Biological Age and Aging Clock: DNA Methylation and Biological Age

Epigenetic changes are one of the characteristics of aging. Aging is likely to be largely due to the loss of epigenomic information. Therefore, the epigenetic clock (EC) is measuring aging by targeting DNA methylation [1]. It aims to measure biological age and can strongly predict morbidity and mortality rates associated with aging, along with various health risks. It represents biological age beyond chronological age and can be called a life-course clock. Currently, there are ECs that only determine based on the degree of DNA methylation in a predetermined CpG region (such as the Horvath clock) and ECs as aging clocks that include multifactorial factors including clinical blood and EC (GrimAge V2, DunedinPACE). In 2011, it was shown that age prediction in chronological order is possible by examining DNA methylation, and in 2013, the concept of an epigenetic aging clock was announced by Hannum and others and has continued to the present (Fig. 13.1). While other biomarkers often measure organ dysfunction, EC is an aging biomarker that can also be applied to fetal tissues. As of 2022, the so-called third-generation EC is being used. Because it uses machine learning, the process is black-boxed, and it has a characteristic of weak connection with traditional biological mechanisms (such as enzymatic reactions). Currently, DunedinPACE, which was developed by adding EC to blood data in prospective cohorts, is being used clinically. Furthermore, each individual’s biological age and its deformation rate (acceleration) are shown. It is widely used in human aging intervention trials and cohort studies. The problem is accuracy, and discussions about sensitivity and specificity are being held. The accuracy of the error between the same samples (intraclass correlation coefficients; ICC) is also under consideration. It is said that it has not yet reached the level of disease treatment judgment.