Correlation of Dyslipidemia and Inflammation With Obstructive Sleep Apnea Severity

Assessment of leukocyte and systemic inflammation index ratios in dyslipidemia patients with dry eye disease: a retrospective case‒control study

BACKGROUND

Dry eye disease (DED) is a complication of dyslipidemia (DLP) that is caused by metabolic syndrome and increased inflammation. This research aimed to assess leukocyte and systemic inflammation index ratios as potential biomarkers for systemic inflammation in dyslipidemia patients with dry eye disease (DLP-DED).

METHODS

Several blood biomarkers were studied in 32 patients with DLP-DED (study group) and 63 patients with DLP-only (control group). The evaluated blood biomarkers included specific systemic inflammation index ratios, such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and neutrophil-to-lymphocyte and platelet ratio (NLPR), and lipid profiles, such as total cholesterol (TC), high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), triglyceride (TG), albumin (ALB), and C-reactive protein (CRP) levels.

RESULTS

Lymphocyte levels were significantly greater in the DLP-DED group than in the DLP-only group (P = 0.044). In addition, a significant negative correlation between HDL and the NLPR (P = 0.007; r= -0.428) and a significant negative correlation between the serum ALB concentration and the PLR (P = 0.008; r= -0.420) were identified as potential inflammatory predictors of DLP-DED.

CONCLUSION

The findings of this study suggest that patients with DLP-DED may benefit from routine blood monitoring of their elevated lipid profile and blood inflammatory biomarkers, such as CRP, leukocytes, and systemic inflammation index ratios (NLR, PLR, MLR, and NLPR), to reduce the complications of DLP on ocular health. The correlation data suggest that the NLPR, PLR, serum ALB concentration, and serum HDL concentration may be valuable inflammatory biomarkers in DLP-DED patients. More research is required to ascertain the significance of the NLR, PLR, MLR, and NLPR and the additive role that leukocytes play.

Differences and Risk Factors of Peripheral Blood Immune Cells in Patients with Obstructive Sleep Apnea

Introduction

Obstructive sleep apnea (OSA) is a respiratory disorder characterized by chronic intermittent hypoxia and fragmented sleep, leading to inflammatory response and oxidative stress. However, the differences in immune inflammatory response in OSA patients with different severity remain unclear.

Purpose

This study aims to examine the differences in peripheral blood immune cells and their risk factors in OSA patients.

Patients and Methods

A total of 277 snoring patients from the Sleep Respiratory Disorder Monitoring Center of Zhongnan Hospital of Wuhan University were recruited in this study. According to the diagnosis and severity criteria of OSA, the included patients were further divided into simple snoring, mild, moderate, and severe groups. Peripheral blood immune cell counts including white blood cells, neutrophils, lymphocytes, monocytes, eosinophils, basophils, red blood cells, platelets, and polysomnography indicators were collected from the patients.

Results

Compared with simple snoring patients, the OSA patients had increased circular monocyte and basophil count levels. In addition, correlation analysis results indicated that monocyte count was positively associated with chronic obstructive pulmonary disease (COPD), smoking, apnea-hypopnea index (AHI), the longest apnea duration, and Oxygen desaturation index (ODI), and negatively correlated with average SpO2 in snoring patients. Finally, multiple linear regression analysis revealed that AHI, COPD, smoking, and maximum heart rate were independent predictors of monocyte count.

Conclusion

OSA patients had a significant increase in their peripheral blood monocyte count. AHI, COPD, smoking, and maximum heart rate were risk factors for increased peripheral blood monocyte count in OSA patients. These findings suggest that peripheral blood monocytes can be considered an inflammatory biomarker of OSA.

Obstructive Sleep Apnea Syndrome and Obesity Indicators, Circulating Blood Lipid Levels, and Adipokines Levels: A Bidirectional Two-Sample Mendelian Randomization Study

Purpose

This investigation sought to elucidate the genetic underpinnings that connect obesity indicators, circulating blood lipid levels, adipokines levels and obstructive sleep apnea syndrome (OSAS), employing a bidirectional two-sample Mendelian randomization (MR) analysis that utilizes data derived from extensive genome-wide association studies (GWAS).

Methods

We harnessed genetic datasets of OSAS available from the FinnGen consortium and summary data of four obesity indices (including neck circumference), seven blood lipid (including triglycerides) and eleven adipokines (including leptin) from the IEU OpenGWAS database. We primarily utilized inverse variance weighted (IVW), weighted median, and MR-Egger methods, alongside MR-PRESSO and Cochran's Q tests, to validate and assess the diversity and heterogeneity of our findings.

