Neuropsychiatric Institute and Medical School of Southeast University, Nanjing, 210009, Jiang Su, China.
Department of Neurology, Affiliated ZhongDa Hospital of Southeast University, Nanjing, 210009, Jiang Su, China.
Brain Imaging Behav. 2020 Oct;14(5):1600-1611. doi: 10.1007/s11682-019-00091-x.
Cognitive deficit is a key feature of late-onset depression (LOD) and remains after clinical recovery. LOD has been associated with widespread neurobiological difficulties, including atrophy in gray and white matter (WM) tissue in areas distributed throughout the brain. However, little is known about the topological pattern changes of WM structural networks in LOD in the remitted state and its relationship to cognitive deficits. We acquired diffusion tensor images in 37 remitted LOD (rLOD) patients and 30 healthy controls. The tract-based spatial statistics method was employed to investigate WM tract integrity in rLOD. Graph-theory based network models were further used to characterize the topological organization of WM structural networks between the two groups. Compared with controls, rLOD patients showed decreased fractional anisotropy values in the left posterior cingulate bundle, right inferior fronto-occipital fasciculus and superior longitudinal fasciculus. Moreover, rLOD patients showed abnormal small-world architecture (i.e., increased path length and decreased network efficiency) in the WM structural networks. rLOD patients also showed reduced nodal efficiencies predominantly in the frontal-striatal-occipital and posterior default-mode regions. Importantly, these structural connectomic changes significantly correlated with cognitive deficits in the rLOD patients. Finally, rLOD networks showed more vulnerable to targeted attacks compared with healthy controls. These findings provide structural evidence to support the concept of rLOD that the core aspects of the pathophysiology of this disease are associated with disruptive alterations in the coordination of large-scale brain networks and advance our understanding of the neurobiological mechanism underlying cognitive deficits in the rLOD patients.
认知缺陷是迟发性抑郁症（LOD）的一个关键特征，并且在临床康复后仍然存在。LOD 与广泛的神经生物学困难有关，包括大脑中分布的灰质和白质（WM）组织的萎缩。然而，对于缓解状态下 LOD 患者 WM 结构网络的拓扑模式变化及其与认知缺陷的关系知之甚少。我们在 37 名缓解期 LOD（rLOD）患者和 30 名健康对照者中获得了扩散张量图像。采用基于束的空间统计学方法研究 rLOD 中的 WM 束完整性。进一步使用基于图论的网络模型来描述两组之间 WM 结构网络的拓扑组织。与对照组相比，rLOD 患者在左后扣带束、右下额枕束和上纵束中表现出分数各向异性值降低。此外，rLOD 患者在 WM 结构网络中表现出异常的小世界结构（即，路径长度增加和网络效率降低）。rLOD 患者还表现出额-纹状体-枕叶和后默认模式区域的节点效率降低。重要的是，这些结构连接组学变化与 rLOD 患者的认知缺陷显著相关。最后，rLOD 网络比健康对照组更容易受到靶向攻击。这些发现提供了结构证据，支持 rLOD 的概念，即这种疾病的病理生理学的核心方面与大脑网络的协调破坏改变有关，并推进了我们对 rLOD 患者认知缺陷的神经生物学机制的理解。
