Martha S. Pitzer Center for Women, Children, & Youth, College of Nursing, The Ohio State University, Columbus, OH.
Center for Research and Health Analytics, College of Nursing, The Ohio State University, Columbus, OH.
Nurs Outlook. 2019 Jul-Aug;67(4):337-344. doi: 10.1016/j.outlook.2019.05.006. Epub 2019 May 17.
A rapidly expanding literature suggests that individuals of the same chronological age show significant variation in biological age.
The purpose of this article is to review the literature surrounding epigenetic age as estimated by DNA methylation, involving the addition or removal of methyl groups to DNA that can alter gene expression without changing the DNA sequence.
This state of the science literature review summarizes current approaches in epigenetic age determination and applications of aging algorithms.
A number of algorithms estimate epigenetic age using DNA methylation markers, primarily among adults. Algorithm application has focused on determining predictive value for risk of disease and death and identifying antecedents to age acceleration. Several studies have incorporated epigenetic age to evaluate intervention effectiveness.
As the research community continues to refine aging algorithms, there may be opportunity to promote health from a precision health perspective.
越来越多的文献表明，同一年龄段的个体在生物学年龄上存在显著差异。
本文旨在回顾 DNA 甲基化估算的表观遗传年龄的文献，甲基化是指在 DNA 上添加或去除甲基基团，这种修饰可以改变基因表达而不改变 DNA 序列。
本科学文献综述总结了当前的表观遗传年龄测定方法和衰老算法的应用。
许多算法使用 DNA 甲基化标记来估计表观遗传年龄，主要针对成年人。算法的应用主要集中在确定疾病和死亡风险的预测价值，以及识别年龄加速的前兆上。一些研究已经将表观遗传年龄纳入其中，以评估干预措施的效果。
随着研究界继续完善衰老算法，从精准健康的角度来看，可能有机会促进健康。
