- Email: [email protected]
Neurocognitive impairment is correlated with oxidative stress in patients with moderate-to-severe obstructive sleep apnea hypopnea syndrome
Respiratory Medicine 120 (2016) 25e30
Contents lists available at ScienceDirect
Respiratory Medicine journal homepage: www.elsevier.com/locate/rmed
Neurocognitive impairment is correlated with oxidative stress in patients with moderate-to-severe obstructive sleep apnea hypopnea syndrome Yanyu He a, b, Rui Chen a, b, *, Jing Wang a, b, Wenying Pan a, b, Yanqiu Sun a, b, Fei Han a, c, Qiaojun Wang a, c, Chunfeng Liu a, c, d a
Sleep Center, The Second Affiliated Hospital of Soochow University, Soochow University, Suzhou, China Department of Respiratory Medicine, The Second Affiliated Hospital of Soochow University, Soochow University, Suzhou, China Department of Neurology, The Second Affiliated Hospital of Soochow University, Soochow University, Suzhou, China d Laboratory of Aging and Nervous Diseases, Institute of Neuroscience, Soochow University, Suzhou, China b c
a r t i c l e i n f o
a b s t r a c t
Article history: Received 22 June 2016 Received in revised form 5 September 2016 Accepted 8 September 2016 Available online 9 September 2016
Background and objectives: Patients with obstructive sleep apnea hypopnea syndrome (OSAHS) are associated with increased risk of neurocognitive impairment, which are largely recognized as mild cognitive impairment (MCI), and oxidative stress is postulated as one of the underlying mechanisms. This study aimed to investigate the relationship between MCI and oxidative stress biomarkers in OSAHS. Methods: A total of 119 middle-aged patients with moderate-to-severe OSAHS were included. Based on the baseline Montreal Cognitive Assessment (MoCA, validated Chinese version), 86 and 33 patients presented with normal cognitive function (NC, MoCA 26) and mild cognitive impairment (MCI, MoCA <26), respectively. Overnight PSG, MoCA and serum levels of ischemia-modified albumin (IMA), malondialdehyde (MDA) and advanced oxidation protein products (AOPP) were collected and analyzed. Results: Compared to NC group, patients with MCI were characterized with significantly greater waistto-height ratio, AHI, ODI and time ratio of SpO2<90%, and lower average SpO2 and time ratio of rapid eye movement (REM). All three oxidative stress biomarkers were markedly elevated in MCI group. Binary logistic regression analysis demonstrated that MCI is significantly correlated with serum levels of IMA, REM ratio and the age of patients. Conclusions: The neurocognitive impairment in moderate-to-severe OSAHS patients is associated with significantly elevated oxidative stress. IMA might be a new useful biomarker correlated with mild cognitive impairment of the patients. © 2016 Published by Elsevier Ltd.
Keywords: Obstructive sleep apnea hypopnea syndrome Cognitive impairment Oxidative stress Ischemia-modified albumin Polysomnography
1. Introduction Obstructive sleep apnea hypopnea syndrome (OSAHS) is one of the sleep-disordered breathing diseases characterized by recurrent episodes of increased upper airway resistance during sleep, leading to spells of apnea/hypopnea and nocturnal sleep fragmentation. It is known to be associated with significantly increased risk of mortality and morbidities that includes cardiovascular and cerebrovascular diseases, metabolic derangement and neurocognitive
* Corresponding author. Department of Respiratory Medicine, The Second Affiliated Hospital of Soochow University, No. 1055, Sanxiang Road, Suzhou, 215004, China. E-mail address: [email protected] (R. Chen). http://dx.doi.org/10.1016/j.rmed.2016.09.009 0954-6111/© 2016 Published by Elsevier Ltd.
impairment [1], the latter of which has recently been increasingly recognized. Untreated OSAHS has been reported with deficits in attention span, divided and sustained attention, working memory, and visuospatial and executive function [2e4]. As reported in our previous work, mild cognitive impairment (MCI) has been the nonnegligible manifestation of cognitive dysfunction in OSAHS patients, and Montreal Cognitive Assessment (MoCA) questionnaire can be used as a simple and sensitive neurocognitive assessment instrument to detect this damage [2]. The underlying mechanisms of neurocognitive impairment associated with sleep apnea may include intermittent hypoxemia, sleep fragmentation, neuroinflammation, cerebrovascular change, and ischemic preconditioning [5e7]. The role of oxidative stress in OSAHS-related cognitive deficit has also been postulated [8,9],
26
Y. He et al. / Respiratory Medicine 120 (2016) 25e30
Abbreviations AHI AOPP BMI ESS IMA MoCA MCI MDA MMSE NC NREM OSAHS PSG REM SpO2 WHR
apnea/hyponea index advanced oxidation protein products body mass index Epworth sleepiness scale ischemia-modified albumin Montreal Cognitive Assessment mild cognitive impairment malondialdehyde Mini-mental state examination normal cognition non-rapid eye movement obstructive sleep apnea hypopnea syndrome polysomnography rapid eye movement pulse oxygen saturation waist-to-height ratio
however, few studies have examined an array of standard and novel biomarkers of oxidative stress and controversy still remains regarding the best biomarker specific for cognitive function in OSAHS patients. Compared to a number of well-established serum oxidative stress biomarkers such as glutathione, superoxide dismutase, malondialdehyde (MDA) and advanced oxidation protein products (AOPP) [10e12], ischemia-modified albumin (IMA) is a novel oxidative stress indicator recently reported in type 2 diabetes mellitus and infectious diseases [13,14], and most interestingly, has been lately demonstrated to be closely correlated with the neurocognitive impairment in Alzheimer's disease [15,16]. In this observational study, the cognitive function of middleaged Chinese patients with moderate-to-severe OSAHS without dementia was evaluated by MoCA [17] to detect and characterize MCI and also the changes in various neuropsychological subdomains. The serum levels of oxidative stress biomarkers including IMA, MDA and AOPP were measured and the correlations between MoCA scores with the clinical & polysomnographic parameters and oxidative stress biomarker levels were investigated in particular.
