort (N=2,258). Subsequently using Fisher's exact tests we investigated the co-occurrence of mTOR-related de novo variants and ASD in the de-novo-db database (N=23,098). We next selected common genetic variants within a set of 96 mTOR-related genes in genome-wide genetic association data of ASD (N=46,350) to test gene-set association using MAGMA. Lastly, we tested genetic correlation between genome-wide genetic association data of ASD (N=46,350) and intracranial volume (N=25,974) globally using linkage disequilibrium score regression as well as mTOR specific by restricting the genetic correlation to the mTOR-related genes using GNOVA. Our results show that both macrocephaly and ASD occur above chance level in individuals carrying rare de novo variants in mTOR-related genes. We found a significant mTOR gene-set association with ASD (p=.0029) and an mTOR-stratified positive genetic correlation between ASD and intracranial volume (p=.027), despite the absence of a significant genome-wide correlation (p=.81). This work indicates that both rare and common variants in mTOR-related genes are associated with brain volume and ASD and genetically correlate them in the expected direction. We demonstrate that genes involved in mTOR signalling are potential mediators of the relationship between having a large brain and having ASD.

Urine lactate concentration as a non-invasive screener for metabolic abnormalities: Findings in children with autism spectrum disorder and regression.

There is increasing evidence that diseases caused by dysfunctional mitochondria (MD) are associated with autism spectrum disorder (ASD). A comprehensive meta-analysis showed that developmental regression was reported in half of the children with ASD and mitochondrial dysfunction which is much higher than in the general population of ASD. The aim of the present exploratory study was to determine lactate concentrations in urine of children with ASD, as a non-invasive large-scale screening method for metabolic abnormalities including mitochondrial dysfunction and its possible association with regression. First, clinical characteristics of MD were examined in 99 children (3-11 years) with ASD. Second, clinical characteristics of MD, severity of ASD and reported regression were compared between children with the 20% lowest lactate concentrations and those with the 20% highest lactate concentrations in urine. Third, clinical characteristics of MD and lactate concentration in urine were compared in children with (n = 37) and without (n = 62) reported regression. An association of urine lactate concentrations with mitochondrial dysfunction and regression could not be demonstrated in our large ASD cohort. However, since ASD children were reported by their parents to show a broad range of phenotypic characteristics of MD (e.g., gastro-intestinal and respiratory impairments), and lactate concentrations in urine are not always increased in individuals with MD, the presence of milder mitochondrial dysfunction cannot be excluded. Development of alternative biomarkers and their implementation in prospective studies following developmental trajectories of infants at elevated likelihood for ASD will be needed in the future to further unravel the association of ASD with mitochondrial dysfunction and eventually improve early detection.

Disease similarity network analysis of Autism Spectrum Disorder and comorbid brain disorders.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder with heterogeneous clinical presentation, variable severity, and multiple comorbidities. A complex underlying genetic architecture matches the clinical heterogeneity, and evidence indicates that several co-occurring brain disorders share a genetic component with ASD. In this study, we established a genetic similarity disease network approach to explore the shared genetics between ASD and frequent comorbid brain diseases (and subtypes), namely Intellectual Disability, Attention-Deficit/Hyperactivity Disorder, and Epilepsy, as well as other rarely co-occurring neuropsychiatric conditions in the Schizophrenia and Bipolar Disease spectrum. Using sets of disease-associated genes curated by the DisGeNET database, disease genetic similarity was estimated from the Jaccard coefficient between disease pairs, and the Leiden detection algorithm was used to identify network disease communities and define shared biological pathways. We identified a heterogeneous brain disease community that is genetically more similar to ASD, and that includes Epilepsy, Bipolar Disorder, Attention-Deficit/Hyperactivity Disorder combined type, and some disorders in the Schizophrenia Spectrum. To identify loss-of-function rare de novo variants within shared genes underlying the disease communities, we analyzed a large ASD whole-genome sequencing dataset, showing that ASD shares genes with multiple brain disorders from other, less genetically similar, communities. Some genes (e.g., SHANK3, ASH1L, SCN2A, CHD2, and MECP2) were previously implicated in ASD and these disorders. This approach enabled further clarification of genetic sharing between ASD and brain disorders, with a finer granularity in disease classification and multi-level evidence from DisGeNET. Understanding genetic sharing across disorders has important implications for disease nosology, pathophysiology, and personalized treatment.

