Brain White Matter Hyperintensities: Relative Importance of Vascular Risk Factors in Nondemented Elderly People

2007 ◽  
Vol 2007 ◽  
pp. 105-106
Author(s):  
B.C. Bowen
Radiology ◽  
2005 ◽  
Vol 237 (1) ◽  
pp. 251-257 ◽  
Author(s):  
Alison D. Murray ◽  
Roger T. Staff ◽  
Susan D. Shenkin ◽  
Ian J. Deary ◽  
John M. Starr ◽  
...  

Neurology ◽  
2014 ◽  
Vol 82 (15) ◽  
pp. 1331-1338 ◽  
Author(s):  
J. M. Wardlaw ◽  
M. Allerhand ◽  
F. N. Doubal ◽  
M. Valdes Hernandez ◽  
Z. Morris ◽  
...  

2013 ◽  
Vol 333 ◽  
pp. e254-e255
Author(s):  
A. Amintaeva ◽  
M. Kravchenko ◽  
O. Andreeva ◽  
Y. Varakin ◽  
G. Gornostaeva ◽  
...  

2018 ◽  
Vol 66 ◽  
pp. 40-48 ◽  
Author(s):  
Mara ten Kate ◽  
Carole H. Sudre ◽  
Anouk den Braber ◽  
Elles Konijnenberg ◽  
Michel G. Nivard ◽  
...  

2012 ◽  
Vol 33 (1) ◽  
pp. 29-34 ◽  
Author(s):  
Thomas Gattringer ◽  
Christian Enzinger ◽  
Stefan Ropele ◽  
Faton Gorani ◽  
Katja Elisabeth Petrovic ◽  
...  

Stroke ◽  
2020 ◽  
Vol 51 (6) ◽  
pp. 1682-1689 ◽  
Author(s):  
Jun Shen ◽  
Daniel J. Tozer ◽  
Hugh S. Markus ◽  
Jonathan Tay

Background and Purpose— Cerebrovascular disease contributes to age-related cognitive decline, but the mechanisms underlying this phenomenon remain incompletely understood. We hypothesized that vascular risk factors would lead to cognitive impairment through the disruption of brain white matter network efficiency. Methods— Participants were 19 346 neurologically healthy individuals from UK Biobank that underwent diffusion MRI and cognitive testing (mean age=62.6). Global efficiency, a measure of network integration, was calculated from white matter networks constructed using deterministic diffusion tractography. First, we determined whether demographics (age, sex, ethnicity, socioeconomic status, and education), vascular risk factors (hypertension, hypercholesterolemia, diabetes mellitus, smoking, body mass index), and white matter hyperintensities were related to global efficiency using multivariate linear regression. Next, we used structural equation modeling to model a multiple regression. The dependent variable was a latent cognition variable using all cognitive data, while independent variables were a latent factor including all vascular risk factors (vascular burden), demographic variables, white matter hyperintensities, and global efficiency. Finally, we used mediation analysis to determine whether global efficiency explained the relationship between vascular burden and cognition. Results— Hypertension and diabetes mellitus were consistently associated with reduced global efficiency even after controlling for white matter hyperintensities. Structural equation models revealed that vascular burden was associated with cognition ( P =0.023), but not after adding global efficiency to the model ( P =0.09), suggesting a mediation effect. Mediation analysis revealed a significant indirect effect of global efficiency on cognition through vascular burden ( P <0.001), suggesting a partial mediation effect. Conclusions— Vascular burden is associated with reduced global efficiency and cognitive impairment in the general population. Network efficiency partially mediates the relationship between vascular burden and cognition. This suggests that treating specific risk factors may prevent reductions in brain network efficiency and preserve cognitive functioning in the aging population.


2017 ◽  
Vol 13 (7S_Part_1) ◽  
pp. P53-P54
Author(s):  
Mara ten Kate ◽  
Carole H. Sudre ◽  
Anouk den Braber ◽  
Elles Konijnenberg ◽  
M. Jorge Cardoso ◽  
...  

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