PROJECT SUMMARY/ABSTRACT
Obstructive sleep apnea is a serious condition associated with increased risk for major comorbidities, including hypertension,
diabetes, and an increased risk of cardiovascular diseases (CVD) and mortality. The repetitive cycles of apnea/hypopnea
during sleep lead to frequent drops in oxygen saturation and cardiac autonomic surges following obstructive respiratory
events. These acute and repeated physiological changes are thought to play a key role in the development of adverse
cardiometabolic consequences.
Observational community-based cohort studies have shown strong associations of OSA with CVD outcomes. However, it
has been challenging to identify/predict high risk individuals potentially due to substantial heterogeneity in OSA population.
A potential explanation is the inability of apnea hypopnea index (AHI), the main metric for OSA diagnosis and management,
to capture the heterogeneity in the OSA-related hypoxemia and autonomic responses during sleep. More importantly, these
physiological changes are thought to vary by age, sex, and race. Therefore, the identification of phenotypic markers that
better quantify OSA-specific hypoxemia and autonomic responses are needed to provide improved prediction of incident
cardiometabolic outcomes.
Herein, we propose to study two novel physiological phenotypes that can be readily extracted from pulse oximetry signal,
the Sleep Apnea Specific Hypoxic Burden (“SASHB”) and the heart rate response to apneas/hypopneas (“¿HR”). We will
use well-defined large community based prospective cohort studies, including the Sleep Heart Health study (SHHS),
Multiethnic Study of Atherosclerosis (MESA), Hispanic community health study of Latinos (HCHS/SOL), the Outcomes
of Sleep Disorders in Older Men (MrOS), and the Jackson Heart Study (JHS), and the Wisconsin Sleep Cohort (WSC) to
pursue the following Aims. In Aim 1, we plan to use individual participant meta-analysis to examine how SASHB/¿HR
determine the incident hypertension, diabetes, and CVD in adults with diverse ethnicity/background. Past studies have
shown that the strength of associations between OSA, as quantified by AHI, and outcomes vary by age, sex, and race. It is
unclear if this observation was due to underlying biological differences or the inability of AHI to capture the heterogeneity
in OSA. In Aim 1(a), we plan to test the extent to which the associations of SASHB/¿HR and incident diabetes, hypertension,
and CVD vary by age, sex, and race. Finally, in Aim 2, we plan to test the added value of SASHB/¿HR in predicting an
established 10-year CVD risk (Pooled Cohort Equations to estimate the atherosclerotic cardiovascular disease) in
comparison with AHI and other conventional CVD risk factors.
Overall, our proposal is expected to demonstrate that SASHB/¿HR are more strongly linked with adverse cardiometabolic
outcomes across the community and improve CVD risk prediction. Furthermore, given that these phenotypes can be easily
extracted from home sleep testing devices, this personalized medicine approach will potentially alter the paradigm of OSA
assessment and management in the community.