2. Methods 2.1. Patient eligibility A total of 119 eligible patients were selected from a cohort of consecutive Chinese patients diagnosed of OSAHS by overnight polysomnography (PSG) in our sleep laboratory from February 2014 to October 2014. The major inclusion criteria contained newly diagnosed moderate-to-severe OSAHS (AHI 15 event/h) without prior history of surgical, orthodontic or CPAP treatment for OSAHS, age of 30e60 years old and minimal requirement of primary school education. The exclusion criteria included: (i) presence of other sleep disorders based on ICSD-II diagnosis [18], such as central sleep apnea, restless legs syndrome, rapid eye movement (REM)sleep behavioral disorder, periodic limb movement disorder and narcoleptic spectral disorder; (ii) Alzheimer's disease, vascular dementia, Parkinson's disease, anxiety, depression or other mental or central nervous system (CNS) diseases, and/or any other conditions requiring pharmacotherapies impacting the mental status or CNS within the last 3 months; (iii) new onset cardiovascular or cerebrovascular accidents within the last 3 months, chronic heart failure, recent infectious diseases, or prior history of malignancy;
(iv) other diseases with abnormal liver, kidney and/or lung function. 2.2. Polysomnographic assessment Overnight PSG (Compumedics, Australia) was performed in an attended setting for all patients at the first night of admission starting from 10 p.m. to 6 a.m. next morning, and at least 7 h of recording time was considered a successful monitoring. The PSG assessments included the following indexes: airflow by using oronasal thermistors and nasal pressure transducer, thoracic and abdominal respiratory movements, arterial oxygen saturation by pulse oximetry, snoring and body position, electroencephalogram (C3/A2, C4/A1, O1/A2, and O2/A1), electrooculogram, chin and leg electromyogram and electrocardiogram. A panel of polysomnographic variables were obtained, which included AHI, oxygen desaturation index (ODI, defined as the sum of the numbers of oxyhemoglobin desaturation of >4% events per hour of sleep), time ratio of SpO2<90% (T90), minimum pulse oxygen saturation (MSpO2), average oxygen saturation (ASpO2), total sleep time (TST), non-rapid eye movement (NREM) sleep phases 1e3, and REM sleep. AHI was defined as the sum of the numbers of apnea or hypopnea events per hour of sleep. Apneas were scored when there was a complete cessation of airflow or 90% drop in the peak thermal sensor excursion for at least 10 s. Hypopneas were scored when there was a drop in nasal pressure signal excursion by 30% of baseline lasting at least 10 s with a 4% desaturation from preevent baseline, or when there was a drop in nasal pressure signal excursion by 50% of baseline lasting at least 10 s with a 3% desaturation from pre-event baseline and/or the event associated with arousal. All PSG studies were analyzed by trained technicians and sleep physicians according to the criteria of the American Academy of Sleep Medicine 2012 [19]. 2.3. Montreal cognitive assessment A Chinese version of the MoCA questionnaire (Beijing version) based on the final English version was used in this study (Beijing version and English version of MoCA are available at http://www. mocatest.org with no permission requirements as declared). MoCA is a 30-point test covering seven cognitive subdomains: (i) visuospatial and executive; (ii) naming; (iii) memory; (iv) attention; (v) language; (vi) abstraction; (vii) delayed recall; and (viii) orientation. A bonus point is given to individuals with <12 years of education. MoCA <26 is considered to be indicative of MCI, otherwise normal cognition function (NC), which was reported with sensitivity of 90% and specificity of 87% [17]. 2.4. Mini-mental state examination (MMSE) A Chinese version of MMSE questionnaire was administered to all the patients. MMSE 27 is considered to be normal. And MMSE 20 was found essentially only in patients with dementia, delirium, schizophrenia or affective disorder as reported when they at least finish their primary school [20]. 2.5. Epworth sleepiness scale (ESS) A validated Chinese version of the ESS questionnaire [21], with eight items and 4-point scale (0e3), which was used in our previous clinical study of OSAHS [2], was also administered to all patients. It is allowed to use under dedicated clinical research (http:// epworthsleepinessscale.com).
Y. He et al. / Respiratory Medicine 120 (2016) 25e30
2.6. Serum oxidative stress biomarker assays Samples of 4 ml venous blood were collected in the morning after overnight PSG of which the serum were then stored at 80 C prior to analyses. Serum levels of the oxidative stress biomarkers including both the novel (IMA) and more standard (MDA and AOPP) biomarkers were measured using the commercial ELISA kits (R&D, America).
2.7. Statistics The data were presented as mean ± standard deviation (SD) unless otherwise noted. Statistical testings between the two groups (NC vs. MCI) were carried out by Student's t-test, non-parametric test (Mann-Whitney) or Chi-square test when appropriate. Pearson and partial correlation analysis and binary logistic regression analysis were performed to investigate the relationships between MoCA scores against the clinical variables, serum biomarker and PSG parameters. All statistical analyses were conducted using SPSS 17.0 software for Windows. All probabilities were 2-tailed, and values of p < 0.05 were considered statistically significant.
Table 1 Sociodemographic and clinical characteristics of moderate-to-severe OSAHS patients.
Age, years Gender, Male n (%) Education, years Smoker, n (%) Alcohol user, n (%) Medical history Hypertension, n (%) Arrhythmia, n (%) Stroke, n (%) Diabetes, n (%) WHR WHR 0.56, n (%) BMI (kg/m2) BMI 30, n (%)
3. Results 3.1. Patient distribution Among the 119 eligible patients from the total of 265 patients screened, 43 of them were diagnosed with moderate OSAHS (AHI 15/h - <30/h) whereas the remaining 76 patients had severe OSAHS (AHI 30/h). According to the baseline MoCA scores, 72% of enrolled patients (N ¼ 86) presented with normal cognition function (NC, MoCA 26) compared to 28% (N ¼ 33) associated with mild cognitive impairment (MCI, MoCA <26) (Table 1). While a total of 19 patients (16%) had a MMSE score <27, no patients presented with baseline MMSE score 20 qualifying for dementia, and they all finished their primary school. (Table 2).
3.2. Sociodemographic and clinical characteristics of OSAHS patients with and without MCI The overall patient in this study was representative of a middleaged population (mean age of 47.46 ± 11.02 years), and predominantly male (104/119, 87%) with a mean education experience of 11.99 ± 3.29 years and a mean BMI of 27.13 ± 2.60 kg/m2 (17% with BMI 30 kg/m2). The baseline demographic and clinical characteristics between the NC and MCI groups are summarized in Table 1. There was no difference in age, gender, education level, smoking or alcohol user, or prior medical histories between the two groups. The waist-toheight ratio (WHR) was significantly greater in the MCI group (0.57 ± 0.06) compared to the NC group (0.55 ± 0.05), associated with higher proportion of patients with WHR 0.56, the median WHR value in this overall patient cohort (64% vs. 43% in the NC group), and BMI 30 kg/m2 (27% vs. 13% in the NC group) in the MCI group.
NC (N ¼ 86)
MCI (N ¼ 33)
P value
46.37 ± 10.96 78 (93.44) 12.21 ± 3.45 41(47.67) 29 (33.72)
50.30 ± 10.81 26 (78.79) 11.42 ± 2.78 11 (33.33) 14(42.42)
0.081 0.119 0.245 0.158 0.376
47 (54.65) 1 (1.16) 1 (1.16) 4 (4.65) 0.55 ± 0.04 37 (43.02) 26.95 ± 2.49 11 (12.79)
17 (51.51) 2 (6.06) 1 (3.03) 3 (9.09) 0.57 ± 0.06* 21 (63.64)* 27.62 ± 2.86 9 (27.27)
0.758 0.186 0.479 0.395 0.011 0.044 0.210 0.059
Data are expressed as mean ± SD, n (%) or as indicated. *p < 0.05 compared to the NC group. NC, normal cognitive function; MCI, mild cognitive impairment; WHR, waist-toheight ratio; BMI, body mass index.
Table 2 Comparisons of neurocognitive assessments by MoCA and ESS scores in NC and MCI groups of patients.
2.8. Ethics The study was approved by our institutional ethics board (approval # 2014K07), and all patients were informed and gave consent prior to the study procedures.
27
MoCA Overall score Subdomains Visuospatial/executive Naming Attention Language Abstraction Delayed recall Orientation MMSE Mean ± SD Medium Minimum, Maximum ESS
NC (N ¼ 86)
MCI (N ¼ 33)
P values
27.52 ± 1.28
23.24 ± 1.75
e
4.24 2.97 5.88 2.62 1.69 3.78 5.99
± ± ± ± ± ± ±
0.77 0.19 0.50 0.69 0.49 0.77 0.11
29.28 ± 0.94 30 27, 30 8.42 ± 4.83
2.82 2.73 5.42 2.06 1.15 2.55 5.97
± ± ± ± ± ± ±
0.98 0.45 0.71 0.78 0.67 1.25 0.17
25.97 ± 2.71 26 21, 30 11.48 ± 4.61
<0.001 0.006 0.001 <0.001 <0.001 <0.001 0.482 <0.001
0.002
Data are presented as mean ± SD and/or median (minimum, maximum). MoCA, Montreal cognitive assessment; MMSE, Mini-mental state examination; ESS: Epworth sleepiness scale.
