Monash Alfred Psychiatry Research Centre, Melbourne, Australia.
Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, Victoria, Australia.
Hum Brain Mapp. 2019 Nov 1;40(16):4618-4629. doi: 10.1002/hbm.24725. Epub 2019 Jul 22.
The neurobiology of major depressive disorder (MDD) remains incompletely understood, and many individuals fail to respond to standard treatments. Repetitive transcranial magnetic stimulation (rTMS) of the dorsolateral prefrontal cortex (DLPFC) has emerged as a promising antidepressant therapy. However, the heterogeneity of response underscores a pressing need for biomarkers of treatment outcome. We acquired resting state functional magnetic resonance imaging (rsfMRI) data in 47 MDD individuals prior to 5-8 weeks of rTMS treatment targeted using the F3 beam approach and in 29 healthy comparison subjects. The caudate, prefrontal cortex, and thalamus showed significantly lower blood oxygenation level-dependent (BOLD) signal power in MDD individuals at baseline. Critically, individuals who responded best to treatment were associated with lower pre-treatment BOLD power in these regions. Additionally, functional connectivity (FC) in the default mode and affective networks was associated with treatment response. We leveraged these findings to train support vector machines (SVMs) to predict individual treatment responses, based on learned patterns of baseline FC, BOLD signal power and clinical features. Treatment response (responder vs. nonresponder) was predicted with 85-95% accuracy. Reduction in symptoms was predicted to within a mean error of ±16% (r = .68, p < .001). These preliminary findings suggest that therapeutic outcome to DLPFC-rTMS could be predicted at a clinically meaningful level using only a small number of core neurobiological features of MDD, warranting prospective testing to ascertain generalizability. This provides a novel, transparent and physiologically plausible multivariate approach for classification of individual response to what has become the most commonly employed rTMS treatment worldwide. This study utilizes data from a larger clinical study (Australian New Zealand Clinical Trials Registry: Investigating Predictors of Response to Transcranial Magnetic Stimulation for the Treatment of Depression; ACTRN12610001071011; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336262).
重度抑郁症（MDD）的神经生物学机制仍不完全清楚，许多患者对标准治疗方法没有反应。重复经颅磁刺激（rTMS）治疗外侧前额叶皮层（DLPFC）已成为一种有前途的抗抑郁治疗方法。然而，反应的异质性突出表明迫切需要治疗结果的生物标志物。我们在接受 5-8 周的 F3 光束 rTMS 治疗之前，从 47 名 MDD 患者和 29 名健康对照者中获取了静息状态功能磁共振成像（rsfMRI）数据。在基线时，MDD 患者的尾状核、前额叶皮层和丘脑的血氧水平依赖（BOLD）信号功率明显较低。关键的是，对治疗反应最好的个体与这些区域的治疗前 BOLD 功率较低有关。此外，默认模式和情感网络的功能连接（FC）与治疗反应相关。我们利用这些发现来训练支持向量机（SVM），根据基线 FC、BOLD 信号功率和临床特征的学习模式，预测个体的治疗反应。治疗反应（应答者与无应答者）的预测准确率为 85-95%。症状的减轻预计在平均误差±16%（r=0.68，p<0.001）内。这些初步发现表明，仅使用 MDD 的少数核心神经生物学特征，就可以在临床上有意义的水平预测 DLPFC-rTMS 的治疗效果，需要前瞻性测试以确定其普遍性。这为成为全球最常用的 rTMS 治疗方法提供了一种新颖、透明且生理上合理的个体反应分类的多变量方法。本研究使用了一项更大的临床研究的数据（澳大利亚和新西兰临床试验注册处：研究经颅磁刺激治疗抑郁症的反应预测因素；ACTRN12610001071011；https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336262）。
