The Cornerstone of the Aberrant Pathophysiology of Obstructive Sleep Apnea: Tissue Responses to Chronic Sustained Versus Intermittent Hypoxia

Association between serum α-synuclein levels and neurocognitive deficits in patients with obstructive sleep apnea: A case-control study

BACKGROUND

Obstructive sleep apnea (OSA) is increasingly recognized as a contributor to neurocognitive dysfunction, yet the underlying biological mechanisms remain insufficiently understood. α-Synuclein, a presynaptic protein implicated in neurodegenerative processes, may be involved in OSA-related cognitive impairment, but its peripheral expression and diagnostic utility have not been fully elucidated.

METHODS

In this case-control study, 108 untreated OSA patients and 100 age- and sex-matched healthy controls underwent overnight polysomnography and neurocognitive assessments, including the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Serum α-synuclein levels were measured using ELISA. Logistic and linear regression analyses were conducted to assess associations between α-synuclein levels and cognitive performance, while ROC curve analysis evaluated the biomarker's predictive accuracy.

RESULTS

Serum α-synuclein levels were significantly elevated in OSA patients compared to controls (385.62 ± 125.47 pg/mL vs. 215.30 ± 78.65 pg/mL, p < 0.001). Elevated α-synuclein levels were independently associated with cognitive impairment in OSA (adjusted OR = 1.832, 95 % CI: 1.624-1.995, p = 0.013). Linear regression showed a significant inverse relationship between α-synuclein and MMSE scores (β = -0.459, p = 0.005). ROC analysis revealed strong predictive value for cognitive deficits (AUC = 0.892, sensitivity = 84.0 %, specificity = 86.0 %).

CONCLUSION

Elevated serum α-synuclein levels are independently associated with neurocognitive impairment in OSA and may serve as a potential biomarker for early detection and risk stratification. Future longitudinal and interventional studies are warranted to validate its clinical utility.

Machine learning methods for adult OSAHS risk prediction

BACKGROUND

Obstructive sleep apnea hypopnea syndrome (OSAHS) is a common disease that can cause multiple organ damage in the whole body. Our aim was to use machine learning (ML) to build an independent polysomnography (PSG) model to analyze risk factors and predict OSAHS.

MATERIALS AND METHODS

Clinical data of 2064 snoring patients who underwent physical examination in the Health Management Center of the First Affiliated Hospital of Shanxi Medical University from July 2018 to July 2023 were retrospectively collected, involving 24 characteristic variables. Then they were randomly divided into training group and verification group according to the ratio of 7:3. By analyzing the importance of these features, it was concluded that LDL-C, Cr, common carotid artery plaque, A1c and BMI made major contributions to OSAHS. Moreover, five kinds of machine learning algorithm models such as logistic regression, support vector machine, Boosting, Random Forest and MLP were further established, and cross validation was used to adjust the model hyperparameters to determine the final prediction model. We compared the accuracy, Precision, Recall rate, F1-score and AUC indexes of the model, and finally obtained that MLP was the optimal model with an accuracy of 85.80%, Precision of 0.89, Recall of 0.75, F1-score of 0.82, and AUC of 0.938.

CONCLUSION

We established the risk prediction model of OSAHS using ML method, and proved that the MLP model performed best among the five ML models. This predictive model helps to identify patients with OSAHS and provide early, personalized diagnosis and treatment options.

Obstructive Sleep Apnea, Hypoxia, and Nonalcoholic Fatty Liver Disease

Recent studies have demonstrated that obstructive sleep apnea (OSA) is associated with the development and evolution of nonalcoholic fatty liver disease (NAFLD), independent of obesity or other shared risk factors. Like OSA, NAFLD is a prevalent disorder associated with major adverse health outcomes: Patients with NAFLD may develop cirrhosis, liver failure, and hepatocellular carcinoma. One major finding that has emerged from these studies is that the OSA-NAFLD association is related to the degree of nocturnal hypoxemia in OSA. Animal models have therefore largely focused on intermittent hypoxia, a key manifestation of OSA, to shed light on the mechanisms by which OSA may give rise to the complex metabolic disturbances that are seen in NAFLD. Intermittent hypoxia leads to tissue hypoxia and can result in oxidative stress, mitochondrial dysfunction, inflammation, and overactivation of the sympathetic nervous system, among many other maladaptive effects. In such models, intermittent hypoxia has been shown to cause insulin resistance, dysfunction of key steps in hepatic lipid metabolism, atherosclerosis, and hepatic steatosis and fibrosis, each of which is pertinent to the development and/or progression of NAFLD. However, many intriguing questions remain unanswered: Principally, how aggressively should the clinician screen for NAFLD in patients with OSA, and vice versa? In this review, we attempt to apply the best evidence from animal and human studies to highlight the relationship between these two disorders and to advocate for further trials aimed at defining these relationships more precisely.

Murine models of sleep apnea: functional implications of altered macrophage polarity and epigenetic modifications in adipose and vascular tissues

Obstructive sleep apnea (OSA) is a highly prevalent disease across the lifespan, is characterized by chronic intermittent hypoxia and sleep fragmentation, and has been independently associated with substantial cardiometabolic morbidity. However, the reversibility of end-organ morbidity with treatment is not always apparent, suggesting that both tissue remodeling and epigenetic mechanisms may be operationally involved. Here, we review the cumulative evidence focused around murine models of OSA to illustrate the temporal dependencies of cardiometabolic dysfunction and its reversibility, and more particularly to discuss the critical contributions of tissue macrophages to adipose tissue insulin resistance and vascular atherogenesis. In addition, we describe initial findings potentially implicating epigenetic alterations in both the emergence of the cardiometabolic morbidity of OSA, and in its reversibility with treatment. We anticipate that improved understanding of macrophage biology and epigenetics in the context of intermittent hypoxia and sleep fragmentation will lead to discovery of novel therapeutic targets and improved cardiovascular and metabolic outcomes in OSA.