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Prognostic implications of obstructive sleep apnea in patients with acute coronary syndrome stratified by homocysteine level: a prospective cohort study

Respiratory Research volume 24, Article number: 313 (2023) Cite this article

Abstract

Background

Sporadic studies have examined the impact of OSA on ACS patients by homocysteine (Hcy) level. This study attempted to comprehensively evaluate the effects of the interaction between Hcy and OSA on long-term cardiovascular outcomes in ACS patients.

Methods

In this prospective, large-scale cohort study, 2160 patients admitted for ACS were recruited to undergo overnight sleep monitoring. OSA was diagnosed when apnea–hypopnea index ≥ 15 events/h. Patients with normohomocysteinemia (NHcy) were defined as having serum Hcy ≤ 15 μmol/L, and the others had hyperhomocysteinemia (HHcy). The primary endpoint was major adverse cerebrocardiovascular event (MACCE), a composite of cardiovascular death, myocardial infarction, stroke, ischemia-driven revascularization and hospitalization for unstable angina and heart failure.

Results

A total of 1553 eligible ACS patients (average age: 56.3 ± 10.5 years) were enrolled, among which 819 (52.7%) had OSA, and 988 (63.6%) were with NHcy. OSA did not significantly affect the level of Hcy. During a median follow-up of 2.9 (1.6, 3.5) years, after adjustment for clinical confounders, OSA was associated with increased risk for MACCE occurrence versus non-OSA ones in ACS patients with NHcy (adjusted hazard ratio [HR] = 1.36, 95% confidence interval [CI] 1.02–1.83, P = 0.039), but not in those with HHcy (adjusted HR = 0.92, 95%CI 0.62–1.36, P = 0.668). There was an absence of interaction between homocysteine level and OSA in relation to MACCE (interaction P = 0.106).

Conclusions

OSA was independently associated with worse prognosis in ACS patients with NHcy. Our study emphasized the necessity to identify potential presence of OSA in such a population.

Trial registration: ClinicalTrials.gov; Number: NCT03362385; URL: www.clinicaltrials.gov.

Introduction

Obstructive sleep apnea (OSA), characterized by repetitive collapse of upper airway followed by snoring, intermittent hypoxemia, sleep fragmentation and autonomic oscillations, has been recognized as a serious global health burden in consideration of the prevalence and the detrimental impacts on neurocognition and cardiovascular systems [1, 2]. OSA is prevalent in general population that affects ~ 34% and 17% of men and women, respectively [3], which could remarkably increase to 50–65% in patients with established acute coronary syndrome (ACS) [4,5,6,7], with respect to the implications of OSA in both etiology and progression of ACS [8, 9]. Based on this notion, accumulating studies from our group and others have demonstrated that OSA contributes as an important risk factors to the occurrence of cardiovascular events in ACS patients during long-term follow-up [4, 5, 10]. Although the underlying mechanisms are intricate and obscure, concomitant metabolic disorders (e.g., hyperglycemia, dyslipidemia and hyperuricemia) function as one of the linchpins of this association [11,12,13], among which homocysteine (Hcy) is a potential risk factor [14, 15].

Hcy, a sulfhydryl-containing amino acid, is an intermediate product in the metabolism of methionine [16]. Elevated serum Hcy is involved in pathogenesis and progression of ACS [16,17,18]. Additionally, several investigators have found the correlation between OSA and Hcy that serum Hcy level increased with the severity of OSA [19, 20]. However, rigorously controlled comparative studies unraveled that OSA per se appeared not to promote the excess of Hcy [14, 21] but otherwise advanced age, obesity, renal dysfunction, thyroid diseases and various drugs accounted more for [15, 22], yielding the hypothesis that variance in Hcy level among OSA patients might be ascribed to distinct risk factor profiles concomitant with OSA [15]. From this perspective, serum Hcy could act as a biomarker reflecting the coexistence of OSA and metabolic disorders. In addition, it was also notable that Hcy and OSA shared analogous pathophysiological pathways in coronary atherogenesis, comprising vascular endothelial dysfunction, platelet aggregation, smooth muscle cell proliferation, oxidative stress, endothelia-leukocyte interaction and inflammatory infiltration [15, 23], contributing synergistically to the development of new-onset hypertension, increased episode of cardiovascular events and higher mortality during long-term follow-up in patients without prior ACS [23, 24].

Nevertheless, to our knowledge, effects of this interaction between OSA and Hcy on the long-term cardiovascular outcomes in patients with established ACS have not been previously evaluated. Therefore, based on a large-scale prospective cohort, we executed current study to investigate the chronic impact exerted by OSA on ACS patients in relation to Hcy level.

Methods

Study population

The OSA-ACS project (NCT03362385), executed by Beijing Anzhen Hospital, Capital Medical University, is a large-scale, prospective cohort study attempting to assess the effects exerted by OSA on cardiovascular prognosis of ACS patients. Designing schemes of the project and criteria for patient recruitment have been explicitly described in our published data [4, 5]. Briefly, 18–85 years patients admitted for ACS from June 2015 to January 2020 were recruited to undergo overnight sleep monitoring after clinical stabilization of ACS. ACS was determined when diagnosed with ST-segment elevation myocardial infarction (STEMI), non-ST-segment elevation myocardial infarction (NSTEMI), or unstable angina (UA). Patients with cardiogenic shock, cardiac arrest, previous or present utilization of continuous positive airway pressure (CPAP), malignancy (life expectancy < 2 years), and invalid recordings during sleep study were further excluded. In addition, we also precluded those with central sleep apnea (≥ 50% central events or central apnea hypopnea index (AHI) ≥ 10 events/h) prevailing, regular CPAP therapy (> 3 months) after discharge and loss of follow-up. In current study, patients with serum Hcy ≤ 15 μmol/L were defined as normohomocysteinemia (NHcy) and the other with Hcy > 15 μmol/L were classified into hyperhomocysteinemia (HHcy) group, in accordance with prior studies [25].

