New genetic test can identify children who are at risk of obesity well before it occurs

More than half the world’s population may be at risk of overweight or obesity by 2035, according to global estimates. Yet current treatments such as surgery, medication, or lifestyle changes do not work equally for everyone and remain out of reach for many.

A new approach focuses instead on prevention. Scientists have created a genetic test called a polygenic risk score (PGS) that can predict the risk of future obesity in children as young as age five. The test uses genetic data to flag those most likely to develop obesity in adulthood.

Obesity and genetic testing

The PGS is based on genetic data from over five million individuals. It can identify children at high genetic risk for adult obesity well before lifestyle or environment take over.

“What makes the score so powerful is its ability to predict, before the age of five, whether a child is likely to develop obesity in adulthood, well before other risk factors start to shape their weight later in childhood,” said assistant professor Roelof Smit from the University of Copenhagen.

Smit added that intervening at this point could have a huge impact.

This insight opens doors for targeted prevention during early development. Childhood interventions are more likely to change long-term health outcomes than adult efforts.

This test comes from the GIANT Consortium, a worldwide network of over 600 researchers. They partnered with institutions and 23andMe, using the largest and most diverse genetic database to date.

The team trained their model on data from millions of people and validated it across over half a million individuals. They used advanced statistical methods to improve prediction accuracy while also addressing genetic diversity challenges.

Improved accuracy over older tests

The new PGS works like a calculator. It adds the small effects of thousands of obesity-related genetic variants to predict someone’s future risk. These include variants that act on the brain, influencing appetite and food preferences.

This new version was twice as accurate as older models at predicting who will develop obesity. It performed well across multiple global datasets.

“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 from the Faculty of Health and Medical Sciences.

Lifestyle still matters for obesity

Researchers also examined how individuals with a higher genetic risk for obesity respond to common weight loss strategies, such as changes in diet or increased physical activity.

Their analysis showed that those with higher polygenic risk scores tended to lose more weight during structured interventions. These interventions included things like meal planning, exercise routines, and lifestyle coaching.

However, this success often did not last. When the support or structured program ended, these individuals were more likely to regain the weight they had lost.

Genes are only part of the story

This pattern highlights an important point: while genetic factors may affect how someone initially responds to weight loss efforts, they do not fully determine long-term outcomes.

In other words, genes are only part of the picture. Daily habits, motivation, access to healthy food, and social support all strongly affect whether weight stays off or comes back.

A person’s environment can either reduce the impact of genetic risk or make it worse. So, genetics shape tendencies, but choices and surroundings still matter deeply.

Why genetic obesity scores matter

One limitation remains: performance differences across ancestry groups. The PGS works better for people of European descent than for those with African ancestry.

Although the model includes more diverse data than earlier efforts, this gap reflects broader issues in genomic research. Most global genetic studies still rely heavily on European datasets.

To address this, the authors used transfer learning techniques and ancestry-aware statistical tools. While this improved the score’s reach, results still vary across populations.

Using obesity risk in real care

This research provides a powerful tool for public health and pediatric care. If used ethically and responsibly, early screening could allow healthcare systems to offer guidance before obesity develops.

To support long-term benefits, the study encourages inclusive datasets and equity-focused model development. It also calls for integration with environmental and behavioral data to enhance real-world impact.

This genetic score will not replace personal choices or medical advice. But it can serve as an early warning system, giving at-risk children a better chance at lifelong health.

The study is published in the journal Nature Medicine.

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