3.3. Neurocognitive profiles of OSAHS patients with and without MCI As described in Table 2, patients in the MCI group compared to the NC group were associated with statistically and clinically significant worse scores of the MoCA questionnaires. In particular, the MoCA scores in the MCI group were significantly lower in both the overall (23.24 ± 1.75 vs. 27.52 ± 1.28 in the NC group) and also most of the cognitive subdomain scores except the orientation subdomain. The MMSE scores were also significantly lower in the MCI group, while the ESS scores were significantly higher (Table 2). 3.4. Comparisons of PSG parameters and serum oxidative stress biomarkers in OSAHS patients with and without MCI The comparisons for PSG parameters between NC and MCI groups are summarized in Table 3. Compared to the NC group, patients in the MCI group were characterized with statistically significantly higher AHI, ODI, and T90, and lower ASpO2 and the time ratio of REM (Table 3). The serum levels of three oxidative stress biomarkers were significantly elevated in the MCI group, compared to the NC group
28
Y. He et al. / Respiratory Medicine 120 (2016) 25e30 Table 3 Comparisons of polysomnographic parameters in NC and MCI groups of patients.
AHI (event/h) ODI (event/h) Minimum SpO2 (%) Average SpO2 (%) T90 (%) TST (min) NREM 1 þ 2 sleep phases (%) NREM 3 sleep phases (%) REM sleep phases (%)
NC (N ¼ 86)
MCI (N ¼ 33)
P values
40.01 ± 19.35 37.44 ± 20.65 75.05 ± 9.09 92.65 ± 2.79 11.65 (0.00,69.50) 421.32 ± 67.98 69.64 ± 10.41 12.87 ± 7.80 17.49 ± 5.52
53.66 ± 24.80 50.70 ± 26.91 71.54 ± 9.89 91.29 ± 3.10 22.40 (4.30,80.30) 422.21 ± 89.01 73.72 ± 8.81 11.48 ± 7.92 14.80 ± 4.91
0.006 0.014 0.069 0.023 0.003 0.954 0.048 0.388 0.016
Data are presented as mean ± SD, except for T90 as median (minimum, maximum). AHI, apnea hypopnea index; SpO2, pulse oxygen saturation; T90, time ratio of SpO2 <90%; TST, total sleep time; REM, rapid eye movement.
(Fig. 1), including IMA (104.56 ± 47.21 vs. 64.67 ± 22.65 kU/L in the NC group, p < 0.01; Fig. 1A), MDA (8.87 ± 6.34 vs. 5.45 ± 2.80 nmol/ mL in the NC group, p < 0.01; Fig. 1B) and AOPP (108.16 ± 54.32 vs. 80.98 ± 34.89 mmol/L in the NC group, p < 0.05; Fig. 1C). 3.5. Correlation of clinical variables and serum oxidative stress biomarkers with MoCA scores To investigate the relationships between MoCA-assessed neurocognitive function with an array of sociodemographic and clinical variables as well as oxidative stress biomarkers, Pearson correlation analysis was performed which demonstrated that the MoCA scores was positively correlated with education level (p < 0.05), and negatively correlated with age (p < 0.01). When the analysis was further adjusted for age and education level, the MoCA scores were negatively and significantly correlated with the level of IMA, MDA and AOPP (p < 0.001), and with the AHI, ODI and T90 as well (p < 0.05), whereas it was positively correlated with average SpO2 and time ratio of REM (p < 0.05) (Table 4). In addition, regression analyses were performed among the sociodemographic and clinical parameters, PSG parameters and serum biomarkers, and it revealed that MCI (MoCA<26) was significantly associated with IMA levels (odds ratio: 1.046, 95% CI: 1.025e1.066; p < 0.001), time ratio of REM (odds ratio: 0.859, 95% CI: 0.773e0.954; p < 0.01), and age (odds ratio: 1.061, 95% CI: 1.009e1.115; p < 0.05). 4. Discussion We conducted an observational study in 119 moderate-tosevere Chinese OSAHS patients to better understand the correlation between neurocognitive impairment and oxidative stress in
OSAHS. Our research provides several key findings that extend the current knowledge of OSAHS-induced neurocognitive impairment: 1) MCI is common in middle-aged moderate-to-severe OSAHS patients; 2) while OSAHS with MCI can be associated with an array of clinical and laboratory characteristics, a novel oxidative stress biomarker of IMA is the notable variable significantly associated with MCI, indicating the important role of oxidative stress underlying the OSAHS-induced neurocognitive impairment. It has been increasingly recognized in recent years that the neurocognitive deficits experienced by OSAHS patients are largely MCI, which is an intermediate clinical state between normal cognitive aging and dementia that precedes and eventually leads to the latter disease state in many cases [22]. Given the important clinical implication of MCI, early diagnosis with proper therapeutic interventions is clearly warranted. MCI can be detected by MoCA covering various important cognitive subdomains and administered to patients in 10e15 min by a healthcare professional. When MCI was defined as MoCA <26 points, it was reported with a sensitivity of 90% and a specificity of 87% in patients with mild Alzheimer's disease compared to healthy elderly controls [17]. We first investigated the clinical utility of MoCA and compared it to MMSE in a large cohort of Chinese patients with a primary compliant of snoring and clinical suspicion of OSAHS, and reported in 2011 that MCI was more common in the moderate (38.6%) and severe (41.4%) OSAHS patients than in patients with mild OSAHS (25.0%) and primary snoring (15.2%) [2]. In the current study, 28% middle-aged OSAHS patients presented with MCI as detected by MoCA (<26), higher than 16% as assessed by MMSE score <27, which is consistent with our previous report. When compared to those with normal cognitive function, the MocA scores were significantly reduced in MCI patients across both the overall and subdomain scores of visuospatial/executive, naming, attention,
Fig. 1. Comparisons of serum levels of oxidative stress biomarkers between NC and MCI group of patients. Data are expressed at mean ± SD. IMA, ischemia-modified albumin; MDA, malondialdehyde; AOPP, advanced protein oxidation products.
Y. He et al. / Respiratory Medicine 120 (2016) 25e30 Table 4 Partial correlation analyses between MoCA scores and the oxidative stress biomarkers and PSG parameters. MDA
AOPP
IMA
AHI
ODI
T90
REM
ASpO2
r 0.332 0.382 0.475 0.240 0.192 0.206 0.197 0.183 P value <0.001 <0.001 <0.001 0.009 0.039 0.026 0.034 0.049 Analyses are adjusted for patients' age and education level. ASpO2, average pulse oxygen saturation; r, correlation coefficient.