This study cohered with the STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) guidelines, and was complied with the principles of Declaration of Helsinki. The protocol was ratified by the Ethics Committee of Beijing Anzhen Hospital, Capital Medical University (2013025). All patients were asked to sign informed consent before enrollment.

Overnight sleep monitoring

Overnight sleep monitoring was performed by type III portable devices (ApneaLink Air, Resmed, Australia), after clinical stabilization of ACS for a median duration of 2 days. Trained research staff, blinded to the clinical characteristics of the patients, randomly assigned devices to the patients one to one before sleep and took back on the next morning to extract related data, including nasal airflow, thoracoabdominal movements, snoring episodes, heart rate, and arterial oxygen saturation. Moreover, the sleep studies were score manually according to criteria proclaimed by the American Academy of Sleep Medicine. Afterwards, apnea was defined as an absence of airflow for ≥ 10 s (coexistence of thoracoabdominal movements indicated obstructive apnea otherwise indicated central apnea), and hypopnea was identified when nasal airflow reduced by at least 30% for ≥ 10 s accompanied by arterial oxygen saturation (SaO2) declining > 4%. Sleep monitoring with effectiveness required sufficient polygraphy signal recording lasting for at least 3 h. Among patients undergoing successful monitoring, AHI (the sum of apneas and hypopneas per hour), oxygen desaturation index (ODI), minimum oxyhemoglobin saturation (SaO2), mean SaO2 and percentage of time with SaO2 < 90% (T90) were recorded. Patients with AHI ≥ 15 events/h was then diagnosed with OSA.

Clinical procedures

During index hospitalization, patients received standard care and medications for ACS, in accordance with current guideline recommendations [26, 27]. Percutaneous coronary intervention (PCI) or coronary artery bypass grafting (CABG) was implemented if clinically indicated. Patients with AHI ≥ 15 events/h, particularly those with excessive daytime sleepiness assessed by the Epworth Sleepiness Scale (ESS) scoring, were referred to the sleep medicine center for assessment to decide further treatment, including CPAP for OSA. The baseline demographic, clinical and procedural information were comprehensively collected.

Follow-up and endpoints

Clinical visits, which was fulfilled via clinic visit, medical records, or telephone calls by researchers blinded to the patients’ data, were scheduled at 1 month, 3 months, 6 months, 12 months, and every 6 months thereafter since index hospitalization.

The primary endpoint was major adverse cerebrocardiovascular events (MACCE) composed of cardiovascular death, recurrent myocardial infarction (MI), stroke, ischemia-driven revascularization, and hospitalization for UA and heart failure (HF). Secondary endpoints comprised every component of primary endpoint, all-cause death, all repeat revascularization, and non-culprit revascularization. All endpoints were complied with the definitions published by the Standardized Data Collection for Cardiovascular Trials Initiative [28] (Additional file 1: Methods).

Statistical analysis

Baseline characteristics, sleep monitoring results and outcomes were stratified by Hcy level (≤ 15 μmol/L or > 15 μmol/L) and OSA status (AHI ≥ 15 events/h or < 15 events/h). Continuous variables were presented as mean ± standard deviation or median (interquartile: first and third quartiles) and were compared by the Student t test or Mann–Whitney U test, respectively. Categorical variables were shown as the number (percentage) and were compared by χ2 statistics or Fisher’s exact test, as appropriate.

In outcome analyses, time-to-event data and cumulative incidence of primary endpoint and secondary endpoints according to the interaction between Hcy and OSA were plotted by Kaplan–Meier curves, and the difference was examined by log-rank test. Schoenfeld residuals were checked to ensure the proportionality assumption in the Cox model for OSA status in relation to MACCE, which was confirmed by a P > 0.05. Univariable and multivariable Cox analyses were executed in both Hcy groups, respectively, to calculate the hazard ratios (HRs) with 95% confidence interval (CI), from which the risk of OSA patients for the occurrence of MACCE and key secondary endpoints, compared to those without OSA, was evaluated. A Finn-Gray model was executed to assess whether competing risk existed between MACCE and non-cardiogenic death. Covariates incorporated in multivariable Cox proportional hazards model were mainly based on the baseline variables which were considered clinically relevant or those showed a univariable association with primary outcomes, encompassing age, gender, body mass index (BMI), hypertension, diabetes mellitus, hyperlipidemia, prior MI, prior stroke, ACS types, smoking status, drinking and estimated glomerular filtration rate (eGFR) < 90 mL/min/1.73 m2. Variables for inclusion were carefully selected in consideration of the number of events available, to fulfill parsimony and accuracy of the final models.

Subgroup analyses of primary endpoint in both Hcy groups were executed based on important characteristics of interest, including age (< 65 or ≥ 65 years), gender, BMI (< 28 or ≥ 28 kg), hypertension (yes or no), diabetes mellitus (yes or no), hyperlipidemia (yes or no), ACS types (STEMI or NSTE-ACS), prior MI (yes or no), prior stroke (yes or no) and renal dysfunction (eGFR < 90 or ≥ 90 mL/min/1.73 m2), where the HRs were adjusted for confounders similar to outcome analyses, except for the grouping variable. Additionally, multiplicative interaction terms were appended to the adjusted COX models to assess whether the grouping variables modified the associations between OSA and risk for MACCE incidence.

All statistical analyses were conducted with SPSS (version 26.0, IBM SPSS Inc, Armonk, NY, USA) and R Statistical Software (version 4.2.0; R Foundation for Statistical Computing, Vienna, Austria). A two-tailed P < 0.05 was considered statistically significant.

