Select your localized edition:

Close ×

More Ways to Connect

Discover one of our 28 local entrepreneurial communities »

Be the first to know as we launch in new countries and markets around the globe.

Interested in bringing MIT Technology Review to your local market?

MIT Technology ReviewMIT Technology Review - logo

 

Unsupported browser: Your browser does not meet modern web standards. See how it scores »

{ action.text }

On the steep slope of plummeting DNA sequencing costs rides the suggestion that whole-genome sequencing will soon be a part of the clinical experience for most patients. But researchers have now shown that deciphering the genetic code of most people would alert them to an increased risk for at least one of 24 common diseases, but fail to warn them about other diseases they will ultimately develop.

It’s not easy to predict the ultimate usefulness of medical genomics, in part because the field is so young and not widely adopted. The researchers estimated the potential of the technique to alter a patient’s lifestyle and medical treatment by studying disease rates from identical twins.

The result is not a big surprise, but experts disagree over the study’s implications. Some welcome a more skeptical look at the promise of the technology that deciphers the As, Ts, Gs, and Cs of a person’s genetic blueprint, and point out that it’s not easy to interpret that blueprint for medical information. Others complain that the new analysis only knocks down a straw man, since we already know that whole-genome sequencing has limits, and it hasn’t yet been applied to common diseases in a clinical setting.

Provoking these disparate reactions may be exactly the authors’ intentions.We became interested in trying to start a debate about the utility and potential benefit of genome-wide sequencing for personal medicine,” says Nicholas Roberts, a graduate student at Johns Hopkins University, and the first author on the study. Roberts says whole-genome sequencing has proved useful for patients with diseases that have a strong link to genetics, but less useful for those with many common and complex diseases, such as cancer or heart disease, that are caused by both genetics and environmental or lifestyle factors.

To see how the technology could affect the broader population, Roberts and coauthors looked to identical twins. The researchers had no actual genome-sequence data for the twins, but instead had data on the long-term incidences of cancer, heart disease, obesity, and other common conditions among the more than 50,000 pairs. Although identical twins share (nearly) identical genome sequences, they do not always develop or die from the same diseases. Other effects, such as diet, exercise, and the varying strength of the effects of particular genetic sequences, can all play a role in whether or not a genetic predisposition leads to an actual malady. How often a disease developed in a person whose twin had the same disease illustrates how well genome sequencing might predict an individual’s disease risk, the authors say.

16 comments. Share your thoughts »

Tagged: Biomedicine, DNA, whole-genome sequencing

Reprints and Permissions | Send feedback to the editor

From the Archives

Close

Introducing MIT Technology Review Insider.

Already a Magazine subscriber?

You're automatically an Insider. It's easy to activate or upgrade your account.

Activate Your Account

Become an Insider

It's the new way to subscribe. Get even more of the tech news, research, and discoveries you crave.

Sign Up

Learn More

Find out why MIT Technology Review Insider is for you and explore your options.

Show Me