ArticleNeuroImage. Clinical2020
Spatial distribution and cognitive impact of cerebrovascular risk-related white matter hyperintensities.
Article in NeuroImage. Clinical, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 43 citations in OpenAlex.
- Functional connectivity changes in cerebral small vessel disease - a systematic review of the resting-state MRI literature.BMC medicine · 2021Pooled it
- Location patterns and longitudinal progression of white matter hyperintensities.medRxiv : the preprint server for health sciences · 2026Article
- The impact of glucose and metabolic disturbances on white matter hyperintensity volume in apparently healthy adults.Frontiers in endocrinology · 2026Article
- Characterizing white matter hyperintensities in myotonic dystrophy type 1 through IVIM derived metrics.Scientific reports · 2025Article
- White matter hyperintensity spatial patterns: Risk factors and clinical correlates.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
- From Big Data to the Clinic: Methodological and Statistical Enhancements to Implement the UK Biobank Imaging Framework in a Memory Clinic.Human brain mapping · 2025Article
- Identifying sources of bias when testing three available algorithms for quantifying white matter lesions: BIANCA, LPA and LGA.GeroScience · 2025Article
- Quantitative Analysis of White Matter Hyperintensities as a Predictor of 1-Year Risk for Ischemic Stroke Recurrence.Neurology and therapy · 2024Article
- Reducing False-Positives in CT Perfusion Infarct Core Segmentation Using Contralateral Local Normalization.AJNR. American journal of neuroradiology · 2024Article
- Progression of white matter hyperintensities is related to blood pressure increases and global cognitive decline - A registered report.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Bayesian Lesion Estimation with a Structured Spike-and-Slab Prior.Journal of the American Statistical Association · 2024Article
- White Matter Hyperintensity Trajectories in Patients With Progressive and Stable Mild Cognitive Impairment.Neurology · 2023Article
- Nutrients and Dementia: Prospective Study.Nutrients · 2023Article
- Cardiometabolic health across menopausal years is linked to white matter hyperintensities up to a decade later.Frontiers in global women's health · 2023Article
- Effects of Diastolic Blood Pressure on Brain Structures and Cognitive Functions in Middle and Old Ages: Longitudinal Analyses.Nutrients · 2022Article
- Article
- Associations between abdominal adipose tissue, reproductive span, and brain characteristics in post-menopausal women.NeuroImage. Clinical · 2022Article
- In vivo myelin imaging and tissue microstructure in white matter hyperintensities and perilesional white matter.Brain communications · 2022Article
- Differential expression of circular RNA in patients with white matter hyperintensity and cognitive impairment.Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2021Article
- Voxel-wise and spatial modelling of binary lesion masks: Comparison of methods with a realistic simulation framework.NeuroImage · 2021Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
objectivesWhite 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.
methodsWe 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.
resultsContrary 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.
conclusionWaist-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.
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