New epigenetic clocks could reinvent how we measure age

Various biological systems change as we age, and by measuring the amount of variation in a system, or combination of systems, we can ascertain where an individual sits on the line of progression between the optimum function associated with youth and the decline and degeneration that comes with aging. These measures – called aging clocks – give a biological age of tissues and organs and can demonstrate how far tissue (or a person) has drifted from their chronological age. The younger your biological age, the more time there should be on your mortality timer.

Longevity.Technology: Epigenetic clocks – machine learning platforms that evaluate DNA methylation levels by measuring the amount of methyl groups added to DNA – have become a popular way of measuring biological age. Now researchers from Brigham and Women’s Hospital have unveiled a new form of epigenetic clock; the novel model distinguishes between genetic differences that slow and accelerate aging, meaning it can predict biological age and evaluate antiaging interventions with increased accuracy [1].

New epigenetic clocks could reinvent how we measure age
Dr Vadim Gladyshev is a PI in the Division of Genetics at BWH

“Previous clocks considered the relationship between methylation patterns and features we know are correlated with aging, but they don’t tell us which factors cause one’s body to age faster or slower. We have created the first clock to distinguish between cause and effect,” said corresponding author Vadim Gladyshev, PhD, a principal investigator in the Division of Genetics at BWH. “Our clocks distinguish between changes that accelerate and counteract aging to predict biological age and assess the efficacy of aging interventions [2].”

DNA methylation is an alteration to the genetic structure that can change the ways genes are expressed, and aging researchers have long acknowledged its influence on the aging process. While lifestyle choices, like smoking and diet, influence DNA methylation, so too do our genes, something that can explain why people with similar lifestyles can age at very different rates.

Existing epigenetic clocks predict biological age using DNA methylation patterns, but until now, no existing clocks have distinguished between the methylation differences that cause biological aging and those that simply correlate with the aging process.

Specific regions of our DNA, known as CpG sites, are more strongly associated with aging. Using a large genetic data set, first author Kejun (Albert) Ying, a graduate student in the Gladyshev lab, performed an epigenome-wide Mendelian Randomization (EWMR), a technique used to randomize data and establish causation between DNA structure and observable traits, on 20,509 CpG sites causal to eight aging-related characteristics. The eight aging-related traits included lifespan, extreme longevity (defined as survival beyond the 90th percentile), healthspan (age at first incidence of major age-related disease), frailty index (a measure of one’s frailty based on the accumulation of health deficits during their lifespan), self-rated health, and three broad aging-related measurements incorporating family history, socioeconomic status, and other health factors [1].

Working from these these traits and their associated DNA sites, Ying created three models – CausAge, a general clock that predicts biological age based on causal DNA factors, and DamAge and AdaptAge, which include only damaging or protective changes. Researchers then analyzed blood samples from 7,036 individuals aged 18 to 93 years old from the ‘Generation Scotland Cohort’, ultimately training their model on data from 2,664 individuals in the cohort.

Leveraging these data, researchers were able to develop a map pinpointing human CpG sites that cause biological aging. This map allows users to identify biomarkers causative to aging and evaluate how different interventions promote longevity or accelerate aging.

The next step was to test the clocks’ validity. Using data collected from 4,651 individuals in the Framingham Heart Study and the Normative Aging Study, the research team found that DamAge correlated with adverse outcomes, including mortality, and AdaptAge correlated with longevity; these findings suggest that age-related damage contributes to the risk of death while protective changes to DNA methylation may contribute to a longer lifespan [1].

Next, the researchers evaluated the clocks’ ability to assess biological age; they reprogrammed stem cells to a pluripotent state and found that when the clocks were applied to the newly transformed cells, DamAge decreased, indicating a reduction in age-related damage during reprogramming, while AdaptAge did not show a particular pattern.

Finally, the team tested their clocks’ performance in biological samples from patients with various chronic conditions, including cancer and hypertension, as well as samples damaged from lifestyle choices like smoking cigarettes. DamAge consistently increased in conditions associated with age-related damage, while AdaptAge decreased, effectively capturing protective adaptations [1].

“Aging is a complex process, and we still do not know what interventions against it actually work,” said Gladyshev, speaking about the results which have been published in Nature Aging. “Our findings present a step forward for aging research, allowing us to more accurately quantify biological age and evaluate the ability of novel aging interventions to increase longevity [2].”


Photograph: Triff/Shutterstock