Results

After applying the Bonferroni correction, we identified significant correlations between OSAS and increased neck circumference (Odds Ratio [OR]: 3.472, 95% Confidence Interval [CI]: 1.954-6.169, P= 2.201E-05) and decreased high-density lipoprotein (HDL) cholesterol levels (OR: 0.904, 95% CI: 0.858-0.952, P= 1.251E-04). Concurrently, OSAS was linked to lower leptin levels (OR: 1.355, 95% CI: 1.069-1.718, P= 0.012) and leptin receptor levels (OR: 0.722, 95% CI: 0.530-0.996, P= 0.047). Sensitivity analyses revealed heterogeneity in HDL cholesterol and leptin indicators, but further multiplicative random effects IVW method analysis confirmed these correlations as significant (P< 0.05) without notable heterogeneity or horizontal pleiotropy in other instrumental variables.

Conclusion

This investigation compellingly supports the hypothesis that OSAS could be a genetic predisposition for elevated neck circumference, dyslipidemia, and adipokine imbalance. These findings unveil potential genetic interactions between OSAS and metabolic syndrome, providing new pathways for research in this domain. Future investigations should aim to delineate the specific biological pathways by which OSAS impacts metabolic syndrome. Understanding these mechanisms is critical for developing targeted prevention and therapeutic strategies.

Evaluate the Relationship Between Obstructive Sleep Apnea and Metabolic Syndrome in Real-World Data

Objective

Obstructive sleep apnea (OSA) is a disorder characterized by disruption in breathing and hypoventilation. In parallel, metabolic syndrome (MetS) mainly co-occur with OSA, however, their association has not been fully elucidated. Therefore, this study aimed to reveal the relationship between OSA and MetS using data from the National Health And Nutrition Examination Survey (NHANES) database and pooled data from Genome-Wide Association Studies (GWAS).

Material and Methods

Data from the National Health and Nutrition Examination Survey and pooled data from genome-wide association analysis (GWAS) were used univariate and multivariate logistic regression analyses were carried out to evaluate the correlation between OSA and MetS, and multivariate logistic regression models were utilized for adjusting for potential confounders. Two-sample Mendelian randomization (MR) was used to assess the causal relationship between OSA and MetS. The variance-weighted inverse method was employed as the main method of analysis.

Results

A positive relationship of OSA with Mets was evidenced by multivariate logistic regression analysis, and OSA was associated with higher incidence rates of all-cause and cardiovascular mortality. OSA is strongly associated with abdominal obesity, hypertension, hyperglycemia, high triglycerides, and low HDL. Furthermore, except for hypertriglyceridemia, MR analysis indicated that genetically driven OSA was causally associated with a higher risk of MetS.

Conclusion

The positive relationship of OSA with Mets was revealed, and higher incidence rates of all-cause mortality and cardiovascular mortality were noted to be correlated with OSA. MR analysis further confirmed the causal relationship of OSA with MetS and cardiovascular disease.

Possible Molecular Mechanisms of Hypertension Induced by Sleep Apnea Syndrome/Intermittent Hypoxia

Intermittent hypoxia (IH) is a central characteristic of sleep apnea syndrome (SAS), and it subjects cells in the body to repetitive apnea, chronic hypoxia, oxygen desaturation, and hypercapnia. Since SAS is linked to various serious cardiovascular complications, especially hypertension, many studies have been conducted to elucidate the mechanism of hypertension induced by SAS/IH. Hypertension in SAS is associated with numerous cardiovascular disorders. As hypertension is the most common complication of SAS, cell and animal models to study SAS/IH have developed and provided lots of hints for elucidating the molecular mechanisms of hypertension induced by IH. However, the detailed mechanisms are obscure and under investigation. This review outlines the molecular mechanisms of hypertension in IH, which include the regulation systems of reactive oxygen species (ROS) that activate the renin-angiotensin system (RAS) and catecholamine biosynthesis in the sympathetic nervous system, resulting in hypertension. And hypoxia-inducible factors (HIFs), Endotheline 1 (ET-1), and inflammatory factors are also mentioned. In addition, we will discuss the influences of SAS/IH in cardiovascular dysfunction and the relationship of microRNA (miRNA)s to regulate the key molecules in each mechanism, which has become more apparent in recent years. These findings provide insight into the pathogenesis of SAS and help in the development of future treatments.

Pulmonary Function Test and Obstructive Sleep Apnea Hypopnea Syndrome in Obese Adults: A Retrospective Study

Objective

We explore risk factors related to severe obstructive sleep apnea (OSA) in obese patients, including pulmonary ventilation function, diffusion function, and impulse oscillometry (IOS) data.

