Independent association of severity of obstructive sleep apnea with lipid metabolism of atherogenic index of plasma (AIP) and apoB/apoAI ratio

Association between obstructive sleep apnea risk and atherosclerosis: A nationwide cross-sectional study in the Korean population

OBJECTIVES

Obstructive sleep apnea (OSA) increases the risk of all-cause and cardiovascular mortality. This study aimed to investigate the association between OSA and atherogenic risk in the Koreans.

METHODS

Data from 8,158 participants (mean age, 57.9 ± 11.7; male/female, 1:1.4) obtained from the Korea National Health and Nutrition Examination Survey between 2019 and 2021. OSA risk was screened using the STOP-BANG score, and atherogenic risk was measured using the atherogenic index of plasma (AIP). Logistic regression was used to evaluate the association between the STOP-BANG scores and high AIP and subgroups according to the presence of diabetes.

RESULTS

The proportions of individuals with atherogenic risk (AIP > 0.24) were 13.7%, 27.6%, and 34.7% in the low-, intermediate-, and high-OSA risk groups (p < 0.001). After adjustment, individuals with intermediate and high OSA risk had 1.35 (95% confidence interval [CI], 1.16-1.58; p < 0.001) and 1.32 (95% CI, 1.08-1.61; p = 0.006) times higher odds of having atherogenic risk than those with low OSA risk. Among patients without diabetes, high OSA risk was not an independent factor affecting atherogenic risk (hazard ratio [HR], 1.17; 95% CI, 0.93-1.47). However, among patients with diabetes, compared with those with low OSA risk, those with intermediate (HR, 1.51; 95% CI, 1.05-2.19) and high OSA risk (HR, 1.58; 95% CI, 1.02-2.46) had significantly increased atherogenic risk.

CONCLUSION

OSA is linked to increased atherogenic risk in the Koreans, especially in individuals with diabetes, thus highlighting the importance of routine OSA screening to manage and reduce cardiovascular risks.

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.

Traditional and nontraditional lipid parameters in Helicobacter pylori infection

Aims: This study sought to evaluate the relationship between Helicobacter pylori infection and traditional and nontraditional lipid parameters, including atherogenic index of plasma, cardiogenic risk ratio, atherogenic coefficient and remnant cholesterol. Methods: After the application of exclusion criteria, 309 patients were allocated according to the absence (n = 52) or presence (n = 257) of H. pylori infection. Results: Total cholesterol, low-density lipoprotein cholesterol (LDL-C) and non-high-density lipoprotein cholesterol (non-HDL-C) levels were nonsignificantly higher, and HDL-C levels were nonsignificantly lower, in the H. pylori-infected patient group. Triglyceride-to-HDL-C ratio, LDL-C-to-HDL-C ratio, atherogenic index of plasma, cardiogenic risk ratio, atherogenic coefficient and remnant cholesterol were comparable among groups. Conclusion: There was no significant association between H. pylori infection and traditional and nontraditional novel lipid parameters and indices.

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.

A Machine Learning Prediction Model of Adult Obstructive Sleep Apnea Based on Systematically Evaluated Common Clinical Biochemical Indicators

Objective

Obstructive sleep apnea (OSA) is a common and potentially fatal sleep disorder. The purpose of this study was to construct an objective and easy-to-promote model based on common clinical biochemical indicators and demographic data for OSA screening.

Methods

The study collected the clinical data of patients who were referred to the Sleep Medicine Center of the Second Affiliated Hospital of Fujian Medical University from December 1, 2020, to July 31, 2023, including data for demographics, polysomnography (PSG), and 30 biochemical indicators. Univariate and multivariate analyses were performed to compare the differences between groups, and the Boruta method was used to analyze the importance of the predictors. We selected and compared 10 predictors using 4 machine learning algorithms which were "Gaussian Naive Bayes (GNB)", "Support Vector Machine (SVM)", "K Neighbors Classifier (KNN)", and "Logistic Regression (LR)". Finally, the optimal algorithm was selected to construct the final prediction model.

