Background: Obstructive sleep apnea (OSA) is associated with several cardiovascular diseases. However, the mechanisms are not completely understood. Recent studies have shown that OSA is associated with multiple markers of endothelial damage. We hypothesized that OSA affects functional and structural properties of large arteries, contributing to atherosclerosis progression. Methods and Measurements: Twelve healthy volunteers, 15 patients with mild to moderate OSA, and 15 with severe OSA matched for age, sex, and body mass index were studied by using (1) full standard overnight polysomnography; (2) carotid-femoral pulse wave velocity with a noninvasive automatic device; and (3) a high-definition echo-tracking device to measure intima-media thickness, diameter, and distensibility. All participants were free of hypertension, diabetes, and smoking, and were not on any medications. Patients with OSA were naive to treatment. Main Results: Significant differences existed between control subjects and patients with mild to moderate and severe OSA (apnea–hypopnea index, 3.1 ± 0.3, 16.2 ± 1.7, and 55.7 ± 5.9 events/hour, respectively) in pulse wave velocity (8.7 ± 0.2, 9.2 ± 0.2, and 10.3 ± 0.2 m/second; p < 0.0001), intima-media thickness (604.4 ± 25.2, 580.2 ± 29.0, and 722.2 ± 35.2 μm; p = 0.004), and carotid diameter (6,607.8 ± 126.7, 7,152.3 ± 114.4, and 7,539.9 ± 161.2 μm; p < 0.0001). Multivariate analyses showed that the apnea–hypopnea index correlated independently with pulse wave velocity and intima-media thickness variability (r = 0.61, p < 0.0001, and r = 0.44, p = 0.004, respectively), whereas minimal oxygen saturation correlated with the carotid diameter (r = −0.60, p < 0.0001). Conclusions: Middle-aged patients with OSA who are free of overt cardiovascular diseases have early signs of atherosclerosis. All vascular abnormalities correlated significantly with the severity of the OSA, which further supports the hypothesis that OSA plays an independent role in atherosclerosis progression.
Obstructive sleep apnea (OSA) is characterized by recurrent episodes of partial or complete obstruction of the upper airway during sleep, with a consequent decrease in oxygen saturation. Epidemiologic studies have shown a strong association between OSA and cardiovascular diseases (1), including the following: hypertension (2), coronary artery disease (3), stroke (4), and heart failure (3). Most notably, compelling evidence indicates that OSA participates in the genesis of these conditions (5). Recent studies have indicated that OSA is associated with multiple causal factors of endothelial damage and atherosclerosis (6). These include the following: inflammation (7); increased levels of plasma vascular endothelial growth factor (VEGF) (8), an important promoter of the growth of smooth muscle cells; production of reactive oxygen species (9); increased levels of soluble adhesion molecules (10); and coagulation factors (11). Furthermore, all of these factors have been reported to significantly decrease after treatment with continuous positive airway pressure (9–13).
Atherosclerosis is a dynamic disease process characterized by vessel wall remodeling that occurs over decades, ultimately becoming clinically manifest as acute cardiovascular events in many individuals. Obesity, aging, hypertension, diabetes, and hyperlipidemia have a major impact on the progression of atherosclerosis. In contrast, some strategies, such as statin therapy, may attenuate or even promote regression of atherosclerotic plaque (14). Because several of these factors are frequently present in patients with OSA and are difficult to control, evidence of the association between OSA and atherosclerosis remains scanty (3, 15–17). Atherosclerosis can be evaluated by both vascular functional and structural parameters. Pulse wave velocity (PWV) is a noninvasive, accurate technique to determine elastic properties of the aorta and the large arteries (18). The mechanical properties of the large arteries are important determinants of circulatory physiology in health and disease. Increased arterial stiffness may precede the onset of systemic hypertension in humans (19) and is an independent risk marker of premature coronary artery disease, atherosclerosis, and cardiovascular mortality (20, 21). Recent studies have shown that measurements of arterial compliance may be useful for the detection of subclinical atherosclerosis (22). Atherosclerosis leads ultimately to changes in vascular structure. Ultrasound devices, such as echo tracking, provide reliable measurements of lumen size, distensibility, wall thickness, and the presence of atheroma in large arteries (23). The measure of common carotid artery intima-media thickness (IMT) has been extensively used as an early marker of atherosclerosis in epidemiologic and clinical studies (24–27). Longitudinal studies showed that increased IMT predicts carotid plaque occurrence (28) and stroke (29). In addition, carotid artery dilatation indicates compensatory vascular mechanism and is found in early stages of atherosclerosis (30).
