Cardiovascular symptoms and longitudinal declines in processing speed differentially predict cerebral white matter lesions in older adults. (September 2018)
- Record Type:
- Journal Article
- Title:
- Cardiovascular symptoms and longitudinal declines in processing speed differentially predict cerebral white matter lesions in older adults. (September 2018)
- Main Title:
- Cardiovascular symptoms and longitudinal declines in processing speed differentially predict cerebral white matter lesions in older adults
- Authors:
- Aichele, Stephen
Rabbitt, Patrick
Ghisletta, Paolo - Abstract:
- Highlights: We used a data mining approach to compare 52 predictors of white matter lesion burden. Strongest predictors were age, cardiovascular symptoms, and processing speed decline. WML-cognition relations may be etiologically heterogeneous across cerebral regions. Abstract: It is well established that cerebral white matter lesions (WML), present in the majority of older adults, are associated with cardiovascular and cerebrovascular diseases and also with cognitive decline. However, much less is known about how WML are related to other important individual characteristics and about the generality vs. brain region-specificity of WML. In a longitudinal study of 112 community-dwelling adults (age 50–71 years at study entry), we used a machine learning approach to evaluate the relative strength of 52 variables in association with WML burden. Variables included socio-demographic, lifestyle, and health indices—as well as multiple cognitive abilities (modeled as latent constructs using factor analysis)—repeatedly measured at three- to six-year intervals. Greater chronological age, symptoms of cardiovascular disease, and processing speed declines were most strongly linked to elevated WML burden (accounting for ∼49% of variability in WML). Whereas frontal lobe WML burden was associated both with elevated cardiovascular symptoms and declines in processing speed, temporal lobe WML burden was only significantly associated with declines in processing speed. These latter outcomesHighlights: We used a data mining approach to compare 52 predictors of white matter lesion burden. Strongest predictors were age, cardiovascular symptoms, and processing speed decline. WML-cognition relations may be etiologically heterogeneous across cerebral regions. Abstract: It is well established that cerebral white matter lesions (WML), present in the majority of older adults, are associated with cardiovascular and cerebrovascular diseases and also with cognitive decline. However, much less is known about how WML are related to other important individual characteristics and about the generality vs. brain region-specificity of WML. In a longitudinal study of 112 community-dwelling adults (age 50–71 years at study entry), we used a machine learning approach to evaluate the relative strength of 52 variables in association with WML burden. Variables included socio-demographic, lifestyle, and health indices—as well as multiple cognitive abilities (modeled as latent constructs using factor analysis)—repeatedly measured at three- to six-year intervals. Greater chronological age, symptoms of cardiovascular disease, and processing speed declines were most strongly linked to elevated WML burden (accounting for ∼49% of variability in WML). Whereas frontal lobe WML burden was associated both with elevated cardiovascular symptoms and declines in processing speed, temporal lobe WML burden was only significantly associated with declines in processing speed. These latter outcomes suggest that age-related WML-cognition associations may be etiologically heterogeneous across fronto-temporal cerebral regions. … (more)
- Is Part Of:
- Archives of gerontology and geriatrics. Volume 78(2018)
- Journal:
- Archives of gerontology and geriatrics
- Issue:
- Volume 78(2018)
- Issue Display:
- Volume 78, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 78
- Issue:
- 2018
- Issue Sort Value:
- 2018-0078-2018-0000
- Page Start:
- 139
- Page End:
- 149
- Publication Date:
- 2018-09
- Subjects:
- White matter lesions -- Cognitive decline -- Aging -- Processing speed -- Random forest analysis -- Machine learning
Aging -- Periodicals
Geriatrics -- Periodicals
Gerontology -- Periodicals
Electronic journals
305.26 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01674943 ↗
http://www.elsevier.com/wps/find/journaldescription.cws%5Fhome/506044/description#description ↗
http://www.clinicalkey.com/dura/browse/journalIssue/01674943 ↗
http://www.clinicalkey.com.au/dura/browse/journalIssue/01674943 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.archger.2018.06.010 ↗
- Languages:
- English
- ISSNs:
- 0167-4943
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 1634.401000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 17027.xml