language, abstraction and delayed recall. Our results are consistent with the deficits in attention, memory and executive dysfunctions reported in the OSAHS patients [5,23,24]. This important finding underscores the paradigm that MCI is fairly common even in middle-aged OSAHS patients and highlight the importance of early diagnosis and interventions. The underlying mechanisms contributing to the OSAHS-induced neurocognitive impairment remain poorly defined. We observed that, in a cohort of middle-aged moderate-to-severe Chinese OSAHS patients, the MCI patients were associated with greater abdominal obesity, nocturnal hypoxia, lower time ratio of REM stage, and significantly elevated serum levels of oxidative stress biomarkers when compared to NC group. These results implicate the multifaceted mechanisms of MCI in OSAHS. When regression analyses were performed among the sociodemographic and clinical parameters, PSG variables and serum biomarkers, it demonstrated that MCI (MoCA <26) was significantly and independently correlated with the IMA level, a finding further supporting and substantiating the role of oxidative stress underlying the development of MCI in OSAHS. Three oxidative stress biomarkers were evaluated in our study. The MDA and AOPP are well-established standard biomarkers related to lipid peroxidation and protein oxidation, respectively [10,11]. IMA is a novel biomarker of oxidative stress, and has been found to be closely correlated with the neurocognitive decline in Alzheimer's disease [15,16]. Yang et al. recently reported that IMA level significantly increased in a group of 32 OSAHS patients compared to the healthy controls [25]. Our results extend these previous studies and, for the first time, suggest its potential value as a more specific biomarker related to cognitive impairment in OSAHS. More research is clearly warranted to evaluate the unique relationship and underlying mechanisms between IMA elevation and MCI. The present study also demonstrated that MCI was independently associated with the time ratio of REM in a cohort of middleaged OSAHS patients (average age: 47 years). Previous studies have reported that decreased time of REM sleep and slow wave sleep are associated with worsening cognitive performance, in elderly MCI and Alzheimer disease patients [26,27]. Our results extend these earlier researches and support the hypothesis of sleep disruption as a potential mechanism for neurocognitive impairment in OSAHS [2]. 5. Study limitations Our findings should be interpreted cautiously as it is an observational, single-center cohort study. The correlation of elevated oxidative stress with the development of neurocognitive impairment in OSAHS patients warrants future investigations in large size patient studies, including the longitudinal and/or interventional studies. 6. Conclusions The
current
study
demonstrated
that
neurocognitive
29
impairment in moderate-to-severe Chinese OSAHS patients is associated with significantly elevated oxidative stress, and IMA might be a useful oxidative stress biomarker correlated with MCI in OSAHS patients. Conflict of interest The authors have indicated no financial conflicts of interest. Acknowledgment This study was supported by research grants from Natural Science Foundation of China (81270147) and the National Key Technology Research and Development Program of the Ministry of Science and Technology of China as part of its “12th Five-Year Plan” (2012BAI05B02). References [1] J.A. Dempsey, S.C. Veasey, B.J. Morgan, et al., Pathophysiology of sleep apnea, Physiol. Rev. 90 (2010) 47e112. [2] R. Chen, K.P. Xiong, J.Y. Huang, et al., Neurocognitive impairment in Chinese patients with obstructive sleep apnea hypopnea Syndrome, Respirology 16 (2011) 842e848. [3] R.S. Bucks, M. Olaithe, P. Eastwood, Neurocognitive function in obstructive sleep apnoea: a meta review, Respirology 18 (2013) 61e70. [4] T.J.A. Vaessen, S. Overeem, M.M. Sitskoorn, Cognitive complaints in obstructive sleep apnea, Sleep. Med. Rev. 19 (2015) 51e58. [5] S.A. Kielb, S. Ancoli-Israel, G.W. Rebok, et al., Cognition in obstructive sleep apnea-hypopnea syndrome (OSAS): current clinical knowledge and the impact of treatment, Neuromol. Med. 14 (2012) 180e193. [6] I. Rosenzweig, S.C. Williams, M.J. Morrell, The impact of sleep and hypoxia on the brain: potential mechanisms for the effects of obstructive sleep apnea, Curr. Opin. Pulm. Med. 20 (2014) 565e571. [7] I. Rosenzweig, M. Glasser, D. Polsek, et al., Sleep apnoea and the brain: a complex relationship, Lancet Respir. Med. 3 (2015) 404e414. [8] M.A. Daulatzai, Evidence of neurodegeneration in obstructive sleep apnea: relationship between obstructive sleep apnea and cognitive dysfunction in the elderly, J. Neurosci. Res. 93 (2015) 1778e1794. [9] Y. Wang, S.X.L. Zhang, D. Gozal, Reactive oxygen species and the brain in sleep apnea, Respir. Physiol. Neurobiol. 174 (2010) 307e316. [10] T. Kizawa, Y. Nakamura, S. Takahashi, et al., Pathogenic role of angiotensin II and oxidised LDL in obstructive sleep apnoea, Eur. Respir. J. 34 (2009) 1390e1398. [11] M. Mancuso, E. Bonanni, A. LoGerfo, et al., Oxidative stress biomarkers in patients with untreated obstructive sleep apnea syndrome, Sleep. Med. 13 (2012) 632e636. [12] L.V. Sales, V.M. Bruin, V. D'Almeida, et al., Cognition and biomarkers of oxidative stress in obstructive sleep apnea, Clin. (Sao Paulo) 68 (2013) 449e455. [13] M. Kaefer, S.J. Piva, J.A. De Carvalho, et al., Association between ischemia modified albumin, inflammation and hyperglycemia in type 2 diabetes mellitus, Clin. Biochem. 43 (2010) 450e454. [14] J. Zuwała-Jagiełło, M. Warwas, M. Pazgan-Simon, Ischemia-modified albumin (IMA) is increased in patients with chronic hepatitis C infection and related to markers of oxidative stress and inflammation, Acta Biochim. Pol. 59 (2012) 661e667. [15] E. Altunoglu, G. Guntas, F. Erdenen, et al., Ischemia modified albumin and advanced oxidation protein products as potential biomarkers of protein oxidation in Alzheimer's disease, Geriatr. Gerontol. Int. 15 (2015) 872e880. [16] M. Can, F. Varlibas, B. Guven, et al., Ischemia modified albumin and plasma oxidative stress markers in Alzheimer's disease, Eur. Neurol. 69 (2013) 377e380. dirian, et al., The Montreal Cognitive [17] Z.S. Nasreddine, N.A. Phillips, V. Be Assessment, MoCA: a brief screening tool for mild cognitive impairment, J. Am. Geriatr. Soc. 53 (2005) 695e699. [18] American Academy of Sleep Medicine, The International Classification of Sleep Disorders: Diagnostic and Coding Manual, second ed., American Academy of Sleep Medicine, Westchester, IL, 2005. [19] R.B. Berry, R. Budhiraja, D.J. Gottlieb, et al., Rules for scoring respiratory events in sleep: update of the 2007 AASM manual for the scoring of sleep and associated events, J. Clin. Sleep. Med. 8 (2012) 597e619. [20] R.C. Petersen, R. Doody, A. Kurz, et al., Current concepts in mild cognitive impairment, Arch. Neurol. 58 (2001) 1985e1992. [21] M.W. Johns, A new method for measuring daytime sleepiness: the Epworth sleepiness scale, Sleep 14 (1991) 540e545. [22] M.F. Folstein, S.E. Folstein, P.R. McHugh, “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician, J. Psychiatr. Res. 12 (1975) 189e198.
30
Y. He et al. / Respiratory Medicine 120 (2016) 25e30
[23] M. Olaithe, R.S. Bucks, Executive dysfunction in OSA before and after treatment: a meta-analysis, Sleep 36 (2013) 1297e1305. [24] E. Crawford-Achour, V. Dauphinot, M.S. Martin, et al., Protective effect of longterm CPAP therapy on cognitive performance in elderly patients with severe OSA: the PROOF study, J. Clin. Sleep. Med. 11 (2015) 519e524. [25] L.X. Yang, S.G. Ma, H. Liu, et al., Influence of obstructive sleep apnea on serum butyrylcholinesterase activity and ischemia-modified albumin levels, Clin.
(Sao Paulo) 68 (2013) 968e973. [26] Y. Song, T. Blackwell, K. Yaffe, et al., Relationships between sleep stages and changes in cognitive function in older men: the MrOS sleep study, Sleep 38 (2014) 411e421. [27] M. Maestri, L. Carnicelli, G. Tognoni, et al., Non-rapid eye movement sleep instability in mild cognitive impairment: a pilot study, Sleep. Med. 16 (2015) 1139e1145.