Results

Study population and factors associated with Hcy level

A total of 2160 ACS patients were assessed for eligibility, among which 2058 underwent successful overnight sleep monitoring, followed by exclusion of patients with central sleep apnea (n = 59), regular CPAP therapy after discharge (n = 42), loss of follow-up (n = 30) and those without Hcy data (n = 374). Eventually, 1553 were involved in further analyses, with an average age of 56.3 ± 10.5 years (Fig. 1). Among them, 819 (52.7%) patients had AHI ≥ 15 events/h. We subsequently observed analogous level and distribution pattern of Hcy between OSA and non-OSA patients (13.1 [9.8, 17.9] vs. 12.8 [9.6, 18.8], P = 0.598; Fig. 2A, P = 0.661). Furthermore, the distribution patterns of AHI, which indicated severity of OSA, also did not differ between HHcy and NHcy patients (Fig. 2B, P = 0.481; Additional file 2: Table S1). In contrast, we identified several factors associated with the variance of Hcy in ACS patients, including advanced age, gender, diabetes mellitus, smoking and renal function (Additional file 3: Fig. S1).

Fig. 1
figure 1

Flow diagram of patient enrollment. ACS acute coronary syndrome, CPAP continuous positive airway pressure, OSA obstructive sleep apnea

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Fig. 2
figure 2

Association between homocysteine level and OSA severity in overall patients. Distribution patterns of all homocysteine subgroups between OSA and non-OSA patients (A); Distribution patterns of all apnea hypopnea index subgroups between patients with normal and high homocysteine (B). AHI apnea hypopnea index, OSA obstructive sleep apnea

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Baseline characteristics and results of overnight sleep monitoring

Nine hundred and eighty eight patients with Hcy ≤ 15 μmol/L were defined as NHcy while 565 patients with Hcy > 15 μmol/L were classified into HHcy group, among which 521 (52.7%) and 298 (52.7%) were diagnosed with OSA, respectively. Baseline characteristics stratified by the interaction between Hcy level and OSA status were summarized in Table 1. OSA Patients were more often male, obese and were more likely with hypertension versus those with relatively normal nocturnal airflow, regardless of Hcy level. Most of other variables, including medical history, medications, disease and procedural characteristics and laboratory examinations, were comparable between OSA and non-OSA patients. In addition, ACS patients with HHcy were less likely comorbid with diabetes mellitus and hyperlipidemia, but with higher rates of prior stroke, current smoker and STEMI, versus NHcy patients.

Table 1 Baseline characteristics
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The results of sleep monitoring stratified by the interaction term (Hcy-OSA categories) were depicted in Table 2. Both in NHcy and HHcy groups, patients with OSA showed increased AHI, ODI and T90, and more apparent sleepy symptoms, concomitant with reduced minimum and mean SaO2, versus those without OSA (all P < 0.001).

Table 2 Overnight sleep monitoring results stratified by the interaction term between OSA and homocysteine
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Outcomes analyses between OSA and non-OSA patients stratified by Hcy level

During a median follow-up of 2.9 years (interquartile range: 1.6–3.5 years), 317 (20.4%) patients suffered from the recurrence of MACCE, with 180 (22.0%) in the OSA group and 137 (18.7%) in the non-OSA group, respectively. However, the incident rate of MACCE was comparable between NHcy and HHcy groups (20.6% vs. 20.0%, log rank P = 0.474) (Additional file 4: Fig. S2). Table 3 summarized all relevant outcome data. Hospitalization for UA and ischemia-driven revascularization accounted for the majority of MACCE. Intriguingly, we found that among ACS patients with NHcy, those who developed OSA had a significantly increased crude incidence of MACCE versus non-OSA ones (23.2% vs. 17.8%, log rank P = 0.015, Fig. 3A), which, in turn, was insignificant among HHcy patients (19.8% vs. 20.2%, log rank P = 0.961, Fig. 3B). Univariable COX analyses further verified this divergence (in NHcy patients, unadjusted HR = 1.41, 95%CI 1.07–1.87, P = 0.015; in HHcy patients, unadjusted HR = 1.01, 95%CI 0.70–1.46, P = 0.961; Table 3). Moreover, after adjustment for clinical confounders, OSA was still associated with increased risk for MACCE in ACS patients with NHcy (adjusted HR = 1.36, 95%CI 1.02–1.83, P = 0.039), but not in HHcy patients (adjusted HR = 0.92, 95%CI 0.62–1.36, P = 0.668) (Table 3). After controlling competing risk for non-cardiogenic death, OSA was still associated with long-term events in patients with normal level of homocysteine (HR = 1.36, 95%CI 1.02–1.83, P = 0.039), but not in those with hyperhomocysteinemia (HR = 0.92, 95%CI 0.62–1.36, P = 0.668). There was an absence of interaction between OSA and homocysteine with respect to MACCE (interaction P = 0.106).

Table 3 Crude incidence and COX analyses of all relevant endpoints
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Fig. 3
figure 3

Kaplan–Meier curves for primary endpoint according to age-OSA categories. Exposure to OSA significantly increased the incidence of major adverse cerebrocardiovascular events (MACCE) in ACS patients with normohomocysteinemia (A), unlike in ACS patients with hyperhomocysteinemia (B)

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However, association between OSA and every secondary endpoint was not statistically significant both in NHcy and HHcy groups (Table 3). Notably, among NHcy patients, OSA nominally increased the risk for hospitalization for UA (adjusted HR = 1.27, 95%CI 0.90–1.78, P = 0.174) and non-culprit revascularization (adjusted HR = 1.59, 95%CI 0.97–2.61, P = 0.067).

Independent risk factors of outcomes stratified by Hcy level

Independent risk factors of clinical outcomes according to Hcy level were shown in Table 4. Intriguingly, among ACS patients with NHcy, only OSA and diabetes mellitus (HR = 1.33, 95%CI 1.00–1.77, P = 0.048) independently predicted the occurrence of MACCE. In stark contrast, in HHcy patients, several risk factors (age, female, diabetes mellitus, prior MI, prior stroke and current smoking) showed potential association with MACCE in univariable analysis (P < 0.100), which, however, transformed to insignificance in multivariable models.