Results

Among all the predictors of OSA, body mass index (BMI) showed the best predictive efficacy with an area under the receiver operating characteristic curve (AUC) = 0.699; among the predictors of biochemical indicators, triglyceride-glucose (TyG) index represented the best predictive performance (AUC = 0.656). The LR algorithm outperformed the 4 established machine learning (ML) algorithms, with an AUC (F1 score) of 0.794 (0.841), 0.777 (0.827), and 0.732 (0.788) in the training, validation, and testing cohorts, respectively.

Conclusion

We have constructed an efficient OSA screening tool. The introduction of biochemical indicators in ML-based prediction models can provide a reference for clinicians in determining whether patients with suspected OSA need PSG.

Sex Differences in the Efficacy of Mediterranean Diet Treatment: A Nutrigenomics Pilot Study

The Mediterranean diet (MedD) has been shown to have beneficial effects on health, well-being, and mental status. It potentially modulates gene expressions linked to oxidative stress, contributing to its beneficial effects on overall health. The aim of this study was to assess the effects of MedD treatment in healthy human volunteers on the expression of ten genes related to oxidative stress and inflammation in women and men. Of 30 enrolled subjects, 17 were eligible, 10 women and 7 men. All of them received the same MedD treatment. Before and after 8 weeks of MedD treatment, an evaluation of body composition, blood tests, and anthropometric and clinical parameters was performed. Furthermore, 10 genes were amplified and analyzed. The study showed significant differences between females and males in body composition and biochemical parameters before and after MedD treatment. Significant differences between females and males in Resistance Force (p < 0.009) and Diastolic Blood Pressure (p < 0.04) before MedD treatment, and in High-Density Lipoprotein (p < 0.02) after MedD treatment, were observed. Moreover, a significant upregulation of Apolipoprotein E and Angiotensin I-Converting Enzyme in females has been shown. Sex differences impact MedD treatment response, and influence the genetic expression of genes related to oxidative stress; our findings may help to personalize diet therapy and contribute to overall health and well-being.

Association between nontraditional lipid profiles and the severity of obstructive sleep apnea: A retrospective study

BACKGROUND

Due to the significant role of dyslipidemia, cardiovascular diseases (CVDs) are very common in obstructive sleep apnea (OSA). Nontraditional lipid indices are considered to be a better predictive index for cardiovascular risk. Nevertheless, the association between nontraditional lipid profiles and the severity of OSA is not clear.

METHODS

A retrospective study was proceeded on 635 patients. Subjects were diagnosed with OSA through polysomnography (PSG). The association between severe OSA and nontraditional lipid profiles [triglyceride (TG)/high-density lipoprotein cholesterol (HDL-C) ratio, total cholesterol (TC)/HDL-C ratio, low-density lipoprotein cholesterol (LDL-C)/HDL-C ratio, non-high-density lipoprotein cholesterol (non-HDL-C), atherogenic index (AI), and lipoprotein combine index (LCI)] was examined by utilizing the restricted cubic spline and multivariate logistic regression analysis.

RESULTS

All nontraditional lipid indices had positive relationships with the severity of OSA. By multivariable adjustment, the per SD increment of the TG/HDL-C, TC/ HDL-C, LDL-C/HDL-C, non-HDL-C, AI, and LCI were significantly associated with 88%, 50%, 42%, 40%, 50%, and 125% higher risk for severe OSA respectively. Compared with the lowest tertiles, the adjusted ORs (95% CI) were 2.42 (1.57-3.75), 2.39 (1.53-3.73), 2.35 (1.52-3.64), 1.86 (1.21-2.86), 2.39 (1.53-3.73), and 2.23 (1.43-3.48) for the top tertiles of TG/HDL-C, TC/ HDL-C, LDL-C/HDL-C, non-HDL-C, AI, and LCI respectively.

CONCLUSION

All nontraditional lipid indices had positive relationship with the severity of OSA. In addition, TG/HDL-C, TC/HDL-C, and AI had better performance than the other nontraditional lipid indices for predicting severe OSA. These findings could help to determine the risk of cardiovascular diseases and improve the dyslipidemia management of OSA patients.

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.

Correlation of cardiovascular risk predictors with overweight and obesity in patients with familial hypercholesterolemia

Purpose

We aimed to analyze the correlation between overweight and obesity-related indicators and cardiovascular risk predictors in patients with familial hypercholesterolemia (FH) and to evaluate their mutual predictive properties.

