1. Amato CA, Fernandes FD. {{[Interactive use of communication by verbal and non-verbal autistic children.]}}. {Pro Fono};2010 (Dec);22(4):373-378.
BACKGROUND: communication of autistic children. AIM: to assess the communication functionality of verbal and non-verbal children of the autistic spectrum and to identify possible associations amongst the groups. METHOD: subjects were 20 children of the autistic spectrum divided into two groups: V with 10 verbal children and NV with 10 non-verbal children with ages varying between 2y10m and 10y6m. All subjects were video recorded during 30 minutes of spontaneous interaction with their mothers. The samples were analyzed according to the functional communicative profile and comparisons within and between groups were conducted. RESULTS: data referring to the occupation of communicative space suggest that there is an even balance between each child and his mother. The number of communicative acts per minute shows a clear difference between verbal and non-verbal children. Both verbal and non-verbal children use mostly the gestual communicative mean in their interactions. Data about the use of interpersonal communicative functions point out to the autistic children’s great interactive impairment. CONCLUSION: the characterization of the functional communicative profile proposed in this study confirmed the autistic children’s difficulties with interpersonal communication and that these difficulties do not depend on the preferred communicative mean.
2. Charman T, Pickles A, Simonoff E, Chandler S, Loucas T, Baird G. {{IQ in children with autism spectrum disorders: data from the Special Needs and Autism Project (SNAP)}}. {Psychol Med};2011 (Mar);41(3):619-627.
BACKGROUND: Autism spectrum disorder (ASD) was once considered to be highly associated with intellectual disability and to show a characteristic IQ profile, with strengths in performance over verbal abilities and a distinctive pattern of ‘peaks’ and ‘troughs’ at the subtest level. However, there are few data from epidemiological studies.MethodComprehensive clinical assessments were conducted with 156 children aged 10-14 years [mean (s.d.)=11.7 (0.9)], seen as part of an epidemiological study (81 childhood autism, 75 other ASD). A sample weighting procedure enabled us to estimate characteristics of the total ASD population. RESULTS: Of the 75 children with ASD, 55% had an intellectual disability (IQ<70) but only 16% had moderate to severe intellectual disability (IQ<50); 28% had average intelligence (115>IQ>85) but only 3% were of above average intelligence (IQ>115). There was some evidence for a clinically significant Performance/Verbal IQ (PIQ/VIQ) discrepancy but discrepant verbal versus performance skills were not associated with a particular pattern of symptoms, as has been reported previously. There was mixed evidence of a characteristic subtest profile: whereas some previously reported patterns were supported (e.g. poor Comprehension), others were not (e.g. no ‘peak’ in Block Design). Adaptive skills were significantly lower than IQ and were associated with severity of early social impairment and also IQ. CONCLUSIONS: In this epidemiological sample, ASD was less strongly associated with intellectual disability than traditionally held and there was only limited evidence of a distinctive IQ profile. Adaptive outcome was significantly impaired even for those children of average intelligence.
3. Fernandes FD, Santos TH, Amato CA, Molini-Avejonas DR. {{[Computerized resources in language therapy with children of the autistic spectrum.]}}. {Pro Fono};2010 (Dec);22(4):415-420.
BACKGROUND: the use of computerized technology in language therapy with children of the autistic spectrum. AIM: to assess the interference of using computers and specific programs during language therapy in the functional communicative profile and socio-cognitive performance of children of the autistic spectrum. METHOD: 23 children with ages ranging between 3 and 12 years were individually video recorded prior to and after a set of 10 regular language therapy sessions (i.e. a total of two video samples per subject) using computerized games according to the child’s choice. RESULTS: the following expressions were used by the therapists to describe the children’s performance during the use of computers: more attentive, more communicative initiatives, more eye contact, more interactive, more verbalizations, more attention and more action requests. Qualitative and quantitative progresses were identified, although without statistical significance. Those progresses were observed after a time period that is smaller than the usually applied to this kind of comparison and it seems to be a promising result. CONCLUSION: more controlled associations and comparisons were not possible due to the groups’ heterogeneity and therefore more consistent conclusions are not possible. It was clear that the subjects presented different reactions to the use of computerized resources during language therapy.
4. Ghanizadeh A. {{May lovastatin target both autism and epilepsy? A novel hypothesized treatment}}. {Epilepsy Behav};2011 (Jan 25)
5. Kirby RS, Wingate MS, Van Naarden Braun K, Doernberg NS, Arneson CL, Benedict RE, Mulvihill B, Durkin MS, Fitzgerald RT, Maenner MJ, Patz JA, Yeargin-Allsopp M. {{Prevalence and functioning of children with cerebral palsy in four areas of the United States in 2006: A report from the Autism and Developmental Disabilities Monitoring Network}}. {Res Dev Disabil};2011 (Jan 25)
AIM: To estimate the prevalence of cerebral palsy (CP) and the frequency of co-occurring developmental disabilities (DDs), gross motor function (GMF), and walking ability using the largest surveillance DD database in the US. METHODS: We conducted population-based surveillance of 8-year-old children in 2006 (N=142,338), in areas of Alabama, Georgia, Wisconsin, and Missouri. This multi-site collaboration involved retrospective record review at multiple sources. We reported CP subtype, co-occurring DDs, Gross Motor Function Classification System (GMFCS) level, and walking ability as well as CP period prevalence by race/ethnicity and sex. RESULTS: CP prevalence was 3.3 (95% confidence interval [CI]: 3.1-3.7) per 1000 and varied by site, ranging from 2.9 (Wisconsin) to 3.8 (Georgia) per 1000, 8-year olds (p<0.02). Approximately 81% had spastic CP. Among children with CP, 8% had an autism spectrum disorder and 35% had epilepsy. Using the GMFCS, 38.1% functioned at the highest level (I), with 17.1% at the lowest level (V). Fifty-six percent were able to walk independently and 33% had limited or no walking ability. INTERPRETATION: Surveillance data are enhanced when factors such as functioning and co-occurring conditions known to affect clinical service needs, quality of life, and health care are also considered.
