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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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Autores principales: Veldsman, Michele, Kindalova, Petya, Husain, Masud, Kosmidis, Ioannis, Nichols, Thomas E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7511743/
https://www.ncbi.nlm.nih.gov/pubmed/32971464
http://dx.doi.org/10.1016/j.nicl.2020.102405
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author Veldsman, Michele
Kindalova, Petya
Husain, Masud
Kosmidis, Ioannis
Nichols, Thomas E.
author_facet Veldsman, Michele
Kindalova, Petya
Husain, Masud
Kosmidis, Ioannis
Nichols, Thomas E.
author_sort Veldsman, Michele
collection PubMed
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 [Formula: see text] 4/ [Formula: see text] 4 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 [Formula: see text] 4 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 [Formula: see text] 4 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.
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spelling pubmed-75117432020-09-30 Spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensities Veldsman, Michele Kindalova, Petya Husain, Masud Kosmidis, Ioannis Nichols, Thomas E. Neuroimage Clin Regular Article 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 [Formula: see text] 4/ [Formula: see text] 4 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 [Formula: see text] 4 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 [Formula: see text] 4 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. Elsevier 2020-09-01 /pmc/articles/PMC7511743/ /pubmed/32971464 http://dx.doi.org/10.1016/j.nicl.2020.102405 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Regular Article
Veldsman, Michele
Kindalova, Petya
Husain, Masud
Kosmidis, Ioannis
Nichols, Thomas E.
Spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensities
title 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_short 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
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7511743/
https://www.ncbi.nlm.nih.gov/pubmed/32971464
http://dx.doi.org/10.1016/j.nicl.2020.102405
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