A systematic review of phenotypic and epigenetic clocks used for aging and mortality quantification in humans.

IF 3.9 3区 医学 Q2 CELL BIOLOGY
Aging-Us Pub Date : 2024-08-30 DOI:10.18632/aging.206098
Brandon Warner, Edward Ratner, Anirban Datta, Amaury Lendasse
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引用次数: 0

Abstract

Aging is the leading driver of disease in humans and has profound impacts on mortality. Biological clocks are used to measure the aging process in the hopes of identifying possible interventions. Biological clocks may be categorized as phenotypic or epigenetic, where phenotypic clocks use easily measurable clinical biomarkers and epigenetic clocks use cellular methylation data. In recent years, methylation clocks have attained phenomenal performance when predicting chronological age and have been linked to various age-related diseases. Additionally, phenotypic clocks have been proven to be able to predict mortality better than chronological age, providing intracellular insights into the aging process. This review aimed to systematically survey all proposed epigenetic and phenotypic clocks to date, excluding mitotic clocks (i.e., cancer risk clocks) and those that were modeled using non-human samples. We reported the predictive performance of 33 clocks and outlined the statistical or machine learning techniques used. We also reported the most influential clinical measurements used in the included phenotypic clocks. Our findings provide a systematic reporting of the last decade of biological clock research and indicate possible avenues for future research.

用于人类衰老和死亡率量化的表型和表观遗传时钟的系统回顾。
衰老是人类疾病的主要驱动因素,对死亡率有着深远的影响。生物钟被用来测量衰老过程,希望能找出可能的干预措施。生物钟可分为表型生物钟和表观遗传生物钟,表型生物钟使用易于测量的临床生物标志物,而表观遗传生物钟则使用细胞甲基化数据。近年来,甲基化钟在预测年龄方面取得了惊人的成就,并与各种与年龄相关的疾病联系在一起。此外,表型时钟已被证明能比计时年龄更好地预测死亡率,从而提供了对衰老过程的细胞内洞察。本综述旨在系统调查迄今为止提出的所有表观遗传学时钟和表型时钟,但不包括有丝分裂时钟(即癌症风险时钟)和使用非人类样本建模的时钟。我们报告了 33 个时钟的预测性能,并概述了所使用的统计或机器学习技术。我们还报告了表型时钟中使用的最有影响力的临床测量方法。我们的研究结果系统地报告了过去十年的生物钟研究,并指出了未来研究的可能途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Aging-Us
Aging-Us CELL BIOLOGY-
CiteScore
10.00
自引率
0.00%
发文量
595
审稿时长
6-12 weeks
期刊介绍: Information not localized
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