001     164983
005     20230915090603.0
024 7 _ |a 10.1212/WNL.0000000000200951
|2 doi
024 7 _ |a pmid:35853750
|2 pmid
024 7 _ |a 0028-3878
|2 ISSN
024 7 _ |a 1526-632X
|2 ISSN
024 7 _ |a altmetric:132842683
|2 altmetric
037 _ _ |a DZNE-2022-01387
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Demnitz-King, Harriet
|0 0000-0002-7421-7101
|b 0
245 _ _ |a Association Between Self-Reflection, Cognition, and Brain Health in Cognitively Unimpaired Older Adults.
260 _ _ |a [S.l.]
|c 2022
|b Ovid
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 1667899154_7090
|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 Self-reflection (the active evaluation of ones thoughts, feelings and behaviours) can confer protection against adverse health outcomes. Its impact on markers sensitive to Alzheimer's disease (AD), however, is unknown. The primary objective of this cross-sectional study was to examine the association between self-reflection and AD-sensitive markers.This study utilised baseline data from cognitively unimpaired older adults enrolled in the Age-Well clinical trial and older adults with subjective cognitive decline from the SCD-Well clinical trial. In both cohorts, self-reflection was measured via the reflective pondering subscale of the Rumination Response Scale, global cognition assessed via the Preclinical Alzheimer's Cognitive Composite 5, and a modified late-life Lifestyle-for-Brain-Health (LIBRA) index computed to assess health and lifestyle factors. In Age-Well, glucose metabolism and amyloid deposition were quantified in AD-sensitive grey matter regions via FDG- and AV45-PET scans, respectively. Associations between self-reflection and AD-sensitive markers (global cognition, glucose metabolism, and amyloid deposition) were assessed via unadjusted and adjusted regressions. Further, we explored whether associations were independent of health and lifestyle factors. To control for multiple comparisons in Age-Well, false discovery rate corrected p-values (p FDR) are reported.A total of 134 (mean age 69.3 ± 3.8 years, 61.9% female) Age-Well and 125 (mean age 72.6 ± 6.9 years, 65.6% female) SCD-Well participants were included. Across unadjusted and adjusted analyses self-reflection was positively associated with global cognition in both cohorts (Age-Well: adjusted-β = 0.22, 95% confidence interval [CI] 0.05-0.40, p FDR = 0.041; SCD-Well: adjusted-β = 0.18, 95% CI 0.03-0.33, p = 0.023) and with glucose metabolism in Age-Well after adjustment for all covariates (adjusted-β = 0.29, 95% CI 0.03-0.55, p FDR = 0.041). Associations remained following additional adjustment for LIBRA but did not survive FDR correction. Self-reflection was not associated with amyloid deposition (adjusted-β = 0.13, 95% CI -0.07-0.34, p FDR = 0.189).Self-reflection was associated with better global cognition in two independent cohorts and with higher glucose metabolism after adjustment for covariates. There was weak evidence that relationships were independent from health and lifestyle behaviours. Longitudinal and experimental studies are warranted to elucidate whether self-reflection helps preserve cognition and glucose metabolism, or whether reduced capacity to self-reflect is a harbinger of cognitive decline and glucose hypometabolism.Age-Well: NCT02977819; SCD-Well: NCT03005652.
