Version of Record online: 19 FEB 2010
Copyright © 2010, International Society for Autism Research, Wiley Periodicals, Inc.
Volume 3, Issue 1, pages 43–44, February 2010
How to Cite
(2010), Lay abstracts. Autism Res, 3: 43–44. doi: 10.1002/aur.117
- Issue online: 19 FEB 2010
- Version of Record online: 19 FEB 2010
A Pharmacogenetic Study of Escitalopram in Autism Spectrum Disorders
Thomas Owley, Camille W. Brune, Jeff Salt, Laura Walton, Steve Guter, Nelson Ayuyao, Robert D. Gibbons, Bennett L. Leventhal, and Edwin H. Cook
Many children with Autism Spectrum Disorders have problems with anxiety, obsessions, compulsions, and insisting that things stay the same. When other interventions are not adequately helping the child deal with these difficulties, sometimes medication is considered a treatment option. Serotonin is inactivated when it is taken back into nerve cells by a protein called the serotonin transporter. Escitalopram blocks this protein. We wanted to know if variation in the gene that produces the protein target for escitalopram would be related to response to this treatment. © 2010 INSAR/Wiley Periodicals, Inc.
Article Citation:Autism Res2010, 3: 1–7. DOI: 10.1002/aur.109
MEG Detection of Delayed Auditory Evoked Responses in Autism Spectrum Disorders: Towards an Imaging Biomarker for Autism
Timothy P.L. Roberts, Sarah Y. Khan, Mike Rey, Justin F. Monroe, Katelyn Cannon, Lisa Blaskey, Sarah Woldoff, Saba Qasmieh, Mike Gandal, Gwen L. Schmidt, Deborah M. Zarnow, Susan E. Levy, and J. Christopher Edgar
Auditory and speech problems are frequently observed in individuals with Autism Spectrum Disorders (ASD). To examine auditory processes in ASD, non-invasive neuroimaging methods were used to assess activity in primary/secondary auditory cortex. Seventeen typically developing children and 25 children with ASD were presented tones with frequencies of 200, 300, 500 and 1000 Hz, and left and right superior temporal gyrus activity at ∼50 and ∼100 ms was examined. The main finding was a latency delay in the right-hemisphere 100 ms response in ASD for all frequencies, a finding that indicates problems encoding simple sensory information. In addition, only in the control group was the expected association of earlier M100 latencies in older than younger children observed. Given similar findings in the language impaired and non-language impaired ASD subjects, a right-hemisphere 100 ms latency delay appears to be an electrophysiological biomarker for autism itself. © 2010 INSAR/Wiley Periodicals, Inc.
Article Citation:Autism Res2010, 3: 8–18. DOI: 10.1002/aur.111
Geographic Distribution of Autism in California: A Retrospective Birth Cohort Analysis
Karla C. Van Meter, Lasse E. Christiansen, Lora D. Delwiche, Rahman Azari, Tim E. Carpenter, and Irva Hertz-Picciotto
Few environmental exposures contributing to autism have been identified. If an exposure from a specific local source such as a factory or waste site were associated with autism, then autism could occur more frequently near this site, forming a geographic cluster. We used a new procedure based on multiple statistical tests to identify clusters that are unlikely to be random. This method would not be useful for common household exposures, nor for outdoor exposures from non-point sources such as traffic. Mothers' residences on 2,453,717 California birth records for the years 1996–2000 were analyzed. Among these children, 9,900 were recorded autism cases in the California Department of Developmental Services (DDS) database through February 2006. The residences at birth for these cases were compared with all births to look for clustering. Each of the 21 DDS Regional Center (RC) regions was examined separately because of differences in diagnostic practices. We identified ten clusters of increased autism risk in eight RC regions and one possible cluster in each of two other RC regions.
We assessed whether the clusters of autism were related to geographic clustering of factors known to be associated with increased incidence of autism: maternal and paternal age, parental maximum education, and race/ethnicity. Most areas of autism clustering were also areas with high parental education. The geographic association of highly educated parents and increased autism incidence may be because RCs do not actively recruit clients and parents with lower educational levels are less likely to successfully seek RC support. © 2010 INSAR/Wiley Periodicals, Inc.
Article Citation:Autism Res2010, 3: 19–29. DOI: 10.1002/aur.110
Independent and Dependent Contributions of Advanced Maternal and Paternal Ages to Autism Risk
Janie F. Shelton, Daniel J. Tancredi, and Irva Hertz-Picciotto
Previous reports on autism among children born to older parents have yielded conflicting results as to which parent, or whether neither, or both, contributes to the risk. We analyzed ten years of births in California, comprising approximately 5 million children. Autism cases were identified from the California Department of Developmental Services database and linked to birth files from 1990–1999. Due to the size of this population, we were able to observe the trend in autism risk for each parent's age, restricted to a narrow age range of the other parent. Analysis was confined to singleton births with complete data on ages and educational levels of both parents (n=4,947,935, cases=12,159). We observed consistent stepwise increased risk for autism with advancing maternal age regardless of the father's age, whereas increased risk with advancing paternal age was primarily observed among younger mothers, namely those <30 years of age. The different effects of father's age depending on the mother's age may indicate that the risk for autism from advancing maternal age past 30 years overwhelms the risk contributed by the father's age. Additionally, we showed that if the distribution of mothers' age had been the only factor to change between 1990 and 1999, then we would have expected the cumulative incidence to have risen only 4.6% during the decade from 1990 to 1999. © 2010 INSAR/Wiley Periodicals, Inc.
Article Citation:Autism Res2010, 3: 30–39. DOI: 10.1002/aur.116