3/3-Recurrence markers, cognitive burden and neurobiological homeostasis in late-life depression

3/3-晚年抑郁症的复发标记、认知负担和神经生物学稳态

• 批准号: 10078636
• 负责人: Olusola A. Ajilore
• 金额: $ 60.52万
• 依托单位: UNIVERSITY OF ILLINOIS AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10078636
• 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; single episode major depressive disorder; stress reactivity; young adult

PROJECT 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.

项目摘要 反复的重度抑郁发作对老年人来说尤其成问题， 比年轻的成年人恢复。我们的数据显示，尽管进行了抗抑郁治疗， 老年人会在四年内复发。除了简单地依靠过去的历史和报告 目前的压力，还不清楚哪些神经生物学因素与复发风险有前瞻性相关， 这些因素何时触发复发，以及它们如何导致认知障碍的高发生率 晚年抑郁症（LLD）使用网络稳态模型，我们证明抑郁症 发作的特征是参与情感调节的关键神经网络的稳态被破坏， 认知功能我们的初步数据表明，治疗非缓解者有残余的功能网络 变化和高网络不稳定性（时间信噪比的更高波动）。我们假设 具有残余功能网络改变和更大不稳定性的汇款人仍然处于高风险， 复发与随后的压力暴露。这种不平衡导致亚综合征症状 然后完全复发。这些过程也可能导致更高的认知障碍率， 在LLD中观察到下降。我们的研究小组报告了缓解的LLD和一个 复发与大脑加速老化的关系。我们假设神经对压力的反应 可能会加速大脑老化和认知能力下降， 依赖于ECN可以作为网络改变的标志物和信号增加的复发风险。的 本研究的目的是：A）确定预测复发风险的神经生物学因素，以及B）研究如何 认知表现的变化既受到这些相同的神经生物学因素的影响， 复发风险。我们的方法是对缓解的LLD进行为期两年的三个地点的纵向研究， 从不沮丧的老人每8个月，我们将进行实验室评估，包括临床，认知， 神经影像学评估和扫描仪内压力范例，沿着突发生态瞬间 情绪变化、压力暴露、认知表现和被动体动记录的EMA评估。作为 作为一个探索性的目标，我们将研究对情绪和活动的持续生态监测是否可以 早期发现复发。将通过EMA和腕动计持续监测亚组， 症状严重程度的状态变化（持续恶化）或方差变化（变异性增加）。当我们换班的时候 情绪症状被确定，他们将从事特设的临床和神经成像测试。结果从这个 通过未来开发易于使用的平台（例如应用程序），研究可转化为临床实践 这向临床医生发出了增加即将复发的风险的信号，从而允许迅速的治疗干预。