1. {{Correction and Republication: Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years – Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2012}}. {MMWR Morbidity and mortality weekly report}. 2018; 67(45): 1279.
On April 1, 2016, MMWR Surveillance Summaries published « Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years-Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2012 » (1). On June 5, 2018, the authors informed MMWR about a number of inadvertent errors throughout the report that resulted from reporting of autism spectrum disorder cases among persons who did not live in the geographic surveillance area. Corrections of these errors do not change the interpretation or the conclusions of the original report. In accordance with December 2017 guidance from the International Committee of Medical Journal Editors (2), MMWR has corrected and republished the report (3). The republished report includes the original report with clearly marked corrections in supplementary materials.
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2. Al Backer NB, Jaafar M, Habibullah H, Bashir S. {{The Relationship between Sleep and Cognitive Performance in Autism Spectrum Disorder (ASD): A Pilot Study}}. {Children (Basel, Switzerland)}. 2018; 5(11).
BACKGROUND: Sleep concerns are common in children with autism spectrum disorders (ASD). The impact of poor sleep on cognitive performance in ASD children is not well-established. We investigated the possible correlation between sleep quality in ASD children and cognitive performance. The Cambridge Neuropsychological Test Automated Battery (CANTAB) was administered to examine specific components of non-verbal cognition. METHODS: The Children’s Sleep Habits Questionnaire (CSHQ) and actigraphy-measured data from 18 children with diagnosis of ASD were evaluated. Motor planning task (MOT), simple reaction time task (SRT) and the intradimensional/extradimensional shift (IED) of CANTAB were administered. RESULTS: ASD good sleeper (ASD-GS) showed significant better response time for SRT task as compared to ASD poor sleeper (ASD-PS) based on CSHQ score. Parameters of bedtime resistance (r = 0.531, p = 0.023), sleep anxiety (r = 0.474, p = 0.047) from CSHQ and actigrapgy dependent (wake after sleep onset (WASO) (r = 0.430, p = 0.024) were significantly correlate with response time of SRT task. CONCLUSION: We conclude that some signs reflecting the presence of poor sleep in ASD correlate with various aspects of motor output on non-verbal performance tasks. The question is raised whether poor sleep in non-complaining persons with autism should be treated.
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3. Bezgin G, Lewis JD, Evans AC. {{Developmental changes of cortical white-gray contrast as predictors of autism diagnosis and severity}}. {Translational psychiatry}. 2018; 8(1): 249.
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.
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4. Bokobza C, Van Steenwinckel J, Mani S, Mezger V, Fleiss B, Gressens P. {{Neuroinflammation in preterm babies and autism spectrum disorders}}. {Pediatric research}. 2018.
Genetic anomalies have a role in autism spectrum disorders (ASD). Each genetic factor is responsible for a small fraction of cases. Environment factors, like preterm delivery, have an important role in ASD. Preterm infants have a 10-fold higher risk of developing ASD. Preterm birth is often associated with maternal/fetal inflammation, leading to a fetal/neonatal inflammatory syndrome. There are demonstrated experimental links between fetal inflammation and the later development of behavioral symptoms consistent with ASD. Preterm infants have deficits in connectivity. Most ASD genes encode synaptic proteins, suggesting that ASD are connectivity pathologies. Microglia are essential for normal synaptogenesis. Microglia are diverted from homeostatic functions towards inflammatory phenotypes during perinatal inflammation, impairing synaptogenesis. Preterm infants with ASD have a different phenotype from term born peers. Our original hypothesis is that exposure to inflammation in preterm infants, combined with at risk genetic background, deregulates brain development leading to ASD.
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5. Ceranoglu TA, Wozniak J, Fried R, Galdo M, Hoskova B, Fong MD, Biederman J, Joshi G. {{A Retrospective Chart Review of Buspirone for the Treatment of Anxiety in Psychiatrically Referred Youth with High-Functioning Autism Spectrum Disorder}}. {Journal of child and adolescent psychopharmacology}. 2018.
