Novel neural circuit biomarkers of depression response to computer-augmented CBT

计算机增强 CBT 抑郁反应的新型神经回路生物标志物

• 批准号: 10166929
• 负责人: YVETTE I SHELINE
• 金额: $ 55.06万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-05 至 2023-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10166929
• 关键词: Adult; Algorithms; Ambulatory Care Facilities; American; Amygdaloid structure; Anterior; Antidepressive Agents; Biological Markers; Brain; Caring; Clinical; Clinical Management; Clinical Trials; Cognitive; Cognitive Therapy; Computer Models; Computers; Conflict (Psychology); Consumption; Control Groups; Coping Behavior; Data; Depressed mood; Diagnosis; Disease; Dorsal; Emotional; FDA approved; Future; Hour; Image; Individual; Inferior frontal gyrus; Lateral; Magnetic Resonance Imaging; Major Depressive Disorder; Measures; Mental Depression; National Institute of Mental Health; Outcome; Outpatients; Participant; Patients; Pennsylvania; Placebos; Population; Prefrontal Cortex; Protocols documentation; Psychological Tests; Randomized; Recovery; Research Personnel; Rest; Risk; Site-Directed Mutagenesis; Structure; Thick; Thinking; Time; Training; Treatment Efficacy; Treatment outcome; Universities; University Hospitals; Variant; Waiting Lists; Work; active method; base; cingulate cortex; clinical decision support; computer program; computerized; cost; cost effective; effective therapy; efficacy testing; evidence base; executive function; functional MRI scan; improved; negative affect; neural circuit; novel; novel marker; programs; recruit; reduce symptoms; rehearsal; response; skills training; treatment effect; treatment response

Every year more than 20% (55 million) of the adult American population suffers from major depression. (MDD). While effective treatments are available, depression remains under-diagnosed and under-treated, in part due to cost and availability of treatment. In the current application in response to NIMH NOT-14-007 we propose a clinical trial to study potential novel biomarkers of depression treatment response rather than to test efficacy of an efficient, cost-effective form of computer-augmented cognitive behavioral therapy (CCBT) which already has proven efficacy. We present pilot data supporting CBT-induced improvements in functional connectivity and task-induced activation in MDD. We also have found in previous work that this model of CCBT, known as Good Days Ahead (GDA), has efficacy for MDD that is not inferior to conventional individual CBT therapy across 8 and 16 weeks of treatment, despite reducing average therapist contact from 16 hours to less than 5 hours. We now propose that this new variation of cognitive therapy, which substitutes intensive, computer- administered skills training for hours of therapist contact, will engage the same brain targets we have previously seen with CBT. We hypothesize that it is rehearsal time during which an individual actively engages in corrective skills training that “mends” the brain connectivity and promotes recovery. We will recruit a total of 60 patients with MDD and 40 matched comparison healthy participants from the outpatient clinics of the Hospitals of the University of Pennsylvania. To take into account the impact of nonspecific factors, half of the MDD participants will be randomized to receive CCBT immediately after baseline assessments and half will first receive 8 weeks of Depression Care Management (DCM) (a clinically responsible alternative to a traditional wait-list control group that includes support and clinical management) before subsequently receiving CCBT. Aim 1: Compare baseline resting state functional connectivity and task-induced activity between MDD and controls. Aim 2: Assess CCBT treatment effects on resting state functional connectivity and task- induced activation in MDD comparing CCBT-treated participants to DCM –treated participants. Exploratory Aim: 1a:Predict the effects of baseline imaging measures on treatment outcomes; 1b: Predict the effects of baseline executive function on treatment outcomes.

每年超过20%（5500万）的美国成年人患有严重抑郁症。（MDD）。 虽然有有效的治疗方法，但抑郁症仍然诊断不足，治疗不足，部分原因是 治疗的成本和可用性。在响应于NIMH NOT-14-007的当前申请中，我们提出了一种方法， 研究抑郁症治疗反应的潜在新生物标志物的临床试验，而不是测试 一种有效的，具有成本效益的计算机增强认知行为疗法（CCBT）， 已被证明有效。我们目前的试点数据支持CBT诱导的功能连接的改善 和任务诱发的激活。我们还发现，在以前的工作中，这种模型的CCBT，称为 Good Days Ahead（GDA）对MDD的疗效不亚于传统的个体CBT疗法 在8周和16周的治疗中，尽管平均治疗师接触时间从16小时减少到不到5小时， 小时我们现在提出，这种新的认知疗法，它取代了密集的，计算机- 管理技能培训的治疗师接触小时，将从事相同的大脑目标，我们有 以前见过CBT。我们假设这是一个人积极参与的排练时间 在矫正技能训练，“修补”大脑连接和促进恢复。我们将招募总共 60例MDD患者和40例匹配的对照健康受试者来自 宾夕法尼亚大学附属医院。考虑到非特异性因素的影响， MDD受试者将在基线评估后立即随机接受CCBT，一半将接受CCBT。 首先接受8周的抑郁症护理管理（DCM）（一种临床上负责的替代治疗）， 传统的等待名单对照组，包括支持和临床管理）， CCBT。 目的1：比较MDD患者的基线静息状态功能连接和任务诱导活动 和控制。目标2：评估CCBT治疗对静息状态功能连接和任务的影响- 比较CCBT治疗的参与者与DCM治疗的参与者在MDD中诱导的激活。 探索性目的：1a：预测基线影像学指标对治疗结局的影响; 1b： 预测基线执行功能对治疗结果的影响。