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绘制重度抑郁症默认模式网络背内侧功能梯度图。

Charting the dorsal-medial functional gradient of the default mode network in major depressive disorder.

机构信息

Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, PR China; Institute of Psychological Science, Hangzhou Normal University, Hangzhou, Zhejiang Province, PR China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang Province, PR China; Jing Hengyi School of Education, Hangzhou Normal University, Hangzhou, Zhejiang Province, PR China.

Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang Province, PR China; Institute of Psychological Science, Hangzhou Normal University, Hangzhou, Zhejiang Province, PR China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang Province, PR China.

出版信息

J Psychiatr Res. 2022 Sep;153:1-10. doi: 10.1016/j.jpsychires.2022.06.059. Epub 2022 Jun 28.

Abstract

Major depressive disorder (MDD) is a common and disabling psychiatric condition associated with aberrant functional activity of the default mode network (DMN). However, it is unclear how the DMN dysfunction in MDD patients is characterized by functional connectivity diversity or gradient and whether antidepressant therapy causes the abnormal functional gradient of the DMN to change toward normalization. In current work, we estimated the functional gradient of the DMN derived from resting state functional magnetic resonance imaging in MDD patients (n = 70) and matching healthy controls (n = 43) and identified MDD-related functional connectivity diversity of the DMN. The longitudinal changes of the DMN functional gradient in 36 MDD patients were assessed before and after 12-week antidepressant treatment. Compared to the healthy controls, the functional gradient of the DMN exhibited relatively relative compression along the dorsal-medial axis in MDD patients at baseline and antidepressant treatment could normalize these DMN gradient abnormalities. A regularized least-squares regression model based on DMN gradient features at baseline significantly predicted the change of Hamilton Depression Rating (HAMD) Scale scores after antidepressant treatment. The medial prefrontal cortex gradient had a more contribution to prediction of antidepressant efficacy. Our findings provided a novel insight into the neurobiological mechanism underlying MDD from the perspective of the DMN functional gradient.

摘要

重度抑郁症(MDD)是一种常见的精神障碍,与默认模式网络(DMN)的功能活动异常有关。然而,目前尚不清楚 MDD 患者的 DMN 功能障碍如何表现为功能连接多样性或梯度,以及抗抑郁治疗是否会导致 DMN 的异常功能梯度向正常化方向改变。在当前的工作中,我们从 MDD 患者(n=70)和匹配的健康对照组(n=43)的静息态功能磁共振成像中估计了 DMN 的功能梯度,并确定了与 MDD 相关的 DMN 功能连接多样性。在 36 名 MDD 患者中,在抗抑郁治疗前和治疗 12 周后评估了 DMN 功能梯度的纵向变化。与健康对照组相比,DMN 的功能梯度在基线时沿背内侧轴表现出相对压缩,而抗抑郁治疗可以使这些 DMN 梯度异常正常化。基于基线时 DMN 梯度特征的正则化最小二乘回归模型显著预测了抗抑郁治疗后汉密尔顿抑郁量表(HAMD)评分的变化。内侧前额叶皮层梯度对预测抗抑郁疗效的贡献更大。我们的研究结果从 DMN 功能梯度的角度为 MDD 的神经生物学机制提供了新的见解。

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