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The Link Between Obstructive Sleep Apnoea and Neurodegeneration and Cognition

The Link Between Obstructive Sleep Apnoea and Neurodegeneration and Cognition Purpose of Review Obstructive sleep apnoea (OSA) is increasingly found to have an impact on neurodegeneration. In this review, we summarise recent findings on the association between OSA and brain morphology, cognition, and processes related to Alzheimer’s dementia (AD) and Parkinson’s disease (PD). Recent Findings Associations between OSA and alterations in grey and white matter, brain diffusivity, and deficits in memory, attention, and executive control were reported. Furthermore, OSA was correlated with higher risks of developing AD and PD and associated pathophysiology. Treatment was found to alleviate but not reverse some of the damage. Summary There are strong indications that OSA plays a major role in neurodegenerative processes. The broad picture however remains elusive, likely due to insufficient sample sizes, heterogeneous outcomes, and OSA definitions failing to quantify the disorder’s sub-processes. While studies resolving these issues are required, the available evidence shows OSA to be a promising target to slow neurodegeneration and delay the onset of related disorders. . . . . Keywords Obstructive sleep apnoea Neurodegeneration Alzheimer’sdementia Parkinson’sdisease Cognitive impairment Introduction sleep lab or at home, with the primary metric being the apnoea-hypopnea index (AHI), which quantifies multiple Obstructive sleep apnoea (OSA) is a common form of sleep- characteristics such as absence or reductions in airflow, oxy- disordered breathing affecting around one-seventh of the gen desaturations, or arousal [2–4]. Treatments typically in- world’spopulation [1]. The disorder is characterised by recur- clude lifestyle changes to counteract risk factors such as obe- rent obstruction of the upper airway, resulting in periods of sity, alcohol intake, lack of exercise or smoking, and contin- reduced or absent breathing (intermittent hypoxia) and sleep uous positive airway pressure (CPAP) during the night, which fragmentation. While often asymptomatic, symptoms can in- keeps the airways open [2]. Alternatively, oral devices or, in clude among others excessive daytime sleepiness, loud snor- extreme cases, surgical procedures are available [2]. A grow- ing, and mood changes such as depression or irritability and ing body of evidence has shown the impact of OSA on re- morning headaches [2]. ThegoldstandardindiagnosingOSA duced cognition [5–9], brain morphology [3, 10–13], and neu- is through overnight polysomnography performed either in a rodegenerative pathophysiology [11, 14–18]. Furthermore, it has been shown that the treatment of OSA mitigates some of its negative consequences [13, 16, 19–21], suggesting that, This article is part of the Topical Collection on Sleep Apnea in the with readily available treatment options, OSA is a promising Golden Age target to delay the onset of neurodegenerative disorders such as dementia, Alzheimer’s disease (AD), or Parkinson’sdis- * Antoine Weihs ease (PD). The present review summarises findings based on antoine.weihs@uni-greifswald.de adult populations published between 2018 and 2021 (see 1 Tables 1 and 2) regarding the effect of obstructive sleep ap- Department of Psychiatry and Psychotherapy, University Medicine noea on brain morphology, cognition, and the two most com- Greifswald, Greifswald, Germany 2 mon neurodegenerative disorders: Alzheimer’s dementia and Site Rostock/Greifswald, German Centre for Neurodegenerative Parkinson’sdisease. Diseases (DZNE), Greifswald, Germany 88 Curr Sleep Medicine Rep (2021) 7:87–96 Table 1 Overview of studies performed between 2018 and 2021 on adult populations analysing the effect of sleep apnoea on the brain using MRI, CSF, or blood Author Study type Sample size Age Gender Cognitive test Sleep apnoea years ± SD (% female) André (2020) Community, cross-sectional 1. AHI ≥ 15: 31 1. 69.0 ± 4.0 1. 58.3% Florbetapir-PET, GM volume, Home-based PSG (1–2nights) 2. AHI < 15: 96 2. 69.2 ± 3.5 2. 77.4% fluorodeoxyglucose-PET Baril (2020) Community, cross-sectional 1. AHI > 15: 20 1. 65.2 ± 5.5 1. 5.0% Free water, brain diffusion (DTI), Lab-based PSG (1 night) 2. < AHI ≤ 15: 27 2. 64.2 ± 5.3 2. 33.3% white matter hyperintensities 3. AHI ≤ 5: 18 3. 65.2 ± 7.2 3. 38.9% Bubu (2019) Community, longitudinal 1. AD: 325 1. 76 1. 37% Florbetapir-PET, CSF-Aβ42, CSF Self-reported clinical diagnosis 2. MCI: 798 2. 74 2. 40% T-tau, CSF P-tau 3. CN: 516 3. 74 3. 49% Bubu (2021) Community, longitudinal 1. MCI: 785 1. 74 1. 49% florbetapir-PET, CSF-Aβ42, CSF Self-reported clinical diagnosis 2. CN: 258 2. 74 2. 47% T-tau, CSF P-tau Cross (2018) Clinic, cross-sectional 83 67.4 ± 7.5 63.86% Cortical thickness and subcortical volume Lab-based PSG (1 night) Díaz-Román (2021) Clinic, cross-sectional 57 66 ± 7.1 54.4% CSF Aβ-42, CSF T-tau, CSF P-tau Lab-based PSG (1 night) Huang (2019) Meta-analysis 1. OSA: 678 1. 16.4% VBM 2. Control: 633 2. 11.8% Jackson (2020) Community, cross-sectional 1. AHI > 10: 34 1. 57.8 ± 8.5 1. 44.1% Pittsburgh compound B-PET Lab- or home-based PSG (1 night) 2. Control: 12 2. 57.1 ± 8.2 2. 50.0% Ju (2019) Community, interventional (CPAP) 18 56.9 ± 8.3 33.3% CSF Aβ40, CSF Aβ42, CSF T-tau Lab-based PSG Kim (2021) Community, cross-sectional 2560 59.0 51.0% GM volume Home-based PSG (1 night) Koo (2020) Clinic and community, cross-sectional 1. AHI >30: 38 1. 45.0 ± 6.6 Male only Brain diffusion (DTI) Lab-based PSG (1 night) 2. Good sleepers: 41 2. 37.2 ± 10.7 23.0% Clinical AD diagnosis Clinical diagnosis Lee (2019) Health insurance, longitudinal 1. Diag. OSA: 727 1. 1. 2. Control: 3635 a. 40–49: 48.8% 2. 23.7% b. 50–59: 34.9% c. 60–69: 14.2% d. ≥ 70: 2.1% a. 40–49: 49.7% b. 50–59: 33.4% c. 60–69: 14.0% d. ≥ 70: 2.9% Liguori (2019) Clinic, cross-sectional 1. AD: 20 1. 66.3 ± 4.2 1. 65.0% CSF Aβ-40, CSF Aβ-42, CSF Lab-based PSG (1 night) 2. OSA: 20 2. 58.8 ± 3.5 2. 30.0% T-tau, CSF P-tau, CSF orexin 3. Control: 15 3. 63.8 ± 8.5 3. 46.7% Macey (2018) Community, cross-sectional 1. Diag. OSA: 65 1. 47.5 ± 9.9 1. 24.6% Hippocampal volume 1. Clinical diagnosis 2. Control: 980 2. 47.5 ± 18.8 2. 56.4% 2. None Marchi (2020) Community, cross-sectional 775 60.3 ± 9.9 49.4% Regional brain volumes Lab-based PSG (1 night) Motamedi (2018) Army personnel, cross-sectional 1. AHI < 5: 24 1. 30.9 ± 7.8 1. 91.7% Tau, Aβ40, Aβ42, c-reactive protein, Lab-based PSG 2. 5 < AHI < 15: 22 2. 34.0 ± 8.2 2. 95.5% TNF-α, interleukin-6, interleukin-10 3. AHI ≥ 15: 28 3. 35.6 ± 7.8 3. 100% (all from blood plasma) Owen (2021) Autopsy, cross-sectional 1. Brainstem: 24 Age at death 1. 58.3% Neurofibrillary tangles and PSG 2. Hippocampus: 34 1. 68.3 ± 11.1 2. 52.9% Aβ plaques from brain autopsy 2. 67.0 ± 11.1 Sharma (2018) Community, longitudinal 1. AHI < 5: 97 1. 67.6 ± 7.3 1. 69.1% Pittsburgh compound B-PET, CSF Home-based PSG (2 nights) 2. 5 ≤ AHI < 15: 76 2. 68.6 ± 7.2 2. 57.9% Aβ-42, CSF T-tau, CSF P-tau 3. AHI ≥ 15: 35 3. 70.7 ± 7.7 3. 51.4% Shi (2018) Meta-analysis 246,786 Curr Sleep Medicine Rep (2021) 7:87–96 89 Sleep Apnoea and Brain Structure Obstructive sleep apnoea is marked by sleep fragmentation and intermittent hypoxia, which have both been associated with alterations in brain structures. However, recent studies analysing grey matter (GM) provided inconsistent results. While some studies found that the presence and severity of OSA are associated with reduced GM volume in cortical (e.g. frontal and parietal cortex and cingulate/paracingulate gyrus) and subcortical cerebral regions (e.g. hippocampus, amygda- la, basal ganglia, and thalamus) and the cerebellum [10, 22], others have found OSA to be associated with increased GM volume. André et al. (2020) (N = 127) found OSA to be associated with increased GM volume, perfusion, and metab- olism, mainly in the posterior cingulate, cuneus, and precuneus [11], as did Kim et al. (2021) (N = 2560), who identified increased total, frontal, parietal, and temporal GM volumes in men, and increased total, frontal, and parietal GM volumes in women [12]. Taylor et al. (2018) (N = 41) found mild-severe OSA to be associated with both increased and decreased GM, with an association with increased volume in the bilateral thalamic regions using a voxel-based morphom- etry analysis (VBM) and increased cortical thicknesses in the left-mid cingulate and decreased thicknesses in the left dorsal posterior insular cortex [23]. Macey et al. (2018) (N = 1045, 65 with clinically diagnosed OSA) reported OSA to be asso- ciated with increased hippocampal volume, reflected as sur- face displacement from the mean, in the bilateral CA1, subiculum and uncus, and decreased volumes in