Contribution of sleep characteristics to the association between obstructive sleep apnea and dyslipidemia

Sleep architecture characteristics in patients with acute ischemic stroke

To investigate the changes in sleep architecture in patients with acute ischemic stroke (AIS) accompanied by sleep-disordered breathing (SDB), providing a basis for clinical treatment strategies. 1367 patients with acute ischemic stroke within 48 h of onset who were hospitalized in the Department of Neurology of Kailuan General Hospital from November 2020 to December 2022 were selected. Among them, 963 cases were male and 404 cases were female, age: 33-92 (66.12 ± 10.62) years old.From the start of hospitalization, patients were monitored for 5 consecutive days using the intelligent mattress type sleep monitoring platform system (IMTSMPS). From day 1 to day 5, there was a difference in non-rapid eye movement 3 (NREM3) sleep (min) day two, and day five compared to day one in the ACI without SDB group (p = 0.019), and rapid eye movement (REM) sleep (min) day three compared to day five in the ACI with SDB group (p = 0.001). TST (min), SL (min), WASO (min), TOB (min), NOA (min), HRV1, fluctuated between 5 d in mild SDB group (p < 0.05). SL (min), TOB (min), NOA (min), and HAV1(%) in the moderate SDB group, with fluctuations between 5 d (P < 0.05). TST (min), SL (min), REML(min), NREM3 (min), REM (min), proportion of REM sleep(%), TOB (min), NOA (min)in severe SDB group, there were fluctuations between 5 d (P < 0.05). SDB is one of the most common concomitant symptoms in AIS patients and is closely associated with multiple forms of altered sleep structure. AIS patients without SDB mainly showed changes in NREM3 sleep structure. AIS and SDB patients mainly showed changes in the structure of REM sleep. Different levels of SDB in AIS patients lead to different forms of structural changes in sleep.

Exploring the evolving frontiers of sleep deprivation research in the post-COVID-19 era

Sleep deprivation research (SDR) has undergone substantial transformations in the aftermath of the COVID-19 pandemic. This comprehensive study explores the SDR's evolving trends, hotspots, and conceptual structure in the post-COVID-19 era. Using bibliometric analysis with VOSviewer and Bibliometrix software, we examined the SDR publications from January 2020 to December 2023. Core sources were identified using Bradford law, and a dataset of 4578 English-based data-driven studies was retrieved from the Scopus database. Our analysis revealed a remarkable annual growth rate of 37.92% in SDR from 2020 to 2023, indicating a heightened research focus in this domain. Among prolific authors, Shao emerged as a key contributor, while Sleep ranked prominently as a leading publication venue. The United States and China have emerged as the most impactful countries for advancing SDR research. Uncovering the most cited documents sheds light on various focal points within SDR, including sleep duration, mental health implications, cardiovascular events, the impact of COVID-19 on sleep patterns, dementia, resilience in children, and sleep patterns among preschoolers. Noteworthy keywords that emerged from the analysis encompassed "sleep deprivation," "depression," "insomnia," "COVID-19," "anxiety," "fatigue," and "obesity." Using a thematic mapping approach, we delineated distinct themes characterized by niche, basic, emerging, and declining patterns. Clusters of SDR research were observed in areas such as "Fatigue," "Sleep apnea," "Sleep," "Sleep deprivation," "Migraine," "Caffeine," and "Recovery." Furthermore, trending themes in SDR encompassed "Sleep disturbance," "excessive daytime sleepiness," and "Gamma-Aminobutyric Acid." These comprehensive findings provide valuable insights into the current landscape of SDR, illuminating emerging trends, identifying hotspots, and offering directions for future research in this critical field.

Determinative sleep traits associated with dyslipidemia in obstructive sleep apnea patients

BACKGROUND

Obstructive sleep apnea (OSA) is recognized to increase the risk of dyslipidemia; however, the specific sleep traits in OSA that influence dyslipidemia are poorly understood. This study sought to determine which sleep traits are independently associated with dyslipidemia and serum lipid profiles in patients with OSA.

METHODS

In this cohort study, 5239 participants were included from the Sleep Heart Health Study. Further, OSA was diagnosed via polysomnography with an AHI ≥ 5 events/h. Sleep traits were assessed using polysomnographic data and questionnaires. Then, logistic regression was used to identify sleep traits that predict dyslipidemia in OSA patients. Non-linear associations between sleep traits and dyslipidemia were evaluated using restricted cubic splines. The potential mediating effect of body mass index (BMI) was also calculated. Later, linear regression analysis identified sleep traits that were independently linked to lipid levels.

RESULTS

After adjusting for confounding factors, logistic regression identified sleep latency (OR: 1.005, 95% CI: 1.002-1.009, P = 0.001), rapid eye movement (REM) stage (OR: 0.987, 95% CI: 0.977-0.998, P = 0.022), REM latency (OR: 1.001, 95% CI: 1.000-1.002, P = 0.027), mean oxygen saturation (meanSpO2) (OR: 0.961, 95% CI: 0.926-0.996, P = 0.031), percentage of time with oxygen saturation below 95% (T95) (OR: 1.003, 95% CI: 1.001-1.005, P = 0.005), and time to fall asleep (OR: 1.004, 95% CI: 1.000-1.007, P = 0.042) as variables independently associated with dyslipidemia. No significant non-linear associations were found (all P >0.05). BMI mediated the association between REM stage, meanSpO2, T95, and dyslipidemia risk. Linear regression analysis identified T95 as a consistent independent determinant of all lipid parameters. Additionally, the meanSpO2 and sleep latency were significant independent determinants of most lipid parameters.

CONCLUSIONS

Sleep latency, sleep architecture, and nocturnal hypoxemia are key factors in dyslipidemia among patients with OSA. These insights suggest potential biomarkers and targeted interventions for the management of lipid-related complications of OSA.

Associations Among Cardiometabolic Risk Factors, Sleep Duration, and Obstructive Sleep Apnea in a Southeastern US Rural Community: Cross-Sectional Analysis From the SLUMBRx-PONS Study

BACKGROUND

Short sleep and obstructive sleep apnea are underrecognized strains on the public health infrastructure. In the United States, over 35% of adults report short sleep and more than 80% of individuals with obstructive sleep apnea remain undiagnosed. The associations between inadequate sleep and cardiometabolic disease risk factors have garnered increased attention. However, challenges persist in modeling sleep-associated cardiometabolic disease risk factors.

