Although obstructive sleep apnea (OSA) is a common disorder, there are no blood biomarkers for identification and management of these patients. This project will study microRNAs in order to develop and validate blood biomarkers that are specific to OSA, useful for identification of cases with OSA, reflective of efficacy of therapy, and able to predict blood pressure response to treatment of OSA.

While obstructive sleep apnea (OSA) is common, there are limited biomarkers for identification and management of the condition. Specific use cases for an OSA biomarker include: (i) improving case identification, (ii) monitoring efficacy of therapy, and (iii) providing prognostic value with respect to who will get particular consequences or how individuals respond to continuous positive airway pressure (CPAP) treatment. While different approaches can be used to define biomarkers, this project will focus on microRNAs, which have very recently been shown to be promising biomarkers in OSA. MicroRNAs are small non-coding RNAs that alter the translation of protein coding RNA. Their expression is dynamic and altered by many challenges, such as hypoxia. Expression of all microRNAs in blood can be assessed by sequencing all short RNAs. Prior studies, albeit with small sample sizes, suggest differences in microRNA expression between OSA cases and controls and that differences in microRNA expression can identify individuals with OSA who will show larger blood pressure responses to CPAP treatment. Using complementary sequencing approaches and clinically-feasible quantitative PCR (qPCR), the investigators propose to validate and extend these initial observations. First, the investigators will seek biomarkers that are specific to OSA by evaluating differences in microRNA profiles between cases with OSA and controls without OSA matched for age, sex, and body mass index and without other underlying conditions that could independently affect microRNA expression. While identifying microRNAs specific to OSA is important, it is also useful to determine microRNAs useful for improving OSA case identification beyond known clinical risk factors. Thus, this project will enroll a larger case-control sample with minimal exclusion criteria in which to assess the predictive value of differences in microRNA expression. To understand the utility of microRNAs as treatment-related biomarkers, cases with OSA will be studied before and after 6 months of CPAP. The investigators anticipate that some microRNAs specific to OSA will normalize with CPAP treatment, thus providing an objective measure of effectiveness. In all OSA cases, the investigators will assess 24-hour ambulatory blood pressure to validate and extend recent reports of a microRNA signature that predicts blood pressure response to CPAP. The investigators will conduct robust validation for all biomarkers.

Inclusion Criteria for Cases:

• age 18-75 years
• moderate-severe OSA (defined as AHI ≥15 events/hour)
• willing to accept PAP therapy

Inclusion Criteria for Controls:

• age 18-75 years
• no OSA (defined as AHI <5 events/hour)

Exclusion Criteria for Cases:

• current use of PAP or other OSA treatments
• home oxygen therapy
• recent changes (within 3 months) to BP medications among those who are on these medications
• presence of Cheyne-Stokes Respiration (CSR) in sleep study
• predominantly central sleep apnea (AHI≥15 events/hour, with >50% central events)
• pregnancy
• clinical history of chronic kidney disease (Stage 5) requiring dialysis, or renal transplant
• organ transplantation
• self-reported sleep duration less than 5 hours per night on weeknights (work nights)
• current night shift work

Exclusion Criteria for Controls:

• home oxygen therapy
• pregnancy
• clinical history of chronic kidney disease (Stage 5) requiring dialysis, or renal transplant
• organ transplantation
• self-reported sleep duration less than 5 hours per night on weeknights (work nights)
• current night shift work

Participants who had a clinical sleep study who meet inclusion criteria for age and AHI and none of the exclusion criteria will be identified using the sleep center databases and electronic medical records. The investigators will also recruit participants from the community- these participants will undergo home sleep study with EEG. The investigators will make a conscious effort to recruit from all ethnic and social economic backgrounds.