Sleep associated electrophysiological activity in subjects at different levels of risk of developing Alzheimer’s disease

Background Alzheimer’s disease (AD) is tightly associated with sleep alterations: as the disease progresses, sleep quality worsens. Therefore, the study of sleep patterns in interaction with other variables could constitute an early biomarker of AD. It is widely known that sleep alterations lead to...

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Veröffentlicht in:Alzheimer's & dementia 2022-12, Vol.18 (S5), p.n/a
Hauptverfasser: García‐Colomo, Alejandra, Nebreda, Alberto, de Frutos, Jaisalmer, Carrasco‐Gómez, Martín, Fernández, Ricardo Bruña, Maestú, Fernando
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Sprache:eng
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Zusammenfassung:Background Alzheimer’s disease (AD) is tightly associated with sleep alterations: as the disease progresses, sleep quality worsens. Therefore, the study of sleep patterns in interaction with other variables could constitute an early biomarker of AD. It is widely known that sleep alterations lead to an impaired cognitive functioning and performance, and recent studies evidence a positive feedback between amyloid beta (AB) accumulation and sleep. Consequently, sleep could constitute an interesting target for interventions aimed at altering the course of the disease. In the present study, we studied the relationship between self‐reported measures of sleep quality (i.e. number of hours of sleep) and the electrophysiological activity at resting‐state recorded using magnetoencephalography (MEG). Method The sample for this study was composed of healthy adults, with varying risks of developing AD (direct relatives vs non‐relatives, and APOE‐E4 carriers vs non‐carriers). All participants completed the Pittsburgh Sleep Quality Index, underwent a MEG scan, and were genotyped for their APOE carriage. Result Preliminary results show different patterns of brain activation in areas classically associated with the development of AD, in relatives and non‐relatives, in relation with the number of hours of sleep. Non‐relatives present a significant cluster that encompases areas such as the precuneus, where a positive correlation is found between the power in the low beta (12‐20Hz) frequency band and the number of hours of sleep. Relatives do not show clusters where relative power and hours of sleep correlate significantly. Conclusion Although further research is needed, a possible interpretation of these results could be the following: non‐relatives’ brain functioning in areas of the default‐mode network, typically associated with AD, are more affected by the number of hours of sleep than relatives, who may not benefit as much due to early damage interfering with the protective effect of sleep.
ISSN:1552-5260
1552-5279
DOI:10.1002/alz.067708