the right CA3/dentate, with some gender-specific variation [20]. Analysing the hypoxia and sleep fragmentation separately, Cross et al. (2018) (N = 83) found that oxygen desaturations were associated with decreased cortical thicknesses in the tem- poral lobe, while increased sleep fragmentation was associat- ed with decreased cortical thicknesses in the right frontal, central, and occipital regions but increased volume in the left hippocampus and amygdala [24]. While it is possible that some of these inconsistencies may at least, in part, be attrib- utable to the small sample sizes or methodological differences such as different OSA definitions, age ranges, or uncontrolled confounders, these results might not be as contradictory as such. Rodents exposed to intermittent hypoxia have been shown to have increased brain water content, while sleep frag- mentation and breathing pattern changes associated with ob- structions have been shown to be independently associated with blood pressure fluctuations in humans, and increased GM was found to be co-localised with greater amyloid burden [11, 21]. Furthermore, a recent study performed by Baril et al. (2020) (N = 65) found that mild OSA was associated with widespread areas of lower diffusivity along the skeleton in the centre of white matter (WM) in projection, association, and commissural fibres but not the brainstem, as well as lower free-water fraction and no changes in fractional anisotropy Table 1 (continued) Author Study type Sample size Age Gender Cognitive test Sleep apnoea years ± SD (% female) Sun (2019) Clinic, cross-sectional 1. Diag. OSA: 42 1. 45.0 ± 9.8 1. 26.2% Plasma total and phosphorylated α-synuclein PSG 2. Control: 46 2. 43.5 ± 9.7 2. 28.3% Sun (2020) Meta-analysis 93,332 Taylor (2018) Community, cross-sectional 1. AHI ≥ 15: 22 1. 59 ± 2 1. 22.7% VBM and cortical thickness Lab-based PSG 2. AHI < 15: 19 2. 59 ± 2 2. 31.6% Tsai (2020) Health insurance, longitudinal 1. Diag. OSA: 3978 1. 1. 34.1% Clinical diagnosis OSA diagnosis and treatment claims 2. Control: 15912 a. 40–59: 70.5% 2. 34.1% b. ≥ 60: 29.5% a. 40–59: 70.5% b. 60: 29.5% Weihs (2021) Community, cross-sectional 690 52.5 ± 13.4 48.8% Brain age, GM volume, brain Lab-based PSG (1 night) volume, and VBM Zhang (2019) Community, cross-sectional 1. Diag. OSA: 20 1. 43.1 ± 10.5 1. 20% Brain diffusion (DTI) 1. Lab-based PSG (1 night) 2. Control: 24 2. 40.7 ± 10.0 2. 37.5% Screened for OSA symptoms Zhu (2018) Meta-analysis 19,940 AD, Alzheimer’sdisease; AHI, apnoea-hypopnea index; CN, cognitively normal; CSF, cerebrospinal fluid; DTI, diffusion tensor imaging; GM, grey matter; MCI, mild cognitive impairment; OSA, obstructive sleep apnoea; PET, positron emission tomography; PSG, polysomnography; P-tau, phosphorylated tau, T-tau,totaltau; VBM, voxel-based morphometry analysis 90 Curr Sleep Medicine Rep (2021) 7:87–96 (FA) or WM hyperintensity volume, while subjects with mod- REM sleep [6]. In the long term, the impact of OSA could be erate to severe OSA showed lower axonal diffusivity in the the result of hypoxia and sleep fragmentation-induced brain corpus callosum (CC) [13]. A similar result has also been changes (see above), resulting in cognitive dysfunction. This reported by Zhang et al. (2019) (N = 44), where subjects with area was investigated by most of the recent studies, but due to moderate-severe OSA exhibited significant lower FA and the wide variety of different cognitive tests, comparing the higher mean and radial diffusivity in the anterior CC [25]. results is complicated. An attempt to resolve this was pro- Furthermore, Koo et al. (2020) (N = 79, male only) found posed by D’Rozario et al. (2018), who developed a brief 30- OSA to be associated with lower FA in the bilateral anterior min assessment which evaluates neurobehavioural function thalamic radiations and the right uncinated fasciculus [26]. [7]. Overall, associations were found between OSA and de- Low FA is considered to be an indication of poor WM integ- creased attention [5, 7, 8, 30, 31], memory [5, 26, 32], and rity, while low diffusivity has been observed in acute patho- executive function [7, 8], which are generally in line with logical processes associated with restricted water movement previous findings. The same can be seen in the results of in cells, such as reactive gliosis, axonal damage, or cytotoxic analyses studying OSA-associated severity markers such as oedema [13]. Together, it was hypothesised that increased AHI or ODI, where the results often fail to replicate the asso- GM may represent pre-symptomatic stages of OSA-caused ciations between the cognitive markers and the presence of brain degeneration characterised by cerebral oedema, in- OSA [5, 7, 30, 31]. Specifically, André et al. (2020) found creased amyloid deposition, and reactive gliosis, which could no significant correlations between OSA-associated parame- eventually lead to reduced GM and WM integrity as the dis- ters and cognition (global cognitive function, processing ease progresses [11, 21]. Indeed, signs of OSA-related brain speed, attention, working memory, executive function, and degeneration were detected by Weihs et al. (2021) (N = 690), episodic memory) [11]. These discrepancies might in part who found that OSA severity, defined by both AHI and ODI, not only be due to low sample sizes and differences in study is associated with age-related local brain atrophy [3]. While no populations and methodologies but also be due to the presence studies regarding treatment were published recently, previous of OSA-associated comorbidities, which might influence cog- studies found indications that treatment of OSA was able to nition or the impact of the length between the beginning of the alleviate OSA-associated damage to the brain [13, 20, 26]. disorder and diagnosis. Short-term CPAP treatment has been shown to improve, but not reverse some cognitive deficits. Bhat et al. (2018) (N = Sleep Apnoea and Cognition 182) found significant improvements in objective vigilance in subjects with severe OSA after at least 1 month of CPAP Sleep apnoea has been associated with cognitive dysfunction. treatment [33]; Jackson et al. (2018) (N = 141) found that 3 months of CPAP resulted in significant improvements, but not In a meta-analysis based on 19,940 subjects, those with OSA were 2.44 times more likely to develop mild cognitive impair- reversal to normal neuropsychological function (verbal fluen- ment (MCI), with women being at a higher risk (RR = 2.06) cy, psychomotor performance, complex cognitive function, than men (RR = 1.18) [27]. Similarly, Beaudin et al. (2020) (N memory, set shifting, mood, quality of life, but not working = 1084) found OSA presence and nocturnal hypoxia to be memory) in subjects with mild-moderate OSA [8]; and associated with higher cognitive impairment and the presence Pecotic et al. (2019) (N = 48) reported slight significant im- of moderate-severe OSA with higher odds of having MCI [5]. provements in convergent thinking, perception, and psycho- Interestingly, according to a study performed on 101 subjects motor performance after 1 year of CPAP treatment [34]. by Gagnon et al. (2019), subjects with OSA and MCI seem to Furthermore, in a meta-analysis based on 1926 subjects, be less aware of their cognitive deficits than subjects without M.L. Wang et al. (2020) reported that CPAP treatment (aver- OSA [28]. There are two prevalent schools of thought in age treatment length: 6 weeks) had a (borderline) significant which OSA is believed to impact cognition, which likely act effect on attention and information processing speed in sub- simultaneously. In the short term, cognitive impairment can be jects with severe OSA, with no effects being identified for a cause of OSA-induced sleep fragmentation and daytime attention and speed of information processing, executive func- sleepiness. Non-rapid eye movement (NREM) sleep for ex- tion, or memory [9]. After the onset of MCI, Richards et al. ample plays an important role in memory processing and con- (2019) (N = 54) and Y. Wang et al. (2020) (N = 17) found that solidation [29]. In an experiment performed by Djonlagic subjects with MCI and mild OSA showed improved et al. (2020) (N = 53), subjects were asked to perform a motor psychomotor/cognitive processing speed after 1 year of sequence test in the evening and again in the morning to assess CPAP treatment [35, 36]. One reason for the lack of strong motor memory consolidation [6]. Subjects suffering from effects is due to poor CPAP treatment compliance. It is how- OSA during rapid eye movement (REM) and NREM sleep ever also likely that the improvements do not represent long- showed significantly lower improvements in the morning tests term permanent changes but are rather related to reduced compared to subjects with no OSA or OSA exclusively during sleepiness and sleep fragmentation as a result of the CPAP Curr Sleep Medicine Rep (2021) 7:87–96 91 Table 2 Overview of studies performed between 2018 and 2021 on adult populations analysing the effect of sleep apnoea on the brain via cognitive tests Author Study type Sample size Age Gender Cognitive test Sleep apnoea years ± SD (% female) Alomri (2020) Clinic, cross-sectional 1. No OSA: 14 1. 