2/3: Recurrence markers, cognitive burden and neurobiological homeostasis in late-life depression (REMBRANDT)

2/3：晚年抑郁症的复发标志物、认知负担和神经生物学稳态（REMBRANDT）

• 批准号: 10308408
• 负责人: Carmen Andreescu
• 金额: $ 103.52万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-15 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10308408
• 关键词: Affect; Affective; Antidepressive Agents; Behavioral; Clinical; Cognitive; Data; Depressed mood; Development; Early Diagnosis; Ecological momentary assessment; Elderly; Environmental Monitoring; Equilibrium; Exhibits; Functional Magnetic Resonance Imaging; Future; Goals; Homeostasis; Impaired cognition; Individual; Laboratories; Longitudinal Studies; Measures; Mental Depression; Monitor; Moods; Neurobiology; Noise; Participant; Performance; Predictive Factor; Prevention; Process; Recording of previous events; Recovery; Recurrence; Regulation; Reporting; Residual state; Risk; Risk Marker; Severities; Signal Transduction; Site; Sleep; Stress; Subgroup; Symptoms; Testing; Therapeutic Intervention; Time; Translating; actigraphy; aging brain; clinical practice; cognitive function; cognitive load; cognitive performance; depressive symptoms; executive function; experience; geriatric depression; high risk; mood symptom; negative affect; network models; neural network; neuroimaging; predictive marker; prospective; relating to nervous system; rumination; single episode major depressive disorder; stress reactivity; young adult

ABSTRACT Repeated major depressive episodes are particularly problematic for older adults who have a more brittle recovery than younger adults. Our data show that, despite antidepressant treatment, almost 60% of remitted older adults experience recurrence within four years. Beyond simply relying on past history and reported current stress, it is unclear what neurobiological factors are prospectively associated with recurrence risk, when these factors trigger recurrence, and how they contribute to the high rates of cognitive impairment observed in late-life depression (LLD). Using a model of network homeostasis, we posit that depressive episodes are characterized by disrupted homeostasis in key neural networks involved in affect regulation and cognitive function. Our preliminary data indicate that treatment non-remitters have residual functional network alterations and high network instability (higher fluctuations in temporal signal-to-noise ratio). We hypothesize that remitters with residual functional network alterations and greater instability remain at high risk of recurrence with subsequent stress exposure. This disequilibrium contributes to subsyndromal symptoms followed by full recurrence. These processes may also contribute to the higher rate of cognitive impairment and decline observed in LLD. Our groups have reported elevated rates of cognitive decline in remitted LLD and an association of recurrence with accelerated brain aging. We hypothesize that greater neural reactivity to stress may accelerate brain aging and cognitive decline and that deficits/variability in performance on tasks dependent on ECN may serve as markers of network alterations and signal increased recurrence risk. The goals of this study are to A) identify neurobiological factors that predict recurrence risk, and B) examine how cognitive performance changes are both influenced by these same neurobiological factors and also predict recurrence risk. Our approach is to conduct a three-site, two-year longitudinal study of remitted LLD and never-depressed elders. Every 8 months we will conduct laboratory assessments, including clinical, cognitive and neuroimaging assessments and an in-scanner stress paradigm, along with burst ecological momentary assessments (EMA) of mood variability, stress exposure, cognitive performance, and passive actigraphy. As an exploratory goal, we will examine whether continuous ecological monitoring of mood and activity can provide early detection of recurrence. A subgroup will be continuously monitored by EMA and actigraphy for state shifts (persistent worsening) or variance shifts (increased variability) in symptom severity. When shifts in mood symptoms are identified, they will engage in ad-hoc clinical and neuroimaging testing. Results from this study may be translated in clinical practice through the future development of easy-to-use platforms (e.g. apps) that signal to clinicians increased risk of impending recurrence, thus allowing for swift therapeutic intervention.

抽象的 重复的重大抑郁发作对于更脆弱的老年人特别有问题 康复比年轻人。我们的数据表明，尽管抗抑郁药治疗，但几乎有60％的汇款 老年人在四年内经历复发。不仅依靠过去的历史并报告 目前的压力，目前尚不清楚哪些神经生物学因素前瞻性地与复发风险相关， 当这些因素触发复发，以及它们如何促进认知障碍的高率 在晚期抑郁症（LLD）中观察到。使用网络稳态模型，我们认为这种抑郁症 情节的特征是在关键的神经网络中涉及影响调节和 认知功能。我们的初步数据表明治疗非临时工具有残留的功能网络 变化和高网络不稳定性（时间信噪比的较高波动）。我们假设 随着残留功能网络改变和更大的不稳定性的汇率，仍然处于高风险 随后的应力暴露会复发。这种不平衡有助于亚素症状 其次是完全复发。这些过程也可能导致更高的认知障碍率和 在LLD中观察到的下降。我们的小组报告说，LLD的认知能力下降率升高 复发与加速大脑衰老的关联。我们假设对压力的神经反应更大 可能会加速大脑衰老和认知能力下降，以及任务绩效的赤字/变异性 取决于ECN可以用作网络改变的标志，并信号增加复发风险。这 这项研究的目标是a）确定可预测复发风险的神经生物学因素，b）检查如何 认知性能的变化都受这些相同的神经生物学因素的影响，也预测 复发风险。我们的方法是对汇出的LLD和 永不沮丧的长者。每8个月，我们将进行实验室评估，包括临床，认知 和神经影像学评估以及扫描仪的压力范式，以及爆发的生态瞬间 情绪变异性，压力暴露，认知表现和被动行为的评估（EMA）。作为 一个探索性的目标，我们将检查情绪和活动的持续生态监测是否可以 提供复发的早期检测。 EMA和Actraphy将不断监视子组 状态转移（持续恶化）或差异转移（增加的变异性）。当移动时 确定了情绪症状，他们将进行临时临床和神经影像学测试。结果 可以通过易于使用的平台的未来开发（例如应用程序）在临床实践中翻译研究 向临床医生发出的信号增加了即将发生的复发风险，从而允许快速治疗干预。