美国国家公共电台 NPR How Helpful Would A Genetic Test For Obesity Risk Be?（在线收听）

RACHEL MARTIN, HOST:

Now, if you're worried about developing heart disease, you could take a blood test to see if you have high cholesterol. But there hasn't been a test to check your risk for obesity. Researchers have now developed an experimental genetic scan to identify people likely to become severely overweight. NPR science correspondent Richard Harris reports.

RICHARD HARRIS, BYLINE: The current obesity epidemic shows that our environments and habits are driving a lot of obesity. But genes play an important role, as well - and not just a few genes, apparently a whole bunch of them. Each makes a tiny contribution. But collectively, they can influence everything from appetite control to metabolism.

Sekar Kathiresan, a cardiologist and geneticist at the Broad Institute at Harvard and MIT, set out to see whether his team could find a bunch of these genetic variants and add up their effects to create a test to predict who is at highest risk of obesity.

SEKAR KATHIRESAN: This information, this genetics could explain why somebody's so big, why they have so much trouble keeping their weight down.

HARRIS: Kathiresan and his colleagues identified more than 2 million DNA variations linked to obesity. He figures most of them are irrelevant. But his hunch is - hidden somewhere in there are a few thousand meaningful variants. And his risk score based on the 2 million variants does identify people who are most at risk of becoming severely obese.

KATHIRESAN: The impact of the genetics starts very early in life, in the preschool years, around the age of 3.

HARRIS: That means prevention efforts are more likely to succeed if they start in childhood. Kathiresan has a more philosophical takeaway from his work as well.

KATHIRESAN: This work hopefully will destigmatize obesity and make it very similar to every other disease, which is a combination of both lifestyle and genetics.

HARRIS: The findings were recently reported in the journal Cell. A lot of the broad conclusions aren't new. Scientists already knew that obesity has a strong genetic component, and other studies show that obese children are at high risk for becoming obese adults. Cecile Janssens, an epidemiologist at Emory University, doesn't think much of this strategy of adding up the minuscule risks from millions of genetic variants to come up with a cumulative risk score.

CECILE JANSSENS: We do not know for sure whether all these variants really matter.

HARRIS: So what is the value of doing something like this then?

JANSSENS: I have no clue. I have no idea.

HARRIS: This type of analysis doesn't reveal anything about the individual genes that are contributing to obesity, which means you can't use it to understand the underlying biology. If obesity were a rare disease, a test could be useful to identify people at elevated risk. But since it affects 40% of Americans, Janssens says really prevention efforts should include everybody.

JANSSENS: It is not really answering a very relevant question from the biological perspective and not really answering a very relevant question from a clinical perspective.

HARRIS: Janssens is among a group of scientists informally rebelling against the gene-centric way of looking at disease. It's frustrating for them to see so much effort poured into this kind of genetics work since the results often don't lead to meaningful actions. Theresa Marteau, who directs the Behaviour and Health Research Unit at the University of Cambridge, says scientists had hoped that using genetic information to inform people that they're at high risk of a disease would make a difference - but no.

THERESA MARTEAU: This kind of personalized risk information has little if no impact on people's actual behavior.

HARRIS: Ewan Birney, who heads the European Bioinformatics Institute, says the critics have a point.

EWAN BIRNEY: One needs to do more than just be able to show a strong statistical association. One really needs to be able to show that you can use that to do an intervention.

HARRIS: There are other cases where you can do that, he says - for example, by using this kind of risk score to identify people who don't know that they could benefit from cholesterol-lowering drugs. So this strategy has its place, he says, along with its limitations.

Richard Harris, NPR News.