Integrating spatial multi-omics and clinical covariates to identify mechanisms of disease in ALS-FTD

肌萎缩侧索硬化症(ALS)和额颞部痴呆(FTD)是致命且无法治疗的疾病的一部分 通过中枢神经系统TDP-43聚集的不同表现而统一的疾病谱 (CNS)组织。高达50%的运动功能障碍患者还存在认知障碍，15%的患者有 Frank FTD，但不同临床和病理表现背后的分子机制仍然 人们对此知之甚少。在我们最近的工作中，我们已经证明了爱丁堡ALS认知和行为屏幕 (ECAs)是一个很好的运动外TDP-43病理的临床预测指标。具体地说，ECAS子域得分 与TDP-43包涵体在受影响认知的脑区的分布有关 域名。然而，TDP-43病理在一个区域的存在并不能预测相关的认知缺陷。 在那个地区。我们假设，可能还有其他更敏感的神经病理因素与认知 尚未确定的受累情况，并假设其他病理特征--包括 核质蛋白定位错误、基因表达紊乱和细胞-细胞功能障碍 交互作用--可能与对应于特定领域的认知障碍更密切相关 额叶皮质的区域。我们将通过一个全面的多元经济学分析来检验这一假说。 身体组织，识别1)细胞类型特定亚群和细胞间相互作用的差异 ALS-FTD病例和对照之间与蛋白质聚集和错位的关系以及2)这些 差异与ALS-FTD的认知障碍有关。我们将使用空间分辨率来实现这些目标 蛋白质组学(AIM 1)和转录组(AIM 2)测量分析临床病理分层 背外侧前额叶皮质组织样本(特别是Brodmann区BA44和BA46) 受损的ALS患者和年龄/性别匹配的对照组。通过使用多种方法的组合来 同时定位所有相互作用的细胞亚群的空间转录组和蛋白质组 区域，我们的目标是阐明细胞间和细胞内活动的起源和时间动力学，这些活动可能 揭示新的诊断和治疗目标。我们之前已经实现了空间转译(ST) 以确定不同细胞类型的亚群内的区域差异 疾病动力学的作用。这些数据将直接与病理指标(例如，病因学)相关联 包裹体)。为了集成和分析跨医疗设备的数据之间的关系，我们将开发一种 协调分析疾病负担的多模式、多经济措施的计算框架(目标 2)。最后，我们将实施高度多元化的免疫成像，以验证我们在独立的ALS- FTD队列(目标3)。我们跨实验模式(单细胞RNA序列、空间模式)的综合分析 转录学、多路成像和蛋白质组学)将产生前所未有的疾病病理学和 阐明在不同细胞群体内和之间协调的神经营养和神经毒性功能。

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are part of a fatal and untreatable disease spectrum that is unified by a diverse presentation of TDP-43 aggregation across central nervous system (CNS) tissue. Up to 50% of patients with motor dysfunction also present with cognitive deficits and 15% have frank FTD, but the molecular mechanisms underlying diverse clinical and pathological presentations remain poorly understood. In our recent work, we have shown that the Edinburgh Cognitive and Behavioural ALS Screen (ECAS) is a good clinical predictor of extra-motor TDP-43 pathology. Specifically, ECAS subdomain scores correlate with the distribution of TDP-43 inclusions in brain regions corresponding to the affected cognitive domains. However, the presence of TDP-43 pathology in a region is not predictive of cognitive deficits associated with that region. We posit that there may be other, more sensitive, neuropathological correlates of cognitive involvement that remain to be identified, and hypothesize that additional pathological features--including nucleocytoplasmic protein mislocalization, perturbations in gene expression, and dysfunctional cell-cell interactions--may correlate more closely with domain-specific cognitive impairment corresponding to a particular region of the frontal cortex. We will test this hypothesis through a comprehensive multi-omic analysis of post- mortem tissue that identifies 1) how differences in cell type-specific subpopulations and intercellular interactions between ALS-FTD cases and controls relate to protein aggregation and mislocalization and 2) how these differences relate to cognitive impairment in ALS-FTD. We will accomplish these goals using spatially resolved proteomic (Aim 1) and transcriptomic (Aim 2) measurements to analyze clinico-pathologically stratified dorsolateral prefrontal cortical tissue samples (specifically, Brodmann areas BA44 and BA46) from cognitively impaired ALS patients and age/gender matched 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. We have previously implemented Spatial Transcriptomics (ST) on the spinal cord to identify regional differences within subpopulations of various cell types that vary as a function of disease dynamics. These data will be directly tied to measures of 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 disease burden (Aim 2). Finally, we will implement highly multiplexed immuno-imaging to validate our findings in an independent ALS- FTD cohort (Aim 3). Our integrated analysis across experimental modalities (single cell RNA-seq, spatial transcriptomics, multiplexed imaging and proteomics) will yield an unprecedented view of disease pathology and elucidate neurotrophic and neurotoxic functions that are coordinated within and across different cell populations.