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Original Research: Sleep Disorders |

Independent Association Between Nocturnal Intermittent Hypoxemia and Metabolic DyslipidemiaMetabolic Dyslipidemia in Obstructive Sleep Apnea FREE TO VIEW

Wojciech Trzepizur, MD; Marc Le Vaillant, PhD; Nicole Meslier, MD; Thierry Pigeanne, MD; Philippe Masson, MD; Marie P. Humeau, MD; Acya Bizieux-Thaminy, MD; François Goupil, MD; Sylvaine Chollet, MD; Pierre H. Ducluzeau, MD, PhD; Frédéric Gagnadoux, MD, PhD; for the Institut de Recherche en Santé Respiratoire des Pays de la Loire (IRSR) Sleep Cohort Group
Author and Funding Information

From the LUNAM University (Drs Trzepizur, Meslier, Ducluzeau, and Gagnadoux), Angers, France; Department of Respiratory Diseases (Drs Trzepizur, Meslier, Ducluzeau, and Gagnadoux) and Department of Endocrinology-Diabetology-Nutrition (Dr Ducluzeau), Angers University Hospital, Angers, France; INSERM U1063 (Drs Trzepizur, Meslier, and Gagnadoux), Angers, France; CERMES (Dr Le Vaillant), CNRS UMR8211-INSERM U988-EHESS, Villejuif, France; Department of Respiratory Diseases (Dr Pigeanne), Pôle santé des Olonnes, Olonnes sur Mer, France; Department of Respiratory Diseases (Dr Masson), Cholet Hospital, Cholet, France; Department of Respiratory Diseases (Dr Humeau), Nouvelles Cliniques Nantaises, Nantes, France; Department of Respiratory Diseases (Dr Bizieux-Thaminy), La Roche sur Yon Hospital, La Roche sur Yon, France; Department of Respiratory Diseases (Dr Goupil), Le Mans Hospital, Le Mans, France; and Department of Respiratory Diseases (Dr Chollet), Nantes University Hospital, Nantes, France.

Correspondence to: Frédéric Gagnadoux, MD, PhD, Université d’Angers, CHU Angers, Département de Pneumologie, 4 rue Larrey, 49033 Angers Cedex, France; e-mail: frgagnadoux@chu-angers.fr


Reproduction of this article is prohibited without written permission from the American College of Chest Physicians. See online for more details.


Chest. 2013;143(6):1584-1589. doi:10.1378/chest.12-1652
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Background:  There is growing evidence from animal models that intermittent hypoxemia (IH) may induce dyslipidemia. Altered lipid metabolism may contribute to the increased cardiovascular risk observed in obstructive sleep apnea (OSA). In this multisite, cross-sectional study, we tested the hypothesis that there is an independent association between nocturnal IH and dyslipidemia in OSA.

Methods:  Fasting serum lipid levels were measured in 2,081 patients (638 women) undergoing nocturnal recording for clinical suspicion of OSA. Multivariate regression analyses were performed to evaluate the independent associations between oxygen desaturation index (ODI) and lipid profile after adjustment for potential confounders, including components of the metabolic syndrome (MS) or the MS itself. Adjusted OR for metabolic dyslipidemia (triglycerides [TG] ≥ 150 mg/dL and high-density lipoprotein cholesterol [HDL-C] ≤ 50 mg/dL for women and ≤ 40 mg/dL for men) according to quartiles of ODI were determined by logistic regression.

Results:  Total cholesterol and low-density lipoprotein cholesterol were not associated with ODI. In contrast, nocturnal IH and OSA severity were associated with higher TG levels and lower HDL-C levels after adjustment for confounding factors. The association between ODI and TG and HDL-C levels was independent of the MS. Adjusted OR (95% CIs) for metabolic dyslipidemia were 1 (reference), 1.56 (1.24-1.96), 1.72 (1.29-2.29), and 1.93 (1.55-2.41) for ODI ≤ 7, > 7 to ≤ 18, > 18 to ≤ 38, and > 38, respectively (P < .0001 for linear trend).

