A new study that describes a newly developed genetic test that can identify newborns at the highest risk of developing severe obesity. The study published in the journal Cell demonstrates that a genetic score based on more than 2 million individual variations in a person's genetic code, is highly predictive of developing obesity and its severe metabolic complications. The authors used previously published data about those variations to develop the Genome-wide Polygenic Score (GPS).

Although each of the variations has only a slight effect, by analyzing them together, the obesity GPS has great predictive power. Middle-aged adults scoring in the top 10 percent of this genetic test have more than a 25-fold greater likelihood of having severe obesity, characterized by a body mass index (BMI) of more than 40 kg/m², than those in the bottom 10 percent. The two groups were separated by an average weight difference of nearly 30 pounds.

Results from the study showed that although a high GPS did not guarantee people would develop obesity and a low score did not rule it out, the score was highly predictive. Among a group of more than 3,700 adolescents and young adults without severe obesity followed for an average of 27 years, the authors found that those who had a high score were 12 times more likely to develop severe obesity than those who scored in the lowest 10 percent.

"It is well-known that body fat in early childhood is not a reliable predictor of adult obesity," the senior author said. "Confirming this observation, we found that the GPS did not correlate well with body fat or body weight in infancy or early childhood, but that it was a strong predictor of obesity later in childhood and adolescence. A GPS determined shortly after birth could therefore be used to identify babies at the highest risk of developing obesity, allowing for early prevention and treatment strategies focused on those individuals."

They also noted that describing a person's genetic make-up using information gathered from across the genome can have important advantages over characterization of single genes or a small number of genes. "In complex diseases like obesity, someone's genetic predisposition most often comes from the sum of a large number of small effects. This same approach should be helpful in more accurately identifying different types of obesity, allowing for better prediction of which treatments will be most effective in individual patients," the senior author said.

The obesity GPS research included more than 400,000 participants. The authors developed the GPS using data derived from more than 100,000 participants in the U.K. Biobank, which enrolled participants 40 to 69 years of age from across the United Kingdom and allowed linkage of measurements such as BMI to extensive genetic data. The authors used those results to optimize the score, which they then validated in several additional populations of adults, adolescents, newborns, and those who had undergone bariatric surgery.

The highly predictive nature of the obesity GPS underscores the important role of genetics in predisposing many people to developing obesity," said another author and added that "we have long known that obesity has a strong genetic basis, but we have identified the relevant genetics in only a small portion of the population with this disease. This study identifies specific genetic contributors in nearly a third of people with severe obesity. In addition to its clinical predictive value, the GPS is likely to provide new insights into the biology of obesity and facilitate development of more effective therapies for this complex disorder."

https://www.cell.com/cell/fulltext/S0092-8674(19)30290-9

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