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Evaluating a Genome-Wide Polygenic Score for Handgrip Strength and Its Interplay with Leisure-Time Physical Activity Across the IGEMS Twin Cohorts

Herranen, P.; Palviainen, T.; Nygaard, M.; Karlsson, I. K.; Thalamuthu, A.; Mather, K. A.; Reynolds, C. A.; Panizzon, M. S.; Rantanen, T.; Finkel, D.; Gatz, M.; Pedersen, N. L.; IGEMS Consortium, ; Kaprio, J.; Sillanpää, E.

2025-08-14 genetic and genomic medicine
10.1101/2025.08.07.25333195 medRxiv
Show abstract

Background Polygenic scores (PGSs) may help assess genetic predisposition to multifactorial traits. We examined whether age, sex, and leisure-time physical activity (LTPA) modify the association between a PGS for handgrip strength (HGS) and measured HGS in older adults. Methods PGS HGS, based on Pan-UK Biobank GWAS data, was calculated for 5103 participants (aged 40-96; 44% women) from eight twin cohorts in Denmark, Sweden, Australia, the United States, and Finland within the IGEMS consortium. Sex-standardized HGS and self-reported LTPA were assessed cross-sectionally. Linear mixed models estimated associations between PGS and HGS, including interactions with age, country, and LTPA, as well as an association between PGS and LTPA. Fixed-effect within-pair models were conducted to assess environmental contributions. Results Higher PGS was associated with greater HGS ({beta} = 2.14, SE = 0.15, p < 0.001), explaining 4.6% of HGS variance overall, with modest variation across countries. In sex-stratified models, PGS explained 5.2% of the variance in females and 4.3% in males. A significant PGS x LTPA interaction ({beta} = -0.034, p = 0.013) indicated that LTPA had a stronger effect among individuals with lower PGS HGS. No statistically significant interaction with age was found. The within-pair models offered limited support for the environmental impact of LTPA. Conclusions PGS for HGS was associated with measured HGS, with effect modification by LTPA. Findings provide some evidence that physical activity may buffer against genetic predisposition to lower HGS. The results highlight the potential of PGSs to capture individual differences in strength-related traits across populations.

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