He Youze, Zhao Baoru, Liu Zhihan, Hu Yudie, Song Jian, Wu Jingsong
College of Rehabilitation Medicine, Fujian University of Traditional Chinese Medicine, Fuzhou, China.
The Academy of Rehabilitation Industry, Fujian University of Traditional Chinese Medicine, Fuzhou, China.
Transl Psychiatry. 2024 Dec 23;14(1):501. doi: 10.1038/s41398-024-03210-5.
Accumulating studies have highlighted the links between stress-related networks and the HPA axis for emotion regulation and proved the mapping associations between altered structural and functional networks (called SC-FC coupling) in depression. However, the signatures of SC-FC coupling in subthreshold depression (StD) individuals and their relationships with HPA axis reactivity, as well as the predictive power of these combinations for discriminating StD, remain unclear. This cross-sectional study enrolled 160 adults, including 117 StD and 43 healthy controls (HC). The propensity score matching method was applied for match-pair analysis between StD and HC. Herein, we measured depression level, cortisol level, and brain imaging outcomes. The functional MRI and diffusion tensor imaging methods were employed to acquire the network SC-FC couplings and topological attributes. Support vector machine models were employed to discriminate StD from HC. Herein, 43 pairs were matched, but four participants were excluded due to over-threshold head motion, leaving 41 participants in each group. General linear model results revealed a significant SC-FC coupling increase in the default mode network (DMN) and decrements of global efficiency in DMN and frontoparietal control network (P < 0.05), while the cortisol secretion significantly increased (P < 0.001) in StD individuals. Partial correlation analysis revealed positive associations between DMN coupling and cortisol values (r = 0.298, P = 0.033), and their combination provided greater power for discriminating StD than another single model, with the classification accuracy and AUC value up to 85.71% and 0.894, respectively. In summary, this study clarified the relationship between stress-related network SC-FC coupling and cortisol secretion in influencing depressive symptoms, whose combination would contribute to discriminating subthreshold depressive states in the future.
越来越多的研究强调了与压力相关的网络和下丘脑-垂体-肾上腺（HPA）轴在情绪调节方面的联系，并证实了抑郁症中结构和功能网络改变（称为结构-功能连接耦合，SC-FC耦合）之间的映射关联。然而，阈下抑郁（StD）个体中SC-FC耦合的特征及其与HPA轴反应性的关系，以及这些组合对区分StD的预测能力仍不清楚。这项横断面研究招募了160名成年人，包括117名StD患者和43名健康对照（HC）。采用倾向得分匹配法对StD和HC进行匹配对分析。在此，我们测量了抑郁水平、皮质醇水平和脑成像结果。采用功能磁共振成像和扩散张量成像方法获取网络SC-FC耦合和拓扑属性。采用支持向量机模型区分StD和HC。在此，43对被匹配，但4名参与者因头部运动超过阈值而被排除，每组各留下41名参与者。一般线性模型结果显示，默认模式网络（DMN）中SC-FC耦合显著增加，DMN和额顶叶控制网络的全局效率降低（P<0.05），而StD个体的皮质醇分泌显著增加（P<0.001）。偏相关分析显示DMN耦合与皮质醇值之间呈正相关（r=0.298，P=0.033），并且它们的组合比另一个单一模型具有更强的区分StD的能力，分类准确率和AUC值分别高达85.71%和0.894。总之，本研究阐明了与压力相关的网络SC-FC耦合和皮质醇分泌在影响抑郁症状方面的关系，其组合将有助于未来区分阈下抑郁状态。
