AUTHOR=Finnsson Eysteinn , Arnardóttir Eydís , Cheng Wan-Ju , Alex Raichel M. , Sigmarsdóttir Þóra B. , Helgason Snorri , Hang Liang-Wen , Ágústsson Jón S. , Wellman Andrew , Sands Scott A. TITLE=Sleep apnea endotypes: from the physiological laboratory to scalable polysomnographic measures JOURNAL=Frontiers in Sleep VOLUME=2 YEAR=2023 URL=https://www.frontiersin.org/journals/sleep/articles/10.3389/frsle.2023.1188052 DOI=10.3389/frsle.2023.1188052 ISSN=2813-2890 ABSTRACT=

Obstructive sleep apnea (OSA) is a common disorder characterized by recurrent upper airway obstruction during sleep. Despite the availability of continuous positive airway pressure (CPAP) as the gold standard treatment, it is not well tolerated by all patients. Accordingly, research has increasingly focused on developing methods for OSA endotyping, which aims to identify underlying pathophysiological mechanisms of the disorder to help guide treatment for CPAP-intolerant individuals. Four key endotypic traits have been identified, namely: collapsibility, upper airway muscle compensation, arousal threshold and loop gain. However, most methods for extracting these traits require specialized training and equipment not available in a standard sleep clinic, which has hampered the ability to assess the full impact of these traits on OSA outcomes. This paper aims to provide an overview of current methods for OSA endotyping, focusing on the Endo-Phenotyping Using Polysomnography (PUP) method and its cloud-based extension, PUPpy, which offer scalable and accessible ways to estimate endotypic traits from standard polysomnography. We discuss the potential for these methods to facilitate precision medicine for OSA patients and the challenges that need to be addressed for their translation into clinical practice.