Association of Polysomnography‐Assessed Sleep Parameters with Alzheimer’s Disease Biomarkers in Older Adults
Background over the past decade, a bi‐directional relationship between sleep and Alzheimer’s disease (AD) has been increasingly recognized, with several studies suggesting a link between self‐reported sleep disturbances and AD biomarkers. However, the association between polysomnography (PSG)‐assess...
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Published in | Alzheimer's & dementia Vol. 20; no. S7 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Hoboken
John Wiley and Sons Inc
01.12.2024
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Subjects | |
Online Access | Get full text |
ISSN | 1552-5260 1552-5279 |
DOI | 10.1002/alz.088517 |
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Abstract | Background
over the past decade, a bi‐directional relationship between sleep and Alzheimer’s disease (AD) has been increasingly recognized, with several studies suggesting a link between self‐reported sleep disturbances and AD biomarkers. However, the association between polysomnography (PSG)‐assessed sleep parameters and AD biomarkers remains unknown.
Method
We examined 128 participants [mean age 70.9 (±9.7) years, 43.8% of men; 23 healthy controls (HC), 41 with mild cognitive impairment (MCI), and 64 with AD] from an outpatient memory clinic. Sleep features were derived from overnight PSG and were categorized by tertiles. Four AD biomarkers were measured, including tau‐181, Brain‐Derived Neurotrophic Factor (BDNF), and neurofilament light (NFL) obtained from blood samples, and Aβ levels measured from amyloid positron emission tomography scans. We used multivariable linear regression models to examine the associations between sleep parameters and AD biomarkers.
Result
After adjustment for age, sex, APOE4 status, diabetes, smoking habits, and body mass index, participants in the highest tertile of rapid eye movement (REM) latency (>192.7 minutes) had higher tau‐181 (β = 0.25, 95% confidence interval (CI) = 0.01;0.55) and Aβ (β = 0.15, 95% CI = 0.06;0.26) levels, and lower BDNF (β = ‐0.51, 95% CI = ‐0.70;‐0.20) compared to the lowest tertile (< 98.2 minutes). Moreover, participants in the middle slow wave sleep (SWS) percentage tertile (2.5‐10.2%) had lower tau‐181 levels (β = ‐0.18, 95% CI = ‐0.34;‐0.02) compared to those in the lowest tertile (< 2.5%). We did not find any association between AD biomarkers and sleep duration, efficiency, latency, or other sleep macro‐architecture features. The association between sleep and AD biomarkers did not differ by cognitive diagnoses (i.e., NC, MCI, or AD).
Conclusion
Longer REM latency was associated with higher levels of AD biomarkers in older adults with and without cognitive impairment. Future research is needed to examine the longitudinal association between sleep architecture and AD biomarkers and clarify underlying mechanisms. |
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AbstractList | Background
over the past decade, a bi‐directional relationship between sleep and Alzheimer’s disease (AD) has been increasingly recognized, with several studies suggesting a link between self‐reported sleep disturbances and AD biomarkers. However, the association between polysomnography (PSG)‐assessed sleep parameters and AD biomarkers remains unknown.
Method
We examined 128 participants [mean age 70.9 (±9.7) years, 43.8% of men; 23 healthy controls (HC), 41 with mild cognitive impairment (MCI), and 64 with AD] from an outpatient memory clinic. Sleep features were derived from overnight PSG and were categorized by tertiles. Four AD biomarkers were measured, including tau‐181, Brain‐Derived Neurotrophic Factor (BDNF), and neurofilament light (NFL) obtained from blood samples, and Aβ levels measured from amyloid positron emission tomography scans. We used multivariable linear regression models to examine the associations between sleep parameters and AD biomarkers.
Result
After adjustment for age, sex, APOE4 status, diabetes, smoking habits, and body mass index, participants in the highest tertile of rapid eye movement (REM) latency (>192.7 minutes) had higher tau‐181 (β = 0.25, 95% confidence interval (CI) = 0.01;0.55) and Aβ (β = 0.15, 95% CI = 0.06;0.26) levels, and lower BDNF (β = ‐0.51, 95% CI = ‐0.70;‐0.20) compared to the lowest tertile (< 98.2 minutes). Moreover, participants in the middle slow wave sleep (SWS) percentage tertile (2.5‐10.2%) had lower tau‐181 levels (β = ‐0.18, 95% CI = ‐0.34;‐0.02) compared to those in the lowest tertile (< 2.5%). We did not find any association between AD biomarkers and sleep duration, efficiency, latency, or other sleep macro‐architecture features. The association between sleep and AD biomarkers did not differ by cognitive diagnoses (i.e., NC, MCI, or AD).
Conclusion
Longer REM latency was associated with higher levels of AD biomarkers in older adults with and without cognitive impairment. Future research is needed to examine the longitudinal association between sleep architecture and AD biomarkers and clarify underlying mechanisms. |
Author | Stankeviciute, Laura Cavaillès, Clémence Winer, Joseph R. Chen, Jiong Milton, Sasha Jin, Jiangli Peng, Dantao Leng, Yue Gao, Song |
AuthorAffiliation | 2 University of California, San Francisco, San Francisco, CA USA 5 Stanford University School of Medicine, Stanford, CA USA 6 Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA USA 1 Peking University Health Science Center, Beijing City, Beijing China 4 Barcelonaβeta Brain Research Center (BBRC), Barcelona Spain 3 China‐Japan Friendship Hospital, Beijing City, Beijing China |
AuthorAffiliation_xml | – name: 2 University of California, San Francisco, San Francisco, CA USA – name: 4 Barcelonaβeta Brain Research Center (BBRC), Barcelona Spain – name: 3 China‐Japan Friendship Hospital, Beijing City, Beijing China – name: 1 Peking University Health Science Center, Beijing City, Beijing China – name: 5 Stanford University School of Medicine, Stanford, CA USA – name: 6 Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA USA |
Author_xml | – sequence: 1 givenname: Jiong surname: Chen fullname: Chen, Jiong organization: Peking University Health Science Center, Beijing City, Beijing – sequence: 2 givenname: Clémence surname: Cavaillès fullname: Cavaillès, Clémence organization: University of California, San Francisco, San Francisco, CA – sequence: 3 givenname: Jiangli surname: Jin fullname: Jin, Jiangli organization: China‐Japan Friendship Hospital, Beijing City, Beijing – sequence: 4 givenname: Laura surname: Stankeviciute fullname: Stankeviciute, Laura organization: Barcelonaβeta Brain Research Center (BBRC), Barcelona – sequence: 5 givenname: Joseph R. surname: Winer fullname: Winer, Joseph R. organization: Stanford University School of Medicine, Stanford, CA – sequence: 6 givenname: Song surname: Gao fullname: Gao, Song organization: Peking University Health Science Center, Beijing City, Beijing – sequence: 7 givenname: Dantao surname: Peng fullname: Peng, Dantao organization: China‐Japan Friendship Hospital, Beijing City, Beijing – sequence: 8 givenname: Yue surname: Leng fullname: Leng, Yue organization: Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA – sequence: 9 givenname: Sasha surname: Milton fullname: Milton, Sasha email: sasha.milton@ucsf.edu organization: University of California, San Francisco, San Francisco, CA |
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Copyright | 2024 The Alzheimer's Association. published by Wiley Periodicals LLC on behalf of Alzheimer's Association. |
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over the past decade, a bi‐directional relationship between sleep and Alzheimer’s disease (AD) has been increasingly recognized, with several... |
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Title | Association of Polysomnography‐Assessed Sleep Parameters with Alzheimer’s Disease Biomarkers in Older Adults |
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