OBJECTIVE

This study aimed to report early findings from the Short Sleep Undermines Cardiometabolic Health-Public Health Observational study (SLUMBRx-PONS).

METHODS

Data for the SLUMBRx-PONS study were collected cross-sectionally and longitudinally from a nonclinical, rural community sample (n=47) in the southeast United States. Measures included 7 consecutive nights of wrist-based actigraphy (eg, mean of 7 consecutive nights of total sleep time [TST7N]), 1 night of sleep apnea home testing (eg, apnea-hypopnea index [AHI]), and a cross-sectional clinical sample of anthropometric (eg, BMI), cardiovascular (eg, blood pressure), and blood-based biomarkers (eg, triglycerides and glucose). Correlational analyses and regression models assessed the relationships between the cardiometabolic disease risk factors and the sleep indices (eg, TST7N and AHI). Linear regression models were constructed to examine associations between significant cardiometabolic indices of TST7N (model 1) and AHI (model 2).

RESULTS

Correlational assessment in model 1 identified significant associations between TST7N and AHI (r=-0.45, P=.004), BMI (r=-0.38, P=.02), systolic blood pressure (r=0.40, P=.01), and diastolic blood pressure (r=0.32, P=.049). Pertaining to model 1, composite measures of AHI, BMI, systolic blood pressure, and diastolic blood pressure accounted for 25.1% of the variance in TST7N (R2adjusted=0.25; F2,38=7.37; P=.002). Correlational analyses in model 2 revealed significant relationships between AHI and TST7N (r=-0.45, P<.001), BMI (r=0.71, P<.001), triglycerides (r=0.36, P=.03), and glucose (r=0.34, P=.04). Results from model 2 found that TST7N, triglycerides, and glucose accounted for 37.6% of the variance in the composite measure of AHI and BMI (R2adjusted=0.38; F3,38=8.63; P<.001).

CONCLUSIONS

Results from the SLUMBRx-PONS study highlight the complex interplay between sleep-associated risk factors for cardiometabolic disease. Early findings underscore the need for further investigations incorporating the collection of clinical, epidemiological, and ambulatory measures to inform public health, health promotion, and health education interventions addressing the cardiometabolic consequences of inadequate sleep.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/27139.

Variability in sleep architecture and alterations in circadian rhythms in patients with acute cerebral infarction accompanied by sleep-disordered breathing

PURPOSE

To continuously and dynamically monitor the sleep status of patients in the acute phase of cerebral infarction, and to investigate the characteristics of acute cerebral infarction(ACI)associated with sleep-disordered breathing (SDB), variations in sleep structure, and changes in sleep circadian rhythms.

METHODS

Patients with ACI within 48 h of onset who were admitted to the Department of Neurology at Kailuan General Hospital from November 2020 to December 2022 were selected. Detailed baseline information such as age, gender, smoking history, drinking history, were recorded for the selected participants. From the beginning of their hospitalization, the selected participants were monitored for their sleep status continuously for 5 days using the Intelligent Mattress-based Sleep Monitoring Platform System(IMSMPS). Based on the heart rate data obtained from the monitoring, the interdaily stability (IS) and intradaily variability (IV) of the sleep circadian rhythm were calculated.

RESULTS

1,367 patients with ACI were selected. Monitoring results over 5 days indicated 147 cases (10.75%) without SDB, and 1,220 cases (89.25%) with SDB. Among the group with SDB, there were 248 cases (18.14%) with continuous mild SDB, 395 cases (28.90%) with moderate SDB, 295 cases (21.58%) with severe SDB, and 282 cases (20.63%) that fluctuated between different severity levels. Within this fluctuating group, 152 cases (53.90%) fluctuated between two severity levels, 120 cases (42.55%) between three levels, and 10 cases (3.55%) among all four levels. There were statistically significant differences (P < 0.05) in the sleep latency, sleep efficiency, non-rapid eye movement stages 1-2, rapid eye movement, proportion of non-rapid eye movement, proportion of rapid eye movement, wake after sleep onset, time out of bed, number of awakenings, respiratory variability index, and heart rate variability index among patients with ACI monitored from day 1 to 5. However, other monitored sleep structure parameters did not show statistically significant differences (P > 0.05). The coefficient of variation for all sleep monitoring parameters ranged between 14.54 and 36.57%. The IV in the SDB group was higher than in the group without SDB (P < 0.05), and the IS was lower than in the group without SDB (P < 0.05).

CONCLUSION

Patients in the acute phase of cerebral infarction have a high probability of accompanying SDB. The sleep structure of these patients shows significant variability based on the onset time of the stroke, and some patients experience fluctuations among different severity levels of SDB. ACI accompanied by SDB can further reduce the IS of a patient's sleep circadian rhythm and increase its IV.

Independent relationship between sleep apnea-specific hypoxic burden and glucolipid metabolism disorder: a cross-sectional study

OBJECTIVES

Obstructive sleep apnea (OSA) is associated with abnormal glucose and lipid metabolism. However, whether there is an independent association between Sleep Apnea-Specific Hypoxic Burden (SASHB) and glycolipid metabolism disorders in patients with OSA is unknown.

METHODS

We enrolled 2,173 participants with suspected OSA from January 2019 to July 2023 in this study. Polysomnographic variables, biochemical indicators, and physical measurements were collected from each participant. Multiple linear regression analyses were used to evaluate independent associations between SASHB, AHI, CT90 and glucose as well as lipid profile. Furthermore, logistic regressions were used to determine the odds ratios (ORs) for abnormal glucose and lipid metabolism across various SASHB, AHI, CT90 quartiles.

RESULTS

The SASHB was independently associated with fasting blood glucose (FBG) (β = 0.058, P = 0.016), fasting insulin (FIN) (β = 0.073, P < 0.001), homeostasis model assessment of insulin resistance (HOMA-IR) (β = 0.058, P = 0.011), total cholesterol (TC) (β = 0.100, P < 0.001), total triglycerides (TG) (β = 0.063, P = 0.011), low-density lipoprotein cholesterol (LDL-C) (β = 0.075, P = 0.003), apolipoprotein A-I (apoA-I) (β = 0.051, P = 0.049), apolipoprotein B (apoB) (β = 0.136, P < 0.001), apolipoprotein E (apoE) (β = 0.088, P < 0.001) after adjustments for confounding factors. Furthermore, the ORs for hyperinsulinemia across the higher SASHB quartiles were 1.527, 1.545, and 2.024 respectively, compared with the lowest quartile (P < 0.001 for a linear trend); the ORs for hyper-total cholesterolemia across the higher SASHB quartiles were 1.762, 1.998, and 2.708, compared with the lowest quartile (P < 0.001 for a linear trend) and the ORs for hyper-LDL cholesterolemia across the higher SASHB quartiles were 1.663, 1.695, and 2.316, compared with the lowest quartile (P < 0.001 for a linear trend). Notably, the ORs for hyper-triglyceridemia{1.471, 1.773, 2.099} and abnormal HOMA-IR{1.510, 1.492, 1.937} maintained a consistent trend across the SASHB quartiles.

