1. Apter A, Steinberg T. {{Autism Spectrum Disorder in Israel}}. {Isr Med Assoc J};2018 (Sep);20(9):584-585.
2. Berg KL, Shiu CS, Feinstein RT, Msall ME, Acharya K. {{Adverse Childhood Experiences Are Associated with Unmet Healthcare Needs among Children with Autism Spectrum Disorder}}. {J Pediatr};2018 (Sep 14)
OBJECTIVE: To explore associations between level of adverse childhood experiences (ACEs) and unmet healthcare needs among children with autism spectrum disorder (ASD) using a population-based sample. STUDY DESIGN: Cross-sectional data from the 2011-2012 National Survey of Child Health were analyzed to estimate prevalence of unmet healthcare needs among children with ASD, aged 2-17 years (ASD = 1624; estimated population = 1 174 871). Multivariate Poisson and logistic regression models were used to estimate the relationship between reported ACEs and unmet healthcare needs among children with ASD. RESULTS: After we adjusted for all other variables, children with ASD who experienced 1-2 ACEs and 3+ ACEs were associated with 1.78 (P < .05) and 2.53 (P < .01) times the incidence rate of unmet healthcare needs in comparison with children without ACEs. Compared with children who experienced 0 ACEs, the adjusted odds of any unmet healthcare need were 2.34 (P < .01) and 2.66 (P < .01) for children with 1-2 ACEs and 3 + ACEs, respectively. CONCLUSION: Although limited to cross-sectional data, our study provides compelling evidence on the link between ACEs and unmet healthcare needs among children with ASD. It advances understanding of risk factors in the child and community context that contribute to health disparities and negatively impact healthcare access and use in this population. Lien vers le texte intégral (Open Access ou abonnement)
3. Charpentier J, Kovarski K, Houy-Durand E, Malvy J, Saby A, Bonnet-Brilhault F, Latinus M, Gomot M. {{Emotional prosodic change detection in autism Spectrum disorder: an electrophysiological investigation in children and adults}}. {J Neurodev Disord};2018 (Sep 18);10(1):28.
BACKGROUND: Autism spectrum disorder (ASD) is characterized by atypical behaviors in social environments and in reaction to changing events. While this dyad of symptoms is at the core of the pathology along with atypical sensory behaviors, most studies have investigated only one dimension. A focus on the sameness dimension has shown that intolerance to change is related to an atypical pre-attentional detection of irregularity. In the present study, we addressed the same process in response to emotional change in order to evaluate the interplay between alterations of change detection and socio-emotional processing in children and adults with autism. METHODS: Brain responses to neutral and emotional prosodic deviancies (mismatch negativity (MMN) and P3a, reflecting change detection and orientation of attention toward change, respectively) were recorded in children and adults with autism and in controls. Comparison of neutral and emotional conditions allowed distinguishing between general deviancy and emotional deviancy effects. Moreover, brain responses to the same neutral and emotional stimuli were recorded when they were not deviants to evaluate the sensory processing of these vocal stimuli. RESULTS: In controls, change detection was modulated by prosody: in children, this was characterized by a lateralization of emotional MMN to the right hemisphere, and in adults, by an earlier MMN for emotional deviancy than for neutral deviancy. In ASD, an overall atypical change detection was observed with an earlier MMN and a larger P3a compared to controls suggesting an unusual pre-attentional orientation toward any changes in the auditory environment. Moreover, in children with autism, deviancy detection depicted reduced MMN amplitude. In addition in children with autism, contrary to adults with autism, no modulation of the MMN by prosody was present and sensory processing of both neutral and emotional vocal stimuli appeared atypical. CONCLUSIONS: Overall, change detection remains altered in people with autism. However, differences between children and adults with ASD evidence a trend toward normalization of vocal processing and of the automatic detection of emotion deviancy with age.
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4. Goncalves MVM, Harger R, Braatz V, Parolin LF, Biondo Eboni AC, Fontana MAN, Anacleto A, Fragoso YD. {{Pediatric acute-onset neuropsychiatric syndrome (PANS) misdiagnosed as autism spectrum disorder}}. {Immunol Lett};2018 (Sep 14)
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5. Grob CM, Lerman DC, Langlinais CA, Villante NK. {{Assessing and teaching job-related social skills to adults with autism spectrum disorder}}. {J Appl Behav Anal};2018 (Sep 16)
Few studies have evaluated interventions to improve the job-related social skills of adults with autism spectrum disorder. In this study, we examined the efficacy of a treatment package for teaching several social skills that are critical to job success, such as responding appropriately to feedback and asking for a task model from the supervisor. Three adults, aged 19 to 27 years, participated. Initial training of each skill consisted of verbal explanations, modeling, and role-play with feedback, along with stimulus prompts to promote generalization to a different setting. The trainer introduced additional intervention components as needed. We also evaluated generalization across different social skills and evocative situations. Results indicated that the treatment package was generally effective in improving the targeted social skills, and that stimulus prompts may be necessary for generalization to a job setting. However, generalized responding across social skills rarely emerged. These findings have important implications for preparing individuals with autism to function successfully on the job.
