Postnatal epigenome-mediated aging control and global trends

Abstract

The epigenome can adequately regulate the on/off states of genes in response to external environmental factors and stress. In recent years, it has been observed that the epigenome, which is modulated through DNA methylation, histone modifications, and chromatin remodeling, changes with age. Alterations in the epigenome lead to the loss of cell-specific epigenome/identity, which in turn triggers a decline in tissue function. In mammals, postnatal epigenomic variations are not only caused by metabolic diseases, such as diabetes or DNA damage, but also by social stress and infectious diseases. Unlike Genome-Wide Association Studies (GWAS), dynamically changing epigenomes, along with their cellular roles, need to be established as objective biomarkers in conjunction with various biological signals, such as walking speed, brain waves, and clinical data. The biological age/aging clock, determined by methylated DNA, has attracted attention, and calorie restriction not only slows the progression of aging, but also seems to suppress it. However, as indicated by gene expression analysis in aging mice, aging is not a linear model, but is represented by nonlinear dynamic changes. Consequently, the development of experimental models and analytical methods that enhance temporal resolution through time-series analysis, tailored to spatial resolution, such as cell distribution and organ specificity, is progressing. Moreover, in recent years, in addition to anti-aging efforts targeting epigenomic variations, global attention has increasingly focused on research and development aimed at rejuvenating treatments, thus leading to the birth of many biotech companies. Aging Hallmarks such as inflammation, stem cells, metabolism, genomic instability, and autophagy, interact closely with the epigenome. Various postnatal and reversible epigenomic controls of aging, including Yamanaka factors (OKSM and OSK), are now entering a new phase. In the future, the development of aging control using diverse modalities, such as mRNA, artificial peptides, and genome editing, is expected, along with an improved molecular understanding of aging and identification of useful biomarkers.