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.

重度抑郁症（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。虽然循证药物和心理疗法可用于治疗MDD， 完全和持续的缓解是不常见的。经颅磁刺激（TMS）是FDA批准的 该研究为治疗难治性抑郁症（TRD）患者提供了一种新的干预策略。TMS是 通过VA临床TMS试点计划在VA内提供。经颅磁刺激是基于神经回路范例 MDD将刺激定位在关键节点（例如，背外侧前额叶皮层）可以恢复功能， 情绪调节的大脑区域网络。虽然有相当数量的TRD患者 但是TMS，很多人没有。这表明，一些患者有一种形式的神经网络功能障碍， 适合TMS。静息脑电描记术（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图标记 与抗抑郁药物的反应有关，但进行了有限的研究，以确定 预测TMS抗抑郁反应的EEG标志物。这是一个关键的差距，因为TMS可能 通过直接调节神经网络活动来操作，使得神经网络中的基线差异 网络功能应有助于识别哪些患者更有可能或更少可能对TMS作出反应。 我们小组的研究人员已经确定了对TMS反应的推定预测性EEG生物标志物， TRD.其中之一（伽马振荡的差分模式）可以具体预测对10 Hz TMS的响应 应用于左背外侧前额叶皮层，>80%的接受TMS的退伍军人接受TMS的类型 TMS试点项目。另一个（治疗过程早期θ波一致性的变化）可以预测 最终对TMS的反应;这种潜在的生物标志物是由Andrew Leuchter博士（该研究的顾问）确定的。 格兰特），并已被证明也预测抗抑郁药物和脑深部电刺激的反应 对于TRD。通过将基线（治疗前）和每周静息EEG评估添加到VA国家 临床TMS试点计划，本研究的目的是：（1）测试潜在的反应生物标志物 在接受TMS治疗抑郁症的退伍军人的大样本中在基线时测量（N=400）;（2） 评估是否存在第二个假定的生物标志物（治疗期间θ一致性的早期变化） 预测对TMS的最终反应;（3）利用这一大样本来识别其他潜在的生物标志物 (such作为对TMS的早期与晚期反应的标志物，对其他TMS参数的反应的标志物 (e.g., 5 Hz、1 Hz或theta burst TMS），以及治疗变化的标志物， 机制）;（3）创建一个基础设施，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VA相关，如PTSD和/或TBI。创建的基础设施最初将包括五个站点 这是这个研究小组的核心，然后在项目过程中扩大到包括总共10个地点。它 希望这一基础设施将随着时间的推移继续扩展，以包括TMS中尽可能多的站点 尽可能的试点。这项研究，以及创建的基础设施，将通过采取高价值的退伍军人 这是向使用TMS治疗TRD的个性化医疗方法迈出的重要一步。