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Joint model shows association of Mapuche genetic ancestry and longitudinal BMI with early menarche

Vicuna, L.; Meza, C.; Alvares, D.; Mericq, V.; Pereira, A.; Eyheramendy, S.

2025-12-09 genetics
10.64898/2025.12.04.692408 bioRxiv
Show abstract

The age at puberty onset varies greatly between individuals and ethnic populations, with significant health implications. Early menarche increases risk for breast cancer, cardiovascular disease, depression, behavioral disorders, diabetes, and all-cause mortality. While genetic factors and higher body mass index (BMI) have been associated with earlier pubertal timing in girls, the effect of Native American genetic ancestry on menarche timing is virtually unknown. We assessed how individual Mapuche Native American genetic ancestry proportions and BMI changes over time influence age at menarche in a cohort of admixed girls with mainly European and Mapuche ancestries. We developed a novel joint statistical model that links a Bernoulli random variable with longitudinal trajectories. The model captures individual-specific BMI trajectory dynamics through individual random effects, linking longitudinal BMI patterns directly to early menarche risk, incorporating the assessment of genetic ancestry effects as well. Two parameter estimation methods were developed, confirming the robustness of the model fit. We found significant ancestry effects, with girls experiencing early menarche having higher mean Mapuche ancestry proportions (47.5% vs 45.1%, p = 0.010). Each 10% increase in Mapuche ancestry substantially increased early menarche risk ({gamma}1 = 3.405, p = 0.010). Childhood BMI growth patterns strongly predicted early menarche: both BMI change rate (1 = 1.189, p < 0.001) and growth acceleration (2 = 9.080, p = 0.003) were significant predictors, while baseline BMI showed no association (p = 0.254). These results demonstrate that higher Mapuche ancestry and accelerating BMI trajectories independently increase early menarche likelihood. Body mass index, early menarche, genetic ancestry, mixed models, joint modeling

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