A Role for Gene-Environment Interactions in Autism Spectrum Disorder Is Supported by Variants in Genes Regulating the Effects of Exposure to Xenobiotics.

Heritability estimates support the contribution of genetics and the environment to the etiology of Autism Spectrum Disorder (ASD), but a role for gene-environment interactions is insufficiently explored. Genes involved in detoxification pathways and physiological permeability barriers (e.g., blood-brain barrier, placenta and respiratory airways), which regulate the effects of exposure to xenobiotics during early stages of neurodevelopment when the immature brain is extremely vulnerable, may be particularly relevant in this context. Our objective was to identify genes involved in the regulation of xenobiotic detoxification or the function of physiological barriers (the XenoReg genes) presenting predicted damaging variants in subjects with ASD, and to understand their interaction patterns with ubiquitous xenobiotics previously implicated in this disorder. We defined a panel of 519 XenoReg genes through literature review and database queries. Large ASD datasets were inspected for in silico predicted damaging Single Nucleotide Variants (SNVs) (N = 2,674 subjects) or Copy Number Variants (CNVs) (N = 3,570 subjects) in XenoReg genes. We queried the Comparative Toxicogenomics Database (CTD) to identify interaction pairs between XenoReg genes and xenobiotics. The interrogation of ASD datasets for variants in the XenoReg gene panel identified 77 genes with high evidence for a role in ASD, according to pre-specified prioritization criteria. These include 47 genes encoding detoxification enzymes and 30 genes encoding proteins involved in physiological barrier function, among which 15 are previous reported candidates for ASD. The CTD query revealed 397 gene-environment interaction pairs between these XenoReg genes and 80% (48/60) of the analyzed xenobiotics. The top interacting genes and xenobiotics were, respectively, CYP1A2, ABCB1, ABCG2, GSTM1, and CYP2D6 and benzo-(a)-pyrene, valproic acid, bisphenol A, particulate matter, methylmercury, and perfluorinated compounds. Individuals carrying predicted damaging variants in high evidence XenoReg genes are likely to have less efficient detoxification systems or impaired physiological barriers. They can therefore be particularly susceptible to early life exposure to ubiquitous xenobiotics, which elicit neuropathological mechanisms in the immature brain, such as epigenetic changes, oxidative stress, neuroinflammation, hypoxic damage, and endocrine disruption. As exposure to environmental factors may be mitigated for individuals with risk variants, this work provides new perspectives to personalized prevention and health management policies for ASD.

Loss-of-function of KMT5B leads to neurodevelopmental disorder and impairs neuronal development and neurogenesis

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders that cause severe social, communication, and behavioral problems. Recent studies show that the variants of a histone methyltransferase gene KMT5B cause neurodevelopmental disorders (NDDs), including ASD, and the knockout of Kmt5b in mice is embryonic lethal. However, the detailed genotype-phenotype correlations and functional effects of KMT5B in neurodevelopment are unclear. By targeted sequencing of a large Chinese ASD cohort, analyzing published genome-wide sequencing data, and mining literature, we curated 39 KMT5B variants identified from NDD individuals. A genotype-phenotype correlation analysis for 10 individuals with KMT5B pathogenic variants reveals common symptoms, including ASD, intellectual disability, languages problem, and macrocephaly. In vitro knockdown of the expression of Kmt5b in cultured mouse primary cortical neurons leads to a decrease in neuronal dendritic complexity and an increase in dendritic spine density, which can be rescued by expression of human KMT5B but not that of pathogenic de novo missense mutants. In vivo knockdown of the Kmt5b expression in the mouse embryonic cerebral cortex by in utero electroporation results in decreased proliferation and accelerated migration of neural progenitor cells. Our findings reveal essential roles of histone methyltransferase KMT5B in neuronal development, prenatal neurogenesis, and neuronal migration.