Contents lists available at ScienceDirect
Respiratory Medicine journal homepage: www.elsevier.com/locate/rmed
Neurocognitive impairment is correlated with oxidative stress in patients with moderate-to-severe obstructive sleep apnea hypopnea syndrome Yanyu He a, b, Rui Chen a, b, *, Jing Wang a, b, Wenying Pan a, b, Yanqiu Sun a, b, Fei Han a, c, Qiaojun Wang a, c, Chunfeng Liu a, c, d a
Sleep Center, The Second Affiliated Hospital of Soochow University, Soochow University, Suzhou, China Department of Respiratory Medicine, The Second Affiliated Hospital of Soochow University, Soochow University, Suzhou, China Department of Neurology, The Second Affiliated Hospital of Soochow University, Soochow University, Suzhou, China d Laboratory of Aging and Nervous Diseases, Institute of Neuroscience, Soochow University, Suzhou, China b c
a r t i c l e i n f o
a b s t r a c t
Article history: Received 22 June 2016 Received in revised form 5 September 2016 Accepted 8 September 2016 Available online 9 September 2016
Background and objectives: Patients with obstructive sleep apnea hypopnea syndrome (OSAHS) are associated with increased risk of neurocognitive impairment, which are largely recognized as mild cognitive impairment (MCI), and oxidative stress is postulated as one of the underlying mechanisms. This study aimed to investigate the relationship between MCI and oxidative stress biomarkers in OSAHS. Methods: A total of 119 middle-aged patients with moderate-to-severe OSAHS were included. Based on the baseline Montreal Cognitive Assessment (MoCA, validated Chinese version), 86 and 33 patients presented with normal cognitive function (NC, MoCA 26) and mild cognitive impairment (MCI, MoCA <26), respectively. Overnight PSG, MoCA and serum levels of ischemia-modified albumin (IMA), malondialdehyde (MDA) and advanced oxidation protein products (AOPP) were collected and analyzed. Results: Compared to NC group, patients with MCI were characterized with significantly greater waistto-height ratio, AHI, ODI and time ratio of SpO2<90%, and lower average SpO2 and time ratio of rapid eye movement (REM). All three oxidative stress biomarkers were markedly elevated in MCI group. Binary logistic regression analysis demonstrated that MCI is significantly correlated with serum levels of IMA, REM ratio and the age of patients. Conclusions: The neurocognitive impairment in moderate-to-severe OSAHS patients is associated with significantly elevated oxidative stress. IMA might be a new useful biomarker correlated with mild cognitive impairment of the patients. © 2016 Published by Elsevier Ltd.
Keywords: Obstructive sleep apnea hypopnea syndrome Cognitive impairment Oxidative stress Ischemia-modified albumin Polysomnography
1. Introduction Obstructive sleep apnea hypopnea syndrome (OSAHS) is one of the sleep-disordered breathing diseases characterized by recurrent episodes of increased upper airway resistance during sleep, leading to spells of apnea/hypopnea and nocturnal sleep fragmentation. It is known to be associated with significantly increased risk of mortality and morbidities that includes cardiovascular and cerebrovascular diseases, metabolic derangement and neurocognitive
* Corresponding author. Department of Respiratory Medicine, The Second Affiliated Hospital of Soochow University, No. 1055, Sanxiang Road, Suzhou, 215004, China. E-mail address: [email protected] (R. Chen). http://dx.doi.org/10.1016/j.rmed.2016.09.009 0954-6111/© 2016 Published by Elsevier Ltd.
impairment [1], the latter of which has recently been increasingly recognized. Untreated OSAHS has been reported with deficits in attention span, divided and sustained attention, working memory, and visuospatial and executive function [2e4]. As reported in our previous work, mild cognitive impairment (MCI) has been the nonnegligible manifestation of cognitive dysfunction in OSAHS patients, and Montreal Cognitive Assessment (MoCA) questionnaire can be used as a simple and sensitive neurocognitive assessment instrument to detect this damage [2]. The underlying mechanisms of neurocognitive impairment associated with sleep apnea may include intermittent hypoxemia, sleep fragmentation, neuroinflammation, cerebrovascular change, and ischemic preconditioning [5e7]. The role of oxidative stress in OSAHS-related cognitive deficit has also been postulated [8,9],
26
Y. He et al. / Respiratory Medicine 120 (2016) 25e30
Abbreviations AHI AOPP BMI ESS IMA MoCA MCI MDA MMSE NC NREM OSAHS PSG REM SpO2 WHR
apnea/hyponea index advanced oxidation protein products body mass index Epworth sleepiness scale ischemia-modified albumin Montreal Cognitive Assessment mild cognitive impairment malondialdehyde Mini-mental state examination normal cognition non-rapid eye movement obstructive sleep apnea hypopnea syndrome polysomnography rapid eye movement pulse oxygen saturation waist-to-height ratio
however, few studies have examined an array of standard and novel biomarkers of oxidative stress and controversy still remains regarding the best biomarker specific for cognitive function in OSAHS patients. Compared to a number of well-established serum oxidative stress biomarkers such as glutathione, superoxide dismutase, malondialdehyde (MDA) and advanced oxidation protein products (AOPP) [10e12], ischemia-modified albumin (IMA) is a novel oxidative stress indicator recently reported in type 2 diabetes mellitus and infectious diseases [13,14], and most interestingly, has been lately demonstrated to be closely correlated with the neurocognitive impairment in Alzheimer's disease [15,16]. In this observational study, the cognitive function of middleaged Chinese patients with moderate-to-severe OSAHS without dementia was evaluated by MoCA [17] to detect and characterize MCI and also the changes in various neuropsychological subdomains. The serum levels of oxidative stress biomarkers including IMA, MDA and AOPP were measured and the correlations between MoCA scores with the clinical & polysomnographic parameters and oxidative stress biomarker levels were investigated in particular.
