Brain and Systemic Oxygenation Coupling in Sleep-Disordered Breathing Tied to Cognition in Elderly

doi:10.21203/rs.3.rs-4908970/v1

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Brain and Systemic Oxygenation Coupling in Sleep-Disordered Breathing Tied to Cognition in Elderly

https://doi.org/10.21203/rs.3.rs-4908970/v1

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Background: Intermittent hypoxia, one of the consequences of sleep-disordered breathing (SDB), could contribute to an increased risk of cognitive decline. However, the association between SDB and cognition varies widely.

Methods: Fifty-two community-dwelling healthy older adults (28 women) without dementia were recruited. All participants underwent neuropsychiatric evaluations, simultaneous in-home polysomnography (PSG), and NIRS recordings. We quantified the average coherence between oxy-Hb and SpO2 signals during SDB events to see if it can predict cognitive outcomes in healthy older adults, where higher coherence represents less protection against systemic hypoxia.

Results: The mean (SD) coherence of oxy-Hb and SpO2 was 0.16 (0.07). Linear regression analysis showed a significant association between mean coherence and increased age and education-adjusted Stroop Color Word Test scores (t=-.304, p=.004). Whereas, oxy-Hb reduction alone did not show a significant association with cognition, and there were no significant correlations between conventional SDB parameters and cognition.

Conclusion: A higher coherence rate of cortical oxy-Hb and systemic SpO2 during SDB possibly reflects a loss of compensatory mechanism against systemic hypoxia and may help stratify older adults with a higher risk for cognitive decline. This is the first report on the association between NIRS parameters in SDB and cognition in older adults.

Biological sciences/Neuroscience/Cognitive ageing

Health sciences/Neurology/Neurological disorders/Sleep disorders

Sleep-disordered breathing (SDB), including conditions such as obstructive sleep apnea (OSA), is prevalent among older adults, with incidence rates ranging from 9% to 60% ^1,2. Untreated SDB has emerged as a recognized risk factor for mild cognitive impairment (MCI) and dementia ^3,4, with numerous studies linking SDB to cognitive dysfunction and neurodegeneration ^3,5. However, the precise mechanism by which SDB contributes to cognitive dysfunction in older adults remains elusive. The association between the apnea-hypopnea index (AHI), commonly used to gauge SDB severity, and cognition remains contentious. Several studies have failed to establish a significant correlation between AHI and cognitive impairment ^6-8. Conversely, hypoxia has been implicated in cognitive decline, suggesting that AHI’s mixed hypoxic and sleep-fragmentation components might weaken its association with cognition ⁹.

Near-infrared spectroscopy (NIRS) offers a promising avenue to investigate the direct impact of SDB on the brain cortex by monitoring cortical oxygenation during SDB events. NIRS measures changes in cortical oxyhemoglobin (oxy-Hb) and deoxyhemoglobin (deoxy-Hb) levels. Emitting two light beams with wavelengths between 700–1300 nm onto the scalp, NIRS detects reflected light beams using photodiodes ^10,11. Oxy-Hb provides a more direct measurement of cerebral oxygenation, while total or deoxy-Hb represents hemodynamic activities. Despite several studies that have used NIRS to assess cortical oxygenation during SDB events, there remains a notable absence of research exploring the association between NIRS parameters during SDB events and cognition in older adults ^12-14. Various factors contribute to this gap in research, including 1) the technical challenges of conducting simultaneous NIRS and polysomnography (PSG) recordings, 2) the uncertainty regarding appropriate neuropsychiatric measures to evaluate the impact of SDB on cognition in older adults, and 3) an insufficient sample size to discern the effect accurately.

Another critical consideration is the individual variability in the compensation mechanism strength during SDB events. Reports suggest defects in the neuromuscular compensation mechanism in the upper airway of patients with SDB ¹⁵. Additionally, sex differences in the muscular compensation mechanism during Non-rapid eye movement (NREM) sleep have been proposed ¹⁶. The cortical arousal response is also regarded as a compensatory mechanism in SDB ^17,18. However, the cortical arousal response, as detected through surface electroencephalogram (EEG) and upper airway opening in patients with SDB, exhibits considerable variation ^17-19.

To date, no PSG or NIRS parameter has been used to measure the strength of compensation against SDB to prevent cortical oxygen desaturation. A study in children reported a decline in cerebral oxygenation preceding the detection of peripheral oxygen desaturation by pulse oximetry during sleep²⁰. Focusing on the coherence of oxy-Hb and peripheral oxygen saturation as a compensation maker during SDB, with a higher ratio representing lower compensation, we conducted simultaneous NIRS and PSG recordings during SDB events to gain new insights into the impact of SDB on cognition in cognitively healthy, community-dwelling older adults.

