Are you going to become obese? A genetic test can say


As obesity becomes epidemic among Americans, many may overestimate or underestimate their chances of accumulating the pounds.

But a new genetical "score" can take the guesswork out of it all, researchers say.

Using information on more than 2 million gene variants linked to body weight, scientists have created a so-called polygenic score that can help quantify a person's risk of obesity.

Researchers found that adults who scored in the top 10% weighed 30 pounds (13.6 kg) more, on average, than adults who scored at 10% lower. And they were 25 times more likely to be severely obese.

"We're not saying this is fate," said researcher Amit Khera of the Broad Institute and Massachusetts General Hospital in Boston. "The weight of any person results from an interaction between genes and environment."

But severe obesity, in particular, seems to have a strong genetic influence. This is not exactly a surprise. But Khera said a clearer understanding of the importance of genes may help lessen some of the stigma surrounding severe obesity.


So, does this mean that doctors will begin to present parents with the baby's obesity risk score?

Probably not soon. Ruth Loos, a researcher who was not involved in the study, was skeptical of the value of genetic scoring.

Weight and obesity are about 50% genetic and 50% lifestyle choices and environment, according to Loos, director of the Mount Sinai Genetics Program for Obesity and Related Metabolic Traits in New York.

The score used in this study, she said, is not responsible for all of this heritability. Even if that happened, that would be just part of a complex story.

"We can not use a single genetic score to accurately predict obesity," Loos said. "We would end up misleading a lot of people."

Algorithms developed

The scoring approach, described on April 18 in the journal Cell, was developed using data from 2.1 million genetic variants linked to body weight. Khera's team used newly developed computational algorithms to distill this genetic information into the scoring system.

They then applied it to people involved in four long-term health studies in the United Kingdom and the United States – three of young and middle-aged adults and one of children.

Overall, the researchers found that the higher a person's genetic score, the more he or she usually weighed. And the risk of serious obesity was particularly high among those who scored in the top 10%.

Among young US adults in this range, for example, nearly 16% became severely obese over the next 27 years. This compares with slightly more than 1% of young adults whose genetic risk scores were 10% lower.

Khera noted that the effects of a high-risk score began to become apparent at 3 years of age.

Some pitfalls

However, many people with the highest genetic risk scores did not become obese. In a large study of middle-aged adults in the United Kingdom, more than half were not obese, although few were of normal weight.

Loos said the predictive value of punctuation does not seem to be "better than family history."

Khera recognized some pitfalls of using punctuation to predict future weight: some people can become "defeatist" and see no sense in exercising and eating healthily.

"We want to use this information to improve people's health," Khera said. "So, there are a lot of questions we ask ourselves: when do we tell people? How would we address them? How could we track the effects that information has on their health outcomes?"

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Loos feared that a genetic risk rating would "unnecessarily frighten" some people and could also cause those with a low score to falsely believe they could eat what they wanted and ignore exercise.

She said the "real value" of studying the genetics of obesity is to better understand the underlying biology. Why are some people susceptible to weight gain while others are not?

Khera agreed and added that it will be important to find out why people with a high genetic score can avoid excessive weight gain.

Khera and her colleague Dr. Sekar Kathiresan are listed as co-inventors of a patent application for the predictor of genetic risk.

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