6. Kumar A, Wadhawan R, Swanwick CC, Kollu R, Basu SN, Banerjee-Basu S. {{Animal model integration to AutDB, a genetic database for autism}}. {BMC Med Genomics};2011 (Jan 27);4(1):15.
ABSTRACT: BACKGROUND: : In the post-genomic era, multi-faceted research on complex disorders such as autism has generated diverse types of molecular information related to its pathogenesis. The rapid accumulation of putative candidate genes/loci for Autism Spectrum Disorders (ASD) and ASD-related animal models poses a major challenge for systematic analysis of their content. We previously created the Autism Database (AutDB) to provide a publicly available web portal for ongoing collection, manual annotation, and visualization of genes linked to ASD. Here, we describe the design, development, and integration of a new module within AutDB for ongoing collection and comprehensive cataloguing of ASD-related animal models. DESCRIPTION: As with the original AutDB, all data is extracted from published, peer-reviewed scientific literature. Animal models are annotated with a new standardized vocabulary of phenotypic terms developed by our researchers which is designed to reflect the diverse clinical manifestations of ASD. The new Animal Model module is seamlessly integrated to AutDB for dissemination of diverse information related to ASD. Animal model entries within the new module are linked to corresponding candidate genes in the original « Human Gene » module of the resource, thereby allowing for cross-modal navigation between gene models and human gene studies. Although the current release of the Animal Model module is restricted to mouse models, it was designed with an expandable framework which can easily incorporate additional species and non-genetic etiological models of autism in the future. CONCLUSIONS: : Importantly, this modular ASD database provides a platform from which data mining, bioinformatics, and/or computational biology strategies may be adopted to develop predictive disease models that may offer further insights into the molecular underpinnings of this disorder. It also serves as a general model for disease-driven databases curating phenotypic characteristics of corresponding animal models.
7. Sonie S, Kassai B, Pirat E, Masson S, Bain P, Robinson J, Reboul A, Wicker B, Chevallier C, Beaude-Chervet V, Deleage MH, Charvet D, Barthelemy C, Rochet T, Tatou M, Arnaud V, Manificat S. {{[French version of screening questionnaire for high-functioning autism or Asperger syndrome in adolescent: Autism Spectrum Quotient, Empathy Quotient and Systemizing Quotient. Protocol and questionnaire translation.]}}. {Presse Med};2011 (Jan 24)
AIM: No tools are currently available in France, for the detection of autism without mental retardation (high functioning autism and Asperger syndrome here referred as TED SDI). Use of screening tests by first-line clinicians would allow better detection of children who are likely to display such difficulties and to improve patients’ care. In England, 3 questionnaires have been evaluated: Autism Spectrum Quotient (AQ), Empathy Quotient (EQ), and Systemizing Quotient (SQ). This is the translation and evaluation of 3 questionnaires in France for TED SDI and control adolescents. METHODS: The translation of the questionnaires into French required two simultaneous translations, two back-translations and two consensus meetings. This is a cross-sectional study comparing scores obtained with the three AQ, EQ and SQ questionnaires. These questionnaires were completed by the parents of four groups of adolescents 11-18 years: 100 TED SDI adolescents (50 with IQ >/= 85 and 50 with 70</=IQ<85), 50 adolescents with another psychiatric disorder (TP) and 200 control adolescents (T). RESULTS: 580 questionnaires have been sent to 40 recruiting centres. By the 28th of February, 2010, 277 completed questionnaires were received completed (TED SDI: 70 (70%); TP: 25 (50%) et T: 182 (91%)). In the control group, 92 girls (mean 14.4+/-1.7 years) and 66 boys (14.5+/-1.7 years) were recruited. In the TED SDI group, 4 girls (14.3+/-2.4 years) and 42 boys (14.5+/-1.7 years) were recruited. One girl (81) and 6 boys (72.2+/-7.7) have an IQ between 70 and 85, and 3 girls (95.3+/-4.2) and 36 boys (102.9+/-12) have an IQ higher than 85. In the TP group, 9 girls (15.9+/-1.7 years) and 4 boys (15.8+/-1.9 years) were recruited. CONCLUSION: The aim of this study is to make the AQ, EQ and SQ questionnaires available in French for French speaking clinicians. This study will allow a rigorous evaluation of the usefulness of the AQ questionnaire in the screening of TED SDI in adolescents.