Table 4 Risk factors of MACCE stratified by level of homocysteine
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Subgroups analyses of outcomes

The association between OSA and the risk for MACCE incidence were further evaluated based on distinct subgroups, encompassing age, gender, obesity, hypertension, diabetes mellitus, hyperlipidemia, ACS types, prior MI, prior stroke and renal dysfunction (Additional file 5: Fig. S3), where none of differences were found, and the association of OSA with MACCE was not modified by these confounding factors (all P for interaction ≥ 0.171).

Discussion

In current study, based on a large-scale, prospective OSA-ACS cohort, we found that the presence of OSA did not change the serum Hcy level of ACS patients, and OSA was only associated with increased risk for cardiovascular events among those with NHcy, but not in HHcy patients. Our study firstly emphasized a fact that ACS patients with a relatively normal level of Hcy also suffered from high risk for cardiovascular events, which was attributed partially to concomitant OSA. Therefore, aggressive screening, definitive diagnosis and effective interventions for OSA especially in such a population were recommended aiming to ameliorate the prognosis.

With fulfillment of great progress in secondary prevention strategies for traditional cardiovascular risk factors (e.g. hyperlipidemia, hypertension, diabetes mellitus) and in revascularization therapy, the overall morbidity, mortality and prognosis of coronary artery disease (CAD) or ACS have been improved over time [29,30,31,32]. However, in 2021, Figtree and the colleagues observed a higher short-term mortality in STEMI patients without standard modifiable cardiovascular risk factors, versus those with at least one [33], yielding the exploration of residual risk factors. Almost simultaneously, the American Heart Association appended sleep health as a novel metric of cardiovascular health [34], where OSA is an essential component, a novel and paramount risk factor involved in the pathogenesis and progression of cardiovascular diseases according to contemporary notion [3, 8].

A plethora of studies have demonstrated detrimental effects exerted by OSA on ACS patients. OSA was involved in the exacerbation of ACS, evidenced by increased cardiac injury, and plaque burden and vulnerability, which were responsible for worse cardiovascular prognosis [35,36,37]. In the Sleep and Stent Study, exposure to OSA increased the risk for the occurrence of MACCE by 57% in CAD patients undergoing PCI, among which 68.5% were ACS, during a median follow-up of 1.9 years [38]. Subsequently, in the mid-term analysis of OSA-ACS project containing 804 ACS patients [4], we reported approximately fourfold risk for the incidence of MACCE in those comorbid with OSA after 1-year follow-up. CPAP has been recommended as the first-line treatment for OSA. CPAP treatment was associated with mild-to-moderate reduction of blood pressure, alleviated sleepy symptoms, improvement of cardiac function and arrhythmias in ACS patients [6, 9, 39], which could contribute synergistically to improving the prognosis [40]. However, in recent, ISAACC studies [6], the largest-scale randomized controlled trials focusing on the therapeutic efficacy of CPAP on ACS patients, demonstrated that CPAP treatment failed to protect against long-term cardiovascular events or sleepy symptoms. Although inclusion of non-sleepy patients and suboptimal adherence might be partially responsible for the negative results, there was a hypothesis that patients with high-risk clinical phenotypes might respond better to CPAP treatment [41]. We have previously identified several specific populations vulnerable to OSA, comprising diabetes mellitus, females, non-obesity and hyperuricemia [5, 11, 12, 42], with the impact stratified by Hcy remaining unelucidated.

Cardiometabolic dysregulation played a crucial role on this association with respect to the fact that OSA interacted diabetes mellitus, dyslipidemia and hypertension with reciprocal causation [43,44,45]. One of these metabolites by rational speculation was Hcy due to the common mechanisms underlying cardiovascular injuries between Hcy and OSA. Nevertheless, the association between OSA and Hcy was controversial. Numerous investigators observed an elevation of Hcy level in OSA patients with or without prior cardiovascular diseases [19, 20, 46,47,48]. Conversely, Svatikova et al. executed a rigorously controlled study enrolling obese but otherwise healthy patients where Hcy level was comparable between OSA and control subjects and neither nocturnal OSA nor sleep disturbance transiently changed Hcy [14]. In addition, CPAP treatment appeared not to affect Hcy [21, 49], further supporting the notion that OSA itself was not associated with the level of Hcy. However, OSA patients were more likely to be elder, male, obese, and concomitant with renal dysfunction, which were prominent risk factors of Hcy elevation [16]. In our current study, we also found that in ACS patients, OSA did not modify the level of Hcy, which, in turn, varied with age, gender, diabetes mellitus, renal dysfunction and smoking. Therefore, coexistence of OSA and elevated Hcy might reflect several variances in metabolic conditions, the identification of which required the implementation of trials with larger sample size and rigorous schemes.

