Impact of obstructive sleep apnea on silent cerebral small vessel disease: a systematic review and meta-analysis

Journal Pre-proof Impact of Obstructive Sleep Apnea on Silent Cerebral Small Vessel Disease: A Systematic Review and Meta-analysis Anthipa Chokesuwattanaskul, MD, Ploypin Lertjitbanjong, MD, Charat Thongprayoon, MD, Tarun Bathini, MD, Konika Sharma, MB, BS, Michael A. Mao, MD, Wisit Cheungpasitporn, MD, Ronpichai Chokesuwattanaskul, MD PII:

S1389-9457(19)31649-1

DOI:

https://doi.org/10.1016/j.sleep.2019.11.1262

Reference:

SLEEP 4256

To appear in:

Sleep Medicine

Received Date: 28 August 2019 Revised Date:

28 October 2019

Accepted Date: 27 November 2019

Please cite this article as: Chokesuwattanaskul A, Lertjitbanjong P, Thongprayoon C, Bathini T, Sharma K, Mao MA, Cheungpasitporn W, Chokesuwattanaskul R, Impact of Obstructive Sleep Apnea on Silent Cerebral Small Vessel Disease: A Systematic Review and Meta-analysis, Sleep Medicine, https:// doi.org/10.1016/j.sleep.2019.11.1262. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier B.V.

Impact of Obstructive Sleep Apnea on Silent Cerebral Small Vessel Disease: A Systematic Review and Meta-analysis Article type: Original article Authors: Anthipa Chokesuwattanaskul, MD1,2*, Ploypin Lertjitbanjong, MD3, Charat Thongprayoon, MD4, Tarun Bathini, MD5, Konika Sharma, MB, BS3, Michael A Mao, MD6, Wisit Cheungpasitporn, MD7, Ronpichai Chokesuwattanaskul, MD2,8 1

Division of Neurology, Faculty of Medicine, Chulalongkorn University and King Chulalongkorn Memorial Hospital, Bangkok, Thailand 2 King Chulalongkorn Memorial Hospital, Thai Red Cross Society, Bangkok, Thailand 3 Department of Internal Medicine, Bassett Medical Center, Cooperstown, NY, USA 4 Department of Internal Medicine Mayo Clinic, Rochester, MN, USA 5 Department of Internal Medicine, University of Arizona, Tucson, AZ, USA 6 Department of Internal Medicine, Mayo Clinic, Jacksonville, FL 32224, USA 7 Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA 8 Department of Medicine, Faculty of Medicine, Chulalongkorn University and King Chulalongkorn Memorial Hospital, Bangkok, Thailand *Corresponding author; Anthipa Chokesuwattanaskul, MD, Address: King Chulalongkorn Memorial Hospital, Bangkok, Thailand Tel: (66) 2-256-4265; Fax: (66) 2-256-4356 E-mail: [email protected]

Running Head: Sleep Apnea and Cerebral Small Vessel Disease. Word count: 2,685 words

Abstract Background: Cerebral small vessel disease (CSVD) is a well-known cause of vascular dementia, a leading medical morbidity in the aging population. Obstructive sleep apnea (OSA) has been validated as a cardiovascular risk factor. However, the relationship between these two clinical syndromes is not well established. We aimed to assess the association between OSA and CSVD. Methods: Databases were searched from inception through May 2019. Studies that reported incidence or odd ratios of CSVD in patients with OSA were included. Effect estimates from the individual studies were extracted and combined using random-effect, generic inverse variance method of DerSimonian and Laird. Results: Fourteen observational studies comprising of 4,335 patients were included into the analysis. Compared to patients without OSA, patients with OSA were significantly associated with CSVD MRI findings of white matter hyperintensity (WMH) and asymptomatic lacunar infarction (ALI) with a pooled OR of 2.31 (95% CI, 1.46-3.66, I2 =79%) and 1.78 (95% CI, 1.063.01, I2 =41%), respectively. However, there was no significant association between OSA and findings of cerebral microbleeds (CMBs), with a pooled OR of 2.15 (95% CI, 0.64-7.29, I2 =55%). Conclusions: Our study demonstrated the association between OSA and CSVD MRI findings of white matter hyperintensity (WMH) and asymptomatic lacunar infarction (ALI) when compared to patients without OSA. The absence of an association of CMBs findings with OSA could be due either by a lower sensitivity of neuroimaging techniques utilized to detect CMBs or a potentially different pathogenesis of CMBs. Keywords: Cerebral Infarction; Meta-analysis; Microbleed; Obstructive sleep apnea; Stroke; White matter.