Conclusions:  Nocturnal IH is independently associated with metabolic dyslipidemia, which may predispose patients with OSA to a higher risk of cardiovascular disease.

Figures in this Article

Obstructive sleep apnea (OSA) is a highly prevalent disease characterized by recurrent episodes of partial or complete obstruction of the upper airways during sleep, leading to repeated falls in oxygen saturation. OSA is recognized as an independent risk factor for cardiovascular (CV) diseases,1 including stroke,2 coronary heart disease, and heart failure.3 There is strong evidence that nocturnal oxygen desaturation plays a key role in the pathophysiology of CV complications in OSA.4

Dyslipidemia is a well-known risk factor for the development and progression of CV diseases.57 In addition to the well-characterized proatherosclerotic effect of high low-density lipoprotein cholesterol (LDL-C) concentrations, there is growing evidence in support of an independent association between incident CV diseases and metabolic dyslipidemia (MD) characterized by a combination of increased triglycerides (TG) levels and low high-density lipoprotein cholesterol (HDL-C) levels.810

Evidence from animal models mimicking sleep-disordered breathing (SDB) showed that intermittent hypoxemia (IH) causes hyperlipidemia and upregulation of genes of lipid biosynthesis in the liver.11,12 IH-induced dyslipidemia may contribute to the increased CV risk observed in OSA. However, previous studies have not provided definitive evidence in support of an independent association between nocturnal IH and altered lipid metabolism.13 This multisite, cross-sectional study evaluated the independent association between nocturnal IH and dyslipidemia in OSA.

Setting

This study was approved by the University of Angers ethics committee (Comité d’Ethique du Centre Hospitalier Universitaire d’Angers, No. 2007/17; Comité Consultative sur le Traitement de l’Information en matière de Recherche dans le domaine de la Santé, 07.207bis), and patients gave written informed consent. Between May 15, 2007, and April 4, 2012, fasting serum lipid levels, including total cholesterol (TC), HDL-C, and TG, were measured in 2,081 patients aged ≥ 18 years (638 women) undergoing overnight polysomnography (PSG) (n = 755) or overnight respiratory recording (n = 1,326) for clinical suspicion of OSA at seven sites from the west of France collaborating in the Institut de Recherche en Santé Respiratoire des Pays de la Loire (IRSR) Sleep Cohort study.14,15 See Table 1 for the number of patients recruited by each study site. LDL-C was calculated using the Friedman formula.

Table Graphic Jump Location
Table 1 —Number of Patients Recruited by Each Study Site Collaborating in the Institut de Recherche en Santé Respiratoire des Pays de la Loire (IRSR) Sleep Cohort
Measurements, Questionnaires, and Sleep Studies

Each patient enrolled in the IRSR Sleep Cohort study completed surveys for anthropomorphic data, smoking habits, alcohol consumption, and medical history. Abdominal obesity was defined as a waist circumference of ≥ 88 cm in women and ≥ 102 cm in men.16 BP was measured by means of a periodically calibrated mercury sphygmomanometer after at least 5 min of rest in the sitting position. The mean of three measurements was recorded. Hypertension was defined by systolic BP ≥ 130 mm Hg or diastolic BP ≥ 85 mm Hg or the presence of antihypertensive treatment. Patients with fasting blood glucose > 126 mg/dL or glycated hemoglobin ≥ 6.5% or those receiving antidiabetic treatment were considered to have diabetes.15,17 The presence of CV morbidity was defined by at least one of the following criteria: ischemic heart disease, cardiac arrhythmia, congestive heart failure, or stroke. Excessive daytime sleepiness was evaluated by the Epworth Sleepiness Scale.18 The presence of the metabolic syndrome (MS) was analyzed according to National Cholesterol Education Program Adult Treatment Panel III clinical criteria.16

