1. Brugha TS, McManus S, Bankart J, Scott F, Purdon S, Smith J, Bebbington P, Jenkins R, Meltzer H. {{Epidemiology of autism spectrum disorders in adults in the community in England}}. {Arch Gen Psychiatry};2011 (May);68(5):459-465.

CONTEXT: To our knowledge, there is no published information on the epidemiology of autism spectrum disorders (ASDs) in adults. If the prevalence of autism is increasing, rates in older adults would be expected to be lower than rates among younger adults. OBJECTIVE: To estimate the prevalence and characteristics of adults with ASD living in the community in England. DESIGN: A stratified, multiphase random sample was used in the third national survey of psychiatric morbidity in adults in England in 2007. Survey data were weighted to take account of study design and nonresponse so that the results were representative of the household population. SETTING: General community (ie, private households) in England. PARTICIPANTS: Adults (people 16 years or older). MAIN OUTCOME MEASURES: Autism Diagnostic Observation Schedule, Module 4 in phase 2 validated against the Autism Diagnostic Interview-Revised and Diagnostic Interview for Social and Communication Disorders in phase 3. A 20-item subset of the Autism-Spectrum Quotient self-completion questionnaire was used in phase 1 to select respondents for phase 2. Respondents also provided information on sociodemographics and their use of mental health services. RESULTS: Of 7461 adult participants who provided a complete phase 1 interview, 618 completed phase 2 diagnostic assessments. The weighted prevalence of ASD in adults was estimated to be 9.8 per 1000 (95% confidence interval, 3.0-16.5). Prevalence was not related to the respondent’s age. Rates were higher in men, those without educational qualifications, and those living in rented social (government-financed) housing. There was no evidence of increased use of services for mental health problems. CONCLUSIONS: Conducting epidemiologic research on ASD in adults is feasible. The prevalence of ASD in this population is similar to that found in children. The lack of an association with age is consistent with there having been no increase in prevalence and with its causes being temporally constant. Adults with ASD living in the community are socially disadvantaged and tend to be unrecognized.

2. Charnsil C, Sriapai P. {{Attention deficit hyperactivity symptoms in children with autistic disorder: a cross-sectional descriptive study}}. {J Med Assoc Thai};2011 (Feb);94(2):231-234.

OBJECTIVE: (1) to examine the co-occurrence of attention deficit and hyperactivity symptoms in children with autistic disorder, and (2) to study the correlation between attention deficit hyperactivity symptoms and the severity of autistic disorder. MATERIAL AND METHOD: This was a clinical based study. The authors used Childhood Autistic Rating scale (CARs) to evaluate the severity of autistic disorder Swanson, Nolan, and Pelham Teacher and Parent Rating Scale, Version IV (SNAP-IV) was used to measure attention deficit and hyperactive symptoms in children with autism. RESULTS: Thirty (n=30) children enrolled in this study. All participants displayed attention deficit symptoms and 18 participants demonstrated hyperactivity as well. Nonparametric correlation showed a high positive correlation (Spa = 0.90, p = 0.00) between the severity of autistic disorder and hyperactivity and not the attention deficit symptoms (Spa = 0.29, p = 0.16). CONCLUSION: The authors finding shows a high comorbid rate of attention deficit and hyperactive symptoms among the participants.

3. Cohen Jr MM. {{ASD is an incorrect abbreviation for autism spectrum disorders}}. {Am J Med Genet A};2011 (Apr 27)

4. Fehr S, Bebbington A, Ellaway C, Rowe P, Leonard H, Downs J. {{Altered Attainment of Developmental Milestones Influences the Age of Diagnosis of Rett Syndrome}}. {J Child Neurol};2011 (May 4)

The early developmental history prior to the manifestation of Rett syndrome features is of clinical interest. This study describes the attainment of gross developmental milestones and regression, and assesses the relationships between genotype and age at diagnosis. The Australian Rett Syndrome Database and International Rett Syndrome Phenotype Database were used to source a total of 293 confirmed female subjects. Most girls learned to sit, were able to babble or use words, and approximately half learned to walk. Altered milestone attainment was associated with earlier diagnosis. There was variation in the acquisition of milestones, the age of regression, and the age of diagnosis by genotype. Most parents expressed concerns about unusual behaviors or development during infancy, and a more subtle atypical development during infancy was reported for most girls. It is important for clinicians to be aware of variable early development in Rett syndrome and that timely genetic testing is not precluded on this account.

