1. Bussu G, Jones EJH, Charman T, Johnson MH, Buitelaar JK. {{Prediction of Autism at 3 Years from Behavioural and Developmental Measures in High-Risk Infants: A Longitudinal Cross-Domain Classifier Analysis}}. {J Autism Dev Disord}. 2018.
We integrated multiple behavioural and developmental measures from multiple time-points using machine learning to improve early prediction of individual Autism Spectrum Disorder (ASD) outcome. We examined Mullen Scales of Early Learning, Vineland Adaptive Behavior Scales, and early ASD symptoms between 8 and 36 months in high-risk siblings (HR; n = 161) and low-risk controls (LR; n = 71). Longitudinally, LR and HR-Typical showed higher developmental level and functioning, and fewer ASD symptoms than HR-Atypical and HR-ASD. At 8 months, machine learning classified HR-ASD at chance level, and broader atypical development with 69.2% Area Under the Curve (AUC). At 14 months, ASD and broader atypical development were classified with approximately 71% AUC. Thus, prediction of ASD was only possible with moderate accuracy at 14 months.
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2. Cole EJ, Barraclough NE, Enticott PG. {{Investigating Mirror System (MS) Activity in Adults with ASD When Inferring Others’ Intentions Using Both TMS and EEG}}. {J Autism Dev Disord}. 2018.
ASD is associated with mentalizing deficits that may correspond with atypical mirror system (MS) activation. We investigated MS activity in adults with and without ASD when inferring others’ intentions using TMS-induced motor evoked potentials (MEPs) and mu suppression measured by EEG. Autistic traits were measured for all participants. Our EEG data show, high levels of autistic traits predicted reduced right mu (8-10 Hz) suppression when mentalizing. Higher left mu (8-10 Hz) suppression was associated with superior mentalizing performances. Eye-tracking and TMS data showed no differences associated with autistic traits. Our data suggest ASD is associated with reduced right MS activity when mentalizing, TMS-induced MEPs and mu suppression measure different aspects of MS functioning and the MS is directly involved in inferring intentions.
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3. Donegan JJ, Boley AM, Lodge DJ. {{Embryonic stem cell transplants as a therapeutic strategy in a rodent model of autism}}. {Neuropsychopharmacology}. 2018.
Autism is a neurodevelopmental disorder characterized by disruptions in three core behavioral domains: deficits in social interaction, impairments in communication, and repetitive and stereotyped patterns of behavior or thought. There are currently no drugs available for the treatment of the core symptoms of ASD and drugs that target comorbid symptoms often have serious adverse side effects, suggesting an urgent need for new therapeutic strategies. The neurobiology of autism is complex, but converging evidence suggests that ASD involves disruptions in the inhibitory GABAergic neurotransmitter system. Specifically, people with autism have a reduction in parvalbumin (PV)-containing interneurons in the PFC, leading to the suggestion that restoring interneuron function in this region may be a novel therapeutic approach for ASD. Here we used a dual-reporter embryonic stem cell line to generate enriched populations of PV-positive interneurons, which were transplanted into the medial prefrontal cortex (mPFC) of the Poly I:C rodent model of autism. PV interneuron transplants were able to decrease pyramidal cell firing in the mPFC and alleviated deficits in social interaction and cognitive flexibility. Our results suggest that restoring PV interneuron function in the mPFC may be a novel and effective treatment strategy to reduce the core symptoms of autism.
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4. Glineburg MR, Todd PK, Charlet-Berguerand N, Sellier C. {{Repeat-associated non-AUG (RAN) translation and other molecular mechanisms in Fragile X Tremor Ataxia Syndrome}}. {Brain Res}. 2018.
Fragile X-associated tremor/ataxia syndrome (FXTAS) is a late-onset inherited neurodegenerative disorder characterized by progressive intention tremor, gait ataxia and dementia associated with mild brain atrophy. The cause of FXTAS is a premutation expansion, of 55 to 200 CGG repeats localized within the 5’UTR of FMR1. These repeats are transcribed in the sense and antisense directions into mutants RNAs, which have increased expression in FXTAS. Furthermore, CGG sense and CCG antisense expanded repeats are translated into novel proteins despite their localization in putatively non-coding regions of the transcript. Here we focus on two proposed disease mechanisms for FXTAS: 1) RNA gain-of-function, whereby the mutant RNAs bind specific proteins and preclude their normal functions, and 2) repeat-associated non-AUG (RAN) translation, whereby translation through the CGG or CCG repeats leads to the production of toxic homopolypeptides, which in turn interfere with a variety of cellular functions. Here, we analyze the data generated to date on both of these potential molecular mechanisms and lay out a path forward for determining which factors drive FXTAS pathogenicity.
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5. Hu X, Zheng Q, Lee GT. {{Using Peer-Mediated LEGO(R) Play Intervention to Improve Social Interactions for Chinese Children with Autism in an Inclusive Setting}}. {J Autism Dev Disord}. 2018.
