Genetic Associations and Epidemiology Open access Peer reviewed

A multi-ancestry polygenic risk score for body mass index predicts longitudinal weight change

Tianyuan Lu, Lily Stalter, Kate Lauer, Bret M. Hanlon and 2 more

Genome Medicine | Aug 5, 2026

Abstract

Abstract

Abstract Background Identifying individuals at risk for future weight gain is challenging, partly because associations with traditional clinical risk factors may be biased by confounding and reverse causation. Polygenic risk scores (PRS) provide a stable, lifelong measure of genetic predisposition to obesity. However, existing PRS have not been evaluated for their association with longitudinal weight change in adulthood and often lack generalizability across diverse genetic ancestry groups. Methods We conducted ancestry-specific genome-wide association study meta-analyses of body mass index (BMI) in populations of European, African or African American, Admixed American, East Asian, and South Asian ancestries and developed ancestry-specific PRS. A multi-ancestry polygenic risk score (MAPRS) was trained using ancestry-specific PRS in a model selection dataset ( N = 39,685) from the All of Us Research Program (AoU). We evaluated the MAPRS in an independent AoU model evaluation dataset ( N = 158,743) for BMI prediction and in a separate AoU test dataset ( N = 78,219) with repeated measurements over 1.5–2.5 years for weight change prediction. The outcomes included change in BMI and ≥ 10% or ≥ 5% total body weight (TBW) gain. We further examined the relationship between MAPRS and 12 clinical risk factors commonly comorbid with obesity in relation to weight change. Results The MAPRS captured 7.05% of the variance in measured BMI in the AoU model evaluation dataset and demonstrated improved generalizability across all non-European genetic ancestry groups. In the AoU test dataset, conditioned on baseline BMI at the second-to-last measurement, a one SD increase in MAPRS was associated with a 0.16 kg/m 2 increase in future BMI (standard error = 0.012 kg/m 2 ; p -value = 2.2 × 10 –39 ), 1.27-fold increased odds of experiencing ≥ 10% TBW gain (95% CI: 1.24–1.31; p -value = 1.4 × 10 –55 ), and 1.15-fold increased odds of experiencing ≥ 5% TBW gain (95% CI: 1.13–1.18; p -value = 2.8 × 10 –39 ). These associations were observed across all genetic ancestry groups and remained highly consistent after adjustment for any clinical risk factor. In contrast, most clinical risk factors demonstrated inconsistent or weaker associations with weight change outcomes. Conclusions We developed an MAPRS for BMI that represents a robust and generalizable risk factor for longitudinal weight gain in adulthood, providing a foundation for genetically informed risk stratification and earlier, more targeted obesity prevention strategies.

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Authors

Researchers on this paper

Tianyuan Lu

first | University of Wisconsin System | ORCID 0000-0002-5664-5698

Lily Stalter

middle | University of Wisconsin–Madison | ORCID 0000-0002-9226-1667

Kate Lauer

middle | University of Wisconsin–Madison | ORCID 0000-0002-1858-6973

Bret M. Hanlon

middle | University of Wisconsin–Madison | ORCID 0000-0002-4517-1204

Wenmin Zhang

middle | University of Manitoba | ORCID 0000-0002-3946-625X

Luke M. Funk

last | University of Wisconsin–Madison

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Citation

BibTeX

@article{Lu2026multi,
  title = {A multi-ancestry polygenic risk score for body mass index predicts longitudinal weight change},
  author = {Tianyuan Lu and Lily Stalter and Kate Lauer and Bret M. Hanlon and Wenmin Zhang and Luke M. Funk},
  journal = {Genome Medicine},
  year = {2026},
  doi = {10.1186/s13073-026-01741-8},
  url = {https://doi.org/10.1186/s13073-026-01741-8}
}

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