When obesity becomes an epidemic among Americans, many might overstate or underestimate their odds of accumulating kilograms.
But a new genetic "score" could solve all the problems, according to the researchers.
Using information on more than 2 million gene variants related to body weight, scientists have created what is called a polygenic score that could help quantify the risk of obesity from a body. nobody.
The investigators found that adults with the highest 10% score on average weighed 30 pounds (13.6 kg) more than those with the lowest score (10%). And they were 25 times more likely to be seriously obese.
"We are not saying that it's a fate," said Dr. Amit Khera, a researcher at Broad Institute and Massachusetts General Hospital in Boston. "The weight of any person results from an interaction of genes and the environment."
But severe obesity, in particular, seems to have a strong genetic influence. This is not really a surprise. But Khera said that a better understanding of the importance of genes could help alleviate some of the stigma surrounding severe obesity.
Does this mean that doctors will start presenting parents with their baby's obesity risk score?
Probably not soon. Ruth Loos, a researcher who did not participate in the study, was skeptical about the value of the genetic score.
Weight and obesity account for about 50% of genetic choices and 50% of lifestyle and the environment, according to Loos, director of the Obesity Genetics and Metabolic Related Disorders Program at Mount Sinai, New York.
The score used in this study, she said, does not account for all this heritability. Even if it were, it would only be part of a complex story.
"We can not use a single genetic score to accurately predict obesity," Loos said. "We would end up misinforming a lot of people."
The method of notation described on April 18 in the newspaper Cell, was developed from data on 2.1 million genetic variants related to body weight. The Khera team used newly developed computer algorithms to distil this genetic information into the scoring system.
Then they applied it to people involved in four long-term health studies in the United Kingdom and the United States – three young and middle-aged adults and one child.
Overall, the researchers found that the higher a person's genetic scores, the more they generally weighed. And the risk of severe obesity was particularly high among those who ranked among the top 10%.
Among young American adults in this bracket, for example, nearly 16% have become severely obese over the next 27 years. This compared to just over 1% of young adults whose genetic risk scores were in the bottom 10%.
Khera noted that the effects of a high risk score began to appear as early as the age of 3 years.
However, many people with even the highest genetic risk scores did not become obese. In a large study of middle-aged British adults, more than half were not obese, although few had a normal weight.
Loos said the predictive value of the score did not seem "even better than the family history".
Khera acknowledged that using a score to predict future weight was a trap: some people could become "defeatists" and not see the value of exercising and eating healthy.
"We would like to use this information to improve the health of the population," said Khera. "So we ask many questions: when will we tell people, how would we tell them, how could we track the effects of this information on their health outcomes?"
& # 39; Actual value & # 39;
Loos feared that a genetic risk score "unnecessarily scares off" some people and could also cause those with a low score to erroneously believe that they can eat what they want and avoid the "bad news" they have. exercise.
She said that the "real value" of studying the genetics of obesity is to better understand the underlying biology. Why are some people likely to gain weight while others are not?
Khera agreed and added that it would be important to understand why people with a very high genetic score manage to avoid excessive weight gain.
Khera and his colleague, Dr. Sekar Kathiresan, are on the list of co-inventors of a patent application for the genetic risk predictor.