Researchers at Brigham and Women’s Hospital have developed a DNA clock to study aging, aiming to unlock its secrets. The epigenetic clocks they created can better predict biological aging and assess anti-aging treatments’ effectiveness. Their research introduces a novel machine-learning model that distinguishes between genetic factors speeding up or slowing down aging, compared to previous models.
Researchers develop epigenetic clock to study aging
The study focuses on DNA methylation, a biological process altering DNA structure and gene function, closely tied to aging. Specific CpG sites play a crucial role. New epigenetic clocks—CausAge, DamAge, and AdaptAge—distinguish between methylation changes associated with aging and those causing it.
Prior studies have examined the correlation between methylation patterns and aging-related traits, yet they fail to elucidate the underlying factors influencing the pace of aging. According to Dr. Vadim Gladyshev, the lead researcher from the Division of Genetics at BWH, the novel clock developed in this study marks a significant advancement. Unlike previous models, the clock can differentiate causative relationships, distinguishing between factors that hasten or decelerate aging. Gladyshev says that the innovation makes it possible to predict biological age accurately and evaluate the effectiveness of interventions targeting aging.
Researchers utilized epigenome-wide Mendelian Randomization (EWMR) to analyze over 20,000 CpG sites across the genome, linking them with 8 aging-related traits. These traits included health span, lifespan, and frailty index. By employing this technique, they established causation between DNA structure and observable aging traits rather than mere correlation.
DNA methylation can accelerate or mitigate aging effects
The models were tested “Generation Scotland Cohort,” blood samples for individuals aged 18 to 93. This facilitated the creation of a comprehensive map of human CpG sites influencing biological aging. The map is a valuable tool for identifying aging biomarkers and assessing the impact of interventions on longevity.
The efficacy of the clocks was confirmed through analysis of data from the Framingham Heart Study and the Normative Aging Study. Results showed that the DamAge model correlated with negative health outcomes, including mortality, whereas the AdaptAge model was linked to longevity, indicating DNA methylation changes may either accelerate or mitigate aging effects.
