1. Al-Mendalawi MD. {{Prevalence of autism spectrum disorders among children (1-10 years of age): Findings of a midterm report from Northwest India}}. {J Postgrad Med}. 2016; 62(1): 52-3.
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2. Barnard RA, Pomaville MB, O’Roak BJ. {{Mutations and Modeling of the Chromatin Remodeler CHD8 Define an Emerging Autism Etiology}}. {Front Neurosci}. 2015; 9: 477.
Autism Spectrum Disorder (ASD) is a common neurodevelopmental disorder with a strong but complex genetic component. Recent family based exome-sequencing strategies have identified recurrent de novo mutations at specific genes, providing strong evidence for ASD risk, but also highlighting the extreme genetic heterogeneity of the disorder. However, disruptions in these genes converge on key molecular pathways early in development. In particular, functional enrichment analyses have found that there is a bias toward genes involved in transcriptional regulation, such as chromatin modifiers. Here we review recent genetic, animal model, co-expression network, and functional genomics studies relating to the high confidence ASD risk gene, CHD8. CHD8, a chromatin remodeling factor, may serve as a « master regulator » of a common ASD etiology. Individuals with a CHD8 mutation show an ASD subtype that includes similar physical characteristics, such as macrocephaly and prolonged GI problems including recurrent constipation. Similarly, animal models of CHD8 disruption exhibit enlarged head circumference and reduced gut motility phenotypes. Systems biology approaches suggest CHD8 and other candidate ASD risk genes are enriched during mid-fetal development, which may represent a critical time window in ASD etiology. Transcription and CHD8 binding site profiles from cell and primary tissue models of early development indicate that CHD8 may also positively regulate other candidate ASD risk genes through both direct and indirect means. However, continued study is needed to elucidate the mechanism of regulation as well as identify which CHD8 targets are most relevant to ASD risk. Overall, these initial studies suggest the potential for common ASD etiologies and the development of personalized treatments in the future.
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3. Berzhanskaya J, Phillips MA, Gorin A, Lai C, Shen J, Colonnese MT. {{Disrupted Cortical State Regulation in a Rat Model of Fragile X Syndrome}}. {Cereb Cortex}. 2016.
Children with Fragile X syndrome (FXS) have deficits of attention and arousal. To begin to identify the neural causes of these deficits, we examined juvenile rats lacking the Fragile X mental retardation protein (FMR-KO) for disruption of cortical activity related to attention and arousal. Specifically, we examined the switching of visual cortex between activated and inactivated states that normally occurs during movement and quiet rest, respectively. In both wild-type and FMR-KO rats, during the third and fourth postnatal weeks cortical activity during periods of movement was dominated by an activated state with prominent 18-52 Hz activity. However, during quiet rest, when activity in wild-type rats became dominated by the inactivated state (3-9 Hz activity), FMR-KO rat cortex abnormally remained activated, resulting in increased high-frequency and reduced low-frequency power during rest. Firing rate correlations revealed reduced synchronization in FMR-KO rats, particularly between fast-spiking interneurons, that developmentally precede cortical state defects. Together our data suggest that disrupted inhibitory connectivity impairs the ability of visual cortex to regulate exit from the activated state in a behaviorally appropriate manner, potentially contributing to disrupted attention and sensory processing observed in children with FXS by making it more difficult to decrease cortical drive by unattended stimuli.
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4. Chen M, Zhao M, Lee CG, Chong SS. {{Identification of microsatellite markers <1 Mb from the FMR1 CGG repeat and development of a single-tube tetradecaplex PCR panel of highly polymorphic markers for preimplantation genetic diagnosis of fragile X syndrome}}. {Genet Med}. 2016. PURPOSE: To develop a single-tube polymerase chain reaction (PCR) panel of highly polymorphic markers for preimplantation genetic diagnosis (PGD) of fragile X syndrome (FXS). METHODS: An in silico search was performed to identify all markers within 1 Mb flanking the FMR1 gene. Selected markers were optimized into a single-tube PCR panel and their polymorphism indices were determined from 272 female samples from three populations. The single-tube assay was also validated on 30 single cells to evaluate its applicability to FXS PGD. RESULTS: Thirteen markers with potentially high polymorphism information content (PIC) and heterozygosity values were selected and optimized into a single-tube PCR panel together with AMELX/Y for gender determination. Analysis of 272 female samples confirmed the high polymorphism (PIC > 0.5) of most markers, with expected and observed heterozygosities ranging from 0.31 to 0.87. More than 99% of individuals were heterozygous for at least three markers, with 95.8% of individuals heterozygous for at least two markers on either side of the FMR1 CGG repeat. CONCLUSION: The tetradecaplex marker assay can be performed directly on single cells or after whole-genome amplification, thus supporting its use in FXS PGD either as a standalone linkage-based assay or as a complement to FMR1 mutation detection.Genet Med advance online publication 07 January 2016Genetics in Medicine (2016); doi:10.1038/gim.2015.185.