CONCLUSIONS

We found SASHB was independently associated with hyperinsulinemia, abnormal HOMA-IR, hyper-total cholesterolemia, hyper-triglyceridemia and hyper-LDL cholesterolemia in Chinese Han population. Further prospective studies are needed to confirm that SASHB can be used as a predictor of abnormal glycolipid metabolism disorders in patients with OSA.

TRIAL REGISTRATION

ChiCTR1900025714 { http://www.chictr.org.cn/ }; Prospectively registered on 6 September 2019; China.

Correlation between serum leptin level and sleep monitoring indexes in patients with obstructive sleep apnea hypopnea syndrome and its predictive value: a cross-sectional analysis

Objective

To investigate the association between serum leptin (LP) level and polysomnography (PSG) parameters in patients with obstructive sleep apnea hypopnea syndrome (OSAHS).

Methods

A cross-sectional study was conducted. The data of subjects who underwent PSG at hospital between January 2021 and December 2022 were collected retrospectively, 220 participants were included. The subjects were categorized into simple snoring group (n = 45), mild OSAHS group (n = 63), moderate OSAHS group (n = 52), and severe OSAHS group (n = 60). The general characteristics, PSG indices, and serological indices were collected retrospectively. Pearson correlation analysis was used to observe the correlation between serum LP level and PSG parameters. The value of serum LP level in predicting OSAHS was analyzed by receiver operating characteristic curve.

Results

The serum LP level was positively correlated with micro-arousal count, micro-arousal index (MAI), high apnea hypopnea index, times of blood oxygen decreased by≥3% and time in saturation lower 90%, and negatively correlated with lowest nocturnal oxygen saturation and mean oxygen saturation (p < 0.05). The area under the curve (AUC) of serum LP level in predicting the occurrence of OSAHS was 0.8276 (95% CI: 0.7713-0.8839), and when the Youden index was 0.587, the sensitivity was 72.00%, and the specificity was 86.67% (p < 0.0001). In the population with high MAI, the AUC of serum LP level in predicting the occurrence of OSAHS was 0.8825 (95% CI: 0.7833-0.9817), and when the Youden index was 0.690, the sensitivity was 79.00% and the specificity was 90.00% (p < 0.0001).

Conclusion

Serum LP level is associated with the severity of OSAHS. Serum LP level demonstrates a strong predictive value for the occurrence of OSAHS, particularly in population with high MAI.

Association of modifiable risk factors with obstructive sleep apnea: a Mendelian randomization study

BACKGROUND

The risk factors involved in obstructive sleep apnea (OSA) have not been clearly identified yet. We attempted to systematically investigate genetically predicted modifiable risk factors and lifestyle behaviors associated with OSA.

METHODS

The association between 34 risk factors and OSA was evaluated using the two-sample Mendelian randomization (MR). Genetic variants for risk factors were acquired from European-descent genome-wide studies. Data sources for OSA were extracted from FinnGen study with 16,761 cases and 201,194 controls. The primary analysis chosen was the inverse-variance weighted method.

RESULTS

MR analyses provide evidence of genetically predicted poor overall health rating (odds ratio (OR), 2.82; 95% confidence interval (CI), 1.95-4.08), nap during day (OR, 2.01; 95% CI, 1.37-2.93), high body mass index (BMI) (OR, 1.14; 95% CI, 1.09-1.19), increased body fat mass (OR, 1.83; 95% CI, 1.83-2.05), elevated body water mass (OR, 1.50; 95% CI, 1.31-1.70) and hypertension (OR, 1.81; 95% CI, 1.34-2.45) were associated with higher OSA risk, while high education level (OR, 0.55; 95% CI, 0.40-0.75) correlated with reduced OSA risk. Suggestive evidence was obtained for smoking and waist-to-hip ratio (WHR) with higher OSA odds, and vigorous physical activity, and HDL cholesterol with lower OSA odds. After adjusting for BMI using multivariable MR analysis, the effects of smoking, WHR, vigorous physical activity, and HDL-cholesterol were fully attenuated.

CONCLUSIONS

This MR study indicates that overall health rating, nap during day, BMI, body fat mass, body water mass, hypertension, and education are causally associated with the risk of OSA, which means that these modifiable risk factors are key targets for OSA prevention.

The impact of obstructive sleep apnea on nonalcoholic fatty liver disease

Obstructive sleep apnea (OSA) is characterized by episodic sleep state-dependent collapse of the upper airway, with consequent hypoxia, hypercapnia, and arousal from sleep. OSA contributes to multisystem damage; in severe cases, sudden cardiac death might occur. In addition to causing respiratory, cardiovascular and endocrine metabolic diseases, OSA is also closely associated with nonalcoholic fatty liver disease (NAFLD). As the prevalence of OSA and NAFLD increases rapidly, they significantly exert adverse effects on the health of human beings. The authors retrieved relevant documents on OSA and NAFLD from PubMed and Medline. This narrative review elaborates on the current knowledge of OSA and NAFLD, demonstrates the impact of OSA on NAFLD, and clarifies the underlying mechanisms of OSA in the progression of NAFLD. Although there is a lack of sufficient high-quality clinical studies to prove the causal or concomitant relationship between OSA and NAFLD, existing evidence has confirmed the effect of OSA on NAFLD. Elucidating the underlying mechanisms through which OSA impacts NAFLD would hold considerable importance in terms of both prevention and the identification of potential therapeutic targets for NAFLD.

Relationship between slow-wave sleep and serum γ-glutamine transaminase in non-obese men with obstructive sleep apnea-hypopnea syndrome

BACKGROUND

Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a disease characterized with intermittent hypoxia and sleep fragmentation. Obesity and gender are major risk factors for the onset of OSAHS. Previous studies on obese men with OSAHS have been performed, while few studies on non-obese men with OSAHS have been carried out. The purpose of this study was to explore the clinical characteristics of polysomnography and blood biochemical indexes in non-obese men with OSAHS and to identify the possible influencing factors.

