Neural predictors of outcome during relapse prevention treatment for anorexia nervosa

神经性厌食症复发预防治疗期间结果的神经预测因素

基本信息

项目摘要

Anorexia nervosa (AN) is a devastating psychiatric illness with significant morbidity and mortality rates, and relapse rates ranging from 40-80% after acute treatment. Extreme restriction of food intake is the central behavioral disturbance in illness, and confers significantly greater risk for relapse. Illness follows a heterogeneous course and clinical predictors of response to treatment are largely unknown. Maladaptive behavior in AN has behavioral and neural features suggesting habitual control. Yet, brain-based factors that relate to long-term outcomes and treatment response have not been studied. In other areas of psychiatry, both neural predictors of persistent illness and neural predictors of treatment response have been identified through patterns of neural activity and neural connectivity. By studying neural predictors of outcome in AN, this study addresses a critical gap in knowledge about the treatment of AN. This developmental study will leverage an existing clinical trial providing relapse prevention treatment for AN for individuals with AN who normalized weight as inpatients in our treatment program. The intervention, Relapse Prevention and Changing Habits (REACH+), targets habitual control of maladaptive behavior, especially restriction of food intake. REACH+ compares different versions of cognitive and behavioral psychotherapeutic interventions in a randomized design. The proposed R21 will acquire fMRI data from patients hospitalized for AN who have achieved full weight restoration, prior to starting REACH+ treatment. To identify neural predictors of outcome, we will acquire fMRI activity during a task with established utility in capturing the maladaptive restriction that predicts relapse in AN (Food Choice Task) as well as functional connectivity at rest. We will test whether these neural markers predict weight slope after hospital discharge, an established marker of longer-term outcome, to test for biomarkers of relapse. In addition, we will acquire fMRI activity during a cognitive control task with established utility in predicting response to cognitive behavior therapy (in non-AN populations). We will explore whether individual differences in cognitive control-related activity, as well as other patterns of resting state connectivity, moderate response to variations in behavioral and cognitive interventions included in REACH+. By evaluating how neural activity predicts outcome, this work is responsive to the NIMH call for the development of clinically relevant biomarkers of recovery and relapse in AN. This study will establish new avenues for research in personalized medicine in AN.
神经性厌食症(AN)是一种具有显著发病率和死亡率的毁灭性精神疾病, 急性治疗后复发率为40-80%。严格限制食物摄入是 行为障碍的疾病,并赋予显着更大的风险复发。疾病是由A 对治疗反应的异质性过程和临床预测因子在很大程度上是未知的。适应不良 AN中的行为具有暗示习惯性控制的行为和神经特征。然而,基于大脑的因素 与长期结果和治疗反应的关系尚未研究。在精神病学的其他领域, 已经通过以下方法确定了持续性疾病的神经预测因子和治疗反应的神经预测因子: 神经活动和神经连接的模式。通过研究AN结局的神经预测因素,本研究 解决了关于AN治疗知识的关键空白。 这项开发性研究将利用现有的临床试验,为AN提供复发预防治疗 对于在我们的治疗计划中体重正常化的AN患者。干预, 复发预防和改变习惯(REACH+),目标是习惯性控制适应不良行为, 特别是限制食物摄入。REACH+比较了不同版本的认知和行为 随机设计的心理治疗干预。 拟议中的R21将从因AN住院的已达到全体重的患者中获取fMRI数据 在开始REACH+治疗之前进行恢复。为了确定神经预测结果,我们将获得功能磁共振成像, 在一项任务中的活动,在捕获预测AN复发的适应不良限制方面具有既定的效用 (Food选择任务)以及休息时的功能连接。我们将测试这些神经标记是否能预测 出院后的体重斜率,一个确定的长期结果的标志物,以测试 复发此外,我们将在认知控制任务中获得功能磁共振成像活动, 预测对认知行为疗法的反应(在非AN人群中)。我们将探讨个体是否 认知控制相关活动以及其他静息状态连接模式的差异,中度 对REACH+中包含的行为和认知干预变化的反应。通过评估神经系统 活动预测结果,这项工作是响应NIMH呼吁发展临床相关的 AN康复和复发的生物标志物。这项研究将为个性化研究建立新的途径。 医学在AN

项目成果

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Alexandra Felicia Muratore其他文献

Alexandra Felicia Muratore的其他文献

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{{ truncateString('Alexandra Felicia Muratore', 18)}}的其他基金

Deciphering the Neural Mechanisms of Restrictive Eating in Anorexia Nervosa Using Repetitive Transcranial Magnetic Stimulation
使用重复经颅磁刺激破译神经性厌食症限制饮食的神经机制
  • 批准号:
    10704120
  • 财政年份:
    2022
  • 资助金额:
    $ 25.33万
  • 项目类别:
Deciphering the Neural Mechanisms of Restrictive Eating in Anorexia Nervosa Using Repetitive Transcranial Magnetic Stimulation
使用重复经颅磁刺激破译神经性厌食症限制饮食的神经机制
  • 批准号:
    10525743
  • 财政年份:
    2022
  • 资助金额:
    $ 25.33万
  • 项目类别:

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