Brain network analysis reveals that amyloidopathy affects comorbid cognitive dysfunction in older adults with depression

Abstract Late-life depression (LLD) may increase the risk of Alzheimer’s dementia (AD). While amyloidopathy accelerates AD progression, its role in such patients has not yet been elucidated. We hypothesized that cerebral amyloidopathy distinctly affects the alteration of brain network topology and m...

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Autores principales:	Suji Lee, Daegyeom Kim, HyunChul Youn, Won Seok William Hyung, Sangil Suh, Marcus Kaiser, Cheol E. Han, Hyun-Ghang Jeong
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/1a90e4b6624c4abca9e40e25f0382a83
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spelling	oai:doaj.org-article:1a90e4b6624c4abca9e40e25f0382a832021-12-02T14:28:22ZBrain network analysis reveals that amyloidopathy affects comorbid cognitive dysfunction in older adults with depression10.1038/s41598-021-83739-32045-2322https://doaj.org/article/1a90e4b6624c4abca9e40e25f0382a832021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-83739-3https://doaj.org/toc/2045-2322Abstract Late-life depression (LLD) may increase the risk of Alzheimer’s dementia (AD). While amyloidopathy accelerates AD progression, its role in such patients has not yet been elucidated. We hypothesized that cerebral amyloidopathy distinctly affects the alteration of brain network topology and may be associated with distinct cognitive symptoms. We recruited 26 and 27 depressed mild cognitive impairment (MCI) patients with (LLD-MCI-A(+)) and without amyloid accumulation (LLD-MCI-A(−)), respectively, and 21 normal controls. We extracted structural brain networks using their diffusion-weighted images. We aimed to compare the distinct network deterioration in LLD-MCI with and without amyloid accumulation and the relationship with their distinct cognitive decline. Thus, we performed a group comparison of the network topological measures and investigated any correlations with neurocognitive testing scores. Topological features of brain networks were different according to the presence of amyloid accumulation. Disrupted network connectivity was highly associated with impaired recall and recognition in LLD-MCI-A(+) patients. Inattention and dysexecutive function were more influenced by the altered networks involved in fronto-limbic circuitry dysfunction in LLD-MCI-A(−) patients. Our results show that alterations in brain network topology may reflect different cognitive dysfunction depending on amyloid accumulation in depressed older adults with MCI.Suji LeeDaegyeom KimHyunChul YounWon Seok William HyungSangil SuhMarcus KaiserCheol E. HanHyun-Ghang JeongNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Suji Lee Daegyeom Kim HyunChul Youn Won Seok William Hyung Sangil Suh Marcus Kaiser Cheol E. Han Hyun-Ghang Jeong Brain network analysis reveals that amyloidopathy affects comorbid cognitive dysfunction in older adults with depression
description	Abstract Late-life depression (LLD) may increase the risk of Alzheimer’s dementia (AD). While amyloidopathy accelerates AD progression, its role in such patients has not yet been elucidated. We hypothesized that cerebral amyloidopathy distinctly affects the alteration of brain network topology and may be associated with distinct cognitive symptoms. We recruited 26 and 27 depressed mild cognitive impairment (MCI) patients with (LLD-MCI-A(+)) and without amyloid accumulation (LLD-MCI-A(−)), respectively, and 21 normal controls. We extracted structural brain networks using their diffusion-weighted images. We aimed to compare the distinct network deterioration in LLD-MCI with and without amyloid accumulation and the relationship with their distinct cognitive decline. Thus, we performed a group comparison of the network topological measures and investigated any correlations with neurocognitive testing scores. Topological features of brain networks were different according to the presence of amyloid accumulation. Disrupted network connectivity was highly associated with impaired recall and recognition in LLD-MCI-A(+) patients. Inattention and dysexecutive function were more influenced by the altered networks involved in fronto-limbic circuitry dysfunction in LLD-MCI-A(−) patients. Our results show that alterations in brain network topology may reflect different cognitive dysfunction depending on amyloid accumulation in depressed older adults with MCI.
format	article
author	Suji Lee Daegyeom Kim HyunChul Youn Won Seok William Hyung Sangil Suh Marcus Kaiser Cheol E. Han Hyun-Ghang Jeong
author_facet	Suji Lee Daegyeom Kim HyunChul Youn Won Seok William Hyung Sangil Suh Marcus Kaiser Cheol E. Han Hyun-Ghang Jeong
author_sort	Suji Lee
title	Brain network analysis reveals that amyloidopathy affects comorbid cognitive dysfunction in older adults with depression
title_short	Brain network analysis reveals that amyloidopathy affects comorbid cognitive dysfunction in older adults with depression
title_full	Brain network analysis reveals that amyloidopathy affects comorbid cognitive dysfunction in older adults with depression
title_fullStr	Brain network analysis reveals that amyloidopathy affects comorbid cognitive dysfunction in older adults with depression
title_full_unstemmed	Brain network analysis reveals that amyloidopathy affects comorbid cognitive dysfunction in older adults with depression
title_sort	brain network analysis reveals that amyloidopathy affects comorbid cognitive dysfunction in older adults with depression
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/1a90e4b6624c4abca9e40e25f0382a83
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Brain network analysis reveals that amyloidopathy affects comorbid cognitive dysfunction in older adults with depression

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