DeMaster Dana, Godlewska Beata R, Liang Mingrui, Vannucci Marina, Bockmann Taya, Cao Bo, Selvaraj Sudhakar
Children's Learning Institute, Department of Pediatrics, University of Texas Health Science Center at Houston, McGovern Medical School, Houston, TX, USA.
Department of Psychiatry, Medical Sciences Division, University of Oxford, United Kingdom.; Oxford Health NHS Foundation Trust, Oxford, United Kingdom.
J Affect Disord. 2022 Jun 15;307:79-86. doi: 10.1016/j.jad.2022.03.041. Epub 2022 Mar 21.
Although depression has been widely researched, findings characterizing how brain regions influence each other remains scarce, yet this is critical for research on antidepressant treatments and individual responses to particular treatments.
To identify pre-treatment resting state effective connectivity (rsEC) patterns in patients with major depressive disorder (MDD) and explore their relationship with treatment response.
Thirty-four drug-free MDD patients had an MRI scan and were subsequently treated for 6 weeks with an SSRI escitalopram 10 mg daily; the response was defined as ≥50% decrease in Hamilton Depression Rating Scale (HAMD) score.
rsEC networks in default mode, central executive, and salience networks were identified for patients with depression. Exploratory analyses indicated higher connectivity strength related to baseline depression severity and response to treatment.
Preliminary analyses revealed widespread dysfunction of rsEC in depression. Functional rsEC may be useful as a predictive tool for antidepressant treatment response. A primary limitation of the current study was the small size; however, the group was carefully chosen, well-characterized, and included only medication-free patients. Further research in large samples of placebo-controlled studies would be required to confirm the results.
尽管抑郁症已得到广泛研究，但关于大脑区域如何相互影响的研究结果仍然很少，然而这对于抗抑郁治疗及个体对特定治疗的反应研究至关重要。
识别重度抑郁症（MDD）患者治疗前静息态有效连接（rsEC）模式，并探讨其与治疗反应的关系。
34名未服用过药物的MDD患者接受了磁共振成像扫描，随后每天服用10毫克SSRI艾司西酞普兰进行为期6周的治疗；反应定义为汉密尔顿抑郁量表（HAMD）评分降低≥50%。
确定了抑郁症患者在默认模式、中央执行和突显网络中的rsEC网络。探索性分析表明，连接强度较高与基线抑郁严重程度和治疗反应相关。
初步分析揭示了抑郁症中rsEC的广泛功能障碍。功能性rsEC可能作为抗抑郁治疗反应的预测工具。本研究的一个主要局限性是样本量小；然而，该组经过精心挑选，特征明确，且仅包括未服用药物的患者。需要在安慰剂对照研究的大样本中进行进一步研究以证实结果。