33.6 ± PVT, Austin maze-10 trails, AMI Lab- and home-based 2. Mild OSA: 30 14.2 PSG 3. Moderate OSA: 2. 38.7 ± 23 11.8 4. Severe OSA: 23 3. 46.8 ± 11.8 4. 46.7 ± 10.3 André (2020) Community, cross-sectional 1. AHI ≥ 15: 31 1. 69.0 ± 4.0 1. 58.3% TMT, Stroop test, Mattis dementia rating scale, Home-based PSG (1–2 2. AHI < 15: 96 2. 69.2 ± 3.5 2. 77.4% D2R, WAIS-IV, California Verbal learning test nights) Bahia (2019) Clinic, cross-sectional 48 63 ± 10.3 14.6 Lab-based PSG (1 night) Beaudin Community, cross-sectional 1. No OSA: 320 1. 51.7 ± 1. 51.6% MoCA, RAVLT, WAIS-IV Digit Home-orlab-based PSG (2020) 2. Mild OSA: 204 14.2 2. 47.1% Symbol Coding subtest 3. Moderate OSA: 2. 56.7 ± 3. 37.9% 240 11.9 4. 34.7% 4. Severe OSA: 320 3. 56.1 ± 12.5 4. 53.6 ± 12.1 Bhat (2018) Clinic, longitudinal 1. 5 ≤ AHI/ REI < 1. 50.3 ± 1. 28.3% PVT Lab- or home-based PSG 30: 92 11.5 2. 25.6% 2. AHI/ REI ≥ 30: 90 2. 52.6 ± 13.3 Delhikar Clinic and community, 1. AHI ≥ 10: 44 1. 49.4 ± 1. 31.8% AMI, autobiographical memory test 1. Lab-based PSG (2019) cross-sectional 2. Control: 44 13.0 2. 77.3% Self-reported 2. 50.0 ± 13.1 Djonlagic Clinic, experimental 1. REM/NREM 1. 37.5 ± 3.0 1. 39.0% PVT, motor sequence task Lab-based PSG (1 night) (2020) OSA: 18 2. 37.2 ± 3.6 2. 41.2% 2. REM OSA: 17 3. 36.2 ± 2.8 3. 44% 3. Control: 18 D’Rozario Clinic and community, 1. RDI ≥ 5: 204 1. 49.3 ± 1. 28.9% Letter cancelation test, 1. PSG (2018) cross-sectional 2. Control: 50 12.5 2. 56.0% Stroop test, N-Back, PVT Screened for OSA 2. 39.2 ± symptoms 14.0 Elfil (2021) Meta-analysis 1. OSA: 474 1. 64.85 MMSE, MoCA 2. Control: 595 2. 63.35 Jackson (2018) Clinic and community, 1. OSA: 110 1. 47.0 ± 0.9 1. 20.2% Digit span test, controlled oral word Lab-based PSG interventional 2. Control: 31 2. 48.0 ± 1.6 2. 25.8% association test, logical memory test, TMT, Stroop test, paced auditory serial attention task, PVT Kaminska Clinic, longitudinal 1. OSA + CPAP: 21 1. 33.4 ± 1. 20% MoCA PSG (2018) 2. OSA − CPAP: 21 10.1 2. 52% 3. Control: 19 2. 65.9 ± 3. 42% 10.3 92 Curr Sleep Medicine Rep (2021) 7:87–96 Table 2 (continued) Author Study type Sample size Age Gender Cognitive test Sleep apnoea years ± SD (% fe- male) 3. 60.7 ± 8.2 Koo (2020) Clinic and community, 1. AHI > 30: 38 1. 45.0 ± 6.6 Male Korean California Verbal Test, Rey complex Lab-based PSG (1 night) cross-sectional 2. Good sleepers: 41 2. 37.2 ± only figure test, Digit span test, Corsi block tapping test, 10.7 TMT, Digit symbol test, Stroop test, Controlled word association test, KoreanBostonnamingtest Lutsey (2018) Community, cross-sectional 1. AHI < 5: 849 1. 62.0 ± 5.5 1. 64.6% Home-based PSG 2. 5 ≤ AHI < 15: 503 2. 63.4 ± 5.3 2. 45.1% 3. 15 ≤ AHI<30: 213 2. 63.6 ± 5.4 3. 30.5% 4. AHI ≥ 30: 102 3. 63.9 ± 5.4 4. 35.3% Meng (2020) Clinic, longitudinal 1. OSA + CPAP: 26 1. 67.4 ± 1. 30.8% PSG 2. OSA − CPAP: 21 10.5 2. 47.6% 3. Control: 20 2. 64.6 ± 3. 40.0% 10.8 3. 61.5 ± 8.4 Pecotic (2019) Clinic and community, 1. Diag. OSA: 25 1. 58.4 ± Complex reactiometer Drenovac Lab-based PSG (1 night) longitudinal 2. Control: 23 11.2 (CRD11, CRD311 and CRD411 subtests) 2. Not provided Richards Clinic, longitudinal 1. MCI + CPAP: 29 1. 67.4 ± 7.2 1. 31.0% HVLT-R, Digit symbol test, Lab-based PSG (2 nights) (2019) 2. MCI − CPAP: 25 2. 73.2 ± 8.6 2. 60.0% MMSE, Stroop test, PVT Shen (2020) Clinic, cross-sectional 1. AHI < 5: 173 1. 62.8 ± 1. 38.7% MMSE, MoCA Lab-based PSG (1 night) 2. AHI ≥ 5: 66 10.9 2. 22.7% 2. 67.9 ± 9.2 Simoes (2018) Clinic and community, 1. AHI > 5: 27 1. 49 ± 17.2 1. 59.3% Continuous visual attention test PSG cross-sectional 2. Control: 27 2. 53 ± 17.9 2. 59.3% M.L. Wang Meta-analysis 1,926 Various covering attention and speed of information, (2020) executive function and memory Y. Wang Community, longitudinal 1. MCI + CPAP: 7 1. 68.4 ± 6.6 1. 28.6% HVLT-R, Digit symbol test, MoCA, Everyday Lab-based PSG (2 nights) (2020) 2. MCI – CPAP: 10 2. 74.6 ± 9.7 2. 70.0% cognition scale, Alzheimer’sDisease Cooperative Study–Clinical Global Impression of Change Scale, Clinical dementia rating scale Zhang (2019) Community, cross-sectional 1. Diag. OSA: 20 1. 43.1 ± 1. 20% Event-based prospective memory test, time-based prospective memory test, Continuous 1. Lab-based PSG (1 2. Control: 24 10.5 2. 37.5% performance task test night) 2. 40.7 ± 2. Screened for OSA 10.0 symptoms AHI, apnoea-hypopnea index; AMI, autobiographical memory interview; CPAP, continuous positive airway pressure; HVLT-R, Hopkins verbal learning test-revised; MCI, mild cognitive impairment; MMSE, Mini-Mental State Examination; MoCA, Montreal Cognitive Assessment; NREM, non-rapid eye-movement sleep; OSA, obstructive sleep apnoea; PSG, polysomnography; PVT, psychomotor vigilance task; RAVLT, Rey Auditory Verbal Learning Test; RDI, respiratory disturbance index; REI, respiratory event index; REM, rapid eye-movement sleep; TMT, Trail Making Test, WAIS-IV,Wechsler Adult Intelligence Scale IV Curr Sleep Medicine Rep (2021) 7:87–96 93 treatment. Indeed, all but M.L. Wang et al. (2020) and Y. was also observed by a study from Bubu et al. (2019) on 1639 Wang (2020) reported a significant decrease in daytime sleep- CN and MCI subjects (mean follow-up period: 2.52 ± 0.51 iness after treatment [8, 9, 33, 34, 36], although Bhat et al. years), who additionally observed that subjects with OSA ex- (2018) did not find changes in sleepiness to be predictive of perienced a greater annual rate of change in florbetapir uptake, improved vigilance [33]. However, older studies based on indicating a greater buildup of amyloid plaques and providing limited data have found that cognitive function did not im- further validity to this mechanism [18]. Similar results were prove after CPAP in subjects who did not experience subjec- found in autopsied hippocampi and brainstems of 34 subjects tive daytime sleepiness, irrespective of OSA severity [9, 37]. with OSA [43]. While not identifying significant correlations in the brainstem, the authors found hypoxia severity to be a significant predictor of Aβ plaque burden in the hippocampus Sleep Apnoea and Alzheimer’s Dementia [43]. Concerning tau, the relationship between the protein and sleep apnoea is even less understood. While some studies Alzheimer’s dementia (AD) is an irreversible and deadly neu- found no association between OSA and CSF total, phosphor- rodegenerative disorder characterised by deteriorating cogni- ylated tau, or neurofibrillary tangles [14, 15, 43], others did, tive abilities. While its cause is still poorly understood, pro- although it remains to be seen if these are caused by OSA itself gression of the disorder is largely associated with amyloid or if they are age-related early manifestations of AD-related plaques, neurofibrillary tangle consisting of tau protein, and pathological processes [18, 44, 45]. With no AD treatment loss of neuronal connections in the brain [18]. Regarding sleep being available, prevention through treatment of risk factors apnoea, there is a complex relationship between OSA and is currently the only way to delay the onset of AD, with OSA Alzheimer’s dementia. While none is responsible for the oth- being a viable target. Indeed, greater CPAP-induced OSA er, both influence each other’s pathological processes improvement was associated with decreased CSF Aβ and resulting in a possible bidirectional relationship [38]. In the Tau levels in 18 OSA subjects, who underwent 1–4months one direction, AD-related changes in the brain result in sleep of CPAP treatment, and OSA subjects receiving CPAP were dysregulation and, as a consequence, high prevalence of sleep found to have a lower risk of developing AD than subjects disorders such as OSA in Alzheimer’s disease patients [38]. In without CPAP treatment [16, 19]. the other direction, OSA has been proposed as a risk factor for AD as it promotes or enhances AD-related subclinical patho- logical processes. In fact, multiple recent studies based on Sleep Apnoea and Parkinson’s Disease large cohorts have shown that subjects with OSA are, depend- ing on the study, between 1.49 and 2.21 times more likely to Parkinson’s disease (PD) is a progressive and, currently, develop AD than individuals not suffering from OSA [16, 17, untreatable neurodegenerative disorder primarily affecting 39–41]. Furthermore, Bubu et al. (2021) showed that individ- the