Study population

52 community-dwelling cognitively healthy older adults were enrolled in the study, following approval from the Institutional Review Board on Human and Animal Research at Stanford University. This research was performed in accordance with the Declaration of Helsinki. Informed consent was obtained from all participants. The inclusion criteria were the following: 60 years of age or older, a score of ≥26 in the Mini-Mental State Exam (MMSE), absence of a diagnosis of possible or probable dementia or a profile on the cognitive battery indicative of dementia, lack of any serious medical illness, and any axis I disorder assessed using the Structured Clinical Interview for DSM-5 within the last two years or major unstable medical diseases or symptoms.

The mean and standard deviation (SD) of participants’ ages and years of education were 72.0 (7.1) and 17.5 (2.8), respectively. Of the 52 participants, 28 were women, 43 identified as Caucasians, and nine identified as Asians.

All participants underwent overnight ambulatory PSG coupled with NIRS recordings at their residences. Adherence to participants’ natural sleep-wake schedules was emphasized throughout the study protocol.

Procedures

Cognitive battery

Participants underwent a comprehensive cognitive assessment utilizing a battery of tests designed to detect mild cognitive impairment (MCI) in older adults ³³. The cognitive domains examined included: 1) delayed verbal recall on the Rey Auditory Verbal Learning Test 20-minute delay trial (RAVLT) ³⁴, 2) information processing speed and attention on the Stroop Color and Word Test (STRCW) ³⁵, 3) phonemic fluency and executive function on Controlled Oral Word Association (COWA) ³⁶, 4) verbal naming on the Boston Naming Test (BNT) ³⁷, and 5) visuospatial ability on the Judgment of Line Orientation (JLO) ³⁸. Notably, participants were screened for color blindness prior to undertaking the STRCW, with none being identified as such. Prior research has consistently associated older age with diminished performance on delayed recall measures ^39,40, while deficits in the remaining cognitive domains are prevalent in older adults and indicative of heightened risk for cognitive decline and dementia ⁴¹. Additionally, the MMSE was administered to provide a succinct assessment of overall cognitive functioning. All selected measures have demonstrated validity and widespread applicability in older populations ^34,35,37,38.

PSG and NIRS recording

For overnight NIRS recordings during sleep, we utilized the Octamon® NIRS system equipped with flat light emitting diode (LED) optodes to mitigate sleep disturbances. To optimize battery usage and minimize interference from hair during overnight recording, data collection was restricted to a single NIRS channel (optode-receiver pair) positioned on the left frontal region. Firm attachment of the probe to the forehead was ensured using a headband. Simultaneous PSG recordings were conducted using the Nox A1 PSG monitoring system, which captures EEG, electrooculogram, submental electromyogram, nasal airway pressure, nasal thermal airflow sensor, finger pulse oximetry, electrocardiogram, rib cage and abdominal movements, snoring, and body position. Following the application of PSG electrodes and NIRS probes, participants adhered to their natural sleep-wake schedules. Data was recorded continuously throughout the night, retrieved the subsequent day, and stored digitally. Sleep stages were manually and visually scored by a board-certified sleep technician or physician according to established standard conventions ⁴². Respiratory events were identified and scored using standard definitions, with related sleep parameters derived from established methodologies ⁴³.

Analytical approach: First, PSG data were visually scored based on standard AASM criteria ⁴⁴. Subsequent quality checks and preprocessing of NIRS data were conducted using an in-house package and Homer 2 in MATLAB ^45-47. Motion artifacts in the optical density data were corrected using a wavelet motion correction procedure, followed by band-pass filtering with cutoff frequencies of 0.008 Hz and 0.5 Hz before conversion to oxy-Hb using the modified Beers-Lambert law ⁴⁸. Next, SDB desaturation events, characterized by a 3% or greater reduction in oxygen saturation from baseline, were scored and visually confirmed. For each SDB desaturation event, the reduction in oxy-Hb was quantified as the maximum drop in oxy-Hb signal normalized by baseline oxy-Hb. Coherence between extracted oxy-Hb and oxygen saturation (SpO₂) signals was quantified using wavelet coherence for each SDB event ^49,50. The mean wavelet coherence values were averaged across the SDB events. Subsequently, the association between the mean coherence of SDB events and cognitive measures was examined. A lower coherence between oxy-Hb and SpO₂ signal would suggest higher decoupling and stronger compensation against peripheral oxygen drops at the cortical level (Figure 1).

