Spatially Resolved Dynamics of Molecular Pathology and Intercellular Interactions in Amytrophic Lateral Sclerosis

项目摘要 肌萎缩侧索硬化症（ALS）是一种破坏性的进行性神经退行性疾病， 上（初级运动皮层，M1）和下（脊髓，SC）运动神经元（MN）最终导致总 瘫痪ALS中的MN损失涉及多种细胞类型中的细胞自主和非细胞自主活动， M1和SC，它们的组织是很好理解的。然而，我们仍然有四个主要差距， 知识：1）M1的各种细胞类型中ALS相关的分子病理学如何与M1中的那些细胞类型相关。 2）特定细胞类型的亚群在这两个区域中的空间排列方式; 3） 不同细胞类型的亚群被组织在更高阶的集合中;以及4）如何协调 这些集合的行为涉及疾病相关的分子病理学（例如，病征 内含物）。为了解决这些问题，我们建议开发一个空间分辨的多组学 ALS患者和健康对照的M1和SC中的细胞亚群目录。通过使用 同时绘制所有相互作用的空间转录组和蛋白质组的方法的组合 在这些地区的细胞亚群，我们的目的是阐明起源和时间动态的间和 细胞内活性，可能揭示新的诊断和治疗ALS的目标。我们的总体 假设ALS病理源于功能失调的MN-神经胶质相互作用，并且这可以预见地不同于 在M1和SC中，根据患者病理学。为了解决这个问题，我们建议使用 空间分辨转录组学和蛋白质组学测量研究完整的人类死后组织， 按临床表现分层的患者（即，最初症状出现的部位，延髓或下肢）。我们有 先前在小鼠和人类SC上实施的空间转录组学，以确定 不同细胞类型的亚群作为疾病动力学的函数而变化。在此，我们建议 我们现有的人类研究，并首次开发出大规模的空间分辨多组学数据集， 匹配的人死后M1和SC样本中的疾病背景（目的1），以实现同时 在完整组织的背景下探索上和下运动神经元。这些数据将直接与 ALS病理学的测量（例如，特异性内含物）。整合和分析 跨模态的数据，我们将开发一个计算框架，用于协调分析多模态，多模态， ALS疾病负担的经济学指标（目标2）。最后，我们将实现高度多重免疫成像， 在单细胞水平原位验证目标1中产生的最佳候选基因（目标3）。我们希望获得一个 在死后ALS M1和SC中细胞相互作用的无与伦比的观点，并且能够直接将这种相互作用联系起来。 与原位ALS病理学特征的相互作用。这将使我们能够识别出导致基因突变的失调信号， ALS患者的上、下运动神经元缺失及相关症状。

Project Abstract Amyotrophic lateral sclerosis (ALS) is a devastating progressive neurodegenerative disease in which the loss of upper (primary motor cortex, M1) and lower (spinal cord, SC) motor neurons (MNs) ultimately leads to total paralysis. MN loss in ALS involves cell autonomous and non-cell autonomous activities in multiple cell types of the M1 and SC, the organization of which are well understood. However, there remain 4 major gaps in our knowledge: 1) How ALS-associated molecular pathology in the various cell types of the M1 relates to those in the SC; 2) How subpopulations of specific cell types are spatially arranged in these two regions; 3) How subpopulations of different cell types are organized in higher-order ensembles; and 4) How the coordinated behavior of these ensembles relates to disease-associated molecular pathology (e.g., pathognomonic inclusions). Towards addressing these questions, we propose to develop a spatially resolved multi-omics catalog of cellular subpopulations in the M1 and SC of patients with ALS and healthy controls. By using a combination of approaches to simultaneously map the spatial transcriptome and proteome of all interacting cellular subpopulations in these regions, our aim is to elucidate the origins and temporal dynamics of inter- and intra-cellular activities that may reveal novel diagnostic and therapeutic targets for ALS. Our overarching hypothesis is that ALS pathology stems from dysfunctional MN-glial interactions, and that this predictably differs in the M1 and SC in accordance with patient symptomatology. To address this hypothesis, we propose to use spatially resolved transcriptomic and proteomic measurements to study intact human postmortem tissue from patients stratified by clinical presentation (i.e., site of initial symptom presentation, bulbar or lower limb). We have previously implemented Spatial Transcriptomics on mouse and human SC to identify regional differences within subpopulations of various cell types that vary as a function of disease dynamics. Here, we propose to build upon our existing human study, and for the first time, develop a spatially resolved multi-omics dataset at scale and in the context of disease in matched human postmortem M1 and SC samples (Aim 1), to enable simultaneous exploration of upper and lower motor neurons in the context of intact tissue. These data will be directly tied to measures of ALS pathology (e.g., pathognomonic inclusions). To integrate and analyze relationships between data across modalities, we will develop a computational framework for harmonized analysis of multi-modal, multi- omic measures of ALS disease burden (Aim 2). Finally, we will implement highly multiplexed immuno-imaging to validate top gene candidates generated in Aim 1 at a single-cell level in situ (Aim 3). We expect to obtain an unmatched view of cellular interactions in the postmortem ALS M1 and SC, and to be able to directly link such interactions to features of ALS pathology in situ. This will allow us to identify dysregulated signaling that drives upper and lower motor neuron loss and associated symptoms in patients in ALS.