Methods

A total of 103 patients with FH included from 2004 to 2017 were retrospectively analyzed. Pearson correlation analysis and multiple linear regression analysis were used to assess the correlation between overweight and obesity-related indicators and cardiovascular risk predictors in FH patients. Subject operating characteristic (ROC) curve was used to analyze their reciprocal predictive performance.

Results

(1) Atherogenic index of plasma (AIP) (β = 0.020) and ApoB/ApoA1 Ratio (BAR) (β = 0.015) were independently correlated with body mass index (BMI) (P &lt; 0.05); AIP (β = 1.176) was independently correlated with waist-to-hip ratio (WHR) (P &lt; 0.01); AIP (β = 1.575), BAR (β = 0.661) and atherogenic coefficient (AC) (β = 0.427) were independently correlated with waist-to-height ratio (WHtR) (P &lt; 0.05). (2) The area under the ROC (AUC) for overweight corresponding to AIP, BAR, and AC were 0.695 (95% CI = 0.593–0.797, P &lt; 0.01), 0.660 (95% CI = 0.555–0.766, P &lt; 0.01), and 0.632 (95% CI = 0.525–0.740, P &lt; 0.05), respectively; and AUCs for central obesity corresponding to AIP, BAR and AC were 0.757 (95% CI = 0.656–0.857, P &lt; 0.001), 0.654 (95% CI = 0.536–0.771, P &lt; 0.05) and 0.651 (95% CI = 0.538–0.764, P &lt; 0.05), respectively. The AUCs for moderate risk of AIP corresponding to BMI, WHR, and WHtR were 0.709 (95% CI = 0.608–0.811, P &lt; 0.001), 0.773 (95% CI = 0.678–0.867, P &lt; 0.001), 0.739 (95% CI = 0.641–0.836, P &lt; 0.001), respectively, and BMI, WHR and WHtR corresponded to an AUC of 0.691 (95% CI = 0.585–0.797, P &lt; 0.01), 0.734 (95% CI = 0.632–0.835, P &lt; 0.001), and 0.706 (95% CI = 0.603–0.810, P &lt; 0.01) for high risk of AIP, respectively.

Conclusion

AIP has independent positive linear correlation with indicators related to overweight and obesity in FH patients; AIP has good predictive performance for overweight and obesity in FH patients, and WHR has good performance for identifying moderate and high risk of AIP in FH patients.

High-density lipoprotein cholesterol efflux capacity in patients with obstructive sleep apnea and its relation with disease severity

Background

Obstructive sleep apnea (OSA) is linked to an accelerated risk of cardiovascular disease (CVD). Some key CVD risk factors are present in patients suffering from OSA such as hypertension, inflammation, oxidative stress, and dyslipidemia. High-density lipoprotein (HDL) cholesterol efflux capacity (CEC) is proposed as a reliable biomarker of HDL function and the present study aimed to quantify this biomarker in patients with OSA.

Methods

ATP binding cassette subfamily A member 1 (ABCA1), non-ABCA1, and total CEC were determined in 69 polysomnographic-confirmed OSA patients and 23 controls. Moreover, paraoxonase (PON) activities, high-sensitivity C-reactive protein (hsCRP), apolipoprotein B (apo B), and apolipoprotein A-I (apo A-I) circulating levels were quantified in the studied population.

Results: All CEC measures were reduced in the OSA group compared to the control group. Strikingly, ABCA1 CEC was diminished in severe OSA in comparison with mild OSA. Furthermore, PON activities and apo A-I showed lower levels, while hsCRP and apo B were elevated in OSA patients compared to controls. Moreover, ABCA1 CEC showed an inverse association with hsCRP and a positive association with apo A-I, while non-ABCA1 CEC presented an association with HDL-C.

Conclusion

These results suggest the presence of an impaired HDL function in OSA. In particular, ABCA1 CEC was associated with disease severity and inflammation which could be a factor increasing the risk of CVD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-022-01723-w.

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.

