Taylor J. Pedersen, Ruijin Lu, Cristina Toedebusch, Ashley Hess, Rachel Richardson, Allyson Quigley, Carling G. Robinson, John C. Morris, David M. Holtzman, Chengjie Xiong, Brian A. Gordon, Brendan P. Lucey
{"title":"纵向睡眠监测在淀粉样蛋白阴性和淀粉样蛋白阳性认知未受损和轻度受损老年人中的变异性","authors":"Taylor J. Pedersen, Ruijin Lu, Cristina Toedebusch, Ashley Hess, Rachel Richardson, Allyson Quigley, Carling G. Robinson, John C. Morris, David M. Holtzman, Chengjie Xiong, Brian A. Gordon, Brendan P. Lucey","doi":"10.1002/alz.70761","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> INTRODUCTION</h3>\n \n <p>Sleep disturbances are associated with Alzheimer's disease (AD) pathology and cognitive symptoms, but few studies have longitudinally assessed sleep, AD biomarkers, and cognition. Understanding how sleep changes over time in older adults with and without AD pathology is crucial for appropriately designing longitudinal studies of aging and AD.</p>\n </section>\n \n <section>\n \n <h3> METHODS</h3>\n \n <p>Sleep was measured over ≈3.5 years in older adults using self-reported questionnaires and an at-home single-channel electroencephalography (scEEG) device. Participants also underwent amyloid imaging and cognitive testing. Longitudinal change of multiple sleep parameters was determined and sample sizes estimated for future clinical trials using sleep as an outcome.</p>\n </section>\n \n <section>\n \n <h3> RESULTS</h3>\n \n <p>In both amyloid groups, EEG spectral power measures demonstrated minimal longitudinal change, whereas self-reported and sleep parameters such as sleep efficiency demonstrated greater variability over time.</p>\n </section>\n \n <section>\n \n <h3> DISCUSSION</h3>\n \n <p>This study characterized how sleep parameters change in older adults with and without AD pathology, offering important guidance for future longitudinal studies targeting sleep and neurodegeneration.</p>\n </section>\n \n <section>\n \n <h3> Highlights</h3>\n \n <div>\n <ul>\n \n <li>Low variability in electroencephalography (EEG) spectral power metrics, including delta, theta, and alpha power.</li>\n \n <li>Greater variability in self-report sleep metrics, including self-reported time to fall asleep and EEG-derived metrics such as sleep duration and N2 sleep.</li>\n \n <li>Understanding the variability in sleep measures over time will offer important guidance for designing future longitudinal studies targeting sleep and neurodegeneration.</li>\n </ul>\n </div>\n </section>\n </div>","PeriodicalId":7471,"journal":{"name":"Alzheimer's & Dementia","volume":"21 10","pages":""},"PeriodicalIF":11.1000,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://alz-journals.onlinelibrary.wiley.com/doi/epdf/10.1002/alz.70761","citationCount":"0","resultStr":"{\"title\":\"Variability of longitudinal sleep monitoring in amyloid-negative and amyloid-positive cognitively unimpaired and mildly impaired older adults\",\"authors\":\"Taylor J. Pedersen, Ruijin Lu, Cristina Toedebusch, Ashley Hess, Rachel Richardson, Allyson Quigley, Carling G. Robinson, John C. Morris, David M. Holtzman, Chengjie Xiong, Brian A. Gordon, Brendan P. Lucey\",\"doi\":\"10.1002/alz.70761\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> INTRODUCTION</h3>\\n \\n <p>Sleep disturbances are associated with Alzheimer's disease (AD) pathology and cognitive symptoms, but few studies have longitudinally assessed sleep, AD biomarkers, and cognition. Understanding how sleep changes over time in older adults with and without AD pathology is crucial for appropriately designing longitudinal studies of aging and AD.</p>\\n </section>\\n \\n <section>\\n \\n <h3> METHODS</h3>\\n \\n <p>Sleep was measured over ≈3.5 years in older adults using self-reported questionnaires and an at-home single-channel electroencephalography (scEEG) device. Participants also underwent amyloid imaging and cognitive testing. Longitudinal change of multiple sleep parameters was determined and sample sizes estimated for future clinical trials using sleep as an outcome.</p>\\n </section>\\n \\n <section>\\n \\n <h3> RESULTS</h3>\\n \\n <p>In both amyloid groups, EEG spectral power measures demonstrated minimal longitudinal change, whereas self-reported and sleep parameters such as sleep efficiency demonstrated greater variability over time.