motor system. OSA often coincides with PD, although uals with OSA have shorter progression times between cog- reported prevalence varies widely between 20 and 70.1% nitively normal (CN) to mild cognitive impairment (MCI) or [46]. There are indications that OSA may act as a risk factor MCI to AD [17]. One proposed mechanism through which before the onset of PD. In a recent meta-analysis performed by OSA could have an effect on AD pathology is via a dysregu- Sun et al. (2020), subjects with OSA were 1.56 times more lation of the Aβ metabolism caused by intermittent hypoxia likely to develop PD than controls [47]. The exact mecha- and reduced clearance from interstitial to cerebrospinal fluid nisms at play are still not fully understood, but, similar to (CSF) caused by sleep fragmentation, resulting in decreased AD, OSA, although not causing the disorder, likely plays a CSF Aβ 40 and 42 levels and increased Aβ plaque formation. role in promoting or enhancing PD-associated pre-clinical Recent studies support this, with Liguori et al. (2019) finding pathological processes. Concurrent with this, Sun et al. that CSF Aβ40 and 42 levels were lower in OSA patients than (2019) (N = 88) reported that both OSA severity and hypoxia those in control subjects but higher than those in AD subjects markers were associated with increased levels of plasma α- [14]; Jackson et al. (2020) (N = 46) finding that OSA severity, synuclein, a key protein involved in PD pathology, in healthy specifically during NREM sleep, was associated with in- adults [48]. With the onset of PD, the relationship between creased brain Aβ burden [42]; and André et al. (2020) identi- OSA and PD becomes more complex. While there is no evi- fying a significant association between increased florbetapir, a dence that the incidence of OSA is higher in the PD than that marker for amyloid plaques, uptake, and OSA presence [11]. in the non-PD population, OSA has an impact on the disorder Longitudinally, in a 2-year follow-up study on 208 CN sub- when present [47]. A meta-analysis performed by Elfi et al. jects, Sharma et al. (2018) identified a significant association (2020) found that subjects with PD and OSA showed greater between the annual rate of change of Aβ 42 and OSA sever- cognitive and motor deficits than subjects with PD but without ity, which was stronger than the change predicted by ApoE4, OSA [49]. Similar results were also observed by Meng et al. currently the strongest risk factor known for AD [15]. This (2020) and Kaminska et al. (2018) (same sample, N = 67), 94 Curr Sleep Medicine Rep (2021) 7:87–96 who additionally found that 12-month CPAP treatment result- pathways [4]. Firstly, the index combines both hypoxic and sleep ed in improved PD-associated non-motor symptoms and a fragmentation-related events, which individually influence neu- stabilisation of motor function [50, 51]. While this indicates rodegenerative processes, but not necessarily in an additive fash- that OSA has a detrimental effect on PD-associated cognitive ion. Furthermore, the index also only assesses the frequency, and motor functions, there are also findings that PD has an while completely ignoring the length of the individual events. effect on OSA severity. In the early stages of PD, the disorder A subject with few but very long events would therefore be has protective effects due to PD-induced weight loss, one of considered “healthier” than a subject with numerous but short the biggest risk factors for OSA, while PD-related factors such events, especially if cutoffs are used. Alternative scores such as as impaired ventilation control and upper airway motor insta- the arousal index and oxygen desaturation index, or to incorpo- bility might increase OSA severity as the disorder progresses rate length, metrics such as percentage/time of sleep spent below [52]. Support for the latter was published by Bahia et al. a certain oxygen saturation threshold, could prove to be much (2019) (N = 48), where PD subjects with a laryngopharyngeal more informative. motor dysfunction were three times more likely to have OSA In conclusion, while not being the cause, there are strong than those without the dysfunction [53]. indications that OSA is a major risk factor for neurodegener- ation and neurodegenerative disorders. OSA treatment was shown to alleviate some of the damage and improve cognitive Conclusion deficits. The underlying mechanisms, however, are yet to be fully understood, highlighting the need for large, preferably There is a complex relationship between OSA and neurodegen- longitudinal studies based on standardised metrics, and more eration, with both influencing each other and different aspects of importantly, assessing OSA-related hypoxia and sleep frag- the disorder having different effects. In this review, we have mentation separately. However, with no viable cure available summarised recent findings on the association between OSA for most neurodegenerative disorders, OSA shows to be a and brain structure, cognition, and the two most common neuro- promising target to delay their onset. degenerative disorders, namely Alzheimer’s dementia and Parkinson’s disease. Overall, recent studies reported associations Funding Open Access funding enabled and organized by Projekt between OSA and grey and white matter alterations [3, 10–12, DEAL. This work specifically was supported by the Deutsche 20, 22–24], and changes in brain diffusion [13, 25, 26], as well as Forschungsgemeinschaft (DFG, grant number: GR 1912/13-1). impaired cognition, specifically regarding memory [5, 6, 26, 32], attention [5, 7, 8, 30, 31], and executive control [7, 8]. Declarations Furthermore, subjects with OSA were found to have a higher risk of developing mild cognitive impairment (MCI) [5, 27], Conflict of Interest HJG has received travel grants and speaker’s hono- Alzheimer’sdementia[16, 17, 39–41], and Parkinson’sdisease raria from Fresenius Medical Care, Neuraxpharm, Servier, and Janssen Cilag as well as research funding from Fresenius Medical Care. [47], and show shorter progression times between cognitively normal and MCI or MCI and Alzheimer’s dementia [17]. But Human and Animal Rights and Informed Consent This article does not while these studies have added further insights, there are some contain any studies with human or animal subjects performed by any of discrepancies in their results and large gaps remain to get a com- the authors. prehensive overview of the exact mechanism at play here. Next Open Access This article is licensed under a Creative Commons to the problem of generally small sample sizes and the presence Attribution 4.0 International License, which permits use, sharing, adap- of a complex and dynamic system influenced by a variety of tation, distribution and reproduction in any medium or format, as long as factors, the lack of conclusive effects might be due to the way you give appropriate credit to the original author(s) and the source, pro- OSA itself is defined. A large majority of studies considered in vide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included this review have defined OSA as a categorical variable based on in the article's Creative Commons licence, unless indicated otherwise in a various AHI cutoffs, medical diagnoses, or self-reported symp- credit line to the material. If material is not included in the article's toms. Next to the difficulty of comparing such results between Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain different studies, there is also the question of what such an asso- permission directly from the copyright holder. To view a copy of this ciation represents, as such a broad phenotype makes it close to licence, visit http://creativecommons.org/licenses/by/4.0/. impossible to distinguish between effects caused by OSA and the ones caused by OSA-associated comorbidities such as obesity, hypertension, diabetes, or depression [54]. Using the continuous AHI instead could be a viable solution, although this does not References resolve all issues either. While this index, in combination with other symptoms, is enough to diagnose OSA in a clinical setting, 1. Benjafield AV, Ayas NT, Eastwood PR, Heinzer R, Ip MSM, it might not be valid to investigate specific OSA-related Morrell MJ, et al. 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Obstructive sleep apnea and Alzheimer’s disease- related cerebrospinal fluid biomarkers in mild cognitive impair- Publisher’sNote Springer Nature remains neutral with regard to jurisdic- ment. Sleep. 2021;44:1–8. tional claims in published maps and institutional affiliations. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Current Sleep Medicine Reports Springer Journals

The Link Between Obstructive Sleep Apnoea and Neurodegeneration and Cognition

