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Published ahead of print on August 11, 2004, doi:10.1164/rccm.200404-458OC
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American Journal of Respiratory and Critical Care Medicine Vol 170. pp. 1114-1119, (2004)
© 2004 American Thoracic Society
doi: 10.1164/rccm.200404-458OC

Original Article

Influence of Weight and Sleep Apnea Status on Immunologic and Structural Features of the Uvula

Frédéric Sériès, Jamila Chakir and Dominick Boivin

Unité de Recherche en Pneumologie, Centre de Recherche de l'Hôpital Laval, Institut Universitaire de Cardiologie et de Pneumologie de l'Université Laval, Québec, Quebec, Canada

Correspondence and requests for reprints should be addressed to Frédéric Sériès, M.D., Hôpital Laval, 2725 Chemin Sainte-Foy, Québec, PQ, G1V 4G5 Canada. E-mail: Frederic.Series{at}med.ulaval.ca


   ABSTRACT
TOP
 ABSTRACT
METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
We investigated the influence of weight and obstructive sleep apnea status on inflammatory and histologic features of the uvula. Tissue samples resected during uvulopalatopharyngoplasty in 11 snorers without obstructive sleep apnea, 11 subjects with obstructive sleep apnea and of similar body mass index and age, and 8 additional obese subjects with obstructive sleep apnea were examined by immunohistochemistry and histologic staining techniques. The frequency and distribution of immune cells, the amount of collagen, and the integrity of the elastin fiber network were evaluated in proximal and distal uvular sections. T cell (CD4+, CD8+) and macrophage counts were higher in the more obese apneic subjects than in the other two groups. In all patients, T cell counts correlated with body mass index, but there was no relationship with the apnea–hypopnea index. A positive correlation was found between elastin fiber network disorganization score and apnea–hypopnea index. We conclude that (1) the amount of inflammatory markers is linked to obesity rather than to sleep-related breathing disorders, and (2) obstructive sleep apnea is associated with a structural alteration of the extracellular matrix of upper airway tissue.

Key Words: collagen • elastin • inflammation • obesity • upper airways

Obstructive sleep apnea (OSA) is characterized by recurrent episodes of upper airway (UA) obstruction during sleep. It is usually associated with repetitive hypoxemia, fragmentation of sleep, and cardiovascular complications (1–5). Epidemiologic studies have estimated the prevalence of OSA in the adult population at between 2 and 4% (6, 7), with age (8, 9), sex (10), and weight (11) being three major factors influencing the prevalence. The maintenance of UA patency depends on the balance between collapsing and dilating forces. Many forces contribute to UA collapse, including the negative transmural pressure gradient and tissue weight. They are counterbalanced by the traction and stiffening of UA tissues resulting from the contraction of dilator muscles. However, in patients with OSA, UA occlusion occurs despite of an increase in UA dilator neuromuscular activity (12–14). Not only is the electromyographic activity of UA dilator muscles higher but their capacity to generate tension is also higher as shown in vitro with the musculus uvulae (15). The discrepancy between the increase in neuromuscular activity and the force developed by the UA dilator muscles, and the persisting propensity of the UA to collapse, may be explained by functional abnormalities of UA tissues that would alter the transmission of the stabilizing force resulting from the contraction of UA muscles to the whole UA structure. We have previously shown that uvular stiffness is higher in subjects with OSA compared with nonapneic snorers (16). This increase in uvular elastance was found to positively correlate with the apnea index, suggesting that the mechanical properties of UA tissues contribute to the ability of UA dilator muscles to stabilize the UA.

Recurrent episodes of UA fluttering and/or UA closure can lead to the development of an inflammatory process and of histologic alterations of UA tissues that can in turn alter the integrity of the extracellular matrix and interfere with the mechanical properties of soft tissues. Only a few studies have examined the inflammatory features of UA tissues in OSA (17), particularly in the uvular mucosa (18, 19). The lack of adequate control subjects (if any) and the descriptive nature of the published results make it difficult to draw any firm conclusions about the role of local inflammatory processes and histologic alterations in the development of uvular functional abnormalities. The primary aim of the present study was to examine the influence of sleep-related obstructive breathing disorders and its severity on uvular tissue histologic characteristics. The proximal and distal sections of the uvula were investigated separately because the degree of tissular abnormality may vary with the degree of mechanical stress. Some of the results of this study have been previously reported in the form of an abstract (20).


