Development of a Predictive Frailty Clock & Longitudinal Investigation of its Epigenetic Determinants

预测衰弱时钟的开发

• 批准号: 10475256
• 负责人: Alice E Kane
• 金额: $ 11.34万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10475256
• 关键词: Acceleration; Age; Age-Months; Aging; Attenuated; Award; Behavior; Behavioral; Biological; Biological Markers; Biology of Aging; Blood; C57BL/6 Mouse; Caloric Restriction; Cessation of life; Chromatin; Chronology; Clinical; Collection; Complete Blood Count; Computer Models; Consumption; DNA; DNA Methylation; Data; Detection; Development; Electrocardiogram; Elements; Epigenetic Process; Female; Fractionation; Gait; Goals; Health; Health Status; Heterogeneity; Histones; Human; Individual; International; Intervention; Investigation; Kinetics; Life; Longevity; Machine Learning; Measures; Mentors; Methodology; Methods; Methylation; Modeling; Molecular; Molecular Weight; Mus; Outcome; Outcome Measure; Pathology; Peptides; Persons; Phase; Phenotype; Physiological; Plasma; Positioning Attribute; Proteins; Reproducibility; Research; Research Personnel; Sampling; Site; Skin Tissue; Statistical Models; Testing; Time; Tissues; Training; Transgenic Organisms; Work; age related; aged; base; career; clinically relevant; cost; cost effective; differential expression; epigenome; frailty; health assessment; healthspan; histone modification; indexing; innovation; liquid chromatography mass spectrometry; machine learning algorithm; machine learning model; male; medical schools; mortality; mouse model; novel; pre-clinical; sex; tool

Project summary/abstract Longevity studies in mice are expensive and time-consuming, and there are currently no measures that can predict mortality in a mouse at an earlier time-point. Additionally, there are very few measures of the overall health of mice that can be assessed longitudinally. In humans, frailty can predict mortality with greater power than the DNA methylation clock. In my early postdoctoral work I have validated a mouse frailty index, that increases with age, is associated with mortality and age-related pathologies, and is sensitive to interventions. In the Sinclair lab I have used machine learning modelling of this mouse frailty index to make the Analysis of Frailty in Death (AFRAID) clock that can predict the lifespan of male C57BL/6 mice aged 21 months or older with accuracy of approximately 1.7 months. We hypothesis that a frailty clock that includes a range of measures including physiological and molecular measures (blood-based Analysis of Frailty in Death, bAFRAID) will accurately predict lifespan in younger, female mice of a different strain. To test this hypothesis I will complete a battery of health assessments, including blood collection for novel peptide biomarker detection, in male and female UM-HET3 mice every 3 months from 15 months of age until death. I will use regression modelling of all measured outcomes to develop an optimized `bAFRAID clock' that predicts time to death in mice. I will complete this part of the project at Harvard Medical School in the lab of Dr David Sinclair, who will act as my mentor and is an internationally recognised expert in the biology of aging. I will receive additional training in biomarker modelling and peptidomics from experts Drs Steve Horvath and Steve Gygi. For the independent phase of this award, I will use longitudinal assessments, and cutting-edge epigenetic tools to investigate the relationship between epigenetic changes and the AFRAID clock. This will increase our understanding of whether epigenetic mechanisms underly the onset of frailty in aging. The completion of this project and the proposed training will position me in an ideal position to achieve my career goal of becoming an independent researcher with a lab focused on understanding the mechanisms of frailty in aging.

项目概要/摘要 在老鼠身上进行的长寿研究既昂贵又耗时，目前还没有 可以预测小鼠在较早时间点的死亡率的措施。另外存在 很少有可以纵向评估小鼠整体健康状况的措施。在 对于人类来说，脆弱可以比DNA甲基化时钟更有效地预测死亡率。在我 早期的博士后工作，我已经验证了小鼠脆弱指数，随着年龄的增长， 与死亡率和年龄相关的病理学有关，对干预措施敏感。在 Sinclair实验室，我使用机器学习建模这个鼠标脆弱指数， 可预测雄性C57 BL/6小鼠寿命的死亡虚弱（AFRAID）时钟分析 年龄在21个月或以上，准确度约为1.7个月。我们假设， 包括一系列测量的脆弱时钟，包括生理和分子测量 （基于血液的死亡虚弱分析，bAFRAID）将准确预测年轻人的寿命， 不同品系的雌性小鼠。为了验证这个假设，我将完成一组健康测试， 评估，包括用于新型肽生物标志物检测的血液采集， 雌性UM-HET 3小鼠从15月龄起每3个月注射一次，直至死亡。我将使用回归 对所有测量结果进行建模，以开发优化的“bAFRAID时钟”， 小鼠死亡时间。我将在2010年的哈佛医学院完成这部分项目。 实验室的大卫辛克莱博士，谁将作为我的导师，是一个国际公认的专家 衰老生物学中最重要的一个我将接受生物标志物建模和肽组学方面的额外培训 来自专家史蒂夫·霍瓦特和史蒂夫·吉吉博士。对于这个奖项的独立阶段，我 将使用纵向评估和尖端的表观遗传工具来调查 表观遗传变化和AFRAID时钟之间的关系。这将增加我们的 了解表观遗传机制是否是衰老脆弱的基础。的 完成这个项目和拟议的培训将使我处于一个理想的位置， 实现我的职业目标，成为一名独立的研究人员，实验室专注于 了解衰老中的脆弱机制。