SEARCH

SEARCH BY CITATION

Keywords:

  • apolipoprotein M;
  • haptoglobin;
  • obstructive sleep apnoea;
  • paraoxonase-1;
  • proteomics;
  • serum

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Conflict of interest
  9. Funding
  10. References

Obstructive sleep apnoea (OSA) is a common syndrome, which is associated with a number of medical problems that impact morbidity and mortality. Although the precise mechanisms that underlie these associations are not fully understood, previous studies have suggested that patients with OSA show elevations of several biomarkers that are associated with cardiovascular risk. This study was undertaken to identify serum proteins associated with OSA by using a proteomics technique and to examine changes in identified protein levels after continuous positive airway pressure treatment. The study participants consisted of 40 male patients (aged 40–49 years) with severe OSA and 34 male control subjects matched for age and body mass index. All subjects underwent polysomnography. Using a proteomics approach, we identified nine proteins that were differentially expressed in patients with severe OSA and controls. Three of these nine proteins, haptoglobin, paraoxonase-1 and apolipoprotein M, were quantified by using enzyme-linked immunosorbent assays, kinetic assays and by using Western blotting. Multiple regression analysis showed that haptoglobin and apolipoprotein M levels are independently related to apnoea–hypopnoea index (P < 0.01). A further study is required to determine the nature of associations between these identified proteins and OSA in a large population.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Conflict of interest
  9. Funding
  10. References

Obstructive sleep apnoea (OSA) is characterized by repetitive obstruction of the upper airway during sleep, and is primarily associated with sleep fragmentation and excessive daytime sleepiness. Furthermore, it has been well documented that this syndrome is closely linked with cardiovascular disease (CVD; Shahar et al., 2001; Young et al., 2002), stroke (Yaggi et al., 2005) and insulin resistance (Punjabi et al., 2004). Recent studies have suggested that individuals with OSA show elevations in several biomarkers associated with cardiovascular risk. Increases in circulating endothelin-1 (Phillips et al., 1999), L-selectin (Ohga et al., 1999), leptin (Atwood, 2005; Tatsumi et al., 2005) and C-reactive protein (Yokoe et al., 2003), which are all recognized independent markers of cardiovascular risk, have also been observed in patients with OSA, even in the absence of CVD.

Historically, two-dimensional electrophoresis (2-DE) has been the primary method of separating and comparing complex protein mixtures, although, recently, impressive improvements in 2-DE technology have been made. These include a proteomic analysis, a hugely powerful and potentially useful technology, which is likely to contribute to the diagnosis, treatment and prevention of human disease (Calvo et al., 2005; Duncan and Hunsucker, 2005). Proteomic analysis has been employed extensively to investigate cancer and many other diseases (Hanash et al., 2002; Jungblut et al., 1999). However, although no proteomic study has been conducted to date on serum samples from patients with OSA, it is anticipated that proteomic technologies will become increasingly used in the context of protein discovery and as a screening tool for the diagnosis of OSA in the clinical setting (Polotsky and O’Donell, 2007). Therefore, the purpose of this study was to identify serum proteins associated with OSA using a proteomic technique, to examine changes in the levels of these proteins after continuous positive airway pressure (CPAP) treatment and to identify proteins that predict the presence of OSA.

Materials and methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Conflict of interest
  9. Funding
  10. References

Subjects

The study subjects consisted of 40 male patients with severe OSA, aged 40–49 years, and age- and body mass index (BMI)-matched 34 normal male control subjects who also underwent polysomnography (PSG). The study subjects were recruited from the Pulmonary Sleep Disorder Center at Korea University Ansan Hospital, where they had been referred for clinical evaluations of possible OSA. Patients with severe OSA were defined as having an apnoea–hypopnoea index (AHI) of ≥ 30 and clinical symptoms. Control subjects were recruited from the database of the Korea Health Genomic Study (KHGS), details of which have been previously described (Cho et al., 2006; Kim et al., 2004; Shin et al., 2005). Control subjects were selected from individuals with an AHI < 5 to match the patients for age and BMI (±3 years and ±2 kg m−2, respectively). Patients with severe OSA were readmitted the next day in order to determine the optimal pressure for nasal CPAP treatment, which was recommended for all patients. After using CPAP at home for 3–5 months, patients were re-examined with PSG at our sleep laboratory. Compliance with CPAP therapy was evaluated by taking readings of a time counter built into the CPAP machines (REMstar; Respironics, Atlanta, GA, USA). Acceptable compliance was defined as CPAP use for at least 4 h per night, five nights a week. Of the 40 patients, 12 were included in a follow-up study. Twenty-eight subjects, who did not use the device (n = 12), had less than acceptable compliance (n = 6) or did not respond to a request for follow-up PSG (n = 10), were excluded from the follow-up analysis. Ten subjects in the severe OSA and in the control groups were randomly selected for the 2-DE analyses. All participants with chronic diseases, such as hypertension, cardiovascular disease CVD, stroke, pulmonary disease, diabetes mellitus and renal disease, were excluded. Informed written consent was obtained from all study subjects, and the study protocol was approved by the ethics committees.