Primary analysis: We examined whether the mean coherence of oxy-Hb and SpO₂ during SDB desaturation events could predict cognition. We performed a linear regression analysis using the RAVLT delayed recall, STRCW, COWA, BNT, and JLO scores as dependent variables. For each primary outcome measure, we conducted linear regression with mean coherence, while adjusting for age, sex, and education.

Secondary analysis: We examined if changes in the NIRS parameters, specifically the reduction of oxy-Hb during desaturation events, could serve as predictors of cognition.Similar to the primary analysis, we performed a linear regression analysis, considering the RAVLT delayed recall, STRCW, COWA, BNT, and JLO scores as dependent variables. For each secondary outcome measure, we conducted linear regression with the change in oxy-Hb during SDB, while adjusting for age, sex, and education.

Exploratory analysis: We further investigated associations between conventional SDB-related sleep parameters and cognitive measures by performing Spearman’s bivariate correlations. This analysis encompassed parameters from both SDB-related sleep (including AHI, ODI 3%, ODI 4%, duration of desaturation less than 90%, and lowest SpO₂) and cognitive measures (comprising RAVLT, STRCW, COWA, BNT, and JLO scores) across all participants.

Adjustment for multiple comparisons: To account for multiple comparisons across the primary, secondary, and exploratory analyses involving five cognitive measures (RAVLT delayed recall, STRCW, COWA, BNT, and JLO), we implemented Bonferroni correction. With a corrected alpha of .05/5, equating to .01, this correction ensures the maintenance of statistical rigor.

Sleep and SDB parameters

The mean (SD) values for total sleep time, sleep latency, wake after sleep onset, N1, N2, N3, REM, REM latency were 397.5 (62.3) min, 71.0 (50.3) min, 74.8 (50.1) min, 13.8 (13.2)%, 56.5 (13.2)% 16.3 (17.9)%, 15.7 (5.7), and 135.2 (83.6) min, respectively. Additionally, the mean (SD) values for AHI, lowest SpO₂, Oxygen Desaturation Index (ODI) 3%, and duration of SpO₂ < 90% were 21.2 (17.3) events/hour, 84.5 (5.8)%, 15.4 (16.3) events/hour, and 40.3 (81.3) min, respectively (Table 1).

Table 1

Demographics and sleep parameters
	M	SD
Age	72.0	7.1
Sex (number, percentage female)	28 (53.8%)
Total sleep time (min)	397.5	62.3
Sleep latency (min)	71.0	50.3
WASO (min)	74.8	50.1
N1 (%)	13.8	13.2
N2 (%)	56.5	13.2
N3 (%)	16.3	17.9
REM (%)	15.7	5.7
REM latency (min)	135.2	83.6
AHI (events/hour)	21.2	17.3
Lowest SpO2 (%)	84.5	5.8
ODI 3% (events/hour)	15.4	16.3
Duration of SpO2 < 90% (min)	40.3	81.3
M: mean, SD: standard deviation; WASO: wake after sleep onset; N1: NREM 1, N2: NREM 2, N3: NREM 3, REM: rapid eye movement sleep, AHI: apnea-hypopnea index; SpO₂: oxygen saturation; ODI: oxygen desaturation index.

Primary analysis

The mean (SD) of the mean coherence of oxy-Hb and SpO₂ was 0.16 (0.07). Linear regression analysis revealed a significant association between mean coherence and worse age and education-adjusted Stroop Color Word Test score (t=-.304, p = .004) (Fig. 2), covarying for sex. Notably, this correlation remained significant after applying Bonferroni correction for multiple comparisons. Additionally, a trend association between mean coherence and worse COWA is suggested (t=-2.66, p = .011), albeit it failed to meet the Bonferroni correction threshold. However, no significant associations were observed with other cognitive measures, including RAVLT (t=-1.662, p = .103), BNT (t = .188, p = .852), and JLO (t = .008, p = .994).

Secondary analysis

As defined above, The mean (SD) of the oxy-Hb reduction from the baseline was 25 (15.7) during SDB desaturation events. While a trend association between oxy-Hb reduction and worse BNT is suggested (t=-2.216, p = .032), it did not pass Bonferroni correction. No significant associations were found between the oxy-Hb reduction and the RAVLT (t = .273, p = .786), JLO (t = .980, p = .332), STRCW (t = 1.522, p = .135), or COWA (t = 1.131, p = .264) scores.

Exploratory Analysis

Bivariate correlation analysis did not show a significant association between conventional SDB measures, including AHI, ODI 3%, ODI 4%, duration of desaturation less than 90%, and lowest SpO₂, and cognitive measures (p > .027), even after applying a Bonferroni-corrected alpha of .01.

