Responsiveness of epigenetic aging biomarkers to longevity interventions in humans

德纳姆 心理干预 表观遗传学 生物标志物 医学 人口 生物信息学 健康衰老 老年学 临床试验 长寿 人口老龄化 DNA甲基化 临床研究设计 干预(咨询) 细胞老化 集合(抽象数据类型) 老化 兴奋 梅德林 衰老 生物 肿瘤科 重症监护医学
作者
Raghav Sehgal,Daniel Borrus,Jenel F. Armstrong,John Gonzalez,Jessica Kasamoto,Yaroslav Markov,Ahana Priyanka,Ryan Smith,Natàlia Carreras-Gallo,Jessica Lasky‐Su,Varun B. Dwaraka,Michael J. Corley,Albert Higgins‐Chen
出处
期刊:Nature Medicine [Nature Portfolio]
被引量:1
标识
DOI:10.1038/s41591-026-04562-9
摘要

Abstract Aging biomarkers can potentially allow researchers to rapidly monitor the impact of an aging intervention without the need for decade-spanning trials. However, before the use of aging biomarkers, such as epigenetic clocks, as surrogate endpoints, their responsiveness to interventions that target aging must be tested. Here we curate TranslAGE, a harmonized database of 51 public and private longitudinal interventional studies, and calculate a consistent set of 16 prominent epigenetic clocks for each study, along with 94 other DNA methylation (DNAm) biomarkers that can help explain the changes observed for each clock. Using this database, we discover patterns of responsiveness across a variety of interventions and DNAm biomarkers. For example, clocks trained to predict mortality or pace of aging show the strongest responses across all interventions and show consistent results with one another; pharmacological and lifestyle interventions drive the strongest responses from DNAm biomarkers; and the characteristics of the study population and study duration are key factors in determining the responsiveness of DNAm biomarkers to an intervention. Moreover, clocks with multiple subscores (that is ‘explainable clocks’) provide specificity and greater mechanistic insight into the responsiveness of interventions than single-score clocks. These findings can help to design future clinical trials by guiding the choice of interventions and of specific subsets of DNAm biomarkers to minimize multiple testing, study duration, study population and sample size, with the eventual aim of uncovering DNAm biomarkers that can be used as surrogate aging endpoints.
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