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1. Introduction Cerebrovascular disease has emerged as one of the leading cause of morbidity and mortality worldwide. Cerebral small vessel disease (CSVD), or disease of the small arteries, arterioles, capillaries and veins of the brain, causes up to a quarter of all ischemic strokes and is one of the main causes of vascular dementia (VaD) (1). The presentation of CSVD ranges from silent findings on neuroimaging (such as white matter hyperintensities (WMH), asymptomatic lacunar infarction (ALI), enlarged perivascular spaces (PVS), cerebral microbleeds (CMBs) and cerebral atrophy) to symptomatic stroke and dementia (2, 3). Although the clinical relevance of the so-called silent lesions are not well-established, they have been linked to an increased risk of stroke, cognitive impairment, dementia, gait problems, urinary problem, mood disorders and death (4-9). As CSVD is a slowly progressive disease, there is merit in early detection and timely treatment of associated causes in its asymptomatic stage to prevent occurrence of future symptomatic cerebrovascular disease (1). Currently, obstructive sleep apnea (OSA) is a known risk factor of several cardiovascular diseases such as arrhythmia, myocardial infarction and stroke (10). However, its particular relationship to CSVD is not well-established. In recent years, with the availability of magnetic resonance imaging (MRI) of the brain, several studies have started to explore the association of OSA specifically with CSVD neuroimaging features as surrogate outcomes, such as WMH, ALI or CMBs, in order to detect CSVD at its early or subclinical stage. So far, the results from these association studies are still inconclusive (11-13). This study aims to investigate the prevalence and association of OSA with asymptomatic CSVD neuroimaging features consisting of WMH, ALI and CMBs. A systematic review and meta-analysis of the relevant published literature was performed for this goal. Cerebral atrophy

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was not a study endpoint because the pathological changes of cerebral atrophy are heterogenous and does not always reflect neuronal loss (3). PVS was not included due to the limited studies on PVS(14).

2. Method 2.1 Search Strategy and Literature review A systematic literature search of EMBASE (1988 to May 2019), Ovid MEDLINE (1946 to May 2019), and the Cochrane Database of Systematic Reviews (database inception to May 2019) was performed to assess the association of OSA on silent cerebrovascular diseases including WMH, ALI and CMBs. The systematic literature review was undertaken independently by two investigators (A.B. and R.C.) using a search approach that incorporated the terms “obstructive sleep apnea” OR “sleep apnoea" AND “silent cerebrovascular disease” OR “silent stroke” OR “silent ischemic stroke” OR “white matter hyperintensity” OR “asymptomatic lacunar infarct” OR “cerebral microbleed” OR “brain microbleed”. The search strategy in each database is provided in online supplementary data 1. The data for this systematic review and all potentially eligible studies from each database are publicly available through the Open Science Framework (URL: osf.io/3hk6g/). No language limitation was applied. A manual search for conceivably relevant studies using references of the included articles was also performed. This study was conducted by the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) statement (15), as provided in online supplementary data 2.

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2.2 Selection criteria To be included in the meta-analysis, studies were required to meet the following criteria: (i) observational studies including cohort, case-control, or cross-sectional studies, (ii) studied the effect of OSA on WMH, ALI or CMBs, (iii) outcome definition was provided, and it (iv) reported odds ratios (OR) or hazard ratios (HR) of any silent cerebrovascular diseases. Review articles and case reports were excluded from this meta-analysis. Retrieved articles were individually reviewed for eligibility by two investigators (A.B. and R.C.). Discrepancies were addressed and resolved by three other investigators (C.T., P.L., and W.C.) by common consensus. Inclusion was not limited by size of study. Newcastle-Ottawa quality assessment scale (16) was used to appraise the quality of each observational study.

2.3 Data abstraction Characteristics of the study including first author, study location, publication year, study design, demographic data of patients, CSVD outcome definition, follow up time, and confounder adjustment were retrieved. ORs and/or HRs reported in each study was extracted.