The mean coherence of oxy-Hb and SpO₂ during SDB desaturation events significantly correlated with poor performance on the Stroop Color Word Test. This association remained significant even after applying Bonferroni correction to adjust for multiple comparisons. changes in oxy-Hb levels were not significantly associated with other cognitive function measures. Furthermore, exploratory analyses revealed no significant association between cognitive measures and conventional SDB parameters, including AHI, lowest SpO₂, ODI3%, ODI4%, and the duration of SpO₂ lower than 90%. These findings suggest that the impairment in compensatory mechanisms against hypoxia may be a more relevant risk factor for cognitive decline in older adults than traditional SDB measures. This study represents the first report of an association between NIRS parameters during SDB events and cognition in older adults.

Impact of SDB on cognition

Prior research has highlighted The negative effects of SDB on cognitive function, particularly in older adults, have been previously discussed ⁴. However, the association is complex. Several studies report a higher risk of cognitive impairment in patients with untreated SDB ^3,5,21. One meta-analysis showed that patients with OSA performed worse in vigilance (effect size d = 1.4), executive function (d = .73), and motor skills (d = 1.21) ²¹. Interestingly, we did not observe significant differences in similar analyses comparing groups with and without OSA (we performed either an AHI cut-off of 15 or 5). This suggests that AHI alone may not be a sensitive parameter to predict cognition in older adults. Hypoxia and sleep fragmentation have been suggested as possible mechanisms underlying the impact of SDB on cognition ²². The association of sleep fragmentation from SDB with cognition is controversial ^9,23. While the systemic hypoxia hypothesis appears more promising than sleep fragmentation, it lacks consistent results. Findley et al. reported that patients with hypoxia and OSA had significantly poorer cognitive function ⁹. In addition, hypoxia has also been suggested as a mechanism involved in Alzheimer's disease (AD) pathology. Sun et al. reported that under hypoxic conditions in mice, amyloid plaque formation was significantly enhanced compared to standard oxygen conditions ²⁴. Blackwell et al. also found a significant association between ODI and global cognitive measures ⁶. However, Alomir et al. reported no association between hypoxia and memory, although an association between hypoxia and attention was found ²⁵. Hence, the domain of cognition most vulnerable to SDB remains unclear.

NIRS and SDB

NIRS has been used to measure the direct impact of oxygen desaturation on the brain during SDB. Prior studies have reported significant changes in cerebral hemodynamics with decreased oxy-Hb and increased deoxy-Hb levels during SDB initiation ^26,27. However, changes in oxy-Hb and deoxy-Hb levels after the initiation of SDB events have been inconsistent ²⁸. It has been suggested that changes in cerebral oxygenation during SDB are caused by complex physiological interactions, including heart rate, age, and sleep stage ²⁸. Using NIRS, Olopade et al. compared 19 patients with OSA to 14 healthy controls and reported lower tissue oxygen levels in the cortex during sleep in patients with OSA ¹². Pizza et al. reported that lower cerebral oxygenation is associated with higher severity of SDB ¹⁴. The changes in SpO₂ and cerebral oxygenation were strongly correlated in the case of severe SDB ^14,29. However, this correlation is weaker for milder SDB ^28,29. These findings suggest a compensatory mechanism in cerebral oxygenation during systemic hypoxemia.

During episodes of hypoxia, cerebral vasculature typically induces cerebrovascular vasodilation to manage oxygen delivery ³⁰, a response known to be affected by aging, particularly during cerebrovascular remodeling ³¹. However, the association between the regulation of cerebral blood flow and cognition has not been clear ³².

Our study utilized the coherence between oxy-Hb changes in the frontal cortex and peripheral SpO₂ changes from a pulse oximeter during oxygen desaturation events to evaluate the potential compensation mechanisms during SDB. We postulate that the coupling between changes in peripheral SpO₂ and cortical oxy-Hb, as indicated by increased coherence, represents lower compensation and predicts cognitive decline. A higher coherence rate was associated with worse STRCW scores, which is used to evaluate executive function. A previous study reported that a higher ODI is associated with the risk of developing MCI or dementia ²³. Our findings also suggest a potential mechanism linking oxygen desaturation to the development of MCI and AD.

We did not observe any association between coherence and other cognitive measures, nor did we observe a significant association between the reduction in oxy-Hb alone or the conventional SDB parameters with cognition. Thus, the loss of compensation mechanism, measured by coherence of oxy-Hb and desaturation, represents a more direct negative impact of SDB on cognitive function in older adults.

