Alzheimer variants: Propagation of shared functional changes across cellular networks

阿尔茨海默病变异：跨细胞网络共享功能变化的传播

• 批准号: 10217808
• 负责人: PHILIP L DE JAGER
• 金额: $ 167.61万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10217808
• 关键词: Address; Alzheimer' s Disease; Alzheimer' s disease pathology; Astrocytes; Biological Assay; Biological Models; Brain; CRISPR screen; Cell Culture Techniques; Cells; Cerebrospinal Fluid; Clinical; Clinical Data; Code; Cognition; Communities; Complex; DNA; Data; Data Set; Databases; Dementia; Disease; Disease Progression; Disease susceptibility; Dissection; Epigenetic Process; Evaluation; Event; Future; Generations; Genes; Genetic Transcription; Genetic Variation; Genetic study; Genome; Goals; Heterogeneity; Human; Impaired cognition; In Situ; In Vitro; Individual; Intervention; Lead; Link; Location; Maps; Measures; Microglia; Mind; Modality; Modeling; Molecular; Multiomic Data; Natural Selections; Nerve Degeneration; Neurons; Nodal; Nucleic Acid Regulatory Sequences; Onset of illness; Outcome; Outcome Measure; Peptides; Predisposition; Proteins; Proteomics; Quantitative Trait Loci; Research; Risk Factors; Role; Sampling; Susceptibility Gene; Symptoms; System; Time; Tissue Stains; Tissues; Variant; Work; base; brain cell; cell type; clinical phenotype; data and analysis portal; endophenotype; epigenomics; experimental study; functional genomics; genetic variant; genomic locus; human DNA; human tissue; in silico; in vivo; induced pluripotent stem cell; intercellular communication; morphometry; multiple omics; network models; novel; precision medicine; programs; relating to nervous system; stem cell model; synergism; trait; transcriptomics

Project Abstract Genetic studies of Alzheimer’s disease (AD) and related-diseases (ADRD) have identified over 72 loci associated with susceptibility. Although some of the most penetrant variants have been studied independently, the majority of sequence variants and features are unlikely to act in isolation. In addition, the range of susceptibility loci cover coding, epigenetic, and regulatory regions of the genome, suggesting complex relationships that cannot be captured by large-scale transcriptomic and proteomic profiling alone. With this in mind, we systematically interrogate combinations of variants across validated AD loci in a cell autonomous and non-autonomous manner using a combination of molecular, epigenetic, and functional assays. This allows to create a functional network across AD loci, and identify nodal points where the effects of individual loci interact to trigger the hallmarks of AD pathology and clinical phenotypes. As part of this effort, we propose to establish a novel AD Locus Annotator interface that synthesizes information about AD-associated sequence features from reference databases encompassing existing multi-omic and clinical data, as well as new data sets that capture quantitative proteoform and cellular functional data; these latter two data modalities have been under-characterized in AD research to date, but are crucial to identifying cross-loci interactions. From this synthesized data analysis and portal effort, we then establish a set of gene editing efforts to validate and extend our mechanistic understanding of multi- locus functional networks from these AD-associated sequence features. Taken together, these analyses and experiments allow us to link the heterogeneity of AD-associated genetic variation and clinical manifestations into a coherent framework that link AD loci with the temporal sequence of events in AD onset and progression.

项目摘要 阿尔茨海默病（AD）及其相关疾病（ADRD）的遗传学研究已经确定了超过72个与AD相关的基因座。 易感性。虽然一些最具渗透力的变体已经被独立研究，但大多数变体都是由 序列变异和特征不太可能单独起作用。此外，易感基因座的范围涵盖 基因组的编码、表观遗传和调控区域，表明了复杂的关系， 仅通过大规模转录组学和蛋白质组学分析就能捕捉到。考虑到这一点，我们系统地 以细胞自主和非自主方式询问经验证的AD基因座上的变体组合 使用分子、表观遗传和功能测定的组合。这允许创建功能网络 跨AD基因座，并确定节点，其中单个基因座的影响相互作用，以触发 AD病理学和临床表型。作为这项工作的一部分，我们建议建立一个新的AD基因座注释器 综合来自参考数据库的AD相关序列特征信息的界面 包括现有的多组学和临床数据，以及捕获定量蛋白质组的新数据集。 和细胞功能数据;后两种数据模式在AD研究中特征不足， 日期，但对于识别跨基因座相互作用至关重要。通过这种综合数据分析和门户工作， 然后，我们建立了一套基因编辑的努力，以验证和扩展我们的多机制的理解， 从这些AD相关的序列特征的基因座功能网络。这些分析和 实验使我们能够将AD相关遗传变异的异质性和临床表现联系起来， 一个连贯的框架，连接AD基因座与AD发病和进展中事件的时间顺序。