Sex differences in obstructive sleep apnea phenotypes, the multi-ethnic study of atherosclerosis

Abstract

Study Objectives The bases for sex disparities in obstructive sleep apnea (OSA), is poorly understood. We quantified the influences of event definitions, sleep-state, and body position on apnea–hypopnea indices (AHIs) in men and women, and evaluated sex differences in pathophysiological endotypes. Methods Polysomnography (PSG) data were analyzed from 2057 participants from the multi-ethnic study of atherosclerosis. Alternative AHIs were compared using various desaturation and arousal criteria. Endotypes (loop gain, airway collapsibility, arousal threshold) were derived using breath-by-breath analysis of PSG signals. Regression models estimated the extent to which endotypes explained sex differences in AHI. Results The sample (mean 68.5 ± 9.2 years) included 54% women. OSA (AHI4P ≥15/h, defined by events with ≥4% desaturations) was found in 41.1% men and 21.8% women. Compared to AHI4P, male/female AHI ratios decreased by 5%–10% when using 3%-desaturation and/or arousal criteria; p < 0.05. REM-OSA (REM-AHI ≥15/h) was similar in men and women regardless of event desaturation criteria. REM-AHI4P ≥15/h was observed in 57% of men and women each. In NREM, AHI4P in men was 2.49 (CI95: 2.25, 2.76) of that in women. Women demonstrated lower loop gain, less airway collapsibility, and lower arousal threshold in NREM (ps < 0.0005). Endotypes explained 30% of the relative sex differences in NREM-AHI4P. Conclusions There are significant sex differences in NREM-AHI levels and in physiological endotypes. Physiological endotypes explained a significant portion of the relative sex differences in NREM-AHI. Definitions that use 4%-desaturation criteria under-estimate AHI in women. Combining NREM and REM events obscures OSA prevalence in REM in women.

Gender and Polysomnographic Profiles Findings in Obstructive Sleep Apnea Syndrome Patients Living in High Altitude

“…While the mean BMI in our subjects was higher than 31 in both genders, other populations had a mean BMI lower than 30. 19 , 22 , 38 , 39 Putting all these factors together, the group of patients described in this study were from a high-altitude city, in a developing country, and they were older and more obese than those in most of the previous reports.…”

“…Previous studies evidenced that OSA patients present different profiles, based on their symptoms, clinical characteristics, and disease severity, nevertheless those articles analyzed populations that differ in many ways such as age, symptoms, sociodemographic, and clinical characteristics. 22–27 However, none of those articles reported clusters from patients exposed to high altitude, which may represent an important modifying factor of OSA phenotypes.…”

An Update on Obstructive Sleep Apnea for Atherosclerosis: Mechanism, Diagnosis, and Treatment

“…The gold standard of AHI detection is measured by overnight polysomnography in the sleep laboratory, and values of 5–15, 15–30, and >30 are defined as mild, moderate, and severe OSA, respectively ( 54 ). Further, polysomnography could give mechanistic indices such as loop gain, arousal threshold, and pharyngeal collapsibility with validated methods, and it was able to distinguish sex differences in patients with OSA ( 55 ). However, cost and accessibility limit the application of polysomnography in all settings.…”

Top 5 Trends in DSM for the Next Decade

“…Phenotyping, incidentally, had been previously presented as a promising yet time consuming, techniquesensitive, costly procedure. A recent study has shown that PSG signals can now be used for phenotyping in a retrospective and relatively inexpensive way 8 , thus making the technique more accessible both clinically and financially.…”