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内源性连接组学是重度抑郁症缓解的预测性生物标志物。

Intrinsic connectomes are a predictive biomarker of remission in major depressive disorder.

机构信息

The Brain Dynamics Centre, Westmead Institute for Medical Research, The University of Sydney, Sydney, Australia.

Discipline of Psychiatry, Western Clinical School, The University of Sydney, Sydney, Australia.

出版信息

Mol Psychiatry. 2020 Jul;25(7):1537-1549. doi: 10.1038/s41380-019-0574-2. Epub 2019 Nov 6.

Abstract

Although major depressive disorder (MDD) is associated with altered functional coupling between disparate neural networks, the degree to which such measures are ameliorated by antidepressant treatment is unclear. It is also unclear whether functional connectivity can be used as a predictive biomarker of treatment response. Here, we used whole-brain functional connectivity analysis to identify neural signatures of remission following antidepressant treatment, and to identify connectomic predictors of treatment response. 163 MDD and 62 healthy individuals underwent functional MRI during pre-treatment baseline and 8-week follow-up sessions. Patients were randomized to escitalopram, sertraline or venlafaxine-XR antidepressants and assessed at follow-up for remission. Baseline measures of intrinsic functional connectivity between each pair of 333 regions were analyzed to identify pre-treatment connectomic features that distinguish remitters from non-remitters. We then interrogated these connectomic differences to determine if they changed post-treatment, distinguished patients from controls, and were modulated by medication type. Irrespective of medication type, remitters were distinguished from non-remitters by greater connectivity within the default mode network (DMN); specifically, between the DMN, fronto-parietal and somatomotor networks, the DMN and visual, limbic, auditory and ventral attention networks, and between the fronto-parietal and somatomotor networks with cingulo-opercular and dorsal attention networks. This baseline hypo-connectivity for non-remitters also distinguished them from controls and increased following treatment. In contrast, connectivity for remitters was higher than controls at baseline and also following remission, suggesting a trait-like connectomic characteristic. Increased functional connectivity within and between large-scale intrinsic brain networks may characterize acute recovery with antidepressants in depression.

摘要

虽然重度抑郁症(MDD)与不同神经网络之间功能耦合的改变有关,但抗抑郁治疗改善这种情况的程度尚不清楚。也不清楚功能连接是否可以用作治疗反应的预测生物标志物。在这里,我们使用全脑功能连接分析来确定抗抑郁治疗后缓解的神经特征,并确定治疗反应的连接预测因子。163 名 MDD 和 62 名健康个体在治疗前基线和 8 周随访期间进行了功能磁共振成像。患者随机分为依地普仑、舍曲林或文拉法辛 XR 抗抑郁药,并在随访时评估缓解情况。分析了 333 个区域中每对区域之间的内在功能连接的基线测量值,以确定区分缓解者和非缓解者的治疗前连接组特征。然后,我们研究了这些连接组差异,以确定它们是否在治疗后发生变化,是否可以区分患者和对照组,以及是否受药物类型的调节。无论药物类型如何,缓解者与非缓解者的区别在于默认模式网络(DMN)内的连接性更强;具体而言,DMN 与额顶叶和躯体运动网络之间、DMN 与视觉、边缘、听觉和腹侧注意网络之间、以及额顶叶和躯体运动网络与扣带回-顶叶和背侧注意网络之间的连接性更强。非缓解者的这种基线低连接性也将他们与对照组区分开来,并在治疗后增加。相比之下,缓解者的连接性在基线和缓解后都高于对照组,这表明存在一种特质性的连接组特征。在抑郁症中,抗抑郁药物治疗可能会导致大脑内部和之间的大尺度固有神经网络的功能连接增加,从而导致急性恢复。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bea8/7303006/3a048034dc41/41380_2019_574_Fig1_HTML.jpg

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