Assessing an electroencephalography (EEG) biomarker of response to transcranial magnetic stimulation for major depression

评估重度抑郁症对经颅磁刺激反应的脑电图 (EEG) 生物标志物

• 批准号: 9933192
• 负责人: Amit Etkin
• 金额: --
• 依托单位: WHITE RIVER JUNCTION VA MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9933192
• 关键词: Antidepressive Agents; Antidepressive Agents; Area; Area; Biological Markers; Biological Markers; Brain; Brain; Brain region; Brain region; Clinical; Clinical; Data Set; Deep Brain Stimulation; Deep Brain Stimulation; Devices; Devices; Disease remission; Disease remission; Electroencephalography; Electroencephalography; Electromagnetics; Electromagnetics; Enrollment; Enrollment; Future; Future; Goals; Goals; Grant; Grant; Infrastructure; Infrastructure; Intervention; Intervention; Left; Left; Machine Learning; Machine Learning; Major Depressive Disorder; Major Depressive Disorder; Measures; Measures; Mental Depression; Mental Depression; Methods; Methods; Patients; Patients; Pattern; Pattern; Pharmaceutical Preparations; Pharmaceutical Preparations; Post-Traumatic Stress Disorders; Post-Traumatic Stress Disorders; Prefrontal Cortex; Prefrontal Cortex; Psychotherapy; Psychotherapy; ROC Curve; ROC Curve; Research; Research; Research Infrastructure; Research Infrastructure; Research Personnel; Research Personnel; Rest; Rest; Sampling; Sampling; Severities; Severities; Site; Site; Testing; Testing; Time; Time; Transcranial magnetic stimulation; Transcranial magnetic stimulation; Veterans; Veterans; Work; Work; base; base; brain electrical activity; brain electrical activity; cost; cost; disability; disability; effective therapy; effective therapy; evidence base; evidence base; expectation; expectation; functional restoration; functional restoration; infrastructure development; infrastructure development; inventory of depressive symptomatology; inventory of depressive symptomatology; large datasets; mood regulation; mood regulation; mortality; mortality; network dysfunction; network dysfunction; neural circuit; neural circuit; neural network; neural network; novel; novel; novel strategies; novel strategies; personalized medicine; personalized medicine; potential biomarker; potential biomarker; predicting response; predicting response; predictive marker; predictive marker; programs; programs; response; response; response biomarker; response biomarker; therapy development; therapy development; treatment planning; treatment planning; treatment response; treatment response; treatment-resistant depression; treatment-resistant depression

Major Depressive Disorder (MDD) is highly prevalent among Veterans and associated with significant cost, disability and mortality. Although evidence-based medications and psychotherapies are available to treat MDD, full and sustained remission is uncommon. Transcranial magnetic stimulation (TMS) is an FDA-cleared intervention that offers a novel strategy for treating patients with treatment-resistant depression (TRD). TMS is available within the VA through the VA Clinical TMS Pilot Program. TMS is based in a neural circuit paradigm of MDD positing that stimulation at a key node (e.g., dorsolateral prefrontal cortex) can restore function within a network of brain regions involved in mood regulation. Although a substantial number of TRD patients respond well to TMS, many do not. This suggests some patients have a form of neural network dysfunction that is more amenable to TMS. Resting electroencephalography (EEG) provides a safe, convenient and reliable way to measure focal brain electrical activity and neural network function. Prior studies have identified EEG markers associated with response to antidepressant medications, but limited research has been conducted to identify EEG markers predictive of an antidepressant response with TMS. This is a critical gap, since TMS likely operates via direct modulation of neural network activity, such that baseline differences in neural network function should help identify which patients are more or less likely to respond to TMS. Investigators in our group have identified putative predictive EEG-based biomarkers for response to TMS for TRD. One of these (differential patterns of gamma oscillations) may specifically predict response to 10 Hz TMS applied to the left dorsolateral prefrontal cortex, the type of TMS received by >80% of Veterans receiving TMS in the TMS Pilot Program. Another (changes in theta cordance early in the course of treatment) may predict eventual response to TMS; this potential biomarker was identified by Dr. Andrew Leuchter (a consultant on this grant) and has been shown to also predict response to antidepressant medications and deep brain stimulation for TRD. By adding baseline (pretreatment) and weekly resting EEG assessment to the VA National Clinical TMS Pilot Program, the goals of this study are to: (1) test a potential response biomarker measured at baseline in a large sample of Veterans receiving TMS to treat depression (N=400); (2) assess whether a second putative biomarker (early changes in theta cordance during treatment) predict eventual response to TMS; (3) leverage this large sample to identify other potential biomarkers (such as markers of early versus late response to TMS, markers of response to other TMS parameters (e.g., 5 Hz, 1 Hz or theta burst TMS), and markers of change with treatment that may speak to mechanism); and (3) create an infrastructure to rapidly identify and test additional EEG-based biomarkers of treatment response in patients with depression and other psychiatric conditions relevant to the VA, such as PTSD and/or TBI. The infrastructure created will initially consist of the five sites that form the core of this study group, then expand to include a total of 10 sites over the course of the project. It is hoped that this infrastructure will continue to expand over time to include as many of the sites in the TMS Pilot Program as possible. This study, and the infrastructure created, will be of high value to Veterans by taking an important step towards a personalized medicine approach to the use of TMS for TRD.