2. Methods 2.1. Patient eligibility A total of 119 eligible patients were selected from a cohort of consecutive Chinese patients diagnosed of OSAHS by overnight polysomnography (PSG) in our sleep laboratory from February 2014 to October 2014. The major inclusion criteria contained newly diagnosed moderate-to-severe OSAHS (AHI 15 event/h) without prior history of surgical, orthodontic or CPAP treatment for OSAHS, age of 30e60 years old and minimal requirement of primary school education. The exclusion criteria included: (i) presence of other sleep disorders based on ICSD-II diagnosis [18], such as central sleep apnea, restless legs syndrome, rapid eye movement (REM)sleep behavioral disorder, periodic limb movement disorder and narcoleptic spectral disorder; (ii) Alzheimer's disease, vascular dementia, Parkinson's disease, anxiety, depression or other mental or central nervous system (CNS) diseases, and/or any other conditions requiring pharmacotherapies impacting the mental status or CNS within the last 3 months; (iii) new onset cardiovascular or cerebrovascular accidents within the last 3 months, chronic heart failure, recent infectious diseases, or prior history of malignancy;
(iv) other diseases with abnormal liver, kidney and/or lung function. 2.2. Polysomnographic assessment Overnight PSG (Compumedics, Australia) was performed in an attended setting for all patients at the first night of admission starting from 10 p.m. to 6 a.m. next morning, and at least 7 h of recording time was considered a successful monitoring. The PSG assessments included the following indexes: airflow by using oronasal thermistors and nasal pressure transducer, thoracic and abdominal respiratory movements, arterial oxygen saturation by pulse oximetry, snoring and body position, electroencephalogram (C3/A2, C4/A1, O1/A2, and O2/A1), electrooculogram, chin and leg electromyogram and electrocardiogram. A panel of polysomnographic variables were obtained, which included AHI, oxygen desaturation index (ODI, defined as the sum of the numbers of oxyhemoglobin desaturation of >4% events per hour of sleep), time ratio of SpO2<90% (T90), minimum pulse oxygen saturation (MSpO2), average oxygen saturation (ASpO2), total sleep time (TST), non-rapid eye movement (NREM) sleep phases 1e3, and REM sleep. AHI was defined as the sum of the numbers of apnea or hypopnea events per hour of sleep. Apneas were scored when there was a complete cessation of airflow or 90% drop in the peak thermal sensor excursion for at least 10 s. Hypopneas were scored when there was a drop in nasal pressure signal excursion by 30% of baseline lasting at least 10 s with a 4% desaturation from preevent baseline, or when there was a drop in nasal pressure signal excursion by 50% of baseline lasting at least 10 s with a 3% desaturation from pre-event baseline and/or the event associated with arousal. All PSG studies were analyzed by trained technicians and sleep physicians according to the criteria of the American Academy of Sleep Medicine 2012 [19]. 2.3. Montreal cognitive assessment A Chinese version of the MoCA questionnaire (Beijing version) based on the final English version was used in this study (Beijing version and English version of MoCA are available at http://www. mocatest.org with no permission requirements as declared). MoCA is a 30-point test covering seven cognitive subdomains: (i) visuospatial and executive; (ii) naming; (iii) memory; (iv) attention; (v) language; (vi) abstraction; (vii) delayed recall; and (viii) orientation. A bonus point is given to individuals with <12 years of education. MoCA <26 is considered to be indicative of MCI, otherwise normal cognition function (NC), which was reported with sensitivity of 90% and specificity of 87% [17]. 2.4. Mini-mental state examination (MMSE) A Chinese version of MMSE questionnaire was administered to all the patients. MMSE 27 is considered to be normal. And MMSE 20 was found essentially only in patients with dementia, delirium, schizophrenia or affective disorder as reported when they at least finish their primary school [20]. 2.5. Epworth sleepiness scale (ESS) A validated Chinese version of the ESS questionnaire [21], with eight items and 4-point scale (0e3), which was used in our previous clinical study of OSAHS [2], was also administered to all patients. It is allowed to use under dedicated clinical research (http:// epworthsleepinessscale.com).
Y. He et al. / Respiratory Medicine 120 (2016) 25e30
2.6. Serum oxidative stress biomarker assays Samples of 4 ml venous blood were collected in the morning after overnight PSG of which the serum were then stored at 80 C prior to analyses. Serum levels of the oxidative stress biomarkers including both the novel (IMA) and more standard (MDA and AOPP) biomarkers were measured using the commercial ELISA kits (R&D, America).
2.7. Statistics The data were presented as mean ± standard deviation (SD) unless otherwise noted. Statistical testings between the two groups (NC vs. MCI) were carried out by Student's t-test, non-parametric test (Mann-Whitney) or Chi-square test when appropriate. Pearson and partial correlation analysis and binary logistic regression analysis were performed to investigate the relationships between MoCA scores against the clinical variables, serum biomarker and PSG parameters. All statistical analyses were conducted using SPSS 17.0 software for Windows. All probabilities were 2-tailed, and values of p < 0.05 were considered statistically significant.
Table 1 Sociodemographic and clinical characteristics of moderate-to-severe OSAHS patients.
Age, years Gender, Male n (%) Education, years Smoker, n (%) Alcohol user, n (%) Medical history Hypertension, n (%) Arrhythmia, n (%) Stroke, n (%) Diabetes, n (%) WHR WHR 0.56, n (%) BMI (kg/m2) BMI 30, n (%)
3. Results 3.1. Patient distribution Among the 119 eligible patients from the total of 265 patients screened, 43 of them were diagnosed with moderate OSAHS (AHI 15/h - <30/h) whereas the remaining 76 patients had severe OSAHS (AHI 30/h). According to the baseline MoCA scores, 72% of enrolled patients (N ¼ 86) presented with normal cognition function (NC, MoCA 26) compared to 28% (N ¼ 33) associated with mild cognitive impairment (MCI, MoCA <26) (Table 1). While a total of 19 patients (16%) had a MMSE score <27, no patients presented with baseline MMSE score 20 qualifying for dementia, and they all finished their primary school. (Table 2).
3.2. Sociodemographic and clinical characteristics of OSAHS patients with and without MCI The overall patient in this study was representative of a middleaged population (mean age of 47.46 ± 11.02 years), and predominantly male (104/119, 87%) with a mean education experience of 11.99 ± 3.29 years and a mean BMI of 27.13 ± 2.60 kg/m2 (17% with BMI 30 kg/m2). The baseline demographic and clinical characteristics between the NC and MCI groups are summarized in Table 1. There was no difference in age, gender, education level, smoking or alcohol user, or prior medical histories between the two groups. The waist-toheight ratio (WHR) was significantly greater in the MCI group (0.57 ± 0.06) compared to the NC group (0.55 ± 0.05), associated with higher proportion of patients with WHR 0.56, the median WHR value in this overall patient cohort (64% vs. 43% in the NC group), and BMI 30 kg/m2 (27% vs. 13% in the NC group) in the MCI group.
NC (N ¼ 86)
MCI (N ¼ 33)
P value
46.37 ± 10.96 78 (93.44) 12.21 ± 3.45 41(47.67) 29 (33.72)
50.30 ± 10.81 26 (78.79) 11.42 ± 2.78 11 (33.33) 14(42.42)
0.081 0.119 0.245 0.158 0.376
47 (54.65) 1 (1.16) 1 (1.16) 4 (4.65) 0.55 ± 0.04 37 (43.02) 26.95 ± 2.49 11 (12.79)
17 (51.51) 2 (6.06) 1 (3.03) 3 (9.09) 0.57 ± 0.06* 21 (63.64)* 27.62 ± 2.86 9 (27.27)
0.758 0.186 0.479 0.395 0.011 0.044 0.210 0.059
Data are expressed as mean ± SD, n (%) or as indicated. *p < 0.05 compared to the NC group. NC, normal cognitive function; MCI, mild cognitive impairment; WHR, waist-toheight ratio; BMI, body mass index.
Table 2 Comparisons of neurocognitive assessments by MoCA and ESS scores in NC and MCI groups of patients.
2.8. Ethics The study was approved by our institutional ethics board (approval # 2014K07), and all patients were informed and gave consent prior to the study procedures.
27
MoCA Overall score Subdomains Visuospatial/executive Naming Attention Language Abstraction Delayed recall Orientation MMSE Mean ± SD Medium Minimum, Maximum ESS
NC (N ¼ 86)
MCI (N ¼ 33)
P values
27.52 ± 1.28
23.24 ± 1.75
e
4.24 2.97 5.88 2.62 1.69 3.78 5.99
± ± ± ± ± ± ±
0.77 0.19 0.50 0.69 0.49 0.77 0.11
29.28 ± 0.94 30 27, 30 8.42 ± 4.83
2.82 2.73 5.42 2.06 1.15 2.55 5.97
± ± ± ± ± ± ±
0.98 0.45 0.71 0.78 0.67 1.25 0.17
25.97 ± 2.71 26 21, 30 11.48 ± 4.61
<0.001 0.006 0.001 <0.001 <0.001 <0.001 0.482 <0.001
0.002
Data are presented as mean ± SD and/or median (minimum, maximum). MoCA, Montreal cognitive assessment; MMSE, Mini-mental state examination; ESS: Epworth sleepiness scale.
