It’s clear now that OSA is caused not only by anatomical obstruction in upper airway but following other physiological factors also play a role in the pathophysiology of OSA-
- Poor upper airway muscle responsiveness
- High loop gain
- Low arousal threshold
Most of the data regarding these physiological endotypes have been published in western populations. We also have less understanding regarding how these physiological endotypes vary with age among males and females.
In a recent study done in Asian patients (https://doi.org/10.1093/sleep/zsae185), it was shown that in men increasing age correlated with increased loop gain, decreased arousal threshold and increased collapsibility of upper airway after the age of 37yrs. Whereas in women increasing age correlated with increased loop gain only.
OSA is more prevalent in men as compared to women before menopause. OSA prevalence increases in women after menopause because the protective effect of estrogen and progesterone on upper airway muscle responsiveness and respiratory system stimulation is gone after menopause. In aging women increased loop gain will be the main contributor to development of OSA in addition to anatomical compromise. So, in women high loop gain should be the target of intervention to treat OSA.
This study done on Asian patients gives us a good reference for future studies to further analyze endotype traits.
Another study (https://doi.org/10.1513/AnnalsATS.202203-271OC) investigates the pathophysiological mechanisms underlying obstructive sleep apnea (OSA) across different demographic factors (e.g., obesity, age, sex, race/ethnicity). The key findings include:
- Major Contributors to OSA Severity:
- Pharyngeal Collapsibility: A primary driver of OSA severity, strongly influenced by demographic factors like obesity, age, and race.
- Loop Gain (Ventilatory Sensitivity): Elevated in obese and older individuals, contributing to ventilatory instability.
- Dilator Muscle Compensation: Reduced in males compared to females, leading to higher OSA severity in men.
- Demographic and Obesity-Related Insights:
- Obesity: Increases pharyngeal collapsibility and loop gain, leading to more severe OSA. Total body fat has a stronger influence than body mass index (BMI) alone.
- Age: Older individuals experience increased pharyngeal collapsibility and loop gain, partly due to age-related declines in cardiac and renal function.
- Sex: Men show higher OSA severity due to reduced pharyngeal muscle compensation and increased collapsibility compared to women.
- Race/Ethnicity:
- Chinese participants exhibit increased collapsibility, explaining their higher OSA severity.
- Black participants show reduced collapsibility but elevated loop gain, suggesting a ventilatory control phenotype for OSA.
- Mediation by Endotypic Traits:
- Traits like collapsibility and loop gain explain a significant portion of the observed differences in OSA severity between demographic groups.
- For example:
- Collapsibility mediates 87% of the increased OSA severity in Chinese participants.
- Reduced collapsibility accounts for 41% of the lower OSA severity in Black participants.
- Clinical Implications:
- Tailored Treatments: Recognizing these variations can improve treatment efficacy by targeting specific mechanisms (e.g., addressing loop gain in obese individuals).
- Population-Specific Strategies: Treatments may need to be customized for different demographic groups, such as stronger anatomical interventions for Chinese individuals or loop-gain-focused therapies for Black individuals.
- Research Implications:
- Emphasizes the importance of precision medicine in addressing OSA, considering the heterogeneity in pathophysiological mechanisms across populations.
These studies highlights the diverse mechanisms driving OSA and underscores the need for tailored interventions to optimize treatment outcomes.
While a lot of literature is published on above physiological endotypes role in the pathophysiology of OSA, they cannot be measured routinely in the clinical sleep lab for decision making in patients management. One need to have complex set of equipment to measure these physiological endotypes in the sleep lab which is not possible in routine sleep studies.
We also do not have any information regarding the night-to-night repeatability and variability of these endotypes when measured with PSG. We also need more information regarding which endotypes and repeatable threshold values of these endotypes are predictive of responses to various treatments. The technology needs to continue to evolve the way these endotypes can be assessed so they can be easily incorporated into routine clinical practice. Some AI based algorithms have been developed to assess these endotypes from routine PSG data, but these algorithms are not accessible to clinicians on a day-to-day basis.
We need to further validate these endotyping tools against relevant gold standard assessments (i.e characterization of criterion validity) given that there is ongoing scientific debate regarding the validity and reliability of measuring OSA endotype information from analysis of the polysomnography data.
Other investigative groups have challenged the methodology based on which these physiological endotypes have been proposed and have suggested alternative metrics for assessing the severity of OSA and to predict the consequences of untreated OSA. We will need to wait how the future data unfolds of these 2 competing groups and how it enhances our understanding of the pathophysiology of OSA.