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

项目总结 以失眠、睡眠不足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、认知衰退和痴呆症风险增加有关。的确有 种族/族裔和性别少数群体之间存在睡眠差距的强有力证据，可能与 认知老化的下游差异。然而，睡眠表型加速的机制 人们对认知老化的认识还不是很清楚。识别睡眠的特定生物途径和生物标记物 表型将能够明确量化睡眠表型对认知老化、风险的影响 分层，并开发潜在的干预目标。 我们将在代表不同美国人的三项纵向队列研究中建立合作。 人口：社区动脉粥样硬化风险(ARIC)研究，西班牙裔社区健康 拉丁美洲人研究/研究(HCHS/SOL)和动脉粥样硬化多民族研究(MESA)，以研究如何 睡眠质量不佳会加速认知老化。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)，采用协调的全球认知老化测量方法。我们 将使用新的方法开发睡眠表型的多基因风险评分(PRSS)，这将适当地 解释研究个体的不同遗传祖先，并识别符合以下条件的睡眠表型 基因上与基于PRSS的认知老化密切相关。我们将使用组学(代谢组学和 蛋白质组学)来解释睡眠-认知衰老关联的生物学途径。我们期待着 我们将识别睡眠对认知老化的相关影响的生物标志物和中介，并使用孟德尔 随机化分析，我们将能够解开一些方向性的联系。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。我们会研究是否已确定 关联和风险预测模型概括为来自以下两个队列的数据集中特定于AD的表型 拉什阿尔茨海默氏症中心。 这项工作将导致识别组学生物标记物，以衡量和中介遗传风险 认知老化的睡眠表型，以及基于PRSS和组学的认知老化的新风险模型。 重要的是，我们的研究将包括来自不同美国人群的个人，我们的方法将确保 这些发现和模型在人群中是有用的。这项工作将指导精准医疗倡议 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.