Clarifying the overlapping pathology of delirium and dementia

项目概要/摘要 痴呆症是美国第六大死因，与生活质量下降和 独立性；它无法预防、治愈，甚至减缓。谵妄是一种突然的混乱状态 与发病率和死亡率增加以及长期认知受损有关。虽然有 谵妄和痴呆这两种疾病都会造成巨大的经济、社会和个人成本 治疗，很大程度上是由于对其发病机制的了解有限。双向倾向 痴呆和谵妄相互提供了一个独特的机会来了解它们重叠的病理学 机制并确定新的治疗方法。例如，容易出现谵妄和痴呆症， 由淀粉样蛋白沉积表示，与额叶α功率增加相关，表明类似的变化 在这两种情况出现之前，大脑动力学的变化就很明显。皮质慢波活动（SWA）是一种共享的 衰老、谵妄和痴呆认知变化的电生理标志。我们建议 了解清醒状态下的 SWA 会影响所有这些条件，将带来新颖的、相互信息丰富的结果 深入了解这些病症的发病机制。我们的总体假设是谵妄是由 炎症与两种关键的痴呆病理学（淀粉样蛋白和淀粉样蛋白）之间的相互作用 神经退行性变，导致皮质 SWA 电生理紊乱并受损 连接性，导致谵妄。在此应用中，我们将测试淀粉样蛋白和神经变性如何 容易出现（具体目标 1），并因（具体目标 3）谵妄发作而加剧。我们还将 通过以下方式研究炎症诱导谵妄、SWA 和连接变化的机制作用 与淀粉样蛋白病理学和神经变性的相互作用（具体目标 2）。这样我们就可以明白如何 谵妄与两种痴呆症病理的轨迹相互作用，同时了解 SWA 是如何发生的，因此 谵妄的认知变化，可以如此突然地出现。我们的技术创新是采用256通道高 密度脑电图（HD-EEG）跟踪行为的电生理变化。我们将来源 使用最先进的电极数字化技术将 SWA 重建为个体受试者解剖结构，以允许 SWA 与受试者的磁共振成像 (MRI) 或正电子发射断层扫描的对应关系 (PET) 淀粉样蛋白数据。绘制病理学的空间重叠是我们的方法创新，它增强了 任何关系的生物学合理性。我们将追踪谵妄如何导致神经病理变化 这可能是手术后认知能力下降的原因。我们的数据将阐明病理重叠 谵妄和痴呆，强调 (i) 淀粉样蛋白筛查/新生物标志物终点的新途径 病理学或谵妄的风险（额叶阿尔法能量）和（ii）针对机制的治疗开发 理解皮质 SWA 作为这些认知变化的基础。

Project Summary/Abstract Dementia is the sixth leading cause of death in the United States and is associated with loss of quality of life and independence; it cannot be prevented, cured, or even slowed. Delirium is a sudden state of confusion that is associated with increased morbidity and mortality and impaired long-term cognition. Although there are substantial costs to both conditions – financial, societal and individual – delirium and dementia are bereft of therapies, largely due to the limited understanding of their pathogeneses. The bidirectional predisposition of dementia and delirium to each other offers a unique opportunity to understand their overlapping pathological mechanisms and to identify new therapeutic approaches. For example, predisposition to delirium and dementia, denoted by amyloid deposition, is associated with increased frontal alpha power, suggesting that similar changes in brain dynamics are evident before the onset of either condition. Cortical slow wave activity (SWA) is a shared electrophysiological hallmark of cognitive changes in aging, delirium and dementia. We propose that understanding SWA in wakefulness, which affects all these conditions, will lead to novel, mutually informative insights into the pathogenesis of those conditions. Our overarching hypothesis is that delirium results from an interaction between inflammation and two key dementia pathologies, amyloid and neurodegeneration, leading to the electrophysiological disturbance of cortical SWA and impaired connectivity, which results in delirium. In this application, we will test how amyloid and neurodegeneration predispose to (Specific Aim 1) and are exacerbated by (Specific Aim 3) an episode of delirium. We will also investigate the mechanistic role of inflammation to induce delirium, SWA, and connectivity changes through interaction with amyloid pathology and neurodegeneration (Specific Aim 2). In this way, we can understand how delirium interacts with the trajectory of two dementia pathologies, while understanding how SWA, and therefore the cognitive changes of delirium, can arise so abruptly. Our technical innovation is to use 256 channel high- density electroencephalogram (HD-EEG) to track the electrophysiological changes with behavior. We will source reconstruct the SWA to individual subject anatomy using state-of-the-art electrode digitization to allow correspondence of the SWA to a subject's magnetic resonance imaging (MRI) or positron emission tomography (PET) amyloid data. Mapping spatial overlap in pathologies is our methodological innovation, which enhances biological plausibility for any relationship. We will track how delirium contributes to neuropathological changes that may account for the cognitive decline after surgery. Our data will illuminate the pathological overlap of delirium and dementia, highlighting (i) new avenues for screening/novel biomarker endpoints for amyloid pathology or risk of delirium (frontal alpha power) and (ii) therapeutic development targeted to a mechanistic understanding of cortical SWA as an underpinning for those cognitive changes.