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(低呼吸暂停)和完全(呼吸暂停)阻塞为特征 在睡眠中的上半身，是一个广泛的诊断类别，其复杂的生理和变量 临床表现。利用聚类分析技术，我们最近确定了三种不同的OSA亚型， 根据主要症状：(1)失眠(表现为入睡困难，白天嗜睡)； (2)过度困倦(白天嗜睡过度，但很少抱怨 睡眠障碍)；以及(3)症状轻微。目前，气道正压(PAP)是一线 治疗所有阻塞性睡眠呼吸暂停综合症患者，无论其症状如何。PAP有望改善症状 通过消除呼吸事件；然而，50%-72%的失眠患者和18%-55%的嗜睡患者 患者在PAP治疗后仍有残留症状，这表明症状存在个体差异。 对一线治疗的反应和对继发性症状管理战略的迫切需要。更好 三种证候亚型的生理机制及辨证论治 回应将为未来的个性化二次治疗提供信息，包括行为和药物治疗 干预措施。目前的建议将使用现有的临床样本直接评估这些机制 来自世界各地的多个睡眠中心和一个新招募的预期样本。首先，我们将 在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)，来自睡眠呼吸暂停全球跨学科联盟(SAGIC)。第二, 我们将前瞻性地招募和跟踪新患者(每种亚型360人，120人)来验证这些 基线的生理特征，确定对一线PAP治疗的症状反应模式，以及 评估每个亚型中症状反应的生理和临床预测因子。为了更好地 为了表征生理和临床特征，我们将利用新的脑电(EEG)来源 变量，包括乘积的优势比(ORP，睡眠深度的连续指数)，以及传统的 多导睡眠图(PSG)测量。用于前瞻性观察研究、诊断和随访PSG 在3个月的PAP治疗后，所有参与者都将接受治疗。此外，两周的活动和睡眠 调查问卷将被用来捕捉在家睡眠的特征和行为。将对症状进行评估 在诊断时和每月超随访。我们还将获取和储存禁食血液样本，用于生物标记物和 组学(即基因组学、蛋白质组学和代谢组学)研究分子和生物机制 未来阻塞性睡眠呼吸暂停综合征的症状亚型。总体而言，这项研究将帮助我们了解 阻塞性睡眠呼吸暂停综合征症状亚型和治疗效果较好的预测因素。结果将通知未来的症状 根据患者的生理和临床信息，针对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.