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L. Lyytikäinen

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Open access Aug 2026

Adolescent weight gain trajectories and their associations with biological aging: a genetically informed study.

BACKGROUND High body mass index (BMI) in adolescence is associated with accelerated biological aging, which might predict the onset of obesity-related diseases before they develop. Genetic factors may shape both adolescent BMI and weight trajectories. METHODS Participants were from the Young Finns Study (n = 3 596, ages 3-18 at baseline), followed from 1980 to 2018-2020. Biological aging was estimated using DNA methylation based epigenetic clocks DunedinPACE (years/calendar year) and PC-GrimAge (years) at three follow-ups (ages 15-56, n = 2045). Genetic predispositions to BMI and childhood body size were quantified using polygenic risk scores (PRSs) (941 and 286 genetic variants). BMI trajectories were modelled from BMI measured at ages 9, 12, 15 and 18 using latent growth curve modelling. Path analysis was used to examine whether genetic liability to BMI is associated with biological aging and if BMI trajectories in adolescence mediate this association. The causal effect of genetically predicted adolescent BMI on biological aging in adulthood was examined with Mendelian randomisation (MR) using individual-level data. RESULTS Higher level of adolescent BMI partly mediated the association between higher BMI-PRS and accelerated biological aging from late adolescence to middle adulthood. MR analyses supported a positive causal effect from genetically predicted adolescent BMI on biological aging, and the causal effect was more consistent when DunedinPACE was used to measure biological aging in 2011 (causal estimate = 0.020 [95% CI = 0.008, 0.031]) and 2018 (0.019 [0.003, 0.035]). CONCLUSIONS Our findings indicate that high BMI in adolescence may accelerate biological aging, especially in individuals with a genetic predisposition to high BMI. Adolescents with a genetic susceptibility to high BMI and elevated BMI might be prone to obesity-related health risks, highlighting early prevention strategies' importance.

Anni Pitkänen, Anna Kankaanpää, E. Raitoharju et al. · 0 citations

Meta-analysis of 49(cid:0)549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

This study illustrates that GWAS with high-scale imputation may still help to unravel the biological mechanism behind circulating lipid levels and identifies more new rare and low-frequency functional variants associated with circulating lipid levels.

E. V. van Leeuwen, A. Sabo, J. Bis et al. · 0 citations

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