Home > Publications Database > Walking time and genetic predisposition for Alzheimer's disease: Results from the HELIAD study. > print

001     276127
005     20250209000703.0
024 7 _ |a 10.1080/13854046.2024.2344869
|2 doi
024 7 _ |a pmid:38741352
|2 pmid
024 7 _ |a 0920-1637
|2 ISSN
024 7 _ |a 1385-4046
|2 ISSN
024 7 _ |a 1744-4144
|2 ISSN
024 7 _ |a altmetric:163451593
|2 altmetric
037 _ _ |a DZNE-2025-00208
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Sampatakakis, Stefanos N
|b 0
245 _ _ |a Walking time and genetic predisposition for Alzheimer's disease: Results from the HELIAD study.
260 _ _ |a Abingdon
|c 2025
|b Routledge, Taylor Francis Group
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 1738661402_12998
|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 Objective: Our study aimed to explore whether physical condition might affect the association between genetic predisposition for Alzheimer's Disease (AD) and AD incidence. Methods: The sample of participants consisted of 561 community-dwelling adults over 64 years old, without baseline dementia (508 cognitively normal and 53 with mild cognitive impairment), deriving from the HELIAD, an ongoing longitudinal study with follow-up evaluations every 3 years. Physical condition was assessed at baseline through walking time (WT), while a Polygenic Risk Score for late onset AD (PRS-AD) was used to estimate genetic predisposition. The association between WT and PRS-AD with AD incidence was evaluated with Cox proportional hazard models adjusted for age, sex, education years, global cognition score and APOE ε-4 genotype. Then, the association between WT and AD incidence was investigated after stratifying participants by low and high PRS-AD. Finally, we examined the association between PRS-AD and AD incidence after stratifying participants by WT. Results: Both WT and PRS-AD were connected with increased AD incidence (p < 0.05), after adjustments. In stratified analyses, in the slow WT group participants with a greater genetic risk had a 2.5-fold higher risk of developing AD compared to participants with lower genetic risk (p = 0.047). No association was observed in the fast WT group or when participants were stratified based on PRS-AD. Conclusions: Genetic predisposition for AD is more closely related to AD incidence in the group of older adults with slow WT. Hence, physical condition might be a modifier in the relationship of genetic predisposition with AD incidence.
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 Alzheimer’s disease
|2 Other
650 _ 7 |a genetic predisposition
|2 Other
650 _ 7 |a physical condition
|2 Other
650 _ 7 |a polygenic risk
|2 Other
650 _ 7 |a walking time
|2 Other
650 _ 2 |a Humans
|2 MeSH
650 _ 2 |a Alzheimer Disease: genetics
|2 MeSH
650 _ 2 |a Alzheimer Disease: epidemiology
|2 MeSH
650 _ 2 |a Female
|2 MeSH
650 _ 2 |a Male
|2 MeSH
650 _ 2 |a Aged
|2 MeSH
650 _ 2 |a Genetic Predisposition to Disease
|2 MeSH
650 _ 2 |a Longitudinal Studies
|2 MeSH
650 _ 2 |a Incidence
|2 MeSH
650 _ 2 |a Cognitive Dysfunction: genetics
|2 MeSH
650 _ 2 |a Cognitive Dysfunction: physiopathology
|2 MeSH
650 _ 2 |a Aged, 80 and over
|2 MeSH
650 _ 2 |a Walking: physiology
|2 MeSH
700 1 _ |a Mourtzi, Niki
|b 1
700 1 _ |a Charisis, Sokratis
|b 2
700 1 _ |a Mamalaki, Eirini
|b 3
700 1 _ |a Ntanasi, Eva
|b 4
700 1 _ |a Hatzimanolis, Alex
|b 5
700 1 _ |a Ramirez, Alfredo
|0 P:(DE-2719)2812825
|b 6
|u dzne
700 1 _ |a Lambert, Jean-Charles
|b 7
700 1 _ |a Yannakoulia, Mary
|b 8
700 1 _ |a Kosmidis, Mary H
|b 9
700 1 _ |a Dardiotis, Efthimios
|b 10
700 1 _ |a Hadjigeorgiou, Georgios
|b 11
700 1 _ |a Megalou, Maria
|b 12
700 1 _ |a Sakka, Paraskevi
|b 13
700 1 _ |a Scarmeas, Nikolaos
|b 14
773 _ _ |a 10.1080/13854046.2024.2344869
|g Vol. 39, no. 1, p. 83 - 99
|0 PERI:(DE-600)1483047-4
|n 1
|p 83 - 99
|t The clinical neuropsychologist
|v 39
|y 2025
|x 0920-1637
909 C O |o oai:pub.dzne.de:276127
|p VDB
910 1 _ |a Deutsches Zentrum für Neurodegenerative Erkrankungen
|0 I:(DE-588)1065079516
|k DZNE
|b 6
|6 P:(DE-2719)2812825
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 2025
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
|d 2024-12-05
|w ger
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b CLIN NEUROPSYCHOL : 2022
|d 2024-12-05
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2024-12-05
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2024-12-05
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0600
|2 StatID
|b Ebsco Academic Search
|d 2024-12-05
915 _ _ |a Peer Review
|0 StatID:(DE-HGF)0030
|2 StatID
|b ASC
|d 2024-12-05
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2024-12-05
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0160
|2 StatID
|b Essential Science Indicators
|d 2024-12-05
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1180
|2 StatID
|b Current Contents - Social and Behavioral Sciences
|d 2024-12-05
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0130
|2 StatID
|b Social Sciences Citation Index
|d 2024-12-05
915 _ _ |a WoS
|0 StatID:(DE-HGF)0113
|2 StatID
|b Science Citation Index Expanded
|d 2024-12-05
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2024-12-05
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2024-12-05
920 1 _ |0 I:(DE-2719)1011101
|k Patient Studies (Bonn)
|l Patient Studies (Bonn)
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-2719)1011101
980 _ _ |a UNRESTRICTED

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21