METHODS

This retrospective study included patients with OSAHS who underwent polysomnography in our hospital. General clinical data such as overnight polysomnography and biochemical indicators were recorded. The patients were divided into two groups according to the apnea-hypopnea index (AHI): mild to moderate OSAHS and severe OSAHS. The differences in biochemical parameters such as the levels of γ-glutamine transaminase (GGT), triglyceride (TG), glucose (GLU), and sleep structure parameters such as N1, N2, slow-wave sleep (SWS), and rapid eye movement (REM) sleep were compared and analyzed. Spearman correlation analysis and logistic regression were used to identify the risk factors of non-obese men with OSAHS. ROC curves were used to evaluate the predictive ability of SWS and GGT on disease severity.

RESULTS

Of 94 non-obese men with OSAHS, 49 had mild to moderate OSAHS and 45 had severe OSAHS. Our data suggested that the levels of low oxygen saturation (L-SaO2), mean oxygen saturation (M-SaO2), SWS, and GGT were significantly changed in the mild to moderate OSAHS group compared with the severe group (p < 0.05). For patients with OSAHS, the proportion of SWS in the group with severe OSAHS was higher than that in the mild to moderate group (p < 0.05), and the serum GGT enzyme levels were significantly elevated in the severe group compared to the mild to moderate group (p < 0.05). Using logistic regression analyses, our data revealed that both SWS and GGT enzyme levels were independent risk factors for AHI (p < 0.05). In addition, the results of correlation analysis indicated that SWS was related to triglyceride (TG), total cholesterol (TC), apolipoprotein E (APOE), and triglyceride glucose (TyG) index (p < 0.05); GGT was related to TG, TC, APOE, and TyG index (p < 0.05). Furthermore, SWS was independently associated with GGT (p < 0.05). The area under the ROC curve plotted with the combined coefficient of SWS and serum GGT was 0.728, which was predictive of the disease severity.

CONCLUSIONS

These results suggest that SWS and GGT are independent associated factors of the severity of the disease. However, TyG index was not an independent associated factor of the severity of disease in non-obese men with OSAHS. In addition, SWS and GGT were negatively correlated. SWS combined with serum GGT may be predictive of the severity of the disease. This study may have added to our understanding of the pathogenesis of OSAHS in non-obese men.

The association of nocturnal hypoxemia with dyslipidemia in sleep-disordered breathing population of Chinese community: a cross-sectional study

BACKGROUND

Currently, there is limited and controversial clinical research on the correlation between sleep-disordered breathing (SDB) and dyslipidemia. This discrepancy in findings may be because studies that primarily focused on hospital-based populations may not be applicable to community-based populations. Therefore, the primary objective of this research endeavor is to scrutinize the correlation between nocturnal hypoxemia and blood lipid concentrations among adult individuals residing in the community who exhibit symptoms of SDB. Additionally, this study aimed to identify the nocturnal hypoxia parameters having the strongest correlation with this relationship.

METHODS

This cross-sectional study collected data from The Guangdong Sleep Health Study, which included 3829 participants. Type IV sleep monitoring was employed to measure hypoxemia parameters, and lipoproteins were evaluated using fasting blood samples. To understand the association between dyslipidemia and hypoxemia parameters, a multivariable logistic regression model was used. Subgroup analyses were conducted to stratify data according to age, sex, waist circumference, and chronic diseases.

RESULTS

The age of the individuals involved in the study spanned from 20 to 90 years. The average age of the participants was 56.15 ± 13.11 years. Of the total sample size, 55.7% were male. In the fully adjusted model, the meanSpO2 was negatively associated with hyperlipidemia (0.9303 [95% confidence interval 0.8719, 0.9925]). Upon conducting a nonlinearity test, the relationship between the meanSpO2 and hyperlipidemia was nonlinear. The inflection points were determined to be 95. When meanSpO2 ≥ 95%, a difference of 1 in the meanSpO2 corresponded to a 0.07 difference in the risk of hyperlipidemia.

CONCLUSIONS

This study revealed that higher meanSpO2 is significantly and negatively associated with hyperlipidemia in adult community residents with SDB, particularly when the meanSpO2 exceeds 95. This finding emphasizes the importance of close monitoring for dyslipidemia, which is considered an early indicator of atherosclerosis in patients with SDB who experience nocturnal hypoxia.

The association of nocturnal hypoxemia with dyslipidemia in sleep-disordered breathing population of Chinese community: a cross-sectional study

BACKGROUND

Currently, there is limited and controversial clinical research on the correlation between sleep-disordered breathing (SDB) and dyslipidemia. This discrepancy in findings may be because studies that primarily focused on hospital-based populations may not be applicable to community-based populations. Therefore, the primary objective of this research endeavor is to scrutinize the correlation between nocturnal hypoxemia and blood lipid concentrations among adult individuals residing in the community who exhibit symptoms of SDB. Additionally, this study aimed to identify the nocturnal hypoxia parameters having the strongest correlation with this relationship.

METHODS

This cross-sectional study collected data from The Guangdong Sleep Health Study, which included 3829 participants. Type IV sleep monitoring was employed to measure hypoxemia parameters, and lipoproteins were evaluated using fasting blood samples. To understand the association between dyslipidemia and hypoxemia parameters, a multivariable logistic regression model was used. Subgroup analyses were conducted to stratify data according to age, sex, waist circumference, and chronic diseases.

RESULTS

The age of the individuals involved in the study spanned from 20 to 90 years. The average age of the participants was 56.15 ± 13.11 years. Of the total sample size, 55.7% were male. In the fully adjusted model, the meanSpO2 was negatively associated with hyperlipidemia (0.9303 [95% confidence interval 0.8719, 0.9925]). Upon conducting a nonlinearity test, the relationship between the meanSpO2 and hyperlipidemia was nonlinear. The inflection points were determined to be 95. When meanSpO2 ≥ 95%, a difference of 1 in the meanSpO2 corresponded to a 0.07 difference in the risk of hyperlipidemia.

CONCLUSIONS

This study revealed that higher meanSpO2 is significantly and negatively associated with hyperlipidemia in adult community residents with SDB, particularly when the meanSpO2 exceeds 95. This finding emphasizes the importance of close monitoring for dyslipidemia, which is considered an early indicator of atherosclerosis in patients with SDB who experience nocturnal hypoxia.

