Pretreatment Brain Connectome Fingerprint Predicts Treatment Response in Major Depressive Disorder.
Pretreatment Brain Connectome Fingerprint Predicts Treatment Response in Major Depressive Disorder.
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DOI：
10.1177/2470547020984726
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发表时间：
2020-01
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影响因子：
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通讯作者：
Abdallah CG
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作者：
Fan S;Nemati S;Akiki TJ;Roscoe J;Averill CL;Fouda S;Averill LA;Abdallah CG
重度抑郁症（MDD）治疗的特点是缓解率低，通常需要数周至数月的治疗。治疗前反应生物标志物的鉴定可能在新药开发、增强预后预测以及提供更个性化的药物方面发挥关键作用。使用网络限制强度预测建模（NRS-PM）方法，本研究的目的是确定治疗前功能性连接体指纹（CFPs），（1）预测症状改善，无论治疗方式如何，（2）预测治疗特异性改善。研究了未用药MDD患者（n = 200）的功能磁共振成像和行为数据。参与者被随机分配到每天治疗舍曲林或安慰剂8周。实施具有10次交叉验证的1000次迭代的NRS-PM，以识别预测第8周抑郁严重程度改善百分比的脑连接特征。该研究确定了一种治疗前CFP，其显著预测了独立于治疗方式的症状改善，但未能确定治疗特异性CFP。无论治疗方式如何，通过默认模式网络中模块与大脑其余部分之间的高预处理连接性，但执行网络中的低外部连接性，预测抗抑郁反应的改善。此外，高预处理内部节点连接在双边尾状核预测更好的反应。鉴定的CFP可能有助于药物开发并最终增强预后预测。然而，这些结果无助于提供个性化药物，因为治疗前功能连接未能预测治疗特异性反应。
Major depressive disorder (MDD) treatment is characterized by low remission rate and often involves weeks to months of treatment. Identification of pretreatment biomarkers of response may play a critical role in novel drug development, in enhanced prognostic predictions, and perhaps in providing more personalized medicine. Using a network restricted strength predictive modeling (NRS-PM) approach, the goal of the current study was to identify pretreatment functional connectome fingerprints (CFPs) that (1) predict symptom improvement regardless of treatment modality and (2) predict treatment specific improvement. Functional magnetic resonance imaging and behavioral data from unmedicated patients with MDD (n = 200) were investigated. Participants were randomized to daily treatment of sertraline or placebo for 8 weeks. NRS-PM with 1000 iterations of 10 cross-validation were implemented to identify brain connectivity signatures that predict percent improvement in depression severity at week-8. The study identified a pretreatment CFP that significantly predicts symptom improvement independent of treatment modality but failed to identify a treatment specific CFP. Regardless of treatment modality, improved antidepressant response was predicted by high pretreatment connectivity between modules in the default mode network and the rest of the brain, but low external connectivity in the executive network. Moreover, high pretreatment internal nodal connectivity in the bilateral caudate predicted better response. The identified CFP may contribute to drug development and ultimately to enhanced prognostic predictions. However, the results do not assist with providing personalized medicine, as pretreatment functional connectivity failed to predict treatment specific response.