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Predicting risk of stroke from one's genetic blueprint
Date:2/25/2009

l was able to predict an individual's risk of cardioembolic stroke with an accuracy of 86 percent. Ultimately, Ramoni envisions doctors using it as a diagnostic tool: a patient's genetic information would simply be entered into the model, which would correlate and analyze the data and output an overall probability of stroke, based on the stroke-related SNPs in the patient's genome. "It sounds like magic," says Ramoni. "But it's just a piece of technology. It gives hope that we will be able to predict early on whether someone is at risk of getting stroke, and allow you to convince them to make life changes."

"The next step is to get more SNPs," Ramoni adds. "These analyses looked at only 1,313 out of 3.3 million known SNPs. Even a million SNPs would cover the vast majority of the genome. We would get much better predictions."

Ramoni also says that by identifying all the genetic variants that modulate the risk of stroke, it could provide insight into its mechanisms and provide targets for future drugs. He is currently refining the model and believes that this technology could be used to predict inherited risk of many other conditions.


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Contact: Keri Stedman
keri.stedman@childrens.harvard.edu
617-919-3110
Children's Hospital Boston
Source:Eurekalert

Page: 1 2

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