Sleep Disorders and Coronary Artery Disease

A sufficient amount and quality sleep is vital components for maintaining optimal physical wellbeing, cognition, and cardiovascular health. Normal sleep provides us with a low physiological stress that promotes overall cardiovascular health. Sleep disorders are common, and often goes undiagnosed. Patients with sleep disorders, commonly suffer from poor quality of life due to the poor quality of their sleep. They are associated with adverse effects on cardiovascular health, such as coronary artery disease. Sleep disorders discussed in this review article include sleep-disordered breathing (obstructive sleep apnea and central sleep apnea), insomnia and restless leg syndrome. Sleep disorders primarily have four acute adverse cardiovascular consequences. First, intermittent hypoxemia-reoxygenation in arterial blood along with PCO 2 fluctuation; second is excessive arousals; third, decreased parasympathetic and increased sympathetic tone; fourth being the large pressure swings in the intrathoracic cavity. This review focuses on classifications, and prevalence of the three major classes of sleep disorders, and the evidence to date on the association between these sleep disorders and coronary artery disease.

Effect of obstructive sleep apnea on prognosis in patients with acute coronary syndromes with varying numbers of standard modifiable risk factors: insight from the OSA-ACS study

BACKGROUND

Standard modifiable risk factors (SMuRFs) increase the risk of cardiovascular events in patients with acute coronary syndrome (ACS) and are also strongly associated with obstructive sleep apnea (OSA) in a bidirectional relationship. However, the association of OSA with recurrent cardiovascular events in ACS patients based on the number of SMuRFs remains unclear. Hence, we aimed to elucidate the prognostic implication of OSA in ACS patients stratified by the number of SMuRFs.

METHODS

This was a post hoc analysis of the OSA-ACS study (NCT03362385), including 1927 patients admitted for ACS and undergoing portable sleep monitoring. OSA was defined as an apnea hypopnea index ≥ 15 events/h. The primary endpoint was major adverse cardiovascular and cerebrovascular event (MACCE) including cardiovascular death, myocardial infarction, stroke, hospitalization for unstable angina or heart failure, and ischemia-driven revascularization. Cox proportional hazards model and Kaplan-Meier analysis were used to investigated the relationship between OSA and subsequent cardiovascular events after patients were stratified by the number of SMuRFs.

RESULTS

Among 1927 patients enrolled, 130 (6.7%) had no SMuRF, 1264 (65.6%) exhibited 1-2 SMuRFs and 533 (27.7%) presented 3-4 SMuRFs. With the increase of the number of SMuRFs, the proportion of OSA in ACS patients tended to increase (47.7% vs. 51.5% vs. 56.6%), but there was no significant difference between them (P = 0.08). After the stratification of ACS patients via SMuRF numbers and adjustment for confounding factors, fully adjusted Cox regression indicated that OSA increased the risk of MACCE (adjusted HR, 1.65; 95%CI, 1.06-2.57; P = 0.026) and ischemia-driven revascularization (adjusted HR, 2.18; 95%CI, 1.03-4.65; P = 0.042) in ACS patients with 3-4 SMuRFs.

CONCLUSIONS

In hospitalized ACS patients, OSA is associated with an increased risk of MACCE and ischemia-driven revascularization among patients with 3-4 SMuRFs. Therefore, screening for OSA should be emphasized in ACS patients with 3-4 SMuRFs, and intervention trials should be prioritized in these high-risk patients.

SMAD4 Expression in Monocytes as a Potential Biomarker for Atherosclerosis Risk in Patients with Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) patients are at special risk of suffering atherosclerosis, leading to major cardiovascular diseases. Notably, the transforming growth factor (TGF-β) plays a crucial role in the development and progression of atherosclerosis. In this context, the central regulator of TGF-β pathway, SMAD4 (small mother against decapentaplegic homolog 4), has been previously reported to be augmented in OSA patients, which levels were even higher in patients with concomitant cardiometabolic diseases. Here, we analyzed soluble and intracellular SMAD4 levels in plasma and monocytes from OSA patients and non-apneic subjects, with or without early subclinical atherosclerosis (eSA). In addition, we used in vitro and ex vivo models to explore the mechanisms underlying SMAD4 upregulation and release. Our study confirmed elevated sSMAD4 levels in OSA patients and identified that its levels were even higher in those OSA patients with eSA. Moreover, we demonstrated that SMAD4 is overexpressed in OSA monocytes and that intermittent hypoxia contributes to SMAD4 upregulation and release in a process mediated by NLRP3. In conclusion, this study highlights the potential role of sSMAD4 as a biomarker for atherosclerosis risk in OSA patients and provides new insights into the mechanisms underlying its upregulation and release to the extracellular space.

Investigating the Relationship between Obstructive Sleep Apnoea, Inflammation and Cardio-Metabolic Diseases

Obstructive sleep apnoea (OSA) is a prevalent underdiagnosed disorder whose incidence increases with age and weight. Uniquely characterised by frequent breathing interruptions during sleep-known as intermittent hypoxia (IH)-OSA disrupts the circadian rhythm. Patients with OSA have repeated episodes of hypoxia and reoxygenation, leading to systemic consequences. OSA consequences range from apparent symptoms like excessive daytime sleepiness, neurocognitive deterioration and decreased quality of life to pathological complications characterised by elevated biomarkers linked to endocrine-metabolic and cardiovascular changes. OSA is a well-recognized risk factor for cardiovascular and cerebrovascular diseases. Furthermore, OSA is linked to other conditions that worsen cardiovascular outcomes, such as obesity. The relationship between OSA and obesity is complex and reciprocal, involving interaction between biological and lifestyle factors. The pathogenesis of both OSA and obesity involve oxidative stress, inflammation and metabolic dysregulation. The current medical practice uses continuous positive airway pressure (CPAP) as the gold standard tool to manage OSA. It has been shown to improve symptoms and cardiac function, reduce cardiovascular risk and normalise biomarkers. Nonetheless, a full understanding of the factors involved in the deleterious effects of OSA and the best methods to eliminate their occurrence are still poorly understood. In this review, we present the factors and evidence linking OSA to increased risk of cardiovascular conditions.