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10.1007/s40675-021-00210-5
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Abstract

Purpose of Review Obstructive sleep apnoea (OSA) is increasingly found to have an impact on neurodegeneration. In this review, we summarise recent findings on the association between OSA and brain morphology, cognition, and processes related to Alzheimer’s dementia (AD) and Parkinson’s disease (PD). Recent Findings Associations between OSA and alterations in grey and white matter, brain diffusivity, and deficits in memory, attention, and executive control were reported. Furthermore, OSA was correlated with higher risks of developing AD and PD and associated pathophysiology. Treatment was found to alleviate but not reverse some of the damage. Summary There are strong indications that OSA plays a major role in neurodegenerative processes. The broad picture however remains elusive, likely due to insufficient sample sizes, heterogeneous outcomes, and OSA definitions failing to quantify the disorder’s sub-processes. While studies resolving these issues are required, the available evidence shows OSA to be a promising target to slow neurodegeneration and delay the onset of related disorders. . . . . Keywords Obstructive sleep apnoea Neurodegeneration Alzheimer’sdementia Parkinson’sdisease Cognitive impairment Introduction sleep lab or at home, with the primary metric being the apnoea-hypopnea index (AHI), which quantifies multiple Obstructive sleep apnoea (OSA) is a common form of sleep- characteristics such as absence or reductions in airflow, oxy- disordered breathing affecting around one-seventh of the gen desaturations, or arousal [2–4]. Treatments typically in- world’spopulation [1]. The disorder is characterised by recur- clude lifestyle changes to counteract risk factors such as obe- rent obstruction of the upper airway, resulting in periods of sity, alcohol intake, lack of exercise or smoking, and contin- reduced or absent breathing (intermittent hypoxia) and sleep uous positive airway pressure (CPAP) during the night, which fragmentation. While often asymptomatic, symptoms can in- keeps the airways open [2]. Alternatively, oral devices or, in clude among others excessive daytime sleepiness, loud snor- extreme cases, surgical procedures are available [2]. A grow- ing, and mood changes such as depression or irritability and ing body of evidence has shown the impact of OSA on re- morning headaches [2]. ThegoldstandardindiagnosingOSA duced cognition [5–9], brain morphology [3, 10–13], and neu- is through overnight polysomnography performed either in a rodegenerative pathophysiology [11, 14–18]. Furthermore, it has been shown that the treatment of OSA mitigates some of its negative consequences [13, 16, 19–21], suggesting that, This article is part of the Topical Collection on Sleep Apnea in the with readily available treatment options, OSA is a promising Golden Age target to delay the onset of neurodegenerative disorders such as dementia, Alzheimer’s disease (AD), or Parkinson’sdis- * Antoine Weihs ease (PD). The present review summarises findings based on antoine.weihs@uni-greifswald.de adult populations published between 2018 and 2021 (see 1 Tables 1 and 2) regarding the effect of obstructive sleep ap- Department of Psychiatry and Psychotherapy, University Medicine noea on brain morphology, cognition, and the two most com- Greifswald, Greifswald, Germany 2 mon neurodegenerative disorders: Alzheimer’s dementia and Site Rostock/Greifswald, German Centre for Neurodegenerative Parkinson’sdisease. Diseases (DZNE), Greifswald, Germany 88 Curr Sleep Medicine Rep (2021) 7:87–96 Table 1 Overview of studies performed between 2018 and 2021 on adult populations analysing the effect of sleep apnoea on the brain using MRI, CSF, or blood Author Study type Sample size Age Gender Cognitive test Sleep apnoea years ± SD (% female) André (2020) Community, cross-sectional 1. AHI ≥ 15: 31 1. 69.0 ± 4.0 1. 58.3% Florbetapir-PET, GM volume, Home-based PSG (1–2nights) 2. AHI < 15: 96 2. 69.2 ± 3.5 2. 77.4% fluorodeoxyglucose-PET Baril (2020) Community, cross-sectional 1. AHI > 15: 20 1. 65.2 ± 5.5 1. 5.0% Free water, brain diffusion (DTI), Lab-based PSG (1 night) 2. < AHI ≤ 15: 27 2. 64.2 ± 5.3 2. 33.3% white matter hyperintensities 3. AHI ≤ 5: 18 3. 65.2 ± 7.2 3. 38.9% Bubu (2019) Community, longitudinal 1. AD: 325 1. 76 1. 37% Florbetapir-PET, CSF-Aβ42, CSF Self-reported clinical diagnosis 2. MCI: 798 2. 74 2. 40% T-tau, CSF P-tau 3. CN: 516 3. 74 3. 49% Bubu (2021) Community, longitudinal 1. MCI: 785 1. 74 1. 49% florbetapir-PET, CSF-Aβ42, CSF Self-reported clinical diagnosis 2. CN: 258 2. 74 2. 47% T-tau, CSF P-tau Cross (2018) Clinic, cross-sectional 83 67.4 ± 7.5 63.86% Cortical thickness and subcortical volume Lab-based PSG (1 night) Díaz-Román (2021) Clinic, cross-sectional 57 66 ± 7.1 54.4% CSF Aβ-42, CSF T-tau, CSF P-tau Lab-based PSG (1 night) Huang (2019) Meta-analysis 1. OSA: 678 1. 16.4% VBM 2. Control: 633 2. 11.8% Jackson (2020) Community, cross-sectional 1. AHI > 10: 34 1. 57.8 ± 8.5 1. 44.1% Pittsburgh compound B-PET Lab- or home-based PSG (1 night) 2. Control: 12 2. 57.1 ± 8.2 2. 50.0% Ju (2019) Community, interventional (CPAP) 18 56.9 ± 8.3 33.3% CSF Aβ40, CSF Aβ42, CSF T-tau Lab-based PSG Kim (2021) Community, cross-sectional 2560 59.0 51.0% GM volume Home-based PSG (1 night) Koo (2020) Clinic and community, cross-sectional 1. AHI >30: 38 1. 45.0 ± 6.6 Male only Brain diffusion (DTI) Lab-based PSG (1 night) 2. Good sleepers: 41 2. 37.2 ± 10.7 23.0% Clinical AD diagnosis Clinical diagnosis Lee (2019) Health insurance, longitudinal 1. Diag. OSA: 727 1. 1. 2. Control: 3635 a. 40–49: 48.8% 2. 23.7% b. 50–59: 34.9% c. 60–69: 14.2% d. ≥ 70: 2.1% a. 40–49: 49.7% b. 50–59: 33.4% c. 60–69: 14.0% d. ≥ 70: 2.9% Liguori (2019) Clinic, cross-sectional 1. AD: 20 1. 66.3 ± 4.2 1. 65.0% CSF Aβ-40, CSF Aβ-42, CSF Lab-based PSG (1 night) 2. OSA: 20 2. 58.8 ± 3.5 2. 30.0% T-tau, CSF P-tau, CSF orexin 3. Control: 15 3. 63.8 ± 8.5 3. 46.7% Macey (2018) Community, cross-sectional 1. Diag. OSA: 65 1. 47.5 ± 9.9 1. 24.6% Hippocampal volume 1. Clinical diagnosis 2. Control: 980 2. 47.5 ± 18.8 2. 56.4% 2. None Marchi (2020) Community, cross-sectional 775 60.3 ± 9.9 49.4% Regional brain volumes Lab-based PSG (1 night) Motamedi (2018) Army personnel, cross-sectional 1. AHI < 5: 24 1. 30.9 ± 7.8 1. 91.7% Tau, Aβ40, Aβ42, c-reactive protein, Lab-based PSG 2. 5 < AHI < 15: 22 2. 34.0 ± 8.2 2. 95.5% TNF-α, interleukin-6, interleukin-10 3. AHI ≥ 15: 28 3. 35.6 ± 7.8 3. 100% (all from blood plasma) Owen (2021) Autopsy, cross-sectional 1. Brainstem: 24 Age at death 1. 58.3% Neurofibrillary tangles and PSG 2. Hippocampus: 34 1. 68.3 ± 11.1 2. 52.9% Aβ plaques from brain autopsy 2. 67.0 ± 11.1 Sharma (2018) Community, longitudinal 1. AHI < 5: 97 1. 67.6 ± 7.3 1. 69.1% Pittsburgh compound B-PET, CSF Home-based PSG (2 nights) 2. 5 ≤ AHI < 15: 76 2. 68.6 ± 7.2 2. 57.9% Aβ-42, CSF T-tau, CSF P-tau 3. AHI ≥ 15: 35 3. 70.7 ± 7.7 3. 51.4% Shi (2018) Meta-analysis 246,786 Curr Sleep Medicine Rep (2021) 7:87–96 89 Sleep Apnoea and Brain Structure Obstructive sleep apnoea is marked by sleep fragmentation and intermittent hypoxia, which have both been associated with alterations in brain structures. However, recent studies analysing grey matter (GM) provided inconsistent results. While some studies found that the presence and severity of OSA are associated with reduced GM volume in cortical (e.g. frontal and parietal cortex and cingulate/paracingulate gyrus) and subcortical cerebral regions (e.g. hippocampus, amygda- la, basal ganglia, and thalamus) and the cerebellum [10, 22], others have found OSA to be associated with increased GM volume. André et al. (2020) (N = 127) found OSA to be associated with increased GM volume, perfusion, and metab- olism, mainly in the posterior cingulate, cuneus, and precuneus [11], as did Kim et al. (2021) (N = 2560), who identified increased total, frontal, parietal, and temporal GM volumes in men, and increased total, frontal, and parietal GM volumes in women [12]. Taylor et al. (2018) (N = 41) found mild-severe OSA to be associated with both increased and decreased GM, with an association with increased volume in the bilateral thalamic regions using a voxel-based morphom- etry analysis (VBM) and increased cortical thicknesses in the left-mid cingulate and decreased thicknesses in the left dorsal posterior insular cortex [23]. Macey et al. (2018) (N = 1045, 65 with clinically diagnosed OSA) reported OSA to be asso- ciated with increased hippocampal volume, reflected as sur- face displacement from the mean, in the bilateral CA1, subiculum and uncus, and decreased volumes in the right CA3/dentate, with some gender-specific variation [20]. Analysing