Blood sampling and biochemical analysis

Venous blood was obtained from patients with severe OSA and controls in overnight fasting state after PSG. Blood samples were aliquoted and stored at −80 °C until analysis. Serum cholesterol, HDL cholesterol, triglycerides and creatinine were analysed using a Hitachi 7600-100 chemistry analyser (Hitachi, Tokyo, Japan).

Overnight polysomnography

All 74 study subjects underwent an overnight sleep study, using a computerized 16-channel PSG system (Alice 4; Respironics, Atlanta, GA, USA). All PSG results were scored manually according to standard criteria (Rechtschaffen and Kales, 1968). Arousals were also identified using established criteria (American Sleep Disorders Association, 1992). Apnoea was defined as the absence of airflow for 10 s and hypopnoea was defined as a discernible reduction in airflow associated with a reduction in oxygen saturation of at least 4% from baseline. AHI was defined as the average number of apnoea plus hypopnoea events per sleep hour.

Two-dimensional electrophoresis

To remove high-abundance proteins from human serum, we used commercial kits (Albumin and IgG Removal Kits; Amersham Biosciences, Uppsala, Sweden). The depleted serum samples obtained were treated for 1 h with lysis solution (8 m urea, 4% CHAPS and 2% IPG buffer) prior to protein quantification. Protein concentrations in depleted serum samples were determined using 2D Quant Kits (Amersham Biosciences). These prepared samples (200 ug) were mixed with a sample buffer solution (7 m urea, 2 m thiourea, 2% CHAPS, 20 mm DTT and 0.5% IPG buffer). Each sample (100 uL) was then subjected to isoelectric focusing using a re-hydrated IPG strip (pH 3–10 NL, 24 cm; Amersham Biosciences); strips were re-hydrated for 18 h in 450 uL of a rehydration buffer. Separation in the first dimension (IEF) was performed on an Ettan IPGphor system (Amersham Biosciences) using a five-phase programme. Subsequently, strips were incubated in an equilibration solution, and the separation in the second dimension was performed on an Ettan DALTsix system using gradient SDS-PAGE gels (12–18% T). Electrophoresis was conducted at 2.5 W per gel until the bromophenol blue marker reached the bottom of the gel.

Silver staining was performed using a previously described staining protocol (Shevchenko et al., 1996). Gels were then scanned and image analysis was performed using the ImageMaster 2-D Platinum (Version 6.0, Amersham Bioscience, Uppsala, Sweden) program. The amounts of proteins in spots were determined by integrating pixel densities and correcting for background; results are expressed as integrated optical densities. Adjusted P-values for step-down multiple testing procedures were applied using the ‘multitest’ library of R package (Westfall and Young, 1993).

MALDI-TOF analysis and database searching

Protein analyses were performed using an Ettan MALDI-TOF (Amersham Biosciences). The search program ProFound, which was developed at The Rockefeller University (New York) (http://prowl.rockefeller.edu/prowl-cgi/profound.exe), was used to identify proteins by peptide mass fingerprinting. The spectra were calibrated using the trypsin auto-digestion ion peak at m/z (842.510, 2211.1046) as internal standards.

Detection of haptoglobin, paraoxonase-1 and apolipoprotein M

Serum haptoglobin levels were determined using commercial ELISA kits (Biosource Inc.; CA, USA), whereas PON1 was determined using a semi-automated microplate assay, as described previously by Charlton-Menys et al. (2006). This assay has an intra- and inter-assay coefficient of variation of 4.7% and 3.7%, respectively. Serum apo M levels were determined by Western blotting, after detecting apoM with anti-apo M monoclonal antibody (1 : 1000, BD Biosciences) and mouse anti-rabbit IgGs conjugated to horseradish peroxidase (1 : 10 000) in a Tris-buffered saline supplemented with 5% non-fat dry milk. Bands corresponding to apo M were visualized by ECL and quantified using a scanner running Quantity One software (version 5.0, Bio-Rad, Hercules, CA, USA). Serum samples from OSA and controls were run in the same gels using a human serum standard as a control. Integrated densities were normalized by dividing values obtained from gels by the fraction of human serum standards run in parallel in the same gels.

