Combined EEG and in silico modeling to investigate the mechanisms of ketamine's sustained antidepressant effect in patients

结合脑电图和计算机建模研究氯胺酮对患者持续抗抑郁作用的机制

• 批准号: 10376804
• 负责人: PATRICK David SKOSNIK
• 金额: $ 19.64万
• 依托单位: YALE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-03-23 至 2023-08-21
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10376804
• 关键词: Affect; Anesthesia procedures; Anesthetics; Animal Model; Antidepressive Agents; Apical; Auditory; Auditory area; Biological Markers; Biophysics; Brain; Brain-Derived Neurotrophic Factor; Chemosensitization; Clinic; Computer Models; Connecticut; Data; Decision Making; Development; Diagnosis; Disease remission; Distal; Dose; Electroencephalography; FDA approved; Frequencies; Glutamatergic Agents; Glutamates; Hospitals; Human; Infusion procedures; Isomerism; Ketamine; Knowledge; Lead; Long-Term Potentiation; Measures; Medial; Memory; Mental Depression; Methods; Modeling; Monitor; Moods; Neocortex; Neuronal Plasticity; Patients; Persons; Pharmaceutical Preparations; Photic Stimulation; Prefrontal Cortex; Publishing; Research; Rodent Model; Role; Sensory; Signal Transduction; Somatosensory Evoked Potentials; Synapses; Synaptic plasticity; System; Techniques; Therapeutic; Therapeutic Effect; Time; United States; Vertebral column; Work; antidepressant effect; density; depression model; depressive symptoms; design; disability; enantiomer; improved; in silico; insight; mortality; neocortical; neuromechanism; novel; public health relevance; recruit; relating to nervous system; response; translational model; translational study; treatment effect; treatment response; treatment-resistant depression

ABSTRACT Depression affects around ten percent of people in the United States. Two-thirds of these patients do not respond to traditional antidepressants and are diagnosed with treatment-resistant depression (TRD). Also, conventional antidepressants take approximately three to four weeks to show effects. Ketamine, a drug that has been traditionally used as an anesthetic agent, represents a promising hope. At doses lower than those utilized for anesthesia, ketamine has been found to improve depressive symptoms in more than half of the patients diagnosed with TRD. Recently, an isomer of ketamine, esketamine, has been approved by the FDA for the treatment of TRD. Repeated dosing of ketamine and esketamine augment their antidepressant effect, prolonging the therapeutic benefit from a few days to up to a few weeks and increasing response and remission rates. Animal models of depression have shown that a single dose of ketamine works by increasing neuroplasticity, the ability of the brain to change and adapt. However, how repeated ketamine treatments augment the antidepressant effect is not known. Understanding the underlying mechanism of augmented therapeutic effect in humans would make it possible to a) prolong ketamine’s antidepressant effect beyond a few weeks, b) increase response and remission rates, and c) develop novel molecules with better response and remission rates. Therefore, we are proposing to combine two techniques to understand the brain changes associated with the augmented improvements in patients. The first technique is electroencephalography (EEG), which monitors the electrical activity of the neocortex, the part of the brain involved in memory, decision making, and mood, features that are affected in depression. Using an EEG task that measures neuroplasticity, we will probe the neocortex to identify changes in neuroplasticity associated with the sustained antidepressant effects in patients diagnosed with TRD treated with repeated ketamine dosing. They will undergo the EEG task before they begin their treatment, after their first treatment, and then again after they finish all their treatments. The second technique is computer modeling of the neocortex using a computer model that has been developed to understand the brain mechanisms generating EEG, called the Human Neocortical Neurosolver (HNN). We will use HNN to make mechanistic interpretations of the neocortical mechanisms underlying the EEG changes associated with the sustained antidepressant effect. This will identify the neocortical changes responsible for the sustained therapeutic response, which may allow for better treatment targeting.

摘要 在美国，大约有10%的人患有抑郁症。这些患者中有三分之二的人 对传统的抗抑郁药物没有反应，并被诊断为难治性抑郁症(TRD)。另外， 传统的抗抑郁药物大约需要三到四周的时间才能显现效果。氯胺酮，一种可以 传统上一直被用作麻醉剂，代表着一种很有前途的希望。剂量低于 用于麻醉的氯胺酮已被发现可以改善一半以上的抑郁症状 被诊断为TRD的患者。最近，氯胺酮的一种异构体，埃斯氯胺酮已经被fda批准。 用于治疗TRD。 反复服用氯胺酮和埃斯氯胺酮可增强其抗抑郁作用，延长 治疗效果从几天到最多几周，并提高反应和缓解率。动物 抑郁症的模型已经表明，单剂量的氯胺酮通过增加神经可塑性而起作用， 大脑改变和适应的能力。然而，重复的氯胺酮治疗如何增加 抗抑郁作用尚不清楚。了解增强疗效的潜在机制 可以将氯胺酮的抗抑郁作用延长几周以上，b) 提高应答率和缓解率，c)开发具有更好应答率和缓解率的新分子 费率。因此，我们建议结合两种技术来了解相关的大脑变化 随着患者病情的进一步改善。 第一种技术是脑电(EEG)，它监测人的脑电活动 新皮质，大脑中涉及记忆、决策和情绪的部分，这些功能受到 抑郁症。使用测量神经可塑性的脑电任务，我们将探测新皮质以识别变化 神经可塑性与TRD治疗后持续的抗抑郁作用相关 反复服用氯胺酮。他们将在开始治疗之前接受脑电检查，在他们的 第一次治疗，然后在他们完成所有治疗后再次治疗。 第二种技术是使用计算机模型对新皮质进行计算机建模，该计算机模型已经被 为了解产生脑电的大脑机制而开发的，称为人类神经皮质神经解算器 (HNN)。我们将使用HNN对潜在的新皮质机制进行机械论解释 脑电变化与持续的抗抑郁作用有关。这将识别新皮质的变化 负责持续的治疗反应，这可能允许更好的治疗靶向。