The overall goal of this project is to address the postulate that the optimal molecular signature for the common disorder obstructive sleep apnea (OSA) is change in relevant biomarkers during the sleep period. In sleep apnea, events lead to sleep fragmentation and cyclical deoxygenation/reoxygenation. It is proposed that these changes will lead to molecular consequences can be detected by assessing biomarkers in blood. To determine which changes are due to OSA and which to circadian/sleep mechanisms, studies will be done in patients with OSA before and after effective treatment with Continuous Positive Airway Pressure (CPAP) and also in controls of similar visceral adiposity without OSA. Multiple assessments of biomarkers will be made before, during and after sleep. Since it is proposed that the magnitude of these dynamic changes across the sleep period will be affected by degree of visceral obesity and be greater in OSA subjects with cardiovascular comorbidities, studies will be done in 4 groups of subjects: lean and obese with and without such morbidities. In assessing biomarkers the primary outcome variables will be: urinary isoprostanes (oxidative stress); plasma tumor necrosis factor alpha (TNFα) (inflammation); plasma norepinephrine (sympathetic activation); and free fatty acids. Secondary biomarkers will be: Interleukin 6 (IL-6), urinary norepinephrine; urinary normetanephrine; glucose, Intercellular Adhesion Molecule (ICAM), leptin. To complement assessment of circulating biomarkers, an approach utilizing a cellular window will be used. Monocytes will be separated from each blood sample (before, during and after sleep) and RNA extracted. Expression of key genes will be assessed by RT-PCR and microarray studies will be performed in a subset of subjects to assess changes in expression of all genes as a result of OSA. A particular focus will be investigating differences between individuals with OSA with and without cardiovascular comorbidities. Three aspects will be evaluated: a)whether individuals with comorbidities have more oxidative stress and inflammatory change for equivalent degrees of OSA than individuals without such comorbidities; b) whether individuals with comorbidities have lower levels of protective mechanisms—melatonin (an anti-oxidant secreted during sleep), IL-10 (antiinflammatory); c) different gene variants based on a genetic association study using a recently developed CV SNP array. Finally, data will be used to determine whether there is a diagnostic urine and/or blood test for OSA.