Molecular mechanisms and social constructs: How genes and environment regulate the rate of aging

分子机制和社会结构：基因和环境如何调节衰老速度

• 批准号: 9551142
• 负责人: Morgan Elyse Levine
• 金额: $ 24.9万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-03-01 至 2020-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9551142
• 关键词: Achievement; Age; Aging; Aging-Related Process; Animal Model; Attenuated; Behavioral; Biochemical; Bioinformatics; Biological Aging; Biology; Biology of Aging; Biometry; Blood; Cardiovascular Diseases; Cessation of life; Chronic; Complex; Computer Simulation; Data; Data Analyses; Deceleration; Development; Diabetes Mellitus; Disease; Environment; Environmental Risk Factor; Epigenetic Process; Genes; Genetic; Genetic Transcription; Goals; Human; Incidence; Individual; Information Networks; Intervention; Knowledge; Laws; Lead; Life Expectancy; Literature; Longevity; Lung diseases; Malignant Neoplasms; Maps; Measures; Mediating; Medical; Medicine; Mentorship; Methylation; Modeling; Molecular; Molecular Genetics; Morbidity - disease rate; NF-kappa B; Network-based; Neurodegenerative Disorders; Onset of illness; Ontology; Outcome; Outcome Measure; Pathway Analysis; Pathway interactions; Phase; Physiological Processes; Policies; Politics; Population; Predisposition; Prevalence; Prevention strategy; Primary Prevention; Process; Quantitative Genetics; Research; Research Personnel; Risk; Risk Assessment; Science; Signal Transduction; Smoker; Socioeconomic Status; System; Techniques; Testing; Time; Training; Variant; Work; age effect; age related; base; disorder risk; effective intervention; frailty; genetic profiling; genetic signature; genetic variant; genome wide methylation; high dimensionality; immune function; improved; insight; insulin signaling; low socioeconomic status; mTOR Signaling Pathway; medical schools; mortality; network models; never smoker; novel; novel strategies; population health; repaired; sarcopenia; social; social genomics; telomere

PROJECT ABSTRACT Physiological processes are carried out by multiple interacting systems, or networks. With aging, these networks lose the ability to function properly, causing dysregulation—network interactions and connectivity degrade as nodes are no longer able to respond to signals from one another. As a result, individual variations in the rate of aging give rise to differences in disease onset, functioning decline, and life expectancy. It has been suggested that the only way to extend healthy lifespan in humans is by slowing the aging process. Thus, identifying the gene networks and environmental components (and their interactions) which alter the rate of aging is essential for improving the health of the population. The goal of the proposed project is to use systems medicine approaches to identify genetic variants, molecular signals, and social/behavioral factors associated with differences in the rate of aging. More specifically, during the K99 phase, the aim of this project is to identify network-based genetic signatures for human healthspan. To accomplish this research goal, the K99 phase will involve training in biomedical sciences, high- dimensional omics data analysis, network analysis, and social genomics. This training will take place at the UCLA David Geffen School of Medicine in the departments of statistical genetics and biostatistics, under the mentorship of Dr. Steve Horvath (bioinformatics, quantitative genetics, network analysis), Dr. Steve Cole (social genomics, computational modeling, biochemical analyses, molecular genetics), and Dr. Rita Effros (biology of aging, immune function, telomere biology). Building on the training during the K99, the goal of the R00 phase will be to: 1) Model transcriptional drift (dysregulation) in humans and test whether it is associated with aging- related disease prevalence or social factors; and 2) Identify age-related genome-wide methylation changes (in blood) that mediate the association between morbidity and socioeconomic status. Aging is a highly complex and multidimensional process, which is influenced by factors ranging from gene variants to social/political policies. This complexity, has presented a challenge for researchers whose goals are to uncover the regulators of biological aging. This proposal presents a truly novel approach for both modeling the aging process and examining factors which alter it. The studies performed during the K99 and R00 phases will advance our understanding of how gene networks and social factors influence the pace of human aging. Additionally, this project will identify molecular signals of aging and transcriptional drift that accumulate with time, and which subsequently give rise to morbidity and mortality. Understanding the molecular and environmental regulators of biological aging is essential for developing effective interventions that slow the aging process and increase healthy life expectancy. This knowledge will also improve risk assessment in relation to multiple-aging related conditions, and aid primary prevention strategies by identifying at-risk groups.

项目摘要 生理过程由多个相互作用的系统或网络进行。随着年龄的增长， 网络失去正常运作的能力，导致网络相互作用和连通性失调 因为节点不再能够响应来自彼此的信号而降级。因此，个体差异 老龄化速度导致疾病发作、功能衰退和预期寿命的差异。已经 认为延长人类健康寿命的唯一方法是减缓衰老过程。因此，在本发明中， 确定改变衰老速度的基因网络和环境成分（及其相互作用） 对改善人民健康至关重要。 拟议项目的目标是使用系统医学方法来识别遗传变异， 分子信号和与衰老速度差异相关的社会/行为因素。更具体地说， 在K99阶段，该项目的目标是识别人类基于网络的遗传特征， healthspan.为了实现这一研究目标，K99阶段将涉及生物医学科学的培训， 维度组学数据分析、网络分析和社会基因组学。本次培训将在 加州大学洛杉矶分校大卫格芬医学院的统计遗传学和生物统计学系，根据 导师：Steve Horvath博士（生物信息学、定量遗传学、网络分析）、Steve科尔博士（社会 基因组学，计算建模，生化分析，分子遗传学），和丽塔埃弗罗斯博士（生物学 衰老、免疫功能、端粒生物学）。在K99培训的基础上，R 00阶段的目标是 将是：1）模型转录漂移（失调）在人类和测试是否与衰老有关- 相关疾病患病率或社会因素;以及2）鉴定年龄相关的全基因组甲基化变化（在 血液），介导发病率和社会经济地位之间的关联。 衰老是一个高度复杂的多方面过程，它受到基因、年龄、性别等多种因素的影响， 社会/政治政策的变化。这种复杂性对研究人员提出了挑战，他们的目标是 来揭示生物衰老的调节因子该提案提出了一种真正新颖的方法， 在K99和R 00阶段进行的研究 将促进我们对基因网络和社会因素如何影响人类衰老速度的理解。 此外，该项目还将确定随着时间的推移而积累的衰老和转录漂移的分子信号， 并且随后引起发病率和死亡率。了解分子和环境 生物老化的调节剂对于开发减缓老化过程的有效干预措施至关重要， 提高健康预期寿命。这些知识也将改善与多重老化有关的风险评估 相关的条件，并通过确定风险群体来帮助初级预防战略。