The aim of this study was to test the hypothesis that early signs of atherosclerosis are present in patients with OSA and correlate with OSA severity. To this end, independent, validated indicators of early signs of atherosclerosis, including PWV, carotid diameter, and IMT, were performed in patients with OSA naive to treatment and in appropriate control subjects. We carefully excluded potential confounding factors for atherosclerosis, including hypertension, smoking, diabetes, regular use of medications, and increased age. Some of the results of this study have been previously reported in the form of an abstract (31).
We studied 12 matched healthy volunteers, 15 patients with mild to moderate OSA, and 15 with severe OSA, matched for age, sex, and body mass index (BMI). The volunteers were recruited from the hospital staff after they completed a Berlin Questionnaire (32), indicating a low risk of OSA. Particular attention was paid to morphometric characteristics to obtain three groups with a comparable BMI.
Exclusion criteria included the following: age younger than 30 or older than 55 years; BMI more than 40 kg/m2; hypertension; diabetes mellitus; cerebrovascular, aortic, or cardiac disease; smoking habit; and chronic use of medications (including nonsteroidal antiinflammatory drugs, oral anticoagulants, and statins). All participants had at least two fasting glucose measurements to exclude diabetes. Hypertension was carefully excluded based on the average of two or more properly measured, seated blood pressure readings on at least two office visits, according to current guidelines (33), by experienced physicians not involved in the study. In addition, venous blood was collected for the measurement of glucose, cholesterol, and hemoglobin levels.
All participants underwent a standard overnight polysomnography (EMBLA; Flagra hf. Medical Devices, Reykjavik, Iceland), including EEG, electrooculography, EMG, oximetry, thermistor, and pressure cannula measurements of airflow, and measurements of ribcage and abdominal movements during breathing. Apnea was defined as complete cessation of airflow for at least 10 seconds. Hypopnea was defined as a reduction in respiratory signals for at least 10 seconds associated with oxygen desaturation of 3%. The apnea–hypopnea index (AHI) was calculated as the total number of respiratory events (apneas plus hypopneas) per hour of sleep. The AHI cutoff for control subjects, patients with mild to moderate OSA, and patients with severe OSA was less than 5, 5 to 30, and more than 30 events per hour of sleep, respectively. Patients with OSA had been recently diagnosed and were naive to treatment.
All participants had their vascular properties evaluated within 2 weeks after polysomnography. Carotid-femoral PWV was analyzed with a noninvasive automatic device, Complior (Colson, Garges les Gonesses, France), and carotid measurements (IMT and carotid diameter) were made with a high-definition echo-tracking device (Wall Track System, Medical Systems Arnhem, Oosterbeck, The Netherlands) by an experienced observer blinded to the clinical condition of each participant. All measurements were taken between 2:00 and 4:00 p.m., with the patient in a recumbent position while awake. During PWV and carotid assessment, continuous noninvasive blood pressure recording was obtained by using the Portapres device (TNO Biomedical Instrumentation, Amsterdam, The Netherlands), which has been shown to accurately estimate intraarterial blood pressure (34). This method has a height correction unit to compensate finger measurements with the heart level. The means of six stable measurements were used for the final analysis. The PWV measurement technique has been described previously (35). Briefly, common carotid artery and femoral artery pressure waveforms were recorded noninvasively by using a TY-306 Fukuda pressure-sensitive transducer (Fukuda, Tokyo, Japan). The pressure waveforms were digitized at the sample acquisition frequency of 500 Hz. The two pressure waveforms were then stored in a memory buffer. A preprocessing system automatically analyzed the gain in each waveform and adjusted it for equality of the two signals. When the operator observed a pulse waveform of sufficient quality on the computer screen, digitization was suspended and calculation of the time delay between the two pressure upstrokes was initiated. Measurements were repeated over 10 different cardiac cycles, and the mean was used for the final analysis. The distance traveled by the pulse wave was measured over the body surface as the distance between the two recording sites (D), whereas pulse transit time (t) was automatically determined by the Complior; PWV was automatically calculated as PWV = D/t. The validation of this automatic method and its reproducibility has been previously described (35). Carotid diameter and IMT were evaluated with a high-resolution echo-tracking system (Wall Track System) coupled with a conventional two-dimensional vascular echograph (Sigma 44 Kontrom Instruments, Watford, UK) equipped with a 7.5-MHz probe. Measurements were performed on the right common carotid arteries 1 cm below the bifurcation at the site of the distal wall. IMT was measured at the thickest point, not including plaques, on the near and far walls with a specially designed computer program. A high rate of IMT reproduction has been previously demonstrated (36). Plaque was defined as a localized thickening greater than 1.2 mm that did not uniformly involve the whole artery. Distensibility was calculated by using the following equation: Distensibility (D) = (2Δd · d + Δd2)/(ΔP · d2), where Δd means change in artery diameter during heart cycle, d means artery diameter, and ΔP means pulse pressure (37).
