Using genetic data from more than five million people, scientists have developed a new polygenic risk score that can predict the risk of adult obesity beginning in early childhood.
The findings, published in Nature Medicine, reveal that this genetic tool explains up to 17.6% of the variation in body mass index (BMI)—a significant leap from earlier models—and could inform early intervention strategies during a child’s critical growth years.
Early genetic patterns track with lifelong weight gain
Obesity is a complex condition influenced by both genes and environment. The World Obesity Federation projects that over half the global population will be overweight or obese by 2035, underscoring the need for effective prevention. Traditional approaches like surgery or medication are limited by access and effectiveness. This study suggests that genetics may offer a reliable, early-warning signal.
The new polygenic risk score (PGS)—developed by an international team from the Universities of Copenhagen and Bristol—was based on subtle differences in DNA across millions of individuals. Researchers found the score was not only strongly linked to adult obesity, but also began showing meaningful associations with BMI before the age of five.
“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,” said Assistant Professor Roelof Smit, the paper’s lead author.
How well does the polygenic score perform?
- The score explains up to 17.6% of BMI variation in people of European ancestry.
- In children from the ALSPAC study, high genetic scores predicted faster BMI gain beginning at age 2.5.
- Adding the PGS to birth predictors nearly doubled the accuracy of forecasting BMI at age 8 (from 11% to 21%).
- The PGS was twice as accurate as the previous best method in predicting obesity risk.
Real-world benefits—and limits
While the PGS could help identify children at risk and guide early lifestyle changes, researchers caution against deterministic thinking. Genetics influence risk, but they don’t seal fate. Interestingly, people with a high genetic risk were more likely to benefit from intensive weight-loss interventions—though they also tended to regain weight more quickly once the programs ended.
“Obesity is a major public health issue… and we believe that some of these [risk factors] originate in childhood,” said Dr. Kaitlin Wade, co-author and epidemiologist at the University of Bristol.
Gaps in performance for diverse populations
One key limitation: the PGS worked far better for people of European descent than for those of African ancestry. For example, it explained just 2.2% of BMI variation in a rural Ugandan cohort. The researchers stress the need to improve genetic prediction tools across ancestries to avoid widening health disparities.
This study adds depth to our understanding of when—and for whom—obesity risk begins to take shape. By shining a light on the earliest roots of weight gain, it may help reframe obesity prevention from a reactive to a proactive science.
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