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

摘要 中风是美国成年人残疾的主要原因，也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(NHW)更大程度上。改善中风的一个机会 通过识别和治疗阻塞性睡眠呼吸暂停，可能存在转归和缩小差距 (OSA)在中风患者中。一般人群中的阻塞性睡眠呼吸暂停综合征在以下方面是不同的 病理生理学、疾病表现、对治疗的反应以及与预后的关系。机械论 睡眠期间呼吸道塌陷的原因可以从多导睡眠图(PSG)数据中归类为OSA 内型，包括一个解剖原因(塌陷)和3个非解剖原因(咽肌 补偿、化学反射反馈环/环增益和唤醒阈值)。与传统的PSG数据不同， 反映OSA的严重程度而不是潜在原因，这些内型决定对治疗的反应，因此 基于PSG的确定内型的新方法为个性化护理创造了新的机会。OSA是 卒中后过多(约75%)，与普通人群相比表现不同。 此外，阻塞性睡眠呼吸暂停在MA卒中患者中更为普遍和严重，他们平均有更高的 体重指数高于健康体重者，因此可能有更大的呼吸道塌陷性。高流行率的原因和 中风后阻塞性睡眠呼吸暂停的机械原因尚不清楚。由于大脑通路的中断，非解剖学的 与普通人群相比，中风后引起阻塞性睡眠呼吸暂停的原因可能更多。相比之下，中风病例中有 先前存在的OSA可能具有与普通人群更相似的内型，其贡献更大 可崩解性。利用长期的基于人群的研究(基础)及其辅助研究的基础设施 关于受试者识别、基线数据收集和基线PSG的研究，这项针对中风的前瞻性研究- 自由对照组，纵向随访：1)确定特定的内型和内型 卒中后阻塞性睡眠呼吸暂停综合征的特征，以及这些特征在种族和非卒中人群中的差异，2) 确定特定的内型图谱如何与OSA严重程度的改善有关，通常在术后早期观察到 以告知哪些患者可能需要长期治疗，哪些患者可能需要重复检测 OSA，以及3)基于临床信息建立预测卒中后OSA内型分布的模型，包括 表型数据，以帮助选择最合适的治疗方案，而不需要PSG。新开 拟议的面部形态测量和其他表型鉴定将补充丰富的人口统计和 临床资料可作为卒中后阻塞性睡眠呼吸暂停低密度脂蛋白内型分布的预测因子。这项研究将扩大我们的 了解卒中后阻塞性睡眠呼吸暂停的病理生理机制，为个体化用药打开大门 中风患者，目前以一刀切的方法为主。

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.