Obstructive sleep apnea (OSA) is a growing global health concern that affects millions of people worldwide. It is a sleep-related breathing disorder marked by repeated episodes of upper airway obstruction during sleep, resulting in intermittent hypoxia (low oxygen levels), hypercapnia (elevated carbon dioxide levels), and fragmented sleep [1]. These episodes of airway collapse lead to a reduction or complete cessation of airflow, causing blood oxygen levels to drop (hypoxemia) and carbon dioxide levels to rise (hypercapnia). In response to these obstructions, the body briefly arouses from sleep, disrupting sleep patterns and preventing restful, restorative sleep. These repeated events are driven by a combination of anatomical and functional factors that affect the upper airway [2].

The prevalence of OSA is continuously rising, especially in populations with higher obesity rates, as obesity is a major risk factor for the disorder. According to epidemiological studies, OSA is particularly common among middle-aged and elderly individuals [3]. Other contributing risk factors include craniofacial abnormalities, upper airway muscle dysfunction, and fluid shifts to the neck that can exacerbate airway collapse during sleep [4]. Despite the increased attention to OSA, the underlying pathophysiological mechanisms, particularly those leading to upper airway collapse, remain incompletely understood.

The consequences of untreated OSA go beyond disrupted sleep and can lead to serious health complications. The intermittent hypoxia and frequent arousals associated with OSA trigger a range of pathological processes that increase the risk of various comorbidities, including cardiovascular diseases such as hypertension, stroke, and heart failure, metabolic disorders like diabetes, and cognitive dysfunction [5]. These comorbidities significantly increase the risk of morbidity and mortality in individuals with OSA, making early diagnosis and effective treatment essential.

OSA is diagnosed through sleep studies, including polysomnography (PSG), which monitors airflow, blood oxygen levels, brain waves, and body movements during sleep. The apnea-hypopnea index (AHI), which measures the frequency of apnea and hypopnea events per hour of sleep, is commonly used to determine the severity of OSA. The AHI categorizes the disorder as mild, moderate, or severe, with severe cases presenting with more than 30 events per hour [1]. These frequent interruptions in breathing not only impact the quality of sleep but also place a substantial burden on the cardiovascular, metabolic, and neurological systems [1].

The growing recognition of OSA’s impact on public health has sparked an increased focus on developing more effective therapeutic interventions, including continuous positive airway pressure (CPAP) therapy, lifestyle modifications, and surgical options. However, more research is necessary to improve treatment outcomes and tailor interventions to the specific needs of individual patients [6].

This study aims to comprehensively explore the pathophysiological mechanisms underlying OSA, synthesizing existing knowledge to enhance the understanding of its multifaceted etiology. By addressing unresolved clinical challenges, the research seeks to highlight the limitations of current diagnostic and therapeutic approaches. Furthermore, the study endeavors to analyze and evaluate tailored treatment strategies based on specific physiological mechanisms, ultimately contributing to the development of personalized interventions. The overarching goal is to establish a framework for improving the quality of life and long-term health outcomes for patients affected by OSA through innovative and evidence-based diagnostic and treatment paradigms.

OSA arises from a combination of anatomical and functional factors that contribute to upper airway collapse during sleep. Anatomically, the soft tissues in the upper airway, such as the soft palate and tongue, become more prone to collapse, especially in patients with a narrower airway structure. Functionally, a lack of sufficient neuromuscular control during sleep prevents the airway from remaining open, leading to airway obstruction. This obstruction results in a cycle of hypoxia and hypercapnia, which subsequently trigger arousals from sleep. These arousals temporarily restore pharyngeal muscle tone and open the airway. However, repeated arousal events lead to fragmented sleep and systemic complications, including cardiovascular and metabolic diseases, cognitive dysfunction, and other serious health consequences [1].

1. Anatomical Contributors

Anatomical features play a significant role in the propensity for airway collapse in OSA patients. Key contributors include a narrow oropharyngeal space, enlarged soft tissues in the airway, and increased tongue volume. Individuals with a large volume of fat deposition in the neck and around the tongue, particularly those who are obese, exhibit a higher risk of collapsing airway. Studies using imaging techniques have demonstrated that a greater volume of tongue fat correlates strongly with the risk of apnea [7,8]. Additionally, structural abnormalities, such as a shorter mandible or a posteriorly displaced maxilla, contribute to airway obstruction by narrowing the pharyngeal space [9-11].

