Targeting Network Dysfunction in Apathy of Late-life Depression Using Digital Therapeutics

使用数字疗法针对晚年抑郁症冷漠中的网络功能障碍

• 批准号: 10591712
• 负责人: Lauren Elizabeth Oberlin
• 金额: $ 19.48万
• 依托单位: WEILL MEDICAL COLL OF CORNELL UNIV
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-01 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10591712
• 关键词: Adult; Aging; Antidepressive Agents; Attention; Behavior; Behavioral; Brain; Caregiver Burden; Caring; Clinical; Clinical Trials; Cognitive; Cognitive deficits; Consultations; Control Groups; Data; Depressed mood; Development; Disease; Disease remission; Educational Intervention; Elderly; Emotional; Evaluation; Exercise; Expectancy; Functional Magnetic Resonance Imaging; Functional disorder; Future; Generations; Goals; Health; Home; Impaired cognition; Impairment; Insula of Reil; Intervention; Investigational Therapies; K-Series Research Career Programs; Knowledge; Major Depressive Disorder; Medical; Mental Depression; Modeling; Mood Disorders; Moods; Morbidity - disease rate; Motivation; National Institute of Mental Health; Network-based; Neurosciences; Nucleus Accumbens; Outcome; Participant; Patients; Performance; Persons; Phenotype; Population; Prefrontal Cortex; Process; Public Health; Quality of life; Randomized; Randomized, Controlled Trials; Research; Research Personnel; Rest; Rewards; Sampling; Series; Severities; Structure; Subgroup; Symptoms; Syndrome; Technical Expertise; Training; Training Programs; Translating; Video Games; Withdrawal; affective disturbance; alternative treatment; arm; attentional control; career; chronic depression; clinical efficacy; clinically significant; cognitive benefits; cognitive control; cognitive process; cognitive training; computerized; depressed patient; depressive symptoms; design; digital; digital delivery; digital treatment; disability; efficacious treatment; executive function; functional decline; functional disability; functional outcomes; geriatric depression; high risk; hospitalization rates; improved; innovation; motivated behavior; neglect; network dysfunction; neuroimaging; non-demented; novel; novel therapeutics; patient engagement; personalized medicine; post intervention; predicting response; primary outcome; reduce symptoms; remote delivery; response; secondary outcome; sedentary lifestyle; skills; social; support network; sustained attention; theories; therapeutic target; training project; treatment strategy; virtual delivery; web platform; white matter

PROJECT SUMMARY/ABSTRACT This K23 Career Development Award is designed to provide the conceptual knowledge and technical skills necessary for the PI to pursue a career as an independent investigator evaluating brain network targets to optimize non-pharmacologic interventions for difficult-to-treat mood and cognitive disturbances in aging. Apathy is a persistent and disabling disorder of motivation that afflicts 30-50% of patients with late-life depression (LLD). Apathy worsens clinical outcomes in LLD, as apathetic depressed patients have poor response to existing treatments and higher rates of hospitalization, functional decline, and increased caregiver burden. Functional network abnormalities in a core set of brain circuits that interact to support motivated behavior (salience, executive control, and reward networks) may underlie apathy of LLD. Options for the efficacious treatment of apathy of LLD are limited, and novel interventions are urgently needed. This proposal is based on the premise that customizing interventions based on theorized brain mechanisms of apathy may increase the potency and scalability of promising therapies. This K23 proposes to conduct a randomized controlled trial evaluating the potential of a customized digital cognitive training (DCT) intervention to target brain network abnormalities in apathy of LLD and reduce symptoms of apathy and related cognitive and behavioral deficits. Eighty-four older adults with major depressive disorder and clinically significant apathy will be randomized to four weeks of a home-based DCT intervention or an active expectancy-matched control. The DCT will involve a suite of exercises designed to engage brain networks disrupted in apathy by targeting cognitive processes (i.e., salience processing, sustained attention, cognitive control) supported by these networks. Aligned with NIMH’s experimental therapeutics approach, we will examine the extent to which a targeted DCT program modulates functional network disturbances in apathy of LLD and improves apathy and associated cognitive deficits. The proposed study will generate preliminary data regarding network targets of a customized digital therapeutic that may translate to mood and cognitive benefits, and may guide future personalization of treatments for motivational disturbances in older adulthood. The training provided through this K23 will advance my knowledge and skillsets in: 1) the design and delivery of a neuroscience-informed, virtually-delivered intervention targeting a distinct subtype of depressed older adults; 2) use of functional MRI to probe mechanisms of action of the proposed DCT; 3) advanced longitudinal modeling of clinical trial data to assess trajectories of change and identify predictors of response and; 4) generating an R-series experimental therapeutics target engagement application. This training will prepare me for an independent research career developing and refining neuroscience-based interventions targeting traditionally intractable and functionally impairing mood and cognitive disturbances in older adulthood.

项目总结/摘要 K23职业发展奖旨在提供概念知识和技术 PI追求职业生涯所需的技能，作为一个独立的研究者评估大脑网络目标 优化非药物干预，以治疗老年人难以治疗的情绪和认知障碍。 冷漠是一种持续性和致残性的动机障碍，困扰着30-50%的老年患者。 抑郁症（LLD）。冷漠影响LLD的临床结局，因为冷漠的抑郁症患者 对现有治疗的反应和更高的住院率、功能下降和护理人员增加 负担一组核心脑回路中的功能网络异常，这些脑回路相互作用以支持有动机的 行为（突出性，执行控制和奖励网络）可能是LLD冷漠的基础。选项 LLD冷漠的有效治疗是有限的，并且迫切需要新的干预措施。 这项建议是基于这样的前提，即根据理论上的大脑定制干预措施， 冷漠的机制可能会增加有前途的治疗的效力和可扩展性。K23建议 进行随机对照试验，评估定制数字认知训练（DCT）的潜力 针对LLD冷漠中脑网络异常进行干预并减轻冷漠及相关症状 认知和行为缺陷。84名患有重度抑郁症的老年人， 显著冷漠者将被随机分配到为期四周的家庭DCT干预或积极的 期望值匹配对照。DCT将涉及一系列旨在参与大脑网络的练习 通过针对认知过程（即，突显加工，持续注意，认知 这些网络的支持。与NIMH的实验治疗方法相一致，我们将 检查有针对性的DCT计划在多大程度上调制功能性网络干扰， LLD和改善冷漠和相关的认知缺陷。拟议的研究将产生初步数据 关于可以转化为情绪和认知益处的定制数字治疗的网络目标， 并可能指导未来对老年人动机障碍的个性化治疗。 通过这个K23提供的培训将提高我在以下方面的知识和技能：1）设计和 提供神经科学信息，虚拟提供干预，针对不同的抑郁亚型 老年人; 2）使用功能性MRI来探测拟议DCT的作用机制; 3）晚期 对临床试验数据进行纵向建模，以评估变化轨迹并识别反应预测因子 以及; 4）生成R系列实验治疗靶点接合应用。本次培训将 为我的独立研究生涯做好准备，开发和完善基于神经科学的干预措施 针对传统上顽固的和功能性损害的情绪和认知障碍，在老年人。