Statistical analysis

All data are presented as mean ± SD for continuous variables and as numbers of subjects (%) for discrete variables. Differences between the two study groups were determined using the Student’s t-test and the paired t-test for continuous variables, and using the chi-squared test for categorical variables. To further evaluate the relationship between protein levels and various variables, a stepwise multiple linear regression analysis was performed using haptoglobin, PON1 and apo M as dependent variables. Statistical significance was accepted for values of P < 0.05. Data analysis was performed using spss version 10.0 for Windows (SPSS Inc., Chicago, IL, USA).

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Conflict of interest
  9. Funding
  10. References

General characteristics of participants

The general characteristics of the study subjects (40 patients with severe OSA and 34 controls) and of the 20 subjects (10 patients with OSA and 10 controls) whose blood was collected for the 2-DE analysis are provided in Table 1. The mean AHI values of the 40 patients with severe OSA and of the 34 controls were 54.1 and 1.7, respectively.

Table 1.   General characteristics of the study subjects
 Screened subjectsTotal subjects
OSA (n = 10)Control (n = 10)OSA (N = 40)Control (N = 34)
  1. AHI, apnoea-hypopnoea index; BMI, body mass index. *< 0.05 versus controls. **< 0.01 versus controls.

Age (years)46.5 ± 3.444.6 ± 2.344.9 ± 4.144.7 ± 2.8
Body mass index MI (kg m−2)27.8 ± 2.326.5 ± 1.227.2 ± 2.126.5 ± 1.4
Current smoking (%)50.050.055.244.8
Systolic blood pressure (mmHg)122.2 ± 8.2119.1 ± 8.1123.5 ± 9.2**114.6 ± 10.3
Diastolic blood pressure (mmHg)81.5 ± 5.783.3 ± 8.882.6 ± 5.9*79.1 ± 7.6
Creatinine (mg dL−1)1.05 ± 0.10.98 ± 0.21.0 ± 0.11.0 ± 0.1
Total cholesterol (mg dl−1)204.1 ± 30.5200.5 ± 34.1213.8 ± 33.5**184.6 ± 34.5
HDL cholesterol (mg dL−1)43.6 ± 6.443.3 ± 6.038.2 ± 6.8*42.4 ± 6.5
Triglyceride (mg dL−1)211.3 ± 83.3162.8 ± 77.1214.6 ± 90.3174.4 ± 98.5
Epworth sleepiness scale9.1 ± 3.2**5.5 ± 3.99.4 ± 3.2**5.8 ± 3.3
Apnoea–hypopnoea index HI (events/h)56.3 ± 16.4**0.7 ± 0.954.1 ± 17.5**1.7 ± 2.1
Lowest desaturation point (%)74.4 ± 6.0**92.0 ± 1.671.8 ± 11.7**89.7 ± 3.8
Arousal index (events/h)58.7 ± 15.7**10.1 ± 5.655.8 ± 16.5**10.3 ± 5.4

Two-dimensional electrophoresis analysis in serum of patients with severe OSA and controls

Two-dimensional electrophoresis was performed twice per sample in order to minimize gel-to-gel variations. Fig. 1 shows a representative 2D gel image of serum from patients with severe OSA and controls. Spots that showed twofold or greater alterations in expression in OSA serum versus normal control serum were defined as being of interest, and as a result, nine proteins were found to be either up- or downregulated in patients with OSA. Of these proteins, three proteins were quantified by ELISA, kinetic assays and Western blotting. Relative intensity differences of these proteins in 2D gel are provided in Table 2.

image

Figure 1.  Representative two-dimensional electrophoresis (2-DE) gel images of serum samples from patients with severe obstructive sleep apnoea (OSA) and controls. Serum proteins were focused on pH 3–10 immobilized gradient strips and then separated on an 12–18% gradient sodium dodecyl sulphate-polyacrylamide gel, stained and visualized (as described in Materials and methods). Protein spots identified by MALDI-TOF MS (arrowed) are marked on the figure with their spot numbers.

Download figure to PowerPoint

Table 2.   The relative intensities of haptoglobin, PON1 and apo M in OSA and control
 OSA (vol%, n = 10)Control (vol%, n = 10)
  1. The spot image was analysed using the ImageMaster 2-D Platinum program. The volume of the spots was calculated by total spot normalization and the quantity of spots was expressed as percentage of volume. *< 0.05 versus controls. **< 0.01 versus controls. apo M, apolipoprotein M; PON1, paraoxonase-1.