It was noticeable that the effects of Hcy on cardiovascular outcomes among ACS patients were also disputed. A plethora of studies have identified elevated Hcy as a strong independent risk factor of worse cardiovascular outcomes in ACS patients [17, 50]. However, Foussas et al. reported an absence of association of between Hcy and long-term mortality in neither STEMI nor NSTE-ACS cohort, after adjustment for prominent risk factors and medical history [22]. A rational explanation for this controversy might be the heterogeneity of recruited patients, adjusted confounders included in multivariable models and a relatively small sample size [22]. Therefore, in our study by utilization of 1553 ACS patients, we observed a comparable incident rate of MACCE between NHcy and HHcy groups. Another convictive evidence against the role for Hcy was that folic acid and vitamin B6/B12 supplement, aiming to prompt the metabolic consumption of Hcy, failed to ameliorate the cardiovascular outcomes of acute myocardial infarction patients in spite of substantial reduction of Hcy [51]. Thus, Hcy might be rather a biomarker clustered with risk factor profiles, than a modifiable risk factor [22]. In addition, although synergistical impacts of OSA and augmented Hcy on cardiovascular events in patients without established ACS was observed [23, 24], there was a knowledge gap of this interaction among ACS patients. However, in HHcy patients, OSA did not increase the risk for MACCE versus non-OSA ones. In stark contrast, ACS patients with NHcy were more vulnerable to the jeopardies derived from OSA. Furthermore, we adjusted several important confounders responsible for Hcy level to avoid potential impacts, including age, gender, renal function, diabetes mellitus and current smoking, and OSA still independently predicted the incidence of MACCE. Taken together, we reasonably hypothesized that comorbid condition of OSA with HHcy might exert a ceiling effect on cardiovascular injuries, where the roles for OSA were overwhelmed, by virtue of that various risk factors often concomitant with OSA showed potential association with MACCE in these patients. Another explanation was that OSA patients with metabolic dysfunction were recommended to have more aggressive lifestyle improvements, including diet, exercise and the combination [3, 52, 53]. A meta-analysis based on randomized controlled trials indicated that weight loss of 14 kg was associated with a reduction of AHI of 16 evens/h and a part of patients could even achieve remission of OSA [54]. Further studies should take lifestyle interventions into account to distinguish the effects of OSA during long-term follow-up. Our study emphasized that the risk for long-term MACCE in ACS patients with NHcy should not be neglected, which might be attributed partially to concomitant OSA. Therefore, it was necessary to execute aggressive screening and diagnosis for OSA, favorable for individual risk stratification and therapy guiding, in such a population. This was of paramount importance to ameliorate cardiovascular outcomes since OSA was prevalent and treatable, and further studies were also required to investigate whether CPAP treatment in ACS patients with NHcy was effective.

Limitations

There were several limitations in our study. First, the OSA-ACS project is a single-center, observational study with inevitable confounding bias. Thus, to control this limitation, professional researchers collecting follow-up data were blinded to the patients’ sleep results and baseline characteristics. Moreover, we adjusted for several important confounders in the outcome analyses to ensure the reliability of results, to an extent. Second, the definition of OSA according to portable sleep monitors may underestimate the severity of OSA. However, portable polygraphy has been validated to substitute for polysomnography with an effectiveness in previous studies [55]. Third, the data from formal sleep center follow-up visits and OSA treatment adherence after discharge was not included in current study, the effects of OSA treatment on MACCE could not be assessed in this study. Fourth, we did not take the effects of lifestyle improvements into account during follow-up. Finally, our study focused on East Asian patients, whether similar findings could extend to other ethnicities required further investigation.

Conclusion

In our current study, OSA did not significantly affect the level of Hcy in ACS patients. Furthermore, Hcy level-dependent effects of OSA on cardiovascular outcomes were observed, where OSA was associated with increased risk for MACCE during long-term follow-up in ACS patients with relatively normal Hcy, but not in those with elevated Hcy. Our study emphasized that regular screening, definitive diagnosis and aggressive treatment were recommended in such a population.

Availability of data and materials

All of the individual patient data collected during the study will be shared. All available data can be obtained by contacting the corresponding author (Shaoping Nie, spnie@ccmu.edu.cn). It will be necessary to provide a detailed protocol for the proposed study, to provide the approval of an ethics committee, to supply a signed data access agreement, and to have discussion with the original authors for re-analysis.

Abbreviations

ACS:

Acute coronary syndrome

AHI:

Apnea hypopnea index

BMI:

Body mass index

CABG:

Coronary artery bypass grafting

CAD:

Coronary artery disease

CPAP:

Continuous positive airway pressure

eGFR:

Estimated glomerular filtration rate

Hcy:

Homocysteine

HHcy:

Hyperhomocysteinemia

MACCE:

Major adverse cerebrocardiovascular events

MI:

Myocardial infarction

NHcy:

Normohomocysteinemia

NSTE-ACS:

Non-ST-segment elevation acute coronary syndrome

NSTEMI:

Non-ST-segment elevation myocardial infarction

OSA:

Obstructive sleep apnea

PCI:

Percutaneous coronary intervention

STEMI:

ST-segment elevation myocardial infarction

References

  1. Benjafield AV, Ayas NT, Eastwood PR, Heinzer R, Ip MSM, Morrell MJ, et al. Estimation of the global prevalence and burden of obstructive sleep apnoea: a literature-based analysis. Lancet Respir Med. 2019;7(8):687–98.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Levy P, Kohler M, McNicholas WT, Barbe F, McEvoy RD, Somers VK, et al. Obstructive sleep apnoea syndrome. Nat Rev Dis Primers. 2015;1:15015.

    Article  PubMed  Google Scholar 

  3. Yeghiazarians Y, Jneid H, Tietjens JR, Redline S, Brown DL, El-Sherif N, et al. Obstructive sleep apnea and cardiovascular disease: a scientific statement from the American Heart Association. Circulation. 2021;144(3):e56–67.

    Article  CAS  PubMed  Google Scholar 

  4. Fan J, Wang X, Ma X, Somers VK, Nie S, Wei Y. Association of obstructive sleep apnea with cardiovascular outcomes in patients with acute coronary syndrome. J Am Heart Assoc. 2019;8(2): e010826.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Wang X, Fan J, Guo R, Hao W, Gong W, Yan Y, et al. Association of OSA with cardiovascular events in women and men with acute coronary syndrome. Eur Respir J. 2022;61:2201110.

    Article  Google Scholar 

  6. Sanchez-de-la-Torre M, Sanchez-de-la-Torre A, Bertran S, Abad J, Duran-Cantolla J, Cabriada V, et al. Effect of obstructive sleep apnoea and its treatment with continuous positive airway pressure on the prevalence of cardiovascular events in patients with acute coronary syndrome (ISAACC study): a randomised controlled trial. Lancet Respir Med. 2020;8(4):359–67.