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5. Garman HD, Spaulding CJ, Webb SJ, Mikami AY, Morris JP, Lerner MD. {{Wanting it Too Much: An Inverse Relation Between Social Motivation and Facial Emotion Recognition in Autism Spectrum Disorder}}. {Child Psychiatry Hum Dev}. 2016.
This study examined social motivation and early-stage face perception as frameworks for understanding impairments in facial emotion recognition (FER) in a well-characterized sample of youth with autism spectrum disorders (ASD). Early-stage face perception (N170 event-related potential latency) was recorded while participants completed a standardized FER task, while social motivation was obtained via parent report. Participants with greater social motivation exhibited poorer FER, while those with shorter N170 latencies exhibited better FER for child angry faces stimuli. Social motivation partially mediated the relationship between a faster N170 and better FER. These effects were all robust to variations in IQ, age, and ASD severity. These findings augur against theories implicating social motivation as uniformly valuable for individuals with ASD, and augment models suggesting a close link between early-stage face perception, social motivation, and FER in this population. Broader implications for models and development of FER in ASD are discussed.
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6. Hulbert SW, Jiang YH. {{Monogenic mouse models of autism spectrum disorders: Common mechanisms and missing links}}. {Neuroscience}. 2015.
Autism spectrum disorders (ASDs) present unique challenges in the fields of genetics and neurobiology because of the clinical and molecular heterogeneity underlying these disorders. Genetic mutations found in ASD patients provide opportunities to dissect the molecular and circuit mechanisms underlying autistic behaviors using animal models. Ongoing studies of genetically modified models have offered critical insight into possible common mechanisms arising from different mutations, but links between molecular abnormalities and behavioral phenotypes remain elusive. The challenges encountered in modeling autism in mice demand a new analytic paradigm that integrates behavioral analysis with circuit-level analysis in genetically modified models with strong construct validity.
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7. Im DS. {{Template to Perpetrate: An Update on Violence in Autism Spectrum Disorder}}. {Harv Rev Psychiatry}. 2016; 24(1): 14-35.
INTRODUCTION: For the past two decades, researchers have been using various approaches to investigate the relationship, if any, between autism spectrum disorder (ASD) and violence. The need to clarify that relationship was reinforced by the tragic mass shooting at Sandy Hook Elementary School in Newtown, Connecticut, in December 2012 by an individual diagnosed with Asperger’s syndrome. The purpose of this article is (1) to provide an updated review of the literature on the association between ASD and violence, and (2) to examine implications for treating, and for preventing violence by, individuals with ASD. METHOD: A review of all published literature regarding ASD and violence from 1943 to 2014 was conducted using electronic and paper searches. RESULTS: Although some case reports have suggested an increased violence risk in individuals with ASD compared to the general population, prevalence studies have provided no conclusive evidence to support this suggestion. Among individuals with ASD, however, generative (e.g., comorbid psychopathology, social-cognition deficits, emotion-regulation problems) and associational (e.g., younger age, Asperger’s syndrome diagnosis, repetitive behavior) risk factors have been identified or proposed for violent behavior. CONCLUSIONS: While no conclusive evidence indicates that individuals with ASD are more violent than those without ASD, specific generative and associational risk factors may increase violence risk among individuals with ASD. Further research would help to clarify or confirm these findings, suggest potential directions for evaluation, treatment, and prevention, and potentially provide compelling empirical support for forensic testimony regarding defendants with ASD charged with violent crimes.
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8. Jing F, Wade JW, Dayi B, Key AP, Warren ZE, Mion LC, Sarkar N. {{A Step towards EEG-based brain computer interface for autism intervention}}. {Conf Proc IEEE Eng Med Biol Soc}. 2015; 2015: 3767-70.
