Polygenic Scores for BMI Can Improve Prediction of Future Obesity

THURSDAY, July 31, 2025 (HealthDay News) — Polygenic scores (PGSs) for body mass index (BMI) can improve obesity prediction, according to a study published online July 21 in Nature Medicine.

Roelof A.J. Smit, Ph.D., from the Icahn School of Medicine at Mount Sinai in New York City, and colleagues used genetic data from up to 5.1 million people from the Genetic Investigation of Anthropometric Traits (GIANT) consortium and 23andMe to develop ancestry-specific and multi-ancestry PGSs for BMI.

The researchers found that 17.6 percent of BMI variation among UK Biobank participants of European ancestry was explained by the multi-ancestry score. In other populations, this ranged from 16 to 2.2 percent in East Asian-Americans and rural Ugandans, respectively. Children with higher PGSs showed accelerated BMI gain from age 2.5 years to adolescence in the Avon Longitudinal Study of Parents and Children (ALSPAC) study, with earlier adiposity rebound. The explained variance for BMI from age 5 onward nearly doubled with addition of PGS to predictors available at birth (e.g., from 11 to 21 percent at age 8). Adding the PGS to early-life BMI up to age 5 improved BMI prediction at age 18 (e.g., from 22 to 35 percent at age 5). Greater adult weight gain was seen in association with higher PGSs. Individuals with higher PGSs lost modestly more weight in the first year in intensive lifestyle intervention trials, but were more likely to regain it.

“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,” Smit said in a statement.

Several authors disclosed ties to the biopharmaceutical industry.

Abstract/Full Text