3.3. Neurocognitive profiles of OSAHS patients with and without MCI As described in Table 2, patients in the MCI group compared to the NC group were associated with statistically and clinically significant worse scores of the MoCA questionnaires. In particular, the MoCA scores in the MCI group were significantly lower in both the overall (23.24 ± 1.75 vs. 27.52 ± 1.28 in the NC group) and also most of the cognitive subdomain scores except the orientation subdomain. The MMSE scores were also significantly lower in the MCI group, while the ESS scores were significantly higher (Table 2). 3.4. Comparisons of PSG parameters and serum oxidative stress biomarkers in OSAHS patients with and without MCI The comparisons for PSG parameters between NC and MCI groups are summarized in Table 3. Compared to the NC group, patients in the MCI group were characterized with statistically significantly higher AHI, ODI, and T90, and lower ASpO2 and the time ratio of REM (Table 3). The serum levels of three oxidative stress biomarkers were significantly elevated in the MCI group, compared to the NC group
28
Y. He et al. / Respiratory Medicine 120 (2016) 25e30 Table 3 Comparisons of polysomnographic parameters in NC and MCI groups of patients.
AHI (event/h) ODI (event/h) Minimum SpO2 (%) Average SpO2 (%) T90 (%) TST (min) NREM 1 þ 2 sleep phases (%) NREM 3 sleep phases (%) REM sleep phases (%)
NC (N ¼ 86)
MCI (N ¼ 33)
P values
40.01 ± 19.35 37.44 ± 20.65 75.05 ± 9.09 92.65 ± 2.79 11.65 (0.00,69.50) 421.32 ± 67.98 69.64 ± 10.41 12.87 ± 7.80 17.49 ± 5.52
53.66 ± 24.80 50.70 ± 26.91 71.54 ± 9.89 91.29 ± 3.10 22.40 (4.30,80.30) 422.21 ± 89.01 73.72 ± 8.81 11.48 ± 7.92 14.80 ± 4.91
0.006 0.014 0.069 0.023 0.003 0.954 0.048 0.388 0.016
Data are presented as mean ± SD, except for T90 as median (minimum, maximum). AHI, apnea hypopnea index; SpO2, pulse oxygen saturation; T90, time ratio of SpO2 <90%; TST, total sleep time; REM, rapid eye movement.
(Fig. 1), including IMA (104.56 ± 47.21 vs. 64.67 ± 22.65 kU/L in the NC group, p < 0.01; Fig. 1A), MDA (8.87 ± 6.34 vs. 5.45 ± 2.80 nmol/ mL in the NC group, p < 0.01; Fig. 1B) and AOPP (108.16 ± 54.32 vs. 80.98 ± 34.89 mmol/L in the NC group, p < 0.05; Fig. 1C). 3.5. Correlation of clinical variables and serum oxidative stress biomarkers with MoCA scores To investigate the relationships between MoCA-assessed neurocognitive function with an array of sociodemographic and clinical variables as well as oxidative stress biomarkers, Pearson correlation analysis was performed which demonstrated that the MoCA scores was positively correlated with education level (p < 0.05), and negatively correlated with age (p < 0.01). When the analysis was further adjusted for age and education level, the MoCA scores were negatively and significantly correlated with the level of IMA, MDA and AOPP (p < 0.001), and with the AHI, ODI and T90 as well (p < 0.05), whereas it was positively correlated with average SpO2 and time ratio of REM (p < 0.05) (Table 4). In addition, regression analyses were performed among the sociodemographic and clinical parameters, PSG parameters and serum biomarkers, and it revealed that MCI (MoCA<26) was significantly associated with IMA levels (odds ratio: 1.046, 95% CI: 1.025e1.066; p < 0.001), time ratio of REM (odds ratio: 0.859, 95% CI: 0.773e0.954; p < 0.01), and age (odds ratio: 1.061, 95% CI: 1.009e1.115; p < 0.05). 4. Discussion We conducted an observational study in 119 moderate-tosevere Chinese OSAHS patients to better understand the correlation between neurocognitive impairment and oxidative stress in
OSAHS. Our research provides several key findings that extend the current knowledge of OSAHS-induced neurocognitive impairment: 1) MCI is common in middle-aged moderate-to-severe OSAHS patients; 2) while OSAHS with MCI can be associated with an array of clinical and laboratory characteristics, a novel oxidative stress biomarker of IMA is the notable variable significantly associated with MCI, indicating the important role of oxidative stress underlying the OSAHS-induced neurocognitive impairment. It has been increasingly recognized in recent years that the neurocognitive deficits experienced by OSAHS patients are largely MCI, which is an intermediate clinical state between normal cognitive aging and dementia that precedes and eventually leads to the latter disease state in many cases [22]. Given the important clinical implication of MCI, early diagnosis with proper therapeutic interventions is clearly warranted. MCI can be detected by MoCA covering various important cognitive subdomains and administered to patients in 10e15 min by a healthcare professional. When MCI was defined as MoCA <26 points, it was reported with a sensitivity of 90% and a specificity of 87% in patients with mild Alzheimer's disease compared to healthy elderly controls [17]. We first investigated the clinical utility of MoCA and compared it to MMSE in a large cohort of Chinese patients with a primary compliant of snoring and clinical suspicion of OSAHS, and reported in 2011 that MCI was more common in the moderate (38.6%) and severe (41.4%) OSAHS patients than in patients with mild OSAHS (25.0%) and primary snoring (15.2%) [2]. In the current study, 28% middle-aged OSAHS patients presented with MCI as detected by MoCA (<26), higher than 16% as assessed by MMSE score <27, which is consistent with our previous report. When compared to those with normal cognitive function, the MocA scores were significantly reduced in MCI patients across both the overall and subdomain scores of visuospatial/executive, naming, attention,
Fig. 1. Comparisons of serum levels of oxidative stress biomarkers between NC and MCI group of patients. Data are expressed at mean ± SD. IMA, ischemia-modified albumin; MDA, malondialdehyde; AOPP, advanced protein oxidation products.
Y. He et al. / Respiratory Medicine 120 (2016) 25e30 Table 4 Partial correlation analyses between MoCA scores and the oxidative stress biomarkers and PSG parameters. MDA
AOPP
IMA
AHI
ODI
T90
REM
ASpO2
r 0.332 0.382 0.475 0.240 0.192 0.206 0.197 0.183 P value <0.001 <0.001 <0.001 0.009 0.039 0.026 0.034 0.049 Analyses are adjusted for patients' age and education level. ASpO2, average pulse oxygen saturation; r, correlation coefficient.
