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迟发性抑郁症患者认知缺陷背后的异常默认模式网络。

Aberrant Default Mode Network Underlying the Cognitive Deficits in the Patients With Late-Onset Depression.

作者信息

Liu Xiaoyun, Jiang Wenhao, Yuan Yonggui

机构信息

Department of Psychosomatics and Psychiatry, Zhongda Hospital, Institute of Psychosomatics, Medical School, Southeast University, Nanjing, China.

出版信息

Front Aging Neurosci. 2018 Oct 3;10:310. doi: 10.3389/fnagi.2018.00310. eCollection 2018.

Abstract

Late-onset depression (LOD) is regarded as a risk factor or a prodrome of Alzheimer's disease (AD). Moreover, LOD patients with cognitive deficits have the higher risk of subsequent AD. Thus, it is necessary to understand the neural underpinnings of cognitive deficits and its pathological implications in LOD. Consistent findings show that the default mode network (DMN) is an important and potentially useful brain network for the cognitive deficits in LOD patients. In recent years, genetics has been actively researched as a possible risk factor in the pathogenesis of LOD. So, in this review, we discuss the current research progress on the cognitive deficits and DMN in LOD through a combined view of brain network and genetics. We find that different structural and functional impairments of the DMN might be involved in the etiological mechanisms of different cognitive impairments in LOD patients.

摘要

迟发性抑郁症(LOD)被视为阿尔茨海默病(AD)的一个风险因素或前驱症状。此外,存在认知缺陷的LOD患者后续患AD的风险更高。因此,有必要了解LOD中认知缺陷的神经基础及其病理意义。一致的研究结果表明,默认模式网络(DMN)是LOD患者认知缺陷的一个重要且可能有用的脑网络。近年来,遗传学作为LOD发病机制中一个可能的风险因素受到了积极研究。所以,在本综述中,我们通过脑网络和遗传学的综合视角来讨论LOD中认知缺陷和DMN的当前研究进展。我们发现,DMN不同的结构和功能损伤可能参与了LOD患者不同认知障碍的病因机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/873c/6178980/51ca7425508c/fnagi-10-00310-g001.jpg

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