As previously described,14,15 overnight PSG was performed, with recording of the following channels: EEG, electrooculogram, chin electromyogram, arterial oxygen saturation (Sao2) (finger oximetry), nasal-oral airflow (pressure cannula), ECG, chest and abdominal wall motion (piezoelectrodes), bilateral tibialis electromyogram, and body position. Overnight respiratory recordings included Sao2, nasal-oral airflow, chest and abdominal wall motion, and body position. Respiratory events were scored manually using recommended criteria.19 Apnea was defined as cessation of airflow for ≥ 10 s. Hypopnea was defined as a ≥ 50% reduction of airflow or a < 50% reduction of airflow accompanied by a ≥ 3% decrease in Sao2 (or followed by an arousal when OSA was diagnosed through overnight PSG). For both PSG and overnight respiratory recordings, the apnea-hypopnea index (AHI) and the 3% oxygen desaturation index (ODI) were defined by the number of events per hour of recording. The percentage of recording time with Sao2 < 90% was also calculated for PSG and overnight respiratory recordings.

Statistical Analysis

All statistical analyses were performed with SAS/STAT package 2002-2003 (SAS Institute Inc) software. Characteristics of the study population were determined according to quartiles of ODI using standard methods to calculate mean values and SDs. P values for linear trends across ODI categories were calculated by simple linear regression for continuous variables and by the Cochran-Armitage trend test for dichotomous variables.

The primary outcome variables were fasting serum lipid levels, including TC, HDL-C, LDL-C, and TG. The primary independent variable was ODI. Multivariate regression analyses were performed to characterize the independent associations between ODI and fasting serum lipid levels. The independent associations between serum lipid levels and AHI, recording time with Sao2 < 90%, and microarousal index (MAI) (n = 755) were also evaluated. To adjust for potential confounders, the following covariates were entered in two consecutive models: Model 1 included age, sex, BMI, smoking habits, alcohol consumption, abdominal obesity, CV morbidity, hypertension, diabetes, use of lipid-lowering drugs, study site, and model 2 included age, sex, smoking habits, alcohol consumption, CV morbidity, study site, and the presence or absence of the MS. Adjustment for study site was performed using a generalized estimating equation model.20 MD was defined by a combination of increased TG levels (≥ 150 mg/dL) and low HDL-C levels (≤ 50 mg/dL for women and ≤ 40 mg/dL for men).8 A dichotomous logistic regression procedure was used to model the associations between quartiles of ODI and the ORs and 95% CIs for having MD after adjustment for confounding factors. A two-tailed P < .05 was considered significant.

As shown in Table 2, patients with elevated ODI were more likely to be older, male, and daily alcohol consumers; to use lipid-lowering drugs, to have higher Epworth Sleepiness Scale scores and BMI; and to have abdominal obesity, hypertension, diabetes, a history of CV diseases, and the MS. A positive dose-response relationship was observed between ODI and serum TG levels. A negative dose-response relationship was observed between ODI and TC, LDL-C, and HDL-C. The percentage of patients with MD increased with quartiles of ODI from 9.2% for ODI ≤ 7 to 22.1% for ODI > 38.

Table Graphic Jump Location
Table 2 —Characteristics of the Study Participants According to Quartiles of ODI

Data are presented as mean ± SD or %. HDL-C = high-density lipoprotein cholesterol; LDL-C = low-density lipoprotein cholesterol; ODI = oxygen desaturation index; Sao2 = arterial oxygen saturation.

a 

Tested by simple linear regression for continuous variables and by the Cochran-Armitage trend test for dichotomous variables.

