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网络与帕金森病患者的抑郁相关:一项静息态成像研究。

Networks Are Associated With Depression in Patients With Parkinson's Disease: A Resting-State Imaging Study.

作者信息

Liao Haiyan, Cai Sainan, Shen Qin, Fan Jie, Wang Tianyu, Zi Yuheng, Mao Zhenni, Situ Weijun, Liu Jun, Zou Ting, Yi Jinyao, Zhu Xiongzhao, Tan Changlian

机构信息

Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, China.

Medical Psychological Center, The Second Xiangya Hospital, Central South University, Changsha, China.

出版信息

Front Neurosci. 2021 Feb 9;14:573538. doi: 10.3389/fnins.2020.573538. eCollection 2020.

Abstract

BACKGROUND

Disturbance of networks was recently proposed to be associated with the occurrence of depression in Parkinson's disease (PD). However, the neurobiological mechanism of depression underlying PD remains unclear.

OBJECTIVE

This study was conducted to investigate whether intra-network and inter-network brain connectivity is differently changed in PD patients with and without depression (PDD and PDND patients, respectively).

METHODS

Forty-one PDD patients, 64 PDND patients, and 55 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (fMRI). The default mode network (DMN), executive control network (ECN), salience network (SN), precuneus network (PCUN), and sensorimotor network (SMN) were extracted using independent component analysis (ICA), and then the functional connectivity (FC) values within and between these networks were measured.

RESULTS

PDD patients exhibited abnormal FC values within the DMN, ECN, SN, PCUN, and SMN. In addition, PDD patients demonstrated decreased connectivity between anterior SN (aSN) and bilateral ECN, between posterior SN (pSN) and dorsal DMN (dDMN), and between PCUN and dDMN/SMN/bilateral ECN. Connectivity within the left hippocampus of dDMN and the right medial superior frontal gyrus of aSN was a significant predictor of depression level in PD patients.

CONCLUSIONS

Aberrant intra- and inter-network FC is involved in several important hubs in the large-scale networks, which can be a biomarker for distinguishing PDD from PDND.

摘要

背景

最近有人提出网络紊乱与帕金森病(PD)中抑郁症的发生有关。然而,PD 中抑郁症潜在的神经生物学机制仍不清楚。

目的

本研究旨在调查伴有和不伴有抑郁症的 PD 患者(分别为 PDD 和 PDND 患者)的脑内网络和脑间网络连接性是否有不同变化。

方法

41 例 PDD 患者、64 例 PDND 患者和 55 例健康对照者(HCs)接受静息态功能磁共振成像(fMRI)检查。使用独立成分分析(ICA)提取默认模式网络(DMN)、执行控制网络(ECN)、突显网络(SN)、楔前叶网络(PCUN)和感觉运动网络(SMN),然后测量这些网络内部和之间的功能连接(FC)值。

结果

PDD 患者在 DMN、ECN、SN、PCUN 和 SMN 内表现出异常的 FC 值。此外,PDD 患者在前 SN(aSN)与双侧 ECN 之间、后 SN(pSN)与背侧 DMN(dDMN)之间以及 PCUN 与 dDMN/SMN/双侧 ECN 之间的连接性降低。dDMN 的左海马体与 aSN 的右内侧额上回之间的连接性是 PD 患者抑郁程度的显著预测指标。

结论

网络内和网络间的 FC 异常涉及大规模网络中的几个重要枢纽,这可能是区分 PDD 和 PDND 的生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/92e0/7901489/7f617e7a9117/fnins-14-573538-g001.jpg

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