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A newly developed tool can assess a person’s risk for becoming obese based on genetic variants at more than 2 million loci in the genome, researchers report today (April 18) in Cell.
“We’ve had evidence for a long time that obesity is affected by genetics. What this really adds is the ability to distill the risk from the genome into a simple number for each person and look at that number in relation to the rest of the population,” study coauthor Sekar Kathiresan, a cardiologist at Massachusetts General Hospital, tells WBUR.
Kathiresan’s team developed an algorithm linking body mass index (BMI) to 2.1 million genetic variants, and validated its accuracy in predicting BMI from genetics using a dataset of 100,000 people. The researchers then applied the risk assessment to more than 300,000 people, finding those who scored on the high end were...
Among the youngest participants in the study, the trend began to emerge as early as age three, when children with high risk scores began to be heavier.
The authors say that knowing people carry such a risk could be useful for preventive interventions, such as weight control drugs, according to Science News.
But there is also a hazard that the score will encourage fatalism. For example, another study found that if people learn they have a genetic propensity toward becoming obese, they eat more, Mark Goodarzi of Cedars Sinai Medical Center in Los Angeles tells Science News. “I think they figured, ‘I’m doomed. I’m going to be obese anyway. Why fight it?’”
The authors acknowledge that a high risk score is not a guarantee of being obese, as their data show. “Despite the strength of these associations, polygenic susceptibility to obesity is not deterministic,” the write in their report. “Among those in the top decile of the GPS [genome-wide polygenic score], 83% were overweight or obese, but 17% had a BMI within the normal range, and 0.2% were underweight.”
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