Title: Association between obstructive sleep apnea and lipid metabolism during REM and NREM sleep
Abstract: Free AccessScientific InvestigationsAssociation between obstructive sleep apnea and lipid metabolism during REM and NREM sleep Huajun Xu, MD, PhD, Yunyan Xia, MD, Xinyi Li, MD, Yingjun Qian, MD; PhD, Jianyin Zou, MD, PhD, Fang Fang, MD, Hongliang Yi, MD, PhD, Hongmin Wu, MD, Jian Guan, MD, PhD, Shankai Yin, MD, PhD Huajun Xu, MD, PhD Department of Otolaryngology Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China Otolaryngological Institute of Shanghai Jiao Tong University, Shanghai, China Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China , Yunyan Xia, MD Department of Otolaryngology Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China Otolaryngological Institute of Shanghai Jiao Tong University, Shanghai, China Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China Department of Otorhinolaryngology Head & Neck Surgery, The First Affiliated Hospital of Nanchang University, Nanchang, China , Xinyi Li, MD Department of Otolaryngology Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China Otolaryngological Institute of Shanghai Jiao Tong University, Shanghai, China Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China , Yingjun Qian, MD; PhD Department of Otolaryngology Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China Otolaryngological Institute of Shanghai Jiao Tong University, Shanghai, China Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China , Jianyin Zou, MD, PhD Department of Otolaryngology Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China Otolaryngological Institute of Shanghai Jiao Tong University, Shanghai, China Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China , Fang Fang, MD Nursing Department of Otolaryngology Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China , Hongliang Yi, MD, PhD Department of Otolaryngology Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China Otolaryngological Institute of Shanghai Jiao Tong University, Shanghai, China Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China , Hongmin Wu, MD Department of Otolaryngology Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China Otolaryngological Institute of Shanghai Jiao Tong University, Shanghai, China , Jian Guan, MD, PhD Department of Otolaryngology Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China Otolaryngological Institute of Shanghai Jiao Tong University, Shanghai, China Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China , Shankai Yin, MD, PhD Department of Otolaryngology Head and Neck Surgery & Center of Sleep Medicine, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China Otolaryngological Institute of Shanghai Jiao Tong University, Shanghai, China Shanghai Key Laboratory of Sleep Disordered Breathing, Shanghai, China Published Online:April 15, 2020https://doi.org/10.5664/jcsm.8242Cited by:15SectionsAbstractPDF ShareShare onFacebookTwitterLinkedInRedditEmail ToolsAdd to favoritesDownload CitationsTrack Citations AboutABSTRACTStudy Objectives:Obstructive sleep apnea (OSA) is thought to be associated with dyslipidemia. However, differences concerning dyslipidemia during rapid eye movement (REM) and non-REM (NREM) sleep have yet to be determined. This study was designed to explore the association between lipid profiles and OSA during REM or NREM sleep.Methods:This is a clinical cohort. A total of 2,619 participants with at least 30 minutes of REM sleep were included. Sleep variables and fasting lipid profiles [total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein (apo)A-I, apoB, apoE, and lipoprotein(a) (Lp(a))] were obtained from each participant. Apnea-hypopnea indices in REM and NREM sleep (AHIREM and AHINREM, respectively) were recorded. Linear regression analysis was used to assess the associations of AHIREM and AHINREM with lipid profiles.Results:When stratified by the AHIREM severity of OSA, all demographics, clinical variables, and sleep parameters differed between the groups except for apoA-I. In fully-adjusted multivariate linear regression models, AHIREM was independently associated with