Dissecting heterogeneity of excessive daytime sleepiness and impact on cardiovascular diseases

剖析白天过度嗜睡的异质性及其对心血管疾病的影响

基本信息

批准号：
10588200
负责人：
Heming Wang
金额：
$ 35.8万
依托单位：
BRIGHAM AND WOMEN'S HOSPITAL
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-20 至 2026-03-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10588200
关键词：
Affect Behavioral Biological Cardiovascular Diseases Cardiovascular system Classification Clinical Communities Data Data Reporting Electroencephalography Excessive Daytime Sleepiness Future Genes Genetic Genetic Diseases Genetic Predisposition to Disease Genomics Goals Health Heterogeneity Hispanic Community Health Study/Study of Latinos Hypersomnolence Idiopathic Hypersomnolence Individual Intervention Jackson Heart Study Knowledge Laboratory Research Link Longitudinal Studies Measurement Measures Mendelian randomization Modification Molecular Morbidity - disease rate Multi-Ethnic Study of Atherosclerosis Multiomic Data Narcolepsy National Heart, Lung, and Blood Institute Outcome Pathway interactions Patient Self-Report Phenotype Physiological Physiology Polysomnography Population Population Heterogeneity Population Study Process Property Proteomics Questionnaires Reporting Resources Risk Risk Factors Sampling Sleep Sleep Architecture Sleep Disorders Sleep Fragmentations Subgroup Testing Trans-Omics for Precision Medicine Variant Women&apos s Health Work actigraphy biobank brain tissue cardiovascular disorder risk clinical risk cohort comorbidity design gene environment interaction genetic analysis genetic variant genome wide association study genome-wide genomic locus improved instrument men metabolomics methylomics mortality neurophysiology novel osteoporosis with pathological fracture population based programs public health intervention risk stratification screening secondary analysis sex trait transcriptomics

项目摘要

ABSTRACT Excessive daytime sleepiness (EDS) affects 10-20% of the population and is associated with cardiovascular diseases (CVD) and mortality. Emerging data suggest that targeting EDS may provide a novel intervention for improving CVD. However, findings are limited by self-reported data and heterogeneity. There is a need to dissect and understand the underlying drivers of EDS subtypes, and to determine whether there are subtypes causally related to CVD and potentially modifiable. Our recent work identified two subtypes of EDS – sleep propensity (SP; characterized by objectively measured long sleep duration, high efficiency, and less fragmentation) and sleep fragmentation (SF; short sleep duration and low efficiency). Each of them is common in the population, associated with adverse cardiovascular outcomes and different genetic backgrounds. We hypothesize that SP is a novel sleep phenotype that reflects a property of the need of staying asleep; dissecting EDS into SP and SF subtypes will facilitate identification of genetic and physiological mechanisms for EDS, and improve understanding of pleiotropic or causal associations with CVD risk. In order to test these hypotheses, we will leverage macro- and micro- sleep architecture measurements, genomics, and other -omics data in population-based cohorts. We will address the following specific aims: 1) To identify demographic, behavioral, clinical and neurophysiological factors (assessed by actigraphy and electroencephalography) for SP and SF, and refine classification of EDS subtypes if needed; 2) To identify genetic variants and molecular pathways associated with EDS subtypes and generate robust polygenetic risk score for risk stratification; 3) To systematically evaluate the causal or non-causal associations between EDS subtypes and CVD traits; 4) To identify the modification effect of each EDS subtype on genetic susceptibility of CVD using gene-environment interaction analyses. This work will advance our understanding of the heterogeneity of EDS, reveal biological mechanisms and pathways linking to CVD, and provide information that will guide clinical and public health interventions as well as provide directions for future laboratory research.

抽象的白天过度嗜睡 (EDS) 影响 10-20% 的人口，并与心血管疾病（CVD）和死亡率的新数据表明，针对 EDS 可能。为改善 CVD 提供了一种新的干预措施，但研究结果受到自我报告的限制。需要剖析和理解 EDS 的根本驱动因素。亚型，并确定是否存在与 CVD 因果关系以及潜在的亚型我们最近的工作确定了 EDS 的两种亚型——睡眠倾向（SP；特征）。通过客观测量睡眠时间长、效率高、碎片少）和睡眠碎片化（SF；睡眠时间短、效率低）。人群，与不良心血管结局和不同的遗传背景相关。我们认为 SP 是一种新颖的睡眠表型，反映了停留需要的属性将 EDS 分解为 SP 和 SF 亚型将有助于识别遗传和 EDS 的生理机制，并提高对多效性或因果关系的理解为了检验这些假设，我们将利用宏观和微观因素。基于人群的队列中的睡眠结构测量、基因组学和其他组学数据。我们将实现以下具体目标：1）确定人口、行为、临床和 SP 和 SF 的神经生理学因素（通过活动记录仪和脑电图评估），并根据需要细化 EDS 亚型的分类； 2) 识别遗传变异和分子与 EDS 亚型相关的途径并生成强大的多基因风险评分分层；3) 系统评估 EDS 之间的因果或非因果关系 4）确定每个EDS亚型对遗传的修饰作用；使用基因-环境相互作用分析对 CVD 的易感性进行研究将推进我们的研究。了解 EDS 的异质性，揭示连接的生物学机制和途径 CVD，并提供指导临床和公共卫生干预措施的信息以及为未来实验室研究提供方向。