OBJECTIVES: Anxiety disorders (ADs) are commonly associated with high-functioning Autism Spectrum Disorder (HF-ASD) and often worsen with age. Buspirone is a commonly prescribed anxiolytic drug with a favorable tolerability profile that may offer potential benefits in anxiety management for patients with HF-ASD. This study examines inadequately explored tolerability and effectiveness of buspirone in treating ADs comorbid with high-functioning ASD. METHODS: A retrospective chart review of a 1-year period was conducted in psychiatrically referred population of HF-ASD youth with AD (age 8-17 years) who were treated with buspirone (N = 31). Information on the demographics and treatment history was recorded. Effectiveness was assessed through the Clinical Global Impressions Scale (CGI) severity (CGI-S) and improvement (CGI-I) scores noted by the treating clinician. RESULTS: A total of 31 patients were prescribed buspirone during the determined period, at a mean dose of 41.61 +/- 24.10 mg for an average duration of 272 +/- 125 days. Change in the CGI-S mean scores with treatment suggests an overall improvement in the severity of anxiety symptoms (MT1 = 4.9 +/- 0.7; MT2 = 2.8 +/- 0.87; p < 0.001). Significant improvement in anxiety symptoms (CGI-I Lien vers le texte intégral (Open Access ou abonnement)
6. Chadha A. {{The Importance of Anxiety in Understanding how Decision Making is Affected in Autism Spectrum Disorder}}. {Psychiatria Danubina}. 2018; 30(Suppl 7): 639-43.
Autobiographical and clinical accounts of individuals with autism spectrum disorder (ASD) have highlighted that these individuals experience several difficulties during the decision making process. A review of the experimental based studies assessing performance in decision making tasks compared to controls emphasizes key differences including altered risk preferences, decreased sensitivity to social rewards, increased deliberative reasoning and atypical integration of emotional cues. Despite several attempts to devise cognitive theories to explain these differences, none so far can account for all the differences seen. However, one key observation, consistent with clinical accounts, is elevated levels of anxiety in populations with ASD. Whilst this has traditionally been considered a bi-product of the decision making process, I argue that increased anxiety may directly influence decision making in individuals with ASD, through 2 main routes. Firstly, elevated anxiety overwhelms Type 1 (intuitive) fast processes (within the Dual Process Model), leading to a decision making style biased by Type 2 (deliberative) processes. In addition, heightened anxiety decreases cognitive flexibility, leading to a more logic based, deliberative decision making style. This is superimposed on pre-existing cognitive impairments which altogether may account for the differences seen. Therefore, anxiety must be considered as a key variable in cognitive models of decision making in ASD. Specific recommendations for future research exploring the role of anxiety are discussed.
7. Chen J, Cohn ES, Orsmond GI. {{Parents’ future visions for their autistic transition-age youth: Hopes and expectations}}. {Autism : the international journal of research and practice}. 2018: 1362361318812141.
Researchers have documented that young adults with autism spectrum disorder have poor outcomes in employment, post-secondary education, social participation, independent living, and community participation. There is a need to further explore contributing factors to such outcomes to better support successful transitions to adulthood. Parents play a critical role in transition planning, and parental expectations appear to impact young adult outcomes for autistic individuals. The aim of this study was to explore how parents express their future visions (i.e. hopes and expectations) for their autistic transition-age youth. Data were collected through focus groups and individual interviews with 18 parents. Parents’ hopes and expectations focused on eight primary domains. In addition, parents often qualified or tempered their stated hope with expressions of fears, uncertainty, realistic expectations, and the perceived lack of guidance. We discuss our conceptualization of the relations among these themes and implications for service providers and research.
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8. Chen YC, Chang YW, Huang YS. {{Dysregulated translation in neurodevelopmental disorders: overview of autism-risk genes involved in translation}}. {Developmental neurobiology}. 2018.
Regulated local translation – whereby specific mRNAs are transported and localized in subcellular domains where they are translated in response to regional signals – allows for remote control of gene expression to concentrate proteins in subcellular compartments. Neurons are highly polarized cells with unique features favoring local control for axonal pathfinding and synaptic plasticity, which are key processes involved in constructing functional circuits in the developing brain. Neurodevelopmental disorders are caused by genetic or environmental factors that disturb the nervous system development during prenatal and early childhood periods. The growing list of genetic mutations that affect mRNA translation raises the question of whether aberrant translatomes in individuals with neurodevelopmental disorders share common molecular features underlying their stereotypical phenotypes and, vice versa, cause a certain degree of phenotypic heterogeneity. Here, we briefly give an overview of the role of local translation during neuronal development. We take the autism-risk gene list and discuss the molecules that (perhaps) are involved in mRNA transport and translation. Both exaggerated and suppressed translation caused by mutations in those genes have been identified or suggested. Finally, we discuss some proof-of-principle regimens for use in autism mouse models to correct dysregulated translation. This article is protected by copyright. All rights reserved.
