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Impact of different white matter hyperintensities patterns on cognition: A cross-sectional and longitudinal study

OBJECTIVES: White matter hyperintensities (WMH) are highly prevalent in older adults and considered to be a contributor to cognition impairment. However, the strategic WMH lesion distribution related to cognitive impairment is still debated. The aim of this study was to characterize the spatial patt...

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Autores principales: Wang, Junjun, Zhou, Ying, He, Yaode, Li, Qingqing, Zhang, Wenhua, Luo, Zhongyu, Xue, Rui, Lou, Min
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8897653/
https://www.ncbi.nlm.nih.gov/pubmed/35255417
http://dx.doi.org/10.1016/j.nicl.2022.102978
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author Wang, Junjun
Zhou, Ying
He, Yaode
Li, Qingqing
Zhang, Wenhua
Luo, Zhongyu
Xue, Rui
Lou, Min
author_facet Wang, Junjun
Zhou, Ying
He, Yaode
Li, Qingqing
Zhang, Wenhua
Luo, Zhongyu
Xue, Rui
Lou, Min
author_sort Wang, Junjun
collection PubMed
description OBJECTIVES: White matter hyperintensities (WMH) are highly prevalent in older adults and considered to be a contributor to cognition impairment. However, the strategic WMH lesion distribution related to cognitive impairment is still debated. The aim of this study was to characterize the spatial patterns of WMH associated with cognitive impairment and explore its risk factors. METHODS: We retrospectively analyzed patients who underwent T2 fluid attenuated inversion recovery (FLAIR) and mini-mental state examination (MMSE) in two centers. WHM was classified into four patterns based on T2 FLAIR as follows: (1) multiple subcortical spots (multi-spots); (2) peri-basal ganglia (peri-BG); (3) anterior subcortical patches (anterior SC patches); and (4) posterior subcortical patches (posterior SC patches). We cross-sectionally and longitudinally estimated associations between different WMH patterns and all-cause dementia and cognitive decline. Multivariable logistic regression analysis was followed to identify risk factors of WMH patterns related to cognitive impairment. RESULTS: A total of 442 patients with WMH were enrolled, with average age of 71.6 ± 11.3 years, and MMSE score of 24.1 ± 5.4. Among them, 281 (63.6%), 66 (14.9%), 163 (36.9%) and 197 (44.6%) patients presented multi-spots, peri-BG, anterior SC patches and posterior SC patches, respectively. Patients with anterior SC patches were more likely to have all-cause dementia in cross-sectional study (OR 2.002; 95% CI 1.098–3.649; p = 0.024), and have cognitive decline in longitudinal analysis (OR 3.029; 95% CI 1.270–7.223; p = 0.012). Four patterns of WMH referred to different cognitive domains, and anterior SC patches had the most significant and extensive impact on cognition after Bonferroni multiple comparison correction (all p < 0.0125). In addition, older age (OR 1.054; 95% CI 1.027–1.082; p < 0.001), hypertension (OR 1.956; 95% CI 1.145–3.341; p = 0.014), higher percentage of neutrophils (OR 1.046; 95% CI 1.014–1.080; p = 0.005) and lower concentration of hemoglobin (OR 0.983; 95% CI 0.967–1.000; p = 0.044) were risk factors for the presence of anterior SC patches. CONCLUSIONS: Different patterns of subcortical leukoaraiosis visually identified on MRI might have different impacts on cognitive impairment. Further studies should be undertaken to validate this simple visual classification of WMH in different population.
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spelling pubmed-88976532022-03-06 Impact of different white matter hyperintensities patterns on cognition: A cross-sectional and longitudinal study Wang, Junjun Zhou, Ying He, Yaode Li, Qingqing Zhang, Wenhua Luo, Zhongyu Xue, Rui Lou, Min Neuroimage Clin Regular Article OBJECTIVES: White matter hyperintensities (WMH) are highly prevalent in older adults and considered to be a contributor to cognition impairment. However, the strategic WMH lesion distribution related to cognitive impairment is still debated. The aim of this study was to characterize the spatial patterns of WMH associated with cognitive impairment and explore its risk factors. METHODS: We retrospectively analyzed patients who underwent T2 fluid attenuated inversion recovery (FLAIR) and mini-mental state examination (MMSE) in two centers. WHM was classified into four patterns based on T2 FLAIR as follows: (1) multiple subcortical spots (multi-spots); (2) peri-basal ganglia (peri-BG); (3) anterior subcortical patches (anterior SC patches); and (4) posterior subcortical patches (posterior SC patches). We cross-sectionally and longitudinally estimated associations between different WMH patterns and all-cause dementia and cognitive decline. Multivariable logistic regression analysis was followed to identify risk factors of WMH patterns related to cognitive impairment. RESULTS: A total of 442 patients with WMH were enrolled, with average age of 71.6 ± 11.3 years, and MMSE score of 24.1 ± 5.4. Among them, 281 (63.6%), 66 (14.9%), 163 (36.9%) and 197 (44.6%) patients presented multi-spots, peri-BG, anterior SC patches and posterior SC patches, respectively. Patients with anterior SC patches were more likely to have all-cause dementia in cross-sectional study (OR 2.002; 95% CI 1.098–3.649; p = 0.024), and have cognitive decline in longitudinal analysis (OR 3.029; 95% CI 1.270–7.223; p = 0.012). Four patterns of WMH referred to different cognitive domains, and anterior SC patches had the most significant and extensive impact on cognition after Bonferroni multiple comparison correction (all p < 0.0125). In addition, older age (OR 1.054; 95% CI 1.027–1.082; p < 0.001), hypertension (OR 1.956; 95% CI 1.145–3.341; p = 0.014), higher percentage of neutrophils (OR 1.046; 95% CI 1.014–1.080; p = 0.005) and lower concentration of hemoglobin (OR 0.983; 95% CI 0.967–1.000; p = 0.044) were risk factors for the presence of anterior SC patches. CONCLUSIONS: Different patterns of subcortical leukoaraiosis visually identified on MRI might have different impacts on cognitive impairment. Further studies should be undertaken to validate this simple visual classification of WMH in different population. Elsevier 2022-03-01 /pmc/articles/PMC8897653/ /pubmed/35255417 http://dx.doi.org/10.1016/j.nicl.2022.102978 Text en © 2022 Published by Elsevier Inc. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Wang, Junjun
Zhou, Ying
He, Yaode
Li, Qingqing
Zhang, Wenhua
Luo, Zhongyu
Xue, Rui
Lou, Min
Impact of different white matter hyperintensities patterns on cognition: A cross-sectional and longitudinal study
title Impact of different white matter hyperintensities patterns on cognition: A cross-sectional and longitudinal study
title_full Impact of different white matter hyperintensities patterns on cognition: A cross-sectional and longitudinal study
title_fullStr Impact of different white matter hyperintensities patterns on cognition: A cross-sectional and longitudinal study
title_full_unstemmed Impact of different white matter hyperintensities patterns on cognition: A cross-sectional and longitudinal study
title_short Impact of different white matter hyperintensities patterns on cognition: A cross-sectional and longitudinal study
title_sort impact of different white matter hyperintensities patterns on cognition: a cross-sectional and longitudinal study
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8897653/
https://www.ncbi.nlm.nih.gov/pubmed/35255417
http://dx.doi.org/10.1016/j.nicl.2022.102978
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