Neural and Molecular Mechanisms Underlying Stress-Induced Inflammatory Responses

压力诱发炎症反应的神经和分子机制

• 批准号: 10185562
• 负责人: Keely Ann Muscatell
• 金额: $ 62.19万
• 依托单位: UNIV OF NORTH CAROLINA CHAPEL HILL
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10185562
• 关键词: Acute; Adrenergic Agents; Adrenergic beta-Antagonists; Affective; American; Amygdaloid structure; Anterior; Atherosclerosis; Biological; Biological Assay; Blood specimen; Brain; Brain region; Cardiac; Cardiovascular Diseases; Cessation of life; Clinical Trials; Computing Methodologies; Data; Development; Dose; Double-Blind Method; Drug usage; Economic Burden; Etiology; Event; Functional Magnetic Resonance Imaging; Future; Gene Expression; Goals; Graph; Human; Inflammation; Inflammatory; Inflammatory Response; Insula of Reil; Interleukin-6; Intervention; Knowledge; Lead; Light; Link; Machine Learning; Maps; Mathematics; Measures; Medial; Mediating; Mediator of activation protein; Molecular; Network-based; Outcome; Pathology; Pathway Analysis; Pathway interactions; Pattern; Pattern Recognition; Pharmacology; Placebos; Play; Procedures; Propranolol; Proteins; Psychological Stress; Psychoneuroimmunology; Randomized; Research; Risk; Risk Factors; Role; Scanning; Shapes; Signal Pathway; Signal Transduction; Stress; Techniques; Testing; Time; Up-Regulation; Work; analytical tool; attenuation; beta-adrenergic receptor; cardiovascular disorder risk; computational neuroscience; cytokine; double-blind placebo controlled trial; economic cost; economic impact; health economics; inflammatory marker; innovation; neural circuit; neural patterning; neuroimaging; neuromechanism; novel; preclinical study; prevent; relating to nervous system; response; social; social genomics; stress reactivity; stressor; tool

PROJECT SUMMARY/ABSTRACT Cardiovascular disease (CVD) is the number one killer of Americans, and also causes significant economic costs to the nation. Thus, understanding the mechanisms through which CVD develops is of paramount importance if we are to successfully identify those at risk for CVD, and intervene to ultimately prevent CVD-related death and economic impact. Psychological stress reactivity has long been appreciated as a risk factor for negative CVD- related outcomes, and recent work suggests that inflammatory reactivity to stress is a critical biological mechanism through which stress increases risk for CVD. However, there are significant gaps in our current knowledge regarding the neural predictors and molecular pathways through which stress leads to inflammation. These knowledge gaps are critical to fill if we are to develop a full mechanistic understanding of how stress leads to CVD risk, and may also shed light on future intervention targets. Thus, the present project will use cutting- edge computational methods to identify neural signatures of stress-related inflammatory reactivity, and will use pharmacological tools to block an important stress-signaling pathway (i.e., beta-adrenergic signaling) and examine its effects on neural and inflammatory reactivity to stress. Study 1 (N=100) will use fMRI to examine neural responses to a social evaluative stress task, with blood samples taken before and after the stressor assayed for pro-inflammatory gene expression and circulating inflammatory proteins. We will use innovative multivariate machine learning analytic techniques to identify the neural patterns that predict changes in inflammation, as well as network-based analytic tools from mathematics to examine how large-scale brain networks change configuration in response to stress in ways that are linked to inflammation. In Study 2 (N=120), we will conduct a mechanistic, randomized, double-blind, placebo-controlled trial of the beta-adrenergic receptor blocker propranolol to examine how blocking beta-adrenergic signaling impacts neural and inflammatory responses to the social evaluative stress task. Together, these two studies will allow us to establish the neural signatures of stress-induced increases in inflammation (Aim 1), determine the effects of beta-adrenergic signaling on neural responses to stress (Aim 2), and examine the neural mediators of beta-adrenergic related attenuations in stress-related inflammatory reactivity (Aim 3). In doing so, this project will ultimately help identify neural signatures of risk for stress-related inflammation, as well as novel targets for future intervention to ameliorate the impact of stress on the brain and body and reduce the health and economic burden of CVD.

项目摘要/摘要 心血管疾病（CVD）是美国人的第一杀手，也导致巨大的经济成本 到国家。因此，了解CVD开发的机制是至关重要的。 我们将成功识别有CVD风险的人，并干预以最终防止与CVD相关的死亡和 经济影响。长期以来，心理压力反应性被认为是负CVD负的危险因素 相关的结果，最近的工作表明，炎症对压力的反应性是关键的生物学 压力增加CVD风险的机制。但是，我们的当前存在很大的差距 关于压力导致炎症的神经预测因子和分子途径的知识。 如果我们要对压力的领导方式建立充分的机械理解，这些知识差距对于填补至关重要 CVD风险，也可能阐明将来的干预目标。因此，本项目将使用替代 边缘计算方法以识别与压力相关的炎症反应性的神经特征，并将使用 阻止重要应力信号途径（即β-肾上腺素能信号传导）和 检查其对压力的神经和炎症反应性的影响。研究1（n = 100）将使用fMRI检查 对社会评估压力任务的神经反应，并在压力源之前和之后进行血样 分析促炎基因表达和循环炎症蛋白。我们将使用创新 多元机器学习分析技术，以识别预测变化的神经模式 炎症以及基于网络的分析工具从数学学院检查大脑的大脑 网络以与炎症有关的方式改变了压力的配置。在研究2（n = 120）中， 我们将进行β-肾上腺素能受体的机械，随机，双盲，安慰剂对照试验 阻断剂普萘洛尔检查阻塞β-肾上腺素能信号如何影响神经和炎症 对社会评估压力任务的响应。这两项研究一起将使我们能够建立神经 压力引起的炎症增加的特征（AIM 1）确定β-肾上腺素能的影响 对胁迫的神经反应的信号（AIM 2），并检查β-肾上腺素相关的神经介体 与压力相关的炎症反应性的衰减（AIM 3）。这样，这个项目最终将有助于确定 与压力相关炎症风险的神经特征，以及未来干预的新目标 缓解压力对大脑和身体的影响，并减轻CVD的健康和经济负担。