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Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors

The clinical presentation of Alzheimer's disease (AD) is not unitary as heterogeneity exists in the disease's clinical and anatomical characteristics. MRI studies have revealed that heterogeneous gray matter atrophy patterns are associated with specific traits of cognitive decline. Althoug...

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Autores principales: Sui, Xiuchao, Rajapakse, Jagath C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6226553/
https://www.ncbi.nlm.nih.gov/pubmed/30412925
http://dx.doi.org/10.1016/j.nicl.2018.10.026
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author Sui, Xiuchao
Rajapakse, Jagath C.
author_facet Sui, Xiuchao
Rajapakse, Jagath C.
author_sort Sui, Xiuchao
collection PubMed
description The clinical presentation of Alzheimer's disease (AD) is not unitary as heterogeneity exists in the disease's clinical and anatomical characteristics. MRI studies have revealed that heterogeneous gray matter atrophy patterns are associated with specific traits of cognitive decline. Although white matter (WM) impairment also contributes to AD pathology, its heterogeneity remains unclear. The Latent Dirichlet Allocation (LDA) method is a suitable framework to study heterogeneity and allows to identify latent impairment factors of AD instead of simply mapping an overall disease effect. By exploring whole brain WM skeleton images by using LDA, three latent factors were revealed in AD: a temporal-frontal impairment factor (temporal and frontal lobes, especially hippocampus and para-hippocampus), a parietal factor (parietal lobe, especially precuneus), and a long fibre bundle factor (corpus callosum and superior longitudinal fasciculus). As revealed by longitudinal analysis, the latent factors have distinct impact on cognitive decline: for executive function (EF), the temporal-frontal factor was more strongly associated with baseline EF compared with the parietal factor, while the long-fibre bundle factor was most associated with decline rate of EF; for memory, the three factors showed almost equal effect on the baseline memory and decline rate. For each participant, LDA estimates his/her composition profile of latent impairment factors, which indicates disease subtype. We also found that the APOE genotype affects the AD subtype. Specifically, APOE ε4 was more associated with the long fibre bundle factor and APOE ε2 was more associated with temporal-frontal factor. By investigating heterogeneity and subtypes of AD through white matter impairment factors, our study could facilitate precision medicine.
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spelling pubmed-62265532018-11-16 Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors Sui, Xiuchao Rajapakse, Jagath C. Neuroimage Clin Regular Article The clinical presentation of Alzheimer's disease (AD) is not unitary as heterogeneity exists in the disease's clinical and anatomical characteristics. MRI studies have revealed that heterogeneous gray matter atrophy patterns are associated with specific traits of cognitive decline. Although white matter (WM) impairment also contributes to AD pathology, its heterogeneity remains unclear. The Latent Dirichlet Allocation (LDA) method is a suitable framework to study heterogeneity and allows to identify latent impairment factors of AD instead of simply mapping an overall disease effect. By exploring whole brain WM skeleton images by using LDA, three latent factors were revealed in AD: a temporal-frontal impairment factor (temporal and frontal lobes, especially hippocampus and para-hippocampus), a parietal factor (parietal lobe, especially precuneus), and a long fibre bundle factor (corpus callosum and superior longitudinal fasciculus). As revealed by longitudinal analysis, the latent factors have distinct impact on cognitive decline: for executive function (EF), the temporal-frontal factor was more strongly associated with baseline EF compared with the parietal factor, while the long-fibre bundle factor was most associated with decline rate of EF; for memory, the three factors showed almost equal effect on the baseline memory and decline rate. For each participant, LDA estimates his/her composition profile of latent impairment factors, which indicates disease subtype. We also found that the APOE genotype affects the AD subtype. Specifically, APOE ε4 was more associated with the long fibre bundle factor and APOE ε2 was more associated with temporal-frontal factor. By investigating heterogeneity and subtypes of AD through white matter impairment factors, our study could facilitate precision medicine. Elsevier 2018-10-29 /pmc/articles/PMC6226553/ /pubmed/30412925 http://dx.doi.org/10.1016/j.nicl.2018.10.026 Text en © 2018 The Authors http://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
Sui, Xiuchao
Rajapakse, Jagath C.
Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors
title Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors
title_full Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors
title_fullStr Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors
title_full_unstemmed Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors
title_short Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors
title_sort profiling heterogeneity of alzheimer's disease using white-matter impairment factors
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6226553/
https://www.ncbi.nlm.nih.gov/pubmed/30412925
http://dx.doi.org/10.1016/j.nicl.2018.10.026
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