Comparison of Composite Lipid Indices in Patients with Obstructive Sleep Apnoea

Association between atherogenic index of plasma level and cardiovascular events in patients with obstructive sleep apnea: The sleep heart health study

BACKGROUND

The atherogenic index of plasma (AIP) has been demonstrated as a predictor for cardiovascular disease (CVD) in various populations. However, there are quite limited studies on the association between AIP and incident CVD among adults with obstructive sleep apnea (OSA).

METHODS

Data were obtained from the Sleep Heart Health Study, including 2578 participants with OSA and without pre-existing CVD. AIP was calculated as lg (triglycerides/high-density lipoprotein-cholesterol). Baseline AIP was stratified into quartiles (Q1-Q4). Multivariate logistic regression and restricted cubic spline analyses were performed to examine the relationship between AIP and CVD.

RESULTS

After a median follow-up of 11.67 years, 580 (22.50 %) OSA patients developed CVD, including 184 (7.10 %) with myocardial infarction (MI), and 400 (15.50 %) with coronary artery disease (CHD [including MI]), and 127 (4.90 %) with stroke. The multivariate logistic regression and restricted cubic spline analyses demonstrated a significant association between AIP and incidence of CVD, CHD, and MI, but not stroke. Compared with Q1 group, the fully adjusted odds ratios from Q2 group to Q4 group were: 1.33 (0.98, 1.80), 1.41 (1.03, 1.92), and 1.54 (1.12, 2.14) for CVD; 1.71 (1.04, 2.86), 1.92 (1.17, 3.21), and 2.01 (1.19, 3.45) for MI; 1.48 (1.04, 2.11), 1.68 (1.18, 2.40), and 1.70 (1.18, 2.47) for CHD.

CONCLUSION

This study demonstrated that higher AIP level is associated with incident CVD, except stroke, independent of OSA severity and hypoxia among OSA patients. These findings suggest that monitoring AIP can facilitate the early identification of OSA patients at high risk of CVD.

The relationship between composite lipid indices and baveno classification in patients with obstructive sleep apnoea

Obstructive Sleep Apnoea (OSA) is associated with the development of cardiovascular disease (CVD); however, the risk is only weekly related to OSA severity traditionally determined by the apnoea-hypopnoea index. The Baveno classification was developed to improve patient selection who would benefit from OSA treatment in terms of symptoms improvement and CVD risk reduction. However, it is unclear how the classification relates to biomarkers of CVD risk. Composite lipid indices were evaluated in various populations and showed good predictive value for incident CVD. One thousand two hundred and forty-two patients with OSA were included in the study. Composite lipid indices, including the atherogenic index of plasma (AIP), visceral adiposity index (VAI), lipid accumulation product (LAP) and cardiometabolic index (CMI) were compared between different Baveno groups (A - minor symptoms, minor comorbidities, B - severe symptoms, minor comorbidities, C - minor symptoms, severe comorbidities, D - severe symptoms, severe comorbidities). All composite lipid indices were higher in group D versus groups A and C. Only LAP (86.93 /58.40-119.49/ vs. 75.73 /48.37-99.04/) and CMI (1.03 /0.69-1.42/ vs. 0.91 /0.63-1.12/) were significantly different between the minimally symptomatic groups (C vs. A), and solely LAP was significantly higher (110.69 /76.76-147.22/ vs. 82.32 /60.35-113.50/) when the highly symptomatic groups (D vs. B) were compared. The Baveno classification correlates with cardiovascular risk estimated with composite lipid indices. Composite lipid indices may help better stratifying cardiovascular risk in both minimally- and highly symptomatic patients.