increasing levels of TG, HDL-C, and apoE (P = .04, P = .01 and P = .01, respectively). AHINREM was independently associated with increasing levels of TC, TG, LDL, and apoB, and lower level of HDL-C (all P < .05). In sensitivity analyses by only exploring associations in patients who had an AHINREM or AHIREM < 5 events/h in separate regression models, AHIREM was not associated with all-lipid profile in almost all adjusted models (all P > .05), whereas AHINREM was associated with elevated TC, LDL-C, and apoB (P = .03, P = .01 and P = .01, respectively).Conclusions:AHINREM was independently associated with the greatest alterations in serum lipids, including TC, LDL-C, and apoB.Citation:Xu H, Xia Y, Li X, et al. Association between obstructive sleep apnea and lipid metabolism during REM and NREM sleep. J Clin Sleep Med. 2020;16(4):475–482.INTRODUCTIONRapid eye movement (REM) sleep accounts for almost 25% of the total sleep time in humans and is associated with distinct physiologic alterations (ie, sympathetic activity, lower vagal tone, and cardiovascular instability).1 During REM sleep, pharyngeal dilator muscles and genioglossus activity are suppressed, which can lead to increased upper airway collapse.2 Such physiologic features during REM sleep can increase the likelihood of obstructive sleep apnea (OSA). In a previous study, patients with OSA experienced a longer duration of decreased oxygen desaturation, with more frequent and worse episodes, during REM sleep compared to non-REM (NREM) sleep.3In line with the pathophysiologic differences that exist between REM and NREM sleep in terms of OSA, the associations of OSA with early cardiovascular disease (CVD) and CVD also appears to differ according to sleep stage (REM versus NREM). In women, severe OSA during REM sleep was independently associated with the early signs of atherosclerosis, as evidenced by intima thickness.4 The apnea-hypopnea index (AHI) during REM sleep (AHIREM) was independently associated with peripheral arterial stiffness in patients with OSA.5 In addition, the occurrence of severe OSA during REM sleep is associated with a higher incidence of common CVD.6,7Because metabolic syndrome is an independent predictor of CVD and all-cause mortality,8 an exploration of the individual components of metabolic syndrome (ie, hypertension, diabetes, and dyslipidemia) during REM and NREM sleep in patients with OSA could help to clarify the possible mechanisms regarding OSA and OSA-related CVD risk. Previously, cross-sectional and longitudinal data from the Wisconsin Sleep Cohort Study determined that OSA during REM sleep was independently associated with hypertension.9 In another study, REM OSA was associated with a nondipping pattern of nocturnal blood pressure.10 In a sample of men without a prior diagnosis of OSA, undiagnosed OSA during REM sleep, but not during NREM sleep, was independently associated with hypertension.11 OSA during REM sleep could influence long-term glycemic control in patients with type 2 diabetes.12 In the Sleep Heart Health Study, AHIREM was associated with insulin resistance, but not with fasting glycemia or glucose intolerance.13 In the HypnoLaus cohort, REM OSA is independently associated with metabolic syndrome and diabetes.14 However, it remains unclear whether OSA during REM sleep could promote dyslipidemia.Therefore, compared with non-REM OSA, REM-related OSA appears to have more detrimental clinical outcomes (ie, hypertension, diabetes, and CVD). Many rodent studies showed that altered serum lipids play a pivotal role in the development of atherosclerosis under conditions of intermittent hypoxia. Our previous clinical studies also showed that OSA was independently associated with impaired dyslipidemia.15,16 Of the various lipids studied, only low-density lipoprotein cholesterol (LDL-C) was independently associated with OSA.16 Thus, whether REM-related OSA leads to more severe dyslipidemia compared to NREM-related OSA, similar to hypertension and glucose metabolism, remains to be determined. In this study, we aimed to assess the relationship between OSA and lipid profiles during REM or NREM sleep in a clinical