2.4 Statistical analysis Analyses were performed utilizing the Comprehensive Meta-Analysis 3.3 software (version 3; Biostat Inc, Englewood, NJ, USA). All included studies were combined into a pooled OR using a random-effects model, generic inverse variance method of DerSimonian and Laird (17). Given the possibility of between-study variance, we used a random-effects model rather than a fixed-effect model. Cochran’s Q test and I2 statistic were applied to determine the between-study heterogeneity. A value of I2 of 0% to 25% represents insignificant heterogeneity,

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26% to 50% low heterogeneity, 51% to 75% moderate heterogeneity and 76–100% high heterogeneity (18). The presence of publication bias was assessed by subjective inspection of both the funnel plot and Egger test (19).

3. Result A total of 75 potentially eligible articles were identified using our search strategy. After the exclusion of 20 articles because they were either vitro studies, animal studies, case reports, correspondences, or review articles, and exclusion of 10 articles due to being duplicates, 45 articles were left for full-length review. Twenty of these were excluded from full-length review as they did not report outcomes of any CSVD neuroimaging features among patients with OSA, while 11 articles were excluded because they were not observational studies. Ultimately, 14 observational studies consisting of 4,335 patients were enrolled. The literature retrieval, review, and selection process are demonstrated in Figure 1. The characteristics of the included studies are presented in Table 1.

3.1 Effects of OSA on CSVD Neuroimaging Features There was a significant association between OSA and WMH with a pooled OR of 2.31 (95% CI, 1.46-3.66, I2 =79%) when compared to patients without OSA (Figure 2). Metaanalysis limited to studies with confounder-adjusted analysis was performed. This showed a pooled OR for WMH of 2.13 (95% CI, 1.31-3.48, I2 =79%) among patients with OSA (Supplementary Figure A.1).

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Figure 1. Outline of our selection process.

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Study name

Statistics for each study

Odds ratio and 95% CI

Odds Lower Upper ratio limit limit Z-Value p-Value Avci et al Baik et al Castillo et al Choi et al Del Brutto et al Ding et al Kepplinger et al Kim et al Song et al

3.200 1.590 2.750 2.530 3.940 0.960 6.030 2.030 4.720 2.312

1.817 1.092 0.509 1.431 1.063 0.789 1.763 1.019 1.128 1.462

5.637 2.315 14.844 4.473 14.601 1.168 20.630 4.045 19.755 3.656

4.026 2.420 1.176 3.193 2.052 -0.407 2.863 2.013 2.125 3.586

Relative weight

0.000 0.016 0.240 0.001 0.040 0.684 0.004 0.044 0.034 0.000

13.91 15.79 5.21 13.87 7.23 17.11 7.77 12.62 6.48 0.01

0.1

1

No WMH

10

100

WMH

Figure 2. Forest plots of the included studies assessing association between OSA and WMH. A diamond data marker depicts the overall rate from each included study (square data marker) and 95%CI.

There was a significant association between OSA and ALI when compared to patients without OSA, with a pooled OR of 1.78 (95% CI, 1.06-3.01, I2 =41%); all studies were confounder-adjusted (Figure 3). Study name

Statistics for each study

Odds ratio and 95% CI

Odds Lower Upper ratio limit limit Z-Value p-Value Alvarez-Sabin et al Cho et al Del Brutto et al Kepplinger et al Lutsey et al Nishibayashi et al Song et al

2.180 2.000 2.070 2.700 0.330 4.180 0.970 1.784

1.060 4.482 0.911 4.393 0.691 6.200 0.769 9.484 0.092 1.190 1.323 13.208 0.213 4.420 1.059 3.006

2.119 1.727 1.300 1.550 -1.694 2.437 -0.039 2.177

Relative weight

0.034 0.084 0.194 0.121 0.090 0.015 0.969 0.030

21.34 19.79 13.89 11.66 11.33 13.08 8.90 0.01

0.1

No ALI

1

10

100

ALI

Figure 3. Forest plots of the included studies assessing association between OSA and ALI. A diamond data marker depicts the overall rate from each included study (square data marker) and 95%CI.