Methods

The medical records of 207 obese patients who were prepared to undergo bariatric surgery in a hospital from May 2020 to September 2021 were retrospectively reviewed. Polysomnography (PSG), pulmonary ventilation function, diffusion function, and IOS parameters were collected according to the ethical standards of the institutional research committee (registration number: KYLL-202008-144). Logistic regression analysis was used to analyze the related independent risk factors.

Results

There were significantly statistical difference in a number of pulmonary ventilation and diffusion function parameters among the non-OSAHS group, the mild-to-moderate OSA group, and the severe OSA group. However, only airway resistance parameters R5%, R10%, R15%, R20%, R25%, and R35% increased with increasing OSA severity and were positively correlated with apnea hypopnea index (AHI). Age (P = 0.012, 1.104 (1.022, 1.192)), body mass index (P< 0.0001, 1.12 (1.057, 1.187)), gender (P = 0.003, 4.129 (1.625, 10.49)), and R25% (P = 0.007, 1.018 (1.005, 1.031)) were independent risk factors for severe OSA. In patients aged 35 to 60, RV/TLC (P = 0.029, 1.272 (1.025, 1.577)) is an independent risk factor for severe OSA.

Conclusion

R25% was an independent risk factor for severe OSA in obese individuals, while RV/TLC was also an independent risk factor in those aged 35 to 60. Pulmonary function tests (PFTs), particularly IOS levels, are recommended to assess severe OSA in obese patients.

Heart rate variability changes in patients with obstructive sleep apnea: A systematic review and meta-analysis

Obstructive sleep apnea is a common sleep breathing disorder related to autonomic nervous function disturbances. Heart rate variability is an important non-invasive indicator of autonomic nervous system function. The PubMed, Embase, Medline and Web of Science databases were systematically searched for English literature comparing patients with obstructive sleep apnea with controls up to May 2021. Heart rate variability outcomes, including integrated indices (parasympathetic function and total variability), time domain indices (the standard deviation of NN intervals and the root mean square of the successive differences between normal heartbeats) and frequency domain indices (high-frequency, low-frequency, very-low-frequency and the ratio of low-frequency to high-frequency) were derived from the studies. Twenty-two studies that included 2565 patients with obstructive sleep apnea and 1089 healthy controls were included. Compared with controls, patients with obstructive sleep apnea exhibited significantly reduced parasympathetic function. For the obstructive sleep apnea severity subgroup meta-analysis, patients with severe obstructive sleep apnea had significantly lower parasympathetic function, high-frequency, root mean square of the successive differences between normal heartbeats and standard deviation of NN intervals, and higher low-frequency and ratios of low-frequency to high-frequency. However, only the ratio of low-frequency to high-frequency was significantly higher in patients with moderate obstructive sleep apnea than in controls. Finally, for the collection time analysis, patients with obstructive sleep apnea had significantly higher low-frequency and ratio of low-frequency to high-frequency at night, significantly lower parasympathetic function, high-frequency, root mean square of the successive differences between normal heartbeats and standard deviation of NN intervals, and a higher ratio of low-frequency to high-frequency during the day than controls. Autonomic function impairment was more serious in patients with severe obstructive sleep apnea. During sleep, low-frequency can well reflect the impairment of autonomic function in obstructive sleep apnea, and the ratio of low-frequency to high-frequency may play an important role in obstructive sleep apnea diagnosis.

Multiple Machine Learning Methods Reveal Key Biomarkers of Obstructive Sleep Apnea and Continuous Positive Airway Pressure Treatment

Obstructive sleep apnea (OSA) is a worldwide health issue that affects more than 400 million people. Given the limitations inherent in the current conventional diagnosis of OSA based on symptoms report, novel diagnostic approaches are required to complement existing techniques. Recent advances in gene sequencing technology have made it possible to identify a greater number of genes linked to OSA. We identified key genes in OSA and CPAP treatment by screening differentially expressed genes (DEGs) using the Gene Expression Omnibus (GEO) database and employing machine learning algorithms. None of these genes had previously been implicated in OSA. Moreover, a new diagnostic model of OSA was developed, and its diagnostic accuracy was verified in independent datasets. By performing Single Sample Gene Set Enrichment Analysis (ssGSEA) and Counting Relative Subsets of RNA Transcripts (CIBERSORT), we identified possible immunologic mechanisms, which led us to conclude that patients with high OSA risk tend to have elevated inflammation levels that can be brought down by CPAP treatment.