Multi-Scale Attention-Based Deep Neural Network for Brain Disease Diagnosis

Whole brain functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging (rs-fMRI) have been widely used in the diagnosis of brain disorders such as autism spectrum disorder (ASD). Recently, an increasing number of studies have focused on employing deep learning techniques to analyze FC patterns for brain disease classification. However, the high dimensionality of the FC features and the interpretation of deep learning results are issues that need to be addressed in the FC-based brain disease classification. In this paper, we proposed a multi-scale attention-based deep neural network (MSA-DNN) model to classify FC patterns for the ASD diagnosis. The model was implemented by adding a flexible multi-scale attention (MSA) module to the auto-encoder based backbone DNN, which can extract multi-scale features of the FC patterns and change the level of attention for different FCs by continuous learning. Our model will reinforce the weights of important FC features while suppress the unimportant FCs to ensure the sparsity of the model weights and enhance the model interpretability. We performed systematic experiments on the large multi-sites ASD dataset with both ten-fold and leave-one-site-out cross-validations. Results showed that our model outperformed classical methods in brain disease classification and revealed robust inter-site prediction performance. We also localized important FC features and brain regions associated with ASD classification. Overall, our study further promotes the biomarker detection and computer-aided classification for ASD diagnosis, and the proposed MSA module is flexible and easy to implement in other classification networks.

A family study implicates GBE1 in the etiology of autism spectrum disorder.

Autism spectrum disorders (ASD) are neurodevelopmental disorders with an estimated heritability of >60%. Family-based genetic studies of ASD have generally focused on multiple small kindreds, searching for de novo variants of major effect. We hypothesized that molecular genetic analysis of large multiplex families would enable the identification of variants of milder effects. We studied a large multigenerational family of European ancestry with multiple family members affected with ASD or the broader autism phenotype (BAP). We identified a rare heterozygous variant in the gene encoding 1,4-ɑ-glucan branching enzyme 1 (GBE1) that was present in seven of seven individuals with ASD, nine of ten individuals with the BAP, and none of four tested unaffected individuals. We genotyped a community-acquired cohort of 389 individuals with ASD and identified three additional probands. Cascade analysis demonstrated that the variant was present in 11 of 13 individuals with familial ASD/BAP and neither of the two tested unaffected individuals in these three families, also of European ancestry. The variant was not enriched in the combined UK10K ASD cohorts of European ancestry but heterozygous GBE1 deletion was overrepresented in large ASD cohorts, collectively suggesting an association between GBE1 and ASD.

EXAMINING THE DIFFERENCES IN AUTISM QUOTIENT SCORESBASED ON ETHNICITY

Definitive explanations on the associations between demographics and cause as well as the cure of Autism Spectrum Disorder (ASD) are yet to be known due to the unavailability of universal datasets and cost-effective diagnostic measures. This study analyzed large ASD screening data to examine whether symptoms of ASD differ based on ethnicity. The result showed a significant difference in the Autism Quotient (AQ) scores based on ethnicity among children, adolescents, and adults. Higher internal consistency was recorded on self-reported cases. This study will advance understanding of the influence of demographics on ASD symptoms. It is suggested that future studies should improve the reliability of AQ as screening tool.

Alpha connectivity and inhibitory control in adults with autism spectrum disorder

BackgroundIndividuals with autism spectrum disorder (ASD) often report difficulties with inhibition in everyday life. During inhibition tasks, adults with ASD show reduced activation of and connectivity between brain areas implicated in inhibition, suggesting impairments in inhibitory control at the neural level. Our study further investigated these differences by using magnetoencephalography (MEG) to examine the frequency band(s) in which functional connectivity underlying response inhibition occurs, as brain functions are frequency specific, and whether connectivity in certain frequency bands differs between adults with and without ASD.MethodsWe analysed MEG data from 40 adults with ASD (27 males; 26.94 ± 6.08 years old) and 39 control adults (27 males; 27.29 ± 5.94 years old) who performed a Go/No-go task. The task involved two blocks with different proportions of No-go trials: Inhibition (25% No-go) and Vigilance (75% No-go). We compared whole-brain connectivity in the two groups during correct No-go trials in the Inhibition vs. Vigilance blocks between 0 and 400 ms.ResultsDespite comparable performance on the Go/No-go task, adults with ASD showed reduced connectivity compared to controls in the alpha band (8–14 Hz) in a network with a main hub in the right inferior frontal gyrus. Decreased connectivity in this network predicted more self-reported difficulties on a measure of inhibition in everyday life.LimitationsMeasures of everyday inhibitory control were not available for all participants, so this relationship between reduced network connectivity and inhibitory control abilities may not be necessarily representative of all adults with ASD or the larger ASD population. Further research with independent samples of adults with ASD, including those with a wider range of cognitive abilities, would be valuable.ConclusionsOur findings demonstrate reduced functional brain connectivity during response inhibition in adults with ASD. As alpha-band synchrony has been linked to top-down control mechanisms, we propose that the lack of alpha synchrony observed in our ASD group may reflect difficulties in suppressing task-irrelevant information, interfering with inhibition in real-life situations.

