QUANTITATIVE ASSESSMENT OF BIOLOGICAL AGE AND ITS APPLICATIONS

生物年龄的定量评估及其应用

• 批准号: 10225348
• 负责人: Vadim N. Gladyshev
• 金额: $ 63.09万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10225348
• 关键词: Address; Age; Aging; Animals; Basic Science; Behavior Therapy; Biological; Biological Aging; Biological Markers; Biology; Biology of Aging; Blood specimen; Caloric Restriction; Categories; Cell Aging; Cell Culture Techniques; Cells; Chronology; Communities; Consensus; Cultured Cells; DNA Damage; DNA Methylation; Data; Development; Epigenetic Process; Exhibits; Future; Gene Expression; Generations; Genetic; Geroscience; Goals; Health; Human; In Vitro; Individual; Intervention; Link; Longevity; Measures; Methylation; Mitochondria; Modeling; Molecular; Monitor; Mus; Organ; Organism; Outcome; Pharmacology; Phenotype; Physiological; Process; Reaction; Recommendation; Reporting; Research; Research Personnel; Resources; Sampling; Series; Signal Transduction; System; Testing; Therapeutic; Time; Tissues; Training; Validation; age related; base; cohort; dietary; dietary restriction; healthspan; in vivo; intervention effect; mimetics; mitochondrial dysfunction; molecular marker; mortality; mouse model; novel; novel therapeutics; phenotypic data; practical application; prognostic; response; screening; senescence; tool

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.

抽象的 量化衰老是老年科学研究的一个主要目标，因为可靠的衰老标志物的可用性可以 促进对衰老的基本生物学的理解，能够跟踪不同情况下的衰老过程 组织和细胞系统，并支持识别和验证延长寿命和 传统上，衰老是通过以下实际年龄、死亡率、年龄相关性来监测的。 基因表达和/或其他分子特征的变化，然而，目前尚未达成共识 定量跟踪衰老进展的最佳实践最近出现的基于生物标记物。 先进的组学方法，例如 DNA 甲基化，为支持基因组学的发展提供了一些希望。 然而，大多数此类测量都是经过训练的。 按时间顺序排列的年龄预测因子，几乎没有整合生物学、功能或表型数据。 基于 DNA 甲基化的衰老测量方法的可修改性，以响应寿命和健康寿命的延长 我们建议通过制定一系列措施来应对这些挑战。 通过整合表型和功能衰老的信息，研究关联，开发新型 DNA 甲基化时钟 DNA 甲基化与衰老标志之间的关系，并评估 DNA 甲基化对长寿的反应 我们建议这些时钟将为老年科学界提供急需的资源。 我们将使用三种通用方法来开发这些时钟，首先，我们将使用培养细胞 (MEF) 进行诱导。 或者建立三个众所周知的衰老标志的模型——细胞衰老、DNA 损伤和 然后，我们将训练这些标志的表观遗传预测因子并在体内验证它们。 我们还将建立表观遗传改变，以响应新的和既定的长寿干预措施。 因此，我们将开发干预反应的生物标志物，可用于测试模仿和/或优化衰老 最后，以 C57Bl/6 和 UM-HET3 动物的高度特征化 SLAM 群体为基础，我们将 产生整个生命周期的纵向甲基化数据，可用于开发表观遗传时钟 我们发现这些新的时钟将更好地捕捉生物信息。 鉴于它们是为了捕捉相关的不同方面而开发的。 随着衰老过程的进行，它们可以结合起来创建一个更具有生物学信息的单一衰老测量方法 并与现有的表观遗传时钟进行比较。