According to model 1, multiple linear regressions showed that ODI was independently associated with HDL-C and TG but not with TC and LDL-C (Table 3). Increasing ODI was associated with higher mean serum TG levels and lower mean serum HDL-C levels after adjustment for confounding variables (Fig 1). The increase in standardized means of TG level was more marked between the first two quartiles of ODI than across higher quartiles. A significant positive linear trend was observed for the odds of MD with increasing ODI after adjusting for confounding variables (Table 4). The recording time with Sao2 < 90% was associated with TG (β = 0.24, P = .0082) and HDL-C (β = −0.07, P = .0131) levels. The AHI was associated with TG and HDL-C levels both in the whole population (TG, β = 0.38, P < .0001; HDL-C, β = −0.04, P < .0001) and in the patients with ODI ≤ 7 (n = 519; TG, β = 0.87, P < .0001; HDL-C, β = −0.10, P < .0001). The MAI (n = 755) was also independently associated with TG level (β = 0.47, P < .0015) but not with HDL-C level (β = −0.05, P = .1014). According to model 2, ODI was associated with TG (β = 0.21, P = .0152) and HDL-C (β = −0.06, P < .0001) levels after adjustment for the MS.

Table Graphic Jump Location
Table 3 —Multiple Linear Regressions for Fasting Blood Lipids

Data are presented as β (SE [β]). See Table 2 legend for expansion of abbreviations.

a 

P < .001.

b 

P < .05.

c 

P < .01.

Table Graphic Jump Location
Table 4 —Adjusted ORs for Metabolic Dyslipidemia According to ODI Categories

ORs were adjusted for age, sex, BMI, smoking habits, alcohol consumption, abdominal obesity, cardiovascular morbidity, hypertension, diabetes, use of lipid-lowering drugs, and study site. See Table 2 legend for expansion of abbreviation.

a 

Tested by the Cochran-Armitage trend test.

Figure Jump LinkFigure 1. Adjusted mean values of fasting triglyceride and HDL cholesterol levels according to quartiles of ODI. A, Fasting triglycerides. B, HDL cholesterol. Data were adjusted for age, sex, BMI, smoking habits, alcohol consumption, abdominal obesity, cardiovascular morbidity, hypertension, diabetes, use of lipid-lowering drugs, and study site. HDL = high-density lipoprotein; ODI = oxygen desaturation index.Grahic Jump Location

The association between LDL-C and coronary heart disease has been clearly established in observational studies and clinical trials. In accordance with previous investigations,13 the present large cross-sectional study shows that TC and LDL-C levels are not associated with nocturnal IH. The focus on MD, characterized by a combination of high TG and low HDL-C levels, has increased regarding CV risk assessment. A population-based study of 25,663 men and women aged 45 to 79 years demonstrated that MD is an independent CV risk factor.8 The increased risk remained significant after adjustment for LDL-C. In the present study, we demonstrate that patients with OSA and more severe nocturnal IH are at higher risk of MD after adjustment for confounding factors.

The ability to generalize previous studies investigating the association between OSA and lipid profile in the clinical setting may be questioned because of a number of methodologic limitations, including small sample size and lack of adjustment for numerous confounders. In one review,13 only three of 13 cross-sectional studies (including two large population-based studies) found that increasing SDB severity was associated with higher TG and lower HDL-C values. More recently, a large study in obese volunteers found that an AHI > 15 and the time with Sao2 < 90% were independently associated with TG but not with HDL-C level.21 Although associations between SDB and either high TG or low HDL-C level had been previously observed,13,21 the link between nocturnal IH and the combination of high TG and low HDL-C levels defining MD has remained largely unknown. The present findings provide strong support for an independent association between nocturnal IH and MD in real-life conditions. The present multisite study can be assumed to describe a typical pattern of OSA because it included a large sample of patients with a wide range of disease severity. A recent study from the IRSR Sleep Cohort Group15 demonstrated that increasing severity of nocturnal IH in patients with OSA and without diabetes was independently associated with a higher risk of hemoglobin A1C values > 6.0%, which are known to predispose to CV disease.22 All together, these findings suggest that nocturnal IH in OSA may contribute to the development of lipid and glucose metabolic disorders associated with a risk of poor CV outcomes.

