文章基本信息

标题：Brain network analysis reveals that amyloidopathy affects comorbid cognitive dysfunction in older adults with depression
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作者：Suji Lee ; Daegyeom Kim ; HyunChul Youn 等
期刊名称：Scientific Reports
电子版ISSN：2045-2322
出版年度：2021
卷号：11
期号：1
页码：4299
DOI：10.1038/s41598-021-83739-3
出版社：Springer Nature
摘要：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.
其他摘要：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.