the hypoxia and sleep fragmentation separately, Cross et al. (2018) (N = 83) found that oxygen desaturations were associated with decreased cortical thicknesses in the tem- poral lobe, while increased sleep fragmentation was associat- ed with decreased cortical thicknesses in the right frontal, central, and occipital regions but increased volume in the left hippocampus and amygdala [24]. While it is possible that some of these inconsistencies may at least, in part, be attrib- utable to the small sample sizes or methodological differences such as different OSA definitions, age ranges, or uncontrolled confounders, these results might not be as contradictory as such. Rodents exposed to intermittent hypoxia have been shown to have increased brain water content, while sleep frag- mentation and breathing pattern changes associated with ob- structions have been shown to be independently associated with blood pressure fluctuations in humans, and increased GM was found to be co-localised with greater amyloid burden [11, 21]. Furthermore, a recent study performed by Baril et al. (2020) (N = 65) found that mild OSA was associated with widespread areas of lower diffusivity along the skeleton in the centre of white matter (WM) in projection, association, and commissural fibres but not the brainstem, as well as lower free-water fraction and no changes in fractional anisotropy Table 1 (continued) Author Study type Sample size Age Gender Cognitive test Sleep apnoea years ± SD (% female) Sun (2019) Clinic, cross-sectional 1. Diag. OSA: 42 1. 45.0 ± 9.8 1. 26.2% Plasma total and phosphorylated α-synuclein PSG 2. Control: 46 2. 43.5 ± 9.7 2. 28.3% Sun (2020) Meta-analysis 93,332 Taylor (2018) Community, cross-sectional 1. AHI ≥ 15: 22 1. 59 ± 2 1. 22.7% VBM and cortical thickness Lab-based PSG 2. AHI < 15: 19 2. 59 ± 2 2. 31.6% Tsai (2020) Health insurance, longitudinal 1. Diag. OSA: 3978 1. 1. 34.1% Clinical diagnosis OSA diagnosis and treatment claims 2. Control: 15912 a. 40–59: 70.5% 2. 34.1% b. ≥ 60: 29.5% a. 40–59: 70.5% b. 60: 29.5% Weihs (2021) Community, cross-sectional 690 52.5 ± 13.4 48.8% Brain age, GM volume, brain Lab-based PSG (1 night) volume, and VBM Zhang (2019) Community, cross-sectional 1. Diag. OSA: 20 1. 43.1 ± 10.5 1. 20% Brain diffusion (DTI) 1. Lab-based PSG (1 night) 2. Control: 24 2. 40.7 ± 10.0 2. 37.5% Screened for OSA symptoms Zhu (2018) Meta-analysis 19,940 AD, Alzheimer’sdisease; AHI, apnoea-hypopnea index; CN, cognitively normal; CSF, cerebrospinal fluid; DTI, diffusion tensor imaging; GM, grey matter; MCI, mild cognitive impairment; OSA, obstructive sleep apnoea; PET, positron emission tomography; PSG, polysomnography; P-tau, phosphorylated tau, T-tau,totaltau; VBM, voxel-based morphometry analysis 90 Curr Sleep Medicine Rep (2021) 7:87–96 (FA) or WM hyperintensity volume, while subjects with mod- REM sleep [6]. In the long term, the impact of OSA could be erate to severe OSA showed lower axonal diffusivity in the the result of hypoxia and sleep fragmentation-induced brain corpus callosum (CC) [13]. A similar result has also been changes (see above), resulting in cognitive dysfunction. This reported by Zhang et al. (2019) (N = 44), where subjects with area was investigated by most of the recent studies, but due to moderate-severe OSA exhibited significant lower FA and the wide variety of different cognitive tests, comparing the higher mean and radial diffusivity in the anterior CC [25]. results is complicated. An attempt to resolve this was pro- Furthermore, Koo et al. (2020) (N = 79, male only) found posed by D’Rozario et al. (2018), who developed a brief 30- OSA to be associated with lower FA in the bilateral anterior min assessment which evaluates neurobehavioural function thalamic radiations and the right uncinated fasciculus [26]. [7]. Overall, associations were found between OSA and de- Low FA is considered to be an indication of poor WM integ- creased attention [5, 7, 8, 30, 31], memory [5, 26, 32], and rity, while low diffusivity has been observed in acute patho- executive function [7, 8], which are generally in line with logical processes associated with restricted water movement previous findings. The same can be seen in the results of in cells, such as reactive gliosis, axonal damage, or cytotoxic analyses studying OSA-associated severity markers such as oedema [13]. Together, it was hypothesised that increased AHI or ODI, where the results often fail to replicate the asso- GM may represent pre-symptomatic stages of OSA-caused ciations between the cognitive markers and the presence of brain degeneration characterised by cerebral oedema, in- OSA [5, 7, 30, 31]. Specifically, André et al. (2020) found creased amyloid deposition, and reactive gliosis, which could no significant correlations between OSA-associated parame- eventually lead to reduced GM and WM integrity as the dis- ters and cognition (global cognitive function, processing ease progresses [11, 21]. Indeed, signs of OSA-related brain speed, attention, working memory, executive function, and degeneration were detected by Weihs et al. (2021) (N = 690), episodic memory) [11]. These discrepancies might in part who found that OSA severity, defined by both AHI and ODI, not only be due to low sample sizes and differences in study is associated with age-related local brain atrophy [3]. While no populations and methodologies but also be due to the presence studies regarding treatment were published recently, previous of OSA-associated comorbidities, which might influence cog- studies found indications that treatment of OSA was able to nition or the impact of the length between the beginning of the alleviate OSA-associated damage to the brain [13, 20, 26]. disorder and diagnosis. Short-term CPAP treatment has been shown to improve, but not reverse some cognitive deficits. Bhat et al. (2018) (N = Sleep Apnoea and Cognition 182) found significant improvements in objective vigilance in subjects with severe OSA after at least 1 month of CPAP Sleep apnoea has been associated with cognitive dysfunction. treatment [33]; Jackson et al. (2018) (N = 141) found that 3 months of CPAP resulted in significant improvements, but not In a meta-analysis based on 19,940 subjects, those with OSA were 2.44 times more likely to develop mild cognitive impair- reversal to normal neuropsychological function (verbal fluen- ment (MCI), with women being at a higher risk (RR = 2.06) cy, psychomotor performance, complex cognitive function, than men (RR = 1.18) [27]. Similarly, Beaudin et al. (2020) (N memory, set shifting, mood, quality of life, but not working = 1084) found OSA presence and nocturnal hypoxia to be memory) in subjects with mild-moderate OSA [8]; and associated with higher cognitive impairment and the presence Pecotic et al. (2019) (N = 48) reported slight significant im- of moderate-severe OSA with higher odds of having MCI [5]. provements in convergent thinking, perception, and psycho- Interestingly, according to a study performed on 101 subjects motor performance after 1 year of CPAP treatment [34]. by Gagnon et al. (2019), subjects with OSA and MCI seem to Furthermore, in a meta-analysis based on 1926 subjects, be less aware of their cognitive deficits than subjects without M.L. Wang et al. (2020) reported that CPAP treatment (aver- OSA [28]. There are two prevalent schools of thought in age treatment length: 6 weeks) had a (borderline) significant which OSA is believed to impact cognition, which likely act effect on attention and information processing speed in sub- simultaneously. In the short term, cognitive impairment can be jects with severe OSA, with no effects being identified for a cause of OSA-induced sleep fragmentation and daytime attention and speed of information processing, executive func- sleepiness. Non-rapid eye movement (NREM) sleep for ex- tion, or memory [9]. After the onset of MCI, Richards et al. ample plays an important role in memory processing and con- (2019) (N = 54) and Y. Wang et al. (2020) (N = 17) found that solidation [29]. In an experiment performed by Djonlagic subjects with MCI and mild OSA showed improved et al. (2020) (N = 53), subjects were asked to perform a motor psychomotor/cognitive processing speed after 1 year of sequence test in the evening and again in the morning to assess CPAP treatment [35, 36]. One reason for the lack of strong motor memory consolidation [6]. Subjects suffering from effects is due to poor CPAP treatment compliance. It is how- OSA during rapid eye movement (REM) and NREM sleep ever also likely that the improvements do not represent long- showed significantly lower improvements in the morning tests term permanent changes but are rather related to reduced compared to subjects with no OSA or OSA exclusively during sleepiness and sleep fragmentation as a result of the CPAP Curr Sleep Medicine Rep (2021) 7:87–96 91 Table 2 Overview of studies performed between 2018 and 2021 on adult populations analysing the effect of sleep apnoea on the brain via cognitive tests Author Study type Sample size Age Gender Cognitive test Sleep apnoea years ± SD (% female) Alomri (2020) Clinic, cross-sectional 1. No OSA: 14 1. 