Metabolomics of obstructive sleep apnea

阻塞性睡眠呼吸暂停的代谢组学

• 批准号: 10453568
• 负责人: Aalim M Weljie
• 金额: $ 112.73万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2024-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10453568
• 关键词: Address; Apnea; Arousal; Atrial Fibrillation; Automobile Driving; Biological Markers; Blood; Body Weight decreased; Cardiometabolic Disease; Characteristics; Clinic; Clinical; Collaborations; Continuous Positive Airway Pressure; Data; Data Collection; Dementia; Diabetes Mellitus; Disease; Drowsiness; European Union; Fingerprint; Frequencies; Functional disorder; Funding; Future; Glycosylated hemoglobin A; Heart Diseases; Heterogeneity; Hour; Hypertension; Hypoxia; Individual; Insulin Resistance; Link; Malignant Neoplasms; Measures; Metabolic; Metabolism; Methods; Molecular; Monitor; National Heart, Lung, and Blood Institute; Nerve Degeneration; Obesity; Observational Study; Obstructive Sleep Apnea; Occupations; Pathway interactions; Patients; Periodicity; Phenotype; Prevalence; Prospective Studies; Proteomics; Protocols documentation; Publications; Randomized; Recurrence; Research; Research Project Grants; Risk; Risk Factors; Role; Safety; Sampling; Severities; Site; Sleep; Sleep Apnea Syndromes; Sleep Disorders; Sleep Fragmentations; Sleep disturbances; Sleeplessness; Societies; Stroke; Symptoms; Techniques; Treatment Efficacy; United States National Institutes of Health; base; cardiovascular risk factor; case control; causal model; clinical application; clinical care; clinical phenotype; clinical practice; clinical subtypes; design; disease heterogeneity; disorder subtype; epigenomics; improved; indexing; individual patient; insight; metabolic abnormality assessment; metabolomics; mortality; non-alcoholic fatty liver disease; novel; patient population; patient subsets; personalized diagnostics; personalized medicine; positive airway pressure; precision medicine; prognostic; prospective; response; sample collection; sleep regulation; treatment response; weight loss intervention

ABSTRACT Obstructive sleep apnea (OSA) is a common disorder that is increasing in prevalence. OSA is known to have heterogeneous pathophysiology, with different subtypes, clinical consequence, and treatment responses among individual patients. A recent publication from the Sleep Research Society and National Heart, Lung and Blood Institute highlighted the potential clinical utility of quantitative OSA biomarkers identified using unbiased “omics” approaches.There are currently no established quantitative biomarkers that can be used to understand heterogeneity or inform clinical practice. Thus, the present study proposes to utilize metabolomic methods which reflect dynamic responses to hypoxia to identify metabolite signatures in OSA. The overarching hypothesis motivating this proposal is that blood-borne metabolite signatures that result from metabolic insults caused by the cyclical intermittent hypoxia, recurrent arousals and lack of deep sleep characteristic of OSA will provide a quantitative biomarker to better understand disease heterogeneity and inform clinical care. In Aim 1, we will differentiate OSA from non-OSA leveraging well- phenotyped samples carefully chosen from a large pool of patients from existing research projects (Aim 1A). Our preliminary suggest clear metabolite differences between patients with OSA and controls. Furthermore, we will leverage these existing samples to determine if established OSA symptom subtypes of disturbed sleep (e.g., insomnia), excessive sleepiness, and minimally symptomatic have distinct metabolomic profiles (Aim 1B) which will provide insights into identified differences in cardiovascular risk and support a precision medicine approach. These analyses utilizing banked samples are supported by a carefully designed prospective study of OSA patients before and after positive airway pressure (PAP) treatment in Aim 2. The study is designed to control for bias related to site-specific variance in sampling and data collection using state-of-the-art causal modeling techniques. As part of the prospective study, we will perform complementary analyses supporting metabolomic signatures (Aim 2A), determine a metabolomic signature that correlates with hours and days of PAP usage (Aim 2B) and evaluate whether the metabolomic changes with PAP treatment differ by obesity (Aim 2C) or symptom subtype (Aim 2D). In support of this Aim, preliminary data suggest metabolomic changes with PAP treatment.. Finally, in Aim 3 we will leverage existing samples of obese OSA subjects that were previously randomized to one of three treatments – weight-loss alone, PAP alone, or combined weight-loss and PAP. Differences in metabolomic changes among these three randomized groups will provide insights into the relative roles of obesity and cyclical intermittent hypoxia on metabolic responses and pathways. Ultimately, results from this proposal will provide comprehensive information on metabolomic signatures that can be utilized as quantitative biomarkers to further our understanding of OSA heterogeneity and inform clinical practice and personalized medicine among OSA patients. R01 Metabolomics of OSA - Page 1

摘要 阻塞性睡眠呼吸暂停（OSA）是一种常见的疾病，患病率正在增加。已知OSA具有 具有不同亚型、临床后果和治疗异质性病理生理学 个别患者的反应。睡眠研究协会和国家卫生研究院最近发表的一份报告显示， 心脏、肺和血液研究所强调了确定的定量OSA生物标志物的潜在临床效用 使用无偏见的“组学”方法。目前还没有建立的定量生物标志物， 用于了解异质性或告知临床实践。因此，本研究建议利用 代谢组学方法反映了对缺氧的动态反应，以鉴定OSA中的代谢物特征。的 激发这一提议的首要假设是， 由周期性间歇性缺氧、反复觉醒和缺乏深层 睡眠呼吸暂停综合征睡眠特征将为更好地了解疾病提供定量生物标志物 异质性和通知临床护理。在目标1中，我们将很好地区分OSA和非OSA- 从现有研究项目的大量患者中精心挑选表型样本（目标1A）。 我们的初步研究表明，OSA患者和对照组之间存在明显的代谢差异。而且我们 将利用这些现有的样本来确定是否已建立的睡眠紊乱的OSA症状亚型（例如， 失眠）、过度嗜睡和轻微症状具有不同的代谢组学特征（目的1B）， 将提供对心血管风险差异的深入了解，并支持精准医学方法。 这些利用库存样本的分析得到了精心设计的OSA前瞻性研究的支持 目的2：观察气道正压通气（PAP）治疗前后患者的气道阻力变化。该研究旨在控制 使用最先进的因果建模，与采样和数据收集中的站点特定方差相关的偏倚 技术.作为前瞻性研究的一部分，我们将进行补充分析，支持代谢组学 特征（Aim 2A），确定与PAP使用时间和天数相关的代谢组学特征（Aim 2B）并评估PAP治疗的代谢组学变化是否因肥胖（目的2C）或症状而异 Aim 2D亚型。为了支持这一目的，初步数据表明PAP治疗的代谢组学变化。 最后，在目标3中，我们将利用先前随机分配的肥胖OSA受试者的现有样本， 三种治疗方法之一-单独减肥，单独PAP，或联合减肥和PAP。差异 这三个随机分组之间的代谢组学变化将提供对以下相对作用的见解： 肥胖和周期性间歇性缺氧对代谢反应和途径的影响。最终，结果 提案将提供关于代谢组学特征的全面信息， 定量生物标志物，以进一步了解OSA异质性并为临床实践提供信息 和个体化用药的能力。 R 01 OSA的代谢组学-第1页