Haptoglobin alpha 2 chain (two spots)1.22 ± 0.58*0.42 ± 0.31
Haptoglobin beta chain (six spots)3.24 ± 1.02**0.87 ± 0.66
PON10.23 ± 0.21*0.86 ± 0.13
apo M0.40 ± 0.22*0.13 ± 0.08

Identification of proteins by MALDI-TOF MS analysis

Details of the nine differentially expressed proteins are summarized in Table 3. Of these proteins, only serum PON1 and alpha-ferrous-carbonmonoxy were downregulated (Fig. 2a, b).

Table 3.   Proteins differentially expressed in serum samples of patients with severe OSA
Area no.ProteinAccession no.Peptide matchSequence coverage (%)Observed PI/mass (Kd)Confirmation method
  1. The sequence coverage indicates the percentage of the calculated peptide weight that was identified in the mass fingerprint. The MS spectra of protein digests were searched for in the NCBInr database using the Profound database-searching program. MS, mass spectrometry.

  2. *Plasma map: SWISS-PROT 2D database (http://www.expasy.ch/ch2d/).

1Haptoglobin alpha 2 chain1006264A6236.6/42.3MS, MAP*
4146.2/42.3
2Haptoglobin beta chainP504177245.5/37.2MS, MAP
3Chain B, Alpha-Ferrous-Carbonmonoxy (T-state)1COHB10756.8/15.9MS, MAP
4Apolipoprotein MNP_0619747265.7/21.5MS
5Complement component 3 precursorNP_00005525176.0/188.5MS
6Serum paraoxonaseAAA601427235.0/37.9MS, MAP
7Complement factor BAAH0414312176.6/86.9MS
8Complement C4 precursorP010281276.7/194.3MS
9Complement component C4aAAB595371596.7/39.9MS, MAP
image

Figure 2.  Differential expressions of the identified nine proteins in patients with severe obstructive sleep apnoea (OSA) and controls. (a) Alteration of identified proteins between OSA and control subjects in areas 1, 2 and 3. (b) Alteration of identified proteins between OSA and control subjects in areas 4, 5 and 6. (c) Alterations of identified proteins between patients with OSA and control subjects in areas 7, 8 and 9.

Download figure to PowerPoint

Concentrations of haptoglobin, PON1 and apo M in serum

Haptoglobin levels were significantly upregulated in patients with OSA (Fig. 3a; mean ± SD: OSA versus control, 1.77 ± 0.46 versus 1.31 ± 0.47 mg mL−1, P < 0.001) and were significantly reduced after CPAP treatment (n = 12; 1.89 ± 0.25 versus 1.54 ± 0.43 mg mL−1, P < 0.01). PON1 levels were also significantly different between patients and controls (Fig. 3b; OSA versus controls, 207.4 ± 71.8 versus 254.9 ± 94.7 mmol min−1 mL−1, P < 0.05), but this difference disappeared after adjusting for cholesterol levels (OSA versus controls, 210.0 ± 72.0 versus 248.9 ± 91.7 mmol min−1 mL−1, P > 0.05). Moreover, no significant changes in these PON1 levels were observed after CPAP treatment (n = 12, before treatment versus after treatment, 207.5 ± 66.0 versus 213.8 ± 70.3 mmol min−1 mL−1, P > 0.05). Apo M expression was significantly upregulated in patients with OSA (Fig. 3c; OSA versus controls, 107.8 ± 8.3 versus 99.3 ± 5.6, P < 0.001), but its level was not significantly changed after CPAP (n = 12, before treatment versus after treatment, 105.5 ± 8.4 versus 104.2 ± 2.2, P > 0.05).

image

Figure 3.  Differences between the proteins levels of haptoglobin, paraoxonase-1 (PON1) and apo M in patients and controls. (a) Serum haptoglobin levels in patients and controls and changes in these levels after CPAP treatment. (b) Serum paraoxonase levels in patients and controls and changes in these levels after CPAP treatment. (c) Apo M levels by Western blotting in patients and controls and changes in these after CPAP treatment. OSA, obstructive sleep apnoea.

Download figure to PowerPoint

Stepwise multiple regression analysis findings of relations between the three proteins and various study variables

To further evaluate the relationship between protein levels and various variables, a stepwise multiple linear regression analysis was performed using haptoglobin, PON1 and apo M as dependent variables (Table 4). Haptoglobin and apo M levels were found to be independently related to AHI after controlling for confounders, whereas PON1 levels were not.

