The intersection of GLP-1, gut microbiota, and brain connectivity in prodromal Alzheimer’s disease

项目摘要： 阿尔茨海默病（AD）的早期识别对于预防或延迟疾病发作至关重要。有 目前没有有效的治疗AD的方法，这可能是由于多种潜在的原因。安装 有证据支持这样的观点，即AD部分是一种具有一系列代谢紊乱的代谢性疾病 在疾病早期，甚至在典型前驱期，即遗忘型轻度认知障碍（aMCI）。 动物模型表明，肠道和神经肽胰高血糖素样肽-1（GLP-1）是一个有前途的联系， AD的肠-脑轴，尽管这种外周-中枢通路尚未在AD中定义。我们提出了一个 前驱AD的新型肠-GLP-1相互作用组。我们假设肠道特异性细菌菌株会影响 GLP-1水平并产生影响aMCI患者脑连接模式的小代谢产物。 我们将在两个具体目标中检验这一科学前提。在目标1中，我们将确定 与年龄匹配对照相比，aMCI中的GLP-1水平和默认模式网络（DMN）连接模式 同伙我们将采用严格的方法学设计来测量餐前和餐后GLP-1水平 并使用最先进的功能性MRI方法评估DMN连接模式。目标2： 确定aMCI和对照中与DMN连接模式相关的细菌菌株和代谢物 组我们将对在相似时间从同一个人收集的粪便样本进行宏基因组测序。 在AIM 1中评估的个人。我们将鉴定可能影响GLP-1水平的细菌基因。代谢 标记将与DMN连接模式相关。总之，这些目标将阐明细菌 前驱AD疾病状态中的代谢生物标志物，其可负面影响GLP-1水平或活性， 影响大脑功能我们将使用这里收集的数据启动一项纵向研究， 代谢和神经成像数据的进展沿着已知的AD病理生物标志物，例如β- 淀粉样蛋白和tau蛋白。我们的目标是确定特定的细菌菌株及其代谢特性， 从正常认知老化到aMCI再到AD的转变。

Project Summary: Early identification of Alzheimer's disease (AD) is essential for preventing or delaying disease onset. There is currently no effective treatment for AD, which may be attributable to multiple underlying causes. Mounting evidence supports the notion that AD is, in part, a metabolic condition with an array of metabolic perturbations early in the disease, even at the prototypical prodromal stage, i.e. amnestic mild cognitive impairment (aMCI). Animal models indicate that gut- and neuropeptide Glucagon like peptide-1 (GLP-1) is a promising link within the gut-brain axis of AD, although this peripheral-central pathway has yet to be defined in AD. We propose a novel gut-GLP-1 interactome of prodromal AD. We hypothesize that gut specific bacterial strains will influence GLP-1 levels and produce small metabolites that influence brain connectivity patterns in patients with aMCI. We will test this scientific premise in two Specific Aims. In Aim 1, we will determine the relationship between GLP-1 levels and default mode network (DMN) connectivity patterns in aMCI compared to age-matched control cohorts. We will apply rigorous methodological design to measure pre- and post- meal testing GLP-1 levels and assess DMN connectivity patterns using a cutting-edge functional MRI method. In Aim 2, we seek to determine bacterial strains and metabolites associated with DMN connectivity patterns in aMCI and control groups. We will conduct metagenomic sequencing on stool samples collected at similar times from the same individuals assessed in Aim1. We will identify bacterial genes with potential to impact GLP-1 levels. Metabolic markers will be correlated with DMN connectivity patterns. Together, these Aims will elucidate bacterial metabolic biomarkers in a prodromal AD disease state that can negatively affect GLP-1 levels or activity to affect brain functioning. We will use the data collected here to initiate a longitudinal study to follow the progression of metabolic and neuroimaging data along with known AD pathologic biomarkers such as beta- amyloid and tau. Our goal is to determine the specific bacterial strains and their metabolic properties that drive the transition from normal cognitive aging to aMCI to AD.