Study toAnalyze individual's genome for risk of dozens of diseases, potential responses to treatment

>> Sunday, May 16, 2010


For the first time, researchers have used a healthy person's complete genome sequence to predict his risk for dozens of diseases and how he will respond to several common medications. The risk analysis, from the Stanford University School of Medicine, also incorporates more-traditional information such as a patient's age and gender and other clinical measurements. The resulting, easy-to-use, cumulative risk report will likely catapult the use of such data out of the lab and into the waiting room of average physicians within the next decade, say the scientists.

"When combined with other sources of information, genomics has the power to predict the diseases a person is most likely to develop and how he or she might respond to certain medicines," said Jeremy Berg, PhD, director of the NIH's National Institute of General Medical Sciences, which funded a portion of the work. "This work provides a glimpse of how genomics can play a role in personalizing the medical care of individual patients."

"We're at the dawn of a new age in genomics," said Stephen Quake, PhD, who is the Lee Otterson Professor of Bioengineering. "Information like this will enable doctors to deliver personalized health care like never before. Patients at risk for certain diseases will be able to receive closer monitoring and more frequent testing, while those who are at lower risk will be spared unnecessary tests. This will have important economic benefits as well, because it improves the efficiency of medicine."

"Patients, doctors and geneticists are about to hit by a tsunami of genome sequence data. The experience with Steve Quake's genome shows we need to start thinking — hard and soon — about how we can deal with that information," said Greely

Of course, a person's environment — in the form of choices he or she makes about diet, exercise and habits like smoking and drinking — can also powerfully affect disease risk. But if clinicians know that a patient has a higher-than-normal risk for a certain disease, they may recommend certain lifestyle changes more strongly.


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