001     1028620
005     20250204113908.0
024 7 _ |a 10.1093/sleep/zsae145
|2 doi
024 7 _ |a 0161-8105
|2 ISSN
024 7 _ |a 1550-9109
|2 ISSN
024 7 _ |a 10.34734/FZJ-2024-04693
|2 datacite_doi
024 7 _ |a 38934787
|2 pmid
024 7 _ |a WOS:001285659400001
|2 WOS
037 _ _ |a FZJ-2024-04693
082 _ _ |a 610
100 1 _ |a Elberse, Jorik D
|0 P:(DE-Juel1)190450
|b 0
|u fzj
245 _ _ |a The interplay between insomnia symptoms and Alzheimer’s Disease across three main brain networks
260 _ _ |a Oxford
|c 2024
|b Oxford Univ. Press
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1729492234_18424
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a Study ObjectivesInsomnia symptoms are prevalent along the trajectory of Alzheimer’s disease (AD), but the neurobiological underpinning of their interaction is poorly understood. Here, we assessed structural and functional brain measures within and between the default mode network (DMN), salience network (SN), and central executive network (CEN).MethodsWe selected 320 subjects from the ADNI database and divided by their diagnosis: cognitively normal (CN), Mild Cognitive Impairment (MCI), and AD, with and without self-reported insomnia symptoms. We measured the gray matter volume (GMV), structural covariance (SC), degrees centrality (DC), and functional connectivity (FC), testing the effect and interaction of insomnia symptoms and diagnosis on each index. Subsequently, we performed a within-group linear regression across each network and ROI. Finally, we correlated observed abnormalities with changes in cognitive and affective scores.ResultsInsomnia symptoms were associated with FC alterations across all groups. The AD group also demonstrated an interaction between insomnia and diagnosis. Within-group analyses revealed that in CN and MCI, insomnia symptoms were characterised by within-network hyperconnectivity, while in AD, within- and between-network hypoconnectivity was ubiquitous. SC and GMV alterations were non-significant in the presence of insomnia symptoms, and DC indices only showed network-level alterations in the CEN of AD individuals. Abnormal FC within and between DMN and CEN hubs was additionally associated with reduced cognitive function across all groups, and increased depressive symptoms in AD.ConclusionsWe conclude that patients with clinical AD present with a unique pattern of insomnia-related functional alterations, highlighting the profound interaction between both conditions.
536 _ _ |a 5252 - Brain Dysfunction and Plasticity (POF4-525)
|0 G:(DE-HGF)POF4-5252
|c POF4-525
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, Journals: juser.fz-juelich.de
700 1 _ |a Saberi, Amin
|0 P:(DE-Juel1)190448
|b 1
700 1 _ |a Ahmadi, Reihaneh
|0 P:(DE-Juel1)194451
|b 2
|u fzj
700 1 _ |a Changizi, Monir
|0 P:(DE-HGF)0
|b 3
700 1 _ |a Bi, Hanwen
|0 P:(DE-Juel1)190453
|b 4
|u fzj
700 1 _ |a Hoffstaedter, Felix
|0 P:(DE-Juel1)131684
|b 5
|u fzj
700 1 _ |a Mander, Bryce A
|0 P:(DE-HGF)0
|b 6
700 1 _ |a Eickhoff, Simon B
|0 P:(DE-Juel1)131678
|b 7
|u fzj
700 1 _ |a Tahmasian, Masoud
|0 P:(DE-Juel1)188400
|b 8
|e Corresponding author
773 _ _ |a 10.1093/sleep/zsae145
|g p. zsae145
|0 PERI:(DE-600)2056761-3
|n 10
|p zsae145
|t Sleep
|v 47
|y 2024
|x 0161-8105
856 4 _ |y OpenAccess
|u https://juser.fz-juelich.de/record/1028620/files/zsae145.pdf
856 4 _ |y OpenAccess
|x icon
|u https://juser.fz-juelich.de/record/1028620/files/zsae145.gif?subformat=icon
856 4 _ |y OpenAccess
|x icon-1440
|u https://juser.fz-juelich.de/record/1028620/files/zsae145.jpg?subformat=icon-1440
856 4 _ |y OpenAccess
|x icon-180
|u https://juser.fz-juelich.de/record/1028620/files/zsae145.jpg?subformat=icon-180
856 4 _ |y OpenAccess
|x icon-640
|u https://juser.fz-juelich.de/record/1028620/files/zsae145.jpg?subformat=icon-640
909 C O |o oai:juser.fz-juelich.de:1028620
|p openaire
|p open_access
|p VDB
|p driver
|p dnbdelivery
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 0
|6 P:(DE-Juel1)190450
910 1 _ |a HHU Düsseldorf
|0 I:(DE-HGF)0
|b 0
|6 P:(DE-Juel1)190450
910 1 _ |a MPI Leipzig
|0 I:(DE-HGF)0
|b 0
|6 P:(DE-Juel1)190450
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 1
|6 P:(DE-Juel1)190448
910 1 _ |a Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences , Leipzig
|0 I:(DE-HGF)0
|b 1
|6 P:(DE-Juel1)190448
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 2
|6 P:(DE-Juel1)194451
910 1 _ |a Julius-Maximilians University of Würzburg
|0 I:(DE-HGF)0
|b 2
|6 P:(DE-Juel1)194451
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 4
|6 P:(DE-Juel1)190453
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 5
|6 P:(DE-Juel1)131684
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 7
|6 P:(DE-Juel1)131678
910 1 _ |a HHU Düsseldorf
|0 I:(DE-HGF)0
|b 7
|6 P:(DE-Juel1)131678
910 1 _ |a Forschungszentrum Jülich
|0 I:(DE-588b)5008462-8
|k FZJ
|b 8
|6 P:(DE-Juel1)188400
913 1 _ |a DE-HGF
|b Key Technologies
|l Natural, Artificial and Cognitive Information Processing
|1 G:(DE-HGF)POF4-520
|0 G:(DE-HGF)POF4-525
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-500
|4 G:(DE-HGF)POF
|v Decoding Brain Organization and Dysfunction
|9 G:(DE-HGF)POF4-5252
|x 0
914 1 _ |y 2024
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2023-10-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2023-10-24
915 _ _ |a Creative Commons Attribution CC BY 4.0
|0 LIC:(DE-HGF)CCBY4
|2 HGFVOC
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2023-10-24
915 _ _ |a OpenAccess
|0 StatID:(DE-HGF)0510
|2 StatID
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2024-12-21
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2024-12-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2024-12-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2024-12-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2024-12-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
|d 2024-12-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
|d 2024-12-21
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2024-12-21
920 1 _ |0 I:(DE-Juel1)INM-7-20090406
|k INM-7
|l Gehirn & Verhalten
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a UNRESTRICTED
980 _ _ |a I:(DE-Juel1)INM-7-20090406
980 1 _ |a FullTexts


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21