PROJECT SUMMARY Despite current evidence-based treatments for cardiovascular and metabolic diseases (CMD), these diseases remain highly prevalent and a leading cause of death. Therefore, identifying new disease mechanisms is paramount to further reduce and/or prevent CMD. Among potential CMD risk factors, the importance of inadequate sleep is gaining recognition. In this project, we will capitalize on a large, ongoing family-based study in Brazil that has recruited and enrolled approximately 2,700 participants. The primary objective of this project is to examine detailed measures of sleep and their associations with biomarkers of CMD, to assess sex differences in sleep and cardiometabolic disease, 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, some previous studies have found sex differences in the association between sleep and CMD, raising questions about whether men or women are more vulnerable to the effects of inadequate sleep. 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 in 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 dyslipidemia (high LDL or low HDL); 2) that the nature of the association between sleep and CMD will differ between men and women; 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 differing levels of SWA. We propose a cost-effective study that will leverage an existing cohort and add sleep PSG/EEG, repeated CMD biomarkers, and (in a subset) metabolomics and 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.