ABSTRACT Excessive daytime sleepiness (EDS) affects 10-20% of the population and is associated with cardiovascular diseases (CVD) and mortality. Emerging data suggest that targeting EDS may provide a novel intervention for improving CVD. However, findings are limited by self-reported data and heterogeneity. There is a need to dissect and understand the underlying drivers of EDS subtypes, and to determine whether there are subtypes causally related to CVD and potentially modifiable. Our recent work identified two subtypes of EDS – sleep propensity (SP; characterized by objectively measured long sleep duration, high efficiency, and less fragmentation) and sleep fragmentation (SF; short sleep duration and low efficiency). Each of them is common in the population, associated with adverse cardiovascular outcomes and different genetic backgrounds. We hypothesize that SP is a novel sleep phenotype that reflects a property of the need of staying asleep; dissecting EDS into SP and SF subtypes will facilitate identification of genetic and physiological mechanisms for EDS, and improve understanding of pleiotropic or causal associations with CVD risk. In order to test these hypotheses, we will leverage macro- and micro- sleep architecture measurements, genomics, and other -omics data in population-based cohorts. We will address the following specific aims: 1) To identify demographic, behavioral, clinical and neurophysiological factors (assessed by actigraphy and electroencephalography) for SP and SF, and refine classification of EDS subtypes if needed; 2) To identify genetic variants and molecular pathways associated with EDS subtypes and generate robust polygenetic risk score for risk stratification; 3) To systematically evaluate the causal or non-causal associations between EDS subtypes and CVD traits; 4) To identify the modification effect of each EDS subtype on genetic susceptibility of CVD using gene-environment interaction analyses. This work will advance our understanding of the heterogeneity of EDS, reveal biological mechanisms and pathways linking to CVD, and provide information that will guide clinical and public health interventions as well as provide directions for future laboratory research.