    Article  PubMed  Google Scholar 

  7. Javaheri S, Barbe F, Campos-Rodriguez F, Dempsey JA, Khayat R, Javaheri S, et al. Sleep apnea: types, mechanisms, and clinical cardiovascular consequences. J Am Coll Cardiol. 2017;69(7):841–58.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Catalan Serra P, Soler X. Obstructive sleep apnea and cardiovascular events in elderly patients. Expert Rev Respir Med. 2022;16(2):197–210.

    Article  CAS  PubMed  Google Scholar 

  9. Randerath W, Bonsignore MR, Herkenrath S. Obstructive sleep apnoea in acute coronary syndrome. Eur Respir Rev. 2019;28(153):180114.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Zapater A, Sanchez-de-la-Torre M, Benitez ID, Targa A, Bertran S, Torres G, et al. The effect of sleep apnea on cardiovascular events in different acute coronary syndrome phenotypes. Am J Respir Crit Care Med. 2020;202(12):1698–706.

    Article  PubMed  Google Scholar 

  11. Zhao X, Li S, Wang X, Fan J, Ai H, Que B, et al. Clinical outcomes of obstructive sleep apnea in patients with acute coronary syndrome in relation to hyperuricemia status. J Sleep Res. 2023;32:e13898.

    Article  PubMed  Google Scholar 

  12. Wang X, Fan J, Du Y, Ma C, Ma X, Nie S, et al. Clinical significance of obstructive sleep apnea in patients with acute coronary syndrome in relation to diabetes status. BMJ Open Diabetes Res Care. 2019;7(1): e000737.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Giampa SQC, Lorenzi-Filho G, Drager LF. Obstructive sleep apnea and metabolic syndrome. Obesity (Silver Spring). 2023;31(4):900–11.

    Article  CAS  PubMed  Google Scholar 

  14. Svatikova A, Wolk R, Magera MJ, Shamsuzzaman AS, Phillips BG, Somers VK. Plasma homocysteine in obstructive sleep apnoea. Eur Heart J. 2004;25(15):1325–9.

    Article  CAS  PubMed  Google Scholar 

  15. Winnicki M, Palatini P. Obstructive sleep apnoea and plasma homocysteine: an overview. Eur Heart J. 2004;25(15):1281–3.

    Article  CAS  PubMed  Google Scholar 

  16. Ganguly P, Alam SF. Role of homocysteine in the development of cardiovascular disease. Nutr J. 2015;14:6.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Minana G, Gil-Cayuela C, Facila L, Bodi V, Valero E, Mollar A, et al. Homocysteine and long-term recurrent infarction following an acute coronary syndrome. Cardiol J. 2021;28(4):598–606.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Cioni G, Marcucci R, Gori AM, Valente S, Giglioli C, Gensini GF, et al. Increased homocysteine and lipoprotein(a) levels highlight systemic atherosclerotic burden in patients with a history of acute coronary syndromes. J Vasc Surg. 2016;64(1):163–70.

    Article  PubMed  Google Scholar 

  19. Lavie L, Perelman A, Lavie P. Plasma homocysteine levels in obstructive sleep apnea: association with cardiovascular morbidity. Chest. 2001;120(3):900–8.

    Article  CAS  PubMed  Google Scholar 

  20. Niu X, Chen X, Xiao Y, Dong J, Zhang R, Lu M, et al. The differences in homocysteine level between obstructive sleep apnea patients and controls: a meta-analysis. PLoS ONE. 2014;9(4): e95794.

    Article  PubMed  PubMed Central  Google Scholar 

  21. Ryan S, Nolan GM, Hannigan E, Cunningham S, Taylor C, McNicholas WT. Cardiovascular risk markers in obstructive sleep apnoea syndrome and correlation with obesity. Thorax. 2007;62(6):509–14.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Foussas SG, Zairis MN, Makrygiannis SS, Manousakis SJ, Patsourakos NG, Adamopoulou EN, et al. The impact of circulating total homocysteine levels on long-term cardiovascular mortality in patients with acute coronary syndromes. Int J Cardiol. 2008;124(3):312–8.

    Article  PubMed  Google Scholar 

  23. Liu L, Su X, Zhao L, Li J, Xu W, Yang L, et al. Association of homocysteine and risks of long-term cardiovascular events and all-cause death among older patients with obstructive sleep apnea: a prospective study. J Nutr Health Aging. 2022;26(9):879–88.

    Article  CAS  PubMed  Google Scholar 

  24. Kim J, Lee SK, Yoon DW, Shin C. Concurrent presence of obstructive sleep apnea and elevated homocysteine levels exacerbate the development of hypertension: a KoGES six-year follow-up study. Sci Rep. 2018;8(1):2665.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Gueant JL, Gueant-Rodriguez RM, Oussalah A, Zuily S, Rosenberg I. Hyperhomocysteinemia in cardiovascular diseases: revisiting observational studies and clinical trials. Thromb Haemost. 2023;123(3):270–82.

    Article  PubMed  Google Scholar 

  26. Ibanez B, James S, Agewall S, Antunes MJ, Bucciarelli-Ducci C, Bueno H, et al. 2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation: the Task Force for the management of acute myocardial infarction in patients presenting with ST-segment elevation of the European Society of Cardiology (ESC). Eur Heart J. 2018;39(2):119–77.

    Article  PubMed  Google Scholar 

  27. Collet JP, Thiele H, Barbato E, Barthelemy O, Bauersachs J, Bhatt DL, et al. 2020 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation. Eur Heart J. 2021;42(14):1289–367.

    Article  PubMed  Google Scholar 

  28. Hicks KA, Tcheng JE, Bozkurt B, Chaitman BR, Cutlip DE, Farb A, et al. 2014 ACC/AHA key data elements and definitions for cardiovascular endpoint events in clinical trials: a report of the American College of Cardiology/American Heart Association Task Force on Clinical Data Standards (Writing Committee to Develop Cardiovascular Endpoints Data Standards). J Am Coll Cardiol. 2015;66(4):403–69.