The purpose of this study was to examine the effects of a peer-mediated LEGO(R) play intervention on improving social skills for children with ASD in an inclusive preschool in China. Three boys with ASD and 13 typically developing children participated in this study. A multiple-probe across participants design was used. The intervention consisted of LEGO(R) construction activities incorporated with peer-mediated strategies for one child with ASD and two typically developing peers. The intervention sessions were conducted two sessions per week with a total of 28-31 sessions for each participant. Results indicated that all three children with ASD increased their social initiations and responses following the completion of the intervention. Social validity was also obtained.
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6. Jin Z, Yang Y, Liu S, Huang H, Jin X. {{Prevalence of DSM-5 Autism Spectrum Disorder Among School-Based Children Aged 3-12 Years in Shanghai, China}}. {J Autism Dev Disord}. 2018.
We estimated the prevalence of ASD in a population-based sample comprising children aged 3-12 years (N = 74,252) in Shanghai. This included a high-risk group sampled from special education schools and a low-risk group randomly sampled from general schools. First, we asked parents and then teachers to complete the Social Communication Questionnaire for participating children. Children who screened positive based on both parental and teachers’ reports were comprehensively assessed. ASD was identified based on DSM-5 criteria. We identified 711 children as being at-risk for ASD, of which 203 were identified as ASD cases. The prevalence of ASD was 8.3 per 10,000, which is likely an underestimate, given that 81.6% of the children diagnosed with ASD had IQs below 40. This is the first report on the prevalence of ASD according to DSM-5 in China.
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7. Martinez M, Thomas KC, Williams CS, Christian R, Crais E, Pretzel R, Hooper SR. {{Family Experiences with the Diagnosis of Autism Spectrum Disorder: System Barriers and Facilitators of Efficient Diagnosis}}. {J Autism Dev Disord}. 2018.
This paper examines family experiences with the efficiency of ASD diagnosis. Children were age 8 or younger with ASD (n = 450). Outcomes were delay from first parent concern to diagnosis, shifting diagnoses, and being told child did not have ASD. Predictors were screening, travel distance, and problems finding providers. Logit models were used to examine associations. Screening was associated with reduced delay in diagnosis; problems finding providers were associated with greater delay. Screening, travel distance, and delay in diagnosis were associated with shifting diagnoses and being told child did not have ASD. Physician and parent training in communication and addressing mental health professional shortages and maldistribution may improve the diagnosis experiences of families of children with ASD.
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8. Ronconi L, Devita M, Molteni M, Gori S, Facoetti A. {{Brief Report: When Large Becomes Slow: Zooming-Out Visual Attention Is Associated to Orienting Deficits in Autism}}. {J Autism Dev Disord}. 2018.
Previous studies independently demonstrated impairments in rapid orienting/disengagement and zooming-out of spatial attention in autism spectrum disorder (ASD). These attentional mechanisms, however, are not completely independent. Aiming at a more complete picture of spatial attention deficits in ASD, we examined the relationship between orienting and zooming in participants with ASD and typically developing peers. We modified a classical spatial cuing task, presenting two small or large cues in the two visual hemifields and subsequently cueing attention to one of them. Our results demonstrate a sluggish orienting mechanism in ASD only when a large attentional focus is deployed. Moreover, only the sluggish orienting mechanism in the large cues condition predicts the severity in the social-interaction symptomatology in individuals with ASD.
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9. Traynor JM, Doyle-Thomas KAR, Hanford LC, Foster NE, Tryfon A, Hyde KL, Anagnostou E, Evans AC, Zwaigenbaum L, Hall GBC. {{Indices of repetitive behaviour are correlated with patterns of intrinsic functional connectivity in youth with autism spectrum disorder}}. {Brain Res}. 2018; 1685: 79-90.
The purpose of the current study was to examine how repetitive behaviour in Autism Spectrum Disorder (ASD) is related to intrinsic functional connectivity patterns in a number of large-scale, neural networks. Resting-state fMRI scans from thirty subjects with ASD and thirty-two age-matched, typically developing control subjects were analysed. Seed-to-voxel and ROI-to-ROI functional connectivity analyses were used to examine resting-state connectivity in a number of cortical and subcortical neural networks. Bivariate correlation analysis was performed to examine the relationship between repetitive behaviour scores from the Repetitive Behaviour Scale – Revised and intrinsic functional connectivity in ASD subjects. Compared to control subjects, ASD subjects displayed marked over-connectivity of the thalamus with several cortical sensory processing areas, as well as over-connectivity of the basal ganglia with somatosensory and motor cortices. Within the ASD group, significant correlations were found between functional connectivity patterns and total RBS-R scores as well as one principal component analysis-derived score from the RBS-R. These results suggest that thalamocortical resting-state connectivity is altered in individuals with ASD, and that resting-state functional connectivity is associated with ASD symptomatology.
