In a set of whole blood samples, the application of the Skin & Blood clock resulted in age estimations with a MAE of 2.5.
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While the latter two aim to provide an improved prediction of mortality and are more closely related to physiological dysregulation, the Skin & Blood clock gives an even more accurate prediction of chronological age of easily accessible human tissues – for example, whole blood, saliva and skin – and cell types often used in research such as fibroblasts and lymphoblastoid cell lines. Recently, three further improved epigenetic clocks were published: The Skin & Blood clock, DNA methylation PhenoAge, and DNA methylation GrimAge. DNA methylation age predicts all-cause mortality better than chronological age, and it has also been associated with physical and mental fitness, vegetable and fish intake, obesity, smoking, alcohol use, lifetime stress, social class and multiple other factors. The epigenetic clock has intriguingly demonstrated to be able to quantify these differences and give a biologically relevant prediction of age, that is, a measurement of biological or physiological age. Biological aging occurs at different rates across individuals who can exhibit considerably distinct physical fitness and age-related disease susceptibilities despite being the same chronological age. There is significant interindividual variability present in the human aging process. However, deviations of the age estimation derived by DNA methylation compared to chronological age do also provide valuable information. And it works very precisely, with a median absolute error (MAE) of only 3.6 years, clearly outperforming previously used molecular biomarkers of age such as telomere length.
These usually small but consistent age-associated changes in DNA methylation are what make the epigenetic clock work. In many positions of the human genome, this methylation heterogeneity changes with age. Thus, methylation β‑values effectively measure cell-to-cell variability within a sample. These proportions are given in β‑values between 0 (unmethylated in all cells) and 1 (methylated in all cells). But as DNA methylation measurements are usually obtained from a pool of tens of thousands of cells, what is measured, is the proportion of the cells in which a locus is methylated. A particular locus in the genome can either be methylated or unmethylated. It plays an important role in the regulation of gene expression, altering the phenotype without changing the genotype.
DNA methylation, the addition of methyl groups to cytosine bases of the DNA, is the most widely studied epigenetic modification so far. Horvath’s multi-tissue clock is based on DNA methylation data. The publication of this multi-tissue clock marked a milestone in epigenetics and aging research, and since then, numerous studies have confirmed not only its ability to accurately estimate an individual’s age but also the clock’s great value for studying the human aging process. In 2013, the first epigenetic age estimation method that works with high accuracy across almost all human tissues and cell types was published by Steve Horvath. Together, these new epigenetic clocks present valuable tools to investigate human aging, shed light on the question of why we all age differently, and develop strategies to extend human life- and healthspan. A hat trick of new epigenetic clocks has recently been published by Horvath et al.: The Skin & Blood clock provides a more precise estimation of chronological age in tissues and cell types frequently used in research and forensics, while PhenoAge and GrimAge aim to capture biological aging and derive an improved prediction of mortality and morbidity risks.