Limitations of our study include 1) the relatively small sample size owing to the technical difficulty in keeping the NIRS probe overnight with PSG at home in a non-technologist-observed ambulatory PSG setting, 2) the use of only a frontal NIRS probe due to discomfort and battery capacity of NIRS device, and 3) the relatively complicated post-hoc synchronization of two recording systems. However, the strengths of our study include 1) comprehensive cognitive measures, 2) simultaneous recording of NIRS and PSG, and 3) probing the compensation mechanism during SDB by examining the coupling between cortical and peripheral oxygenation.

In conclusion, the strength of the compensation mechanism during SDB, measured by the coupling of cortical oxy-Hb and peripheral SpO₂ changes and not the parameters directly reflecting peripheral or central oxygen desaturation, may predict cognitive decline in healthy community-dwelling older adults.

This study highlights the importance of the coherence between cortical oxygenated hemoglobin (oxy-Hb) and systemic oxygen saturation (SpO2) during sleep-disordered breathing (SDB) events as a predictor of cognitive impairment in older adults. Our findings suggest that higher coherence, indicating a loss of compensatory mechanisms against hypoxia, is significantly associated with poorer executive function, as measured by the Stroop Color Word Test. Traditional SDB severity measures, such as the apnea-hypopnea index (AHI), did not show significant correlations with cognitive outcomes, underscoring the need for novel biomarkers like NIRS to better predict the impact of SDB on cognition. Despite limitations, including the small sample size and technical challenges, this study provides new insights into the mechanistic links between SDB and cognitive dysfunction, emphasizing the potential of using NIRS parameters to identify older adults at higher risk for cognitive decline.

Author Contribution

M.K.:• Conceptualization: M.K. conceived the research idea and designed the experimental framework.• Methodology: M.K. developed the experimental methodology and performed comprehensive statistical analyses, including data validation.• Investigation: M.K. led the experimental execution, including data collection and primary data interpretation.• Writing – Original Draft Preparation: M.K. drafted the manuscript.• Writing – Review & Editing: M.K. critically revised the manuscript for important intellectual content and approved the final version.S.M.H.H.:• Conceptualization: S.M.H.H. co-conceived the research idea and contributed to the experimental design alongside M.K.• Methodology: S.M.H.H. developed the methodology with a focus on post hoc signal processing and contributed to advanced statistical analyses.• Writing – Review & Editing: S.M.H.H. reviewed the draft manuscript, provided critical revisions, and approved the final manuscript.C.B.:• Investigation: C.B. contributed to the execution of experiments, including data collection and initial data analysis.• Writing – Review & Editing: C.B. reviewed the manuscript, provided substantive feedback, and approved the final version.R.K.:• Investigation: R.K. conducted experimental procedures and contributed to data acquisition and analysis.• Writing – Review & Editing: R.K. reviewed and revised the manuscript, offering key insights, and approved the final manuscript.K.P.F.:• Investigation: K.P.F. participated in the experiments and was involved in data collection and preliminary analysis.• Writing – Review & Editing: K.P.F. reviewed the manuscript, provided critical feedback, and approved the final version.P.T.T.:• Investigation: P.T.T. contributed to experimental implementation and data gathering.• Writing – Review & Editing: P.T.T. reviewed the manuscript for accuracy and integrity, provided necessary revisions, and approved the final manuscript.All authors have read and approved the final manuscript.

Acknowledgement

The authors thank Dr. Ruth O’Hara for her in-depth and constructive instruction and mentorship. We thank Ms. Isabelle Cotto for her support and communication while this work was written.

Data Availability

The datasets used and analysed during the current study available from the corresponding author on reasonable request.

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No competing interests reported.

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Reviews received at journal
22 Sep, 2024
Reviewers agreed at journal
21 Sep, 2024
Reviewers agreed at journal
29 Aug, 2024
Reviewers invited by journal
29 Aug, 2024
Editor assigned by journal
29 Aug, 2024
Editor invited by journal
27 Aug, 2024
Submission checks completed at journal
26 Aug, 2024
First submitted to journal
13 Aug, 2024

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Brain and Systemic Oxygenation Coupling in Sleep-Disordered Breathing Tied to Cognition in Elderly

Status:

Version 1

Abstract

Figures

Introduction

Methods

Results

Sleep and SDB parameters

Primary analysis

Secondary analysis

Exploratory Analysis

Discussion

Conclusions

Declarations

Author Contribution

Acknowledgement

Data Availability

References

Additional Declarations

Status:

Version 1