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

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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.