Comparison of Composite Lipid Indices in Patients with Obstructive Sleep Apnoea

PURPOSE

Obstructive sleep apnoea (OSA) is a recognised risk factor for cardiovascular disease. However, it is difficult to evaluate the risk of cardiovascular disease in patients with OSA due to multiple shared risk factors. Composite lipid indices, such as atherogenic index of plasma (AIP), visceral adiposity index (VAI) and lipid accumulation product (LAP) have been shown to predict cardiovascular disease better than their individual lipid components. This study aimed to evaluate these indices in patients with OSA.

PATIENTS AND METHODS

Six hundred sixty-seven (667) patients with OSA and 139 non-OSA control volunteers participated in the study. Fasting serum triglycerides, total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol (HDL-C) levels were measured, and AIP, LAP and VAI were calculated following cardiorespiratory polygraphy. The relationship between lipid parameters, OSA and its comorbidities was evaluated using receiver operating curve (ROC) analysis.

RESULTS

We found a significant difference in all lipid parameters between OSA patients and controls. Comparing ROCs, LAP was significantly more strongly associated with OSA compared to all the other parameters. The optimal cut-off value for LAP to detect OSA was 76.4, with a sensitivity of 63% and a specificity of 76%. In addition, LAP was the best parameter to predict hypertension and diabetes in patients with OSA, and it was predictive for ischaemic heart disease together with HDL-C.

CONCLUSION

Our results support the use of LAP in clinical practice when evaluating cardiovascular risk in patients with OSA. However, the optimal cut-off value should be determined in large-scale follow-up studies.

Associations of work-related stress and total sleep time with cholesterol levels in an occupational cohort of Japanese office workers

OBJECTIVE

The aim of the study was to investigate the associations of total sleep time (TST) and occupational stress based on the Brief Job Stress Questionnaire (BJSQ) with cholesterol levels in an occupational cohort of Japanese office workers.

METHODS

The present study is a secondary analysis of a subset of participants from a randomized controlled trial. Participants were 179 employees from 5 companies in Tokyo who participated as the intervention group in a 3-month lifestyle intervention study among office workers with metabolic syndrome or at risk of metabolic syndrome. All intervention-group participants used a mobile app and a wearable device. The final population for analysis in the present study were 173 participants. Cholesterol measures were derived from participants' annual health check-up data in the fiscal year preceding their inclusion in the study. Multiple linear regression models were used to determine the association between exposures and outcome.

RESULTS

Overall, stress levels were significantly and inversely associated with LDL-C (-7.12 mg/dl; 95% CI: -11.78, -2.45) and LDL-C/HDL-C ratio (-0.16 mg/dl; 95% CI: -0.27, -0.04) per standard deviation increase. Compared to average TST 5.9-7.2 hours, average TST of 4.0-5.3 hours (-4.82 mg/dl; 95% CI: -9.22, -0.43) was inversely associated with HDL-C.

CONCLUSION

Incremental increases of stress were significantly and inversely associated with LDL-C and LDL-C/HDL-C ratio. The shortest average TST was inversely associated with HDL-C. The results should be interpreted with care given certain methodological limitations.

Atherogenic Index of Plasma in Obstructive Sleep Apnoea

Background: Dyslipidaemia is well recognised in obstructive sleep apnoea (OSA) and could contribute to the development of cardiovascular disease (CVD). Atherogenic index of plasma (AIP) predicts cardiovascular morbidity and mortality better than the individual lipid levels. The aim of this study was to investigate the AIP in patients with OSA in relation with disease severity. Methods: Four hundred sixty-one patients with OSA and 99 controls participated in this study. AIP was assessed in the morning following a diagnostic sleep study. The association between lipid values and OSA were adjusted for age, gender, and body mass index. Results: Patients with OSA had higher AIP and triglyceride, and lower high-density lipoprotein cholesterol (HDL-C) levels (all p < 0.05). AIP significantly correlated with the Epworth Sleepiness Scale score (ρ = 0.19), the apnoea-hypopnoea index (ρ = 0.40) and oxygen desaturation index (ρ = 0.43, all p < 0.05). However, there was no relationship between the AIP and markers of sleep quality such as total sleep time, sleep period time, sleep efficiency, arousal index or percentage of REM sleep (all p > 0.05). AIP was not a better predictor for self-reported cardiovascular disease or diabetes than HDL-C. Conclusions: AIP is elevated in OSA and is related to disease severity. However, it does not seem to have an additional clinical value compared to HDL-C.