The data, from one of the nation’s largest and most diverse genomics projects — Genetic Epidemiology Research on Aging (GERA) — have just been made available to qualified researchers through the database of Genotypes and Phenotypes (dbGaP), an online genetics database of the National Institutes of Health.
The GERA cohort — average age 63 — was developed collaboratively by Kaiser Permanente and the University of California, San Francisco (UCSF). The addition of the data to dbGaP was made possible with $24.9 million in support from the National Institute on Aging (NIA) and the National Institute of Mental Health, and the Office of the Director, all at NIH. Catherine Schaefer, Ph.D., of Kaiser Permanente Northern California and Neil Risch, Ph.D., of UCSF are co-principal investigators for GERA.
“Data from this immense and ethnically diverse population will be a tremendous resource for science,” said NIH Director Francis S. Collins, M.D., Ph.D. “It offers the opportunity to identify potential genetic risks and influences on a broad range of health conditions, particularly those related to aging.”
The GERA cohort is part of the Research Program on Genes, Environment, and Health (RPGEH), which includes more than 430,000 adult members of the Kaiser Permanente Northern California system. Data from this larger cohort include electronic medical records, behavioral and demographic information from surveys, and saliva samples from 200,000 participants obtained with informed consent for genomic and other analyses. The RPGEH database was made possible largely through early support from the Robert Wood Johnson Foundation to accelerate such health research.
“The GERA cohort has the largest number of people — of any age — with data in dbGaP,” said NIA Director Richard J. Hodes, M.D. “Federal funds were used to develop new approaches to genomics for this project and I’m pleased that the data are now ready in dbGaP for researchers’ use. I look forward to new insights that such a unique resource might offer for better health with age.”
The genetic information in the GERA cohort translates into more than 55 billion bits of genetic data. Using newly developed techniques, the researchers conducted genome-wide scans to rapidly identify single nucleotide polymorphisms (SNPs) in the genomes of the people in the GERA cohort. These data will form the basis of genome-wide association studies (GWAS) that can look at hundreds of thousands to millions of SNPs at the same time. The RPGEH then combined the genetic data with information derived from Kaiser Permanente’s comprehensive longitudinal electronic medical records, as well as extensive survey data on participants’ health habits and backgrounds, providing researchers with an unparalleled research resource.
In addition to diseases and conditions traditionally associated with aging, such as cardiovascular disease, cancer and osteoarthritis, researchers can explore the potential genetic underpinnings of a variety of diseases that affect people in adulthood, including depression, insomnia, diabetes, certain eye diseases and many others representing a variety of disease domains. Researchers will also be able to use the database to confirm or disprove other studies that use data from relatively small numbers of people, as well as to increase the size and power of their samples by adding participants from GERA to meta-analyses. The large cohort will also serve as a reference source of controls that researchers can compare to individuals with different conditions that they have studied.
“An exciting aspect of this dataset is that it will be updated and refreshed,” noted Winifred Rossi, deputy director of NIA’s Division of Geriatrics and Clinical Gerontology and program officer for the project. “As information is added to the Kaiser-UCSF database, the dbGaP database will also be updated.”
dbGaP was developed and is managed by the National Center for Biotechnology Information, a division of the National Library of Medicine at NIH. Investigators who are interested in applying for access to this database should follow the procedures on the dbGaP website.