Last updated: February 26, 2012
Researchers Can Apply Now for Access to GAIN Data
Researchers Can Apply Now for Access to GAIN Data
June 2007
The Genetic Association Information Network (GAIN) is now accepting applications from researchers who want access to the rich trove of data that its genome-wide association studies of common diseases will begin generating within the next few months.
GAIN is a public-private partnership formed to support efforts to find genetic factors influencing risks for common, complex conditions. The partnership, which was launched by the Foundation for the National Institutes of Health (FNIH) in February 2006, currently involves the National Institutes of Health (NIH), Pfizer, Inc., of New York City, Affymetrix, Inc., of Santa Clara, Calif., and the FNIH, as well as Perlegen Sciences, Inc., of Mountain View, Calif., Abbott, of Abbott Park, Ill., and the Broad Institute of the Massachusetts Institute of Technology and Harvard University in Cambridge, Mass.
After a competitive, peer-reviewed process, GAIN announced in October 2006 the selection of six studies for genome-wide association (GWA) genotyping: attention deficit hyperactivity disorder (ADHD) [ncbi.nlm.nih.gov], psoriasis, schizophrenia, bipolar disorder, depression and type 1 diabetes.
Data from the ADHD study are expected to be deposited in the GAIN database by the end of June. Data from the other five GAIN studies will be rolled out over the next six months as they become available. The GAIN database resides within the database of Genotypes and Phenotypes (dbGaP), which includes results from numerous GWA studies in addition to the GAIN data. The National Library of Medicine's National Center for Biotechnology Information operates dbGaP.
"We are optimistic that making these data readily available to qualified researchers will accelerate efforts to understand the genetic risk factors for these common and serious illnesses," said Teri Manolio, M.D., Ph.D., Senior Advisor to the Director for Population Genomics at the National Human Genome Research Institute, which is leading the NIH effort for GAIN. "We believe this research will open the door to finding more effective and individualized strategies for diagnosing, treating and, ultimately, preventing these disorders."
For researchers who want to view GAIN data , dbGaP offers two levels of access. The first is open-access, which means the data are available without restriction, and the second is controlled-access, which requires preauthorization for the individual researcher seeking to view. The open-access section allows users to view study documents, such as protocols and summaries of genotype and phenotype data. The controlled-access portion of the database allows approved researchers to download individual-level genotype and phenotype data from which the study participants? personal identifiers, such as names, have been removed.
Although personally identifying information is removed for those who volunteered to participate in GWA studies, concern remains that it may someday be possible to identify someone based on their genetic profile; only researchers agreeing not to identify individuals in the database will be given access to the data.
Researchers may request access to GAIN's individual-level data by going to dbGaP - Genotype and Phenotype [view.ncbi.nlm.nih.gov]. The principal investigator and the signing official at each researcher's institution must co-sign a request for data access, which contains a data user certification. To complete this step, both the principal investigator and signing official must have current accounts or apply for accounts with NIH eRA Commons, which is the online system used to apply for NIH grants. The request will be reviewed by an NIH Data Access Committee at the appropriate NIH Institute or Center. On average, approval of these requests is anticipated to take 2 to 3 weeks.
For more detailed information on the data request process, go to Genotype and Phenotype Data Now Available from the NCBI dbGaP Database [dbgap.ncbi.nlm.nih.gov] .
To view the PDF on this page, you will need Adobe Acrobat Reader.
Last Reviewed: February 26, 2012