New Delhi: Researchers have developed a new genetic test that can predict a child’s risk of developing obesity by the age of five. Known as a polygenic risk score (PGS), the test could help identify children with a high genetic risk of obesity and allow for early lifestyle interventions to prevent weight-related health problems later in life.
The study, published in Nature Medicine, involved an international team of more than 600 scientists from 500 institutions worldwide. Using genetic data from over five million people, the researchers created a PGS that combines the effects of numerous genetic variants to generate an overall risk score for obesity.
“What makes this score so powerful is its ability to predict whether a child is likely to become obese as an adult—even before other risk factors, like diet or physical activity, come into play,” said Roelof Smit, lead author and Assistant Professor at the NNF Center for Basic Metabolic Research at the University of Copenhagen. “Intervening at this early stage can make a huge difference.”
Professor Ruth Loos, also from the University of Copenhagen, said the new score offers a major improvement in predicting obesity risk. “It’s a big step forward in making genetic testing more clinically useful,” she noted.
According to the World Obesity Federation, more than half the global population is expected to be overweight or obese by 2035. Obesity is linked to serious health conditions such as heart disease, diabetes, high blood pressure, and cancer.
The study also examined how a person’s genetic risk of obesity affects their response to lifestyle changes, such as diet and exercise. It found that individuals with higher genetic risk tended to respond better to interventions—but were also more likely to regain weight after the interventions ended.
Despite being developed from a globally diverse genetic dataset, the PGS was more accurate for individuals with European ancestry than for those with African ancestry. Researchers note this as a key area for further improvement to ensure the tool is effective across all populations.