Increasing the Use of the National Database for Autism Research (NDAR)
NAMHC Concept Clearance •
Michelle Freund, Ph.D.
Chief, Molecular Biotechnology and Neurotechnology Programs
Chair, NDAR Data Access Committee
Division of Neuroscience and Basic Behavioral Science (DNBBS)
The purpose of this initiative is to encourage researchers to use the data in the National Database for Autism Research (NDAR) to: (1) reproduce and extend published data; (2) validate hypotheses generated during experiments performed on small samples; and, (3) generate new findings and hypotheses. To stimulate utilization and mining of the increasingly diverse data available in NDAR, NIH is considering issuing a Challenge, in which a small monetary prize will be offered to a winning proposal that uses NDAR data to make progress towards discovering relationships among NDAR data that are novel or unexpected, or confirming hypothesized, but as yet unproven concepts in the field of autism spectrum disorder (ASD) research. Information about Challenges sponsored by the U.S. Government can be found at http://challenge.gov.
NDAR serves as a secure repository for research data related to ASD. The goal of the data repository is to accelerate scientific discovery in ASD through data sharing, data harmonization, and the reporting of research results. NDAR contains ASD-related data from NIH funded researchers and facilitates access to three additional autism data repositories: the Interactive Autism Network, the Autism Tissue Program, and the Autism Genetic Resource Exchange.
Created in 2006, with the first data submissions occurring 2008, NDAR has since expanded to contain more than 170,000 data records from over 25,000 research participants, from over 100 different sources. The data can be classified into four main categories: demographics, clinical assessments, neuroimaging, and genomics. The ASD research community has embraced the use of NDAR global unique identifier (GUID) software, which allows data from individuals who participate in multiple studies at multiple sites to be aggregated without revealing personally identifiable information about that individual. The community has also helped NDAR create data dictionaries that define the lexicon for all of the reported experiments. These data definitions help the community standardize the way that data is collected and reported.
Now containing sufficiently diverse and large amounts of data, NDAR is poised to allow researchers to make significant progress in ASD research, leading to the definition of biologically meaningful sub-groups among individuals with ASD or yielding insights into gene-brain-behavior relationships.