Article

Accuracy of phenotyping of autistic children based on Internet implemented parent report.

Department of Human Genetics, University of California-Los Angeles, 695 Charles E. Young Dr. South, Los Angeles, CA 90095, USA.
American Journal of Medical Genetics Part B Neuropsychiatric Genetics (Impact Factor: 3.27). 09/2010; 153B(6):1119-26. DOI: 10.1002/ajmg.b.31103
Source: PubMed

ABSTRACT While strong familial evidence supports a substantial genetic contribution to the etiology of autism spectrum disorders (ASD), specific genetic abnormalities have been identified in only a small minority of all cases. In order to comprehensively delineate the genetic components of autism including the identification of rare and common variants, overall sample sizes an order of magnitude larger than those currently under study are critically needed. This will require rapid and scalable subject assessment paradigms that obviate clinic-based time-intensive behavioral phenotyping, which is a rate-limiting step. Here, we test the accuracy of a web-based approach to autism phenotyping implemented within the Interactive Autism Network (IAN). Families who were registered with the IAN and resided near one of the three study sites were eligible for the study. One hundred seven children ascertained from this pool who were verbal, age 4-17 years, and had Social Communication Questionnaire (SCQ) scores > or =12 (a profile that characterizes a majority of ASD-affected children in IAN) underwent a clinical confirmation battery. One hundred five of the 107 children were ASD positive (98%) by clinician's best estimate. One hundred four of these individuals (99%) were ASD positive by developmental history using the Autism Diagnostic Interview-Revised (ADI-R) and 97 (93%) were positive for ASD by developmental history and direct observational assessment (Autism Diagnostic Observational Schedule or expert clinician observation). These data support the reliability and feasibility of the IAN-implemented parent-report paradigms for the ascertainment of clinical ASD for large-scale genetic research.

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