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9. Christensen DL, Braun KVN, Baio J, Bilder D, Charles J, Constantino JN, Daniels J, Durkin MS, Fitzgerald RT, Kurzius-Spencer M, Lee LC, Pettygrove S, Robinson C, Schulz E, Wells C, Wingate MS, Zahorodny W, Yeargin-Allsopp M. {{Prevalence and Characteristics of Autism Spectrum Disorder Among Children Aged 8 Years – Autism and Developmental Disabilities Monitoring Network, 11 Sites, United States, 2012}}. {Morbidity and mortality weekly report Surveillance summaries (Washington, DC : 2002)}. 2018; 65(13): 1-23.
PROBLEM/CONDITION: Autism spectrum disorder (ASD). PERIOD COVERED: 2012. DESCRIPTION OF SYSTEM: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that provides estimates of the prevalence and characteristics of ASD among children aged 8 years whose parents or guardians reside in 11 ADDM Network sites in the United States (Arkansas, Arizona, Colorado, Georgia, Maryland, Missouri, New Jersey, North Carolina, South Carolina, Utah, and Wisconsin). Surveillance to determine ASD case status is conducted in two phases. The first phase consists of screening and abstracting comprehensive evaluations performed by professional service providers in the community. Data sources identified for record review are categorized as either 1) education source type, including developmental evaluations to determine eligibility for special education services or 2) health care source type, including diagnostic and developmental evaluations. The second phase involves the review of all abstracted evaluations by trained clinicians to determine ASD surveillance case status. A child meets the surveillance case definition for ASD if one or more comprehensive evaluations of that child completed by a qualified professional describes behaviors that are consistent with the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revision diagnostic criteria for any of the following conditions: autistic disorder, pervasive developmental disorder-not otherwise specified (including atypical autism), or Asperger disorder. This report provides ASD prevalence estimates for children aged 8 years living in catchment areas of the ADDM Network sites in 2012, overall and stratified by sex, race/ethnicity, and the type of source records (education and health records versus health records only). In addition, this report describes the proportion of children with ASD with a score consistent with intellectual disability on a standardized intellectual ability test, the age at which the earliest known comprehensive evaluation was performed, the proportion of children with a previous ASD diagnosis, the specific type of ASD diagnosis, and any special education eligibility classification. RESULTS: For 2012, the combined estimated prevalence of ASD among the 11 ADDM Network sites was 14.5 per 1,000 (one in 69) children aged 8 years. Estimated prevalence was significantly higher among boys aged 8 years (23.4 per 1,000) than among girls aged 8 years (5.2 per 1,000). Estimated ASD prevalence was significantly higher among non-Hispanic white children aged 8 years (15.3 per 1,000) compared with non-Hispanic black children (13.1 per 1,000), and Hispanic (10.2 per 1,000) children aged 8 years. Estimated prevalence varied widely among the 11 ADDM Network sites, ranging from 8.2 per 1,000 children aged 8 years (in the area of the Maryland site where only health care records were reviewed) to 24.6 per 1,000 children aged 8 years (in New Jersey, where both education and health care records were reviewed). Estimated prevalence was higher in surveillance sites where education records and health records were reviewed compared with sites where health records only were reviewed (17.1 per 1,000 and 10.4 per 1,000 children aged 8 years, respectively; p<0.05). Among children identified with ASD by the ADDM Network, 82% had a previous ASD diagnosis or educational classification; this did not vary by sex or between non-Hispanic white and non-Hispanic black children. A lower percentage of Hispanic children (78%) had a previous ASD diagnosis or classification compared with non-Hispanic white children (82%) and with non-Hispanic black children (84%). The median age at earliest known comprehensive evaluation was 40 months, and 43% of children had received an earliest known comprehensive evaluation by age 36 months. The percentage of children with an earliest known comprehensive evaluation by age 36 months was similar for boys and girls, but was higher for non-Hispanic white children (45%) compared with non-Hispanic black children (40%) and Hispanic children (39%). INTERPRETATION: Overall estimated ASD prevalence was 14.5 per 1,000 children aged 8 years in the ADDM Network sites in 2012. The higher estimated prevalence among sites that reviewed both education and health records suggests the role of special education systems in providing comprehensive evaluations and services to children with developmental disabilities. Disparities by race/ethnicity in estimated ASD prevalence, particularly for Hispanic children, as well as disparities in the age of earliest comprehensive evaluation and presence of a previous ASD diagnosis or classification, suggest that access to treatment and services might be lacking or delayed for some children. PUBLIC HEALTH ACTION: The ADDM Network will continue to monitor the prevalence and characteristics of ASD among children aged 8 years living in selected sites across the United States. Recommendations from the ADDM Network include enhancing strategies to 1) lower the age of first evaluation of ASD by community providers in accordance with the Healthy People 2020 goal that children with ASD are evaluated by age 36 months and begin receiving community-based support and services by age 48 months; 2) reduce disparities by race/ethnicity in identified ASD prevalence, the age of first comprehensive evaluation, and presence of a previous ASD diagnosis or classification; and 3) assess the effect on ASD prevalence of the revised ASD diagnostic criteria published in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition. Lien vers le texte intégral (Open Access ou abonnement)
10. Ezell J, Hogan A, Fairchild A, Hills K, Klusek J, Abbeduto L, Roberts J. {{Prevalence and Predictors of Anxiety Disorders in Adolescent and Adult Males with Autism Spectrum Disorder and Fragile X Syndrome}}. {Journal of autism and developmental disorders}. 2018.