33.6 ± PVT, Austin maze-10 trails, AMI Lab- and home-based 2. Mild OSA: 30 14.2 PSG 3. Moderate OSA: 2. 38.7 ± 23 11.8 4. Severe OSA: 23 3. 46.8 ± 11.8 4. 46.7 ± 10.3 André (2020) Community, cross-sectional 1. AHI ≥ 15: 31 1. 69.0 ± 4.0 1. 58.3% TMT, Stroop test, Mattis dementia rating scale, Home-based PSG (1–2 2. AHI < 15: 96 2. 69.2 ± 3.5 2. 77.4% D2R, WAIS-IV, California Verbal learning test nights) Bahia (2019) Clinic, cross-sectional 48 63 ± 10.3 14.6 Lab-based PSG (1 night) Beaudin Community, cross-sectional 1. No OSA: 320 1. 51.7 ± 1. 51.6% MoCA, RAVLT, WAIS-IV Digit Home-orlab-based PSG (2020) 2. Mild OSA: 204 14.2 2. 47.1% Symbol Coding subtest 3. Moderate OSA: 2. 56.7 ± 3. 37.9% 240 11.9 4. 34.7% 4. Severe OSA: 320 3. 56.1 ± 12.5 4. 53.6 ± 12.1 Bhat (2018) Clinic, longitudinal 1. 5 ≤ AHI/ REI < 1. 50.3 ± 1. 28.3% PVT Lab- or home-based PSG 30: 92 11.5 2. 25.6% 2. AHI/ REI ≥ 30: 90 2. 52.6 ± 13.3 Delhikar Clinic and community, 1. AHI ≥ 10: 44 1. 49.4 ± 1. 31.8% AMI, autobiographical memory test 1. Lab-based PSG (2019) cross-sectional 2. Control: 44 13.0 2. 77.3% Self-reported 2. 50.0 ± 13.1 Djonlagic Clinic, experimental 1. REM/NREM 1. 37.5 ± 3.0 1. 39.0% PVT, motor sequence task Lab-based PSG (1 night) (2020) OSA: 18 2. 37.2 ± 3.6 2. 41.2% 2. REM OSA: 17 3. 36.2 ± 2.8 3. 44% 3. Control: 18 D’Rozario Clinic and community, 1. RDI ≥ 5: 204 1. 49.3 ± 1. 28.9% Letter cancelation test, 1. PSG (2018) cross-sectional 2. Control: 50 12.5 2. 56.0% Stroop test, N-Back, PVT Screened for OSA 2. 39.2 ± symptoms 14.0 Elfil (2021) Meta-analysis 1. OSA: 474 1. 64.85 MMSE, MoCA 2. Control: 595 2. 63.35 Jackson (2018) Clinic and community, 1. OSA: 110 1. 47.0 ± 0.9 1. 20.2% Digit span test, controlled oral word Lab-based PSG interventional 2. Control: 31 2. 48.0 ± 1.6 2. 25.8% association test, logical memory test, TMT, Stroop test, paced auditory serial attention task, PVT Kaminska Clinic, longitudinal 1. OSA + CPAP: 21 1. 33.4 ± 1. 20% MoCA PSG (2018) 2. OSA − CPAP: 21 10.1 2. 52% 3. Control: 19 2. 65.9 ± 3. 42% 10.3 92 Curr Sleep Medicine Rep (2021) 7:87–96 Table 2 (continued) Author Study type Sample size Age Gender Cognitive test Sleep apnoea years ± SD (% fe- male) 3. 60.7 ± 8.2 Koo (2020) Clinic and community, 1. AHI > 30: 38 1. 45.0 ± 6.6 Male Korean California Verbal Test, Rey complex Lab-based PSG (1 night) cross-sectional 2. Good sleepers: 41 2. 37.2 ± only figure test, Digit span test, Corsi block tapping test, 10.7 TMT, Digit symbol test, Stroop test, Controlled word association test, KoreanBostonnamingtest Lutsey (2018) Community, cross-sectional 1. AHI < 5: 849 1. 62.0 ± 5.5 1. 64.6% Home-based PSG 2. 5 ≤ AHI < 15: 503 2. 63.4 ± 5.3 2. 45.1% 3. 15 ≤ AHI<30: 213 2. 63.6 ± 5.4 3. 30.5% 4. AHI ≥ 30: 102 3. 63.9 ± 5.4 4. 35.3% Meng (2020) Clinic, longitudinal 1. OSA + CPAP: 26 1. 67.4 ± 1. 30.8% PSG 2. OSA − CPAP: 21 10.5 2. 47.6% 3. Control: 20 2. 64.6 ± 3. 40.0% 10.8 3. 61.5 ± 8.4 Pecotic (2019) Clinic and community, 1. Diag. OSA: 25 1. 58.4 ± Complex reactiometer Drenovac Lab-based PSG (1 night) longitudinal 2. Control: 23 11.2 (CRD11, CRD311 and CRD411 subtests) 2. Not provided Richards Clinic, longitudinal 1. MCI + CPAP: 29 1. 67.4 ± 7.2 1. 31.0% HVLT-R, Digit symbol test, Lab-based PSG (2 nights) (2019) 2. MCI − CPAP: 25 2. 73.2 ± 8.6 2. 60.0% MMSE, Stroop test, PVT Shen (2020) Clinic, cross-sectional 1. AHI < 5: 173 1. 62.8 ± 1. 38.7% MMSE, MoCA Lab-based PSG (1 night) 2. AHI ≥ 5: 66 10.9 2. 22.7% 2. 67.9 ± 9.2 Simoes (2018) Clinic and community, 1. AHI > 5: 27 1. 49 ± 17.2 1. 59.3% Continuous visual attention test PSG cross-sectional 2. Control: 27 2. 53 ± 17.9 2. 59.3% M.L. Wang Meta-analysis 1,926 Various covering attention and speed of information, (2020) executive function and memory Y. Wang Community, longitudinal 1. MCI + CPAP: 7 1. 68.4 ± 6.6 1. 28.6% HVLT-R, Digit symbol test, MoCA, Everyday Lab-based PSG (2 nights) (2020) 2. MCI – CPAP: 10 2. 74.6 ± 9.7 2. 70.0% cognition scale, Alzheimer’sDisease Cooperative Study–Clinical Global Impression of Change Scale, Clinical dementia rating scale Zhang (2019) Community, cross-sectional 1. Diag. OSA: 20 1. 43.1 ± 1. 20% Event-based prospective memory test, time-based prospective memory test, Continuous 1. Lab-based PSG (1 2. Control: 24 10.5 2. 37.5% performance task test night) 2. 40.7 ± 2. Screened for OSA 10.0 symptoms AHI, apnoea-hypopnea index; AMI, autobiographical memory interview; CPAP, continuous positive airway pressure; HVLT-R, Hopkins verbal learning test-revised; MCI, mild cognitive impairment; MMSE, Mini-Mental State Examination; MoCA, Montreal Cognitive Assessment; NREM, non-rapid eye-movement sleep; OSA, obstructive sleep apnoea; PSG, polysomnography; PVT, psychomotor vigilance task; RAVLT, Rey Auditory Verbal Learning Test; RDI, respiratory disturbance index; REI, respiratory event index; REM, rapid eye-movement sleep; TMT, Trail Making Test, WAIS-IV,Wechsler Adult Intelligence Scale IV Curr Sleep Medicine Rep (2021) 7:87–96 93 treatment. Indeed, all but M.L. Wang et al. (2020) and Y. was also observed by a study from Bubu et al. (2019) on 1639 Wang (2020) reported a significant decrease in daytime sleep- CN and MCI subjects (mean follow-up period: 2.52 ± 0.51 iness after treatment [8, 9, 33, 34, 36], although Bhat et al. years), who additionally observed that subjects with OSA ex- (2018) did not find changes in sleepiness to be predictive of perienced a greater annual rate of change in florbetapir uptake, improved vigilance [33]. However, older studies based on indicating a greater buildup of amyloid plaques and providing limited data have found that cognitive function did not im- further validity to this mechanism [18]. Similar results were prove after CPAP in subjects who did not experience subjec- found in autopsied hippocampi and brainstems of 34 subjects tive daytime sleepiness, irrespective of OSA severity [9, 37]. with OSA [43]. While not identifying significant correlations in the brainstem, the authors found hypoxia severity to be a significant predictor of Aβ plaque burden in the hippocampus Sleep Apnoea and Alzheimer’s Dementia [43]. Concerning tau, the relationship between the protein and sleep apnoea is even less understood. While some studies Alzheimer’s dementia (AD) is an irreversible and deadly neu- found no association between OSA and CSF total, phosphor- rodegenerative disorder characterised by deteriorating cogni- ylated tau, or neurofibrillary tangles [14, 15, 43], others did, tive abilities. While its cause is still poorly understood, pro- although it remains to be seen if these are caused by OSA itself gression of the disorder is largely associated with amyloid or if they are age-related early manifestations of AD-related plaques, neurofibrillary tangle consisting of tau protein, and pathological processes [18, 44, 45]. With no AD treatment loss of neuronal connections in the brain [18]. Regarding sleep being available, prevention through treatment of risk factors apnoea, there is a complex relationship between OSA and is currently the only way to delay the onset of AD, with OSA Alzheimer’s dementia. While none is responsible for the oth- being a viable target. Indeed, greater CPAP-induced OSA er, both influence each other’s pathological processes improvement was associated with decreased CSF Aβ and resulting in a possible bidirectional relationship [38]. In the Tau levels in 18 OSA subjects, who underwent 1–4months one direction, AD-related changes in the brain result in sleep of CPAP treatment, and OSA subjects receiving CPAP were dysregulation and, as a consequence, high prevalence of sleep found to have a lower risk of developing AD than subjects disorders such as OSA in Alzheimer’s disease patients [38]. In without CPAP treatment [16, 19]. the other direction, OSA has been proposed as a risk factor for AD as it promotes or enhances AD-related subclinical patho- logical processes. In fact, multiple recent studies based on Sleep Apnoea and Parkinson’s Disease large cohorts have shown that subjects with OSA are, depend- ing on the study, between 1.49 and 2.21 times more likely to Parkinson’s disease (PD) is a progressive and, currently, develop AD than individuals not suffering from OSA [16, 17, untreatable neurodegenerative disorder primarily affecting 39–41]. Furthermore, Bubu et al. (2021) showed that individ- the motor system. OSA often coincides with PD, although uals with OSA have