2. Neuromuscular Factors

While structural abnormalities contribute significantly to the development of OSA, they only account for about one-third of the variability in its severity. The remaining variability is largely influenced by neuromuscular responses [12]. Patients with OSA heavily rely on neuromuscular activity to maintain airway patency during sleep, especially as pharyngeal muscle tone decreases at sleep onset, predisposing them to airway obstruction [13].

During rapid eye movement (REM) sleep, the reduction in neuromuscular tone is particularly pronounced, which can exacerbate OSA, especially in female and children [2]. Certain drugs, such as alcohol and sedatives, further diminish the active neuromuscular responses to airway obstruction, thereby contributing to upper airway collapse. Benzodiazepines, for instance, can worsen obstructive apneas and hypopneas [14]. Though the effects of opioid medications on airway collapsibility are not well studied, evidence suggests that narcotics may increase susceptibility to airway obstruction by affecting neuromuscular activity [15].

There is also evidence that endogenous neurohormonal agents can influence neuromuscular control of the upper airway, potentially explaining the differences in OSA severity between male and female. Female, especially during non-REM sleep, demonstrate greater neuromuscular compensation compared to male [16]. Male with OSA exhibit a stronger respiratory response to spontaneous arousal from non-REM sleep compared to female, which leads to elevated airway resistance [17]. This suggests that increased upper airway resistance prior to arousal may contribute to airway instability upon returning to sleep, with the effect being more pronounced in male [18]. In obese patients, an increase in pro-inflammatory chemokines, such as TNF-α, is associated with reduced neuromuscular activity, thereby worsening OSA [19]. As serum leptin levels, known as obese protein, increase, both the AHI and the duration of hypoxemia also rise [20,21].

Additionally, chemical and mechanical reflexes play a critical role in controlling neuromuscular activity. Hypercapnia (high CO₂ levels) stimulates upper airway neuromuscular activity, which decreases the likelihood of airway collapse [22], while hypocapnia (low CO₂ levels) increases airway collapsibility [23]. The neuromuscular responses are also regulated by sensory feedback mechanisms from the pharynx, and any impairment in these responses—such as from mucosal inflammation—can worsen airway obstruction during sleep [24]. This will be discussed in more detail below.

3. Respiratory Control

Another important factor contributing to OSA is respiratory control instability, also known as “loop gain.” This refers to the sensitivity of the respiratory system to changes in blood gases, particularly carbon dioxide. Patients with high loop gain tend to experience exaggerated ventilatory responses to minor changes in blood gas levels, leading to oscillatory breathing patterns during sleep. According to a study by Messineo et al. [25], loop gain is directly related to breath-hold time, with shorter breath-hold times indicating higher loop gain. This suggests that exercises aimed at reducing respiratory sensitivity could benefit patients with high loop gain [25]. This instability in respiratory control increases the likelihood of airway collapse and contributes to the pathophysiology of OSA [26].

During OSA, when breathing stops, CO₂ accumulates in the body, acting as a primary stimulus for ventilation. An increase of just 2-5 mmHg in CO₂ levels can more than double ventilation. Individuals with high loop gain show excessive ventilation in response to slight increases in CO₂, leading to rapid breathing and large tidal volumes, which reduce CO₂ levels too much and result in hypocapnia. When CO₂ levels are too low, the brain fails to send the necessary signals to maintain breathing, potentially causing central apnea [27,28].

At the same time, reduced respiratory signals lead to decreased effectiveness of airway-opening muscles, increasing upper airway resistance and the risk of collapse. When respiratory drive is low, airway dilator muscles become less active, contributing to airway obstruction [29].

High loop gain can thus create a vicious cycle where exaggerated breathing responses inhibit respiratory signals, potentially triggering central apneas. Increased airway collapsibility further contributes to obstructive apneas [30]. Therefore, high loop gain plays a key role in perpetuating apneas, as evidenced by its correlation with AHI scores.

