Department of Biomedical Engineering, University of Houston, 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 Aug 1;310:68-74. doi: 10.1016/j.jad.2022.04.123. Epub 2022 Apr 29.
Antidepressant drugs are the mainstay of treatment for patients with major depressive disorders (MDD). Given the critical role of the underlying neural control mechanism in the physiopathology of depression, this study aims to investigate the effects of escitalopram, a type of antidepressant drug, on the changes of functional brain controllability throughout the escitalopram treatment for MDD. We collected resting-state functional magnetic resonance imaging data from 20 unmedicated major depressive patients at baseline (visit 1, pre-treatment), one week (visit 2, 1-week after the onset of the treatment) and six weeks (visit 3, after the 6-week escitalopram treatment). Our results revealed that the global average and modal controllability of MDD patients were significantly larger and smaller, respectively, compared to healthy subjects (P < 0.01). Furthermore, the modal controllability rank of the frontoparietal network in depression patients was also significantly smaller than the healthy subjects (P < 0.01). However, throughout the escitalopram treatment, the global average and modal controllability, and the controllability of the default mode network and frontoparietal network of MDD patients were consistently changed to the healthy subjects' level. Our results also showed that the changes of global average and modal controllability measures can predict the improvements of clinical scores of the MDD patients as the escitalopram treatment advanced (P < 0.05). In conclusion, this study reveals promising brain controllability-based biomarkers to mechanistically understand and predict the effects of the escitalopram treatment for depression and maybe extended to predict and understand the effects of other interventions for other neurological and psychiatric diseases.
抗抑郁药物是治疗重度抑郁症（MDD）患者的主要方法。鉴于潜在的神经控制机制在抑郁症病理生理学中的关键作用，本研究旨在探讨抗抑郁药依他普仑对 MDD 患者接受依他普仑治疗期间功能性大脑可控性变化的影响。我们从 20 名未经治疗的重度抑郁症患者中采集了静息态功能磁共振成像数据，这些患者分别在基线时（第 1 次就诊，治疗前）、治疗开始后一周（第 2 次就诊，治疗后 1 周）和治疗 6 周后（第 3 次就诊）进行了采集。我们的研究结果表明，与健康对照组相比，MDD 患者的全局平均可控性和模态可控性均显著更大和更小（P<0.01）。此外，抑郁患者的额顶网络模态可控性排名也显著小于健康对照组（P<0.01）。然而，在依他普仑治疗期间，MDD 患者的全局平均可控性和模态可控性以及默认模式网络和额顶网络的可控性一直朝着健康对照组的水平变化。我们的研究结果还表明，全局平均可控性和模态可控性测量的变化可以预测 MDD 患者的临床评分随着依他普仑治疗的进展而改善（P<0.05）。总之，本研究揭示了基于大脑可控性的有前景的生物标志物，有助于从机制上理解和预测依他普仑治疗抑郁症的效果，也许还可以扩展到预测和理解其他干预措施对其他神经和精神疾病的效果。