5. Goldman SE, Richdale AL, Clemons T, Malow BA. {{Parental Sleep Concerns in Autism Spectrum Disorders: Variations from Childhood to Adolescence}}. {J Autism Dev Disord};2011 (May 3)

Sleep problems of adolescents and older children with Autism Spectrum Disorder (ASD) were compared to toddlers and young children in 1,859 children. Sleep was measured with the Children’s Sleep Habits Questionnaire. Total sleep problems were significant across all age groups, however the factors contributing to these problems differed. Adolescents and older children had more problems with delayed sleep onset, shorter sleep duration, and daytime sleepiness; while younger children had more bedtime resistance, sleep anxiety, parasomnias, and night wakings. The results suggest that sleep problems persist through adolescence in ASD with differences in types of problems experienced and emphasize the need for clinicians to address sleep behaviors not only in young children with ASD but throughout the age span.

6. Hazlett HC, Poe MD, Gerig G, Styner M, Chappell C, Smith RG, Vachet C, Piven J. {{Early brain overgrowth in autism associated with an increase in cortical surface area before age 2 years}}. {Arch Gen Psychiatry};2011 (May);68(5):467-476.

CONTEXT: Brain enlargement has been observed in 2-year-old children with autism, but the underlying mechanisms are unknown. OBJECTIVE: To investigate early growth trajectories in brain volume and cortical thickness. DESIGN: Longitudinal magnetic resonance imaging study. SETTING: Academic medical centers. PARTICIPANTS: Fifty-nine children with autism spectrum disorder (ASD) and 38 control children. Intervention Children were examined at approximately 2 years of age. Magnetic resonance imaging was repeated approximately 24 months later (when aged 4-5 years; 38 children with ASD; 21 controls). MAIN OUTCOME MEASURES: Cerebral gray and white matter volumes and cortical thickness. RESULTS: We observed generalized cerebral cortical enlargement in individuals with ASD at both 2 and 4 to 5 years of age. Rate of cerebral cortical growth across multiple brain regions and tissue compartments in children with ASD was parallel to that seen in the controls, indicating that there was no increase in rate of cerebral cortical growth during this interval. No cerebellar differences were observed in children with ASD. After controlling for total brain volume, a disproportionate enlargement in temporal lobe white matter was observed in the ASD group. We found no significant differences in cortical thickness but observed an increase in an estimate of surface area in the ASD group compared with controls for all cortical regions measured (temporal, frontal, and parieto-occipital lobes). CONCLUSIONS: Our longitudinal magnetic resonance imaging study found generalized cerebral cortical enlargement in children with ASD, with a disproportionate enlargement in temporal lobe white matter. There was no significant difference from controls in the rate of brain growth for this age interval, indicating that brain enlargement in ASD results from an increased rate of brain growth before age 2 years. The presence of increased cortical volume, but not cortical thickness, suggests that early brain enlargement may be associated with increased cortical surface area. Cortical surface area overgrowth in ASD may underlie brain enlargement and implicates a distinct set of pathogenic mechanisms.

7. Jameson R, Lorence D, Lee J. {{Integrating Computerized Primitives and Annotated Video Patterns: A Proposed Model for Autism Diagnosis and Research}}. {J Med Syst};2011 (May 3)

The use of computerized, digital video as a means for interactive data capture has been suggested as an alternative to direct observation of behavior. The appeal of observational measures is that they are presumed to be less vulnerable to potential biases from informants, such as parents or teachers, and permit more individualized assessment that may be lost with the use of rating scales. As a potential tool for long-term, automated observation and analysis. In this technology review we propose one promising model for the integration of computerized primitives recognition and annotated video patterns as an approach to large-scale autism diagnosis and research.

8. Mukaetova-Ladinska EB, Perry E, Baron M, Povey C. {{Ageing in people with autistic spectrum disorder}}. {Int J Geriatr Psychiatry};2011 (Apr 27)