setting with a large sample size.METHODSStudy populationFrom 2007 to 2014, participants who experienced primary snoring and/or daytime sleepiness were consecutively enrolled from the Sleep Center of Shanghai Jiao Tong University Affiliated Sixth People’s Hospital. Prior to the study, each participant completed a questionnaire capturing basic information, such as health status and medical history. Patients were excluded if they met the following criteria: (1) age younger than 18 years (n = 26); (2) previous anti-OSA therapy such as continuous positive airway pressure (CPAP) treatment, upper airway surgery, or application of an oral appliance (n = 122); (3) history of dyslipidemia and/or on lipid-lowering drugs (n = 198); (4) unstable systemic diseases such as hepatic, pulmonary, or cardiac failure (n = 38); (5) other common sleep disorders (eg, central sleep apnea, restless leg syndrome, upper airway resistance syndrome, or narcolepsy) (n = 26); (6) alcoholism or drug addiction (n = 8); and (7) REM sleep time < 30 minutes (n = 466).The study was conducted according to the World Medical Association Declaration of Helsinki in 1975 (trial registration number: ChiCTR1900025714), as revised in 1983, and was approved by the Ethical Committee of Shanghai Jiao Tong University Affiliated Sixth People’s Hospital. All participants provided their informed written consent.Anthropometric and biochemical measurementsWell-trained physicians measured common anthropometric indices, such as height, weight, neck circumference (NC), waist circumference (WC), and hip circumference (HC) in each participant. Height was measured by a portable stadiometer having an accuracy of 0.1 cm, with the patient in a standing position. Weight was measured by a digital scale with an accuracy of 0.1 kg, with the patient wearing only undergarments. NC was measured at the level of the cricothyroid membrane. WC was measured at the midpoint between the lowest rib and the iliac crest, with an accuracy of 1 mm. HC was measured at the widest girth at the greater trochanter, with an accuracy of 1 mm. All measurements were recorded twice and the mean value was noted.Fasting venous blood was collected from each participant. Serum lipid profiles [high-density lipoprotein cholesterol (HDL-C), LDL-C, total cholesterol (TC) and triglycerides (TG), apolipoprotein (apo)A-I, apoB, apoE, and lipoprotein(a) (Lp(a))] were measured using routine procedures in a hospital laboratory.Sleep evaluationThe Chinese version of the Epworth Sleepiness Scale was used to evaluate the daytime sleepiness of each participant. The total Epworth Sleepiness Scale scores ranged from 0 to 24.17 Hospital-based polysomnography (PSG) (Alice 4 or 5; Respironics, Pittsburgh, Pennsylvania, USA) was used to evaluate the objective sleep status. Standard PSG equipment includes electroencephalography channels (C3-M2 and C4-M1) and allows for electrooculography, submental electromyography, electrocardiography, oronasal airflow monitoring (using both a nasal pressure transducer and oronasal thermistor), monitoring of thoracoabdominal movements (using piezoelectric belts) and snoring sounds, and pulse oximetry. The PSG equipment used herein could automatically record sleep parameters such as apnea, hypopnea, pulse oxygen desaturation, and microarousals. A skilled technician, following the 2007 alternative American Academy of Sleep Medicine (AASM) criteria definition,18 also manually checked the scores.Calculation and definitionBody mass index (BMI) was calculated as weight divided by height squared (kg/m2). The waist/hip ratio (WHR) was calculated as WC divided by HC. Hypertension was defined as a systolic blood pressure of > 140 mmHg or a diastolic blood pressure of > 90 mmHg. A history of hypertension and current antihypertensive drug treatment were considered to be additional indicators of hypertension. Diabetes was defined as a fasting plasma glucose concentration of ≥ 7.0 mmol/L or the known use of antidiabetic medication before the measurement.Apnea was defined as reduction in oronasal airflow by at least 90% for at least 10 seconds. Hypopnea was defined as an at least 50% decrease