Obstructive sleep apnea (OSA) is a common disorder that is increasing in prevalence. OSA is known to have heterogeneous pathophysiology, with different subtypes, clinical consequence, and treatment responses among individual patients. A recent publication from the Sleep Research Society and National Heart, Lung and Blood Institute highlighted the potential clinical utility of quantitative OSA biomarkers identified using unbiased ?omics? approaches.There are currently no established quantitative biomarkers that can be used to understand heterogeneity or inform clinical practice. Thus, the present study proposes to utilize metabolomic methods which reflect dynamic responses to hypoxia to identify metabolite signatures in OSA. The overarching hypothesis motivating this proposal is that blood-borne metabolite signatures that result from metabolic insults caused by the cyclical intermittent hypoxia, recurrent arousals and lack of deep sleep characteristic of OSA will provide a quantitative biomarker to better understand disease heterogeneity and inform clinical care.
In Aim 1, we will differentiate OSA from non-OSA leveraging well- phenotyped samples carefully chosen from a large pool of patients from existing research projects (Aim 1A). Our preliminary suggest clear metabolite differences between patients with OSA and controls. Furthermore, we will leverage these existing samples to determine if established OSA symptom subtypes of disturbed sleep (e.g., insomnia), excessive sleepiness, and minimally symptomatic have distinct metabolomic profiles (Aim 1B) which will provide insights into identified differences in cardiovascular risk and support a precision medicine approach. These analyses utilizing banked samples are supported by a carefully designed prospective study of OSA patients before and after positive airway pressure (PAP) treatment in Aim 2. The study is designed to control for bias related to site-specific variance in sampling and data collection using state-of-the-art causal modeling techniques. As part of the prospective study, we will perform complementary analyses supporting metabolomic signatures (Aim 2A), determine a metabolomic signature that correlates with hours and days of PAP usage (Aim 2B) and evaluate whether the metabolomic changes with PAP treatment differ by obesity (Aim 2C) or symptom subtype (Aim 2D). In support of this Aim, preliminary data suggest metabolomic changes with PAP treatment.. Finally, in Aim 3 we will leverage existing samples of obese OSA subjects that were previously randomized to one of three treatments ? weight-loss alone, PAP alone, or combined weight-loss and PAP. Differences in metabolomic changes among these three randomized groups will provide insights into the relative roles of obesity and cyclical intermittent hypoxia on metabolic responses and pathways. Ultimately, results from this proposal will provide comprehensive information on metabolomic signatures that can be utilized as quantitative biomarkers to further our understanding of OSA heterogeneity and inform clinical practice and personalized medicine among OSA patients. R01 Metabolomics of OSA - Page 1
! Obstructive sleep apnea (OSA) is very common sleep disorder. Our team has found at least three known subtypes of OSA with different causes and symptoms, but these are difficult to distinguish in the clinic. OSA is linked to disorders such as heart disease, diabetes, cancer and dementia. We do not yet have any biomarkers for OSA to help guide treatment. We propose to study metabolic fingerprints to understand OSA heterogeneity and to what degree CPAP treatment or obesity has on these metabolite fingerprints. Results from this project will enable future OSA research to differentiate OSA subtypes and personalize the diagnosis and management of OSA.! R01 Metabolomics of OSA - Page 1