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All included studies assessing the association between OSA and CMBs were performed with confounder-adjusted analysis. There was no significant association between OSA and CMBs with a pooled OR of 2.15 (95% CI, 0.64-7.29, I2 =55%) when compared to patients without OSA (Figure 4). Study name

Statistics for each study

Odds ratio and 95% CI

Odds Lower Upper ratio limit limit Z-Value p-Value

Relative weight

Del Brutto et al

0.500

0.094

2.661

-0.813

0.416

28.26

Koo et al

4.170

1.281 13.573

2.371

0.018

38.53

Song et al

3.470

0.840 14.331

1.719

0.086

33.21

2.154

0.637

1.234

0.217

7.292

0.01

0.1

No CMBs

1

10

100

CMBs

Figure 4. Forest plots of the included studies assessing association between OSA and CMBs. A diamond data marker depicts the overall rate from each included study (square data marker) and 95%CI.

3.2 Evaluation for publication bias To evaluate publication bias, we examined the contour-enhanced funnel plots (Supplementary Figure A.2-A.4) and calculated Egger’s regression asymmetry of the included studies. While there was no publication bias with p = 0.43 and p = 0.30 for the analyses assessing risks of ALI and CMBs among patients with OSA, respectively, there was the presence of publications in favor of positive studies (p = 0.002) in the analysis evaluating risk of WMH in patients with OSA.

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4. Discussion Our study demonstrated that OSA is associated with features of CSVD, specifically WMH and ALI. However, our study failed to demonstrate a significant association between OSA and CMBs. Association of OSA with WMH is one of the most common issues being studied. Our search found nine studies addressing this association with a pooled OR of 2.31 (95% CI, 1.463.66, I2 =79%) (11, 12, 20-26). The meta-analysis result remained significant when limited to the six studies that were confounder-adjusted (11, 12, 20, 23-25). Our result is consistent with the result of a recent systematic review and meta-analysis by Ho et al.(27), which showed a higher prevalence of white matter change (WMC) in patients with OSA compared to controls (OR 2.06). WMH of presumed vascular origin are defined as white matter lesions of variable sizes that are hyperintense on T2-weighted (T2) and fluid attenuated inversion recovery (FLAIR) MRI sequences(3). These areas are presumably caused by chronic hypoperfusion and blood-brain barrier leakage resulting in subsequent axonal and myelin loss(1, 5, 28-31). Analysis of a total of seven confounder-adjusted studies showed a significant association between OSA and ALI with a pooled OR of 1.78 (95% CI, 1.06-3.01, I2 =41%) (11-13, 24, 3234). ALI, although ostensibly clinically silent due to their small size and location, harbors the same risk factors as symptomatic strokes (35). Indeed, studies have reported that the presence of ALI increases risk for recurrent symptomatic stroke (36, 37). Our findings agree with the results from several large cohort studies that provide evidence for the association of OSA and stroke. These studies show that the presence of OSA increases the risk of first-ever stroke and recurrent stroke, even after controlling for traditional cardiovascular risk factors. Furthermore, the risk of stroke also increases with increasing severity of OSA (38-42).

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Three studies exploring the association of CMB and OSA showed no significant association (11, 12, 43). Two of the three studies also investigated other CSVD markers, namely WMH and ALI (11, 12). These studies found a significant association with WMH and OSA, but not ALI. Although it is known that not all neuroimaging markers will be present in most cases of CSVD, it is noteworthy that all three studies used gradient echo (GRE) sequence rather than the more sensitive susceptibility-weighted imaging (SWI) sequence currently recommended for identification of CMBs (44). Moreover, the intensity of the MRI magnetic field affects the sensitivity for CMBs findings to a greater extent than other MRI features: 3 Tesla offers greater sensitivity for CMB detection than 1.5 Tesla (45). Hence, it is possible that the association of CMBs and OSA may have been significant if a more sensitive imaging technique was utilized in the included studies. Studies have also reported a significant correlation between CMB location and certain underlying causes. Cortical CMBs are associated with the presence of amyloid angiopathy while deep CMBs are associated with hypertension and other cardiovascular risk factors, such as OSA (43, 46-48). Among the three studies investigating CMB, only one study specifically identified deep CMBs (11). This raises the question if the lack of specificity affected the outcome. Technicalities aside, there is still no clear explanation for the discrepancy in the presence, severity and location of each CSVD neuroimaging marker observed in each individual case. Nonetheless, the correlation between each neuroimaging feature of CSVD has been reported in several studies, suggesting they share some of the same pathogenic processes (35). In recent years, an emerging concept of the relationship between cerebral perivascular space (PVS) and the rate of cerebral metabolic and waste clearance during the night-time brought scientists’ attention scrutinizing this area. Recent studies were conducted to verify the association between OSA severity and PVS dilatation. Song et al. reported a significant increase