Integrative Analysis and Experimental Validation of Competing Endogenous RNAs in Obstructive Sleep Apnea

Background: Obstructive sleep apnea (OSA) is highly prevalent yet underdiagnosed. This study aimed to develop a predictive signature, as well as investigate competing endogenous RNAs (ceRNAs) and their potential functions in OSA. Methods: The GSE135917, GSE38792, and GSE75097 datasets were collected from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. Weighted gene correlation network analysis (WGCNA) and differential expression analysis were used to identify OSA-specific mRNAs. Machine learning methods were applied to establish a prediction signature for OSA. Furthermore, several online tools were used to establish the lncRNA-mediated ceRNAs in OSA. The hub ceRNAs were screened using the cytoHubba and validated by real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR). Correlations between ceRNAs and the immune microenvironment of OSA were also investigated. Results: Two gene co-expression modules closely related to OSA and 30 OSA-specific mRNAs were obtained. They were significantly enriched in the antigen presentation and lipoprotein metabolic process categories. A signature that consisted of five mRNAs was established, which showed a good diagnostic performance in both independent datasets. A total of twelve lncRNA-mediated ceRNA regulatory pathways in OSA were proposed and validated, including three mRNAs, five miRNAs, and three lncRNAs. Of note, we found that upregulation of lncRNAs in ceRNAs could lead to activation of the nuclear factor kappa B (NF-κB) pathway. In addition, mRNAs in the ceRNAs were closely correlated to the increased infiltration level of effector memory of CD4 T cells and CD56bright natural killer cells in OSA. Conclusions: In conclusion, our research opens new possibilities for diagnosis of OSA. The newly discovered lncRNA-mediated ceRNA networks and their links to inflammation and immunity may provide potential research spots for future studies.

Obstructive Sleep Apnoea and Lipid Metabolism: The Summary of Evidence and Future Perspectives in the Pathophysiology of OSA-Associated Dyslipidaemia

Obstructive sleep apnoea (OSA) is associated with cardiovascular and metabolic comorbidities, including hypertension, dyslipidaemia, insulin resistance and atherosclerosis. Strong evidence suggests that OSA is associated with an altered lipid profile including elevated levels of triglyceride-rich lipoproteins and decreased levels of high-density lipoprotein (HDL). Intermittent hypoxia; sleep fragmentation; and consequential surges in the sympathetic activity, enhanced oxidative stress and systemic inflammation are the postulated mechanisms leading to metabolic alterations in OSA. Although the exact mechanisms of OSA-associated dyslipidaemia have not been fully elucidated, three main points have been found to be impaired: activated lipolysis in the adipose tissue, decreased lipid clearance from the circulation and accelerated de novo lipid synthesis. This is further complicated by the oxidisation of atherogenic lipoproteins, adipose tissue dysfunction, hormonal changes, and the reduced function of HDL particles in OSA. In this comprehensive review, we summarise and critically evaluate the current evidence about the possible mechanisms involved in OSA-associated dyslipidaemia.

Annual review of selected scientific literature: A report of the Committee on Scientific Investigation of the American Academy of Restorative Dentistry

The Scientific Investigation Committee of the American Academy of Restorative Dentistry offers this review of the 2021 dental literature in restorative dentistry to inform busy dentists regarding noteworthy scientific and clinical progress over the past year. Each member of the committee brings discipline-specific expertise to coverage of this broad topical area. Specific subject areas addressed, in order of the appearance in this report, include COVID-19 and the dental profession (new); prosthodontics; periodontics, alveolar bone, and peri-implant tissues; implant dentistry; dental materials and therapeutics; occlusion and temporomandibular disorders; sleep-related breathing disorders; oral medicine and oral and maxillofacial surgery; and dental caries and cariology. The authors focused their efforts on reporting information likely to influence daily dental treatment decisions with an emphasis on future trends in dentistry. With the tremendous volume of dentistry and related literature being published daily, this review cannot possibly be comprehensive. Rather, its purpose is to update interested readers and provide important resource material for those interested in pursuing greater details on their own. It remains our intent to assist colleagues in negotiating the extensive volume of important information being published annually. It is our hope that readers find this work useful in successfully managing the patients and dental problems they encounter.

Cardiovascular remodeling in obstructive sleep apnea: focus on arterial stiffness, left ventricular geometry and atrial fibrillation

INTRODUCTION

Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder that is associated with increased risk of cardiovascular disease. The main interest of this clinical review is to discuss the cardiovascular consequences of OSA with a special focus on left ventricular (LV) function and structure, arterial stiffness and atrial fibrillation.

AREA COVERED

We present an overview of the definition, prevalence, and risk factors of OSA and outline the association between OSA and cardiovascular complications. We then briefly discuss echocardiographic assessment in OSA with focus on the left atrium and LV. Finally, we highlight the importance of adherence to continuous positive airway pressure (CPAP) therapy with regard to reducing the risk of cardiovascular disease.

EXPERT COMMENTARY

Although OSA has a strong association with cardiovascular complications, it is often underdiagnosed and undertreated. Patients with resistant hypertension and atrial fibrillation with poor therapeutic success after cardioversion or catheter ablation should be more often screened for OSA. Patients with nocturnal adverse cardiovascular events (stroke, arrhythmias, angina, coronary events) should be closely assessed with regard to OSA, and if confirmed, timely treated by lifestyle modification, CPAP, and aggressive antihypertensive treatment. Adherence to CPAP in OSA patients is essential in terms of reducing the risk of cardiovascular events.

Changes of circulating biomarkers of inflammation and glycolipid metabolism by CPAP in OSA patients: a meta-analysis of time-dependent profiles

Background:

Continuous positive airway pressure (CPAP) is the first-line therapy for moderate-to-severe obstructive sleep apnea (OSA). Specifying timing of CPAP benefits on OSA-related biomarkers will help to assess the effectiveness of CPAP and to optimize the treatment strategies.

Purpose:

To explore the time-dependent changes of circulating biomarkers to CPAP treatment in patients with OSA, including inflammatory biomarkers [C-reactive protein (CRP) and tumor necrosis factor–α (TNF-α)] and glycolipid metabolic biomarkers [fasting blood glucose (FBG), fasting insulin (FINS), low-density lipoprotein (LDL), high-density lipoprotein (HDL), total cholesterol (TC), and triglyceride (TG)].

Methods:

Searches of PubMed and Embase database were completed. Two independent reviewers extracted data from 68 included studies. A meta-analysis was conducted using a random-effect (or fixed-effect) model and standardized mean difference (SMD) model. The timing profiles of circulating biomarkers changes of inflammation and glycolipid metabolism were analyzed based on different CPAP duration, that is, short-term (<3 months), mid-term (3–6 months), and long-term (⩾6 months).