shorter progression times between cog- reported prevalence varies widely between 20 and 70.1% nitively normal (CN) to mild cognitive impairment (MCI) or [46]. There are indications that OSA may act as a risk factor MCI to AD [17]. One proposed mechanism through which before the onset of PD. In a recent meta-analysis performed by OSA could have an effect on AD pathology is via a dysregu- Sun et al. (2020), subjects with OSA were 1.56 times more lation of the Aβ metabolism caused by intermittent hypoxia likely to develop PD than controls [47]. The exact mecha- and reduced clearance from interstitial to cerebrospinal fluid nisms at play are still not fully understood, but, similar to (CSF) caused by sleep fragmentation, resulting in decreased AD, OSA, although not causing the disorder, likely plays a CSF Aβ 40 and 42 levels and increased Aβ plaque formation. role in promoting or enhancing PD-associated pre-clinical Recent studies support this, with Liguori et al. (2019) finding pathological processes. Concurrent with this, Sun et al. that CSF Aβ40 and 42 levels were lower in OSA patients than (2019) (N = 88) reported that both OSA severity and hypoxia those in control subjects but higher than those in AD subjects markers were associated with increased levels of plasma α- [14]; Jackson et al. (2020) (N = 46) finding that OSA severity, synuclein, a key protein involved in PD pathology, in healthy specifically during NREM sleep, was associated with in- adults [48]. With the onset of PD, the relationship between creased brain Aβ burden [42]; and André et al. (2020) identi- OSA and PD becomes more complex. While there is no evi- fying a significant association between increased florbetapir, a dence that the incidence of OSA is higher in the PD than that marker for amyloid plaques, uptake, and OSA presence [11]. in the non-PD population, OSA has an impact on the disorder Longitudinally, in a 2-year follow-up study on 208 CN sub- when present [47]. A meta-analysis performed by Elfi et al. jects, Sharma et al. (2018) identified a significant association (2020) found that subjects with PD and OSA showed greater between the annual rate of change of Aβ 42 and OSA sever- cognitive and motor deficits than subjects with PD but without ity, which was stronger than the change predicted by ApoE4, OSA [49]. Similar results were also observed by Meng et al. currently the strongest risk factor known for AD [15]. This (2020) and Kaminska et al. (2018) (same sample, N = 67), 94 Curr Sleep Medicine Rep (2021) 7:87–96 who additionally found that 12-month CPAP treatment result- pathways [4]. Firstly, the index combines both hypoxic and sleep ed in improved PD-associated non-motor symptoms and a fragmentation-related events, which individually influence neu- stabilisation of motor function [50, 51]. While this indicates rodegenerative processes, but not necessarily in an additive fash- that OSA has a detrimental effect on PD-associated cognitive ion. Furthermore, the index also only assesses the frequency, and motor functions, there are also findings that PD has an while completely ignoring the length of the individual events. effect on OSA severity. In the early stages of PD, the disorder A subject with few but very long events would therefore be has protective effects due to PD-induced weight loss, one of considered “healthier” than a subject with numerous but short the biggest risk factors for OSA, while PD-related factors such events, especially if cutoffs are used. Alternative scores such as as impaired ventilation control and upper airway motor insta- the arousal index and oxygen desaturation index, or to incorpo- bility might increase OSA severity as the disorder progresses rate length, metrics such as percentage/time of sleep spent below [52]. Support for the latter was published by Bahia et al. a certain oxygen saturation threshold, could prove to be much (2019) (N = 48), where PD subjects with a laryngopharyngeal more informative. motor dysfunction were three times more likely to have OSA In conclusion, while not being the cause, there are strong than those without the dysfunction [53]. indications that OSA is a major risk factor for neurodegener- ation and neurodegenerative disorders. OSA treatment was shown to alleviate some of the damage and improve cognitive Conclusion deficits. The underlying mechanisms, however, are yet to be fully understood, highlighting the need for large, preferably There is a complex relationship between OSA and neurodegen- longitudinal studies based on standardised metrics, and more eration, with both influencing each other and different aspects of importantly, assessing OSA-related hypoxia and sleep frag- the disorder having different effects. In this review, we have mentation separately. However, with no viable cure available summarised recent findings on the association between OSA for most neurodegenerative disorders, OSA shows to be a and brain structure, cognition, and the two most common neuro- promising target to delay their onset. degenerative disorders, namely Alzheimer’s dementia and Parkinson’s disease. Overall, recent studies reported associations Funding Open Access funding enabled and organized by Projekt between OSA and grey and white matter alterations [3, 10–12, DEAL. This work specifically was supported by the Deutsche 20, 22–24], and changes in brain diffusion [13, 25, 26], as well as Forschungsgemeinschaft (DFG, grant number: GR 1912/13-1). impaired cognition, specifically regarding memory [5, 6, 26, 32], attention [5, 7, 8, 30, 31], and executive control [7, 8]. Declarations Furthermore, subjects with OSA were found to have a higher risk of developing mild cognitive impairment (MCI) [5, 27], Conflict of Interest HJG has received travel grants and speaker’s hono- Alzheimer’sdementia[16, 17, 39–41], and Parkinson’sdisease raria from Fresenius Medical Care, Neuraxpharm, Servier, and Janssen Cilag as well as research funding from Fresenius Medical Care. [47], and show shorter progression times between cognitively normal and MCI or MCI and Alzheimer’s dementia [17]. But Human and Animal Rights and Informed Consent This article does not while these studies have added further insights, there are some contain any studies with human or animal subjects performed by any of discrepancies in their results and large gaps remain to get a com- the authors. prehensive overview of the exact mechanism at play here. Next Open Access This article is licensed under a Creative Commons to the problem of generally small sample sizes and the presence Attribution 4.0 International License, which permits use, sharing, adap- of a complex and dynamic system influenced by a variety of tation, distribution and reproduction in any medium or format, as long as factors, the lack of conclusive effects might be due to the way you give appropriate credit to the original author(s) and the source, pro- OSA itself is defined. A large majority of studies considered in vide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included this review have defined OSA as a categorical variable based on in the article's Creative Commons licence, unless indicated otherwise in a various AHI cutoffs, medical diagnoses, or self-reported symp- credit line to the material. If material is not included in the article's toms. Next to the difficulty of comparing such results between Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain different studies, there is also the question of what such an asso- permission directly from the copyright holder. To view a copy of this ciation represents, as such a broad phenotype makes it close to licence, visit http://creativecommons.org/licenses/by/4.0/. impossible to distinguish between effects caused by OSA and the ones caused by OSA-associated comorbidities such as obesity, hypertension, diabetes, or depression [54]. Using the continuous AHI instead could be a viable solution, although this does not References resolve all issues either. While this index, in combination with other symptoms, is enough to diagnose OSA in a clinical setting, 1. Benjafield AV, Ayas NT, Eastwood PR, Heinzer R, Ip MSM, it might not be valid to investigate specific OSA-related Morrell MJ, et al. 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Obstructive sleep apnea and Alzheimer’s disease- related cerebrospinal fluid biomarkers in mild cognitive impair- Publisher’sNote Springer Nature remains neutral with regard to jurisdic- ment. Sleep. 2021;44:1–8. tional claims in published maps and institutional affiliations.

Journal

Current Sleep Medicine Reports – Springer Journals

Published: Sep 1, 2021

Keywords: Obstructive sleep apnoea; Neurodegeneration; Alzheimer’s dementia; Parkinson’s disease; Cognitive impairment

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