Towards personalized medicine: pathophysiologic contributions to post-stroke sleep apnea

摘要 中风是美国成人残疾的主要原因，是美国人的头号杀手，并影响墨西哥人。 美国人（MA）比非西班牙裔白人（NHWs）在更大程度上。一次改善中风的机会 通过识别和治疗阻塞性睡眠呼吸暂停， (OSA)在中风患者中。普通人群中的OSA在以下方面是异质性的： 病理生理学、疾病表达、对治疗的反应以及与结果的关联。机械论 睡眠期间气道塌陷的原因可以从多导睡眠图（PSG）数据分类为OSA 内型，包括解剖学原因（可吸收性）和3个非解剖学原因（咽肌 补偿、化学反射反馈回路/回路增益和唤醒阈值）。与传统PSG数据不同， 反映OSA的严重程度，而不是根本原因，这些内型决定了对治疗的反应，因此 新的基于PSG的确定内型的方法为个性化护理创造了新的机会。OSA是 卒中后高比例（约75%），与一般人群相比表现不同。 此外，OSA在MA中风患者中更普遍和严重，平均而言， BMI比NHW高，因此可能更容易呼吸道阻塞。高流行率的原因和 中风后OSA的机械原因尚不清楚。由于大脑通路中断，非解剖性 中风后OSA的病因可能比一般人群更容易发生。相比之下， 预先存在的OSA可能具有与普通人群更相似的内型， 可扩展性。利用长期的基于人群的研究（BASIC）及其辅助研究的基础设施 研究受试者识别、基线数据收集和基线PSG，这项前瞻性研究采用卒中- 自由对照组，纵向随访旨在：1）确定特定的内型和内型 导致卒中后OSA的特征，以及这些特征在种族和非卒中人群中的差异，2） 确定特定的内型特征如何与通常在治疗后早期观察到的OSA严重程度的改善相关。 中风，以告知哪些患者可能需要长期治疗，哪些可能需要重复测试， OSA，以及3）基于包括以下的临床信息建立模型以预测中风后OSA内型谱： 表型数据，以帮助选择最合适的治疗方案，而不需要PSG。新 拟议的面部形态测量和其他表型将补充丰富的人口统计， 临床数据作为中风后OSA内型特征的预测因子。这项研究将扩大我们的 了解中风后OSA的病理生理学，并为个性化治疗打开大门， 中风患者，目前主要采用一刀切的方法。

Abstract Stroke is the leading cause of adult disability in the US, a top killer of Americans, and impacts Mexican Americans (MAs) to a greater extent than non-Hispanic whites (NHWs). One opportunity to improve stroke outcomes and reduce disparities may exist through identification and treatment of obstructive sleep apnea (OSA) in individuals with stroke. OSA in the general population is heterogeneous with respect to pathophysiology, expression of disease, response to therapies, and association with outcomes. Mechanistic causes of airway collapse during sleep can be categorized from polysomnography (PSG) data as OSA endotypes, including an anatomic cause (collapsibility), and 3 non-anatomic causes (pharyngeal muscle compensation, chemoreflex feedback loop/loop gain, and arousal threshold). Unlike traditional PSG data that reflect OSA severity and not underlying cause, these endotypes determine response to treatments, and thus new PSG-based methods to determine endotypes create novel opportunities for personalized care. OSA is overrepresented after stroke (~75%) and manifests differently compared to the general population. Furthermore, OSA is more prevalent and severe among MA stroke patients, who on average have a higher BMI than NHWs, and therefore likely more airway collapsibility. Reasons for the high prevalence and the mechanistic causes of post-stroke OSA are unknown. Due to interruption of brain pathways, non-anatomical causes of OSA may be more likely after stroke than in the general population. In contrast, stroke cases with pre-existing OSA may have endotypes more similar to the general population, with greater contribution from collapsibility. Leveraging the infrastructure of a longstanding population-based study (BASIC) and its ancillary study for subject identification, baseline data collection, and baseline PSG, this prospective study with a stroke- free comparison group, with longitudinal follow-up seeks to: 1) determine specific endotypes and endotypic profiles that contribute to post-stroke OSA, and how these differ by ethnicity and from those without stroke, 2) determine how specific endotypic profiles relate to improvement in OSA severity typically observed early after stroke in order to inform which patients may need longer-term treatment and which may need repeat testing for OSA, and 3) build a model to predict post-stroke OSA endotypic profiles based on clinical information including phenotypic data, to assist in selection of most appropriate treatment options without the need for PSG. Newly proposed facial morphometric measures and other phenotyping will complement the rich demographic and clinical data for consideration as predictors of post-stroke OSA endotypic profiles. This study will expand our understanding of the pathophysiology of post-stroke OSA and open the door to personalized medicine for stroke patients, currently dominated by a one-size-fits-all approach.