Personalizing obstructive sleep apnea management: associating symptom subtype to objective sleep traits and physiological biomarkers

摘要 阻塞性睡眠呼吸暂停（OSA），以反复部分（呼吸不足）和完全（呼吸暂停）阻塞为特征 睡眠中的上呼吸道疾病，是一个广泛的诊断类别，具有复杂的病理生理学和可变的 临床表现。使用聚类分析技术，我们最近确定了三种不同的OSA亚型， 根据主要症状：（1）失眠（表现为睡眠困难，白天嗜睡）; (2)过度嗜睡（白天表现为过度嗜睡，但很少抱怨 睡眠障碍）;和（3）症状轻微。目前，气道正压通气（PAP）是一线 所有OSA患者的治疗，无论症状表现如何。PAP有望改善症状 但是，50-72%的共病失眠患者和18-55%的睡眠障碍患者 患者在PAP治疗后仍有残留症状，表明症状存在个体差异 对一线治疗的反应和对继发症状管理策略的迫切需求。更好 了解3种症状亚型的生理机制和区别治疗 反应将为未来的个性化二级治疗提供信息，包括行为和药理学 干预措施。目前的建议将直接评估这些机制使用现有的临床样本， 来自世界各地的多个睡眠中心和一个新招募的前瞻性样本。一是 在一个大型数据库中调查诊断时症状亚型的潜在生理特征， OSA患者（n = 853）从睡眠呼吸暂停全球跨学科联盟（SAGIC）招募。第二、 我们将前瞻性招募和随访新患者（n = 360，每种亚型n = 120），以验证这些 基线生理特征，识别对一线PAP治疗的症状反应模式，和 评估每个亚型内症状反应的生理和临床预测因素。更好地 表征生理和临床签名，我们将利用新的脑电图（EEG）衍生 变量，包括产品的比值比（ORP，睡眠深度的连续指数），以及传统的 多导睡眠图（PSG）对于前瞻性观察性研究，诊断和随访PSG PAP治疗3个月后，将在所有参与者中进行。此外，2周的活动记录和睡眠 将使用问卷来捕获在家睡眠的特征和行为。将评估症状 在诊断和每月随访时。我们还将获得并储存空腹血液样本，用于生物标志物， 组学（即，基因组学、蛋白质组学和代谢组学）研究，以探索分子和生物学机制 阻塞性睡眠呼吸暂停综合征的症状亚型总的来说，这项研究将帮助我们了解 OSA症状亚型和更好治疗反应的预测因子结果将告知未来的症状 根据患者的生理和临床信息，为每个亚组制定个性化的管理策略。

ABSTRACT Obstructive sleep apnea (OSA), characterized by repeated partial (hypopnea) and complete (apnea) obstruction of the upper aiways during sleep, is a broad diagnostic category with its complex phathophysiology and variable clinical presentations. Using cluster-analysis techniques, we recently identified three distinct OSA subtypes, based on predominant symptoms: (1) Insomnia (presenting with difficulty sleeping with little daytime sleepiness); (2) Excessively sleepy (presenting with excessive drowsines during the daytime, but few complaints about disturbed sleep); and (3) Minimally Symptomatic. Currently, Positive Airway Pressure (PAP) is the first-line treatment for all OSA patients, regardless of the symptom presentation. PAP is expected to improve symptoms by eliminating respiratory events; however, 50-72% of patients with comorbid insomnia and 18-55% of Sleepy patients still suffer from residual symptoms after PAP treatment, suggesting individual differences in symptom responses to the first-line treatment and a critical need for secondary symptom management strategies. Better understanding of physiological mechanisms underlying the 3 symptom subtypes and differential treatment responses will inform future personalized secondary treatments, including behavioral and pharmacologic interventions. The current proposal will directly evaluate these mechanisms using both an existing clinical sample from multiple sleep centers throughout the world and a newly recruited prospective sample. First, we will investigate the underlying physiological signatures of the symptom subtypes at diagnosis in a large database of OSA patients (n = 853) recruited from the Sleep Apnea Global Interdisciplinary Consortium (SAGIC). Second, we will prospectively recruit and follow new patients (n = 360, n = 120 for each subtype) to validate these physiological signatures at baseline, identify patterns of symptom responses to the first-line PAP treatment, and evaluate the physiological and clinical predictors of symptom response within each subtype. To better characterize physiological and clinical signatures, we will leverage novel electroencephalogram (EEG)-derived variables, including the odds ratio of product (ORP, a continuous index of sleep depth), as well as conventional measures from polysomnography (PSG). For the prospective observational study, diagnostic and follow-up PSG after 3 months of PAP treatment will be conducted in all participants. In addition, 2-week actigraphy and sleep questionnaires will be used to capture at-home sleep characteristics and behaviors. Symptoms will be assessed at diagnosis and monthly over follow-up. We will also obtain and bank fasting blood samples for biomarker and Omics (i.e., genomics, proteomics, and metabolomics) studies to explore molecular and biological mechanisms of OSA symptom subtypes in the future. Overall, this study will help us understand the underlying physiology of OSA symptom subtypes and predictors of better treatment response. Results will inform future symptom management strategies, personalized by patients' physiological and clinical information, for each subgroup.