Mechanisms that Account for Different Symptom Subtypes of OSA

OSA 不同症状亚型的机制

• 批准号: 10555811
• 负责人: Anne Justice
• 金额: $ 22.19万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-01 至 2028-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10555811
• 关键词: Affect; Apnea; Arousal; Biological; Biological Models; Cardiac health; Cells; Clinical; Communities; DNA Methylation; Data; Diagnosis; Drowsiness; Electroencephalography; Epigenetic Process; Frequencies; Gene Expression; Genetic; Genetic Risk; Genetic Variation; Genomic Segment; Genomics; Goals; Health; Heritability; Hispanic; Individual; Intervention; Investigation; Knowledge; Laboratories; Maps; Measures; Medical; Medicine; Meta-Analysis; Metabolic; Methodology; Methods; Molecular; Multiomic Data; National Heart, Lung, and Blood Institute; Obstructive Sleep Apnea; Odds Ratio; Outcome; Pathway interactions; Patient Self-Report; Patients; Persons; Phenotype; Physiological; Physiology; Polysomnography; Predictive Factor; Reproducibility; Research; Risk; Risk Factors; Sampling; Severity of illness; Signal Transduction; Sleep; Sleep Apnea Syndromes; Sleep Architecture; Sleep Disorders; Sleep Stages; Sleep disturbances; Snoring; Staging; Symptoms; Testing; Trans-Omics for Precision Medicine; Visual; Work; biomarker identification; cardiovascular risk factor; causal variant; cohort; cost effective; data resource; disorder risk; experience; follow-up; genetic analysis; genetic architecture; genetic risk factor; genetic variant; genome wide association study; genome-wide; genomic locus; improved; in silico; indexing; insight; metabolomics; methylomics; multiple omics; novel; polygenic risk score; precision medicine; programs; response; risk variant; sleep pattern; sleep physiology; trait; transcriptomics

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.

抽象的 阻塞性睡眠呼吸暂停（OSA）是一种常见，可遗传和严重的医疗状况 不良健康后果范围。 OSA呈现形成亚型的异质症状 其特征是过度嗜睡，睡眠不足和缺乏传统症状的特征。更远， 下游疾病风险因症状亚型而异。例如，增加的心血管风险增加 OSA是由过度困倦的亚型中的患者驱动的，强调了这种症状的重要性。这 项目建立在OSA症状亚型的既定存在和相关性，并试图扩展 通过理解与生理学，遗传结构和多摩学特征相关的知识 OSA症状亚型，特别关注过度嗜睡。目标1利用传统和新颖 基于脑电图（EEG）的指标，以评估生理反应的差异是否对OSA的差异 解释不同的症状表现。先前的数据表明，不同亚型的患者的呼吸暂停相似 呼吸道指数（AHI），但尚未对其他生理特征进行详细的检查。 AIM 2用途 现有的数据资源来检查与 OSA症状亚型，过度嗜睡的定量度量以及OSA的生理特征 症状亚型。先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 对于OSA和嗜睡，并强调了甲基甲基，转录组和 具有OSA和相关症状的代谢组谱。因此，AIM 3将采用集成方法来组合 使用NHLBI顶级程序中的多摩学数据对数据进行测序，以识别潜在的因果基因和 遗传风险基因基因座影响OSA症状亚型和危险因素的生物学途径。 我们提出了一种有效且具有成本效益的方法来识别生理，遗传和其他OMIC预测因子 OSA症状亚型和过度嗜睡。最终，结果将通过连接来向前移动该领域 对生物学机制和生理指标的遗传变异，从而改善了我们的科学 在确定早期和精确干预措施的新预测因素和生物学目标的同时。这 国家睡眠障碍研究中心（NCSDR）最近确定了高优先级关键机会 帮助实现其战略目标，包括识别睡眠障碍的生物标志物和使用OMICS方法 推进精确医学。该项目直接讲述了这些机会。