</p>\\n </section>\\n \\n <section>\\n \\n <h3> DISCUSSION</h3>\\n \\n <p>This study characterized how sleep parameters change in older adults with and without AD pathology, offering important guidance for future longitudinal studies targeting sleep and neurodegeneration.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Highlights</h3>\\n \\n <div>\\n <ul>\\n \\n <li>Low variability in electroencephalography (EEG) spectral power metrics, including delta, theta, and alpha power.</li>\\n \\n <li>Greater variability in self-report sleep metrics, including self-reported time to fall asleep and EEG-derived metrics such as sleep duration and N2 sleep.</li>\\n \\n <li>Understanding the variability in sleep measures over time will offer important guidance for designing future longitudinal studies targeting sleep and neurodegeneration.</li>\\n </ul>\\n </div>\\n </section>\\n </div>\",\"PeriodicalId\":7471,\"journal\":{\"name\":\"Alzheimer's & Dementia\",\"volume\":\"21 10\",\"pages\":\"\"},\"PeriodicalIF\":11.1000,\"publicationDate\":\"2025-10-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://alz-journals.onlinelibrary.wiley.com/doi/epdf/10.1002/alz.70761\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Alzheimer's & Dementia\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://alz-journals.onlinelibrary.wiley.com/doi/10.1002/alz.70761\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CLINICAL NEUROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Alzheimer's & Dementia","FirstCategoryId":"3","ListUrlMain":"https://alz-journals.onlinelibrary.wiley.com/doi/10.1002/alz.70761","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
Variability of longitudinal sleep monitoring in amyloid-negative and amyloid-positive cognitively unimpaired and mildly impaired older adults
INTRODUCTION
Sleep disturbances are associated with Alzheimer's disease (AD) pathology and cognitive symptoms, but few studies have longitudinally assessed sleep, AD biomarkers, and cognition. Understanding how sleep changes over time in older adults with and without AD pathology is crucial for appropriately designing longitudinal studies of aging and AD.
METHODS
Sleep was measured over ≈3.5 years in older adults using self-reported questionnaires and an at-home single-channel electroencephalography (scEEG) device. Participants also underwent amyloid imaging and cognitive testing. Longitudinal change of multiple sleep parameters was determined and sample sizes estimated for future clinical trials using sleep as an outcome.
RESULTS
In both amyloid groups, EEG spectral power measures demonstrated minimal longitudinal change, whereas self-reported and sleep parameters such as sleep efficiency demonstrated greater variability over time.
DISCUSSION
This study characterized how sleep parameters change in older adults with and without AD pathology, offering important guidance for future longitudinal studies targeting sleep and neurodegeneration.
Highlights
Low variability in electroencephalography (EEG) spectral power metrics, including delta, theta, and alpha power.
Greater variability in self-report sleep metrics, including self-reported time to fall asleep and EEG-derived metrics such as sleep duration and N2 sleep.
Understanding the variability in sleep measures over time will offer important guidance for designing future longitudinal studies targeting sleep and neurodegeneration.
期刊介绍:
Alzheimer's & Dementia is a peer-reviewed journal that aims to bridge knowledge gaps in dementia research by covering the entire spectrum, from basic science to clinical trials to social and behavioral investigations. It provides a platform for rapid communication of new findings and ideas, optimal translation of research into practical applications, increasing knowledge across diverse disciplines for early detection, diagnosis, and intervention, and identifying promising new research directions. In July 2008, Alzheimer's & Dementia was accepted for indexing by MEDLINE, recognizing its scientific merit and contribution to Alzheimer's research.