Autism Spectrum Disorder (ASD) is a prevalent and costly neurodevelopmental disorder. Individuals with ASD often have deficits in social communication skills as well as adaptive behavior skills related to daily activities. We have recently designed a novel virtual reality (VR) based driving simulator for driving skill training for individuals with ASD. In this paper, we explored the feasibility of detecting engagement level, emotional states, and mental workload during VR-based driving using EEG as a first step towards a potential EEG-based Brain Computer Interface (BCI) for assisting autism intervention. We used spectral features of EEG signals from a 14-channel EEG neuroheadset, together with therapist ratings of behavioral engagement, enjoyment, frustration, boredom, and difficulty to train a group of classification models. Seven classification methods were applied and compared including Bayes network, naive Bayes, Support Vector Machine (SVM), multilayer perceptron, K-nearest neighbors (KNN), random forest, and J48. The classification results were promising, with over 80% accuracy in classifying engagement and mental workload, and over 75% accuracy in classifying emotional states. Such results may lead to an adaptive closed-loop VR-based skill training system for use in autism intervention.
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9. Katuwal GJ, Cahill ND, Baum SA, Michael AM. {{The predictive power of structural MRI in Autism diagnosis}}. {Conf Proc IEEE Eng Med Biol Soc}. 2015; 2015: 4270-3.
Diagnosis of Autism Spectrum Disorder (ASD) using structural magnetic resonance imaging (sMRI) of the brain has been a topic of significant research interest. Previous studies using small datasets with well-matched Typically Developing Controls (TDC) report high classification accuracies (80-96%) but studies using the large heterogeneous ABIDE dataset report accuracies less than 60%. In this study we investigate the predictive power of sMRI in ASD using 373 ASD and 361 TDC male subjects from the ABIDE. Brain morphometric features were derived using FreeSurfer and classification was performed using three different techniques: Random Forest (RF), Support Vector Machine (SVM) and Gradient Boosting Machine (GBM). Although high classification accuracies were possible in individual sites (with a maximum of 97% in Caltech), the highest classification accuracy across all sites was only 60% (sensitivity = 57%, specificity = 64%). However, the accuracy across all sites improved to 67% when IQ and age information were added to morphometric features. Across all three classifiers, volume and surface area had more discriminative power. In general, important features for classification were present in the frontal and temporal regions and these regions have been implicated in ASD. This study also explores the effect of demographics and behavioral measures on the predictive power of sMRI. Results show that classification accuracy increases with autism severity and that ASD detection with sMRI is easier before the age of 10 years.
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10. Kumar A, Juneja M, Mishra D. {{Prevalence of Autism Spectrum Disorders in Siblings of Indian Children With Autism Spectrum Disorders}}. {J Child Neurol}. 2016.
This study determined the prevalence of autism spectrum disorders in 201 siblings of children with autism spectrum disorders. Siblings were screened using Modified Checklist for Autism in Toddlers and Social Responsiveness Scale, parent version. Screen-positive siblings were assessed using Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition) criteria. The risk of autism spectrum disorder in siblings was correlated with various familial and disease characteristics of the index case. Prevalence of autism spectrum disorder in siblings was 4.97%. There was a significant effect of the presence of aggressive behavior, externalizing problems and total problems in the proband, assessed using Childhood Behavior Checklist, and the young age of the father at conception on sibling risk of autism spectrum disorder. Results of our study are in line with previous studies reporting similar prevalence but have also brought up the association with behavioral problems as a possible risk factor. Siblings of children with autism spectrum disorder should be routinely screened, and genetic counseling for this increased risk should be explained to the family.
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11. Mandell D, Mandy W. {{Should all young children be screened for autism spectrum disorder?}}. {Autism}. 2015; 19(8): 895-6.
12. Nadig A, Seth S, Sasson M. {{Global Similarities and Multifaceted Differences in the Production of Partner-Specific Referential Pacts by Adults with Autism Spectrum Disorders}}. {Front Psychol}. 2015; 6: 1888.
Over repeated reference conversational partners tend to converge on preferred terms or referential pacts. Autism spectrum disorders (ASD) are characterized by pragmatic difficulties that are best captured by less structured tasks. To this end we tested adults with ASD who did not have language or intellectual impairments, and neurotypical comparison participants in a referential communication task. Participants were directors, describing unlexicalized, complex novel stimuli over repeated rounds of interaction. Group comparisons with respect to referential efficiency showed that directors with ASD demonstrated typical lexical entrainment: they became faster over repeated rounds and used shortened referential forms. ASD and neurotypical groups did not differ with respect to the number of descriptors they provided or the number of exchanges needed for matchers to identify figures. Despite these similarities the ASD group was slightly slower overall. We examined partner-specific effects by manipulating the common ground shared with the matcher. As expected, neurotypical directors maintained referential precedents when speaking to the same matcher but not with a new matcher. Directors with ASD were qualitatively similar but displayed a less pronounced distinction between matchers. However, significant differences and different patterns of reference emerged over time; neurotypical directors incorporated the new matcher’s contributions into descriptions, whereas directors with ASD were less likely to do so.