Influence of sleep on physiological systems in atherosclerosis

Sleep is a fundamental requirement of life and is integral to health. Deviation from optimal sleep associates with numerous diseases including those of the cardiovascular system. Studies, spanning animal models to humans, show that insufficient, disrupted or inconsistent sleep contribute to poor cardiovascular health by disrupting body systems. Fundamental experiments have begun to uncover the molecular and cellular links between sleep and heart health while large-scale human studies have associated sleep with cardiovascular outcomes in diverse populations. Here, we review preclinical and clinical findings that demonstrate how sleep influences the autonomic nervous, metabolic and immune systems to affect atherosclerotic cardiovascular disease.

Protective Role of TRPC3 Gene Polymorphism (rs10518289) in Obstructive Sleep Apnea Hypopnea Syndrome Among Hypertensive Patients

BACKGROUND Obstructive sleep apnea-hypopnea syndrome (OSAHS) presents a significant health concern, particularly among individuals with essential hypertension (EH). Understanding the genetic underpinnings of this association is crucial for effective management and intervention. We investigated the relationship between TRPC3 gene polymorphisms and susceptibility to OSAHS in patients with EH. MATERIAL AND METHODS We enrolled 373 patients with EH hospitalized at the First Affiliated Hospital of Xinjiang Medical University between April 2015 and November 2017. Patients were categorized into EH (n=74) and EH+OSAHS (n=299) groups according to the apnea-hypopnea index. Sequenom detection technology was used for TRPC3 gene single-nucleotide polymorphism genotyping, including genotypes at rs953691, rs10518289, rs2292232, rs4995894, rs951974, and rs4292355. RESULTS Sex, smoking history, alcohol history, hypertension duration, fasting blood glucose, urea, creatinine, total cholesterol, HDL-C, LDL-C, glycosylated hemoglobin, 24-h mean systolic BP, and 24-h mean diastolic BP were not significantly different between the 2 groups (P>0.05); however, age, BMI, triglyceride levels differed significantly (P<0.05). No significant difference was detected in distribution frequency of polymorphisms of TRPC3 gene between the 2 groups (P>0.05), while genotype, dominant genotype, and recessive genotype at rs10518289 and alleles at rs4292355 differed significantly (P<0.05). Logistic regression analysis showed age, BMI, and CG+GG genotypes at rs10518289 were risk factors for OSAHS in patients with EH. Interaction between TRPC3 (rs10518289) and obesity was not a risk of OSAHS with EH (P>0.05). CONCLUSIONS CC genotype of rs10518289 in the TRPC3 gene could be a protective genetic marker of OSAHS, and CG+GG genotype may be a risk genetic marker of OSAHS with EH.

Association between the triglyceride glucose index and obstructive sleep apnea and its symptoms: results from the NHANES

BACKGROUND

Certain studies have indicated a link between obstructive sleep apnea and insulin resistance in specific populations. To gain more clarity, extensive research involving a broad sample of the overall population is essential. The primary objective of this study was to investigate this correlation by utilizing data from the National Health and Nutrition Examination Survey database.

METHODS

The analysis incorporated data from the National Health and Nutrition Examination Survey database spanning the time periods from 2005 to 2008 and from 2015 to 2018, with a focus on American adults aged 18 years and older after applying weight adjustments. Key variables such as obstructive sleep apnea, triglyceride glucose index, and various confounding factors were considered. A generalized linear logistic regression model was used to investigate the association between obstructive sleep apnea and the triglyceride glucose index, with additional exploration of the consistency of the results through hierarchical analysis and other techniques.

RESULTS

The study included participants aged between 18 and 90 years, with an average age of 46.75 years. Among the total sample, 50.76% were male. The triglyceride glucose index demonstrated a diagnostic capability for obstructive sleep apnea, with an AUC of 0.701 (95% CI: 0.6619-0.688). According to the fully adjusted model, individuals in the fourth quartile of the triglyceride glucose index showed an increased likelihood of having obstructive sleep apnea compared to those in the first quartile (OR: 1.45; 95% CI: 1.02-2.06; P < 0.05). Subgroup analysis indicated that male sex (OR: 2.09; 95% CI: 1.76-2.45; P < 0.05), younger age (OR: 2.83; 95% CI: 2.02-3.96; P < 0.05), white ethnicity (OR: 2.29; 95% CI: 1.93-2.73; P < 0.05), and obesity (OR: 1.54; 95% CI: 1.28-1.85; P < 0.05) were correlated with an elevated risk of OSA.

