Liang Nana, Xue Zhenpeng, Xu Jianchang, Sun Yumeng, Li Huiyan, Lu Jianping
State Key Laboratory of Chemical Oncogenomics, Shenzhen Key Laboratory of Chemical Genomics, Peking University Shenzhen Graduate School, Shenzhen, China; Department of Child Psychiatry of Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen Institute of Mental Health, Shenzhen, China.
Department of Child Psychiatry of Shenzhen Kangning Hospital, Shenzhen Mental Health Center, Shenzhen Institute of Mental Health, Shenzhen, China.
Psychiatry Res Neuroimaging. 2025 Apr;348:111961. doi: 10.1016/j.pscychresns.2025.111961. Epub 2025 Feb 11.
Depression is linked to abnormalities in brain networks. Resting-state functional connectivity (FC), as measured using resting-state fMRI (rs-fMRI), is a crucial tool for exploring the brain network abnormalities associated with depressive symptoms, as it reveals how disruptions in brain region interactions occur. However, research focusing on adolescents with depression is limited and inconsistent, highlighting the need for further studies in this area.
Fifty-five adolescents with Depressive episodes (DE) and 26 healthy controls (HCs) underwent resting-state fMRI. Depressive symptoms were assessed using the 17-item Hamilton Rating Scale for Depression (HAMD-17). Seed regions were defined based on Yeo's seven-network scheme, including the sensorimotor network (SMN), ventral attention network (VAN), dorsal attention network (DAN), visual network (VN), frontoparietal network (FPN), default mode network (DMN), and limbic network (LN). These seed regions were derived from analysis of large-scale FC in healthy individuals, and were selected for their relevance to cognition, emotion, and depression research. Network-based statistical analyses were used to compare the adolescents with DE to the HCs, and correlation analyses were employed to examine the relationships between FC changes and cognitive performance.
The results showed significant differences in FC between the DE and HCs groups, involving 17 nodes and 17 edges across seven networks. Decreased FC was observed within the FPN, as well as between the FPN and VAN, the FPN and DMN, and the SMN and both the DAN and VN. Increased FC was observed between the FPN and VN, between the DAN and other networks (i.e., the DMN and FPN), and between the SMN and multiple networks. Notably, FC between the right superior parietal (SMN) and right precuneus (DMN) showed a negative correlation with HAMD-17 scores.
These results suggest that adolescents with DE experience widespread brain network abnormalities characterized by hypoactivity in external networks such as the SMN and VN, as well as hyperactivity in associative regions, including the DMN, FPN, SMN, and LN. Although these changes in FC are evident, the specific mechanisms linking them to clinical symptoms remain unclear and warrant further investigation.
抑郁症与大脑网络异常有关。静息态功能连接（FC）通过静息态功能磁共振成像（rs-fMRI）进行测量，是探索与抑郁症状相关的大脑网络异常的关键工具，因为它揭示了大脑区域间相互作用是如何被破坏的。然而，针对青少年抑郁症患者的研究有限且结果不一致，这凸显了该领域进一步研究的必要性。
55名患有抑郁发作（DE）的青少年和26名健康对照者（HCs）接受了静息态功能磁共振成像检查。使用17项汉密尔顿抑郁量表（HAMD-17）评估抑郁症状。种子区域基于Yeo的七网络方案定义，包括感觉运动网络（SMN）、腹侧注意网络（VAN）、背侧注意网络（DAN）、视觉网络（VN）、额顶网络（FPN）、默认模式网络（DMN）和边缘网络（LN）。这些种子区域来自对健康个体大规模FC的分析，因其与认知、情感和抑郁症研究的相关性而被选中。基于网络的统计分析用于比较DE组青少年与HCs组，相关分析用于检验FC变化与认知表现之间的关系。
结果显示，DE组和HCs组在FC上存在显著差异，涉及七个网络中的17个节点和17条边。在FPN内，以及FPN与VAN之间、FPN与DMN之间、SMN与DAN和VN之间，均观察到FC降低。在FPN与VN之间、DAN与其他网络（即DMN和FPN）之间以及SMN与多个网络之间，观察到FC增加。值得注意的是，右侧顶上叶（SMN）与右侧楔前叶（DMN）之间的FC与HAMD-17评分呈负相关。
这些结果表明，患有DE的青少年经历了广泛的大脑网络异常，其特征是外部网络（如SMN和VN）活动减退，以及包括DMN、FPN、SMN和LN在内的关联区域活动亢进。尽管FC的这些变化很明显，但将它们与临床症状联系起来的具体机制仍不清楚，值得进一步研究。
