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.

项目摘要/摘要 这项K23职业发展奖旨在提供概念知识和技术 私家侦探从事评估大脑网络目标的独立调查员所需的技能 优化对老年难治性情绪和认知障碍的非药物干预。 冷漠是一种持续性和致残性的动力障碍，30%-50%的老年患者受到这种疾病的困扰 抑郁(LLD)。冷漠会恶化LLD的临床结果，因为冷漠抑郁患者的预后很差 对现有治疗的反应和更高的住院率、功能衰退和增加的照顾者 负担。相互作用以支持动机的一组核心脑回路中的功能网络异常 行为(显着性、执行控制和奖励网络)可能是导致LLD冷漠的原因。的选项 对LLD冷漠的有效治疗是有限的，迫切需要新的干预措施。 这一建议是基于这样一个前提，即基于理论化的大脑定制干预 冷漠的机制可能会增加有希望的治疗方法的效力和可扩展性。这位K23建议 进行一项随机对照试验，评估定制数字认知训练(DCT)的潜力 干预对LLD冷漠及相关症状的靶向性脑网络异常 认知和行为缺陷。84例患有严重抑郁障碍和临床症状的老年人 显著的冷漠将随机分为四周的基于家庭的DCT干预或积极的 与预期匹配的对照组。DCT将包括一套旨在参与大脑网络的练习 被针对认知过程的冷漠所扰乱(例如，显著加工、持续注意、认知 控制)由这些网络支持。与NIMH的实验治疗学方法保持一致，我们将 检查有针对性的DCT计划在多大程度上调节功能性网络干扰 LLD，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动机障碍的个性化治疗。 通过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 针对一种不同的抑郁症亚型提供神经科学知识的虚拟干预 老年人；2)使用功能磁共振来探索拟议的DCT的作用机制；3)先进的 对临床试验数据进行纵向建模，以评估变化轨迹并确定反应的预测因素 以及4)生成R系列实验治疗学目标参与应用。这次培训将 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 针对传统上难以解决的和功能受损的情绪和认知障碍的老年患者。