A recent study in patients with OSA with (n = 28) and without (n = 30) the MS concluded that the MS was the only independent predictor of LDL-C particle size and subclasses, whereas OSA severity did not contribute independently to alterations of LDL-C phenotype.23 It would have been impossible to assess LDL-C phenotype in the large sample of the present study, but we also found no link between LDL-C levels and nocturnal IH. In a report from Barceló et al,16 free fatty acid (FFA) levels were significantly associated with SDB after adjustment for the MS. Measurement of FFA levels was not performed in the present study, but an association was demonstrated between TG levels and nocturnal IH independently of the MS. FFA levels were recently demonstrated to be associated with serum TG level and insulin sensitivity independently of adiposity.24 By promoting insulin resistance,25,26 nocturnal IH may contribute to increases in both TG and FFA levels.

Data from animal models suggest that IH may disrupt lipid metabolism by increasing adipose tissue lipolysis and FFA flux to the liver by upregulating hepatic TG biosynthesis and lipoprotein secretion and suppressing lipoprotein clearance.27 The present findings that ODI is independently related to MD provide additional evidence that nocturnal IH is involved in the relationship between OSA and impaired lipid metabolism. Interestingly, the increase in TG values was more marked between the first two quartiles of ODI than across the higher quartiles of ODI. Furthermore, a highly significant correlation was observed between AHI and TG level in patients with low ODI (≤ 7), suggesting that sleep fragmentation could also contribute to lipid metabolism impairment. This hypothesis was supported by an independent association between MAI and TG level. It could also be hypothesized that the influence of nocturnal IH on TG levels is less marked in patients with high ODI because of more severe comorbid conditions also influencing lipid metabolism.

We acknowledge a number of limitations of the present study. The cross-sectional design does not allow for conclusions to be drawn regarding the causal pathway of these associations. Robust data from randomized controlled trials are still needed to investigate a causal relationship between OSA and dyslipidemia. The largest study from Robinson et al28 of 220 patients with OSA demonstrated only a trend toward a significant fall in TC level with CPAP (P = .06) compared with the control group. Kohler et al29 observed no change in lipid profiles after CPAP withdrawal for 2 weeks. In contrast, a crossover trial of 29 patients with moderate to severe OSA demonstrated an improvement in postprandial TG and TC levels after 2 months of CPAP (vs sham CPAP).30 Sharma et al31 demonstrated a significant decrease in TC, non-HDL-C, LDL-C, and TG levels after CPAP treatment (vs sham CPAP) for 3 months in 86 patients with moderate to severe OSA, of whom 87% had the MS. However, inconsistent with most previous randomized trials, CPAP was also associated with a reduction in BMI and visceral fat, which may have contributed to the improvement of lipid metabolism.31,32 We also acknowledge that sleep recording analysis and serum lipid assays were performed locally in the present study. However, adjustment for study site in the regression model did not modify the magnitude of the association between nocturnal IH and lipid profile. Therefore, we do not believe that differences in serum lipid measurement or sleep recording analysis between sites could have influenced the results.

In conclusion, nocturnal IH is independently associated with MD. This association may predispose patients with OSA to a higher risk of CV diseases.

Author contributions: Dr Gagnadoux had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Dr Trzepizur: contributed to the data research, discussion, writing of the manuscript, and review and editing of the manuscript.

Dr Le Vaillant: contributed to the data research, discussion, writing of the manuscript, and review and editing of the manuscript.

Dr Meslier: contributed to the data research, discussion, writing of the manuscript, and review and editing of the manuscript.

Dr Pigeanne: contributed to the data research, discussion, and review and editing of the manuscript.

Dr Masson: contributed to the data research, discussion, and review and editing of the manuscript.

Dr Humeau: contributed to the data research, discussion, and review and editing of the manuscript.

Dr Bizieux-Thaminy: contributed to the data research, discussion, and review and editing of the manuscript.

Dr Goupil: contributed to the data research, discussion, and review and editing of the manuscript.

Dr Chollet: contributed to the data research, discussion, and review and editing of the manuscript.

Dr Ducluzeau: contributed to the data research, discussion, and review and editing of the manuscript.

