New Genetic Test Predicts Obesity in Childhood

Current treatment options such as lifestyle changes, surgery, and medication are not universally effective or accessible. Moreover, identifying individuals at high risk early enough to prevent the onset of obesity remains a major challenge. Subtle variations in our genomes play a role in increasing susceptibility to obesity, especially through mechanisms like appetite regulation in the brain. Early identification of genetic risk before physical symptoms develop could help enable preventive strategies. Now, a new genetic approach offers the ability to identify children at high risk for obesity well before their weight is affected, potentially opening the door to earlier and more effective interventions.

Researchers from the University of Copenhagen (Copenhagen, Denmark) and the University of Bristol (Bristol, UK) have developed a new polygenic score (PGS) to predict obesity risk. The PGS was created using the genetic data of over five million people, the largest and most diverse dataset of its kind. The score aggregates the effects of thousands of individual genetic variants linked to obesity and calculates an overall risk value for each person. The researchers tested the PGS using data from more than 500,000 individuals and explored its predictive power through the lens of both physical traits and genetic profiles. They also examined how heart health indicators like BMI, sex, and hypertension influence risk. The work draws on contributions from over 600 scientists across 500 institutions globally, as part of a broader effort to understand anthropometric traits such as BMI and height.

The PGS was found to be twice as effective as previous best-in-class tests for predicting obesity risk. It was also particularly effective in identifying genetic risk in early childhood, even before the age of five. The findings, published in Nature Medicine, show that individuals with higher genetic risk scores responded more strongly to lifestyle-based weight loss interventions like diet and exercise but they also tended to regain weight more quickly once those interventions stopped. However, a key limitation remains: the PGS was significantly more accurate in people of European ancestry than those of African ancestry, despite the use of a more globally representative genetic dataset. Moving forward, the researchers aim to refine the model to improve its predictive power across more diverse populations and continue exploring its use in early prevention strategies.

"This new polygenic score is a dramatic improvement in predictive power and a leap forward in the genetic prediction of obesity risk, which brings us much closer to clinically useful genetic testing," said Professor Ruth Loos, senior author of the study.