严重抑郁障碍(MDD)在退伍军人中非常普遍，并与巨大的成本相关， 残疾和死亡率。尽管有循证药物和心理疗法可用于治疗MDD， 完全和持续的缓解是罕见的。经颅磁刺激(TMS)是FDA批准的 干预为治疗难治性抑郁症(TRD)患者提供了一种新的策略。TMS是 通过退伍军人管理局临床TMS试点计划在退伍军人管理局内提供。TMS基于神经电路范例 假设刺激关键节点(例如，背外侧前额叶皮质)可以恢复 参与情绪调节的大脑区域网络。尽管相当数量的TRD患者对 好吧，TMS，很多人都不这么认为。这表明一些患者有某种形式的神经网络功能障碍， 易受TMS影响的。静息脑电(EEG)提供了一种安全、方便、可靠的方法 测量局部脑电活动和神经网络功能。先前的研究已经确定了脑电标记物 与抗抑郁药物的反应有关，但进行的研究有限 脑电标记物预测TMS的抗抑郁反应。这是一个关键的差距，因为TMS很可能 通过直接调节神经网络活动来运作，从而使神经网络中的基线差异 网络功能应该有助于确定哪些患者对TMS有更多或更少的反应。 我们小组的研究人员已经确定了推测的基于脑电的生物标记物，用于治疗TMS TRD。其中之一(伽马振荡的不同模式)可以专门预测对10赫兹TMS的响应 应用于左侧背外侧前额叶皮质，80%接受TMS的退伍军人接受TMS的类型 在TMS试点计划中。另一种(治疗早期theta Cordance的变化)可能会预测 对TMS的最终反应；这个潜在的生物标记物是由Andrew Leuchter博士(这方面的顾问)确定的 GRANT)，并已被证明还可以预测抗抑郁药物和大脑深部刺激的反应 为了TRD。通过将基线(前处理)和每周静息脑电评估添加到退伍军人管理局国家 临床TMS试点计划，本研究的目标是：(1)测试潜在的反应生物标记物 在接受TMS治疗抑郁症的退伍军人中进行基线测量(N=400)；(2) 评估第二个可能的生物标志物(治疗期间theta Cordance的早期变化) 预测最终对TMS的反应；(3)利用这个大样本来确定其他潜在的生物标志物 (例如对TMS的早期和晚期响应的标记、对其他TMS参数的响应的标记 (例如，5赫兹、1赫兹或爆发性TM)，以及随着治疗的改变的标记 机制)；以及(3)创建基础设施以快速识别和测试额外的基于EEG的 抑郁症和其他精神疾病患者治疗反应的生物标志物 与退伍军人事务部相关，如创伤后应激障碍和/或创伤后应激障碍。创建的基础设施最初将由五个站点组成 这构成了这个研究小组的核心，然后扩展到在项目过程中总共包括10个地点。它 希望随着时间的推移，这种基础设施将继续扩展，以包括TMS中的尽可能多的站点 尽可能地实施试点计划。这项研究和建立的基础设施将对退伍军人具有很高的价值，因为 使用TMS治疗TRD的个性化医学方法是重要的一步。