1. {{Correction for Schumann et al., Genome-wide association and genetic functional studies identify autism susceptibility candidate 2 gene (AUTS2) in the regulation of alcohol consumption}}. {Proc Natl Acad Sci U S A};2011 (May 31);108(22):9316.
2. Bajaj N, Soon D, Quinn N. {{Fragile X-Associated tremor ataxia syndrome sine tremor}}. {Mov Disord};2011 (May 31)
3. Delong G. {{A Positive Association found between Autism Prevalence and Childhood Vaccination uptake across the U.S. Population}}. {J Toxicol Environ Health A};2011 (Jan);74(14):903-916.
The reason for the rapid rise of autism in the United States that began in the 1990s is a mystery. Although individuals probably have a genetic predisposition to develop autism, researchers suspect that one or more environmental triggers are also needed. One of those triggers might be the battery of vaccinations that young children receive. Using regression analysis and controlling for family income and ethnicity, the relationship between the proportion of children who received the recommended vaccines by age 2 years and the prevalence of autism (AUT) or speech or language impairment (SLI) in each U.S. state from 2001 and 2007 was determined. A positive and statistically significant relationship was found: The higher the proportion of children receiving recommended vaccinations, the higher was the prevalence of AUT or SLI. A 1% increase in vaccination was associated with an additional 680 children having AUT or SLI. Neither parental behavior nor access to care affected the results, since vaccination proportions were not significantly related (statistically) to any other disability or to the number of pediatricians in a U.S. state. The results suggest that although mercury has been removed from many vaccines, other culprits may link vaccines to autism. Further study into the relationship between vaccines and autism is warranted.
4. Dewitt JC, Dietert RR. {{Response to « Theoretical aspects of autism: Causes-A review » by Ratajczak, HV (Journal of Immunotoxicology 8:68-79, 2011)}}. {J Immunotoxicol};2011 (May 31)
5. Happe F. {{Criteria, Categories, and Continua: Autism and Related Disorders in DSM-5}}. {J Am Acad Child Adolesc Psychiatry};2011 (Jun);50(6):540-542.
6. Lai G, Schneider HD, Schwarzenberger JC, Hirsch J. {{Speech Stimulation during Functional MR Imaging as a Potential Indicator of Autism}}. {Radiology};2011 (May 31)
Purpose: To determine the feasibility of applying functional magnetic resonance (MR) imaging as an objective indicator of language disability in autism by using passive speech stimulation. Materials and Methods: This prospective study was approved by the institutional review board, and informed consent was obtained from the parents or guardians of all subjects. Functional MR imaging was performed during passive presentations of prerecorded speech in 15 control subjects (mean age +/- standard deviation, 12.1 years +/- 4.3) and 12 language-impaired, age-matched autistic subjects (mean age, 12.4 years +/- 4.7). An additional 27 autistic children (mean age, 8.4 years +/- 3.1), who underwent imaging while sedated with propofol as part of routine clinical MR evaluations, were also included. Activation maps for each subject were computed by using univariate general linear model analyses. The spread (quantified as number of voxels) and amplitude of the functional MR imaging activation were then quantified within two anatomically specified regions of interest known to be involved with language: the primary auditory cortex (A1) and the superior temporal gyrus (STG). Group differences were compared by using analysis of variance, two-sample t tests, and Wilcoxon rank sum tests where appropriate. The threshold for autism was defined as 1 standard deviation below the control mean for subjects imaged in the alert state. A similar threshold was estimated for sedated autistic subjects on the basis of differences between nonsedated and sedated autistic subjects. Results: Activity in A1 did not differ between autistic and control subjects. However, mean amplitude and spread of activity in the STG differed between autistic and control subjects (P < .001). Values for 10 of the 12 (83%) nonsedated autistic subjects decreased at least 1 standard deviation below the control distribution. The threshold derived from sedation-adjusted values of the control group enabled identification of 26 of the 27 (96%) sedated autistic subjects. Conclusion: Functional MR imaging activation within the STG in response to passive speech stimulation helped differentiate autistic from control subjects, demonstrating the potential utility of functional MR imaging as an objective indicator of language impairment in autism. Future studies may lead to an early and objective indicator for autism with these methods. (c) RSNA, 2011.
7. Li BM, Liu XR, Yi YH, Deng YH, Su T, Zou X, Liao WP. {{Autism in Dravet syndrome: Prevalence, features, and relationship to the clinical characteristics of epilepsy and mental retardation}}. {Epilepsy Behav};2011 (May 25)
Autism is a pervasive developmental disorder that frequently co-occurs with epilepsy. Dravet syndrome is a severe epileptic encephalopathy associated with psychomotor developmental delay. Autism in Dravet syndrome, however, has rarely been studied. In this study, the prevalence and features of autism in patients with Dravet syndrome, their potential association with mental retardation, and the clinical characteristics of epilepsy were investigated. Clinical data of 37 patients with Dravet syndrome were collected, and evaluations of autism and mental retardation were performed. Nine patients (24.3%) met the criteria for autism. All patients with autism showed speech delay, no emotional reciprocity, and narrow interests, whereas 89.3, 46.4, and 39.9% of patients without autism had speech delay, short temper, and narrow interests, respectively. Mental retardation was observed in 94.6% of patients with Dravet syndrome, with more frequent severe or profound mental retardation in those with autism. The clinical features of epilepsy did not statistically differ between the patients with autism and the patients without autism.