Anxiety disorders affect ~ 15-20% of youths without neurodevelopmental disorders, with persons having autism spectrum disorder (ASD) and fragile X syndrome (FXS) at elevated risk for anxiety disorders. Few studies have compared rates and predictors of anxiety disorders in adolescents with FXS or ASD. This study directly compares rates, predictors, and medication of anxiety disorders between age-matched, male adolescents with FXS (n = 31) or ASD (n = 20). Results indicate that 51.6% of FXS and 50.0% of ASD adolescents met criteria for an anxiety disorder. Cognitive scores and ASD severity did not predict anxiety. Of those with anxiety, ~ 40% of the FXS and 20% of the ASD participants were prescribed medications for anxiety.
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11. Galazka MA, Asberg Johnels J, Zurcher NR, Hippolyte L, Lemonnier E, Billstedt E, Gillberg C, Hadjikhani N. {{Pupillary Contagion in Autism}}. {Psychological science}. 2018: 956797618809382.
Pupillary contagion is an involuntary change in the observer’s pupil size in response to the pupil size of another person. This effect, presumed to be an important adaption for individuals living in groups, has been documented in both typical infants and adults. Here, for the first time, we report pupillary contagion in individuals with autism, a disorder of social communication. We found that, compared with a typical group ( n = 63), individuals with autism ( n = 54) exhibited comparable pupillary contagion when observing pictures of emotional faces, despite less spontaneous attention toward the eye region. Furthermore, the magnitude of the pupillary response in the autism group was negatively correlated with time spent fixating the eye region. The results suggest that even with less looking toward the eyes, individuals with autism respond to the affective and arousal levels transmitted from other individuals. These results are discussed in the context of an overarousal account of socioaffective-processing differences in autism.
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12. Halayem S, Charfi N, Touati M, Mrabet A, Bouden A. {{Sensitivity to pain in autistic spectrum disorders: Its links with self-gressivity}}. {La Tunisie medicale}. 2018; 96(8-09): 501-4.
OBJECTIVES: To investigate the link between pain sensitivity in autism spectrum disorders (ASD) and self-aggressive behavior. METHODS: we performed a cross-sectional study which involved 50 children fulfilling DSM-V criteria for ASD; confirmed by the Autism Diagnostic Interview Revised. The severity of autism was determined using the Childhood Autism Rating Scale (CARS).The psycho-educational profile (PEP-R) was used to assess the age of development and perception. Sensitivity to pain was assessed with item IX of the CARS. Self-aggressive behavior was assessed by the Behavior Problems Inventory. RESULTS: Pain sensitivity was lowered in 40% and elevated in 4% of children. In the univariate analysis, no statistically significant association was found between normal sensitivity or hyper sensitivity to pain and the presence of auto-aggressiveness. A significant association was found between the presence of hypo-sensitivity to pain and the following variables: auto-aggression (p = 0.007, OR = 5.8, 95% CI = 1.5-21) , frequency of self-aggression (p = 0.001), intensity of self-aggression (p = 0.05), location of auto-aggressiveness at head and (P = 0.007, OR = 7.6, 95% CI = 1.8-14), higher score at CARS, and lower perception score at PEP-R (p = 0.012). Multiple-varied analysis identified risk factors for hypo-sensitivity to pain: lower perceptual score (p = 0.003, adjusted OR = 4.3, 95% CI = 1.9-54) and location of self-aggression at head and hands (p = 0.001, adjusted OR = 1.09, 95% CI = 1.02-1.09). CONCLUSION: It would be interesting to develop tools allowing a fine and precise evaluation of the painful sensation.
