An epigenetic clock is a biochemical test that can be used to measure age. The test is based on DNA methylation levels, measuring the accumulation of methyl groups to one's DNA molecules.
History
The strong effects of age on DNA methylation levels have been known since the late 1960s. A vast literature describes sets of CpGs whose DNA methylation levels correlate with age. The first robust demonstration that DNA methylation levels in saliva could generate age predictors with an average accuracy of 5.2 years was published by a UCLA team including Sven Bocklandt, Steve Horvath, and Eric Vilain in 2011 (Bocklandt et al. 2011). The laboratories of Trey Ideker and Kang Zhang at the University of California, San Diego published the Hannum epigenetic clock (Hannum 2013), which consisted of 71 markers that accurately estimate age based on blood methylation levels. The first multi-tissue epigenetic clock, Horvath's epigenetic clock, was developed by Steve Horvath, a professor of human genetics and biostatistics at UCLA (Horvath 2013). Horvath spent over 4 years collecting publicly available Illumina DNA methylation data and identifying suitable statistical methods.
The personal story behind the discovery was featured in Nature. The age estimator was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. The major innovation of Horvath's epigenetic clock lies in its wide applicability: the same set of 353 CpGs and the same prediction algorithm is used irrespective of the DNA source within the organism, i.e. it does not require any adjustments or offsets. This property allows one to compare the ages of different areas of the human body using the same aging clock. Shortly afterwards, a derivation of Horvath's clock, the IEAA (Intrinsic Epigenetic Age Acceleration), an estimator based on the cellular composition of the blood, was developed.
A second generation of epigenetic clocks emerged a few years later and improved on the first in age estimation. This was thanks to the incorporation not only of epigenetic variants such as DNA methylation but also environmental variants such as smoking or chronological age. Among these clocks, the PhenoAge and GrimAge clocks stand out. PhenoAge is an epigenetic clock that takes chronological age into account, and GrimAge uses the mortality risks of age together with the smoking variant among others as a risk factor. Taking into account environmental variants allows GrimAge to outperform any other epigenetic clock in "predicting death".
Third-generation epigenetic clocks are designed to be applicable across multiple species simultaneously. Specifically, pan-mammalian epigenetic clocks determine the age of tissues from all mammalian species by analyzing cytosine methylation in DNA regions that are highly conserved
New age estimation tools have been developed continuously, which also facilitate the prognosis of certain diseases.
Relationship to a cause of biological aging
It is not yet known what exactly is measured by DNA methylation age. Horvath hypothesized that DNA methylation age measures the cumulative effect of an epigenetic maintenance system but details are unknown. The fact that DNA methylation age of blood predicts all-cause mortality in later life has been used to argue that it relates to a process that causes aging. However, if a particular CpG played a direct causal role in the aging process, the mortality it created would make it less likely to be observed in older individuals, making the site less likely to have been chosen as a predictor; the 353 clock CpGs therefore likely have no causal effect whatsoever. Rather, the epigenetic clock captures an emergent property of the epigenome.