BACKGROUND: Although autism in children and in adults attracts attention with respect to clinical and research needs, autism in the older individuals has not been considered to any degree. We review the evidence for urgently addressing the question of ageing in people with autistic spectrum disorder (ASD), focusing on those with disability. METHODS: Perspectives are reviewed in relation to demographics, experiences of relatives or carers, anticipated residential care needs, requirement for specifically designed cognitive assessment tools and importance of initiating new brain ageing research initiatives in this area. RESULTS: With escalating numbers of ASD individuals with disability reaching old age, provision of care is the paramount issue that is only beginning to be addressed in a few European communities and in the USA. How ageing affects cognition in such individuals as they reach an age no longer consistent with parental care is unknown, lacking any published evidence, and there is a clear need to design cognitive and behavioural assessment tools appropriate to ageing in ASD individuals with disability, as was the case with respect to dementia as a whole. Although there is a growing body of evidence on pathological, imaging, neuropharmacological and other key brain abnormalities in ASD, these are, to date, confined to children and young (only rarely to middle aged) adults. CONCLUSIONS: The need for new initiatives in research into ageing in ASD is urgent. Apart from a growing care crisis, the prospect of understanding brain ageing in this population may bring potential rewards beyond immediate clinical need given the precedent of Down syndrome. Copyright (c) 2011 John Wiley & Sons, Ltd.

9. Pinborough-Zimmerman J, Bakian AV, Fombonne E, Bilder D, Taylor J, McMahon WM. {{Changes in the Administrative Prevalence of Autism Spectrum Disorders: Contribution of Special Education and Health from 2002-2008}}. {J Autism Dev Disord};2011 (May 3)

This study examined changes in the administrative prevalence of autism spectrum disorders (ASD) in Utah children from 2002 to 2008 by record source (school and health), age (four, six, and eight), and special education classification. Prevalence increased 100% with 1 in 77 children aged eight identified with ASD by 2008. Across study years and age groups rates were higher when health and school data were combined with a greater proportion of cases ascertained from health. The proportion of children with both a health ASD diagnosis and a special education autism classification did not significantly change. Most children with an ASD health diagnosis did not have an autism special education classification. Findings highlight the growing health and educational impact of ASD.

10. Rutherford MD, Troje NF. {{IQ Predicts Biological Motion Perception in Autism Spectrum Disorders}}. {J Autism Dev Disord};2011 (May 3)

Biological motion is easily perceived by neurotypical observers when encoded in point-light displays. Some but not all relevant research shows significant deficits in biological motion perception among those with ASD, especially with respect to emotional displays. We tested adults with and without ASD on the perception of masked biological motion and the perception of direction from coherent and scrambled biological motion. Within the autism spectrum group, there was a large and statistically significant relationship between IQ and the ability to perceive directionality in masked biological motion. There were no group differences in sensitivity to biological motion or the ability to identify the direction of motion. Possible explanations are discussed, including the possible use of compensatory strategies in high IQ ASD.

11. Tassone F, Qi L, Zhang W, Hansen RL, Pessah IN, Hertz-Picciotto I. {{MAOA, DBH, and SLC6A4 variants in CHARGE: a case-control study of autism spectrum disorders}}. {Autism Res};2011 (Apr 29)

Genetic factors are established to contribute to the development of autism. We examined three loci, serotonin transporter (SLC6A4), dopamine beta-hydroxylase (DBH), and the variable number of tandem repeat promoter of the monoamine oxidase A (MAOA) for association with autism in participants from the Childhood Autism Risks from Genetics and the Environment (CHARGE ) Study, the first large-scale population-based case-control investigation of both environmental and genetic contributions to autism risk. Among male children enrolled in the CHARGE study we tested associations between each of the three polymorphisms and autism (AU) (n = 119), or a combined group of autism and other autism spectrum disorders (AU+ASD, which includes an additional n = 53) as compared with typically developing controls (TD, n = 137). The case-control association analysis showed neither SLC6A4 nor DBH to be statistically significantly associated with AU or ASD. However, the male children carrying 4 tandem repeats in the promoter region of the MAOA gene showed a two-fold higher risk of AU (or AU+ASD) than those carrying allele 3, adjusted for confounders (OR = 2.02, 95% CI = 1.12, 3.65, P = 0.02 for AU vs. TD, and OR = 2.05, 95% CI = 1.19, 3.53, P = 0.01 for ASD vs. TD). In addition, children of mothers homozygous for the 4 tandem repeat allele showed at least a three-fold higher risk of AU (or AU+ASD) than those with mothers homozygous for allele 3 (OR = 3.07, 95% CI = 1.19, 7.91, P = 0.02 for AU vs. TD, and OR = 3.26, 95% CI = 1.35, 7.89, P = 0.009 for AU+ASD vs. TD). These results suggest a potential role of the functional MAOA promoter alleles in the male child, the mother, or both in ASD. Autism Res 2011,4:xxx-xxx. (c) 2011 International Society for Autism Research, Wiley Periodicals, Inc.