Tracing Autism Traits in Large Multiplex Families to Identify Endophenotypes of the Broader Autism Phenotype.

Families comprising many individuals with Autism Spectrum Disorders (ASD) may carry a dominant predisposing mutation. We implemented rigorous phenotyping of the “Broader Autism Phenotype” (BAP) in large multiplex ASD families using a novel endophenotype approach for the identification and characterisation of distinct BAP endophenotypes. We evaluated ASD/BAP features using standardised tests and a semi-structured interview to assess social, intellectual, executive and adaptive functioning in 110 individuals, including two large multiplex families (Family A: 30; Family B: 35) and an independent sample of small families (n = 45). Our protocol identified four distinct psychological endophenotypes of the BAP that were evident across these independent samples, and showed high sensitivity (97%) and specificity (82%) for individuals classified with the BAP. Patterns of inheritance of identified endophenotypes varied between the two large multiplex families, supporting their utility for identifying genes in ASD.

Individual Differences in Intrinsic Brain Networks Predict Symptom Severity in Autism Spectrum Disorders.

The neurobiology of heterogeneous neurodevelopmental disorders such as Autism Spectrum Disorders (ASD) is still unknown. We hypothesized that differences in subject-level properties of intrinsic brain networks were important features that could predict individual variation in ASD symptom severity. We matched cases and controls from a large multicohort ASD dataset (ABIDE-II) on age, sex, IQ, and image acquisition site. Subjects were matched at the individual level (rather than at group level) to improve homogeneity within matched case-control pairs (ASD: n = 100, mean age = 11.43years, IQ = 110.58; controls: n = 100, mean age = 11.43years, IQ = 110.70). Using task-free functional magnetic resonance imaging, we extracted intrinsic functional brain networks using projective non-negative matrix factorization. Intrapair differences in strength in subnetworks related to the salience network (SN) and the occipital-temporal face perception network were robustly associated with individual differences in social impairment severity (T = 2.206, P = 0.0301). Findings were further replicated and validated in an independent validation cohort of monozygotic twins (n = 12; 3 pairs concordant and 3 pairs discordant for ASD). Individual differences in the SN and face-perception network are centrally implicated in the neural mechanisms of social deficits related to ASD.

Callous-unemotional traits in youth with autism spectrum disorder (ASD): replication of prevalence estimates and associations with gaze patterns when viewing fearful faces.

Research suggests an increased prevalence of callous-unemotional (CU) traits in children with autism spectrum disorder (ASD), and a similar impairment in fear recognition to that reported in non-ASD populations. However, past work has used measures not specifically designed to measure CU traits and has not examined whether decreased attention to the eyes reported in non-ASD populations is also present in individuals with ASD. The current paper uses a measure specifically designed to measure CU traits to estimate prevalence in a large community-based ASD sample. Parents of 189 adolescents with ASD completed questionnaires assessing CU traits, and emotional and behavioral problems. A subset of participants completed a novel emotion recognition task (n = 46). Accuracy, reaction time, total looking time, and number of fixations to the eyes and mouth were measured. Twenty-two percent of youth with ASD scored above a cut-off expected to identify the top 6% of CU scores. CU traits were associated with longer reaction times to identify fear and fewer fixations to the eyes relative to the mouth during the viewing of fearful faces. No associations were found with accuracy or total looking time. Results suggest the mechanisms that underpin CU traits may be similar between ASD and non-ASD populations.

