Neural and Molecular Mechanisms Underlying Stress-Induced Inflammatory Responses

项目概要/摘要 心血管疾病（CVD）是美国人的头号杀手，也造成了巨大的经济损失 对国家的贡献因此，了解CVD发展的机制至关重要， 我们要成功地识别那些有CVD风险的人，并进行干预，最终预防CVD相关的死亡， 经济影响。长期以来，心理应激反应一直被认为是负性CVD的危险因素- 最近的研究表明，对压力的炎症反应是一种关键的生物学反应， 压力增加CVD风险的机制。然而，我们目前的差距很大， 关于神经预测因子和应激导致炎症的分子途径的知识。 如果我们要对压力如何导致的问题有一个完整的机械的理解，这些知识缺口是至关重要的， 心血管疾病的风险，也可能揭示未来的干预目标。因此，本项目将使用切割- 边缘计算方法，以确定神经签名的压力相关的炎症反应，并将使用 阻断重要的应激信号传导途径的药理学工具（即，β-肾上腺素能信号传导）和 检查它对神经和炎症反应的影响。研究1（N=100）将使用fMRI检查 神经反应的社会评价压力任务，与血液样本采取之前和之后的压力 测定促炎基因表达和循环炎性蛋白。我们将使用创新的 多变量机器学习分析技术，以识别预测神经元变化的神经模式。 炎症，以及基于网络的分析工具，从数学来研究如何大规模的大脑 神经网络会改变结构以应对压力，这种方式与炎症有关。在研究2（N=120）中， 我们将对β-肾上腺素能受体进行一项机制性、随机、双盲、安慰剂对照试验， 阻断剂普萘洛尔检查阻断β-肾上腺素能信号传导如何影响神经和炎症 对社会评价压力任务的反应。这两项研究将使我们能够建立神经系统 压力诱导的炎症增加的特征（目的1），确定β-肾上腺素能受体的作用。 信号对应激神经反应的影响（目的2），并检查β-肾上腺素能相关的神经介质 减轻应激相关的炎症反应性（目的3）。通过这样做，该项目将最终帮助确定 压力相关炎症风险的神经特征，以及未来干预的新目标， 减轻压力对大脑和身体的影响，减轻心血管疾病的健康和经济负担。

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.