   METHODS
TOP
 ABSTRACT
 METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Subjects
Thirty subjects (Table 1) who underwent an uvulopalatopharyngoplasty (UPPP) for the treatment of OSA or nonapneic snoring were included in the study. None of the subjects had been previously treated for OSA or snoring at the time of surgery. No subject was taking neuroleptics, antidepressors, or any medication that affects breathing during sleep. No subjects with diabetes mellitus were included. All had normal thyroid function. All subjects had a conventional sleep recording taken preceding UPPP. The 30 subjects were distributed into 3 groups (Table 1). The first group was made up of nonapneic snorers, the second consisted of patients with OSA whose body mass index (BMI) was similar to that of the snorers (OSA 1), and the third group was made up of subjects with OSA who could not be associated with nonapneic snorers on the basis of their BMI (OSA 2). There was a similar number of smokers in each group (four among the nonapneic snorers, three in the OSA 1 group, and three in the OSA 2 group). The other subjects were nonsmokers or had stopped smoking for more than 1 year. No alcohol intake was reported by three nonapneic snorers, four OSA 1 subjects, and three OSA 2 subjects. Alcohol consumption was considered low to moderate (two or fewer glasses of alcoholic beverage per day) among the other subjects. No subject was known to have asthma or allergic rhinitis and none was using topical steroids. The internal review board of our institution (Université Laval, Québec, PQ, Canada) approved the protocol and informed consent was obtained from each subject.


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  		TABLE 1. Anthropomorphic and polysomnographic data from nonapneic snorers and patients with obstructive sleep apnea

 
Sleep Studies
The sleep studies were conducted using conventional polysomnographic techniques (21, 22). Airflow was quantified with the nasal pressure signal obtained from nasal prongs (nasal oxygen cannula [Baxter, Valencia, CA] or a nasal CO2 sample line [Ohmeda, Madison, WI]) connected to a pressure transducer (Validyne MP-45 [Validyne Engineering, Northridge, CA], ± 100 cm H2O) (23). Apnea was defined as an interruption of airflow for more than 10 seconds. Hypopnea was defined as a 50% reduction in airflow for more than 10 seconds associated with a drop of at least 3% in blood oxygen saturation and/or arousal or awakening.

Biopsy Procedures
Uvular tissue samples were resected during a conventional UPPP procedure as described previously (24). After surgery, the resected tissue was immediately divided into two sections (proximal and distal). Each section was then divided transversely. One was fixed in 4% paraformaldehyde and embedded in paraffin and the other was frozen in optimal cutting temperature compound (Ted Pella, Redding, CA). All subsequent measurements were done blind to patient status and uvula section.

Immunohistochemistry
Sections (8 µm) were cut from the frozen tissues and were stained with the following antibodies: mouse anti-human CD4 and CD8 (T cell subpopulations), diluted 1:10; mouse anti-human CD68 (macrophages), diluted 1:10; and mouse anti-human neutrophilic elastase (neutrophils), diluted 1:200. Immunostaining was performed as described previously (25). Sections were incubated with the primary antibody and then with a biotinylated secondary antibody. A preformed avidin–biotin–horseradish peroxidase complex was then added. To detect bound antibodies, sections were incubated with aminoethylcarbazole substrate until staining was visible by microscope. Washing with water stopped the reaction. Mayer hematoxylin was used for counterstaining. Slides were mounted with Crystal/Mount (Biomeda, Foster City, CA). Irrelevant isotypic antibodies served as negative controls.

Quantification of Immunohistochemical Staining
All slides were coded and stained cells on each section were counted blindly. Six consecutive visual fields including the basement membrane and subepithelial tissue were randomly analyzed at a magnification of x200, using a SPOT RT slider camera (Diagnostic Instruments, Sterling Heights, MI) and Image-Pro Plus (MediaCybernetics, Silver Spring, MD). Counts were expressed as the number of positive cells per millimeter of basement membrane.

Histologic Staining
Paraffin sections (8 µm) were cut from the proximal part of proximal and distal sections and stained for elastic fibers, using the Verhoeff technique (26).

Morphologic Analysis
Elastin fiber disorganization was evaluated on whole samples, using a 1-cm2 grid with a magnification of x100 (27, 28). Tissue sections were divided into three areas for analysis. The subepithelial field corresponded to a zone 150 µm under the basement membrane, and the perimuscular field consisted of tissues up to 150 µm around the musculus uvulae. The mucosal area included tissue lying between the subepithelial and perimuscular fields. Each field was then given a disorganization score between 0 and 100%. Intact and well-oriented fibers lying parallel to the epithelium were scored as 0 (an example is given in Figure 1A). For tissues with a degree of disorganization, the higher the score, the higher the level of fragmentation, the disparity in fiber length, and the disorientation of elastin fibers, that is, small elastin fibers of variable size, lack of systematic orientation parallel to the epithelium, and fibers crossing. An example of disorganized fibers is given in Figure 1B. Two independent raters validated the scoring and the interrater scoring variability was less than 10%. Results are expressed as the average percentage of disorganization for each area.




