Despite current evidence-based treatments for cardiovascular and metabolic diseases (CMD), these disease remain highly prevalent and a leading cause of death. Therefore, identifying new disease mechanisms is paramount to further reduce or prevent CMD. Moreover, there are large racial disparities in CMD in the US such that minority groups, particularly African Americans, experience a greater burden of disease. Among potential CMD risk factors, the importance of inadequate sleep is gaining recognition. In this project, we will capitalize on a large, on-going family-based study in Brazil that has collected genetic, metabolomic and cardiometabolic data. The primary objective of this project is to examine detailed measures of sleep and their associations with biomarkers of CMD, to assess whether sleep is associated with race, genetic ancestry, and social disparity, and to identify transcriptional and metabolic pathways as potential mechanisms to explain the effects of sleep on CMD development. Accumulating data suggest that specific EEG-based characteristics of sleep, such as slow-wave sleep (SWS) or slow-wave activity (SWA; EEG spectral power in the 0.5-4 Hz range), are highly heritable traits that may be drivers of subclinical cardiac and metabolic disease acting through the pleiotropic modulation of several risk factors. Furthermore, sleep duration, quality and SWS are reduced in African Americans compared to whites, raising questions about the degree to which sleep mediates racial health disparities. Current research has not fully explored the relationship between SWS/SWA and CMD, nor does it address the unknown underlying mechanisms. Therefore, the current proposal aims to fill this gap in knowledge by adding PSG to an existing study with 2,000 participants aged 18 to 90 years. We hypothesize: 1) that less SWS/SWA is associated with increased CMD risk, including higher fasting glucose and estimated insulin resistance (HOMA), higher hemoglobin A1c and chronic inflammation (hsCRP); 2) that greater African genetic ancestry will be associated with less SWS/SWA, regardless of self-referred race; 3) that transcriptional and metabolomic signatures will differ between those at the low and high ends of the distribution of SWA, and that these differences can inform on the upstream drivers and downstream consequences of different SWA. We propose a cost-effective study that will leverage existing data (metabolic and cardiovascular markers, and -omic platforms) and add sleep PSG/EEG and, in a subset, RNA sequencing to improve our understanding of the CMD implications of specific sleep EEG traits. These objectives are concordant with the stated NHLBI scientific priorities, including an investigation into sleep-related factors that account for differences in health among populations and identification of sleep as a factor that accounts for individual differences in pathobiology.
|Effective start/end date||2/15/19 → 1/31/23|
- National Heart, Lung, and Blood Institute (5R01HL141881-03)