Brain-Behavior Markers of Emotion in Depressed Mothers and Their Daughters

抑郁母亲及其女儿的大脑行为情绪标记

• 批准号: 9750809
• 负责人: Katie L Burkhouse
• 金额: $ 19.09万
• 依托单位: UNIVERSITY OF ILLINOIS AT CHICAGO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9750809
• 关键词: Address; Affect; Affective; Age; Amygdaloid structure; Behavior; Behavioral; Behavioral Mechanisms; Biological; Brain; Chicago; Child; Chronic; Corpus striatum structure; Coupled; Data; Daughter; Depressed mood; Development; Ecological momentary assessment; Emotional; Emotions; Environment; Exhibits; Face; Family; Female; Foundations; Functional Magnetic Resonance Imaging; Future; Goals; Illinois; Individual; Laboratories; Life; Link; Major Depressive Disorder; Measures; Mental Depression; Mentorship; Methodology; Methods; Mothers; Motivation; Mydriasis; Onset of illness; Parents; Peripheral; Phenotype; Population; Prevention; Preventive Intervention; Protocols documentation; Psychiatry; Psychopathology; Recording of previous events; Recurrence; Regulation; Research; Rewards; Risk; Risk Factors; Risk Marker; Sampling; Statistical Models; Stimulus; Testing; Time; Training; Universities; Work; Youth; affective neuroscience; behavior measurement; brain behavior; career; child depression; clinically significant; depressive symptoms; design; disorder risk; emerging adult; experience; flexibility; follow-up; girls; high risk; high risk population; imaging study; intergenerational; longitudinal analysis; longitudinal design; maternal depression; multilevel analysis; negative affect; neural circuit; neurobehavioral; neuromechanism; offspring; prevent; programs; prospective; recruit; relating to nervous system; response; social; transmission process

Daughters of depressed mothers are at extremely high risk (HR) for developing major depressive disorder (MDD) by early adulthood. To develop more targeted, mechanistic prevention efforts for this HR population, it is essential to clarify the familial mechanisms implicated in this risk. Prior studies suggest that a dysfunctional neural circuit characterizes HR offspring during negative social-emotional and motivational processing. Despite replicable findings documenting this effect, it is not clear whether disrupted neural circuit activation among HR offspring mirrors that of their depressed mothers, representing a neural signature of depression risk that is transmitted from the mother to the daughter. It is also largely unknown if and how this neural signature relates to reactivity and regulation of affect in the real world, which is key to understanding its clinical significance and identifying brain-behavior targets for prevention and intervention. In the current K23 application, the candidate proposes to examine neurobehavioral markers of social-emotional and motivational processing in a sample of 40 mothers with a history of recurrent MDD (rMDD) and their non-MDD, HR daughters (ages 13-16), and 40 mothers with no history of psychopathology and their non-MDD, low risk (LR) daughters. By combining neural and behavioral measures with a longitudinal design, the candidate will test whether neural regions implicated in negative social- emotional and motivational processing (a) differentiate HR from LR dyads and are concordant between mothers and their daughters, representing a familial risk marker, (b) are predictive of offspring’s behavioral ratings of affective processing outside of the laboratory using Ecological Momentary Assessment (EMA), and (c) are associated with the trajectory of offspring’s depressive symptoms over a multi-wave follow-up. In the current proposal, the candidate seeks to build upon her strong foundation in multiple levels of analysis to study affective processing and youth depression risk by gaining additional training in three new domains: 1) Developmental affective neuroscience and functional magnetic resonance imaging (fMRI) methodology, 2) Ecological momentary assessment (EMA), and 3) Advanced statistical modeling for nested, multi-method, longitudinal data. The Department of Psychiatry at the University of Illinois at Chicago is an outstanding environment in which to engage in interdisciplinary training. The candidate's mentorship team (Drs. Phan, Keenan, and Mermelstein) and consultant team (Drs. Hedeker and Gotlib) have extensive experience in developmental affective neuroscience methods (including fMRI), longitudinal high risk designs, use of EMA methods, and statistical expertise in multilevel and longitudinal analyses. The proposed study will inform the design of larger R01 studies examining whether neural and behavioral mechanisms of risk can be altered to prevent the development of depression in HR offspring. This study coupled with completion of the identified training goals will effectively propel the candidate towards establishing an independent program of research focused on identifying behavioral-brain risk phenotypes and preventative interventions for youth depression.

沮丧的母亲的女儿患有严重抑郁症（MDD）的风险极高（HR） 成年初。为了为该人力资源人群开发更多针对性的预防机械预防工作，这是必不可少的 阐明在这种风险中实施的家庭机制。先前的研究表明功能失调的神经回路 在负面的社会情感和动机处理过程中表征人力资源后代。尽管可复制 调查结果文档此效果，尚不清楚HR后代的神经回路激活是否破坏 反映了他们沮丧的母亲，代表抑郁症风险的神经信号 从母亲到女儿。这也很大程度上未知，该神经特征与反应性如何相关 和对现实世界中影响的调节，这是理解其临床意义和识别的关键 大脑行为预防和干预目标。在当前的K23应用程序中，候选 在40个母亲的样本中检查社会情感和动机处理的神经行为标记 具有复发性MDD（RMDD）及其非MDD，HR女儿（13-16岁）的历史 没有心理病理学的史及其非MDD，低风险（LR）女儿。通过结合神经和行为 通过纵向设计的措施，候选人将测试是否以负面社会的方式实施中性地区 情感和动机处理（a）将人力资源与LR二元组区分开，并且是母亲之间的一致性 以及代表家庭风险标记的女儿（b）可以预测后代的行为评级 使用生态瞬时评估（EMA）和（c）在实验室之外的情感处理是 与后代的抑郁症状轨迹相关。在电流中 提案，候选人试图在多个分析中以她的坚强基础为基础，以研究情感 加工和青年抑郁症风险通过在三个新领域获得额外的培训来风险：1）发展 情感神经科学和功能磁共振成像（fMRI）方法，2）生态学 瞬时评估（EMA）和3）嵌套，多方法，纵向数据的高级统计建模。 芝加哥伊利诺伊大学精神病学系是一个杰出的环境 进行跨学科培训。候选人的Mentalship团队（Phan博士，Keenan和Mermelstein）和 顾问团队（Hedeker博士和Gotlib博士）在发展情感神经科学方面拥有丰富的经验 方法（包括fMRI），纵向高风险设计，使用EMA方法以及统计专业知识 多级和纵向分析。拟议的研究将告知大型R01研究的设计 是否可以改变风险的神经元和行为机制，以防止抑郁的发展 人力资源部后代。这项研究加上确定的培训目标的完成将有效推动 候选人建立一个独立的研究计划，重点是确定行为 - 脑风险 对青年抑郁症的表型和预防干预措施。