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In the past year or two, a great deal of effort on the part of leading researchers has gone into trying to standardize the use of a single epigenetic clock based on DNA methylation status of CpG sites on the genome. Suitable candidate universal mammalian clocks now exist. There are good reasons for standardization. Given that any large amount of omics data can be used to produce aging clocks, where “clock” in this context means a weighted combination of measured values that correlates well with chronological age or biological age, there is an essentially infinite number of potential clocks. People can build or cherry pick clocks that are optimized to produce large numbers for their specific therapeutic approach to age-slowing or age-reversing intervention. Further, comparing results obtained with different clocks is essentially impossible. This leads to wasted effort.
As an example of why standardization is important, we might look at today’s open access paper, in which researchers pick a clock that isn’t one of the proposed standards, uses only four CpG sites (a tiny number!) and show large differences between study groups. One wonders if they picked the clock because the numbers are large. One can’t really do anything to compare this data with data obtained from different clocks: this paper is thus unlikely to contribute meaningfully to the advance of knowledge. Further, we should probably assume that any epigenetic clock built using such a small number of CpG sites is reflecting only a very narrow slice of the full panoply of processes of degenerative aging. It is reasonable to think that no such clock will be able to usefully assess the results of interventions that target only a subset of the processes of aging. All in all, this isn’t helpful.
Decelerated Epigenetic Aging in Long Livers
Epigenetic aging is a hot topic in the field of aging research. The present study estimated epigenetic age in long-lived individuals, who are currently actively being studied worldwide as an example of successful aging due to their longevity. We used Bekaert’s blood-based age prediction model to estimate the epigenetic age of 50 conditionally “healthy” and 45 frail long-livers over 90 years old. Frailty assessment in long-livers was conducted using the Frailty Index. The control group was composed of 32 healthy individuals aged 20-60 years.
The DNA methylation status of the 4 CpG sites (ASPA CpG1, PDE4C CpG1, ELOVL2 CpG6, and EDARADD CpG1) included in the epigenetic clock was assessed through pyrosequencing. According to the model calculations, the epigenetic age of long-livers was significantly lower than their chronological age (on average by 21 years) compared with data from the group of people aged 20 to 60 years. This suggests a slowing of epigenetic and potentially biological aging in long livers.
At the same time, the obtained results showed no statistically significant differences in delta age (difference between the predicted and chronological age) between “healthy” long livers and long livers with frailty. We also failed to detect sex differences in epigenetic age either in the group of long livers or in the control group. It is possible that the predictive power of epigenetic clocks based on a small number of CpG sites is insufficient to detect such differences. Nevertheless, this study underscores the need for further research on the epigenetic status of centenarians to gain a deeper understanding of the factors contributing to delayed aging in this population.
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