Results:

Those first improved by short-term treatment include CRP [SMD: 0.73, 95% confidence interval (CI): 0.15–1.31; p = 0.014], TNF-α [SMD: 0.48 (95% CI: 0.10–0.86; p = 0.014)], FBG [SMD: 0.32 (95% CI: 0.07–0.57; p = 0.011)], and LDL [SMD: 0.40 (95% CI: 0.18–0.62; p = 0.000)]. Those first improved by the mid-term or long-term treatment include HDL [SMD: –0.20 (95% CI: –0.36 to –0.03; p = 0.018)] and TC [SMD: 0.20 (95% CI: 0.05–0.34; p = 0.007)]. There were insignificant changes for TG and FINS after short or long CPAP.

Conclusion:

Our results imply that changes of circulating biomarkers for patients with OSA under CPAP treatment have a time-dependent profile.

A Review of the Associations Between Obstructive Sleep Apnea and Gestational Diabetes Mellitus and Possible Mechanisms of Disease

Obstructive sleep apnea (OSA) usually leads to the occurrence of diabetes. Gestational diabetes mellitus (GDM) is a common gestational complication associated with adverse maternal and fetal outcomes. Increasing studies suggest that women with OSA during pregnancy may be at a significantly greater risk of developing GDM. It is crucial to explore the association between OSA and GDM and the mechanisms underlying this association. In this review, we presented a comprehensive literature review of the following: the association between OSA and GDM, the possible mechanisms of this association, and the effects of continuous positive airway pressure (CPAP) on OSA with GDM. The results showed that most authors suggested that there was an association between OSA and GDM. The intermittent hypoxemia (IH) and reduction of slow-wave sleep (SWS) may be the key to this association. IH induces the products of oxidative stress and inflammation as well as dysregulation of the hypothalamic-pituitary-adrenal, which lead to diabetes. In addition, SWS reduction in OSA enhances the inflammation by increasing the inflammatory cytokines, increases the sympathetic activation, and causes changes in leptin level, which result in the development of GDM. Additionally, whether CPAP is beneficial to GDM remains still unclear.

CPAP Intervention as an Add-On Treatment to Lipid-Lowering Medication in Coronary Artery Disease Patients with Obstructive Sleep Apnea in the RICCADSA Trial

Dyslipidaemia is a well-known risk factor for coronary artery disease (CAD), and reducing lipid levels is essential for secondary prevention in management of these high-risk individuals. Dyslipidaemia is common also in patients with obstructive sleep apnea (OSA). Continuous positive airway pressure (CPAP) is the first line treatment of OSA. However, evidence of a possible lipid-lowering effect of CPAP in CAD patients with OSA is scarce. We addressed the effect of CPAP as an add-on treatment to lipid-lowering medication in a CAD cohort with concomitant OSA. This study was a secondary analysis of the RICCADSA trial (Trial Registry: ClinicalTrials.gov; No: NCT00519597), that was conducted in Sweden between 2005 and 2013. In total, 244 revascularized CAD patients with nonsleepy OSA (apnea-hypopnea index ≥ 15/h, Epworth Sleepiness Scale score < 10) were randomly assigned to CPAP or no-CPAP. Circulating triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL) and low-density lipoprotein (LDL) levels (all in mg/dL) were measured at baseline and 12 months after randomization. The desired TG levels were defined as circulating TG < 150 mg/dL, and LDL levels were targeted as <70 mg/dL according to the recent guidelines of the European Cardiology Society and the European Atherosclerosis Society. A total of 196 patients with available blood samples at baseline and 12-month follow-up were included (94 randomized to CPAP, 102 to no-CPAP). We found no significant between-group differences in circulating levels of TG, TC, HDL and LDL at baseline and after 12 months as well as in the amount of change from baseline. However, there was a significant decline regarding the proportion of patients with the desired TG levels from 87.2% to 77.2% in the CPAP group (p = 0.022), whereas there was an increase from 84.3% to 88.2% in the no-CPAP group (n.s.). The desired LDL levels remained low after 12 months in both groups (15.1% vs. 17.2% in CPAP group, and 20.8% vs. 18.8% in no-CPAP group; n.s.). In a multiple linear regression model, the increase in the TG levels was predicted by the increase in body-mass-index (β = 4.1; 95% confidence interval (1.0-7.1); p = 0.009) adjusted for age, sex and CPAP usage (hours/night). CPAP had no lipid-lowering effect in this revascularized cohort with OSA. An increase in body-mass-index predicted the increase in TG levels after 12 months, suggesting that lifestyle modifications should be given priority in adults with CAD and OSA, regardless of CPAP treatment.

Obesity and Obstructive Sleep Apnea

Obstructive sleep apnea (OSA) is characterized by upper airway collapse during sleep. Chronic intermittent hypoxia, sleep fragmentation, and inflammatory activation are the main pathophysiological mechanisms of OSA. OSA is highly prevalent in obese patients and may contribute to cardiometabolic risk by exerting detrimental effects on adipose tissue metabolism and potentiating the adipose tissue dysfunction typically found in obesity. This chapter will provide an update on: (a) the epidemiological studies linking obesity and OSA; (b) the studies exploring the effects of intermittent hypoxia and sleep fragmentation on the adipose tissue; (c) the effects of OSA treatment with continuous positive airway pressure (CPAP) on metabolic derangements; and (d) current research on new anti-diabetic drugs that could be useful in the treatment of obese OSA patients.

The Causal Effects of Lipid Profiles on Sleep Apnea

Introduction

Observational studies have suggested that lipid profiles were associated with risk of sleep apnea (SA). However, the specific lipid types and whether this relationship has a causal effect are uncertain. This study conducted two-sample Mendelian randomization (MR) and multivariable Mendelian randomization (MVMR) to investigate the potential causal relationship between lipid profiles and risk of SA.

Materials and Methods

We used the largest genome-wide association study (GWAS) on European participants on the UK Biobank. After a rigorous single nucleotide polymorphism screening process to remove confounding effects, we performed MR and MVMR to explore the causal relationship between lipid profiles and SA risk.

Results

Both MR and MVMR showed causal effects of increased triglyceride on SA risk [MR: per 10 units, odds ratio (OR): 1.0156; 95% CI: 1.0057-1.0257; P value = 0.002; MVMR: per 10 units, OR: 1.0229; 95% CI: 1.0051-1.0411; P value = 0.011]. The sensitivity analysis including Cochran's Q test, MR-Egger intercept, and MR pleiotropy residual sum and outlier (MR-PRESSO) test indicated that our findings were robust. The causal effects of triglyceride on SA did not change after adjusting for potential confounders (obesity, age, sex, and airway obstruction).