in oronasal airflow for 10 seconds or longer, associated with at least a 3% reduction in oxygen saturation or arousal according to the AASM 2007 alternative criteria.18 The AHI was defined as the sum of apnea and hypopnea events/h of sleep.19 The oxygen desaturation index (ODI) was defined as the total number of oxyhemoglobin desaturation ≥ 3% events/h of sleep. Arousal was defined as abrupt shifts in electroencephalographic frequency lasting at least 3 seconds, and the microarousal index was defined as the mean number of arousal events/h of sleep according to the AASM 2007 alternative criteria. OSA was classified into 4 classes: no OSA (AHI < 10 events/h), mild OSA (AHI 10 < 20 events/h), moderate OSA (AHI 20 < 30 events/h), and severe OSA (AHI ≥ 30 events/h).18 AHIREM and AHINREM were calculated as the number of apnea and hypopnea events/h of REM and NREM sleep, respectively.Statistical analysisAll statistical analyses in this study were performed using SPSS software (version 22.0; SPSS Inc., Chicago, Illinois, USA). Data are presented as medians (interquartile range), means, and standard deviation (SD), or percentages (for skewed, normally distributed, and categorical data, respectively). Differences in basic characteristics among the 4 OSA groups were examined using the Kruskal-Wallis H-test, 1-way analysis of variance, or the chi-square test, as appropriate. If distributions of variables were skewed, the variables [AHIREM, AHINREM, TG, apoE and Lp(a)] were natural log transformed. The associations of AHIREM [we treated AHIREM as a continuous variable: log (AHIREM + 1)], AHINREM [we treated AHINREM as a continuous variable: log (AHINREM + 1)] with lipid profile were evaluated using multiple linear regression. AHI in either REM or NREM sleep was always included as a covariate in all models. In models for evaluating the association of AHIREM with lipid metabolism, AHINREM was adjusted. Similarly, in models for evaluating the association of AHINREM with lipid metabolism, AHIREM was adjusted. The associations were first explored in a model adjusted for age, sex, and BMI, and then in a multivariable-adjusted model additionally adjusted for WHR, presence of diabetes and presence of hypertension. We also performed a sensitivity analysis by only exploring associations in patients who had an AHINREM or AHIREM < 5 events/h, respectively. Values of P for linear trends across the four groups (non, mild, moderate, and severe OSA) were calculated using the polynomial linear trend test for continuous variables. A value of P < .05 was considered to indicate statistical significance.RESULTSBaseline characteristicsA total of 2,619 participants were enrolled in this study. The demographic and clinical characteristics of the study participants are presented in Table 1. Patients suspected of having OSA were stratified by OSA severity according to AHIREM quartiles. Table 1 shows that participants with more severe REM-related OSA were older and more likely to be male and had a higher BMI and other obesity indices such as NC, WC, HC, and WHR. Moreover, all indices of arousal or apnea frequency, and nearly all biochemical indices, were increased with OSA severity, but not with the presence of apoA-I. Fasting serum levels of TC, TG, LDL-C, apoA-I, apoB, and apoE were generally elevated with OSA severity. However, other lipids, including HDL-C and Lp(a), were decreased with OSA severity.Table 1 Basic characteristics of the overall population by the AHIREM severity of OSA.Characteristics< 10 (n = 708)10 to < 20 (n = 226)20 to < 30 (n = 219)≥ 30 (n = 1,466)PDemographics Age, years40.0 ± 12.143.7 ± 12.542.9 ± 12.543.8 ± 11.5< .001 Male, n (%)467 (66.0)172 (76.1)171 (78.1)1,253 (85.5)< .001 BMI, kg/m224.3 ± 3.225.5 ± 3.226.1 ± 3.127.7 ± 3.7< .001 NC, cm37.0 ± 3.538.5 ± 3.138.6 ± 3.340.3 ± 3.4< .001 WC, cm88.4 ± 9.893.2 ± 9.293.9 ± 8.998.5 ± 10.0< .001 HC, cm97.6 ± 6.899.8 ± 6.9100.2 ± 6.1103.0 ± 6.4< .001 WHR0.90 ± 0.070.93 ± 0.060.94 ± 0.060.96 ± 0.05< .001Biochemistry assays TC (mmol/L)4.44 ± 0.904.54 ± 0.904.67 ± 1.034.90 ± 0.95< .001 TG (mmol/L)1.23 (0.82–1.79)1.46 (1.04–2.12)1.47 (1.02–2.06)1.76 (1.23–2.52)< .001 