Table 4.   Stepwise multiple linear regression analysis of the relationships between haptoglobin and apo M levels, paraoxonase activity and various study variables
Independent variablesHaptoglobin (n = 74)Paraoxonase (n = 74)Apo M (n = 74)
βSE(β)βSE(β)βSE(β)
  1. AHI, apnoea-hypopnoea index; BMI, body mass index. The parameters included in the analysis were age, BMI, smoking status, creatinine, total cholesterol, HDL cholesterol and AHI. **< 0.01.

Constant1.310.0772.258.9123.09.7
BMI−0.020.032.686.580.680.51
Creatinine0.440.4945.088.21.96.8
Total cholesterol−0.0010.0020.170.39−0.020.03
HDL cholesterol−0.0040.013.89**1.440.050.14
AHI0.008**0.002−0.530.430.17**0.02
r20.220.160.40

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Conflict of interest
  9. Funding
  10. References

The association between OSA and vascular morbidity, including hypertension, CVD and stroke, is a major concern, as several studies have concluded that patients with OSA show elevated levels of biomarkers of CVD (Atwood, 2005; Ohga et al., 1999; Phillips et al., 1999; Tatsumi et al., 2005). However, the mechanism that links OSA and these biomarkers is not understood.

Proteomics is a potentially useful technology that allows changes in protein expression to be determined and 2-DE is primarily used for this purpose. However, the protein profiling of biological samples using proteomic approaches is challenging, regardless of the method chosen. For example, the abundance and diversity of post-translational modifications substantially complicates serum proteome analysis (Anderson and Anderson, 2002), and the removal of albumin from serum may also remove low abundance proteins, such as cytokines and others that might predict clinical outcome (Granger et al., 2005). Accordingly, we were unable to examine changes in cytokine and adhesion molecule levels in the present study. Even though serum is similar to plasma, fibrinogen is removed to form the clot, and limited series of other protein changes (mainly proteolytic cleavages) take place (Anderson and Anderson, 2002). Accordingly, the use of serum samples for 2-DE may have affected observed protein expressions in the present study. Nevertheless, comprehensive examinations of differences in protein expression profiles in disease and control samples offer opportunities to identify key disease-related molecules (Hortin et al., 2006).

In the present study, we studied for the first time, proteins differentially expressed in the serum of patients with severe OSA and normal controls. Nine identified proteins can be categorized as acute-phase proteins (haptoglobin), anti-oxidant proteins (PON1), apolipoproteins (apo M) and complement components (complement component 3 precursor, complement factor B, complement C4 precursor and complement C4a). Furthermore, we examined the concentrations of haptoglobin, PON1 and apo M in 40 patients with OSA and 34 controls to determine whether their differential expressions are related to the presence of OSA. The other six proteins are the subject of on-going study. The complement system is thought to play a major role in initiating inflammatory events, especially those that occur after ischemia and reperfusion (Arumugam et al., 2006). Furthermore, the complement system activates neutrophil adhesion to the endothelium. Accordingly, our findings suggest that further studies are required to determine the relation between the complement system and inflammation in patients with OSA.

One of the main findings of the present study is that serum haptoglobin, a known acute-phase protein (Langlois and Delanghe, 1996), was elevated in patients with OSA. Furthermore, haptoglobin levels were significantly reduced after CPAP in patients with OSA (P < 0.01), and serum haptoglobin levels were found to be significantly correlated with AHI by using multiple regression analysis after controlling for confounding factors (P < 0.01). In addition, haptoglobin is known to play an important role in protection against heme-driven oxidative stress (Langlois and Delanghe, 1996) and to participate in the inhibition of neutrophil chemotactic activity in vivo (Wagner et al., 1996). Several studies have also reported that increased serum haptoglobin levels during inflammatory and ischemic conditions are a potential marker of arterial pathology and that haptoglobin promotes growth of collateral vessels (Cid et al., 1993). Moreover, epidemiologic studies have suggested that elevated haptoglobin levels are significantly associated with increased incidences of myocardial infarction and stroke (Engström et al., 2002, 2004). Patients with OSA undergo repeated episodes of hypoxia, and the reoxygenation/reperfusion phase is believed to result in ROS (reactive oxygen species) production and oxidative stress (Lavie, 2003; Suzuki et al., 2006). Moreover, it has been demonstrated that a haptoglobin polymorphism is a risk factor for CVD in patients with OSA (Lavie et al., 2003). These findings indicate that a further study is required on the association between OSA and haptoglobin phenotypes in a statistically meaningful population.

