July 29, 2025, 11:28 am | Read time: 5 minutes
A new mega-study with data from over five million people worldwide shows: A genetic test–a so-called polygenic risk score–can provide surprisingly early indications of an increased risk of obesity. A connection is visible even in toddlers. However, the test does not work equally well across all population groups.
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What is the study about?
Obesity often begins in childhood–and usually persists into adulthood. The researchers wanted to find out if a genetic test can identify early on who has a particularly high risk of obesity, meaning severe overweight.1 To do this, they developed a so-called polygenic risk score, or PGS for short.
What is a polygenic risk score?
A polygenic score (PGS) combines many small genetic differences in the genome into a single value. On their own, these differences have little impact–but together they show how high the hereditary risk is for a particular trait, such as obesity.2
What exactly was done?
The team analyzed genetic data from more than 5.1 million people worldwide. Participants from various backgrounds were considered: European, African, East Asian, South Asian, and American. From this data, the scientists developed both population-specific and overarching, multiethnic risk scores. These new scores were then tested: How well do they predict body mass index (BMI) in different age groups? And how useful are they in predicting later weight gain or success in weight loss programs?
The tested polygenic risk score
To develop the genetic risk score, the researchers used modern computational methods that allow the evaluation of the effects of millions of genetic variants simultaneously. For different population groups–such as European, African, or Asian–individual risk values were initially created. The researchers then combined these into a common score that works for as many people as possible, regardless of their background. The basis was large datasets from previous genetic studies, known as GWAS, which have already examined the relationships between genes and body weight.
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What were the results?
The new score worked best for adults of European descent: It could explain 17.6 percent of the differences in BMI. In comparison, a previously commonly used score achieved only about 8.5 percent. In other groups, the predictive power was lower–for example, only 2.2 percent for people in rural regions of Uganda.
Obesity in children: Genetic risk is evident from toddler age
A clear connection was also seen in children: From about 2.5 years old, children with a high genetic risk gained weight significantly faster. They also more frequently experienced an early so-called obesity rebound. This refers to the point when BMI, after naturally declining in toddlerhood, begins to rise again. A very early rebound (before the age of four) is considered a risk factor for later obesity. The new score doubled the predictive power from about age eight compared to traditional birth data such as birth weight or mother’s weight.
What is the significance of the score in adulthood?
The score also showed significant effects in adults: People with a high genetic risk gained more weight on average between the ages of 20 and 50–women more so than men.
Surprisingly, in weight reduction programs–so-called “intensive lifestyle interventions”–people with a high genetic risk even lost slightly more weight in the first year than others (an average of 0.55 kilograms per genetic risk unit). However, they also tended to regain weight more frequently afterward.
What does this mean for practice?
The genetic risk score could become a valuable tool in preventing obesity in the future–especially in children. Particularly in the early years of life, when BMI says little about the future, the score can assess the risk much better.
In adults, the score can also identify early on who has a long-term increased risk of obesity–often years or even decades before the weight actually increases.
However, there is a limitation: The score does not work equally well in all population groups. Particularly for people of African descent, the predictive power is currently significantly lower. This is because they are significantly underrepresented in previous genetic studies. There is an urgent need for research here to improve predictive power and avoid health inequalities.
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Context and open questions
The study is the largest of its kind to date and combines state-of-the-art analysis methods with a vast data base. It covers all age groups–from birth to middle adulthood–and allows for the first time systematic comparisons between ethnic groups.
Despite the promising results, questions remain:
- The polygenic risk score is extremely complex: How exactly should the score be used in practice?
- At what point is someone considered “high risk”?
- How do you explain the value to parents or those affected–without causing insecurity or stigma?
Conclusion
The study shows: Genetic risk scores can help identify obesity early–especially in childhood. The new risk score is significantly better than previous models and provides important insights even in toddlers. For widespread application, however, the predictive power must be improved for all population groups. Properly used, the score could become a useful tool for personalized health care.