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  		Figure 1. (A) Cross-section of the distal portion of the uvula, showing well-organized network of parallel elastin fibers in the mucosal tissue. (B) Cross-section of the uvula, showing a disorganized network of elastin fibers in the mucosal tissue. The fibers do not follow any discernable pattern and are of variable size. Original magnification: (A and B) x100.

 
Statistical Analysis
Data are expressed as means ± SD. Anthropometric data were analyzed by one-way analysis of variance. Comparisons between groups were performed by the Tukey multiple comparison technique. The normality assumption was verified using graphic representations and the Shapiro–Wilk test. The Brown and Forsythe variation of Levene's statistic test was used to verify the homogeneity of variances. All assumptions were fulfilled except for BMI and the apnea–hypopnea index (AHI). Logarithm transformations were applied to these variables to fulfill the normality and variance assumptions. One-way analysis of variance was used to analyze disorganization data. An arc sinus transformation of the square root was applied as these values are expressed as percentages. Categorical variables were analyzed by Fisher exact test. Pearson correlation coefficients were used to measure the relationship between parameters. Results were considered significant at p <= 0.05. All analyses were conducted with the SAS statistical package (SAS Institute, Cary, NC).


   RESULTS
TOP
 ABSTRACT
 METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Anthropometric and polysomnographic data are summarized in Table 1. On the basis of selection criteria, OSA 2 patients had a significantly higher BMI than did subjects of the two other groups. The OSA 1 and OSA 2 groups also differed in neck circumference, which was significantly higher in the OSA 2 group. The neck circumference of both OSA groups was also significantly higher than for snorers. No difference was found in AHI, desaturation index, or magnitude of SaO2 fall at night between the two OSA groups.

Immunohistochemistry
Table 2 summarizes cell counts. The number of CD4+ T cells in the subepithelial area of the uvular tissue was significantly higher in OSA 2 subjects than in OSA 1 subjects and nonapneic snorers. This difference was observed both in the proximal and distal uvular sections. The same pattern was observed with CD8+ T cells, with the most obese subjects with OSA having higher cell count than the other subjects (Table 2). No differences in the numbers of macrophages or neutrophils in the proximal uvular sections were found between the three groups. However, in the distal uvula, cell counts were significantly higher in OSA 2 subjects than in OSA 1 subjects and nonapneic snorers (Table 2). No differences in the numbers of lymphocytes, macrophages, or neutrophils were found between the OSA 1 and nonapneic snorer groups in either the proximal or distal sections of the uvula.


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  		TABLE 2. Cell counts in nonapneic snorers and subjects with obstructive sleep apnea

 
An independent positive relationship was found for the entire study population between CD4+ and CD8+ cell counts and BMI (Figure 2). A similar relationship was observed between CD4+ and CD8+ cell counts and neck circumference (r = 0.5, p <= 0.0002). Interestingly, no relationship was found between these cell counts and AHI, desaturation index, or percent total sleep time < 90% SaO2.




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  		Figure 2. Relationship between body mass index and CD4+ cells (A) and CD8+ cells (B).

 
Morphology
The structural arrangement of the network of elastin fibers was homogeneous in the proximal uvular tissue, with no difference between the three groups (data not shown). However, the structural arrangement was nonhomogeneous in the different fields of the distal part of the uvula. Figure 1 shows an example of elastin fiber staining in distal uvular sections. In the three subject groups the percentage of disorganization was more important in the mucosal than in the perimuscular tissue (p = 0.006) (Table 3). While the percentage of elastin fibers disorganization was slightly higher in the mucosal tissue of the OSA 1 and OSA 2 groups than in nonapneic snorers, the difference was not significant. The percentage of elastin fiber disorganization in the mucosal tissue positively correlated with the AHI (r = 0.61, p = 0.002) and the desaturation index (r = 0.59, p = 0.003) for all subjects.


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  		TABLE 3. Percentage of disorganization of elastin fiber network in distal portion of the uvula

 

   DISCUSSION
TOP
 ABSTRACT
 METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
We found that OSA associated with obesity was a more important determinant of uvular tissue inflammatory features than the sleep apnea status itself. OSA also altered the organization of elastin fibers in the distal part of the uvula.