Individualised MRI training for paediatric neuroimaging: A child-focused approach

Magnetic Resonance Imaging (MRI) in paediatric cohorts is often complicated by reluctance to enter the scanner and head motion-related imaging artefacts. The process is particularly challenging for children with neurodevelopmental disorders where coping with novel task demands in an unfamiliar setting may be more difficult due to symptom-related deficits or distress. These issues often give rise to excessive head motion that can significantly reduce the quality of images acquired, or render data unusable. Here we report an individualised MRI training procedure that enables children with Autism Spectrum Disorders (ASD) to better tolerate the MRI scanner environment based on a child-focused approach and individualised familiarisation strategies, including a pre-visit interview, familiarisation package, and personalised rewards. A medical imaging mobile application was utilised to familiarise participants to multi-sensory aspects of the neuroimaging experience through a variety of themed mini-games and activities. The MRI training procedure was implemented for monozygotic twins (n = 12; 6 twin pairs; age range 7.1–12.9 years) concordant or discordant for ASD. MRI image quality indices were better or comparable to images acquired from a large independent multi-centre ASD cohort. Present findings are promising and suggest that child-focused strategies could improve the quality of paediatric neuroimaging in clinical populations.

The Drosophila Gene Sulfateless Modulates Autism-Like Behaviors.

Major challenges to identifying genes that contribute to autism spectrum disorder (ASD) risk include the availability of large ASD cohorts, the contribution of many genes overall, and small effect sizes attributable to common gene variants. An alternative approach is to use a model organism to detect alleles that impact ASD-relevant behaviors and ask whether homologous human genes infer ASD risk. Here we utilized the Drosophila genetic reference panel (DGRP) as a tool to probe for perturbation in naturally occurring behaviors in Drosophila melanogaster that are analogous to three behavior domains: impaired social communication, social reciprocity and repetitive behaviors or restricted interests. Using 40 of the available DGRP lines, we identified single nucleotide polymorphisms (SNPs) in or near genes controlling these behavior domains, including ASD gene orthologs (neurexin 4 and neuroligin 2), an intellectual disability (ID) gene homolog (kirre), and a gene encoding a heparan sulfate (HS) modifying enzyme called sulfateless (sfl). SNPs in sfl were associated with all three ASD-like behaviors. Using RNAi knock-down of neuronal sfl expression, we observed significant changes in expressive and receptive communication during mating, decreased grooming behavior, and increased social spacing. These results suggest a role for HS proteoglycan synthesis and/or modification in normal social communication, repetitive behavior, and social interaction in flies. Finally, using the DGRP to directly identify genetic effects relevant to a neuropsychiatric disorder further demonstrates the utility of the Drosophila system in the discovery of genes relevant to human disease.

Recessive gene disruptions in autism spectrum disorder.

Autism spectrum disorder (ASD) affects up to 1 in 59 individuals1. Genome-wide association and large-scale sequencing studies strongly implicate both common variants2–4 and rare de novo variants5–10 in ASD. Recessive mutations have also been implicated11–14 but their contribution remains less well defined. Here we demonstrate an excess of biallelic loss-of-function and damaging missense mutations in a large ASD cohort, corresponding to ~5% of total cases, including 10% of females, consistent with a female protective effect. We document biallelic disruption of known or emerging recessive neurodevelopmental genes (CA2, DDHD1, NSUN2, PAH, RARB, ROGDI, SLC1A1, USH2A) as well as other genes not previously implicated in ASD including the transcription factor FEV, a key regulator of the serotonergic circuitry. Our data refine estimates of the contribution of recessive mutation to ASD and suggest new paths for illuminating novel biological pathways responsible for this condition.

Patients with autism spectrum disorders display reproducible functional connectivity alterations.

Despite the high clinical burden, little is known about pathophysiology underlying autism spectrum disorder (ASD). Recent resting-state functional magnetic resonance imaging (rs-fMRI) studies have found atypical synchronization of brain activity in ASD. However, no consensus has been reached on the nature and clinical relevance of these alterations. Here, we addressed these questions in four large ASD cohorts. Using rs-fMRI, we identified functional connectivity alterations associated with ASD. We tested for associations of these imaging phenotypes with clinical and demographic factors such as age, sex, medication status, and clinical symptom severity. Our results showed reproducible patterns of ASD-associated functional hyper- and hypoconnectivity. Hypoconnectivity was primarily restricted to sensory-motor regions, whereas hyperconnectivity hubs were predominately located in prefrontal and parietal cortices. Shifts in cortico-cortical between-network connectivity from outside to within the identified regions were shown to be a key driver of these abnormalities. This reproducible pathophysiological phenotype was partially associated with core ASD symptoms related to communication and daily living skills and was not affected by age, sex, or medication status. Although the large effect sizes in standardized cohorts are encouraging with respect to potential application as a treatment and for patient stratification, the moderate link to clinical symptoms and the large overlap with healthy controls currently limit the usability of identified alterations as diagnostic or efficacy readout.

