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

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 c...

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Autores principales: Jiménez-Balado, Joan, Corlier, Fabian, Habeck, Christian, Stern, Yaakov, Eich, Teal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8816933/
https://www.ncbi.nlm.nih.gov/pubmed/35121804
http://dx.doi.org/10.1038/s41598-022-06019-8
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author Jiménez-Balado, Joan
Corlier, Fabian
Habeck, Christian
Stern, Yaakov
Eich, Teal
author_facet Jiménez-Balado, Joan
Corlier, Fabian
Habeck, Christian
Stern, Yaakov
Eich, Teal
author_sort Jiménez-Balado, Joan
collection PubMed
description 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.
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spelling pubmed-88169332022-02-07 Effects of white matter hyperintensities distribution and clustering on late-life cognitive impairment Jiménez-Balado, Joan Corlier, Fabian Habeck, Christian Stern, Yaakov Eich, Teal Sci Rep Article 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. Nature Publishing Group UK 2022-02-04 /pmc/articles/PMC8816933/ /pubmed/35121804 http://dx.doi.org/10.1038/s41598-022-06019-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Jiménez-Balado, Joan
Corlier, Fabian
Habeck, Christian
Stern, Yaakov
Eich, Teal
Effects of white matter hyperintensities distribution and clustering on late-life cognitive impairment
title Effects of white matter hyperintensities distribution and clustering on late-life cognitive impairment
title_full Effects of white matter hyperintensities distribution and clustering on late-life cognitive impairment
title_fullStr Effects of white matter hyperintensities distribution and clustering on late-life cognitive impairment
title_full_unstemmed Effects of white matter hyperintensities distribution and clustering on late-life cognitive impairment
title_short Effects of white matter hyperintensities distribution and clustering on late-life cognitive impairment
title_sort effects of white matter hyperintensities distribution and clustering on late-life cognitive impairment
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8816933/
https://www.ncbi.nlm.nih.gov/pubmed/35121804
http://dx.doi.org/10.1038/s41598-022-06019-8
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