Individual variation in brain network topology is linked to course of illness in major depressive disorder. (12th February 2022)

• Record Type: Journal Article
• Authors: Sheng, Wei; Cui, Qian; Jiang, Kexing; Chen, Yuyan; Tang, Qin; Wang, Chong; Fan, Yunshuang; Guo, Jing; Lu, Fengmei; He, Zongling; Chen, Huafu
• Is Part Of: Cerebral cortex. Volume 32:Number 23(2022)
• Page Start: 5301
• Page End: 5310
• Publication Date: 2022-02-12
• Subjects: major depressive disorder -- course of illness -- functional connectivity -- multivariate distance-based matrix regression; Cerebral cortex -- Periodicals; Brain -- Periodicals; 612.825
• DOI: 10.1093/cercor/bhac015
• Languages: English
• ISSNs: 1047-3211

Abstract

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.