Data were analyzed with SPSS 10.0 statistical software (SPSS, Inc., Chicago, IL). Quantitative variables were expressed as the mean ± SEM. After checking normality with the Kolmogorov-Smirnov test, one-way analysis of variance with the Bonferroni post hoc test was used to compare means. Pearson correlation coefficients between polysomnographic and vascular data were obtained. Linear regression models with vascular parameters, including PWV, IMT, and carotid diameter as dependent variables, were constructed. Multiple regression analysis was used to identify variables that were independently associated with the vascular parameters and to adjust for possible confounding factors. Categoric variables were expressed by the frequency distribution, and their association was tested with likelihood ratio tests. A value of p < 0.05 was considered significant.
The local ethics committee approved the protocol, and all participants gave written, informed consent.
Of approximately 450 patients with established OSA, we initially invited for the study 45 patients who were eligible according to our rigorous exclusion criteria. We enrolled 30 patients because five refused to participate and 10 had already initiated continuous positive airway pressure therapy. Seventeen volunteers were studied by overnight polysomnography, but five were excluded because of mild OSA, leaving 12 for the vascular study.
Baseline characteristics of the study population, including control, mild-to-moderate, and severe OSA groups, are described in Table 1
Control (n = 12) | Mild to moderate OSA (n = 15) | Severe OSA (n = 15) | p Value | |
---|---|---|---|---|
Age, yr | 42 ± 2 | 43 ± 1 | 44 ± 1 | 0.67 |
Males, % | 93 | 93 | 84 | 0.64 |
Body mass index, kg/m2 | 28.9 ± 0.7 | 28.4 ± 0.6 | 29.3 ± 0.8 | 0.66 |
Whites, % | 83 | 67 | 80 | 0.35 |
Systolic blood pressure, mm Hg | 115.4 ± 3.5 | 114.2 ± 2.5 | 117.4 ± 3.0 | 0.74 |
Diastolic blood pressure, mm Hg | 58.9 ± 2.4 | 57.2 ± 1.3 | 58.0 ± 1.9 | 0.83 |
Pulse pressure, mm Hg | 56.6 ± 1.8 | 57.0 ± 1.9 | 59.4 ± 2.4 | 0.60 |
Heart rate, bpm | 75 ± 2 | 75 ± 2 | 76 ± 2 | 0.87 |
Fasting glucose, mg/dl | 96 ± 2 | 95 ± 3 | 98 ± 1 | 0.74 |
Cholesterol, mg/dl | 226 ± 14 | 226 ± 6 | 236 ± 8 | 0.67 |
LDL, mg/dl | 156 ± 8 | 137 ± 11 | 152 ± 8 | 0.46 |
HDL, mg/dl | 47 ± 5 | 44 ± 3 | 45 ± 2 | 0.73 |
Hemoglobin, g/dL | 15.0 ± 0.4 | 15.5 ± 0.4 | 15.3 ± 0.4 | 0.52 |
Hematocrit, % | 43.5 ± 1.2 | 45.8 ± 0.8 | 45.1 ± 0.9 | 0.26 |
Awake oxygen saturation, % | 95 ± 0.4 | 95 ± 0.4 | 95 ± 0.4 | 1.00 |
AHI, events/hour | 3.1 ± 0.3 | 16.2 ± 1.7 | 55.7 ± 5.9 | < 0.0001 |
SaO2min | 90 ± 1 | 81 ± 1 | 73 ± 1 | < 0.0001 |
SaO2 < 90% | 0.5 ± 0.4 | 3.7 ± 0.9 | 30.3 ± 5.7 | < 0.0001 |
Univariate analysis (Table 2)
PWV | p Value | IMT | p Value | CD | p Value | |
---|---|---|---|---|---|---|
Age, yr | 0.39 | 0.011 | 0.23 | NS | 0.28 | NS |
BMI, kg/m2 | 0.30 | NS | −0.02 | NS | 0.21 | NS |
SBP, mm Hg | 0.25 | NS | 0.031 | NS | 0.006 | NS |
PP, mm Hg | 0.28 | NS | 0.070 | NS | 0.13 | NS |
Cholesterol, mg/dl | 0.27 | NS | 0.25 | NS | 0.06 | NS |
AHI, events/hour | 0.61 | < 0.0001 | 0.44 | 0.004 | 0.45 | 0.004 |
SaO2min | −0.42 | 0.005 | −0.24 | NS | –0.60 | < 0.0001 |
SaO2 < 90% , % TST | 0.44 | 0.005 | 0.28 | NS | 0.45 | 0.004 |
In the multivariate analysis, AHI was the only significant variable remaining to explain PWV and IMT variability. The best and only variable to explain carotid diameter in the multivariate analysis was the SaO2min. These differences remained significant after adjustment for age and systolic blood pressure. No significant correlations were noted with any other parameter analyzed, including age, BMI, systolic blood pressure, pulse pressure, heart rate, and cholesterol levels. Figure 2