13. Healy S, Garcia JM, Haegele JA. {{Environmental Factors Associated with Physical Activity and Screen Time Among Children With and Without Autism Spectrum Disorder}}. {Journal of autism and developmental disorders}. 2018.
This study aimed to examine how environmental factors are associated with physical activity (PA) and screen-time (ST) among children with and without ASD (n = 1380 and 1411, respectively). For TD children, the absence of a bedroom television and neighborhood support were associated with PA. For children with ASD, no environmental factors were associated with PA. Regarding ST, the presence of a bedroom television, absence of limits on ST, lack of neighborhood amenities and support, and adverse neighborhood factors were all associated with ST among TD children. For children with ASD, the presence of a bedroom television and the absence of limits on ST were associated with ST. Potential explanations for this dichotomy and suggestions for future research are discussed.
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14. Hollander E, Uzunova G, Taylor BP, Noone R, Racine E, Doernberg E, Freeman K, Ferretti CJ. {{Randomized crossover feasibility trial of helminthic Trichuris suis ova versus placebo for repetitive behaviors in adult autism spectrum disorder}}. {The world journal of biological psychiatry : the official journal of the World Federation of Societies of Biological Psychiatry}. 2018: 1-9.
OBJECTIVES: Inflammatory mechanisms are implicated in the aetiology of autism spectrum disorder (ASD), and use of the immunomodulator Trichuris suis Ova (TSO) is a novel treatment approach. This pilot study determined the effect sizes for TSO versus placebo on repetitive behaviours, irritability and global functioning in adults with ASD. METHODS: A 28-week double-blind, randomised two-period crossover study of TSO versus placebo in ten ASD adults, aged 17-35, was completed, with a 4-week washout between each 12-week period at Montefiore Medical Center, Albert Einstein College of Medicine. Subjects with ASD, history of seasonal, medication or food allergies, Y-BOCS >/=6 and IQ >/=70 received 2,500 TSO ova or matching placebo every 2 weeks of each 12-week period. RESULTS: Large effect sizes for improvement in repetitive behaviours (d = 1.0), restricted interests (d = 0.82), rigidity (d = 0.79) and irritability (d = 0.78) were observed after 12 weeks of treatment. No changes were observed in the social-communication domain. Differences between treatment groups did not reach statistical significance. TSO had only minimal, non-serious side effects. CONCLUSIONS: This proof-of-concept study demonstrates the feasibility of TSO for the treatment of ASD, including a favourable safety profile, and moderate to large effect sizes for reducing repetitive behaviours and irritability. Clinicaltrials.gov: NCT01040221.
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15. Irwin JL, Yeates AJ, Mulhern MS, McSorley EM, Strain JJ, Watson GE, Grzesik K, Thurston SW, Love TM, Smith TH, Mruzek DW, Shamlaye CF, Monthy C, Myers GJ, Davidson PW, van Wijngaarden E. {{Maternal Gestational Immune Response and Autism Spectrum Disorder Phenotypes at 7 Years of Age in the Seychelles Child Development Study}}. {Molecular neurobiology}. 2018.
Findings from observational and experimental studies suggest that maternal inflammation during pregnancy is associated with autism spectrum disorder (ASD). We report the first study in humans to examine this association in a large prospective birth cohort. We studied 788 mother-child pairs from the Seychelles Child Development Study Nutrition Cohort 2. Thirteen inflammatory markers were measured in mothers’ serum at 28 weeks’ gestation, along with the sum of T-helper 1 (Th1) and 2 (Th2) cytokines. The Social Communication Questionnaire (SCQ) and Social Responsiveness Scale (SRS) were administered at age 7 years to obtain information on ASD phenotype. We evaluated associations between maternal inflammatory markers and ASD phenotype using multivariable linear regression. For the SCQ, increased MCP-1 (a chemokine that is upregulated in response to pro-inflammatory cytokines) was associated with fewer ASD symptoms (B = – 0.40; 95% CI = – 0.72, – 0.09). Increased IL-4 (a cytokine that is typically associated with an enhanced anti-inflammatory response) was associated with more ASD symptoms (B = 2.10; 95% CI = 0.78, 3.43). For the SRS, higher concentrations of the anti-inflammatory cytokine IL-10 were associated with fewer ASD symptoms (B = – 0.18; 95% CI = – 0.35, – 0.01), but only after removal of outliers. No associations were observed for other markers. These findings suggest that a shift in the maternal immune balance during pregnancy may be associated with ASD symptomatology. While the use of well-established measures that capture ASD phenotypic variability is a strength of the study, measurement of peripheral immune markers only once during gestation is a limitation. Our results should be confirmed using maternal immune markers measured throughout gestation.
