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功能性便秘患者脑内固有功能结构的改变:一项基于表面的网络研究

Altered intrinsic functional brain architecture in patients with functional constipation: a surface-based network study.

作者信息

Yu Xiang, Yu Jingjie, Li Yuwei, Cong Jiying, Wang Chao, Fan Ran, Wang Wanbing, Zhou Lige, Xu Chen, Li Yiming, Liu Yawu

机构信息

Department of Radiology, Tianjin Union Medical Center, Tianjin, China.

Department of Psychiatry and Psychology, Tianjin Union Medical Center, Tianjin, China.

出版信息

Front Neurosci. 2023 Sep 21;17:1241993. doi: 10.3389/fnins.2023.1241993. eCollection 2023.

DOI:10.3389/fnins.2023.1241993
PMID:37811328
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10551127/
Abstract

BACKGROUND

Functional constipation (FCon) is a common functional gastrointestinal disorder (FGID). Studies have indicated a higher likelihood of psychiatric disorders, such as anxiety, depression, sleep disturbances, and impaired concentration, among patients with FCon. However, the underlying pathophysiological mechanisms responsible for these symptoms in FCon patients remain to be fully elucidated. The human brain is a complex network architecture with several fundamental organizational properties. Neurological interactions between gut symptoms and psychiatric issues may be closely associated with these complex networks.

METHODS

In the present study, a total of 35 patients with FCon and 40 healthy controls (HC) were recruited for a series of clinical examinations and resting-state functional magnetic imaging (RS-fMRI). We employed the surface-based analysis (SBA) approach, utilizing the Schaefer cortical parcellation template and Tikhonov regularization. Graph theoretical analysis (GTA) and functional connectivity (FC) analysis of RS-fMRI were conducted to investigate the aberrant network alterations between the two groups. Additionally, correlation analyses were performed between the network indices and clinical variables in patients with FCon.

RESULTS

At the global level, we found altered topological properties and networks in patients with FCon, mainly including the significantly increased clustering coefficient (C), local efficiency (E), and shortest path length (L), whereas the decreased global efficiency (E) compared to HC. At the regional level, patients with FCon exhibited increased nodal efficiency in the frontoparietal network (FPN). Furthermore, FC analysis demonstrated several functional alterations within and between the Yeo 7 networks, particularly including visual network (VN), limbic network (LN), default mode network (DMN), and somatosensory-motor network (SMN) in sub-network and large-scale network analysis. Correlation analysis revealed that there were no significant associations between the network metrics and clinical variables in the present study.

CONCLUSION

These results highlight the altered topological architecture of functional brain networks associated with visual perception abilities, emotion regulation, sensorimotor processing, and attentional control, which may contribute to effectively targeted treatment modalities for patients with FCon.

摘要

背景

功能性便秘(FCon)是一种常见的功能性胃肠疾病(FGID)。研究表明,FCon患者出现精神障碍的可能性更高,如焦虑、抑郁、睡眠障碍和注意力不集中。然而,FCon患者这些症状的潜在病理生理机制仍有待充分阐明。人类大脑是一个具有多种基本组织特性的复杂网络结构。肠道症状与精神问题之间的神经相互作用可能与这些复杂网络密切相关。

方法

在本研究中,共招募了35例FCon患者和40名健康对照(HC)进行一系列临床检查和静息态功能磁共振成像(RS-fMRI)。我们采用基于表面的分析(SBA)方法,利用Schaefer皮质分区模板和蒂霍诺夫正则化。对RS-fMRI进行图论分析(GTA)和功能连接(FC)分析,以研究两组之间异常的网络改变。此外,对FCon患者的网络指标与临床变量进行了相关性分析。

结果

在整体水平上,我们发现FCon患者的拓扑特性和网络发生了改变,主要包括聚类系数(C)、局部效率(E)和最短路径长度(L)显著增加,而与HC相比,全局效率(E)降低。在区域水平上,FCon患者在额顶叶网络(FPN)中的节点效率增加。此外,FC分析显示Yeo 7网络内部和之间存在一些功能改变,特别是在子网和大规模网络分析中的视觉网络(VN)、边缘网络(LN)、默认模式网络(DMN)和体感运动网络(SMN)。相关性分析显示,在本研究中网络指标与临床变量之间无显著关联。

结论

这些结果突出了与视觉感知能力、情绪调节、感觉运动处理和注意力控制相关的功能性脑网络拓扑结构改变,这可能有助于为FCon患者制定有效的靶向治疗方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49e3/10551127/21d8746e0401/fnins-17-1241993-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49e3/10551127/998f1000f329/fnins-17-1241993-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49e3/10551127/6a12253f5688/fnins-17-1241993-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49e3/10551127/751d7267fad3/fnins-17-1241993-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49e3/10551127/f410add62aa3/fnins-17-1241993-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49e3/10551127/21d8746e0401/fnins-17-1241993-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49e3/10551127/998f1000f329/fnins-17-1241993-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49e3/10551127/6a12253f5688/fnins-17-1241993-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49e3/10551127/751d7267fad3/fnins-17-1241993-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49e3/10551127/f410add62aa3/fnins-17-1241993-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/49e3/10551127/21d8746e0401/fnins-17-1241993-g005.jpg

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Front Neurosci. 2022 Jul 22;16:957620. doi: 10.3389/fnins.2022.957620. eCollection 2022.
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