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6. Hatta K, Hosozawa M, Tanaka K, Shimizu T. {{Exploring Traits of Autism and Their Impact on Functional Disability in Children with Somatic Symptom Disorder}}. {J Autism Dev Disord};2018 (Sep 18)
Subclinical traits of autism were measured in children with somatic symptom disorder (SSD, n = 28) and compared with age-matched controls (n = 26) using the Autism Spectrum Quotient (AQ) children’s version. The KINDL(R) quality of life questionnaire was used to assess functional disability. Although there was no significant group difference in total traits of autism, SSD group had significantly greater difficulty in attention switching domain. Logistic regression analysis confirmed attention switching and age were associated with increased likelihood of SSD. In SSD group, difficulty in attention switching significantly negatively correlated with total, family, and friends quality of life scores. In conclusion, assessment and treatment targeting difficulties in attention switching could be useful when dealing with children with SSD.
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7. Kerub O, Haas E, Menashe I, Davidovitch N, Meiri G. {{Autism Spectrum Disorder: Evolution of Disorder Definition, Risk Factors and Demographic Characteristics in Israel}}. {Isr Med Assoc J};2018 (Sep);20(9):576-581.
8. Prendeville P, Kinsella W. {{The Role of Grandparents in Supporting Families of Children with Autism Spectrum Disorders: A Family Systems Approach}}. {J Autism Dev Disord};2018 (Sep 18)
A family systems approach is required to identify the needs of families of children with autism. This paper explores how grandparents support children with autism and their parents using a family systems perspective. A thematic analysis of eighteen semi-structured interviews was conducted with participants from nine families, capturing experiences of both parents’ and grandparents’. Themes identified were family recalibrating; strengthening the family system; and current needs and future concerns of grandparents. The views of families indicated the overwhelming need to acknowledge the grandparental role in supporting families that strengthen the family system by supporting the needs of a child with autism. Findings revealed that grandfathers have a calming role in these families where children have significant behavioural difficulties.
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9. Ridderinkhof A, de Bruin EI, van den Driesschen S, Bogels SM. {{Attention in Children With Autism Spectrum Disorder and the Effects of a Mindfulness-Based Program}}. {J Atten Disord};2018 (Sep 15):1087054718797428.
OBJECTIVE: Children with autism spectrum disorder (ASD) show atypical attention. Mindfulness-based programs (MBPs), with self-regulation of attention as a basic component, could benefit these children. METHOD: We investigated how 49 children with ASD differed from 51 typically developing (TD) children in their attention systems; and whether their attention systems were improved by an MBP for children and their parents (MYmind), using a cognitive measure of attention, the Attention Network Test. RESULTS: Children with ASD did not differ from TD children in the speed of the attention systems, but were somewhat less accurate in their orienting and executive attention. Also, MYmind did not significantly improve attention, although trend effects indicated improved orienting and executive attention. Robustness checks supported these improvements. CONCLUSION: Trend effects of the MBP on the attention systems of children with ASD were revealed, as well as minor differences between children with ASD and TD children in their attention systems.
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10. Zhang M, Ma W, Zhang J, He Y, Wang J. {{Analysis of gut microbiota profiles and microbe-disease associations in children with autism spectrum disorders in China}}. {Sci Rep};2018 (Sep 18);8(1):13981.
Autism spectrum disorder (ASD) is a set of complex neurodevelopmental disorders. Recent studies reported that children with ASD have altered gut microbiota profiles compared with typical development (TD) children. However, few studies on gut bacteria of children with ASD have been conducted in China. Here, in order to elucidate changes of fecal microbiota in children with ASD, 16S rRNA sequencing was conducted and the 16S rRNA (V3-V4) gene tags were amplified. We investigated differences in fecal microbiota between 35 children with ASD and 6 TD children. At the phylum level, the fecal microbiota of ASD group indicated a significant increase of the Bacteroidetes/Firmicutes ratio. At the genus level, we found that the relative abundance of Sutterella, Odoribacter and Butyricimonas was much more abundant in the ASD group whereas the abundance of Veillonella and Streptococcus was decreased significantly compared to the control group. Functional analysis demonstrated that butyrate and lactate producers were less abundant in the ASD group. In addition, we downloaded the association data set of microbe-disease from human microbe-disease association database and constructed a human disease network including ASD using our gut microbiome results. In this microbe-disease network based on microbe similarity of diseases, we found that ASD is positively correlated with periodontal, negatively related to type 1 diabetes. Therefore, these results suggest that microbe-based disease analysis is able to predict novel connection between ASD and other diseases and may play a role in revealing the pathogenesis of ASD.
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11. Zhao Y, Zhou C, Yu H, Zhang W, Cheng F, Yu H, Zhou D, Li B, Liu J, Dai J, Zhong J, Chen M, Huang T, Pan R, Duan S, Hu Z. {{Association between the methylation of six apoptosisassociated genes with autism spectrum disorder}}. {Mol Med Rep};2018 (Sep 10)
Excessive apoptosis hinders the process of brain maturation and is regarded as one of the principal risk factors for the development of autism spectrum disorder (ASD). The aim of the present study was to investigate the association between the methylation of six apoptosisassociated genes [transforming growth factor beta 1 (TGFB1), BCL2 associated X, apoptosis regulator, insulin like growth factor binding protein 3, protein kinase C beta 1, presenilin 2 and CC motif chemokine ligand 2] and ASD. Using quantitative methylationspecific polymerase chain reaction technology, DNA methylation levels were detected in 42 autistic and 26 control subjects. The logistic regression analysis results demonstrated that of the six genes, only TGFB1 was significantly hypomethylated in peripheral blood samples from children with autism compared with control samples (mean percentage of methylated reference, 0.011% vs. 0.019%; ageadjusted P=0.028). In addition, TGFB1 methylation was identified to be positively associated with the interaction ability score from the Autism Behavior Checklist (r=0.452; P=0.035). These data suggested that decreased TGFB1 methylation may contribute to the development of ASD.