536 _ _ |a 353 - Clinical and Health Care Research (POF4-353)
|0 G:(DE-HGF)POF4-353
|c POF4-353
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: pub.dzne.de
650 _ 7 |a Amyloid beta-Peptides
|2 NLM Chemicals
650 _ 7 |a Biomarkers
|2 NLM Chemicals
650 _ 7 |a Glucose
|0 IY9XDZ35W2
|2 NLM Chemicals
650 _ 2 |a Aged
|2 MeSH
650 _ 2 |a Alzheimer Disease: metabolism
|2 MeSH
650 _ 2 |a Amyloid beta-Peptides: metabolism
|2 MeSH
650 _ 2 |a Biomarkers: metabolism
|2 MeSH
650 _ 2 |a Brain: diagnostic imaging
|2 MeSH
650 _ 2 |a Brain: metabolism
|2 MeSH
650 _ 2 |a Cognition: physiology
|2 MeSH
650 _ 2 |a Cognitive Dysfunction: diagnostic imaging
|2 MeSH
650 _ 2 |a Cognitive Dysfunction: metabolism
|2 MeSH
650 _ 2 |a Cross-Sectional Studies
|2 MeSH
650 _ 2 |a Female
|2 MeSH
650 _ 2 |a Glucose: metabolism
|2 MeSH
650 _ 2 |a Humans
|2 MeSH
650 _ 2 |a Magnetic Resonance Imaging
|2 MeSH
650 _ 2 |a Male
|2 MeSH
650 _ 2 |a Positron-Emission Tomography
|2 MeSH
700 1 _ |a Gonneaud, Julie
|0 0000-0003-0566-5581
|b 1
700 1 _ |a Klimecki, Olga M
|0 0000-0003-0757-7761
|b 2
700 1 _ |a Chocat, Anne
|b 3
700 1 _ |a Collette, Fabienne
|0 0000-0001-9288-9756
|b 4
700 1 _ |a Dautricourt, Sophie
|0 0000-0001-8848-8300
|b 5
700 1 _ |a Jessen, Frank
|0 P:(DE-2719)2000032
|b 6
|u dzne
700 1 _ |a Krolak-Salmon, Pierre
|0 0000-0001-7815-7022
|b 7
700 1 _ |a Lutz, Antoine
|0 0000-0002-0258-3233
|b 8
700 1 _ |a Morse, Rachel M
|0 0000-0001-6367-756X
|b 9
700 1 _ |a Molinuevo, José Luis
|b 10
700 1 _ |a Poisnel, Géraldine
|0 0000-0001-7943-1281
|b 11
700 1 _ |a Touron, Edelweiss
|0 0000-0001-7906-934X
|b 12
700 1 _ |a Wirth, Miranka
|0 P:(DE-2719)2814122
|b 13
|u dzne
700 1 _ |a Walker, Zuzana
|0 0000-0001-7346-8200
|b 14
700 1 _ |a Chételat, Gaël
|0 0000-0002-4889-7932
|b 15
700 1 _ |a Marchant, Natalie L
|b 16
700 1 _ |a Group, Medit-Ageing Research
|b 17
|e Collaboration Author
773 _ _ |a 10.1212/WNL.0000000000200951
|g p. 10.1212/WNL.0000000000200951 -
|0 PERI:(DE-600)1491874-2
|n 13
|p e1422 - e1431
|t Neurology
|v 99
|y 2022
|x 0028-3878
909 C O |p VDB
|o oai:pub.dzne.de:164983
910 1 _ |a External Institute
|0 I:(DE-HGF)0
|k Extern
|b 6
|6 P:(DE-2719)2000032
910 1 _ |a Deutsches Zentrum für Neurodegenerative Erkrankungen
|0 I:(DE-588)1065079516
|k DZNE
|b 13
|6 P:(DE-2719)2814122
913 1 _ |a DE-HGF
|b Gesundheit
|l Neurodegenerative Diseases
|1 G:(DE-HGF)POF4-350
|0 G:(DE-HGF)POF4-353
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Clinical and Health Care Research
|x 0
914 1 _ |y 2022
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2021-01-27
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2021-01-27
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2021-01-27
915 _ _ |a Allianz-Lizenz
|0 StatID:(DE-HGF)0410
|2 StatID
|d 2022-11-12
|w ger
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2022-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2022-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2022-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2022-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1110
|2 StatID
|b Current Contents - Clinical Medicine
|d 2022-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
|d 2022-11-12
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b NEUROLOGY : 2021
|d 2022-11-12
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2022-11-12
915 _ _ |a IF >= 10
|0 StatID:(DE-HGF)9910
|2 StatID
|b NEUROLOGY : 2021
|d 2022-11-12
920 1 _ |0 I:(DE-2719)1710011
|k AG Wirth
|l Brain aging: Biomarkers, lifestyle factors and prevention of dementia
|x 0
920 1 _ |0 I:(DE-2719)1710008
|k AG Donix
|l Clinical planning and intersite group
|x 1
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-2719)1710011
980 _ _ |a I:(DE-2719)1710008
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21