Biomarker panel in sleep apnea patients after an acute coronary event
Introduction
Coronary artery disease has become the leading cause of death worldwide. Its main manifestation is the acute coronary syndrome (ACS), whose symptoms are due to an insufficient oxygen supply to the cardiac muscle caused by an obstruction in the coronary vessels [1,2]. A myriad of cardiovascular risk factors have been described and helped in the understanding of the pathophysiology of ACS, as well as in its prediction and characterization.
Obstructive sleep apnea (OSA), a very prevalent respiratory disease, stands out as one of the main modifiable cardiovascular risk factors [3,4]. It results from a narrowing in the upper airway during sleep, which causes a reduction in the oxyhemoglobin saturation (hypoxemia), an increase in partial carbon dioxide pressure in blood (hypercapnia) and small awakenings aiming to restore normal airflow (arousals) [5,6]. These intermittent events of airway collapse lead to the development of comorbidities associated with OSA, especially cardiovascular, cerebrovascular and neurocognitive diseases, and a higher global mortality rate [4,7,8], which might be explained by the complex pathophysiology of OSA, including oxidative stress and metabolic dysfunction, systemic inflammation and immune activation, sympathetic activation and endothelial dysfunction, among others [6].
A very powerful tool for the objective assessment of these links are biomarkers in blood, the measurement of which may also help in the prediction and screening, diagnosis and staging to the monitoring of a therapeutical response of almost any pathology [[9], [10], [11]]. The use of known biomarkers reflecting the abovementioned individual pathophysiological aspects of OSA could be a great aid to explain its close relationship with coronary disease and interpret the underlying molecular mechanisms.
Myeloperoxidase (MPO) is a known and well-established biomarker of oxidative stress [12]. The concentration of soluble CD40 (sCD40) may approach endothelial dysfunction and immune activation [13], while systemic inflammation may be studied through the quantification of the high-sensitivity C-reactive protein (hsCRP) and the matrix metalloproteinase-9 (MMP9), which is also implicated in angiogenesis and tissue remodeling and plays a key role in atherosclerotic plaque development and atherothrombosis [14]. Other biomarkers for an integral assessment of cardiovascular-related diseases include N-terminal pro-brain natriuretic peptide (Nt-proBNP) as hemodynamic marker, and the placental growth factor (PlGF) and the soluble fms-like tyrosine-kinase domain-1 (sFlt1) as angiogenesis-related biomarkers [15].
Therefore, the two objectives of this study were (1) to evaluate the impact of OSA on the association between cardiovascular risk biomarkers and ACS severity and (2) to assess the relationship of these biomarkers with OSA in patients after an acute coronary event.
Section snippets
Study participants and procedures
This is an ancillary study of the ISAACC Study (NCT01335087), which is an open-label, parallel, prospective, randomized and controlled clinical trial and aims to evaluate whether CPAP treatment reduces the incidence of new cardiovascular events in OSA patients after a first ACS episode [16]. It started in April 2011, and patients were recruited across the country (15 hospitals), and provided written, informed consent. The study was approved by the Ethics Board of each participating center. ACS
Study population
A total of 361 individuals with an ACS diagnosis evaluated in coronary care units or cardiology hospitalization were classified into two groups according to the presence of OSA, resulting in 152 participants without OSA and 209 participants with OSA.
The anthropometric, demographic and sleep-related characteristics of the participants are outlined on Table 1, together with the mean and standard deviations of the 11 biochemical markers. In the OSA group, individuals were older, with a higher BMI
Discussion
The results of this study have shown that although some biomarkers were associated with ACS severity-related parameters, this association was independent of the presence of OSA or any other confounding variable assessed. Besides, individual clinical measures and biomarkers could distinguish between individuals with and without OSA in our population, and our results reveal that the combination of 4 parameters in a diagnostic algorithm could improve and maximize their discriminating power: age,
Conclusions
In patients admitted after a coronary event, despite a combination of clinical measures and biomarkers could be useful for the detection of OSA, such biomarkers did not show any differential prognostic value in patients with sleep-disordered breathing.
Our mathematical model for the diagnosis of OSA integrates different aspects of the complex pathophysiology and epidemiology of the sleep apnea syndrome. Nevertheless, the presence of OSA in patients with ACS does not affect the association
Author contributions
Conceived and designed the experiments (AB, FB), collected samples/reagents (MP, AS, MS, JA, JD, OM, MJM, AU, JT), performed the experiments (JMB, LF, JP, MA), analyzed the data (JMB, PS, AB), wrote the manuscript (JMB, AB, AS, MS), guarantor of the study (FB).
Conflict of interest disclosures
FB received a research grant from the following organizations to develop the ISAACC clinical trial (NCT01335087): ResMed Ltd., Australia; the Health Research Fund of the Spanish Ministry of Health (PI10/02763 and PI10/02745); the Spanish Respiratory Society (SEPAR); the Catalonian Cardiology Society; Esteve-Teijin, Spain; Oxigen Salud, Spain; and ALLER. All other authors declare that they have no conflicts of interest.
No sponsor did play any role in the design of the experiments, analysis,
Acknowledgements
All authors have read the journal's policy on disclosure of potential conflicts of interest. All authors have disclosed all potential conflicts of interest, personal or professional.
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