Epigenetic modifiers as game changers for healthy ageing

The Heterogeneity of Post-Menopausal Disease Risk: Could the Basis for Why Only Subsets of Females Are Affected Be Due to a Reversible Epigenetic Modification System Associated with Puberty, Menstrual Cycles, Pregnancy and Lactation, and, Ultimately, Menopause?

For much of human evolution, the average lifespan was <40 years, due in part to disease, infant mortality, predators, food insecurity, and, for females, complications of childbirth. Thus, for much of evolution, many females did not reach the age of menopause (45-50 years of age) and it is mainly in the past several hundred years that the lifespan has been extended to >75 years, primarily due to public health advances, medical interventions, antibiotics, and nutrition. Therefore, the underlying biological mechanisms responsible for disease risk following menopause must have evolved during the complex processes leading to Homo sapiens to serve functions in the pre-menopausal state. Furthermore, as a primary function for the survival of the species is effective reproduction, it is likely that most of the advantages of having such post-menopausal risks relate to reproduction and the ability to address environmental stresses. This opinion/perspective will be discussed in the context of how such post-menopausal risks could enhance reproduction, with improved survival of offspring, and perhaps why such risks are preserved. Not all post-menopausal females exhibit risk for this set of diseases, and those who do develop such diseases do not have all of the conditions. The diseases of the post-menopausal state do not operate as a unified complex, but as independent variables, with the potential for some overlap. The how and why there would be such heterogeneity if the risk factors serve essential functions during the reproductive years is also discussed and the concept of sets of reversible epigenetic changes associated with puberty, pregnancy, and lactation is offered to explain the observations regarding the distribution of post-menopausal conditions and their potential roles in reproduction. While the involvement of an epigenetic system with a dynamic "modification-demodification-remodification" paradigm contributing to disease risk is a hypothesis at this point, validation of it could lead to a better understanding of post-menopausal disease risk in the context of reproduction with commonalities may also lead to future improved interventions to control such risk after menopause.

Exponential dynamics of DNA methylation with age

The association of DNA methylation with age has been extensively studied. Previous work has investigated the trajectories of methylation with age, and developed predictive biomarkers of age. However, we still have a limited understanding of the functional form of methylation-age dynamics. To address this we present a theoretical framework to model the dynamics of DNA methylation at single sites. We show that this model leads to convergence to a steady-state methylation level at an exponential rate. By fitting the model to a dataset that measures changes in DNA methylation in the brain from birth to old age, we show that the timescales of this exponential convergence are heterogeneous across sites. To model this heterogeneity we generated a simulation of CpG Methylation changes with time and investigated the functional form of the dynamics of methylation with age under the empirical distribution of timescales estimated from the dataset. The resulting dynamics of the average methylation of the system were characterized and were found to closely follow an exponential trajectory. We conclude that DNA methylation can be modeled as a system that starts out of equilibrium at birth and approaches equilibrium with age in an exponential fashion. These insights illustrate the importance of accounting for nonlinear dynamics when utilizing age associated DNA methylation changes for constructing biomarkers of aging. Thus DNA methylation, along with the exponentially increasing risk of mortality with age, further establishes the exponential nature of aging.