PON1 level has been extensively studied in the toxicology field (Mackness et al., 1998). PON1 has been shown to protect both LDL and HDL against lipid peroxidation, and its activity has been reported to be reduced in the presence of coronary artery disease (Durrington et al., 2004). Furthermore, it has been demonstrated that PON1 reduces the adhesion of monocytes to endothelial cells (Ahmed et al., 2003). Recently, Lavie et al. (2004) reported that PON1 activity is lower in patients with OSA with cardiovascular disease CVD and that is significantly and negatively correlated with the respiratory disturbance index. Similarly, our study supports the notion that PON1 level is diminished in patients with OSA. In the present study, PON1 level was lower in patients with OSA than in controls. However, the significance of the association between PON1 and AHI was lost during multivariate regression analysis. On the other hand, we found that PON1 and HDL cholesterol levels were significantly correlated, after controlling for confounders. The probable reasons for this apparent discrepancy between our findings and those of Lavie et al. are that subjects included in the present study were free of chronic diseases, our sample size was too small, and that different selection criteria applied.

Apo M is a newly characterized human apolipoprotein that is believed to associate with HDL in plasma. It has been demonstrated that apo M is exclusively expressed in renal tubular cells and in hepatocytes (Zhang et al., 2003). Several researchers have suggested that apo M is involved in host defence response, because the apo M gene is located in the histocompatibility complex III region on chromosome 6. Many genes in this region are related to immune response, and the apo M gene is situated near the TNF-α and lymphotoxin genes (Luo et al., 2004). However, the pathophysiological function is not understood. Previous studies have found that platelet activating factor receptor (PAF-R) enhances apo M secretion and expression in a dose-dependent manner in HepG2 cells, whereas lexipafan, which is a PAF-R antagonist, inhibits apo M expression (Xu et al., 2002). In a clinical study, Xu et al. observed that apo M levels are significantly and positively correlated with leptin, BMI and fasting insulin levels. Furthermore, correlations between apo M and cholesterol levels and between apoM and leptin levels remained significant even after adjusting for the influence of BMI (Xu et al., 2004). In the present study, apo M was found to be independently and positively associated with AHI after controlling for the effects of BMI and other confounders (P < 0.01). However, no study has been undertaken as yet to establish the nature of the relationship between OSA and apo M. Further studies are needed to establish the natures of the associations between leptin and apo M and the pathophysiology of OSA.

Summarizing, despite limitation associated with the non-inclusion of patients with mild OSA, and the inclusion of only 12 subjects in the follow-up analysis, the present study demonstrates for the first time, using a proteomics approach, that nine proteins are differentially expressed in the serum of patients with severe OSA. Of these proteins, haptoglobin, paraoxonase and apoM were quantified by using ELISA, kinetic assays and Western blotting in 74 subjects. Furthermore, both haptoglobin and apo M were found to be independently related to AHI. We suggest that further studies are required to examine associations between the nine identified proteins and pathophysiological aspects of OSA in a larger population.

Acknowledgement

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Conflict of interest
  9. Funding
  10. References

The authors extend their thanks to Dr Lee for his constructive advice.

Funding

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Conflict of interest
  9. Funding
  10. References

