Characterizing Shared Features of Innate Immune Cells across Neurodegenerative Diseases using Single Cell Expression and Chromatin Accessibility Data

由于几乎没有有效的干预措施，超过1000万患者受到影响，神经退行性疾病是 一个密集的基础科学和临床研究领域。全基因组关联研究（Genome Wide Association Studies，GWAS） 神经生物学家已经发现了许多与免疫基因相关的风险变异， 神经退化的炎症基础在退行性疾病，如阿尔茨海默病 (AD)和进行性多发性硬化症（MS），应用于单细胞数据集的计算技术， 确定免疫细胞在驱动大脑病理变化中的作用。例如，最近的单细胞 在AD中的表达研究已经鉴定了一种新类型的疾病相关小胶质细胞（DAM）， 这种疾病我对从视网膜组织中产生的单细胞表达数据进行了初步分析， 患有AMD相关黄斑变性（AMD）的患者在AMD中重现了这种DAM表型。 衍生的小胶质细胞。此外，分析显示，AMD衍生的星形胶质细胞驱动新血管形成， AMD的病理标志，通过VEGF的表达增加。这些发现意味着 AMD中的神经变性和病理变化是由先天免疫细胞驱动的，并且，进一步地，这些免疫细胞是由先天免疫细胞驱动的。 先天免疫细胞的功能在神经退行性疾病中可能是相似的。我假设先天的 免疫细胞功能和调节驱动病理是共享的神经退行性疾病 条件为了确定这些共同的特点，我将设计和应用新的计算算法，以单一的 来自多种神经退行性疾病- AMD，AD和MS -的细胞数据集，以阐明先天性 免疫细胞在不同条件下的反应在目标1中，我将应用一个粗粒度算法，扩散凝聚， 以所有粒度水平群集细胞，以识别单个细胞中的病理性小胶质细胞和星形胶质细胞亚群 从AMD患者的视网膜组织产生的表达数据。我将进一步将这种技术应用于子集 这些先天免疫细胞在MS和AD中的公开可用的单细胞表达数据集中， 基因模块在疾病中的小胶质细胞和星形胶质细胞之间共享。在目标2中，我将应用多模态数据 整合单细胞表达和染色质可及性数据的比对算法Harmonic Alignment 为每个细胞产生丰富的联合表达和可及性谱，以确定表观遗传调节因子， 表情当用于整合来自AMD患者和对照的数据集时，该算法将能够 鉴定染色质区域和调节基因表达的候选转录因子， 小胶质细胞和星形胶质细胞功能障碍。通过重叠我们对AMD、AD和AD的GWAS风险等位基因的了解， MS，在神经退行性疾病背景下先天免疫细胞功能障碍的预测表观遗传调节因子之上， 我希望能够阐明风险变异在细胞类型特异性方式诱导疾病中的作用。这些 这些项目将有助于确定先天免疫细胞中共有的基因组和调控机制， 神经退行性疾病，并将有助于确定未来治疗发展的共同途径。

With few effective interventions available and over 10 million patients affected, neurodegenerative diseases are an area of intense basic science and clinical research. Inspired by Genome Wide Association Studies (GWAS) that have identified many risk variants linked to immune genes, neurobiologists are just beginning to understand the inflammatory basis for neurodegeneration. Across degenerative conditions, such as Alzheimer’s Disease (AD) and Progressive Multiple Sclerosis (MS), computational techniques applied to single cell datasets are identifying the role of immune cells in driving pathological changes in the brain. For instance, recent single cell expression studies in AD have identified a novel type of Disease Associated Microglia (DAM) associated with the disease. Preliminary analysis I performed on single cell expression data produced from retinal tissue of patients suffering from Age-related Macular Degeneration (AMD) recapitulated this DAM phenotype in AMD- derived microglia. Furthermore, analysis revealed that AMD-derived astrocytes drive neovascularization, a pathologic hallmark of AMD, through the increased expression of VEGF. These findings imply that neurodegeneration and pathologic changes in AMD are driven by innate immune cells, and, further, that these innate immune cell functions may be similar across neurodegenerative diseases. I hypothesize that innate immune cell function and regulation that drives pathology is shared across neurodegenerative conditions. To identify these shared features, I will design and apply novel computational algorithms to single cell datasets from multiple neurodegenerative diseases - AMD, AD and MS - to elucidate the role of innate immune cells across conditions. In aim 1, I will apply a coarse graining algorithm, Diffusion Condensation, that clusters cells at all levels of granularity to identify pathologic microglial and astrocyte subsets in single cell expression data produced from retinal tissue of patients with AMD. I will further apply this technique to subset these innate immune cells in publicly available single cell expression datasets in MS and AD in order to identify gene modules shared among microglia and astrocytes across diseases. In aim 2, I will apply a multi-modal data alignment algorithm, Harmonic Alignment, that integrates single cell expression and chromatin accessibility data to produce a rich, joint expression and accessibility profile for every cell to identify epigenetic regulators of expression. When used to integrate datasets derived from AMD patients and controls, this algorithm will be able to identify chromatin regions and candidate transcription factors that regulate the expression of genes key to microglial and astrocytic dysfunction. By overlapping our knowledge of GWAS risk alleles from AMD, AD and MS, on top of predicted epigenetic regulators of innate immune cell dysfunction in a neurodegenerative context, I hope to be able to elucidate the effect of risk variants in inducing disease in a cell-type specific manner. These projects will help identify shared genomic and regulatory mechanisms in innate immune cells across neurodegenerative diseases and will help identify common pathways for future therapeutic development.