Dr Gagnadoux: contributed to the data research, discussion, writing of the manuscript, and review and editing of the manuscript.

Financial/nonfinancial disclosures: The authors have reported to CHEST that no potential conflicts of interest exist with any companies/organizations whose products or services may be discussed in this article.

Other contributions: The members of the IRSR Sleep Cohort Group are as follows: Centre Hospitalier Universitaire, Angers (Frédéric Gagnadoux, MD, PhD; Nicole Meslier, MD; and Christine Person, MD); Centre Hospitalier, Le Mans (François Goupil, MD; Isabelle Simon, MD; and Olivier Molinier, MD); Centre Hospitalier, La Roche sur Yon (Acya Bizieux-Thaminy, MD; Philippe Breton, MD; and Kamel Berkani, MD); Pôle santé des Olonnes, Olonnes sur Mer (Thierry Pigeanne, MD); Centre Hospitalier Universitaire, Nantes (Sylvaine Chollet, MD; Sandrine Jaffre, MD; Frédéric Corne, MD; Marianne Boeffard, MD; and Béatrice Nogues, MD); Nouvelles Cliniques Nantaises (Marie P. Humeau, MD; Marc Normand de la Tranchade, MD; and Charlotte Kierzkowski, MD); ALTADIR (Jean L. Racineux, MD, and Christelle Gosselin, MSc); and CERMES, CNRS UMR8211-INSERM U988-EHESS, Site CNRS (Marc Le Vaillant, PhD, and Nathalie Pelletier-Fleury, MD, PhD).

AHI

apnea-hypopnea index

CV

cardiovascular

FFA

free fatty acid

HDL-C

high-density lipoprotein cholesterol

IH

intermittent hypoxemia

IRSR

Institut de Recherche en Santé Respiratoire des Pays de la Loire

LDL-C

low-density lipoprotein cholesterol

MAI

microarousal index

MD

metabolic dyslipidemia

MS

metabolic syndrome

ODI

oxygen desaturation index

OSA

obstructive sleep apnea

PSG

polysomnography

Sao2

arterial oxygen saturation

SDB

sleep-disordered breathing

TC

total cholesterol

TG

triglycerides

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Figures

Figure Jump LinkFigure 1. Adjusted mean values of fasting triglyceride and HDL cholesterol levels according to quartiles of ODI. A, Fasting triglycerides. B, HDL cholesterol. Data were adjusted for age, sex, BMI, smoking habits, alcohol consumption, abdominal obesity, cardiovascular morbidity, hypertension, diabetes, use of lipid-lowering drugs, and study site. HDL = high-density lipoprotein; ODI = oxygen desaturation index.Grahic Jump Location

Tables

Table Graphic Jump Location
Table 1 —Number of Patients Recruited by Each Study Site Collaborating in the Institut de Recherche en Santé Respiratoire des Pays de la Loire (IRSR) Sleep Cohort
Table Graphic Jump Location
Table 2 —Characteristics of the Study Participants According to Quartiles of ODI

Data are presented as mean ± SD or %. HDL-C = high-density lipoprotein cholesterol; LDL-C = low-density lipoprotein cholesterol; ODI = oxygen desaturation index; Sao2 = arterial oxygen saturation.

a 

Tested by simple linear regression for continuous variables and by the Cochran-Armitage trend test for dichotomous variables.

Table Graphic Jump Location
Table 3 —Multiple Linear Regressions for Fasting Blood Lipids

Data are presented as β (SE [β]). See Table 2 legend for expansion of abbreviations.

a 

P < .001.

b 

P < .05.

c 

P < .01.

Table Graphic Jump Location
Table 4 —Adjusted ORs for Metabolic Dyslipidemia According to ODI Categories

ORs were adjusted for age, sex, BMI, smoking habits, alcohol consumption, abdominal obesity, cardiovascular morbidity, hypertension, diabetes, use of lipid-lowering drugs, and study site. See Table 2 legend for expansion of abbreviation.

a 

Tested by the Cochran-Armitage trend test.

References

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