HDL-C (mmol/L)1.11 ± 0.261.07 ± 0.241.08 ± 0.241.05 ± 0.23< .001 LDL-C (mmol/L)2.77 ± 0.812.86 ± 0.782.96 ± 0.603.14 ± 0.83< .001 ApoA-I (g/L)1.12 ± 0.211.10 ± 0.221.11 ± 0.201.11 ± 0.20.224 ApoB (g/L)0.77 ± 0.180.81 ± 0.190.81 ± 0.190.88 ± 0.18< .001 ApoE (mg/dL)3.99 (3.28–4.76)4.04 (3.46–4.99)4.07 (3.33–5.07)4.54 (3.69–5.67)< .001 Lp(a) (mg/L)7.60 (4.01–16.60)8.70 (4.40–17.38)7.40 (3.40–14.20)7.20 (3.60–14.40)< .001Sleep apnea AHI3.0 (1.0–7.7)11.3 (6.4–19.8)17.0 (9.7–27.0)55.1 (35.5–70.4)< .001 AHIREM2.6 (0.0–5.7)14.3 (12.0–16.6)24.3 (22.1–27.4)56.1 (45.4–66.4)< .001 AHINREM2.7 (0.8–8.3)10.8 (5.1–20.4)15.0 (7.1–27.6)55.2 (32.6–71.8)< .001 ODI3.3 (1.1–9.0)11.7 (6.1–19.9)17.3 (9.5–28.6)55.5 (35.7–71.2)< .001 ODIREM2.5 (0.0–6.6)14.2 (10.8–17.6)24.0 (20.2–29.6)56.6 (44.8–68.0)< .001 ODINREM2.9 (1.0–9.3)11.5 (4.7–20.7)16.0 (7.2–28.0)55.1 (33.5–72.5)< .001 MAI14.9 (10.5–22.7)18.8 (12.2–26.7)21.6 (14.9–31.7)36.2 (21.9–56.2)< .001 MAIREM11.3 (6.5–18.2)15.4 (7.8–23.0)18.9 (11.1–27.9)31.1 (18.5–45.0)< .001 MAINREM12.5 (8.6–20.1)15.1 (10.4–23.6)18.6 (12.1–28.8)30.0 (18.5–45.9)< .001 ESS5.0 (1.0–9.0)7.0 (3.0–11.0)7.0 (4.0–11.0)9.0 (5.0–14.0)< .001Medical history Hypertension, n (%)99 (15.2)38 (17.9)46 (23.2)427 (31.9)< .001 Diabetes, n (%)17 (2.4)11 (4.9)17 (7.8)126 (8.6)< .001The data are presented as mean ± standard deviation, median (interquartile range), and n (%) where indicated. Differences in the baseline characteristics among the four groups were examined using the polynomial linear trend test for continuous variables and the linear-by-linear association test for dichotomous variables. AHI = apnea-hypopnea index, AHIREM = apnea-hypopnea index during rapid eye movement sleep, AHINREM = apnea-hypopnea index during non-rapid eye movement sleep, ApoA-I = apolipoprotein A-I, ApoB = apolipoprotein B, ApoE = apolipoprotein E, BMI = body mass index, DBP = diastolic blood pressure, ESS = Epworth Sleepiness Scale, HC = hip circumference, HDL-C = high-density lipoprotein cholesterol, HOMA-IR = homeostasis model assessment for insulin resistance, LDL-C = low-density lipoprotein, cholesterol, Lp(a) = lipoprotein (a), MAI = microarousal index, MAIREM = microarousal index during rapid eye movement sleep, MAINREM: microarousal index during non-rapid eye movement sleep, NC = neck circumference, ODI = oxygen desaturation index, ODIREM = oxygen desaturation index during rapid eye movement sleep, ODINREM: oxygen desaturation index during non-rapid eye movement sleep, OSA = obstructive sleep apnea, SBP = systolic blood pressure, TC = total cholesterol, TG = triglyceride, WC = waist circumference, WHR = waist/hip ratio.Relationship between AHIREM and the lipid profileAHIREM was independently associated with increasing levels of TG (β = .029; P = .042), HDL-C (β = .040; P = .005), and apoE (β = .021; P = .014) after fully adjusting for confounders including age, sex, BMI, WHR, presence of diabetes, presence of hypertension and AHINREM (Table 2). However, AHIREM was not associated with TC, LDL-C, apoA-I, apoB and Lp(a) (all P > .05, after adjustment including AHINREM) (Table 2). In sensitivity analyses, we excluded patients who had an AHINREM > 5 events/h and only explored associations in AHINREM < 5 events/h. AHIREM was not associated with all lipid profile in almost all adjusted models (Table 3).Table 2 Associations between AHIREM and AHINREM with serum lipid levels (AHIREM and AHINREM analyzed in same regression models).Adjusteda log(AHIREM + 1)Multivariable AdjustedbAdjusteda log(AHINREM + 1)Multivariable AdjustedbTC β (95% CI).12 (.01 to .23).10 (−.01 to .22).20 (.09 to .32).19 (.07 to .31) P.03.07< .01< .01 R2.07.08.07.08log(TG) β (95% CI).03 (.00 to .06).03 (.00 to .06).05 (.02 to .07).04 (.00 to .06) P.03.04< .01.02 R2.18.22.18.22HDL-C β (95% CI).04 (.01 to .06).04 (.01 to .07)−.04 (−.06 to −.01)−.04 (−.07 to −.08) P.01.01.01.02 R2.14.14.14.14LDL-C β (95% CI).08 (−.01 to .18).08 (−.02 to .18).18 (.08 to .28).17 (.07 to .28) P.08.13< .01< .01 R2.06.06.06.06apoA-I β (95% CI).01 (−.02 to .03).01 (−.02 to .03).01 (−.01 to .04).02 (−.01 to .04) P.58.57.33.23 R2.08.09.08.09apoB β (95% CI).01 (−.01 to .03).01 (−.01 to .03).06 (.03 to .08).05 (.03 to .07) P.23.41< .01< .01 R2.11.12.11.12log(apoE) β (95% CI).02 (.01 to .04).02 (.00 to .04).02 (.00 to .03).01 (−.01 to .03) P.01.01.05.18 R2.08.10.08.10log(Lp(a)) β (95% CI)−.04 (−.09 to .02)−.05 (−.01 to .01)−.01 (−.07 to .05).00 (−.06 to .06) P.17.11.74.93 R2.02.02.02.02aAdjusted for age, sex and BMI. bMultivariable adjusted for age, sex, BMI, WHR, presence of diabetes and presence of hypertension. A total of 2,619 participants were included in all the regression models. AHIREM = apnea-hypopnea index during rapid eye movement sleep, AHINREM = apnea-hypopnea index during non-rapid eye movement sleep, apo = apolipoprotein, Lp(a) = lipoprotein(a), BMI = body mass index, CI = confidence interval, HDL-C = high-density lipoprotein-cholesterol, LDL-C = low-density lipoprotein-cholesterol, TC = total cholesterol, TG = triglyceride, WHR = waist/hip ratio.Table 3 Associations between AHIREM and AHINREM with serum lipid levels (AHIREM and AHINREM analyzed in separate regression models) by excluding AHINREM ≥ 5 events/h in log (AHIREM + 1) models and AHIREM ≥ 5 events/h in log (AHINREM + 1) models.Adjusteda log(AHIREM + 1)Multivariable AdjustedbAdjusteda log(AHINREM + 1)Multivariable AdjustedbTC β (95% CI).05 (−.13 to .24).07 (−.13 to .27).26 (.05 to .47).24 (.03 to .46) P.57.47.01.03 R2.10.11.12.13log(TG) β (95% CI).01 (−.03 to .06).02 (−.03 to .06).05 (−.00 to .10).03 (−.02 to .09) P.58.52.06.20 R2.23.27.26.29HDL-C β (95% CI).06 (.00 to .11).06 (.00 to .11)−.01 (−.07 to .05).00 (−.06 to .07) P.05.05.65.92 R2.17.19.18.19LDL-C β (95% CI).04 (−.13 to .20).04 (−.13 to .21).29 (.10 to .47).25 (.06 to .44) P.68.62< .01.01 R2.11.12.14.16apoA-I β (95% CI).02 (−.02 to .06).02 (−.03 to .06).01 (−.03 to .06).03 (−.02 to .08) P.40.43.56.26 R2.12.15.10.11apoB β (95% CI)−.01 (−.05 to .02)−.01 (−.05 to .03).07 (.03 to .10).06 (.02 to .10) P.47.54< .01.01 R2.16.16.21.22log(apoE) β (95% CI).02 (−.00 to .05).02 (−.04 to .05).02 (−.02 to .05).01 (−.02 to .04) P.08.10.30.52 R2.06.08.05.07log(Lp(a)) β (95% CI)−.00 (−.10 to .09).01 (−.10 to .11)−.03 (−.14 to .08)−.03 (−.14 to .09) P.97.91.63.66 R2.02.03.03.04aAdjusted for age, sex and BMI. bMultivariable adjusted for age, sex, BMI, waist/hip ratio, presence of diabetes and presence of hypertension. All adjusted models were also comprised with additional adjustments for AHINREM in log (AHIREM + 1) models and AHIREM in log (AHINREM + 1) models. A total of 495 participants were included in log (AHINREM + 1) models by excluding AHIREM ≥ 5 events/h, and a total of 564 participants were included in log (AHIREM + 1) models by excluding AHINREM ≥ 5 events/h. AHIREM = apnea-hypopnea index during rapid eye movement sleep, AHINREM = apnea-hypopnea index during non-rapid eye movement sleep, apo = apolipoprotein, BMI = body mass index, CI = confidence interval, HDL-C = high-density lipoprotein-cholesterol, LDL-C = low-density lipoprotein-cholesterol, Lp(a) = lipoprotein(a), TC = total cholesterol, TG = triglyceride.Relationship between AHINREM and the lipid profileAHINREM was independently associated with increasing levels of TC, TG, LDL and apoB, and inversely correlated with levels of HDL-C after adjustment for confounders including AHIREM (all P < .05) (Table 2). We also performed sensitivity analyses by only exploring associations between AHINREM and lipid profile in patients who had an AHIREM < 5 events/h. AHINREM was associated with elevated TC (β = .244; P = .029), LDL-C (β = .246; P = .012), and apoB (β = .055; P = .008) levels (Table 3). There was no relationship between AHINREM and other lipids such as TG, HDL-C, apoA-I, apoE/Lp(a) (all P > .05, after adjustment including AHIREM) (Table 3).DISCUSSIONThis study is the first to reveal a positive association between OSA during REM and NREM sleep and the lipid profile. In this large-scale observational study, we found that AHIREM was independently associated with increasing levels of TG, HDL-C, and apoE. AHINREM was independently associated with increasing levels of TC, TG, LDL, and apoB, and a lower level of HDL-C. However, only AHINREM was associated with elevated levels of TC, LDL-C, and