Spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensities
Objectives: White matter hyperintensities (WMHs) are considered macroscale markers of cerebrovascular burden and are associated with increased risk of vascular cognitive impairment and dementia. However, the spatial location of WMHs has typically been considered in broad categories of periventricula...
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doaj-bce8ec73c23149a495fb587be13ebd6f2020-12-19T05:06:05ZengElsevierNeuroImage: Clinical2213-15822020-01-0128102405Spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensitiesMichele Veldsman0Petya Kindalova1Masud Husain2Ioannis Kosmidis3Thomas E. Nichols4Wellcome Centre for Integrative Neuroscience, Department of Experimental Psychology, University of Oxford, UK; Corresponding author.Department of Statistics, University of Oxford, UKWellcome Centre for Integrative Neuroscience, Department of Experimental Psychology, University of Oxford, UKDepartment of Statistics, University of Warwick, UK; The Alan Turing Institute, London, UKDepartment of Statistics, University of Warwick, UK; Big Data Institute, Nuffield Department of Population Health, University of Oxford, UKObjectives: White matter hyperintensities (WMHs) are considered macroscale markers of cerebrovascular burden and are associated with increased risk of vascular cognitive impairment and dementia. However, the spatial location of WMHs has typically been considered in broad categories of periventricular versus deep white matter. The spatial distribution of WHMs associated with individual cerebrovascular risk factors (CVR), controlling for frequently comorbid risk factors, has not been systematically investigated at the population level in a healthy ageing cohort. Furthermore, there is an inconsistent relationship between total white matter hyperintensity load and cognition, which may be due to the confounding of several simultaneous risk factors in models based on smaller cohorts. Methods: We examined trends in individual CVR factors on total WMH burden in 13,680 individuals (aged 45–80) using data from the UK Biobank. We estimated the spatial distribution of white matter hyperintensities associated with each risk factor and their contribution to explaining total WMH load using voxel-wise probit regression and univariate linear regression. Finally, we explored the impact of CVR-related WMHs on speed of processing using regression and mediation analysis. Results: Contrary to the assumed dominance of hypertension as the biggest predictor of WMH burden, we show associations with a number of risk factors including diabetes, heavy smoking, APOE ε4/ε4 status and high waist-to-hip ratio of similar, or greater magnitude to hypertension. The spatial distribution of WMHs varied considerably with individual cerebrovascular risk factors. There were independent effects of visceral adiposity, as measured by waist-to-hip ratio, and carriage of the APOE ε4 allele in terms of the unique spatial distribution of CVR-related WMHs. Importantly, the relationship between total WMH load and speed of processing was mediated by waist-to-hip ratio suggesting cognitive consequences to WMHs associated with excessive visceral fat deposition. Conclusion: Waist-to-hip ratio, diabetes, heavy smoking, hypercholesterolemia and homozygous APOE ε4 status are important risk factors, beyond hypertension, associated with WMH total burden and warrant careful control across ageing. The spatial distribution associated with different risk factors may provide important clues as to the pathogenesis and cognitive consequences of WMHs. High waist-to-hip ratio is a key risk factor associated with slowing in speed of processing. With global obesity levels rising, focused management of visceral adiposity may present a useful strategy for the mitigation of cognitive decline in ageing.http://www.sciencedirect.com/science/article/pii/S2213158220302424White matter hyperintensitiesStructural MRIAPOEVisceral adiposityCardiovascular risk |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Michele Veldsman Petya Kindalova Masud Husain Ioannis Kosmidis Thomas E. Nichols |
spellingShingle |
Michele Veldsman Petya Kindalova Masud Husain Ioannis Kosmidis Thomas E. Nichols Spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensities NeuroImage: Clinical White matter hyperintensities Structural MRI APOE Visceral adiposity Cardiovascular risk |
author_facet |
Michele Veldsman Petya Kindalova Masud Husain Ioannis Kosmidis Thomas E. Nichols |
author_sort |
Michele Veldsman |
title |
Spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensities |
title_short |
Spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensities |
title_full |
Spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensities |
title_fullStr |
Spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensities |
title_full_unstemmed |
Spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensities |
title_sort |
spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensities |
publisher |
Elsevier |
series |
NeuroImage: Clinical |
issn |
2213-1582 |
publishDate |
2020-01-01 |
description |
Objectives: White matter hyperintensities (WMHs) are considered macroscale markers of cerebrovascular burden and are associated with increased risk of vascular cognitive impairment and dementia. However, the spatial location of WMHs has typically been considered in broad categories of periventricular versus deep white matter. The spatial distribution of WHMs associated with individual cerebrovascular risk factors (CVR), controlling for frequently comorbid risk factors, has not been systematically investigated at the population level in a healthy ageing cohort. Furthermore, there is an inconsistent relationship between total white matter hyperintensity load and cognition, which may be due to the confounding of several simultaneous risk factors in models based on smaller cohorts. Methods: We examined trends in individual CVR factors on total WMH burden in 13,680 individuals (aged 45–80) using data from the UK Biobank. We estimated the spatial distribution of white matter hyperintensities associated with each risk factor and their contribution to explaining total WMH load using voxel-wise probit regression and univariate linear regression. Finally, we explored the impact of CVR-related WMHs on speed of processing using regression and mediation analysis. Results: Contrary to the assumed dominance of hypertension as the biggest predictor of WMH burden, we show associations with a number of risk factors including diabetes, heavy smoking, APOE ε4/ε4 status and high waist-to-hip ratio of similar, or greater magnitude to hypertension. The spatial distribution of WMHs varied considerably with individual cerebrovascular risk factors. There were independent effects of visceral adiposity, as measured by waist-to-hip ratio, and carriage of the APOE ε4 allele in terms of the unique spatial distribution of CVR-related WMHs. Importantly, the relationship between total WMH load and speed of processing was mediated by waist-to-hip ratio suggesting cognitive consequences to WMHs associated with excessive visceral fat deposition. Conclusion: Waist-to-hip ratio, diabetes, heavy smoking, hypercholesterolemia and homozygous APOE ε4 status are important risk factors, beyond hypertension, associated with WMH total burden and warrant careful control across ageing. The spatial distribution associated with different risk factors may provide important clues as to the pathogenesis and cognitive consequences of WMHs. High waist-to-hip ratio is a key risk factor associated with slowing in speed of processing. With global obesity levels rising, focused management of visceral adiposity may present a useful strategy for the mitigation of cognitive decline in ageing. |
topic |
White matter hyperintensities Structural MRI APOE Visceral adiposity Cardiovascular risk |
url |
http://www.sciencedirect.com/science/article/pii/S2213158220302424 |
work_keys_str_mv |
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