1. Berrillo-Batista S, Morales-Chacon LM, Baez-Martin MM, Gomez-Fernandez L, Vera-Cuesta H, Maragoto-Rizo C, Sanchez-Coroneaux A, Perez-Mayo L. {{[Functional connectivity derived from an electroencephalogram during non-REM sleep in autism spectrum disorders]}}. {Revista de neurologia}. 2018; 67(2): 41-9.
AIM: To know the differences in the patterns of functional connectivity, the topological characteristics of the network and the relationship between these latter and the interictal epileptiform anomalies in children with primary and secondary autism spectrum disorder (ASD). PATIENTS AND METHODS: A retrospective study was conducted with 27 children aged between 3 and 13 years diagnosed with ASD. Subjects were submitted to an electroencephalogram in a functional state of spontaneous sleep. Functional connectivity and the properties of the network were analysed using data obtained from the electroencephalogram during the N2 stage of non-REM sleep. The frequency of discharge of the interictal epileptiform activity (FDIEA) was determined and was correlated with the topological properties of the network. RESULTS: Synchronisation was diminished in patients with secondary ASD for the alpha frequency and increased for the theta and delta frequency compared with patients with primary ASD. Local alpha efficiency was higher in patients who presented interictal epileptiform activity. Additionally, in patients with secondary ASD there was a statistically significant positive and negative correlation between FDIEA and the topological properties of the network. CONCLUSIONS: Patients with secondary ASD display patterns of functional connectivity that are weaker for the alpha frequency and stronger for theta and delta than patients with primary ASD. In patients with secondary ASD, the interictal epileptiform activity is related to local and global connectivity of the network for the alpha and beta bands during non-REM sleep.
2. Gowda VK, Srinivasan VM, Bhat M, Benakappa A. {{Tay-Sachs Disease Presenting as Refractory Epilepsy with Autistic Regression Secondary to a Novel Mutation in HEXA Gene}}. {Indian journal of pediatrics}. 2018.
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3. Hayes J, Ford T, Rafeeque H, Russell G. {{Clinical practice guidelines for diagnosis of autism spectrum disorder in adults and children in the UK: a narrative review}}. {BMC Psychiatry}. 2018; 18(1): 222.
BACKGROUND: Research suggests that diagnostic procedures for Autism Spectrum Disorder are not consistent across practice and that diagnostic rates can be affected by contextual and social drivers. The purpose of this review was to consider how the content of clinical practice guidelines shapes diagnoses of Autism Spectrum Disorder in the UK; and investigate where, within those guidelines, social factors and influences are considered. METHODS: We electronically searched multiple databases (NICE Evidence Base; TRIP; Social Policy and Practice; US National Guidelines Clearinghouse; HMIC; The Cochrane Library; Embase; Global health; Ovid; PsychARTICLES; PsychINFO) and relevant web sources (government, professional and regional NHS websites) for clinical practice guidelines. We extracted details of key diagnostic elements such as assessment process and diagnostic tools. A qualitative narrative analysis was conducted to identify social factors and influences. RESULTS: Twenty-one documents were found and analysed. Guidelines varied in recommendations for use of diagnostic tools and assessment procedures. Although multidisciplinary assessment was identified as the ‘ideal’ assessment, some guidelines suggested in practice one experienced healthcare professional was sufficient. Social factors in operational, interactional and contextual areas added complexity to guidelines but there were few concrete recommendations as to how these factors should be operationalized for best diagnostic outcomes. CONCLUSION: Although individual guidelines appeared to present a coherent and systematic assessment process, they varied enough in their recommendations to make the choices available to healthcare professionals particularly complex and confusing. We recommend a more explicit acknowledgement of social factors in clinical practice guidelines with advice about how they should be managed and operationalised to enable more consistency of practice and transparency for those coming for diagnosis.
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4. Landucci E, Brindisi M, Bianciardi L, Catania LM, Daga S, Croci S, Frullanti E, Fallerini C, Butini S, Brogi S, Furini S, Melani R, Molinaro A, Lorenzetti FC, Imperatore V, Amabile S, Mariani J, Mari F, Ariani F, Pizzorusso T, Pinto AM, Vaccarino FM, Renieri A, Campiani G, Meloni I. {{iPSC-derived neurons profiling reveals GABAergic circuit disruption and acetylated alpha-tubulin defect which improves after iHDAC6 treatment in Rett syndrome}}. {Experimental cell research}. 2018; 368(2): 225-35.