Conclusion

Genetically increased triglyceride levels have independent causal effects on risk of sleep apnea without the confounding effects of obesity, suggesting that lowering triglyceride concentrations may help to reduce the risk of sleep apnea.

Identification and Validation of Prognostic Factors of Lipid Metabolism in Obstructive Sleep Apnea

Background: Obstructive sleep apnea (OSA) is considered to be an independent factor affecting lipid metabolism. This study explored the relationship between immune genes and lipid metabolism in OSA.

Methods: Immune-related Differentially Expressed Genes (DEGs) were identified by analyzing microarray data sets from the Gene Expression Omnibus (GEO) database. Subsequently, we conducted protein-protein interaction (PPI) network analysis and calculated their Gene Ontology (GO) semantic similarity. The GO, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, Disease Ontology (DO), gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were employed for functional enrichment analyses and to determine the most significant functional terms. Combined with the results of boruta and random forest, we selected predictors to build a prognostic model, along with seeking out the potential TFs and target drugs for the predictive genes.

Results: Immune-related DEGs included 64 genes upregulated and 98 genes downregulated. The enrichment analysis might closely associate with cell adhesion and T cell-mediated immunity pathways and there were many DEGs involved in lipid and atherosclerosis signaling pathways. The highest-ranking hub gene in PPI network have been reported lowly expressed in OSA. In line with the enrichment analysis, DO analysis reveal that respiratory diseases may be associated with OSA besides immune system disorders. Consistent with the result of the KEGG pathway, the analysis of GSVA revealed that the pro-inflammation pathways are associated with OSA. Monocytes and CD8 T cells were the predominant immune cells in adipose tissue. We built a prognostic model with the top six genes, and the prognostic genes were involved in the polarization of macrophage and differentiation of T lymphocyte subsets. In vivo experimental verification revealed that EPGN, LGR5, NCK1 and VIP were significantly down-regulated while PGRMC2 was significantly up-regulated in mouse model of OSA.

Conclusions: Our study demonstrated strong associations between immune genes and the development of dyslipidemia in OSA. This work promoted the molecular mechanisms and potential targets for the regulation of lipid metabolism in OSA.

Circulating levels of ghrelin, galanin, and orexin-A orexigenic neuropeptides in obstructive sleep apnea syndrome

PURPOSE

The orexigenic peptides, ghrelin, galanin, and orexin-A, have an important role in food intake and energy homeostasis and regulate the higher brain functions including the sleep-wake state. Although the interactions of these neuropeptides affect neuroendocrine systems resulting in obesity, a major risk factor for obstructive sleep apnea syndrome (OSAS), the mechanism has not been fully elucidated. The objective of this study was to evaluate the association of serum ghrelin, galanin, and orexin-A levels with OSAS.

METHODS

In this cross-sectional study, patients who underwent one-night polysomnography and conformed to the inclusion criteria were asked to participate. A blood sample was obtained from all participants on the morning of the sleep test to evaluate the serum levels of ghrelin, galanin, and orexin-A using the enzyme-linked immunosorbent assay (ELISA) method. Demographic characteristics, polysomnography data, and serum levels of the participants were recorded and analyzed. Comparison between the OSAS groups was performed by independent sample t-test, Mann-Whitney U test, and Kruskal-Wallis test with post hoc K-W test using SPSS 20.0.

RESULTS

Of 272 patients, those in the OSAS group (n=210) were older than patients in the non-OSAS group (n=62), p < 0.003, and had increased BMI, p < 0.006. Patients with, serum ghrelin, galanin, and orexin-A levels were significantly elevated in patients with OSAS (635.9 pg/mL vs. 420.7 pg/mL, 91.0 pg/mL vs. 60.0 pg/mL, 600.3 pg/mL vs. 485.6 pg/mL, respectively) and found to be higher in patients with severe OSAS than mild and moderate cases (p < 0.01). In multinomial logistic regression to predict the OSAS severity, levels of serum ghrelin (OR = 1.016 [1.010-1.021]; p < 0.001), galanin (OR = 1.050 [1.020-1.081]; p < 0.001), and orexin-A (OR = 1.021 [1.012-1.030]; p < 0.001) were significantly associated only with a moderate level of OSAS.

CONCLUSION

The orexigenic neuropeptides were found to be an independent determinant of the presence of OSAS and correlate with the severity of OSAS. Increased levels of ghrelin, galanin, and orexin-A were associated with the presence of moderate OSAS.

The Association of Obstructive Sleep Apnea and Nocturnal Hypoxemia with Lipid Profiles in a Population-Based Study of Community-Dwelling Australian Men

OBJECTIVE

To determine the association of obstructive sleep apnea and nocturnal hypoxemia with serum lipid profiles in unselected community-dwelling men.

METHODS

Cross-sectional data from participants of the Men Androgen Inflammation Lifestyle Environment and Stress (MAILES) study (n=753) who underwent full in-home polysomnography (Embletta X100) was used. Triglycerides, high- (HDL), low-density lipoprotein (LDL), and total cholesterol were assessed on a fasting morning blood sample. Multivariable linear regression analyses assessed associations between lipids and continuous measures of nocturnal hypoxemia (oxygen desaturation index (3%) (ODI), apnea-hypopnea index (AHI), and rapid eye movement sleep apnea-hypopnea index (REM-AHI)), adjusted for chronic conditions, risk behavior and sociodemographic factors. Sensitivity analyses examined the effect of lipid lowering therapies on reported estimates. Effect modification was examined through stratification by waist circumference groups.

RESULTS

In 753 participants with mean (SD) age of 60.8 (10.9) years and waist circumference: 99.3 (11.6) cm, the prevalence of OSA (AHI≥10) was 52.6%. Overall, no significant associations between OSA metrics and lipid measures were found. Similarly, sensitivity analysis excluding lipid lowering therapies showed no significant associations. In analysis stratified by waist circumference (<95cm, 95-100cm, >100cm), ODI (3%, unstandardized B: 0.027, 95% CI: 0.015-0.040), AHI (0.023, 0.012-0.033) and AHI_REM (0.012, 0.001-0.022) were positively associated with serum triglycerides in participants with a normal waist circumference (<95cm).

CONCLUSION

Obstructive sleep apnea metrics were positively associated with serum triglyceride levels in men with a normal waist circumference. Healthy weight individuals with OSA require clinical attention to improve cardiometabolic risk profiles.