CONCLUSIONS

This study demonstrated a strong association between an elevated TG index and OSA. Additionally, the triglyceride glucose index could serve as an independent predictor of obstructive sleep apnea.

Association between obstructive sleep apnea and visceral adiposity index and lipid accumulation product: NHANES 2015-2018

BACKGROUND

Obesity refers to a significant contributor to the development of obstructive sleep apnea (OSA). Early prediction of OSA usually leads to better treatment outcomes, and this study aims to employ novel metabolic markers, visceral adiposity index (VAI), and lipid accumulation product (LAP) to evaluate the relationship to OSA.

METHODS

The data used in the current cross-sectional investigation are from the National Health and Nutrition Examination Survey (NHANES), which was carried out between 2015 and 2018. To examine the correlation between LAP and VAI levels and OSA, multivariate logistic regression analysis was adopted. In addition, various analytical methods were applied, including subgroup analysis, smooth curve fitting, and threshold effect analysis.

RESULTS

Among totally 3932 participants, 1934 were included in the OSA group. The median (Q1-Q3) values of LAP and VAI for the participants were 40.25 (21.51-68.26) and 1.27 (0.75-2.21), respectively. Logistic regression studies indicated a positive correlation between LAP, VAI, and OSA risk after adjusting for potential confounding variables. Subgroup analysis revealed a stronger correlation between LAP, VAI levels, and OSA among individuals aged < 60 years. Through smooth curve fitting, specific saturation effects of LAP, VAI, and BMD were identified, with inflection points at 65.684 and 0.428, respectively.

CONCLUSION

This study demonstrates that elevated levels of LAP and VAI increase the risk of OSA, suggesting their potential as predictive markers for OSA and advocating for dietary and exercise interventions to mitigate OSA risk in individuals with high LAP and VAI levels.

Application Value of Cardiometabolic Index for the Screening of Obstructive Sleep Apnea with or Without Metabolic Syndrome

Background

Obstructive sleep apnea (OSA) is a common chronic disease with various comorbidities. The cardiometabolic index (CMI) reflects visceral fat tissue distribution and function, assessing the risk of obesity-related conditions such as metabolic syndrome (MetS) and stroke, which are strongly connected to OSA. The relationship between CMI with OSA and OSA combined with MetS (OMS) remains unclear. This study aims to evaluate the screening value of CMI for OSA and OMS, compared to the lipid accumulation product (LAP).

Methods

A total of 280 participants who underwent polysomnography were finally included, with the measurements of metabolic-related laboratory test results such as total cholesterol and triglyceride. Receiver operating curve (ROC) analysis and calculation of the area under the curve (AUC) were conducted to assess the screening potential of CMI, LAP, and the logistic regression models established based on them for OSA and OMS. The Youden index, sensitivity, and specificity were used to determine the optimal cutoff points.

Results

ROC curve analysis revealed that the AUCs for CMI in screening OSA and OMS were 0.808 and 0.797, and the optimal cutoff values were 0.71 (sensitivity 0.797, specificity 0.776) and 0.89 (sensitivity 0.830, specificity 0.662), respectively, showing higher Youden index than LAP. The AUCs of screening models based on CMI for OSA and OMS were 0.887 and 0.824, respectively.

Conclusion

CMI and LAP can effectively screen for OSA and OMS, while CMI has more practical cutoff values for identifying the diseased states. Screening models based on CMI demonstrate a high discriminatory ability for OSA and OMS, which needs verification in a large-scale population.

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.

