Utility of microRNAs for Obstructive Sleep Apnea Identification

Rationale: Obstructive sleep apnoea (OSA) is a common disease caused by repeated episodes of collapse of the upper airway during sleep, and is associated with a higher risk of cardiovascular disease, cancer and overall mortality. The tools for the screening of OSA, mainly based in questionnaires, showed limited ability in the discrimination between OSA and Non-OSA patients. The evaluation of the mi RNA profile could allow characterizing the disease and also could help to diagnose OSA in a most accurate and cost-effective way. We aimed to examine the circulating miRNA profile to establish the differences between Non-OSA and OSA patients and to explore their clinical usefulness in disease diagnose.

Methodology: Observational and cross-sectional study that includes 230 patients referred to the Sleep Unit due to OSA suspicion. Two groups were defined according to the apnea-hypopnea index (AHI) measured by polysomnography: Non-OSA (AHk15 events/hour) and patients with OSA (AHl~15 events/hour). An initial expression profile of 188 miRNAs in peripheral blood samples was determined in 27 subjects (6 Non-OSA and 21 OSA} by TaqMan Low-Density Array (TLDA) (RT-qPCR Taqman (Applied Biosystems, Foster City, CA, USA)). The groups were homogeneous for sex, age and body mass index. mi RNA differentially expressed and/or associated with AHI were selected to validate in the 203 (64 Non-OSA and 139 OSA} remaining patients by RT -qPCR (qPCR cohort). Three prediction models were built in order to discriminate between Non-OSA and OSA: A) NoSAS score (Marti-Soler H., et al. Lancen Respir Med., 2016), B) differentially expressed miRNAs, C) a combination of NoSAS score plus miRNAs.

Results: Patients were middle aged and mainly male. OSA patients present, in general, severe OSA. From TLDA, 14 miRNAs were selected as candidates. 6 of them were differentially expressed in the qPCR cohort. The AUG of the models were 0.73 for the NoSAS score, 0.81 for the miRNAs and 0.86 for the combination of NoSAS score plus miRNAs. Conclusion: A singular cluster of miRNAs was identified that specifically differentiates between non-OSA and OSA patients, moreover miRNAs improve discrimination models based in anthropometric and clinical variables showing the uti lity of miRNAs in the diagnose of OSA.