shows the correlations that remained significant in multivariate analysis (i.e., PWV and IMT with AHI and carotid diameter with SaO2min).The novel finding in the present study is that middle-aged patients with severe OSA, without overt cardiovascular diseases, demonstrate early signs of atherosclerosis by means of increased arterial stiffness and carotid remodeling measured by noninvasive, validated methods. In these patients, we observed a significant increase in PWV, IMT, and carotid diameter. Moreover, OSA severity was significantly and independently correlated with the vascular parameters evaluated by univariate analyses and were the only significant variables remaining in multivariate analyses. These signs of impaired arterial properties and arterial remodeling in patients with OSA were not present in the well-matched control subjects. Patients with OSA and control subjects were otherwise free from hypertension and other cardiovascular diseases, and differences cannot be explained by demographic or clinical conditions, including age, BMI, blood pressure levels, heart rate, glucose, and cholesterol levels. Because the different study groups presented no difference in classical cardiovascular risk factors, the vascular abnormalities are independently associated with OSA.
Atherosclerosis is much more complex than mere lipid storage, determined by environment associated with genetic factors. It involves several highly interrelated processes, including endothelial dysfunction, inflammation, oxidative stress, vascular smooth cell activation, platelet activation, and thrombosis. It is remarkable that OSA is also associated with the majority of these factors. Venous (38) and arterial (6, 39) endothelial dysfunction, systemic inflammation (7), increased levels of plasma VEGF (8), reactive oxygen species (9), soluble adhesion molecules (10), coagulation factors (11), and endothelin-1 (40) have been reported in patients with OSA. There is also evidence that some of these factors directly influence vascular elastic properties. For instance, it was recently demonstrated that endothelin-1 directly regulates PWV in vivo (41). Therefore, several or all these factors may contribute and help to explain the early signs of vascular dysfunction and remodeling observed in our relatively young patients with OSA who were otherwise free of overt cardiovascular diseases.
Two recent studies evaluated vascular elastic properties in patients with OSA. Nagahama and colleagues (15) found a significant increase in brachial-ankle PWV in patients with OSA as compared with that in control subjects. However, polysomnography was not performed in the control group. More importantly, patients with OSA were older and had more risk factors for atherosclerosis. Jelic and colleagues (42) described acute oscillations with an increase in arterial stiffness during OSAs assessed by applanation tonometry in the radial artery. In contrast, to avoid possible cyclic variations or immediate effects of apneas to arterial properties, all measurements in our study were performed in the afternoon while the patients were awake with stable breathing. Therefore, the repetitive increase in arterial stiffness during apneas, as described by Jelic and coworkers, may ultimately lead to the long-lasting changes in arterial stiffness observed in our study.