8. Mattila ML, Kielinen M, Linna SL, Jussila K, Ebeling H, Bloigu R, Joseph RM, Moilanen I. {{Autism Spectrum Disorders According to DSM-IV-TR and Comparison With DSM-5 Draft Criteria: An Epidemiological Study}}. {J Am Acad Child Adolesc Psychiatry};2011 (Jun);50(6):583-592 e511.
OBJECTIVE: The latest definitions of autism spectrum disorders (ASDs) were specified in DSM-IV-TR in 2000. DSM-5 criteria are planned for 2013. Here, we estimated the prevalence of ASDs and autism according to DSM-IV-TR, clarified confusion concerning diagnostic criteria, and evaluated DSM-5 draft criteria for ASD posted by the American Psychiatry Association (APA) in February 2010. METHOD: This was an epidemiological study of 5,484 eight-year-old children in Finland, 4,422 (81%) of them rated via the Autism Spectrum Screening Questionnaire by parents and/or teachers, and 110 examined by using a structured interview, semi-structured observation, IQ measurement, school-day observation, and patient records. Diagnoses were assigned according to DSM-IV-TR criteria and DSM-5 draft criteria in children with a full-scale IQ (FSIQ) >/=50. Patient records were evaluated in children with an FSIQ <50 to discover diagnoses of ASDs. RESULTS: The prevalence of ASDs was 8.4 in 1,000 and that of autism 4.1 in 1,000 according to DSM-IV-TR. Of the subjects with ASDs and autism, 65% and 61% were high-functioning (FSIQ >/=70), respectively. The prevalence of pervasive developmental disorder not otherwise specified was not estimated because of inconsistency in DSM-IV-TR criteria. DSM-5 draft criteria were shown to be less sensitive in regard to identification of subjects with ASDs, particularly those with Asperger’s syndrome and some high-functioning subjects with autism. CONCLUSIONS: DSM-IV-TR helps with the definition of ASDs only up to a point. We suggest modifications to five details of DSM-5 draft criteria posted by the APA in February 2010. Completing revision of DSM criteria for ASDs is a challenging task.
9. Montes G, Halterman JS. {{White-Black Disparities in Family-Centered Care Among Children with Autism in the United States: Evidence From the NS-CSHCN 2005-2006}}. {Acad Pediatr};2011 (May 27)
OBJECTIVES: The aim of this study was to compare the reported receipt of family-centered care between parents of white and black children with autism spectrum disorders (ASD) in the United States, and to disentangle the associations of race and ASD on different aspects of family-centered care. METHODS: Parents of 35 386 children, aged 0 to 17 years, were surveyed by the National Survey of Children with Special Health Care Needs (NS-CSHCN) 2005-2006. Autism was defined by the question, « To the best of your knowledge, does [child] currently have autism or autism spectrum disorder, that is, ASD? » Family-centered care was measured with 5 key indicators on a 4-point Likert scale. Univariate and multivariate analyses were used, with adjustment for the complex sampling design. RESULTS: The prevalence of autism in this sample was 5.4% (n = 1869). We found that, among children with SHCN but no ASD, more white parents than black parents reported receiving family-centered care. Further, fewer parents of both white children and black children with ASD reported receiving family-centered care compared with those with a child who had special needs other than ASD. Lastly, among parents with a child with ASD, being black was associated with lower reporting of family-centered care for 3 of 5 items. In multivariate analyses, black parents with a child with ASD had 2 to 5 times greater odds of not reporting family-centered care on each item compared with white parents without a child with ASD. CONCLUSION: Targeted efforts are needed to improve family-centered care for parents with a child with ASD, and particularly for black families.
10. Nicolaidis C, Raymaker D, McDonald K, Dern S, Ashkenazy E, Boisclair C, Robertson S, Baggs A. {{Collaboration strategies in nontraditional community-based participatory research partnerships: lessons from an academic-community partnership with autistic self-advocates}}. {Prog Community Health Partnersh};2011 (Summer);5(2):143-150.
Background: Most community-based participatory research (CBPR) projects involve local communities defined by race, ethnicity, geography, or occupation. Autistic self-advocates, a geographically dispersed community defined by disability, experience issues in research similar to those expressed by more traditional minorities. Objectives: We sought to build an academic-community partnership that uses CBPR to improve the lives of people on the autistic spectrum. Methods: The Academic Autistic Spectrum Partnership in Research and Education (AASPIRE) includes representatives from academic, self-advocate, family, and professional communities. We are currently conducting several studies about the health care experiences and well-being of autistic adults. Lessons Learned: We have learned a number of strategies that integrate technology and process to successfully equalize power and accommodate diverse communication and collaboration needs. Conclusions: CBPR can be conducted successfully with autistic self-advocates. Our strategies may be useful to other CBPR partnerships, especially ones that cannot meet in person or that include people with diverse communication needs.
