Childhood Genetics: Your DNA Already Knows If You'll Gain Weight

Scientists have discovered a way to use DNA to predict obesity risk from childhood. A new "genetic score" analyzes thousands of small variations in DNA to identify children who are more likely to gain weight over the course of their lives. This information can help doctors and families take action early, with healthy habits, before the problem arises.

Obesity is a growing public health problem affecting millions of people worldwide. In addition to reducing life expectancy, it is linked to the emergence of several chronic diseases, such as diabetes, hypertension, and heart problems. It is estimated that by 2035, more than half of the global population will be overweight or obese.

While treatments such as bariatric surgery, medications, and lifestyle changes exist, these options are not always available to everyone, are expensive, or involve risks. Therefore, prevention, especially from an early age, has become essential.

One of the most promising developments in early obesity prevention comes from genetics. Scientists have created a tool called a polygenic risk score (PGS), which uses a person's DNA to predict their likelihood of developing obesity over the course of their lifetime.

This score works like a kind of "genetic calculator," adding up the effects of thousands of small DNA variations that, together, can influence body weight.

Using genetic data from more than five million people, the largest dataset of its kind ever studied, researchers were able to develop a highly accurate PGS.

They found that this score can predict obesity risk from early childhood, often before the age of five. This means that even before a child shows visible signs of weight gain, it is possible to identify a high risk and take preventative action with guidance on diet and physical activity.

In children followed in long-term studies, such as the "Children of the 90s," those with a higher genetic score had faster weight gain from the age of two and a half and showed signs of obesity risk as early as adolescence.

Including this genetic score among the factors assessed at birth nearly doubled the accuracy in predicting body mass index (BMI) at ages five to eight. This makes it possible to develop personalized health strategies from a very early age.

Studies have also shown that the PGS performs well in predicting variations in adult BMI, especially among people of European descent, where it explained about 17% of weight differences.

However, the results were less accurate in populations of other origins, such as Africans, highlighting the importance of developing more inclusive tools that consider global genetic diversity.

Furthermore, the researchers observed that people with a higher genetic risk of obesity responded slightly better to weight loss programs based on lifestyle changes (such as diet and exercise).

However, these individuals were also more likely to regain weight after the interventions ended. In other words, understanding genetic risk can help personalize not only prevention but also long-term monitoring.

This discovery paves the way for a new era in public health, where genetics can help predict and prevent diseases like obesity more effectively and in a personalized way. By identifying children at risk early, it is possible to take action before the problem sets in, with positive impacts that last a lifetime.

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Polygenic prediction of body mass index and obesity through the life course and across ancestries

Roelof A. J. Smit, Kaitlin H. Wade, Qin Hui, Joshua D. Arias, Xianyong Yin, Malene R. Christiansen, Loic Yengo, Michael H. Preuss, Mariam Nakabuye, Ghislain Rocheleau, Sarah E. Graham, Victoria L. Buchanan, Geetha Chittoor, Marielisa Graff, Marta Guindo-Martínez, Yingchang Lu, Eirini Marouli, Saori Sakaue, Cassandra N. Spracklen, Sailaja Vedantam, Emma P. Wilson, Shyh-Huei Chen, Teresa Ferreira, Yingjie Ji, Tugce Karaderi, Kreete Lüll, Moara Machado, Deborah E. Malden, Carolina Medina-Gomez, Amy Moore, Sina Rüeger, Masato Akiyama, Matthew A. Allison, Marcus Alvarez, Mette K. Andersen, Vivek Appadurai, Liubov Arbeeva, Eric Bartell, Seema Bhaskar, Lawrence F. Bielak, Joshua C. Bis, Sailalitha Bollepalli, Jette Bork-Jensen, Jonathan P. Bradfield, Yuki Bradford, Caroline Brandl, Peter S. Braund, Jennifer A. Brody, Ulrich Broeckel, Kristoffer S. Burgdorf, Brian E. Cade, Qiuyin Cai, Silvia Camarda, Archie Campbell, Marisa Cañadas-Garre, Jin-Fang Chai, Alessandra Chesi, Seung Hoan Choi, Paraskevi Christofidou, Christian Couture, Gabriel Cuellar-Partida, Rebecca Danning, Frauke Degenhardt, Graciela E. Delgado, Alessandro Delitala, Ayşe Demirkan, Xuan Deng, Alexander Dietl, Maria Dimitriou, Latchezar Dimitrov, Rajkumar Dorajoo, …, Cristen J. Willer, Kristin L. Young, Segun Fatumo, Jeanne M. McCaffery, Nicholas J. Timpson, Joel N. Hirschhorn, Yan V. Sun, Sonja I. Berndt, and Ruth J. F. Loos

Nature Medicine. 21 July 2025 

DOI: 10.1038/s41591-025-03827-z

Abstract: 

Polygenic scores (PGSs) for body mass index (BMI) may guide early prevention and targeted treatment of obesity. Using genetic data from up to 5.1 million people (4.6% African ancestry, 14.4% American ancestry, 8.4% East Asian ancestry, 71.1% European ancestry and 1.5% South Asian ancestry) from the GIANT consortium and 23andMe, Inc., we developed ancestry-specific and multi-ancestry PGSs. The multi-ancestry score explained 17.6% of BMI variation among UK Biobank participants of European ancestry. For other populations, this ranged from 16% in East Asian-Americans to 2.2% in rural Ugandans. In the ALSPAC study, children with higher PGSs showed accelerated BMI gain from age 2.5 years to adolescence, with earlier adiposity rebound. Adding the PGS to predictors available at birth nearly doubled explained variance for BMI from age 5 onward (for example, from 11% to 21% at age 8). Up to age 5, adding the PGS to early-life BMI improved prediction of BMI at age 18 (for example, from 22% to 35% at age 5). Higher PGSs were associated with greater adult weight gain. In intensive lifestyle intervention trials, individuals with higher PGSs lost modestly more weight in the first year (0.55 kg per s.d.) but were more likely to regain it. Overall, these data show that PGSs have the potential to improve obesity prediction, particularly when implemented early in life.