Associations Between 40‐Year Trajectories of <scp>BMI</scp> and Proteomic and Epigenetic Aging Clocks: Deciphering Nonlinearity and Interactions

The potential of proteomic aging clocks for obesity research, and the extent of nonlinearity in longitudinal associations between body weight and biological aging, remain underexplored. We investigated 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. Analyses were conducted in 401 Finnish twins with up to nine self-reported or measured BMI values collected over 40 years. Olink proteomic and Illumina DNA methylation data were generated from blood drawn at the last BMI measurement. From these data, we derived four proteomic and five epigenetic age estimates and modeled BMI change over time using mixed-effects models. Generalized additive models were then applied to examine (1) nonlinear associations between BMI trajectories and biological aging, adjusting for chronological age, and (2) interactions of baseline BMI with BMI change and BMI at ~60 years. 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 further 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). In 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.

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Publication Details

Journal
Aging Cell
Published
2026-01-29
DOI
https://doi.org/10.1111/acel.70397
Primary Topic
Epigenetics and DNA Methylation
Type
article
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article

Associations Between 40‐Year Trajectories of BMI and Proteomic and Epigenetic Aging Clocks: Deciphering Nonlinearity and Interactions

Gabin Drouard, Aino Heikkinen, Jaakko Kaprio, Miina Ollikainen et al.
Aging Cell
Epigenetics and DNA Methylation
article

Associations Between 40‐Year Trajectories of BMI and Proteomic and Epigenetic Aging Clocks: Deciphering Nonlinearity and Interactions

Gabin Drouard, Aino Heikkinen, Jaakko Kaprio, Miina Ollikainen, M. Austin Argentieri
article en

Abstract

The potential of proteomic aging clocks for obesity research, and the extent of nonlinearity in longitudinal associations between body weight and biological aging, remain underexplored. We investigated 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. Analyses were conducted in 401 Finnish twins with up to nine self-reported or measured BMI values collected over 40 years. Olink proteomic and Illumina DNA methylation data were generated from blood drawn at the last BMI measurement. From these data, we derived four proteomic and five epigenetic age estimates and modeled BMI change over time using mixed-effects models. Generalized additive models were then applied to examine (1) nonlinear associations between BMI trajectories and biological aging, adjusting for chronological age, and (2) interactions of baseline BMI with BMI change and BMI at ~60 years. 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 further 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). In 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.

Aging CellVol. 25(2)
Broad Institute (US), University of Helsinki (FI), Massachusetts General Hospital (US), Minerva Foundation (FI), Institute for Molecular Medicine Finland (FI)
Openalex Percentile: Top 75%
Epigenetics and DNA Methylation
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