NIH Launches dbGaP- A Database of Whole Genome Association Studies
News Dec 15, 2006
The National Library of Medicine (NLM), part of the National Institutes of Health (NIH), has announced the introduction of dbGaP, a database designed to archive and distribute data from genome wide association (GWA) studies.
GWA studies can explore the association between specific genes (genotype information) and observable traits, such as blood pressure and weight, or the presence or absence of a disease or condition (phenotype information).
Connecting phenotype and genotype data can provide information about the genes that may be involved in a disease process or condition, which can be critical for understanding the disease and for developing new diagnostic methods and treatments.
dbGaP, the database of Genotype and Phenotype, will provide a central location for interested parties to see all study documentation and to view summaries of the measured variables in an organized and searchable web format.
The database will also provide pre-computed analyses of the level of statistical association between genes and selected phenotypes. Genotype data are obtained by using high-throughput genotyping arrays to test subjects' DNA for single nucleotide polymorphisms (SNPs), areas of the genome that have been found to vary among humans.
The initial release of dbGaP contains data on two studies:
• The Age-Related Eye Diseases Study (AREDS), a 600-subject, multicenter, case-controlled, prospective study of the clinical course of age-related macular degeneration and age-related cataracts that was supported by the National Eye Institute.
• The National Institute of Neurological Disorders and Stroke (NINDS) Parkinsonism Study, a case-controlled study that gathered DNA, cell line samples and detailed phenotypic data on 2,573 subjects. NEI and NINDS worked closely with NCBI in placing data from the two studies in dbGaP.
"The availability of AREDS data in this database, which can be accessed free of charge, signals a whole new way of conducting vision research," said Paul Sieving, M.D., Ph.D., director of NEI.
"Having this information widely available will help researchers better understand gene-based eye diseases, will likely speed development of effective therapies, and, thereby, will prove to be a worthwhile investment for the taxpayers who funded this important medical research."
Danilo Tagle, Ph.D., a program director for NINDS's neurogenetics program, commented: "The launch of dbGaP addresses the critical need for sharing of genotype and phenotype information coming from genome wide association studies. The large collection of DNA samples and well-described clinical information from these studies, and subsequent genotyping analyses, are strategic investments by the institute that will surely pay huge returns. They will continue to pay dividends as other groups access dbGaP to do meta-analyses of GWA datasets."
"The dbGaP project marks a new milestone in data sharing," said NLM Director Donald A. B. Lindberg, M.D. "Researchers, students and the public will have access to a level of study detail that was not previously available and to genotype-phenotype associations that should provide a wealth of hypothesis-generating leads," he said.
"These data will be linked to related literature in PubMed and molecular data in other NCBI databases, thereby enhancing the research process."
Data from the Genetic Association Information Network (GAIN), a public-private partnership, also will be added to dbGaP. The project is being led by the Foundation for NIH (FNIH), with participation and/or funding from Pfizer, Affymetrix, Perlegen Sciences, Abbott, the Broad Institute of MIT and Harvard, and NIH. Private donors have contributed $26 million to help fund GAIN, which provides for genotyping DNA samples from participants in clinical studies that were already conducted.
GlaxoSmithKline plc (GSK) has launched a five-year, $67 million collaboration with the San Francisco and Berkeley campuses of the University of California to build a state-of-the-art laboratory. The goal is to use CRISPR technologies to explore how genes cause disease and to rapidly accelerate the discovery of new drugs.