Obesity is a growing global concern, with the World Obesity Federation predicting that over half the world’s population could be overweight or obese by 2035. Despite available treatments such as lifestyle changes, surgery, and medications, their accessibility and effectiveness remain limited. This has intensified the search for early detection and prevention approaches.
To develop the polygenic risk score, the research team analyzed the genomes of over five million people, combining data from sources including the Genetic Investigation of ANthropometric Traits (GIANT) consortium and DNA-testing company 23andMe. The polygenic risk score aggregates the small effects of thousands of genetic variantsmany of which influence appetite via the brain into a single predictive score.
The study found that this polygenic risk score could explain 17% of the variation in body mass index (BMI), making it nearly twice as effective as previous genetic models in predicting obesity. Researchers validated the score using data from over 500,000 individuals, including longitudinal BMI data from participants in the long-running “Children of the 90s” cohort study.
“What makes the score so powerful is the consistency of associations between the genetic score and body mass index before the age of five and through to adulthood timing that starts well before other risk factors start to shape their weight later in childhood,” said Assistant Professor Roelof Smit, lead author from the University of Copenhagen.
The findings point to the potential of integrating genetic screening into early-life healthcare to better identify children at risk and tailor interventions accordingly.
Reference: Smit, R.A.J., Wade, K.H., Hui, Q. et al. Polygenic prediction of body mass index and obesity through the life course and across ancestries. Nat Med (2025). https://doi.org/10.1038/s41591-025-03827-z
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