Additionally, about one-third of OSA patients have a low arousal threshold, meaning they wake up too easily from minor respiratory disturbances [31]. This premature awakening prevents the respiratory stimuli needed to activate airway muscles, leading to repetitive apneas [32]. Medications that raise the arousal threshold may help by allowing these respiratory stimuli to accumulate [33], though more research is needed to confirm their long-term benefits.

1. Obstructive Sleep Apnea Endotypes

Recent advances in the understanding of OSA have led to the identification of specific endotypes that describe the distinct physiological mechanisms underlying the disorder. The key factors contributing to OSA can be grouped into several endotypes, each reflecting different mechanisms. These include anatomical compromise, impaired pharyngeal dilator muscle function, unstable ventilatory control, known as high loop gain, and a low arousal threshold, where individuals are more likely to wake up easily due to respiratory disturbances. Additional factors, such as reduced end-expiratory lung volume, increased arousal intensity, and fluid redistribution within the body, also influence the development of OSA.

Recognizing these different endotypes is crucial for developing personalized treatment strategies for OSA. In some cases, multiple treatment approaches may be necessary to address the various mechanisms involved. Furthermore, certain endotypes can predict how well patients will respond to specific therapies, such as positive airway pressure (PAP) therapy or surgery [34]. This understanding of OSA endotypes holds great promise for improving the management of the disorder, though it is not yet widely implemented in clinical practice [35,36].

2. Obstructive Sleep Apnea Phenotypes

Venkataraman et al. [37] conducted a cluster analysis on OSA patients, identifying three main groups: those with sleepiness and cardiovascular risk, those with disrupted sleep and insomnia, and asymptomatic patients. Their work demonstrated that sleepy patients who adhere to PAP therapy tend to show improvement in symptoms and reduced somnolence, while asymptomatic patients show little improvement. Importantly, sleepy OSA patients are at the highest cardiovascular risk. Various studies have used cluster analysis to define OSA phenotypes, employing methods like latent class analysis or hierarchical clustering to identify distinct subgroups [38-40]. These studies have often focused on a combination of comorbidities and symptoms, although some have incorporated anatomical or polysomnographic data. The primary goal has been to identify unique subgroups of OSA patients, each with minimal variability within the group but clear differences between groups.

In summary, this research emphasizes the importance of identifying OSA phenotypes to guide personalized treatment approaches. Specific phenotypes may help predict cardiovascular risk, treatment response, and long-term outcomes, although these findings are not yet widely implemented in clinical practice.

OSA has far-reaching health implications, particularly in terms of cardiovascular and metabolic diseases. The chronic intermittent hypoxia associated with apneic episodes activates the sympathetic nervous system, leading to increased blood pressure, hypertension, arrhythmias, and the development of atherosclerosis. Additionally, OSA is closely linked to metabolic disorders, including insulin resistance and type 2 diabetes. Patients with untreated OSA are also at a higher risk of motor vehicle accidents due to excessive daytime sleepiness, making early diagnosis and treatment critical for preventing serious health outcomes [41].

The diagnosis of OSA is primarily established through PSG, which measures various sleep parameters, including apneic events, hypopneas, oxygen desaturation, and sleep architecture. The AHI is used to quantify the severity of OSA, with higher values indicating more severe forms of the disorder. Patients with an AHI above 30 are considered to have severe OSA (Tables 1, 2) [42].

1. A New Approach Beyond Apnea-Hypopnea Index

AHI is a fundamental measure used for diagnosing OSA, classifying disease severity, studying prevalence, evaluating treatment outcomes, and predicting prognosis [43]. It is moderately correlated with factors such as oxygen desaturation and sleep fragmentation. AHI, which is calculated by dividing the total number of apneas and hypopneas by the total sleep time, is simple to understand and easy to obtain through testing. However, this simplicity also highlights its limitations. AHI does not reflect the duration or severity of respiratory events and is insufficient to represent arousal thresholds, respiratory responses, or sleep fragmentation directly. This limitation is significant, especially considering that in a classification study of three clinical subtypes, there was no difference in AHI among the groups [37].

