Fight Aging!

The important point made by the authors of today's open access paper is that, in the matter of epigenetic clocks, the focus of the research community should shift from the production of ever more refined clocks that better correlate with chronological age, biological age, or specific manifestations of aging, to attempts to understand how exactly the mechanisms and dysfunctions of aging determine change in these clocks. This is now well understood in most parts of the research community, but it still has to be said, and often.

The real promise of epigenetic clocks, and clocks built on transcriptomic, proteomic, and other similar data, is to make the assessment of potential rejuvenation therapies a rapid and cost-effective process. Simply run the clock before and after the treatment, a very favorable alternative to the lengthy studies that are the only present alternative. Without an understanding of which biological processes the clock reflects, however, that data can't be trusted until that specific clock is calibrated against the specific therapeutic approach with slow, expensive lifespan studies. Perhaps the clock undervalues some mechanisms of aging and overvalues others. At present no-one knows whether or not this is the case for any given clock. This state of affairs is a roadblock for the goal of speeding up the process of research and development.

Epigenetic aging: Biological age prediction and informing a mechanistic theory of aging

Nearly a decade ago, researchers showed that a large number of CpG sites in the human genome increase or decrease in methylation fraction over time, such that one can select among these CpG sites to measure the rate at which an individual ages. These so-called "epigenetic clocks" train regularized linear regression models to predict the chronological age of an individual from the methylation values of CpG sites distributed across the genome. During training, the CpG sites for which the methylation fractions are most predictive of chronological age are identified and selected for use in the linear regression equation. The number of CpG sites selected has depended greatly on the particular approach used but is typically between two and a few hundred.

In the time since these epigenetic clocks were introduced, substantial development effort has been invested into improving their predictive accuracy and extending their range of applications. The first randomized clinical trial using an epigenetic clock as the main validator of intervention efficacy was recently conducted. The prediction of epigenetic age has also been made more accessible and efficient; epigenetic clock software packages are readily available, with some requiring methylation values at only a few CpG sites for accurate age predictions. The sophistication of epigenetic clocks today is greater than it was a decade ago because the tools have broader reach, and we fully expect this trend to continue.

While optimization of existing concepts and methods is important, it is also vital that the field keeps moving. Beyond the construction of increasingly accurate chronological clocks, there are many unanswered questions related to the specific mechanisms by which the epigenome influences aging and, reciprocally, by which aging influences the epigenome. Prediction of age was an important first step, but - in our view - the focus must shift from chasing increasingly accurate age computations to understanding the links between the epigenome and the mechanisms and physiological changes of aging.