Composite lipid indices in patients with obstructive sleep apnea: a systematic review and meta-analysis

BACKGROUND

One of the most prevalent sleep disorders affecting the individual's daily life is obstructive sleep apnea (OSA), for which obesity is a major risk factor. Several novel lipid indices have been suggested to have associations with OSA, among which visceral adiposity index (VAI), atherogenic index of plasma (AIP), and lipid accumulation product (LAP) are the most important ones. Herein, the current study aimed to systematically investigate the association between these indices and OSA.

METHODS

Four international databases, including PubMed, Scopus, the Web of Science, and Embase were searched in order to find relevant studies that investigated LAP, VAI, or AIP in OSA and compared them with non-OSA cases or within different severities of OSA. Random-effect meta-analysis was used to generate the standardized mean difference (SMD) and 95% confidence interval (CI) of the difference in lipid indices between OSA and non-OSA cases. Moreover, the pooled area under the receiver operating characteristic curves (AUCs) observed in individual studies for diagnosis of OSA based on these lipid indices were calculated by random-effect meta-analysis.

RESULTS

Totally 14 original studies were included, comprised of 14,943 cases. AIP, LAP, and VAI were assessed in eight, five, and five studies, respectively. Overall, these lipid indices had acceptable diagnostic ability (AUC 0.70, 95% CI 0.67 to 073). Meta-analysis revealed that AIP was significantly higher in patients with OSA (SMD 0.71, 95% CI 0.45 to 0.97, P < 0.01). Moreover, AIP also increased in higher severities of OSA. Regarding LAP, a higher LAP was observed in OSA/patients with high risk for OSA rather than in controls/low risk for OSA (SMD 0.53, 95% CI 0.25 to 0.81, P < 0.01). VAI was also increased in OSA based on results from two studies.

CONCLUSION

These findings suggest that composite lipid indices are increased in OSA. Also, these indices can have the potential beneficiary diagnostic and prognostic ability in OSA. Future studies can confirm these findings and enlighten the role of lipid indices in OSA.

Association between glycolipids and risk of obstructive sleep apnea: A population-based study

Background

This study aimed to investigate the associations between multiple glycolipid biomarkers and the risk of obstructive sleep apnea (OSA).

Methods

Participants (10,286) aged from 35 to 74 years old were included in this cross-sectional study from the baseline survey of the Guangzhou Heart Study. OSA was ascertained using both Berlin Questionnaire and STOP-BANG Questionnaire. Fasting blood samples were collected from each participant; fasting blood glucose (FBG) and serum concentrations of high-density lipoprotein cholesterol (HDL-CH), low-density lipoprotein cholesterol (LDL-CH), total cholesterol (TC), and triglyceride (TG) were determined. Odds ratio (OR) with 95% confidence interval (CI) was calculated using the multivariate logistic regression model after adjustment for covariates.

Results

Of the participants included, 15.56% were categorized into the pre-OSA group, and 8.22% into the OSA group. When comparing the highest with the lowest quartiles, HDL-HC was associated with a 22% (OR: 0.78, 95% CI: 0.65–0.94) and 41% (OR: 0.59, 95% CI: 0.45–0.78) reduced risk of pre-OSA and OSA, triglyceride was associated with a 32% (OR 1.32, 95% CI 1.08–1.60) and a 56% (OR 1.56, 95% CI 1.18–2.07) increased risk of pre-OSA and OSA, and FBG was associated with a 1.37-fold (95% CI 1.13–1.67) risk of pre-OSA and 1.38-fold (95% CI 1.03–1.85) risk of OSA. A significant exposure-response trend was observed for HDL-HC, TG, and FBG with both OSA and Pre-OSA (all p &lt; 0.05). No significant association of LDL-CH and TC with the risk of both pre-OSA and OSA was observed.

Conclusion

The findings suggest that serum HDL-CH was inversely associated with OSA risk, while elevated serum TG and FBG could increase the risk of OSA. Healthy glycolipid metabolism warrants more attention in the field of OSA prevention.

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.