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in the prevalence of high-grade perivascular spaces in cases with moderate-to-severe OSA compared to controls(12). The authors also found that patients with more OSA severity index demonstrated higher prevalence of neuroimaging features of cerebral small vessel disease, such as white matter hyperintensity and lacunar infarction. Their findings supported the result in our meta-analysis. However, a study by Del Brutto et al. found no association between apneahypopnea index (AHI) as a measure of OSA severity and enlarged perivascular spaces (49). Due to the inconsistent results and a limited number of studies, future studies exploring enlarged perivascular spaces as one of the CSVD features are needed to explore this association further. OSA is potentially an independent risk factor of CSVD, through both direct and indirect mechanisms. Each OSA apneic episode directly causes a variable degree of intermittent hypoxia and associated hemodynamic changes (32, 50). Activation of the chemoreflex-mediated sympathetic system releases catecholamines resulting in high blood pressure and low heart rate variability(51-53). This pathologic process is more detrimental in OSA due to its intermittent, repetitive and chronic nature (54, 55). This hypothesis is partially supported by a study by Del Brutto et al. in which the researchers found that low night-time heart rate variability, reflecting sympathetic overactivity, plays a significant role in the association of OSA and CSVD(56). However, heart rate variability relies on several contributing factors, not limited to the imbalance of the autonomic nervous system. These factors include baroreceptor sensitivity, reninangiotensin system, physical and mental stress, medications, and aging process(57). Therefore, heart rate variability is not the sine qua non to define sympathetic overactivity. In addition, the impaired cerebrovascular autoregulation in OSA further exacerbates the hypoxia induced cerebral hypoperfusion and ischemia(58). Reperfusion following each apneic episode then causes further brain injury through activation of the oxidative stress and

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neuroinflammatory pathway, which lead to increased levels of reactive oxygen species (ROS), inflammatory cytokines and activation of leukocytes in the brain (59-63). OSA has also been shown to induce a hypercoagulability state through increased platelet aggregation and fibrinogen levels as a result of sympathetic activation and inflammation (64-67). All of these pathophysiologic processes directly and indirectly cause damage to vascular endothelial tissue resulting in subsequent cerebrovascular diseases (38, 39, 68-71). Previously, risk factors and disease modification strategies are evaluated by their influence on development or prevention of future illnesses, including stroke or dementia. Modern neuroimaging technology has now allowed us to detect CSVD in its asymptomatic stage. In 2013, Wardlaw proposed the Standards for Reporting Vascular Changes on Neuroimaging (STRIVE), which introduced neuroimaging features related to CSVD. These consisting of small subcortical infarcts and lacunes, WMH, CMBs, PVS and cerebral atrophy (3). These findings are the presumed sequelae from brain small vessel pathology, such as arteriolosclerosis, lipohyalinosis or fibrinoid necrosis (1). Some of the CSVD neuroimaging features are easily detectable on conventional MRI (WMH and lacunes), while others require special MRI sequences or are better detected on higher resolution MRI (PVS and CMBs) (72). Each CSVD harbors both local effects to adjacent normal-appearing brain tissue and remote effects to connected grey and white matter resulting in subsequent neurodegeneration and decreased global connectivity (73-76). In summary, CSVD is a significant clinical and pathophysiologic marker of high risk individuals. The total burden of the lesions and their locations are important factors that could determine the overall clinical impact (14, 77). One strength of this meta-analysis is that only studies with proven OSA by polysomnography were included. The severity of OSA in each study was also provided. Most

