Mechanisms that Account for Different Symptom Subtypes of OSA

摘要 阻塞性睡眠呼吸暂停（OSA）是一种常见的、可遗传的、严重的医学疾病， 一系列不利的健康后果。阻塞性睡眠呼吸暂停综合征表现出一系列不同的症状， 其特征在于过度嗜睡、睡眠紊乱和缺乏传统症状的程度。此外，本发明还 下游疾病风险因症状亚型而异。例如，增加的心血管风险由 OSA是由过度嗜睡亚型的患者驱动的，突出了这种症状的重要性。这 项目建立了OSA症状亚型的存在和相关性，并寻求扩大 通过了解生理学知识，遗传结构和多组学签名相关 OSA症状亚型，特别关注过度嗜睡。Aim 1利用传统和新颖 基于脑电图（EEG）的指标，以评估对OSA的生理反应是否存在差异 解释不同的症状表现。先前的数据表明不同亚型的患者有相似的呼吸暂停- 低通气指数（AHI），但尚未详细检查其他生理特征。Aim 2用途 现有的数据资源，以检查潜在的常见和罕见的频率遗传变异相关的 OSA症状亚型、过度嗜睡的定量测量和OSA的生理特征 症状亚型。以前的研究和我们自己的初步数据已经确定了几个基因座遗传风险基因座 并强调甲基化组、转录组和 代谢组学谱与OSA和相关症状。因此，目标3将采用综合方法将联合收割机 测序数据与来自NHLBI的TOPMed计划的多组学数据，以确定潜在的致病基因， 遗传风险基因座影响OSA症状亚型和风险因素的生物学途径。 我们提出了一种有效和具有成本效益的方法来确定生理，遗传和其他Omic预测因子 阻塞性睡眠呼吸暂停综合征的症状亚型和过度嗜睡。最终，结果将通过连接 遗传变异的生物机制和生理指标，从而提高我们的科学 同时为早期和精确的干预确定新的预测因子和生物靶点。的 国家睡眠障碍研究中心（NCSDR）最近确定了高优先级的关键机会 帮助实现其战略目标，包括确定睡眠障碍的生物标志物和使用组学方法 来推进精准医疗该项目直接涉及这些机会。

ABSTRACT Obstructive sleep apnea (OSA) is a common, heritable, and serious medical condition associated with a wide range of adverse health consequences. OSA presents with a heterogeneous set of symptoms that form subtypes characterized by degrees of excessive sleepiness, disturbed sleep, and a lack of traditional symptoms. Further, downstream disease risk differs by symptom subtypes. For example, increased cardiovascular risk conferred by OSA is driven by patients in the excessively sleepy subtype, highlighting the importance of this symptom. This Project builds off the established existence and relevance of OSA symptom subtypes, and seeks to expand knowledge by understanding the physiology, genetic architecture and multi-Omics signatures associated with OSA symptom subtypes, with a particular focus on excessive sleepiness. Aim 1 leverages traditional and novel electroencephalographic (EEG)-based metrics to assess whether differences in the physiologic response to OSA explain different symptom manifestations. Prior data suggest patients in different subtypes have similar apnea- hypopnea index (AHI), but there has not been a detailed examination of other physiological traits. Aim 2 uses existing data resources to examine the underlying common and rare frequency genetic variation associated with OSA symptom subtypes, a quantitative measure of excessive sleepiness, and physiological features of OSA symptom subtypes. Previous studies and our own preliminary data have identified several loci genetic risk loci for OSA and sleepiness, and highlight a possible relationship of changes in methylomic, transcriptomic, and metabolomic profiles with OSA and related symptoms. Thus, Aim 3 will apply integrative methods to combine sequencing data with multi-Omics data from NHLBI's TOPMed Program to identify potential causal genes and biological pathways through which genetic risk loci operate to affect OSA symptom subtypes and risk factors. We propose an efficient and cost-effective approach to identify physiological, genetic and other Omic predictors of OSA symptom subtypes and excessive sleepiness. Ultimately, results will move the field forward by connecting genetic variation to biological mechanisms and physiological indicators, thus improving our scientific understanding while identifying new predictors and biological targets for early and precise interventions. The National Center on Sleep Disorders Research (NCSDR) has recently identified high priority critical opportunities to help reach its strategic goals, including identifying biomarkers for sleep disorders and using Omics approaches to advance precision medicine. This Project speaks directly to these opportunities.