Recently, to overcome these limitations of AHI, new interpretations based on various neurophysiological signals obtained from PSG have been proposed. One prominent approach is the quantification of oxygen desaturation associated with OSA. Traditional methods for quantifying desaturation include the oxygen desaturation index, which is the total number of oxygen desaturation events (3% or 4% drops from baseline) divided by sleep time, T90 and T80, which represent the time spent with oxygen saturation below 90% and 80% respectively, and the lowest oxygen saturation recorded during sleep [44]. These methods are as simple and easy to obtain as AHI but have some limitations [45].

1) The causes of oxygen desaturation are varied and not exclusive to OSA; other conditions such as chronic obstructive pulmonary disease, chronic bronchitis, and neuromuscular diseases can also cause desaturation.

2) The cutoff values of 3% and 4% for oxygen desaturation are arbitrary.

3) These measures simply quantify the severity of hypoxemia without considering the underlying pathophysiology.

Recently, new methods like obstructive severity, hypoxia load, and hypoxic burden aim to overcome these limitations by considering the length and severity of respiratory events, oxygen desaturation related to these events, and the restoration of oxygen levels. For example, studies using hypoxic burden in large cohorts, such as the Sleep Heart Health study and the Osteoporotic Fracture in Men study, have demonstrated that hypoxic burden can predict cardiovascular-related mortality [46,47].

Additionally, other methods are being explored, such as applying approximate entropy, a statistical method used to quantify the unpredictability and regularity of time-series data like heart rate, oxygen saturation, and respiration [48]. Another example is the odds ratio product, an automated method for measuring sleep depth through electroencephalography spectral analysis [49].

1. Continuous Positive Airway Pressure

CPAP therapy remains the most effective treatment for OSA. By delivering continuous positive air pressure, CPAP prevents the airway from collapsing during sleep, significantly reducing apneic events. Numerous studies have shown that CPAP not only improves daytime sleepiness but also reduces the risk of cardiovascular complications and enhances overall quality of life [34].

2. Oral Appliance Therapy

For patients with OSA, oral appliances such as mandibular advancement devices (MADs) provide an effective alternative to CPAP. These devices work by repositioning the jaw to keep the airway open during sleep. Weight loss has also been shown to enhance the effectiveness of MADs, particularly by reducing tongue fat, which contributes to airway obstruction [34].

3. Emerging Therapies

Emerging treatments for OSA include hypoglossal nerve stimulation, which helps activate the genioglossus muscle to maintain airway patency. Additionally, pharmacological approaches targeting respiratory control mechanisms, such as acetazolamide and oxygen therapy, have shown promise in reducing loop gain and improving the clinical outcomes of OSA [49].

Numerous health problems, including cardiovascular disease, metabolic diseases, and cognitive dysfunction, can result from OSA, a complex illness impacted by anatomical, neuromuscular, and ventilatory control variables. Newer techniques that concentrate on oxygen desaturation and hypoxic burden may provide better forecasts, particularly for cardiovascular risk, while more conventional diagnostic techniques, including the AHI, have limits in determining the disorder’s entire severity.

Although CPAP is still the best treatment, additional individualized options are offered by alternatives such oral appliances, hypoglossal nerve stimulation, and medications that target loop gain. Treatments are shifting toward customized approaches based on the unique processes of each patient as knowledge advances. For OSA patients to have better quality of life and long-term health outcomes, early diagnosis and focused treatment are essential.

Soo-Min Ok and Hye-Min Ju serve on the editorial board of the Journal of Oral Medicine and Pain. But they have no role in the decision to publish this article. Except for that, no potential conflict of interest relevant to this article was reported.

Data sharing is not applicable to this article because no new data were created or analyzed in this study.

This work was supported by a 2-year Research Grant of Pusan National University.

Conceptualization: SMO. Data curation: SHJ, SMO. Formal analysis: HMJ (Hye-Mi Jeon). Funding acquisition: SMO. Investigation: HMJ (Hye-Mi Jeon). Methodology: JWJ. Resources: YWA. Supervision & project administration: SMO. Validation: JWJ. Visualization: HMJ (Hye-Min Ju). Writing original draft: SMO. Writing review & editing: JWJ. All authors have read and agreed to the published version of the manuscript.