Evaluating Sex and Age Differences in ADI-R and ADOS Scores in a Large European Multi-site Sample of Individuals with Autism Spectrum Disorder

Research on sex-related differences in Autism Spectrum Disorder (ASD) has been impeded by small samples. We pooled 28 datasets from 18 sites across nine European countries to examine sex differences in the ASD phenotype on the ADI-R (376 females, 1763 males) and ADOS (233 females, 1187 males). On the ADI-R, early childhood restricted and repetitive behaviours were lower in females than males, alongside comparable levels of social interaction and communication difficulties in females and males. Current ADI-R and ADOS scores showed no sex differences for ASD severity. There were lower socio-communicative symptoms in older compared to younger individuals. This large European ASD sample adds to the literature on sex and age variations of ASD symptomatology.

Exonic Mosaic Mutations Contribute Risk for Autism Spectrum Disorder

Genetic risk factors for autism spectrum disorder (ASD) have yet to be fully elucidated. Postzygotic mosaic mutations (PMMs) have been implicated in several neurodevelopmental disorders and overgrowth syndromes. By leveraging whole-exome sequencing data on a large family-based ASD cohort, the Simons Simplex Collection, we systematically evaluated the potential role of PMMs in autism risk. Initial re-evaluation of published single-nucleotide variant (SNV) de novo mutations showed evidence consistent with putative PMMs for 11% of mutations. We developed a robust and sensitive SNV PMM calling approach integrating complementary callers, logistic regression modeling, and additional heuristics. In our high-confidence call set, we identified 470 PMMs in children, increasing the proportion of mosaic SNVs to 22%. Probands have a significant burden of synonymous PMMs and these mutations are enriched for computationally predicted impacts on splicing. Evidence of increased missense PMM burden was not seen in the full cohort. However, missense burden signal increased in subcohorts of families where probands lacked nonsynonymous germline mutations, especially in genes intolerant to mutations. Parental mosaic mutations that were transmitted account for 6.8% of the presumed de novo mutations in the children. PMMs were identified in previously implicated high-confidence neurodevelopmental disorder risk genes, such as CHD2, CTNNB1, SCN2A, and SYNGAP1, as well as candidate risk genes with predicted functions in chromatin remodeling or neurodevelopment, including ACTL6B, BAZ2B, COL5A3, SSRP1, and UNC79. We estimate that PMMs potentially contribute risk to 3%-4% of simplex ASD case subjects and future studies of PMMs in ASD and related disorders are warranted.

Efficacy of romantic and sexual psycho-educational training for adolescent with high-functioning autism spectrum disorder: A pilot study

IntroductionRomantic and sexual functioning in individuals with autism spectrum disorder (ASD) are understudied. Recent findings evidenced that adolescents and adults with present romantic and sexual behaviors comparable with their neurotypical peers. However, it is worth to note that dysfunctional and inappropriate romantic and sexual behaviors are often described in this population.ObjectivesTo investigate efficacy of a psycho-educational training in a small group of adolescent with high-functioning ASD (HFA, QI > 70).MethodsSix adolescents (all males, range age 14–16 years) have been evaluated before (T0) and after (T1) a 10-session sexual and romantic psycho-educational structured group training, of 90′ each session. Clinical evaluation included parent-report questionnaires, as SBS for sexual behaviors and CBCL for behavioral problems, and a self-report questionnaire for sexual behaviors, called SESAMO. Moreover, autistic symptoms were investigated with ADOS-2 at T0.ResultsPreliminary analysis revealed a statistically significant differences between T0 and T1 in sexual education (P = 0.02) and frequency of dysfunctional sexual behaviors (P = 0.02) of SBS and in sexual expectations about the partner in SESAMO (P = 0.04). No differences were found in CBCL.ConclusionPreliminary results showed an improvement of romantic and sexual functioning in adolescent boys with HFA, as reported by either parents and adolescents, after participating to a structured psycho-educational training. More sexual education and information, less inappropriate sexual behaviors and more-appropriate expectations about potential partner were reported at the end of the training. These results should be confirmed in studies including larger ASD and control sample.Disclosure of interestThe authors have not supplied their declaration of competing interest.