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13. Saiano M, Garbarino E, Lumachi S, Solari S, Sanguineti V. {{Effect of interface type in the VR-based acquisition of pedestrian skills in persons with ASD}}. {Conf Proc IEEE Eng Med Biol Soc}. 2015; 2015: 5728-31.
Possession of `social’ skills is crucial for persons with autism spectrum disorders (ASD) to maintain a certain independence and a better quality of life, and interaction with virtual environments seems an effective learning aid. In a previous study, we reported that in adults with ASD interaction with a virtual environment (a virtual city) is beneficial to the acquisition of pedestrian skills (street crossing and street navigation). Interaction was based on a gesture-based interface (Microsoft Kinect). Here we compare the learning performance when the same virtual environment is operated by a gamepad interface. We used exactly the same training protocol and data analysis than the original study. We found that both interface types are effective in the acquisition of street crossing and city navigation skills. The gamepad interface seems easier to use (thus leading to faster interaction), but gesture-based interfaces are superior in terms of transfer of the learned skills to real road environments (as reported by parents and caregivers).
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14. Tang X, Kim J, Zhou L, Wengert E, Zhang L, Wu Z, Carromeu C, Muotri AR, Marchetto MC, Gage FH, Chen G. {{KCC2 rescues functional deficits in human neurons derived from patients with Rett syndrome}}. {Proc Natl Acad Sci U S A}. 2016.
Rett syndrome is a severe form of autism spectrum disorder, mainly caused by mutations of a single gene methyl CpG binding protein 2 (MeCP2) on the X chromosome. Patients with Rett syndrome exhibit a period of normal development followed by regression of brain function and the emergence of autistic behaviors. However, the mechanism behind the delayed onset of symptoms is largely unknown. Here we demonstrate that neuron-specific K+-Cl- cotransporter2 (KCC2) is a critical downstream gene target of MeCP2. We found that human neurons differentiated from induced pluripotent stem cells from patients with Rett syndrome showed a significant deficit in KCC2 expression and consequently a delayed GABA functional switch from excitation to inhibition. Interestingly, overexpression of KCC2 in MeCP2-deficient neurons rescued GABA functional deficits, suggesting an important role of KCC2 in Rett syndrome. We further identified that RE1-silencing transcriptional factor, REST, a neuronal gene repressor, mediates the MeCP2 regulation of KCC2. Because KCC2 is a slow onset molecule with expression level reaching maximum later in development, the functional deficit of KCC2 may offer an explanation for the delayed onset of Rett symptoms. Our studies suggest that restoring KCC2 function in Rett neurons may lead to a potential treatment for Rett syndrome.
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15. Xavier J, Vignaud V, Ruggiero R, Bodeau N, Cohen D, Chaby L. {{A Multidimensional Approach to the Study of Emotion Recognition in Autism Spectrum Disorders}}. {Front Psychol}. 2015; 6: 1954.
Although deficits in emotion recognition have been widely reported in autism spectrum disorder (ASD), experiments have been restricted to either facial or vocal expressions. Here, we explored multimodal emotion processing in children with ASD (N = 19) and with typical development (TD, N = 19), considering uni (faces and voices) and multimodal (faces/voices simultaneously) stimuli and developmental comorbidities (neuro-visual, language and motor impairments). Compared to TD controls, children with ASD had rather high and heterogeneous emotion recognition scores but showed also several significant differences: lower emotion recognition scores for visual stimuli, for neutral emotion, and a greater number of saccades during visual task. Multivariate analyses showed that: (1) the difficulties they experienced with visual stimuli were partially alleviated with multimodal stimuli. (2) Developmental age was significantly associated with emotion recognition in TD children, whereas it was the case only for the multimodal task in children with ASD. (3) Language impairments tended to be associated with emotion recognition scores of ASD children in the auditory modality. Conversely, in the visual or bimodal (visuo-auditory) tasks, the impact of developmental coordination disorder or neuro-visual impairments was not found. We conclude that impaired emotion processing constitutes a dimension to explore in the field of ASD, as research has the potential to define more homogeneous subgroups and tailored interventions. However, it is clear that developmental age, the nature of the stimuli, and other developmental comorbidities must also be taken into account when studying this dimension.
