

DNA Methylation-based Measures of Biological Age
Jan 4, 2022
14:18
Aging-US published "DNA methylation-based measures of biological age: meta-analysis predicting time to death" in 2016, which reported that estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans.
These authors previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, they expanded their original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, they examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality.
All considered measures of epigenetic age acceleration were predictive of mortality, independent of chronological age, even after adjusting for additional risk factors.
The authors said, "DNA methylation-based biomarkers, often referred to as ‘epigenetic age’ or ‘epigenetic clock’, are robust estimators of chronological age of an individual."
Full Press Release - https://www.aging-us.com/news_room/dna-methylation-based-measures-of-biological-age
Full Text - https://www.aging-us.com/article/101020/text/
Correspondence to: Steve Horvath email: shorvath@mednet.ucla.edu
Keywords: all-cause mortality, lifespan, epigenetics, epigenetic clock, DNA+methylation, mortality
About Aging-US
Launched in 2009, Aging-US publishes papers of general interest and biological significance in all fields of aging research and age-related diseases, including cancer—and now, with a special focus on COVID-19 vulnerability as an age-dependent syndrome. Topics in Aging-US go beyond traditional gerontology, including, but not limited to, cellular and molecular biology, human age-related diseases, pathology in model organisms, signal transduction pathways (e.g., p53, sirtuins, and PI-3K/AKT/mTOR, among others), and approaches to modulating these signaling pathways.
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