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，并且成本很高， 残疾和死亡率。尽管可用于治疗MDD的循证药物和心理治疗 完全持续的缓解并不常见。经颅磁刺激（TMS）是FDA清除的 干预措施为治疗耐药性抑郁症患者（TRD）提供了新的策略。 TMS是 通过VA临床TMS试点计划在VA内获得。 TMS基于神经电路范式 MDD认为刺激在关键节点（例如，背外侧前额叶皮层）可以恢复功能 与情绪调节有关的大脑区域网络。尽管大量的TRD患者反应 对TMS很好，许多人没有。这表明某些患者有一种神经网络功能障碍，更多的是 适合TMS。静止脑电图（EEG）提供了一种安全，方便和可靠的方式 测量局灶性大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 与对抗抑郁药的反应有关，但进行了有限的研究以识别 EEG标记可预测用TMS的抗抑郁反应。这是一个关键的差距，因为TM可能 通过直接调节神经网络活动进行操作，从而使神经的基线差异 网络功能应有助于确定哪些患者对TMS有反应或多或少。 我们小组的研究人员已经确定了基于脑电图的假定预测性生物标志物，以响应TMS trd。这些（γ振荡的差异模式）之一可能会特别预测对10 Hz TMS的响应 应用于左侧外侧前额叶皮层，接收TMS的退伍军人的TMS类型 在TMS试点计划中。另一个（在治疗过程中早期theta绳索的变化）可能预测 最终对TMS的响应；这种潜在的生物标志物是由安德鲁·莱克特（Andrew Leuchter）博士确定的（有关此的顾问 授予），并已证明还可以预测对抗抑郁药和深脑刺​​激的反应 对于trd。通过添加基线（预处理）和每周休息的脑电图评估 临床TMS试点计划，本研究的目标是：（1）测试潜在的响应生物标志物 在接受TMS治疗抑郁症的大量退伍军人样本中以基线测量（n = 400）； （2） 评估第二个假定的生物标志物（治疗期间theta绳索的早期变化） 预测最终对TMS的响应； （3）利用这一大样本来识别其他潜在的生物标志物 （例如早期和对TM的晚期响应的标记，对其他TMS参数的响应标记 （例如，5 Hz，1 Hz或Theta Burst tms），以及可以与治疗有关的变化标记 机制）; （3）创建一个基础架构，以快速识别和测试其他基于EEG的基础架构 抑郁症和其他精神病患者的治疗反应生物标志物 与VA相关，例如PTSD和/或TBI。创建的基础架构最初将由五个站点组成 该研究小组的核心构成了该小组的核心，然后在整个项目过程中包括10个站点。它 希望这种基础架构将随着时间的推移继续扩展，以包括TMS中的许多站点 试点计划。这项研究以及创建的基础设施对退伍军人来说将具有很高的价值 迈向使用TMS进行TRD的个性化医学方法的重要一步。