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importantly, the neuroimaging features of CSVD were used as surrogate outcomes instead of clinical outcomes. This would theoretically allow for earlier detection and treatments to prevent the sequelae of clinical stroke or dementia in OSA patients. This study has several limitations. Due to the fact that most studies had a cross-sectional study design, causal relationship between OSA and CSVD cannot be established. In addition, there is moderate to high heterogeneity in the studies investigating outcomes of WMH and CMBs. The source of the heterogeneity stems from several areas. First, the variability in the population being studied. Recruitment of participants in the studies was performed in one of the two main settings: community and sleep clinics. Participants from sleep clinics often had noticeable symptoms of OSA and more severe OSA than participants from the community clinic. Second, there is a significant difference in outcome measurements as a result of different intensities of the magnetic field (1.5 Tesla and 3 Tesla), different MRI sequences utilized and the criteria selected for measurement of each neuroimaging features. Third, studies adopted different criteria for exposed and control group. For example, several studies chose to compare moderate or severe OSA to mild OSA and healthy controls, while others compared OSA of all severity categories to healthy controls. As a generalization, most of the included studies included middleaged or older adults, and most studies focused on moderate to severe OSA. Findings of our metaanalysis may not be applicable to a younger patient population or those who have mild OSA. Lastly, we identified publication bias favoring positive studies for an association between OSA and WMH. This could lead to overestimation of the true result.

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5. Conclusion In conclusion, this study demonstrates that OSA is an independent risk factor of asymptomatic CSVD, specifically WMH and ALI. The mechanisms responsible are vascular endothelial dysfunction, hypoxia, hypoperfusion and reperfusion, oxidative stress, neuroinflammation, and a hypercoagulability state (38, 68, 71). Individuals with asymptomatic CSVD have a substantially higher risk of developing clinical syndromes in the future that can lead to higher morbidity and mortality. These neurologic diseases include, but are not limited to, strokes, mood disorders, gait problems, and dementia (35, 78, 79). This study supports OSA as an independent factor for CSVD, introducing it as a hypothetically promising target for future research in CSVD treatment.

Author Contributions: All authors confirmed they have contributed to the intellectual content of this paper and approved the final manuscript. Funding: None (author’s own work). Acknowledgments: None. All authors had access to the data and played significant roles in writing and review of the manuscript. Conflicts of Interest: The authors deny any conflict of interest. Appendix A : Supplementary data

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Table 1 Main characteristic of studies included in meta-analysis of obstructive sleep apnea and cerebral small vessel disease Del Brutto et al.(11)

Cho et al.(33)

Koo et al.(43)

Lutsey et al.(34)

Country

Ecuador

Korea

Korea

USA

Study design

Cross-sectional

Cross-sectional

Cross-sectional

Prospective cohort

Year

2017

2013

2017

2016

F/U

N/A

N/A

N/A

14.8 ± 1

Population

Adults age ≥ 60 years with moderate-severe OSA

Community dwelling-adult Exclude history of symptomatic CVD

Sleep clinic patients Exclude history of CVD

Community dwelling-adult with OSA

Total number

AHI ≥ 15: 27, AHI < 15: 70

AHI ≥15: 90, AHI < 15: 656

75

312

Male sex (%) Mean age ± SD Sleep tools AHI or RDI mean ± SD

35% 72.3 ± 7 Portable PSG ≥ 15

N/A 59.3 ± 7.2 Portable PSG 6.6 ± 8.3

60% 60.6 ±14.46 PSG 17 ± 19

Imaging CSVD features (Outcome)

1.5T MRI - WMH by Fazekas scale - ALI - Deep CMB on GRE imaging AHI ≥ 15 AHI < 15 - Moderate-severe WMH OR 3.94 (1.09-14.97) - ALI OR 2.07 (0.69-6.19) - Deep CMB OR 0.5 (0.092.55) Age, total cholesterol

1.5T MRI - ALI

MRI - CMB on GRE imaging

46% 61.7 ± 5 Overnight unattended PSG 19% AHI ≥15, 28% AHI ≥ 5-15, 53%, AHI < 5 3T MRI - WMH volume - ALI

AHI ≥ 15 AHI < 15 - ALI OR 2.00 (0.91-4.39)

AHI ≥ 15 AHI < 15 - CMB OR 4.17 (1.28-13.56)

AHI ≥ 15 AHI < 5 - ALI OR 0.33 (0.09-1.17)

