QUANTITATIVE ASSESSMENT OF BIOLOGICAL AGE AND ITS APPLICATIONS

摘要 量化衰老是老年科学研究的一个主要目标，因为可靠的衰老标记物的可用性可以 促进了解衰老的基本生物学，使追踪不同年龄的衰老过程成为可能 组织和细胞系统，并支持识别和验证可延长寿命和 健康跨度。传统上，通过按年龄、死亡率、与年龄相关的时间顺序监测老龄化 然而，关于基因表达和/或其他分子特征的变化，目前还没有达成共识 通过老化定量跟踪进展的最佳实践。生物标志物的最新问世 先进的组学方法，如DNA甲基化，为支持 对人类和老鼠的年龄进行了精确的估计。尽管如此，大多数这类措施都是经过培训的 时间顺序的年龄预测，很少或根本没有整合生物学、功能或表型数据。此外， 基于DNA甲基化的衰老措施对寿命和健康延长的可修饰性 干预措施几乎是完全未知的。我们建议通过制定一系列 整合表型和功能老化信息，研究连接的新DNA甲基化时钟 DNA甲基化和衰老特征之间的关系，以及评估DNA甲基化对长寿的反应 干预措施。我们建议，这些时钟将为老年科学界提供急需的资源。 我们将使用三种一般方法来开发这些时钟。首先，我们将使用培养细胞(MEF)来诱导 或者建立三个众所周知的衰老特征的模型--细胞衰老、DNA损伤和 线粒体失调。然后，我们将训练这些特征的表观遗传学预测因子，并在体内验证它们。 我们还将建立表观遗传学改变，以回应新的和已建立的长寿干预措施。正在做 因此，我们将开发干预反应的生物标记物，可用于测试模拟，和/或优化衰老 生物标志物。最后，在高度特征化的C57BL/6和UM-HET3动物SLAM群体的基础上，我们将 在生命周期内产生纵向甲基化数据，可用于开发表观遗传时钟 可以作为健康寿命的可靠预测指标。我们假设这些新的时钟将更好地捕捉生物 年龄比按年代划分的年龄训练的时钟。考虑到它们的开发目的是捕获相关的不同方面 随着老化过程的进行，它们可以结合在一起，创建更具生物学意义的单一老化测量方法 并与现有的表观遗传学时钟进行了比较。

ABSTRACT Quantifying aging is a major goal in Geroscience research as the availability of a reliable marker of aging can facilitate understanding of the fundamental biology of aging, enable tracking of the aging process in different tissues and cell systems, and support identification and validation of interventions that extend lifespan and healthspan. Traditionally, aging has been monitored by following chronological age, mortality, age-related changes in gene expression, and/or other molecular features, however, there is currently no consensus on the best practices for quantitatively tracking progression through aging. The recent advent of biomarkers based on advanced omics approaches, such as DNA methylation, have provided some hope to support development of precise estimates of age, both in humans and mice. Nevertheless, the majority of such measures are trained as chronological age predictors, with little to no integration of biological, functional, or phenotypic data. Further, the modifiability of aging measures based on DNA methylation in response to lifespan and healthspan extending interventions is almost entirely unknown. We propose to address these challenges by developing a series of novel DNA methylation clocks by integrating information on phenotypic and functional aging, investigating links between DNA methylation and aging hallmarks, and evaluating DNA methylation responses to longevity interventions. We suggest that these clocks will offer a much-needed resource for the Geroscience community. We will develop these clocks using three general approaches. First, we will use cultured cells (MEFs) to induce or establish models of three well-known hallmarks of aging—cellular senescence, DNA damage, and mitochondrial dysregulation. We will then train epigenetic predictors of these hallmarks and validate them in vivo. We will also establish epigenetic alterations in response to novel and established longevity interventions. In doing so, we will develop biomarkers of intervention response that can be used to test mimetics, and/or optimize aging biomarkers. Finally, building on the highly characterized SLAM colony of C57Bl/6 and UM-HET3 animals, we will produce longitudinal methylation data across the lifespan that can be used to develop an epigenetic clock that can serve as a robust predictor of healthspan. We hypothesize that these new clocks will better capture biological age than chronological age trained clocks. Given that they were developed to capture different facets associated with the aging process, they can be combined to create a single aging measure that is more biologically informed and characterized compared to existing epigenetic clocks.