Mutations in MECP2 gene have been identified in more than 95% of patients with classic Rett syndrome, one of the most common neurodevelopmental disorders in females. Taking advantage of the breakthrough technology of genetic reprogramming, we investigated transcriptome changes in neurons differentiated from induced Pluripotent Stem Cells (iPSCs) derived from patients with different mutations. Profiling by RNA-seq in terminally differentiated neurons revealed a prominent GABAergic circuit disruption along with a perturbation of cytoskeleton dynamics. In particular, in mutated neurons we identified a significant decrease of acetylated alpha-tubulin which can be reverted by treatment with selective inhibitors of HDAC6, the main alpha-tubulin deacetylase. These findings contribute to shed light on Rett pathogenic mechanisms and provide hints for the treatment of Rett-associated epileptic behavior as well as for the definition of new therapeutic strategies for Rett syndrome.
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5. Najdowski AC, St Clair M, Fullen JA, Child A, Persicke A, Tarbox J. {{Teaching children with autism to identify and respond appropriately to the preferences of others during play}}. {Journal of applied behavior analysis}. 2018.
We observed three children with autism spectrum disorder during structured play dates in which play partners displayed interest or disinterest in the toys with which they were playing. We then taught subjects to identify play partners’ preferences and to make appropriate toy offers using a multiple-exemplar training package consisting of rules, midplay preference questions, prompting, and praise with observed generalization across untrained partners.
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6. Safra L, Ioannou C, Amsellem F, Delorme R, Chevallier C. {{Distinct effects of social motivation on face evaluations in adolescents with and without autism}}. {Sci Rep}. 2018; 8(1): 10648.
Individual differences in social motivation have an influence on many behaviours in both clinical and non-clinical populations. As such, social motivation has been identified as a biological trait that is particularly well-suited for dimensional approaches cutting across neuropsychological conditions. In the present paper, we tested whether social motivation had a similar impact in the general population and in a neuropsychological condition characterized by diminished social motivation: Autism Spectrum Disorders (ASD). More precisely, we evaluated the effect of social motivation on face evaluations in 20 adolescents with ASD and 20 matched controls using avatars parametrically varying in dominance and trustworthiness. In line with previous research, we found in the control group that participants with higher levels of social motivation relied more on perceived trustworthiness when producing likeability judgments. However, this pattern was not found in the ASD group. Social motivation thus appears to have a different effect in ASD and control populations, which raises questions about the relevance of subclinical or non-clinical populations to understand ASD.
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7. Sharp WG, Postorino V, McCracken CE, Berry RC, Criado KK, Burrell TL, Scahill L. {{Dietary Intake, Nutrient Status, and Growth Parameters in Children with Autism Spectrum Disorder and Severe Food Selectivity: An Electronic Medical Record Review}}. {Journal of the Academy of Nutrition and Dietetics}. 2018.
BACKGROUND: Food selectivity is common in children with autism spectrum disorder (ASD). The clinical characteristics, however, of severe food selectivity in children with ASD is not well documented. OBJECTIVE: This study examined the demographic characteristics, anthropometric parameters, risk of nutritional inadequacy, dietary variety, and problematic mealtime behaviors in a sample of children with ASD with severe food selectivity. DESIGN: The study involved a cross-sectional electronic medical record review. Data extraction followed a systematic protocol for data extraction. PARTICIPANTS/SETTING: Children (age 2 to 17 years) with ASD, severe food selectivity, and complete nutritional data who received a multidisciplinary evaluation at a specialty feeding clinic in the southeastern United States between January 2014 and January 2016. Criteria for severe food selectivity used in this clinical practice required complete omission of one or more food groups (eg, fruit, vegetable, protein, grain, dairy) or consuming a narrow range of items on a weekly basis (eg, five or fewer total food items). MAIN OUTCOME MEASURES: Analyses examined demographic characteristics, dietary preferences, risk for nutritional inadequacies, anthropometric parameters, and problematic mealtime behaviors. RESULTS: Of the 279 patients evaluated during the 24-month period, 70 children with ASD and severe food selectivity met inclusion criteria. Caregivers reported 67% of the sample (n=47) omitted vegetables and 27% omitted fruits (n=19). Seventy-eight percent consumed a diet at risk for five or more inadequacies. Risk for specific inadequacies included vitamin D (97% of the sample), fiber (91%) vitamin E (83%), and calcium (71%). Children with five or more nutritional inadequacies (n=55) were more likely to make negative statements during meals (P<0.05). Severe food selectivity was not associated with compromised growth or obesity. CONCLUSION: Children with ASD and severe food selectivity may be at increased risk for nutritional inadequacies. Future research should examine causes, consequences, and remediation of severe food selectivity in this population. Lien vers le texte intégral (Open Access ou abonnement)