This study was supported by a grant (K0507801) from the Research Center for Korean University Medical Science.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgement
  8. Conflict of interest
  9. Funding
  10. References
  • Ahmed, Z., Babaei, S., Maguire, G. F., Draganov, D., Kuksis, A., La Du, B. N. and Connelly, P. W. Paraoxonase-1 reduces monocyte chemotaxis and adhesion to endothelial cells due to oxidation of palmitoyl, linoleoyl glycerophosphorylcholine. Cardiovasc. Res., 2003, 57: 225231.
  • American Sleep Disorders Association. EEG arousals: scoring rules and examples: a preliminary report from the sleep disorders atlas task force of the American Sleep Disorders Association. Sleep, 1992, 15: 173184.
  • Anderson, N. L. and Anderson, N. G. The human plasma proteome: history, character, and diagnostic prospects. Mol. Cell Proteomics, 2002, 1: 845867.
  • Arumugam, T. V., Magnus, T., Woodruff, T. M., Proctor, L. M., Shiels, I. A. and Taylor, S. M. Complement mediators in ischemia–reperfusion injury. Clin. Chim. Acta, 2006, 374: 3345.
  • Atwood, C. W. Sleep-related hypoventilation: the evolving role of leptin. Chest, 2005, 128: 10791081.
  • Calvo, K. R., Liotta, L. A. and Petricoin, E. F. Clinical proteomics: from biomarker discovery and cell signaling profiles to individualized personal therapy. Biosci. Rep., 2005, 25: 107125.
  • Charlton-Menys, V., Liu, Y. and Durrington, P. N. Semiautomated method for determination of serum paraoxonase activity using paraoxon as substrate. Clin. Chem., 2006, 52: 453457.
  • Cho, N., Joo, S., Kim, J., Abbott, R. D., Kim, J., Kimm, K. and Shin, C. Relation of habitual snoring with components of metabolic syndrome in Korean adults. Diabetes Res. Clin. Pract., 2006, 71: 256263.
  • Cid, M. C., Grant, D. S., Hoffman, G. S., Auerbach, R., Fauci, A. S. and Kleinman, H. K. Identification of haptoglobin as an angiogenic factor in sera from patients with systemic vasculitis. J. Clin. Invest., 1993, 91: 977985.
  • Duncan, M. W. and Hunsucker, S. W. Proteomics as a tool for clinically relevant biomarker discovery and validation. Exp. Biol. Med. (Maywood), 2005, 230: 808817.
  • Durrington, P. N., Mackness, B. and Mackness, M. I. Paraoxonase polymorphisms and coronary heart disease. Lancet, 2004, 364: 579580. Author reply 580.
  • Engström, G., Lind, P., Hedblad, B., Stavenow, L., Janzon, L. and Lindgärde, F. Effects of cholesterol and inflammation-sensitive plasma proteins on incidence of myocardial infarction and stroke in men. Circulation, 2002, 105: 26322637.
  • Engström, G., Hedblad, B., Stavenow, L., Tydén, P., Lind, P., Janzon, L. and Lindgärde, F. Fatality of future coronary events is related to inflammation-sensitive plasma proteins: a population-based prospective cohort study. Circulation, 2004, 110: 2731.
  • Granger, J., Siddiqui, J., Copeland, S. and Remick, D. Albumin depletion of human plasma also removes low abundance proteins including the cytokines. Proteomics, 2005, 5: 47134718.
  • Hanash, S. M., Madoz-Gurpide, J. and Misek, D. E. Identification of novel targets for cancer therapy using expression proteomics. Leukemia, 2002, 16: 478485.
  • Hortin, G. L., Jortani, S. A., Ritchie, J. C. Jr, Valdes, R. Jr and Chan, D. W. Proteomics: a new diagnostic frontier. Clin. Chem., 2006, 52: 12181222.
  • Jungblut, P. R., Zimny-Arndt, U., Zeindl-Eberhart, E., Stulik, J., Koupilova, K., Pleissner, K. P., Otto, A., Müller, E. C., Sokolowska-Köhler, W., Grabher, G. and Stöffler, G. Proteomics in human disease: cancer, heart and infectious diseases. Electrophoresis, 1999, 20: 21002110.
  • Kim, J., In, K., Kim, J., You, S., Kang, K., Shim, J., Lee, S., Lee, J., Lee, S., Park, C. and Shin, C. Prevalence of sleep-disordered breathing in middle-aged Korean men and women. Am. J. Respir. Crit. Care Med., 2004, 170: 11081113.
  • Langlois, M. R. and Delanghe, J. R. Biological and clinical significance of haptoglobin polymorphism in humans. Clin. Chem., 1996, 42: 15891600.
  • Lavie, L. Obstructive sleep apnoea syndrome – an oxidative stress disorder. Sleep Med. Rev., 2003, 7: 3551.
  • Lavie, L., Lotan, R., Hochberg, I., Herer, P., Lavie, P. and Levy, A. P. Haptoglobin polymorphism is a risk factor for cardiovascular disease in patients with obstructive sleep apnea syndrome. Sleep, 2003, 26: 592595.
