Using polygenic risk scores and omics to study how suboptimal sleep accelerates cognitive aging in diverse populations

使用多基因风险评分和组学研究次优睡眠如何加速不同人群的认知衰老

• 批准号: 10735647
• 负责人: Tamar Sofer
• 金额: $ 95.95万
• 依托单位: BETH ISRAEL DEACONESS MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-20 至 2028-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10735647
• 关键词: Acceleration; Aging; Alzheimer' s Disease; Alzheimer' s disease related dementia; Atherosclerosis Risk in Communities; Biological; Biological Markers; Clinical Research; Cognitive; Cognitive aging; Collaborations; Data; Data Set; Dementia; Development; Disease; Disease Progression; Disparity; Ensure; Ethnic Origin; Gender; Gene Expression; Genetic; Genetic Determinism; Genetic Predisposition to Disease; Genetic Risk; Genetic study; Health; Hispanic Community Health Study; Hispanic Community Health Study/Study of Latinos; Impaired cognition; Individual; Intervention; Investments; Latino Population; Longitudinal cohort study; Measures; Mediating; Mediation; Mediator; Mendelian randomization; Methodology; Modeling; Multi-Ethnic Study of Atherosclerosis; Obstructive Sleep Apnea; Pathway interactions; Phenotype; Population; Population Heterogeneity; Precision Medicine Initiative; Process; Proteomics; Race; Risk; Risk Factors; Sample Size; Sampling; Sleep; Sleep Apnea Syndromes; Sleep Disorders; Sleeplessness; Structure; United States National Institutes of Health; Work; biomarker identification; cognitive change; cognitive function; cognitive performance; cohort; cost effective; dementia risk; ethnic minority; gender minority; genetic predictors; genome wide association study; improved; metabolomics; novel; polygenic risk score; precision medicine; racial minority; research study; risk prediction model; risk stratification

PROJECT SUMMARY Suboptimal sleep, characterized by phenotypes such as insomnia, short sleep, and obstructive sleep apnea, is associated with reduced cognitive performance and increased cognitive decline and dementia risk. There is strong evidence of sleep disparities between race/ethnic and gender minorities, potentially relating to downstream disparities in cognitive aging. However, the mechanisms by which sleep phenotypes accelerate cognitive aging are not well understood. Identifying specific biological pathways and biomarkers of sleep phenotypes will enable unconfounded quantification of the effect of sleep phenotypes on cognitive aging, risk stratification, and development of potential intervention targets. We will establish a collaboration across three longitudinal cohort studies representing the diverse U.S. population: the Atherosclerosis Risk In Communities (ARIC) study, the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), and the Multi-Ethnic Study of Atherosclerosis (MESA), to study how suboptimal sleep accelerates cognitive aging. We will study the associations of sleep disorders (insomnia, short and long sleep, and obstructive sleep apnea) with harmonized, global measures of cognitive aging. We will develop polygenic risk scores (PRSs) for sleep phenotypes using novel methodology, that will appropriately account for heterogeneous genetic ancestry of study individuals, and identify sleep phenotypes that are genetically strongly associated with cognitive aging based on PRSs. We will use omics (metabolomics and proteomics) to explain biological pathways underlying the sleep-cognitive aging associations. We expect that we will identify biomarkers and mediators of the sleep-related effects on cognitive aging, and using Mendelian Randomization analyses, we will be able to untangle some of the directional associations. Finally, we will study risk prediction models for cognitive aging that use sleep-related measures. We will study whether the identified associations and risk prediction models generalize to AD-specific phenotypes in datasets of two cohorts from the Rush Alzheimer's Disease Center. This work will result in the identification of omics biomarkers that measure and mediate the genetic risk of sleep phenotypes on cognitive aging, and new risk models for cognitive aging based on PRSs and omics. Importantly, our study will include individuals from diverse U.S. populations, and our methodology will ensure that the findings and models are useful across populations. This work will guide precision medicine initiatives to improve cognitive health in aging individuals from diverse genetic backgrounds.

项目摘要 次级睡眠，其特征是失眠，睡眠短和阻塞性睡眠呼吸暂停等表型 与认知能力降低以及认知能力下降和痴呆症风险的增加有关。有 种族/种族和性别少数群体之间睡眠差异的有力证据，可能与 认知衰老的下游差异。但是，睡眠表型加速的机制 认知衰老尚不清楚。识别特定的生物学途径和睡眠生物标志物 表型将使睡眠表型对认知衰老的影响无关量化，风险 分层和潜在干预目标的发展。 我们将在三项代表美国多样化的纵向队列研究中建立合作。 人口：社区的动脉粥样硬化风险（ARIC）研究，西班牙裔社区健康 拉丁美洲人（HCHS/SOL）的研究/研究和动脉粥样硬化的多种族研究（MESA），以研究如何研究 次优睡眠会加速认知衰老。我们将研究睡眠障碍的关联（失眠， 短而长的睡眠和阻塞性睡眠呼吸暂停），具有统一的全球认知衰老量度。我们 将使用新方法发展为睡眠表型的多基因风险评分（PRS），这将适当 考虑研究个体的异质遗传血统，并确定睡眠表型 基于PRS的认知衰老在遗传上密切相关。我们将使用OMICS（代谢组学和 蛋白质组学）解释了睡眠认知衰老关联的基础生物学途径。我们期望这一点 我们将确定与睡眠相关的对认知衰老影响的生物标志物和介体，并使用Mendelian 随机分析，我们将能够解开一些方向关联。最后，我们将学习 使用与睡眠相关的措施的认知老化的风险预测模型。我们将研究确定的 关联和风险预测模型在两个同类的数据集中推广到来自AD的表型 阿尔茨海默氏病中心。 这项工作将导致鉴定Omics生物标志物，以测量和介导 认知衰老的睡眠表型以及基于PRS和OMICS的认知衰老的新风险模型。 重要的是，我们的研究将包括来自美国不同人群的个人，我们的方法将确保 发现和模型在人群中很有用。这项工作将指导精确医学计划 改善来自不同遗传背景的老龄化个体的认知健康。