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.