Mai Naikeng, Wu Yujie, Zhong Xiaomei, Chen Ben, Zhang Min, Peng Qi, Ning Yuping
Department of Neurology, The Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangdong, China.
School of Psychology, South China Normal University, Guangdong, China.
Front Aging Neurosci. 2021 Feb 9;13:625175. doi: 10.3389/fnagi.2021.625175. eCollection 2021.
Modular organization reflects the activity patterns of our brain. Different disease states may lead to different activity patterns and clinical features. Early onset depression (EOD) and late onset depression (LOD) share the same clinical symptoms, but have different treatment strategies and prognosis. Thus, explored the modular organization of EOD and LOD might help us understand their pathogenesis. The study included 82 patients with late life depression (EOD 40, LOD 42) and 90 healthy controls. We evaluated the memory, executive function and processing speed and performed resting-stage functional MRI for all participants. We constructed a functional network based on Granger causality analysis and carried out modularity, normalized mutual information (NMI), Phi coefficient, within module degree z-score, and participation coefficient analyses for all the participants. The Granger function network analysis suggested that the functional modularity was different among the three groups ( = 0.0300), and NMI analysis confirmed that the partition of EOD was different from that of LOD ( = 0.0190). Rh.10d.ROI (polar frontal cortex) and Rh.IPS1.ROI (dorsal stream visual cortex) were shown to be the potential specific nodes in the modular assignment according to the Phi coefficient ( = 0.0002, = 0.0744 & = 0.0004, = 0.0744). This study reveal that the functional modularity and partition were different between EOD and LOD in Granger function network. These findings support the hypothesis that different pathological changes might exist in EOD and LOD.
模块化组织反映了我们大脑的活动模式。不同的疾病状态可能导致不同的活动模式和临床特征。早发性抑郁症(EOD)和晚发性抑郁症(LOD)具有相同的临床症状,但治疗策略和预后不同。因此,探索EOD和LOD的模块化组织可能有助于我们理解它们的发病机制。该研究纳入了82例老年抑郁症患者(EOD组40例,LOD组42例)和90名健康对照者。我们评估了所有参与者的记忆、执行功能和处理速度,并进行了静息态功能磁共振成像。我们基于格兰杰因果分析构建了一个功能网络,并对所有参与者进行了模块化、标准化互信息(NMI)、Phi系数、模块内度z分数和参与系数分析。格兰杰功能网络分析表明,三组之间的功能模块化存在差异( = 0.0300),NMI分析证实EOD组的划分与LOD组不同( = 0.0190)。根据Phi系数( = 0.0002, = 0.0744 & = 0.0004, = 0.0744),Rh.10d.ROI(额极皮层)和Rh.IPS1.ROI(背侧视觉皮层)被证明是模块化分配中的潜在特定节点。这项研究表明,在格兰杰功能网络中,EOD和LOD之间的功能模块化和划分是不同的。这些发现支持了EOD和LOD可能存在不同病理变化的假设。