    Article  PubMed  Google Scholar 

  29. Arora S, Stouffer GA, Kucharska-Newton AM, Qamar A, Vaduganathan M, Pandey A, et al. Twenty year trends and sex differences in young adults hospitalized with acute myocardial infarction. Circulation. 2019;139(8):1047–56.

    Article  PubMed  PubMed Central  Google Scholar 

  30. Bittner VA, Szarek M, Aylward PE, Bhatt DL, Diaz R, Edelberg JM, et al. Effect of alirocumab on lipoprotein(a) and cardiovascular risk after acute coronary syndrome. J Am Coll Cardiol. 2020;75(2):133–44.

    Article  CAS  PubMed  Google Scholar 

  31. Miyachi H, Yamamoto T, Takayama M, Miyauchi K, Yamasaki M, Tanaka H, et al. 10-Year temporal trends of in-hospital mortality and emergency percutaneous coronary intervention for acute myocardial infarction. JACC Asia. 2022;2(6):677–88.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Roth GA, Mensah GA, Johnson CO, Addolorato G, Ammirati E, Baddour LM, et al. Global burden of cardiovascular diseases and risk factors, 1990–2019: update from the GBD 2019 study. J Am Coll Cardiol. 2020;76(25):2982–3021.

    Article  PubMed  PubMed Central  Google Scholar 

  33. Figtree GA, Vernon ST, Hadziosmanovic N, Sundstrom J, Alfredsson J, Arnott C, et al. Mortality in STEMI patients without standard modifiable risk factors: a sex-disaggregated analysis of SWEDEHEART registry data. Lancet. 2021;397(10279):1085–94.

    Article  CAS  PubMed  Google Scholar 

  34. Lloyd-Jones DM, Allen NB, Anderson CAM, Black T, Brewer LC, Foraker RE, et al. Life’s essential 8: updating and enhancing the American Heart Association’s construct of cardiovascular health: a presidential advisory From the American Heart Association. Circulation. 2022;146(5):e18–43.

    Article  PubMed  PubMed Central  Google Scholar 

  35. Barbe F, Sanchez-de-la-Torre A, Abad J, Duran-Cantolla J, Mediano O, Amilibia J, et al. Effect of obstructive sleep apnoea on severity and short-term prognosis of acute coronary syndrome. Eur Respir J. 2015;45(2):419–27.

    Article  PubMed  Google Scholar 

  36. Nakashima H, Kurobe M, Minami K, Furudono S, Uchida Y, Amenomori K, et al. Effects of moderate-to-severe obstructive sleep apnea on the clinical manifestations of plaque vulnerability and the progression of coronary atherosclerosis in patients with acute coronary syndrome. Eur Heart J Acute Cardiovasc Care. 2015;4(1):75–84.

    Article  PubMed  Google Scholar 

  37. Lu M, Fang F, Wang Z, Xu L, Sanderson JE, Zhan X, et al. Association between OSA and quantitative atherosclerotic plaque burden: a coronary CT angiography study. Chest. 2021;160(5):1864–74.

    Article  PubMed  Google Scholar 

  38. Lee CH, Sethi R, Li R, Ho HH, Hein T, Jim MH, et al. Obstructive sleep apnea and cardiovascular events after percutaneous coronary intervention. Circulation. 2016;133(21):2008–17.

    Article  PubMed  Google Scholar 

  39. Sanchez-de-la-Torre M, Gracia-Lavedan E, Benitez ID, Zapater A, Torres G, Sanchez-de-la-Torre A, et al. Long-term effect of obstructive sleep apnea and continuous positive airway pressure treatment on blood pressure in patients with acute coronary syndrome: a clinical trial. Ann Am Thorac Soc. 2022;19(10):1750–9.

    Article  PubMed  Google Scholar 

  40. Yang D, Li L, Dong J, Yang W, Liu Z. Effects of continuous positive airway pressure on cardiac events and metabolic components in patients with moderate to severe obstructive sleep apnea and coronary artery disease: a meta-analysis. J Clin Sleep Med. 2023;19:2015.

    Article  PubMed  Google Scholar 

  41. McEvoy RD, Antic NA, Heeley E, Luo Y, Ou Q, Zhang X, et al. CPAP for prevention of cardiovascular events in obstructive sleep apnea. N Engl J Med. 2016;375(10):919–31.

    Article  PubMed  Google Scholar 

  42. Hao W, Wang X, Fan J, Guo R, Gong W, Yan Y, et al. Prognostic implications of OSA in acute coronary syndrome by obesity status. Chest. 2023;164:219.

    Article  PubMed  Google Scholar 

  43. Reutrakul S, Mokhlesi B. Obstructive sleep apnea and diabetes: a state of the art review. Chest. 2017;152(5):1070–86.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Torres G, Sanchez-de-la-Torre M, Barbe F. Relationship between OSA and hypertension. Chest. 2015;148(3):824–32.

    Article  PubMed  Google Scholar 

  45. Mesarwi OA, Loomba R, Malhotra A. Obstructive sleep apnea, hypoxia, and nonalcoholic fatty liver disease. Am J Respir Crit Care Med. 2019;199(7):830–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Chen M, Wu B, Ye X, Zhou Z, Yue X, Wang Q, et al. Association between plasma homocysteine levels and obstructive sleep apnoea in patients with ischaemic stroke. J Clin Neurosci. 2011;18(11):1454–7.

    Article  CAS  PubMed  Google Scholar 

  47. Sariman N, Levent E, Aksungar FB, Soylu AC, Bektas O. Homocysteine levels and echocardiographic findings in obstructive sleep apnea syndrome. Respiration. 2010;79(1):38–45.

    Article  CAS  PubMed  Google Scholar 

  48. Wang L, Li J, Xie Y, Zhang XG. Association between serum homocysteine and oxidative stress in elderly patients with obstructive sleep apnea/hypopnea syndrome. Biomed Environ Sci. 2010;23(1):42–7.

