Associations between 40-year trajectories of BMI and proteomic and epigenetic aging clocks: deciphering nonlinearity and interactions
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Background
While studies have examined associations between changes in BMI and biological aging, the use of biological age estimates derived from omics other than DNA methylation data as well as nonlinearity and interactions in these associations are underexplored.
Objective
We aimed to investigate how BMI at ages 18 and ∼60, as well as changes in BMI from age 18 to ∼60, relate to downstream epigenetic and proteomic aging. We also examined nonlinearity and interactions in these associations.
Methods
We analyzed data from 401 Finnish participants with up to 9 self-reported or measured BMI values collected over 40 years. Olink proteomics and Illumina DNA methylation data were generated from blood samples taken at the last BMI measurement. We calculated 4 and 5 estimates of biological age from proteomic and epigenetic clocks, respectively. Changes in BMI over time were estimated using mixed-effects models. We applied generalized additive models to explore 1) nonlinearity in associations between BMI trajectories and biological aging while adjusting for chronological age and 2) smooth interactions between baseline BMI with changes in BMI and BMI at ∼60 years old.
Results
BMI at 18 and ∼60 years old and changes in BMI were associated with increased biological aging for most aging estimates. We found statistical evidence of nonlinearity for about one-third of the significant associations, mostly observed for proteomic clocks. We identified suggestive evidence for interactions between BMI at 18 years and BMI at ∼60 years in explaining variability in two proteomic clocks (p=0.07; p=0.09).
Conclusion
Our study illustrates the potential of proteomic clocks in obesity research and highlights that assuming linearity in associations between BMI trajectories and biological aging is a critical oversight. Associations between BMI and biological aging are likely modulated by past BMI, which warrants validation by other studies.
