18897
Creating a Spatial Data Architecture for the National Database for Autism Research

Friday, May 15, 2015: 10:00 AM-1:30 PM
Imperial Ballroom (Grand America Hotel)
M. L. Miranda1,2, P. Maxson1, N. Sandberg1 and D. Hall3, (1)National Center for Geospatial Medicine, University of Michigan, Ann Arbor, MI, (2)School of Natural Resources and Environment, University of Michigan, Ann Arbor, MI, (3)Omnitec Solutions Inc., Bethesda, MD
Background:  The etiology of autism spectrum disorder (ASD) remains largely unknown. While genetic vulnerabilities have been linked to development of ASD, much remains unexplained. Researchers have begun to identify social and environmental stressors that might influence early brain development which may manifest as changes commonly associated with ASD. Linking social and environmental data to the clinical, genomic, and imaging data in the National Database for Autism Research (NDAR) holds great potential for building a more robust research platform for basic science and clinical research on ASD. 

Objectives:  The National Institute for Mental Health, Omnitec, and the National Center for Geospatial Medicine (NCGM) at the University of Michigan are partnering to capture geospatial information on families affected by ASD. The collaborative team is especially interested in residential information on parents and children over both space and time. The resulting spatially-enabled data architecture will link environmental and social data to existing NDAR data. By combining clinical, social, and environmental data on a national scale, scientists can investigate the relationships among chemical and non-chemical stressors and ASD. 

Methods:  NCGM will employ strategies to consent families living with ASD, many of whom may already be enrolled in the NDAR. NCGM will launch a website through which affected families can enter self-reported information. Families will complete a short, secure, online questionnaire designed to gather geographic data to facilitate linkage of NDAR clinical, genomic, and imaging data with social and environmental exposure data.  

Results:  The resulting website and subsequent datasets will facilitate collaboration across families, clinicians, and researchers to better understand autism spectrum disorder. This national effort will grow as families become more aware of the resource. Once clinical information is linked with social and environmental data, the research community will be able to look at spatial relationships. Spatial patterns in the data can inform new research questions as well as identify areas for targeted recruitment and intervention strategies.

Conclusions:  This ground-breaking effort will be the first of its kind to generate self-reported patient information that is geographically linked to relevant social and environmental stressors and to further connect those datasets with research-grade data captured by NIH-funded laboratories. Long-term benefits of this effort include the building of collaborative relationships among affected families, clinicians, and scientists; the creation of nationally-based samples for future research; and increased awareness and understanding of autism spectrum disorders.