Previous studies have suggested an increased IMT in patients with OSA (16, 17). However, the population studied by Silvestrini and coworkers (16) included 22% smokers, 65% hypertensive subjects, and 17% patients with diabetes who were on average 20 years older than our sample. Similarly, almost 50% of the patients studied by Suzuki and colleagues (17) had hypertension. In contrast, we carefully excluded classical cardiovascular risk factors, including hypertension, smoking, and diabetes. In addition, a narrow range of age was studied, excluding elderly patients. Therefore, our unique study design allowed us to demonstrate the association of OSA with these vascular abnormalities.
An important finding in our study is the increased carotid diameter in patients with OSA. Nieto and colleagues (43) also reported increased diameters of large arteries in patients with OSA during the study of resting brachial artery diameter during flow-mediated vasodilation in a subset of elderly subjects of the Sleep Heart Health Study cohort. Previous studies showed that carotid artery dilatation is a compensatory mechanism in early stages of atherosclerosis (30). Vascular remodeling implies the concept of compensatory vessel enlargement to preserve luminal dimensions during atheromatous plaque development. Enlargement of large arteries with aging and high blood pressure has been extensively described (44, 45) and is generally attributed to the fracture of the load-bearing elastin fibers in response to the fatiguing effect of tensile stress. Increased artery diameter has been recently associated with mortality in patients with impaired glucose tolerance (46) and in patients with end-stage renal disease (47). According to our results, OSA is emerging as a new factor that promotes artery enlargement.
Although we observed several structural changes in the carotid arteries of patients with OSA, the functional properties evaluated by arterial distensibility were unchanged. These latter results suggest that structural modifications of the carotid artery associated with OSA could be a means by which arteries maintain normal distensibility, as was previously demonstrated in another study (48).
The exact mechanism by which OSA triggers all mediators that ultimately will lead to atherosclerosis is not completely understood. Previous experimental studies demonstrated the effects of intermittent and continuous hypoxia on the aortic wall in rabbits (49–51). Neither intermittent nor continuous hypoxia induced gross or microscopic alterations in the aorta. However, significant reductions in the amount of glycosaminoglycans and collagen were observed, directly influencing the mechanical properties of the aorta and impaired healing of vascular injury, without a significant alteration in arterial blood pressure. Supporting these findings, arterial hypoxia increased the severity of atherosclerosis in cholesterol-fed rabbits (52), and hyperoxia reversed plaque formation in this model (53), providing biological plausibility to justify the results observed in humans. Because all severity parameters in OSA, including oxygen parameters and AHI, are correlated, our study is limited and does not allow the isolation of which factor is more important for determining vascular dysfunction and structural changes. Although PWV and IMT correlated more with AHI, carotid diameter was more strongly related to SaO2min. In contrast to our results, Suzuki and coworkers (17) and Schulz and colleagues (54) found that IMT was related to the degree of nocturnal hypoxia. Independent of the exact mechanism, our study further supports the hypothesis that OSA is a potential atherogenic factor (55), leading to damage of the arterial wall of large arteries.
The biological relevance of our data can be evidenced when we compare the vascular parameters in different populations with traditional risk factors to cardiovascular diseases. The range of IMT values observed in our patients with severe OSA is similar to those observed in the intermediate quartiles in a longitudinal population that was almost 20 years older (age range, 59–71 years) (28) than our sample. This particular subgroup presented an age- and sex-adjusted odds ratio to carotid plaque occurrence of 2.66 (95% confidence interval, 1.58–4.46; p < 0.001) in a 4-year follow-up. In a population of patients with end-stage renal disease, a PWV greater than 9.4 m/second (as compared with 9.2 and 10.3 m/second in our patients with mild to moderate and severe OSA, respectively) was an independent predictor of all-cause and mainly cardiovascular mortality in a 7-year follow-up. For each PWV increase of 1 m/second, the all-cause mortality adjusted odds ratio was 1.39 (95% confidence interval, 1.19–1.62) (56). Similarly, in a population with type 2 diabetes, aortic PWV independently predicted all-cause and cardiovascular mortality for each 1 m/second increase (hazard ratio, 1.08; 95% confidence interval, 1.03–1.14) (57). Therefore, the vascular abnormalities observed in our population with OSA strongly suggest an increased risk for cardiovascular diseases.
In conclusion, early signs of atherosclerosis are present in young adults with OSA, who are free of cardiovascular diseases. These findings are proportional to OSA severity and support the hypothesis that OSA plays an independent role in atherosclerosis progression.
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