Previous studies have focused on the effects of snoring/sleep apnea status on the inflammatory process in the UA mucosa. Proinflammatory mediators and a higher proportion of polymorphonuclear cells have been observed in the uvular tissue of snorers and apneic subjects than in control subjects (17). Other studies have reported histopathologic changes in the soft palate of patients with OSA (15, 29, 30). For instance, Sekosan and coworkers reported that the total leukocyte count was higher in the mucosa of the uvular tissue of patients with OSA than in a control group of postmortem subjects who were supposed to have been free of nocturnal breathing disorders (18). Paulsen and coworkers (19) found that the number of leukocytes (mainly CD3+ lymphocytes) along the uvular epithelial–connective boundary is higher in the patient group than in the control group. In both these studies, the use of postmortem samples as control tissues may have significantly interfered with interpretation of the data because OSA was ruled out only by medical histories, which are known to be unspecific, and because postmortem cell damage can interfere with immune cell counts (31). Furthermore, and most importantly, the anthropomorphic characteristics (BMI and neck circumference) of the subjects in these studies significantly differed between OSA and control subjects. This would presumably affect the inflammatory features of the tissue, as our results would suggest.

It is now acknowledged that obesity is a proinflammatory condition. This is attributed to the endocrine properties of adipose tissue (32), with the release of inflammatory mediators such as interleukin-6 and tumor necrosis factor-{alpha} and a secondary increase in C-reactive protein (33), all of which are thought to be involved in the obesity-related increase in cardiovascular morbidity (34). The increase in the number of CD4+ and CD8+ cells in the uvula of the most overweight subjects with OSA suggests that the systemic inflammatory features associated with obesity also result in greater UA tissue inflammation. It is not possible to preclude that these features are specific to UA tissues or that they are also present in other organs because UA tissues play a key role in the occurrence of obstructed breaths and are exposed to repetitive mechanical stretchings. This can lead to velopharyngeal inflammation even during wakefulness (35). Our results at least suggest that obesity promotes inflammation in tissues subjected to chronic mechanical damage and highlight two important points. The first is that obesity contributes to the development of local UA inflammation more than sleep apnea per se. On the one hand, no differences in the uvular inflammatory profile were observed between subjects with OSA and nonapneic snorers with similar BMI. On the other hand, BMI but not AHI or desaturation index differed between the two OSA groups. However, this situation may be even more complex given that systemic inflammatory markers are higher in overweight subjects with sleep apnea than in nonapneic subjects with identical BMI (36), and that the decrease in these markers when sleep apnea is cured is independent of weight loss (37). This suggests that obesity is not the only proinflammatory factor in these patients. To explore the respective influence of obesity and sleep apnea on these tissue characteristics, the effects of weight loss and continuous positive airway pressure before UPPP should be examined separately. Such a study would obviously be ethically difficult to conduct if the treatment is randomized. The second point is that snoring per se leads to a similar degree of UA inflammation as OSA when obesity is not a factor. This is supported by a comparison of our data with the results published by Sekosan and coworkers (18). They reported lymphocyte and plasma cell counts in the uvular mucosa of a control population that were half those of the nonapneic snorers in our study. It is conceivable that the UA fluttering that characterizes snoring could lead to velopharyngeal mechanical damage similar to UA closure.

One could ask to what extent UA inflammation could be involved in the pathophysiology of UA closure. McNicholas and coworkers (38) reported that patients with acute exacerbations of allergic rhinitis (which is known to be associated with UA inflammation) have longer and more frequent episodes of disordered breathing during sleep than during the remission phase. In acute UA inflammation, several factors such as edema, modifications in surface tension forces, and/or tissue stiffening may impede the transmission of the traction forces developed by UA dilator muscle contraction. In the present study, no correlation was found between the presence of immune cells in the uvular mucosa and the AHI. In the absence of a clinical allergic context, tissue inflammation would be a consequence rather than a cause of breathing disturbances. Because the frequency of nocturnal breathing disorders was the same in the two OSA groups, there was no evidence that uvular tissue inflammatory infiltrates contributed to OSA severity.