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16. Jeon SJ, Gonzales EL, Mabunga DFN, Valencia ST, Kim DG, Kim Y, Adil KJL, Shin D, Park D, Shin CY. {{Sex-specific Behavioral Features of Rodent Models of Autism Spectrum Disorder}}. {Experimental neurobiology}. 2018; 27(5): 321-43.
Sex is an important factor in understanding the clinical presentation, management, and developmental trajectory of children with neuropsychiatric disorders. While much is known about the clinical and neurobehavioral profiles of males with neuropsychiatric disorders, surprisingly little is known about females in this respect. Animal models may provide detailed mechanistic information about sex differences in autism spectrum disorder (ASD) in terms of manifestation, disease progression, and development of therapeutic options. This review aims to widen our understanding of the role of sex in autism spectrum disorder, by summarizing and comparing behavioral characteristics of animal models. Our current understanding of how differences emerge in boys and girls with neuropsychiatric disorders is limited: Information derived from animal studies will stimulate future research on the role of biological maturation rates, sex hormones, sex-selective protective (or aggravating) factors and psychosocial factors, which are essential to devise sex precision medicine and to improve diagnostic accuracy. Moreover, there is a strong need of novel strategies to elucidate the major mechanisms leading to sex-specific autism features, as well as novel models or methods to examine these sex differences.
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17. Kalinli M, Ekinci O, Gunes S, Ekinci N. {{Autistic-Like Traits in Pena-Shokeir Syndrome}}. {Journal of autism and developmental disorders}. 2018.
Pena-Shokeir syndrome (PSS) is a rare, early lethal disease. PSS is characterized by fetal growth restriction, craniofacial deformities, multiple ankyloses and pulmonary hypoplasia. Because of the primary concern of physical health problems, psychiatric evaluation is frequently underestimated in PSS patients. Our case report describes a child with PSS who presented with autistic spectrum disorder symptoms.
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18. Lazzaro SC, Weidinger L, Cooper RA, Baron-Cohen S, Moutsiana C, Sharot T. {{Social Conformity in Autism}}. {Journal of autism and developmental disorders}. 2018.
Humans are extremely susceptible to social influence. Here, we examine whether this susceptibility is altered in autism, a condition characterized by social difficulties. Autistic participants (N = 22) and neurotypical controls (N = 22) completed a memory test of previously seen words and were then exposed to answers supposedly given by four other individuals. Autistic individuals and controls were as likely to alter their judgements to align with inaccurate responses of group members. These changes reflected both temporary judgement changes (public conformity) and long-lasting memory changes (private conformity). Both groups were more susceptible to answers believed to be from other humans than from computer algorithms. Our results suggest that autistic individuals and controls are equally susceptible to social influence when reporting their memories.
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19. Leo M, Carcagni P, Distante C, Spagnolo P, Mazzeo PL, Rosato AC, Petrocchi S, Pellegrino C, Levante A, De Lume F, Lecciso F. {{Computational Assessment of Facial Expression Production in ASD Children}}. {Sensors (Basel, Switzerland)}. 2018; 18(11).
In this paper, a computational approach is proposed and put into practice to assess the capability of children having had diagnosed Autism Spectrum Disorders (ASD) to produce facial expressions. The proposed approach is based on computer vision components working on sequence of images acquired by an off-the-shelf camera in unconstrained conditions. Action unit intensities are estimated by analyzing local appearance and then both temporal and geometrical relationships, learned by Convolutional Neural Networks, are exploited to regularize gathered estimates. To cope with stereotyped movements and to highlight even subtle voluntary movements of facial muscles, a personalized and contextual statistical modeling of non-emotional face is formulated and used as a reference. Experimental results demonstrate how the proposed pipeline can improve the analysis of facial expressions produced by ASD children. A comparison of system’s outputs with the evaluations performed by psychologists, on the same group of ASD children, makes evident how the performed quantitative analysis of children’s abilities helps to go beyond the traditional qualitative ASD assessment/diagnosis protocols, whose outcomes are affected by human limitations in observing and understanding multi-cues behaviors such as facial expressions.