  • Lavie, L., Vishnevsky, A. and Lavie, P. Evidence for lipid peroxidation in obstructive sleep apnea. Sleep, 2004, 27: 123128.
  • Luo, G., Zhang, X., Nilsson-Ehle, P. and Xu, N. Apolipoprotein M. Lipids Health Dis., 2004, 3: 21.
  • Mackness, B., Durrington, P. N. and Mackness, M. I. Human serum paraoxonase. Gen. Pharmacol., 1998, 31: 329336.
  • Ohga, E., Nagase, T., Tomita, T., Teramoto, S., Matsuse, T., Katayama, H. and Ouchi, Y. Increased levels of circulating ICAM-1, VCAM-1, and I-selectin in obstructive sleep apnea syndrome. J. Appl. Physiol., 1999, 87: 1014.
  • Phillips, B. G., Narkiewicz, K., Pesek, C. A., Haynes, W. G., Dyken, M. E. and Somers, V. K. Effects of obstructive sleep apnea on endothelin-1 and blood pressure. J. Hypertens., 1999, 17: 6166.
  • Polotsky, V. Y. and O’Donell, C. P. Genomics of sleep-disordered Breathing. Proc. Am. Thorac. Soc., 2007, 4: 121126.
  • Punjabi, N. M., Shahar, E., Redline, S., Gottlieb, D. J., Givelber, R. and Resnick, H. E. Sleep-disordered breathing, glucose intolerance, and insulin resistance: the Sleep Heart Health Study. Am. J. Epidemiol., 2004, 160: 521530.
  • Rechtschaffen, A. and Kales, A. A Manual of Standardized Terminology, Techniques and Scoring System for Sleep Stages of Human Subjects. NIH Publication No. 204. US Government Printing Office, Washington, DC, 1968.
  • Shahar, E., Whitney, C. W., Redline, S., Lee, E. T., Newman, A. B., Javier Nieto, F., O’Connor, G. T., Boland, L. L., Schwartz, J. E. and Samet, J. M. Sleep-disordered breathing and cardiovascular disease: cross-sectional results of the sleep heart health study. Am. J. Respir. Crit. Care Med., 2001, 163: 1925.
  • Shevchenko, A., Wilm, M., Vorm, O. and Mann, M. Mass spectrometric sequencing of proteins silver-stained polyacrylamide gels. Anal. Chem., 1996, 68: 850858.
  • Shin, C., Kim, J., Kim, J., Lee, S., Shim, J., In, K., Kang, K., Yoo, S., Cho, N., Kimm, K. and Joo, S. Association of habitual snoring with glucose and insulin metabolism in nonobese Korean adult men. Am. J. Respir. Crit. Care Med., 2005, 171: 287291.
  • Suzuki, Y. J., Jain, V., Park, A. M. and Day, R. M. Oxidative stress and oxidant signaling in obstructive sleep apnea and associated cardiovascular diseases. Free Radic. Biol. Med., 2006, 40: 16831692.
  • Tatsumi, K., Kasahara, Y., Kurosu, K., Tanabe, N., Takiguchi, Y. and Kuriyama, T. Sleep oxygen desaturation and circulating leptin in obstructive sleep apnea–hypopnea syndrome. Chest, 2005, 127: 716721.
  • Wagner, L., Gessl, A., Parzer, S. B., Base, W., Waldhäusl, W. and Pasternack, M. S. Haptoglobin phenotyping by newly developed monoclonal antibodies. Demonstration of haptoglobin uptake into peripheral blood neutrophils and monocytes. J. Immunol., 1996, 156: 19891996.
  • Westfall, P. and Young, S. Resampling-based Multiple Testing: Examples and Methods for P-value Adjustment. John Wiley & Sons, London, 1993.
  • Xu, N., Zhang, X. Y., Dong, X., Ekström, U., Ye, Q. and Nilsson-Ehle, P. Effects of platelet-activating factor, tumor necrosis factor, and interleukin-1alpha on the expression of apolipoprotein M in HepG2 cells. Biochem. Biophys. Res. Commun., 2002, 292: 944950.
  • Xu, N., Nilsson-Ehle, P. and Ahren, B. Correlation of apolipoprotein M with leptin and cholesterol in normal and obese subjects. J. Nutr. Biochem., 2004, 15: 579582.
  • Yaggi, H. K., Concato, J., Kernan, W. N., Lichtman, J. H., Brass, L. M. and Mohsenin, V. Obstructive sleep apnea as a risk factor for stroke and death. N. Engl. J. Med., 2005, 353: 20342041.
  • Yokoe, T., Minoguchi, K., Matsuo, H., Oda, N., Minoguchi, H., Yoshino, G., Hirano, T. and Adachi, M. Elevated levels of C-reactive protein and interleukin-6 in patients with obstructive sleep apnea syndrome are decreased by nasal continuous positive airway pressure. Circulation, 2003, 107: 11291134.
  • Young, T., Peppard, P. E. and Gottlieb, D. J. Epidemiology of obstructive sleep apnea: a population health perspective. Am. J. Respir. Crit. Care Med., 2002, 165: 12171239.
  • Zhang, X. Y., Dong, X., Zheng, L., Luo, G. H., Liu, Y. H., Ekström, U., Nilsson-Ehle, P., Ye, Q. and Xu, N. Specific tissue expression and cellular localization of human apolipoprotein M as determined by in situ hybridization. Acta Histochem., 2003, 105: 6772.