    Article  PubMed  Google Scholar 

  49. Li J, Yu LQ, Jiang M, Wang L, Fang Q. Homocysteine level in patients with obstructive sleep apnea/hypopnea syndrome and the impact of continuous positive airway pressure treatment. Adv Clin Exp Med. 2018;27(11):1549–54.

    Article  PubMed  Google Scholar 

  50. Zhu M, Mao M, Lou X. Elevated homocysteine level and prognosis in patients with acute coronary syndrome: a meta-analysis. Biomarkers. 2019;24(4):309–16.

    Article  CAS  PubMed  Google Scholar 

  51. Bonaa KH, Njolstad I, Ueland PM, Schirmer H, Tverdal A, Steigen T, et al. Homocysteine lowering and cardiovascular events after acute myocardial infarction. N Engl J Med. 2006;354(15):1578–88.

    Article  CAS  PubMed  Google Scholar 

  52. Dobrosielski DA, Papandreou C, Patil SP, Salas-Salvado J. Diet and exercise in the management of obstructive sleep apnoea and cardiovascular disease risk. Eur Respir Rev. 2017;26(144):160110.

    Article  PubMed  PubMed Central  Google Scholar 

  53. Gleeson M, McNicholas WT. Bidirectional relationships of comorbidity with obstructive sleep apnoea. Eur Respir Rev. 2022;31(164):210256.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Mitchell LJ, Davidson ZE, Bonham M, O’Driscoll DM, Hamilton GS, Truby H. Weight loss from lifestyle interventions and severity of sleep apnoea: a systematic review and meta-analysis. Sleep Med. 2014;15(10):1173–83.

    Article  PubMed  Google Scholar 

  55. Corral J, Sanchez-Quiroga MA, Carmona-Bernal C, Sanchez-Armengol A, de la Torre AS, Duran-Cantolla J, et al. Conventional polysomnography is not necessary for the management of most patients with suspected obstructive sleep apnea. Noninferiority, randomized controlled trial. Am J Respir Crit Care Med. 2017;196(9):1181–90.

    Article  PubMed  Google Scholar 

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Acknowledgements

Not applicable.

Funding

The study has been funded by National Natural Science Foundation of China (Grant Numbers 81970292, 82270258, 82100260), National Key Research and Development Program of China (Grant Number 2020YFC2004800).

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Author notes

  1. Xiuhuan Chen and Lei Zhen contributed equally to the manuscript.

Authors and Affiliations

  1. Center for Coronary Artery Disease, Division of Cardiology, Beijing Anzhen Hospital, Capital Medical University, 2 Anzhen Road, Chaoyang District, Beijing, 100029, China

    Xiuhuan Chen, Lei Zhen, Hui Ai, Bin Que, Jingyao Fan, Xiao Wang, Yan Yan, Siyi Li, Zekun Zhang, Yun Zhou, Wei Gong & Shaoping Nie

  2. National Clinical Research Center for Cardiovascular Diseases, Beijing, China

    Xiuhuan Chen, Lei Zhen, Hui Ai, Bin Que, Jingyao Fan, Xiao Wang, Yan Yan, Siyi Li, Zekun Zhang, Yun Zhou, Wei Gong & Shaoping Nie

  3. Beijing Institute of Heart, Lung, and Blood Vessel Diseases, Beijing, China

    Xiuhuan Chen, Lei Zhen, Hui Ai, Bin Que, Jingyao Fan, Xiao Wang, Yan Yan, Siyi Li, Zekun Zhang, Yun Zhou, Wei Gong & Shaoping Nie

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  1. Xiuhuan Chen
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Contributions

SN and WG conceived the study. XC, XW, SN and WG designed the study. XC, JF, ZZ and YZ contributed to the statistical analysis. XC, LZ, HA, SL and YY interpreted the data. XC and LZ drafted of the manuscript. NS, WG and BQ modified the manuscript. All authors critically read the manuscript and approved the final manuscript.

Corresponding authors

Correspondence to Wei Gong or Shaoping Nie.

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Ethics approval and consent to participate

The study was approved by the Institutional Review Board of Beijing Anzhen Hospital, Capital Medical University (2013025) and all patients provided written informed consent. All the authors consent to the publication of the manuscript.

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The authors declare that they have no competing interests.

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Supplementary Information

Additional file 1: Methods.

Definition of study endpoints.

Additional file 2: Table S1.

Baseline characteristics between patients with homocysteine ≤ 15 μmol/L and those > 15 μmol/L.

Additional file 3: Figure S1.

Factors associated with the level of homocysteine in ACS patients, comprising gender (A), diabetes mellitus (B), renal dysfunction (eGFR < 90 or not) (C), age (≥ 65 or not) (D), obesity (BMI ≥ 28 or not) (E), hypertension (F), current smoking (G) and ACS types (STEMI or NSTE-ACS) (H). ACS: acute coronary syndrome; eGFR: estimated glomerular filtration rate; BMI: body mass index; STEMI: ST-segment elevation myocardial infarction; NSTE-ACS: non-ST-segment elevation acute coronary syndrome.

Additional file 4: Figure S2.

Kaplan–Meier curves for primary endpoint according to Hcy level.

Additional file 5: Figure S3.

Subgroup analyses for the association between OSA and risk for incidence of MACCE. *: All HRs were adjusted for age, gender, body mass index (BMI), hypertension, diabetes mellitus, hyperlipidemia, prior MI, prior stroke, ACS types, smoking status, drinking and estimated glomerular filtration rate (eGFR) < 90 mL/min/1.73 m2, except for the grouping variable.

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Chen, X., Zhen, L., Ai, H. et al. Prognostic implications of obstructive sleep apnea in patients with acute coronary syndrome stratified by homocysteine level: a prospective cohort study. Respir Res 24, 313 (2023). https://doi.org/10.1186/s12931-023-02627-8

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Keywords

Respiratory Research

ISSN: 1465-993X

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