Age, HT, DM

HT, cardiovascular disease

Age, sex, education, ethanol, smoking, physical activity, APOE E4, BMI, hsCRP, DM, HT, CAD, field center

Groups Result

Confounder adjusted

S2 S3 S2 S3 C2 C2 C2 C2 O3 O3 O3 O2 Abbreviation: AHI, apnea hypopnea index. ALI, asymptomatic lacunar infarct. APOE, apolipoprotein E. BMI, body mass index. CAD, coronary artery disease. CMB, cerebral microbleed. CSVD, cerebral small vessel disease. CVD, cerebrovascular disease. DM, diabetes mellitus. GRE, gradient echo. hs-CRP, high sensitivity C-reactive protein. HT, hypertension. MRI, magnetic resonance imaging. N/A, not applicable. OR, odds ratio. OSA, obstructive sleep apnea. PSG, polysomnography. RDI, respiratory disturbance index. SD, standard deviation. T, tesla. WMH, white matter hyperintensity. S, C, O, selection, comparability, and outcome.

Quality assessment

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Nishibayashi et al.(13) Japan Cross-sectional 2008 N/A Community-dwelling adult Exclude past history of CVD

Song et al.(12) Korea Cross-sectional 2016 N/A Sleep clinic patients

Kim et al.(25) Korea Cross-sectional 2013 N/A Community-dwelling adult age 40-69 Exclusion: past history of CVD or major CV accidents

Castillo et al.(21) Ecuador Cross-sectional 2015 N/A Age ≥ 60 years Exclusion: past history of CVD or AF

Kepplinger et al.(24) Germany Cross-sectional 2014 N/A Acute ischemic stroke or TIA

Total number Male sex (%) Mean age ± SD Sleep tools AHI or RDI mean ± SD Imaging CSVD features (Outcome)

192 88% 50.6 ± 13.5 PSG 40.7 ± 29.6

170 N/A 58 ± 13 PSG 20.2 ± 21.7

503 23% 59.63 ± 7.48 Portable PSG 22.3 ± 7.9

25 48% 73.1 ± 7.2 Portable PSG N/A

56 46% 64.3 ± 7.8 Portable PSG 23.6 ± 19.3

1.5T MRI - ALI

1.5T MRI - WMH by ARWMC scale

1.5T MRI WMH by Fazekas scale

3T MRI or 64-slice CT scan - WMH by Wahlund score - ALI

Groups

AHI ≥ 15 AHI < 15 - ALI OR 4.18 (1.3213.18)

3T MRI - WMH : Fazekas scale - ALI - CMB on GRE imaging AHI ≥ 15 AHI < 5 - high-grade WMH OR 4.72 (1.14-19.47) - CMB OR 3.47 (0.89-15.18) - ALI OR 0.97 (0.21-4.36)

AHI ≥ 15 AHI < 5 -WMH OR 2.03 (1.02-4.05)

AHI ≥ 15 AHI < 15 - Moderate-severe WMH 56 % vs 31%, p = 0.397 (OR 2.53, 1.43-4.47)

AHI ≥ 15 AHI < 15 - Moderate-severe WMH OR 6.03 (1.76-20.6) - ALI OR 2.7 (0.77-9.5)

Age, sex, HT, DM, previous stroke, minimal SaO2, arousal index

Age, sex, BMI, alcohol, smoking, DM, DLP, HT

-

Age, HT, DM

Country Study design Year F/U Population

Result

Confounder adjusted

Age, gender, BMI, smoking, alcohol, HT, DM, DLP, ODI

S2 S2 S3 S3 S3 C2 C2 C2 C0 C2 O2 O3 O3 O3 O3 Abbreviation: AF, atrial fibrillation. AHI, apnea hypopnea index. ALI, asymptomatic lacunar infarct. ARWMC, age-related white mater changes. BMI, body mass index. CMB, cerebral microbleed. CT, computer tomography. CV, cardiovascular. CSVD, cerebral small vessel disease. CVD, cerebrovascular disease. DLP, dyslipidemia. DM, diabetes mellitus. GRE, gradient echo. HT, hypertension. MRI, magnetic resonance imaging. N/A, not applicable. ODI, oxygen desaturation index. OR, odds ratio. PSG, polysomnography. RDI, respiratory disturbance index. SaO2, oxygen saturation. SD, standard deviation. T, tesla. TIA, transient ischemic attack. WMH, white matter hyperintensity. S, C, O, selection, comparability, and outcome.