apoB in further sensitivity analyses.OSA has been associated with an altered lipid profile in both clinical and community-based studies.16,20 However, few current studies have focused on the relationship between the lipid profile and REM or NREM sleep. Previous studies showed that REM OSA, as opposed to NREM OSA, was independently associated with hemoglobin A1c, insulin resistance, and hypertension.11–13 Similarly, OSA during REM sleep might also contribute to dyslipidemia, which may also be attributable to elevated sympathetic activity and the accompanying intermittent hypoxia and recurrent arousal/sleep fragmentation. However, association did not persist in REM OSA and lipids when sensitivity analyses were performed. This seems that lipids were more prone to be related to AHINREM. The results were largely inconsistent with our original hypothesis that AHINREM might be a better predictor for dyslipidemia. Because sympathetic tone is already elevated during REM sleep, there may be a ceiling effect, such that further bursts in sympathetic tone from apneas/hypopneas in REM have limited effect on further freeing circulating lipids during this stage. Contrary to our expectations, we observed a positive association between AHIREM and HDL (which one might interpret as being cardioprotective), though the association did not persist after sensitivity analysis in which participants with AHINREM > 5 events/h were excluded. This might be partly explained by other potential residual confounders not adjusted for in our study.During sleep, patients with OSA exhibited a marked increase in free fatty acids compared to control participants, and this increase persisted throughout the entire sleep period (mostly in NREM sleep).21 Increased levels of free fatty acids might decrease the production of growth hormone, which is mainly secreted during deep sleep.22 Reduced growth hormone appears to contribute independently to dyslipidemia.23 Thyrotropin also increased in NREM sleep and is closely associated with dyslipidemia.24 These altered hormone levels might partly explain why lipids (including TC, LDL-C, and apoB) are independently associated with AHINREM. Interestingly, we found that other lipids such as TG and apoE were not associated with AHINREM. This lack of a relationship between TG, apoE, and AHINREM was seen after adjusting for the obesity indices. Thus, obesity had a much greater effect on TG/apoE compared to AHINREM. A previous study also showed that OSA had no independent association with lipid profile abnormalities, with obesity being the major determinant of metabolic abnormalities.25 HDL-C, apoA-I, and Lp(a) were also uncorrelated with AHINREM. Recently, the European Sleep Apnea Database cohort with the largest sample size revealed that OSA severity was independently associated with TC, not HDL-C.26 This was consistent with our findings. Because apoA-I is the main component of HDL-C, the change of apoA-I is in agreement with that of LDL-C. Similar to our previous reports that Lp(a) was not correlative with AHI, level of Lp(a) was also unaltered in this study.15From meta-analysis of observational studies, patients with OSA appeared to have an increased risk of dyslipidemia, evidenced by high TC, LDL-C, and TG levels, and a low HDL-C level.27 However, in interventional studies, the effects of CPAP on lipid levels were equivocal. Our previous meta-analysis showed that CPAP could decrease the TC level, especially in patients with OSA who use CPAP over a relatively long period.28 Recent clinical studies drew different conclusions. In one such study, 3 months of CPAP treatment did not alter any metabolic variable, including the lipid profile, in women.29 Recently, a randomized controlled trial compared the effects of 2 months of CPAP usage with sham-CPAP on Lp(a), and a negative result was found [Lp(a) was not changed]. However, Lp(a) improved in those adherent to CPAP.30 Such conflicting results might be partly explained by the duration of CPAP usage. In our study, NREM OSA was mainly associated with elevated lipid levels. CPAP adherence is greater in the earlier part of the night where NREM sleep predo