Kaiser, UC-San Francisco Bolster NIH Database With Genetic Data

February 27, 2014 in News

On Wednesday, Kaiser Permanente and the University of California-San Francisco announced that they have provided 55 billion bits of genetic information to an NIH database used by researchers worldwide, the San Francisco Business Times‘ “Bay Area BizTalk” reports.


According to Kaiser and UCSF, the initiative to input the new data into NIH’s database of genotypes and phenotypes used a combined $24.9 million in funding from several organizations, including the:

  • National Institute on Aging;
  • National Institute of Mental Health; and
  • Office of the NIH Director.

Details of Data

The data are a segment of a more comprehensive database under Kaiser’s Research Program on Genes, Environment and Health, which is compiled of voluntarily submitted data from more than 430,000 adult members of the Kaiser Foundation Health Plan. About 200,000 of those individuals also submitted blood and saliva samples for genetic research.

Researchers at the UCSF Institute for Human Genetics scanned genetic markers in the genomes of 74,000 of those Kaiser members and combined the genetic data with members’:

  • Electronic health records;
  • Health habit surveys; and
  • Other patient-specific information.

The data will be made available to researchers around the world through NIH’s database of Genotypes and Phenotypes (Rauber, “Bay Area BizTalk,” San Francisco Business Times, 2/26).


In a release, NIH Director Francis Collins said the new initiative “offers the opportunity to identify potential genetic risks and influences on a broad range of health conditions, particularly those related to aging.”

In addition, Neil Risch, director of the UCSF Institute for Human Genetics, said, “Collecting large amounts of health data from people — and processing it — is labor intensive and expensive.”

He said, “With this data set, no one has to collect clinical information, take bio samples, safeguard and store them, or conduct genome-wide genotyping of their DNA,” adding, “They can simply sit at a computer, ask questions of the data and extract information” (NIH release, 2/26).

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