Quality assessment

22

Country Study design Year F/U Population

Alvarez-Sabin et al.(32) Japan Cross-sectional 2018 N/A Adult age 50-70 with HT Exclusion: past history of CVD or dementia

Baik et al.(20) Korea Cross-sectional 2015 N/A Adult age 40-69

Ding et al.(23) USA Cohort study 2004 5 Community-dwelling individual Exclusion: treatment for sleep apnea, oxygen therapy, tracheostomy

Choi et al.(22) Korea Cross-sectional 2016 N/A Community-dwelling individual age 40-70 years

235 OSA, 235 control

Avci et al.(26) Turkey Cross-sectional 2017 N/A Adult age ≥ 18 Exclusion: central sleep apnea, narcolepsy, COPD, asthma, renal failure, hepatic damage, malignancy, dementia, head trauma, brain tumor 223 OSA, 74 control

Total number

183

789

420

64.1 ± 4.5 PSG 22.3 ± 7.9

68.1% 60.8 ± 7.7 Portable PSG 24.8 ± 10.9

70% 55.2 ±12.9 PSG N/A

40.9% 77.8 ± 4.3 Portable PSG 9.7 ± 12.2

40.5% 61.3 ± 7.2 Portable PSG 7.2 ± 7.7

1.5T MRI - ALI

1.5T MRI - WMH by ARWMC scale

1.0T MRI - WMH

1.5T MRI - New WMH in the brainstem

1.5T MRI - WMH by ARWMC scale

AHI ≥ 15 AHI < 5 - WMH OR 1.59 (1.09-2.31)

AHI ≥ 5 AHI < 5 - WMH OR 3.2 (1.84-5.71)

-

Result

AHI > 30 AHI ≤ 30 - ALI OR 2.18 (1.06-4.48)

AHI ≥ 15 AHI < 5 - WMH OR 2.53 (1.434.47)

Confounder adjusted

DM, DLP, smoking, IHD, PAD

Age, sex, BMI, neck circumference, alcohol, NRG1 genotype

-

Quality assessment

S3 C2 O3

S2 C2 O3

S2 C0 O3

Male sex (%) Mean age ± SD Sleep tools AHI or RDI mean ± SD Imaging CSVD features (Outcome) Groups

brainstem WMH : OR 0.96 (0.79 - 1.17) per 1 SD increase in AHI Age, sex, race, community, BMI, smoking, alcohol, SBP, antihypertensive medication S4 C2 O2

-

S2 C0 O3

Abbreviation: AHI, apnea hypopnea index. ALI, asymptomatic lacunar infarct. ARWMC, age-related white mater changes. BMI, body mass index. COPD, chronic obstructive pulmonary disease. CVD, cerebrovascular disease. CSVD, cerebral small vessel disease. DLP, dyslipidemia. DM, diabetes mellitus. IHD, ischemic heart disease. MRI, magnetic resonance imaging. N/A, not applicable. NRG1, neuregulin-1. OR, odds ratio. OSA, obstructive sleep apnea. PAD, peripheral arterial disease. PSG, polysomnography. RDI, respiratory disturbance index. SBP, systolic blood pressure. SD, standard deviation. T, tesla. WMH, white matter hyperintensity. S, C, O, selection, comparability, and outcome.

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Figure Legends Figure 1: Outline of our selection process. Figure 2: Forest plots of the included studies assessing association between OSA and WMH. A diamond data marker depicts the overall rate from each included study (square data marker) and 95%CI. Figure 3: Forest plots of the included studies assessing association between OSA and ALI. A diamond data marker depicts the overall rate from each included study (square data marker) and 95%CI. Figure 4: Forest plots of the included studies assessing association between OSA and CMBs. A diamond data marker depicts the overall rate from each included study (square data marker) and 95%CI.

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Highlights •

Cerebral small vessel disease is one of the main cause of stroke and vascular dementia.

•

Our study found an association between obstructive sleep apnea and silent neuroimaging markers of cerebral small vessel disease.

•

Treatment of obstructive sleep apnea may be a promising target for the prevention of overt cerebral small vessel disease.