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

项目摘要 以失眠、睡眠时间短和阻塞性睡眠呼吸暂停等表型为特征的次优睡眠， 与认知能力下降、认知能力下降和痴呆风险增加有关。有 种族/民族和性别少数群体之间睡眠差异的有力证据，可能与以下因素有关： 认知老化的下游差异。然而，睡眠表型加速的机制 认知老化还没有被很好地理解。识别睡眠的特定生物学途径和生物标志物 表型将使睡眠表型对认知老化、风险 分层和潜在干预目标的开发。 我们将建立一个跨三个纵向队列研究的合作，代表了美国不同的国家。 人群：社区动脉粥样硬化风险（ARIC）研究，西班牙裔社区健康 研究/拉丁美洲人的研究（HCHS/SOL），和动脉粥样硬化的多民族研究（梅萨），研究如何 睡眠不足会加速认知老化我们将研究睡眠障碍（失眠， 短睡眠和长睡眠，以及阻塞性睡眠呼吸暂停）与协调的，全球认知老化的措施。我们 将使用新的方法开发睡眠表型的多基因风险评分（PRS）， 解释研究个体的异质遗传祖先，并确定睡眠表型， 与认知老化密切相关我们将使用组学（代谢组学和 蛋白质组学）来解释睡眠-认知老化相关的生物学途径。我们预计 我们将确定与认知老化有关的睡眠影响的生物标志物和介质，并使用孟德尔 随机化分析，我们将能够解开一些方向性的关联。最后，我们将研究 使用睡眠相关测量的认知老化风险预测模型。我们将研究是否确定 关联和风险预测模型概括为两个队列数据集中的AD特异性表型， 拉什老年痴呆症中心 这项工作将导致确定组学生物标志物，测量和介导的遗传风险， 睡眠表型对认知老化的影响，以及基于PRS和组学的认知老化新风险模型。 重要的是，我们的研究将包括来自不同美国人群的个体，我们的方法将确保 这些发现和模型对不同人群都有用。这项工作将指导精准医学倡议， 改善来自不同遗传背景的老年人的认知健康。

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.