language, abstraction and delayed recall. Our results are consistent with the deficits in attention, memory and executive dysfunctions reported in the OSAHS patients [5,23,24]. This important finding underscores the paradigm that MCI is fairly common even in middle-aged OSAHS patients and highlight the importance of early diagnosis and interventions. The underlying mechanisms contributing to the OSAHS-induced neurocognitive impairment remain poorly defined. We observed that, in a cohort of middle-aged moderate-to-severe Chinese OSAHS patients, the MCI patients were associated with greater abdominal obesity, nocturnal hypoxia, lower time ratio of REM stage, and significantly elevated serum levels of oxidative stress biomarkers when compared to NC group. These results implicate the multifaceted mechanisms of MCI in OSAHS. When regression analyses were performed among the sociodemographic and clinical parameters, PSG variables and serum biomarkers, it demonstrated that MCI (MoCA <26) was significantly and independently correlated with the IMA level, a finding further supporting and substantiating the role of oxidative stress underlying the development of MCI in OSAHS. Three oxidative stress biomarkers were evaluated in our study. The MDA and AOPP are well-established standard biomarkers related to lipid peroxidation and protein oxidation, respectively [10,11]. IMA is a novel biomarker of oxidative stress, and has been found to be closely correlated with the neurocognitive decline in Alzheimer's disease [15,16]. Yang et al. recently reported that IMA level significantly increased in a group of 32 OSAHS patients compared to the healthy controls [25]. Our results extend these previous studies and, for the first time, suggest its potential value as a more specific biomarker related to cognitive impairment in OSAHS. More research is clearly warranted to evaluate the unique relationship and underlying mechanisms between IMA elevation and MCI. The present study also demonstrated that MCI was independently associated with the time ratio of REM in a cohort of middleaged OSAHS patients (average age: 47 years). Previous studies have reported that decreased time of REM sleep and slow wave sleep are associated with worsening cognitive performance, in elderly MCI and Alzheimer disease patients [26,27]. Our results extend these earlier researches and support the hypothesis of sleep disruption as a potential mechanism for neurocognitive impairment in OSAHS [2]. 5. Study limitations Our findings should be interpreted cautiously as it is an observational, single-center cohort study. The correlation of elevated oxidative stress with the development of neurocognitive impairment in OSAHS patients warrants future investigations in large size patient studies, including the longitudinal and/or interventional studies. 6. Conclusions The
current
study
demonstrated
that
neurocognitive
29
impairment in moderate-to-severe Chinese OSAHS patients is associated with significantly elevated oxidative stress, and IMA might be a useful oxidative stress biomarker correlated with MCI in OSAHS patients. Conflict of interest The authors have indicated no financial conflicts of interest. Acknowledgment This study was supported by research grants from Natural Science Foundation of China (81270147) and the National Key Technology Research and Development Program of the Ministry of Science and Technology of China as part of its “12th Five-Year Plan” (2012BAI05B02). References [1] J.A. Dempsey, S.C. Veasey, B.J. Morgan, et al., Pathophysiology of sleep apnea, Physiol. Rev. 90 (2010) 47e112. [2] R. Chen, K.P. Xiong, J.Y. Huang, et al., Neurocognitive impairment in Chinese patients with obstructive sleep apnea hypopnea Syndrome, Respirology 16 (2011) 842e848. [3] R.S. Bucks, M. Olaithe, P. Eastwood, Neurocognitive function in obstructive sleep apnoea: a meta review, Respirology 18 (2013) 61e70. [4] T.J.A. Vaessen, S. Overeem, M.M. Sitskoorn, Cognitive complaints in obstructive sleep apnea, Sleep. Med. Rev. 19 (2015) 51e58. [5] S.A. Kielb, S. Ancoli-Israel, G.W. Rebok, et al., Cognition in obstructive sleep apnea-hypopnea syndrome (OSAS): current clinical knowledge and the impact of treatment, Neuromol. Med. 14 (2012) 180e193. [6] I. Rosenzweig, S.C. Williams, M.J. Morrell, The impact of sleep and hypoxia on the brain: potential mechanisms for the effects of obstructive sleep apnea, Curr. Opin. Pulm. Med. 20 (2014) 565e571. [7] I. Rosenzweig, M. Glasser, D. Polsek, et al., Sleep apnoea and the brain: a complex relationship, Lancet Respir. Med. 3 (2015) 404e414. [8] M.A. Daulatzai, Evidence of neurodegeneration in obstructive sleep apnea: relationship between obstructive sleep apnea and cognitive dysfunction in the elderly, J. Neurosci. Res. 93 (2015) 1778e1794. [9] Y. Wang, S.X.L. Zhang, D. Gozal, Reactive oxygen species and the brain in sleep apnea, Respir. Physiol. Neurobiol. 174 (2010) 307e316. [10] T. Kizawa, Y. Nakamura, S. Takahashi, et al., Pathogenic role of angiotensin II and oxidised LDL in obstructive sleep apnoea, Eur. Respir. J. 34 (2009) 1390e1398. [11] M. Mancuso, E. Bonanni, A. LoGerfo, et al., Oxidative stress biomarkers in patients with untreated obstructive sleep apnea syndrome, Sleep. Med. 13 (2012) 632e636. [12] L.V. Sales, V.M. Bruin, V. D'Almeida, et al., Cognition and biomarkers of oxidative stress in obstructive sleep apnea, Clin. (Sao Paulo) 68 (2013) 449e455. [13] M. Kaefer, S.J. Piva, J.A. De Carvalho, et al., Association between ischemia modified albumin, inflammation and hyperglycemia in type 2 diabetes mellitus, Clin. Biochem. 43 (2010) 450e454. [14] J. Zuwała-Jagiełło, M. Warwas, M. Pazgan-Simon, Ischemia-modified albumin (IMA) is increased in patients with chronic hepatitis C infection and related to markers of oxidative stress and inflammation, Acta Biochim. Pol. 59 (2012) 661e667. [15] E. Altunoglu, G. Guntas, F. Erdenen, et al., Ischemia modified albumin and advanced oxidation protein products as potential biomarkers of protein oxidation in Alzheimer's disease, Geriatr. Gerontol. Int. 15 (2015) 872e880. [16] M. Can, F. Varlibas, B. Guven, et al., Ischemia modified albumin and plasma oxidative stress markers in Alzheimer's disease, Eur. Neurol. 69 (2013) 377e380. dirian, et al., The Montreal Cognitive [17] Z.S. Nasreddine, N.A. Phillips, V. Be Assessment, MoCA: a brief screening tool for mild cognitive impairment, J. Am. Geriatr. Soc. 53 (2005) 695e699. [18] American Academy of Sleep Medicine, The International Classification of Sleep Disorders: Diagnostic and Coding Manual, second ed., American Academy of Sleep Medicine, Westchester, IL, 2005. [19] R.B. Berry, R. Budhiraja, D.J. Gottlieb, et al., Rules for scoring respiratory events in sleep: update of the 2007 AASM manual for the scoring of sleep and associated events, J. Clin. Sleep. Med. 8 (2012) 597e619. [20] R.C. Petersen, R. Doody, A. Kurz, et al., Current concepts in mild cognitive impairment, Arch. Neurol. 58 (2001) 1985e1992. [21] M.W. Johns, A new method for measuring daytime sleepiness: the Epworth sleepiness scale, Sleep 14 (1991) 540e545. [22] M.F. Folstein, S.E. Folstein, P.R. McHugh, “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician, J. Psychiatr. Res. 12 (1975) 189e198.
30
Y. He et al. / Respiratory Medicine 120 (2016) 25e30
[23] M. Olaithe, R.S. Bucks, Executive dysfunction in OSA before and after treatment: a meta-analysis, Sleep 36 (2013) 1297e1305. [24] E. Crawford-Achour, V. Dauphinot, M.S. Martin, et al., Protective effect of longterm CPAP therapy on cognitive performance in elderly patients with severe OSA: the PROOF study, J. Clin. Sleep. Med. 11 (2015) 519e524. [25] L.X. Yang, S.G. Ma, H. Liu, et al., Influence of obstructive sleep apnea on serum butyrylcholinesterase activity and ischemia-modified albumin levels, Clin.
(Sao Paulo) 68 (2013) 968e973. [26] Y. Song, T. Blackwell, K. Yaffe, et al., Relationships between sleep stages and changes in cognitive function in older men: the MrOS sleep study, Sleep 38 (2014) 411e421. [27] M. Maestri, L. Carnicelli, G. Tognoni, et al., Non-rapid eye movement sleep instability in mild cognitive impairment: a pilot study, Sleep. Med. 16 (2015) 1139e1145.