No measurements were obtained from a nonsnoring group. Results from such a group would be helpful to specifically evaluate the effect of snoring per se on UA tissue inflammatory features. However, just as we were convinced that a polysomnographic study had to be done in all our subjects, the plus value of including a nonsnoring group would depend on our ability to firmly exclude any possible diagnosis of sleep-disordered breathing in these patients. Given the limited diagnostic value of clinical prediction rules, the only alternative would be to conduct presurgery polysomnographic studies. This would exclude the possibility of using postmortem specimens (in addition to the inaccuracy of measurements when using cadaver tissue samples). On the other hand, other UA tissues such as tonsillar tissue can be obtained from patients undergoing tonsillectomies. However, this procedure is rarely performed in adults like those who participated to the present study. In addition, significant differences in age and BMI could be anticipated between study subjects, which would dramatically interfere with the interpretation of the results, particularly in the context of the results obtained in the present study. Therefore, when it is totally unacceptable to collect UA samples (other than limited tongue biopsies) in a well-selected and well-identified population free of any surgical indication, it is difficult to see how we could have included nonsnoring subjects in our study. Because of this, the data of Sekosan and coworkers (18) are particularly important for supporting the hypothesis that snoring by itself leads to upper airway inflammation independent of apneic activity.

It is reasonable to question to what extent the lack of significant differences between snorers and OSA 1 subjects may be due to an overlap between these two groups in terms of sleep-disordered breathing. From a clinical point of view, none of the snoring subjects reported any symptoms suggestive of sleep apnea, their weight had remained stable for the previous 6 months, they were not taking any medication, and none of them complained of allergic rhinitis. Furthermore, for these subjects, at least 40% of the recorded total sleep time was spent supine. The usual conditions that might potentially be associated with night-to-night worsening of sleep apnea activity were thus not seen in these patients. Another way to evaluate the possible influence of fluctuations of nocturnal breathing disorders is to examine the homogeneity of the inflammatory tissue features in our different groups. We reasoned that if a significant overlap in nocturnal breathing disorders between our snoring subjects and subjects with sleep apnea altered our capacity to identify differences in inflammatory features, we would expect a greater fluctuation in the inflammatory variables in our nonapneic snorers. Data reported in Table 2 clearly demonstrate that the fluctuation in these variables was dramatically lower in the nonapneic group than in the two other groups. Insofar as these UA tissue inflammatory markers can be considered as reflecting the long-term consequences of nocturnal breathing disorders, there is no evidence that fluctuations in AHI could account for the nonsignificant differences in these markers between nonapneic and mildly apneic subjects.

A third methodologic issue that could alter the significance of our findings is the lack of statistical power. We determined that the statistical power was 39% for the study reported here and that 48 (16 per group) patients would be needed to reach a statistically significant difference in elastin fiber disorganization between OSA subjects and snorers with a 80% statistical power and an {alpha} error of 0.05. From a physiological point of view, demonstrating such a difference between groups would not provide much more information than the significant correlation that was observed between elastin network disorganization and the frequency of sleep-related breathing disorders. In fact, it would demonstrate only that the AHI threshold of 15 episodes/hour adequately discriminates for the severity of elastin network disorganization. It is important to specify that because our results obtained from 30 patients demonstrate a pivotal role of AHI in UA elastin fiber disorganization, this correlation would be further strengthened by increasing the sample size.

We found that elastin network disorganization correlated with AHI. Given the similarity in elastin disorganization scores for the two OSA groups and the difference in tissular inflammatory features between the two groups, it is reasonable to hypothesize that these two findings are unrelated. The proximal and distal sections of the uvula behave differently, with a significant difference in disorganization scores between the three fields in the distal section of the uvula. Such local alterations in elastin fiber organization may result from recurrent tissue stretching and crushing of the uvula between anterior (tongue) and posterior (posterior pharyngeal wall) UA tissues (39). Such extracellular matrix disorganization has been previously reported in the bronchial mucosa of subjects with asthma (28). It can be speculated that the disorganization of the elastin fiber network may contribute to the loss of uvular elasticity observed in vitro in patients with OSA (16).

Our results show that the increase in UA tissue inflammatory features is linked to obesity rather than to obstructive sleep apnea status. Consequently, the UA inflammatory process can be dissociated from the structural alterations of the extracellular matrix observed in sleep-related breathing disorders that are independent of body weight.


   Acknowledgments
 
The authors thank Caroline Paquet, Doris Cantin, and Sabrina Biardel for technical assistance, and Serge Simard for statistical analysis.


   FOOTNOTES
 
Supported by the Canadian Institutes of Health Research.

Conflict of Interest Statement: F.S. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript; J.C. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript; D.B. does not have a financial relationship with a commercial entity that has an interest in the subject of this manuscript.

Received in original form April 5, 2004; accepted in final form August 10, 2004


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 METHODS
 RESULTS
 DISCUSSION
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