Abstract
Background
Aging is marked by changes in DNA methylation (DNAm) including an increase in randomness or entropy in the epigenome. Here, we computed epigenetic entropy using DNAm data from the Women's Health Initiative (WHI) ancillary study AS315 (n = 2192), and tested for replication in WHI ancillary studies, BA23 (n = 1989) and AS311 (n = 868). We investigated how different metrics of epigenetic stochasticity relate to demographic variables, health, and mortality risk, and how these compare to machine-learning based models of aging such as the DunedinPACE.Results
Epigenetic entropy had robust and consistent negative associations with income and education in the WHI. Notably, low income was related to increased stochasticity and higher methylation in DNA regions that are targeted by the polycomb proteins-key regulators of cellular memory and embryonic development. While higher income was associated with reduced entropy scores and lower DunedinPACE in White women, this effect of income was diminished in Black and Hispanic women, and on average, Black and Hispanic women had relatively higher stochastic variability. Painting a complex picture, our analysis of the polycomb regions in a small cohort of children showed significant positive associations with parental income. Additionally, in the WHI, higher DunedinPACE predicted higher mortality risk, while the maintenance of methylation at enhancer regions was associated with improved survival.Conclusions
These findings indicate close ties between social and economic factors and aspects of epigenetic aging, and highlight the polycomb targeted CpGs as potential sensors of the social environment and related exposures across demographic groups.