Effects of white matter hyperintensities distribution and clustering on late-life cognitive impairment

Joan Jiménez-Balado,Teal Eich,Yaakov Stern,Christian Habeck,Fabian Corlier

doi:10.1038/s41598-022-06019-8

Joan Jiménez-Balado, Teal Eich + Show 3 more

Open Access

https://doi.org/10.1038/s41598-022-06019-8

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Abstract

White matter hyperintensities (WMH) are a key hallmark of subclinical cerebrovascular disease and are known to impair cognition. Here, we parcellated WMH using a novel system that segments WMH based on both lobar regions and distance from the ventricles, dividing the brain into a coordinate system composed of 36 distinct parcels (‘bullseye’ parcellation), and then investigated the effect of distribution on cognition using two different analytic approaches. Data from a well characterized sample of healthy older adults (58 to 84 years) who were free of dementia were included. Cognition was evaluated using 12 computerized tasks, factored onto 4 indices representing episodic memory, speed of processing, fluid reasoning and vocabulary. We first assessed the distribution of WMH according to the bullseye parcellation and tested the relationship between WMH parcellations and performance across the four cognitive domains. Then, we used a data-driven approach to derive latent variables within the WMH distribution, and tested the relation between these latent components and cognitive function. We observed that different, well-defined cognitive constructs mapped to specific WMH distributions. Speed of processing was correlated with WMH in the frontal lobe, while in the case of episodic memory, the relationship was more ubiquitous, involving most of the parcellations. A principal components analysis revealed that the 36 bullseye regions factored onto 3 latent components representing the natural aggrupation of WMH: fronto-parietal periventricular (WMH principally in the frontal and parietal lobes and basal ganglia, especially in the periventricular region); occipital; and temporal and juxtacortical WMH (involving WMH in the temporal lobe, and at the juxtacortical region from frontal and parietal lobes). We found that fronto-parietal periventricular and temporal & juxtacortical WMH were independently associated with speed of processing and episodic memory, respectively. These results indicate that different cognitive impairment phenotypes might present with specific WMH distributions. Additionally, our study encourages future research to consider WMH classifications using parcellations systems other than periventricular and deep localizations.

Highlights

White matter hyperintensities (WMH) are a key hallmark of subclinical cerebrovascular disease and are known to impair cognition
There is evidence that lobar anatomy might influence the effect of WMH on cognitive impairment: a previous study by Moura et al (2019) that assessed the relation between cognition and WMH according to the lobar region found that parietal WMH mediated the relation between age and performance on the speed of processing tasks[20]
Among the 108 participants (Additional file 1: see Supplementary Table 1) in which we could evaluate the presence of WMH, WMH were more abundant around the lateral ventricles for all lobar regions except the occipital lobe, in which most WMH were found in layer 4 (Fig. 2A,B)

Summary

Introduction

White matter hyperintensities (WMH) are a key hallmark of subclinical cerebrovascular disease and are known to impair cognition. We found that fronto-parietal periventricular and temporal & juxtacortical WMH were independently associated with speed of processing and episodic memory, respectively These results indicate that different cognitive impairment phenotypes might present with specific WMH distributions. Sudre and collaborators (2018) recently proposed a novel classification of WMH based on both lobar regions and distance from the ventricles, dividing the brain into a coordinate system composed of 36 distinct parcels, which they refer to as a ‘bullseye’ p arcellation[22] This parcellation of brain white matter was originally designed to train raters in the administration of WMH visual scales, which could be correlated with WMH volume in different brain regions[22]. This could generate new knowledge about the typology of WMH within the brain parenchyma and help to determine which patterns or distributions pose a greater risk of cognitive impairment

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