Associations of objective and subjective sleep quality with MRI markers of brain ageing and Alzheimer's disease. (31st December 2021)

• Record Type: Journal Article
• Authors: Weihs, Antoine; Frenzel, Stefan; Katharina, Wittfeld; Obst, Anne; Stubbe, Beate; Berger, Klaus; Fietze, Ingo; Penzel, Thomas; Bülow, Robin; Voelzke, Henry; Grabe, Hans J.
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 5
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-31
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.051688
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Sleep is increasingly recognised as a major risk‐factor for cognitive ageing and neurodegenerative disorders such as late‐onset Alzheimer's Disease (LOAD). Poor sleep quality has been linked to impaired cerebral clearance of amyloid‐beta, neurofibrillary tangles and reduced cognitive function. Recent studies have also highlighted a relationship between disturbed sleep and age‐related changes in brain structure. Method: We used ordinary least‐squared regression adjusted for age, gender, BMI, intracranial volume and APOE4‐status to investigate the associations of MRI‐based markers of brain ageing and LOAD‐related brain atrophy patterns (Frenzel et al. 2019; Janowitz et al. 2016 and Weihs et al. 2020) as well as cognitive performance in terms of the immediate and delayed wordlist recollection from the Nuremberg‐Age‐Inventory (NAI) with questionnaire and polysomnography (PSG) based measures of sleep quality in 717 subjects from the large‐scale population‐based Study of Health in Pomerania (SHIP‐Trend). We analysed the percentage of total sleep time (TST) spent in slow‐wave and rapid eye movement (REM) sleep, sleep duration, sleep efficiency and sleep latency as objective sleep quality measures and the Pittsburgh sleep quality index (PSQI) as subjective sleep quality measure. Result: We have identified inverse associations of the percentage of TST spent in slow‐wave and REM sleep with brain atrophy related to ageing and LOAD, which was mainly driven by slow‐wave sleep, with both percentages of TST and duration showing significant inverse associations. Furthermore, there was a non‐linear u‐shaped association between sleep duration and age‐related atrophy patterns. Similar associations were found for the NAI sum score and the NAI delayed recollection sub‐score, but neither were significant after correcting for multiple testing. No associations with the PSQI score were found. Conclusion: We identified associations between PSG based sleep quality markers, but not subjective sleep quality, and brain atrophy related to ageing and LOAD. With no treatment being yet available, improving objective sleep quality, especially slow‐wave sleep, could prove a viable target to slow‐down the process of cognitive decline and reduce the risk of neurodegenerative disorders such as LOAD.