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20. Li N, Li L, Gai Z, Li G. {{The association of auditory integration training in children with autism spectrum disorders among Chinese: A meta-analysis}}. {Bioscience reports}. 2018.
Randomized controlled trials (RCTs) have reported an inconsistent relationship about the auditory integration training (AIT) in children with autism spectrum disorders (ASD) among Chinese. The current study was to investigate the efficacy of AIT for children with ASD compared to those in control group by using meta-analysis. Relevant trials published were identified by an electronic search of PubMed, CENTRAL, EMBASE, WanFang, CNKI, and SinoMed databases up to December 31th, 2017. Outcome of interest included childhood autism rating scale (CARS), autism behavior checklist (ABC), intelligence quotient (IQ), and autism treatment evaluation checklist (ATEC). Standardized mean difference (SMD) with 95% confidence intervals (CI) was calculated using a random-effect model. Thirteen RCTs with 976 children with ASD were included for analysis. The pooled SMD showed that children with ASD had significantly lower ABC scores [summary SMD = -0.58, 95%CI= -0.79 to -0.38] and ATEC scores [summary SMD= -0.75, 95%CI= -1.05 to -0.45] in AIT group compared to that in control group. The analysis of pooled statistics put forward AIT could increase the IQ score when compared to that in control group [summary SMD= 0.59, 95%CI= 0.41 to 0.77]. A negative association was found about CARS scores between AIT group and control group. No publication bias was found and no single study had essential effect on the pooled results. In conclusions, AIT can reduce the score of ABC and ATEC and can increase the IQ score among children with ASD in Chinese. Therefore, it is recommended for Chinese children with ASD to receive AIT.
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21. Liao W. {{Psychomotor dysfunction in Rett syndrome: insights into the neurochemical and circuit roots}}. {Developmental neurobiology}. 2018.
Rett syndrome (RTT) is a monogenic neurodevelopmental disorder caused by mutations in the methyl-CpG binding protein 2 (MECP2) gene. Patients with RTT develop symptoms after 6-18 months of age, exhibiting characteristic movement deficits, such as ambulatory difficulties and loss of hand skills, in addition to breathing abnormalities and intellectual disability. Given the striking psychomotor dysfunction, numerous studies have investigated the underlying neurochemical and circuit mechanisms from different aspects. Here, I review the evidence linking MeCP2 deficiency to alterations in neurotransmission and neural circuits that govern psychomotor function and discuss a recently identified pathological origin likely underlying the psychomotor deficits in RTT. This article is protected by copyright. All rights reserved.
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22. Lin CW, Lin HY, Lo YC, Chen YJ, Hsu YC, Chen YL, Tseng WI, Gau SS. {{Alterations in white matter microstructure and regional volume are related to motor functions in boys with autism spectrum disorder}}. {Progress in neuro-psychopharmacology & biological psychiatry}. 2018.
BACKGROUND: Altered inter-regional structural connectivity related to higher cognitive functions has been commonly reported in individuals with autism spectrum disorder (ASD). However, whether these alterations similarly involve cortico-cerebellar motor circuitries remains largely elusive. METHODS: Using a cross-modality approach accounting for in-scanner motion levels, we investigated white matter (WM) properties in motor circuits of 55 boys with ASD (aged 8-18years) and 68 age-matched typically developing boys. Regional WM volumes in the primary motor, supplementary motor, somatosensory, and cerebellar areas were investigated using voxel-based morphometry. Diffusion spectrum imaging tractography was used to estimate WM integrity of the corticospinal, cortico-ponto-cerebellar (including fronto-ponto-cerebellar and parieto-ponto-cerebellar), and dentato-rubro-thalamo-cortical tracts. The reaction time test in the Cambridge Neuropsychological Test Automated Battery was used to assess motor performances. RESULTS: Boys with ASD had shorter movement time, increased WM volumes in the left somatosensory area, but decreased generalized fractional anisotropy value in the left parieto-ponto-cerebellar tract, compared to controls. A positive correlation between movement time and microstructural properties of the left parieto-ponto-cerebellar tract was found in boys with ASD. CONCLUSIONS: As the first study to demonstrate altered WM properties in the left somatosensory area, and its descending pathway connecting to the cerebellum in ASD, current results may highlight a potential new target of interventions for motor performance in ASD.
