People with an older biological age than their chronological age may be more at risk for dementia. (© svetazi - stock.adobe.com)
BOSTON — Can we finally stop the aging process? Researchers at Brigham and Women’s Hospital (BWH) are hoping so after developing a DNA clock that may unlock the secrets of aging. These new epigenetic clocks can more accurately predict biological aging and the effectiveness of anti-aging treatments. This study introduces a machine-learning model capable of distinguishing between genetic factors that either accelerate or decelerate the aging process, a distinction not made by previous models.
The research revolves around the concept of DNA methylation, a biological process that modifies the DNA structure and affects how genes function. This process is closely linked to aging, with certain DNA regions, known as CpG sites, being particularly influential. The novel epigenetic clocks, named CausAge, DamAge, and AdaptAge, are designed to parse out which methylation changes are merely associated with aging from those that directly cause it.
“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,” says study corresponding author Dr. Vadim Gladyshev, a principal investigator in the Division of Genetics at BWH, in a media release. “Our clocks distinguish between changes that accelerate and counteract aging to predict biological age and assess the efficacy of aging interventions.”
To develop these clocks, researchers employed an epigenome-wide Mendelian Randomization (EWMR) on over 20,000 CpG sites across the genome, correlating them with eight aging-related traits, including lifespan, health span, and frailty index. This technique allowed them to establish causation rather than a mere correlation between DNA structure and observable aging traits.
Researchers tested their models on blood samples from the “Generation Scotland Cohort,” comprising individuals between 18 and 93 years-old, to develop a comprehensive map of human CpG sites that influence biological aging. This map can now be used to identify biomarkers of aging and assess how various interventions might impact longevity.
Further validation of the clocks was conducted using data from the Framingham Heart Study and the Normative Aging Study. The findings revealed that the DamAge model correlated with negative health outcomes, such as mortality, while the AdaptAge model was associated with longevity, indicating that DNA methylation changes could either harm or protect against aging.
An intriguing application of these clocks was in assessing the biological age of reprogrammed stem cells. The researchers found that DamAge decreased in these cells, suggesting a reduction in age-related damage, while AdaptAge showed no consistent pattern.
The team also explored the clocks’ performance in biological samples from patients with chronic conditions and lifestyle-induced damage, finding that DamAge increased with age-related damage, whereas AdaptAge decreased, capturing protective adaptations against aging.
“Aging is a complex process, and we still do not know what interventions against it actually work,” notes Dr. Gladyshev. “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.”
The study is published in the journal Nature Aging.
