A team led by Johns Hopkins Kimmel Cancer Center's Nicholas Roberts discusses "the predictive capacity of personal genome sequencing" in a paper published online in advance in Science Translational Medicine this week. As our sister publication GenomeWeb Daily News reports, Roberts and his colleagues "used data generated from previously published studies on twins to show that while many individuals could be alerted to a predisposition to at least one disease, for the majority, whole-genome sequencing would be uninformative for most diseases, and the risk of developing these diseases would be similar to that of the general population."
Several mainstream news organizations also reported on the team's findings.
Study co-author Bert Vogelstein tells The New York Times that his group's findings "[put] limits on what people might expect with this sort of testing." Harvard Medical School's David Altshuler, who was not a part of the research, tells the Times that, overall, the study's main point rings true. "Even if you know everything about genetics, prediction will remain probabilistic and not deterministic," Altshuler says.
Bloomberg Businessweek spoke with the Scripps Research Institute's Eric Topol, who also was not a part of the research. Topol says it's not yet time to "abandon the importance of the DNA sequence."
ABC News concludes that "whole-genome sequencing is not the magic bullet for prevention — at least not yet," and Scientific American notes that while many companies "advertise a laundry list of disease risks associated with your genes … your genome is unlikely to reveal whether or not you will actually get one of these conditions."
The study had people talking on Twitter, too.
In response to a tweet from Kendall Morgan, communications director at the Duke Institute for Genome Sciences & Policy, David Pendleton King did not mince his words. "In other news, the sky is blue, water is wet," King tweeted. "Genetic info can be very helpful [without] answering every question, or being 100 [percent] predictive. Integrate it with other data!" he later added.
The Institute for Systems Biology's Leroy Hood tweeted: "It's correct from their viewpoint. But they miss the very important aspect of 'actionable gene variants.'"