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Introduction Pubertal timing influences metabolic disease risk, but its links to the plasma proteome and non-lipid metabolome remain unclear. We investigated associations of pubertal development with these profiles in early adulthood and examined genetic and environmental contributions. Data and methods Finnish twins (630, 57% female) reported pubertal development using the Pubertal Development Scale (PDS) at ages 11.5 and 14, and retrospectively via pubertal age (PA) at ~17.5 years. Plasma proteomics and metabolomics were measured at ~22 years. PDS and PA were tested against proteome and non-lipid metabolome molecules using linear mixed-effects models. Significant associations were decomposed into genetic and environmental components using structural equation modeling. Results Three plasma proteins (desmoglein-2, CD14, complement C6) and one metabolite (histidine) were associated with PDS at age 14. Desmoglein-2 ( r A = –0.08) and CD14 ( r A = –0.13) showed genetic but no significant environmental correlations. The C6 association reflected nonshared environmental factors ( r E = 0.31), with a non-significant genetic correlation. Histidine showed no clear genetic or environmental contributions. Conclusion Pubertal development at age 14 influences plasma molecules in early adulthood. Protein associations reflect both genetic and environmental contributions, with weak, suggestive genetic correlations. Puberty may thus be a critical period for long-term metabolic programming. Impact Pubertal timing at age 14 is associated with specific plasma proteins and metabolites in early adulthood, indicating early-life molecular signatures of metabolic health. Genetic factors may suggestively contribute to some associations (desmoglein-2, CD14), while environmental factors influence others (complement component C6), highlighting targets for personalized risk assessment. These findings suggest that puberty is a critical window for identifying individuals at risk of future metabolic or cardiovascular disorders, offering opportunities for early prevention and intervention strategies.
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Fernandez et al. (2026) studied this question.
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