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23. Mandak K, Light J, McNaughton D. {{Digital Books with Dynamic Text and Speech Output: Effects on Sight Word Reading for Preschoolers with Autism Spectrum Disorder}}. {Journal of autism and developmental disorders}. 2018.
Despite the importance of literacy in today’s educational curriculum, learning to read is a challenge for many children with autism spectrum disorder (ASD). One of the foundational skills of early literacy learning is the ability to recognize sight words. This study used a single-subject, multiple-probe, across-participants design, to investigate the effects of a new software feature, dynamic text and speech output, on the acquisition of sight words by three pre-literate preschoolers with ASD during shared digital book reading experiences. All participants demonstrated successful acquisition of the target sight words with minimal exposure to the words. Limitations and future research directions are discussed, including the importance of investigating how the new software feature can be integrated into a more comprehensive literacy curriculum.
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24. Wang L, Li G, Shi F, Cao X, Lian C, Nie D, Liu M, Zhang H, Li G, Wu Z, Lin W, Shen D. {{Volume-Based Analysis of 6-Month-Old Infant Brain MRI for Autism Biomarker Identification and Early Diagnosis}}. {Medical image computing and computer-assisted intervention : MICCAI International Conference on Medical Image Computing and Computer-Assisted Intervention}. 2018; 11072: 411-9.
Autism spectrum disorder (ASD) is mainly diagnosed by the observation of core behavioral symptoms. Due to the absence of early biomarkers to detect infants either with or at-risk of ASD during the first postnatal year of life, diagnosis must rely on behavioral observations long after birth. As a result, the window of opportunity for effective intervention may have passed when the disorder is detected. Therefore, it is clinically urgent to identify imaging-based biomarkers for early diagnosis and intervention. In this paper, for the first time, we proposed a volume-based analysis of infant subjects with risk of ASD at very early age, i.e., as early as at 6 months of age. A critical part of volume-based analysis is to accurately segment 6-month-old infant brain MRI scans into different regions of interest, e.g., white matter, gray matter, and cerebrospinal fluid. This is actually very challenging since the tissue contrast at 6-month-old is extremely low, caused by inherent ongoing myelination and maturation. To address this challenge, we propose an anatomy-guided, densely-connected network for accurate tissue segmentation. Based on tissue segmentations, we further perform brain parcellation and statistical analysis to identify those significantly different regions between autistic and normal subjects. Experimental results on National Database for Autism Research (NDAR) show the advantages of our proposed method in terms of both segmentation accuracy and diagnosis accuracy over state-of-the-art results.
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25. Zhou H, Li CP, Huang Y, Zou XB, Luo XR, Wu LJ, Zhang L, Xu X, Yan WL, Wang Y. {{Reliability and validity of the translated Chinese version of Autism Spectrum Rating Scale (2-5 years)}}. {World journal of pediatrics : WJP}. 2018.
BACKGROUND: Early autism screening is of great value, but there is lack of a screening tool of early age (2-5 years) in China. The Autism Spectrum Rating Scale (ASRS, 2-5 years) is a newly developed autism screening tool in the USA. This study aimed to evaluate the reliability and validity of the translated Chinese version of ASRS (C_ASRS) in Chinese children population before its application in China for early autism screening. METHODS: Caregivers of general children aged 2-5 years from 17 kindergartens and autism spectrum disorder (ASD) cases from five special education schools in five cities were recruited to complete the C_ASRS. 1910 valid questionnaires from kindergarteners and 192 from ASD cases were included for analyses. RESULTS: The item reliability (Cronbach’s alpha) was more than 0.80 in the screening scale and DSM-5 scale, and 0.51-0.81 in the treatment scale. ASD cases scored higher on total score and most subscales compared to the kindergarteners (Cohen’s d ranging from 1.34 to 3.37). C_ASRS showed good discriminatory validity with an area under the receiver operating characteristic curve of 0.850 (95% confidence interval: 0.819-0.881). The cutoff >/= 60 achieved sensitivity of 65.63% and specificity of 85.63% in discriminating autism children from the general population. CONCLUSION: The results indicate that C_ASRS (2-5 years) could be used as an early level-2 screening tool for autism screening in China and should be further revised for level-1 screening.
