Suppr超能文献

大脑网络拓扑结构的个体差异与重度抑郁症的病程相关。

Individual variation in brain network topology is linked to course of illness in major depressive disorder.

作者信息

Sheng Wei, Cui Qian, Jiang Kexing, Chen Yuyan, Tang Qin, Wang Chong, Fan Yunshuang, Guo Jing, Lu Fengmei, He Zongling, Chen Huafu

机构信息

The Clinical Hospital of Chengdu Brain Science Institute, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China.

MOE Key Lab for Neuroinformation, High Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu 611731, China.

出版信息

Cereb Cortex. 2022 Nov 21;32(23):5301-5310. doi: 10.1093/cercor/bhac015.

Abstract

Major depressive disorder (MDD) is a chronic and highly recurrent disorder. The functional connectivity in depression is affected by the cumulative effect of course of illness. However, previous neuroimaging studies on abnormal functional connection have not mainly focused on the disease duration, which is seen as a secondary factor. Here, we used a data-driven analysis (multivariate distance matrix regression) to examine the relationship between the course of illness and resting-state functional dysconnectivity in MDD. This method identified a region in the anterior cingulate cortex, which is most linked to course of illness. Specifically, follow-up seed analyses show this phenomenon resulted from the individual differences in the topological distribution of three networks. In individuals with short-duration MDD, the connection to the default mode network was strong. By contrast, individuals with long-duration MDD showed hyperconnectivity to the ventral attention network and the frontoparietal network. These results emphasized the centrality of the anterior cingulate cortex in the pathophysiology of the increased course of illness and implied critical links between network topography and pathological duration. Thus, dissociable patterns of connectivity of the anterior cingulate cortex is an important dimension feature of the disease process of depression.

摘要

重度抑郁症(MDD)是一种慢性且高复发性的疾病。抑郁症中的功能连接性受病程累积效应的影响。然而,先前关于异常功能连接的神经影像学研究主要未聚焦于病程,病程被视为次要因素。在此,我们使用数据驱动分析(多变量距离矩阵回归)来研究MDD中病程与静息态功能失调连接之间的关系。该方法在扣带回前部识别出一个与病程关联最为紧密的区域。具体而言,后续的种子点分析表明,这种现象源于三个网络拓扑分布的个体差异。在病程短的MDD个体中,与默认模式网络的连接较强。相比之下,病程长的MDD个体表现出与腹侧注意网络和额顶网络的过度连接。这些结果强调了扣带回前部在病程延长的病理生理学中的核心地位,并暗示了网络拓扑结构与病理病程之间的关键联系。因此,扣带回前部可分离的连接模式是抑郁症疾病过程的一个重要维度特征。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验