Understanding the functional impact of cumulative genetic risk in Alzheimer Disease

阿尔茨海默病（Alzheimer disease，AD）是一种复杂的表型，受多种遗传因素的累积影响， 元素虽然环境因素和年龄肯定有助于表型表达，我们假设 AD的潜在生物学过程是由影响风险的遗传变异负担驱动的。 了解遗传负担如何导致疾病可以为开发更有效的AD提供信息 治疗学此外，已知的AD遗传风险变体的谱涉及许多细胞类型， 因此，了解变异如何影响生物网络，以及哪种细胞类型对指导治疗至关重要， 目标设计 在这项提案中，我们利用我们的合作和跨学科的AD研究计划在大学 的华盛顿和SAGE Bionetworks创建一个AD细胞类型特异性系统生物学程序。我们 假设非编码变体通过破坏细胞途径而赋予AD风险， 通过AD患者脑组织的分子表型鉴定并在体外测定。具体来说，我们专注于 内体生物学考虑到内体途径和神经细胞功能之间的联系， 与内体遗传变异风险和AD相关。通过使用内体途径特异性 多基因风险评分，我们可以丰富我们的AD队列，使其更有可能表现出由内体基因驱动的AD。 功能障碍 我们将采用单核转录组学和功能研究，在重编程的神经细胞中， 研究内体途径中遗传风险对AD病理生理学的影响。 我们将1）确定高内体途径多基因风险评分是否预测内体功能障碍， 神经元和2）确定高内体多基因风险如何影响小胶质细胞功能。通过 这些数据集的开发，将通过SAGE Bionetworks作为开源提供，我们可以 开始鉴定AD中与内体变体负荷相关的细胞类型特异性转录组学变化， 以及使用诱导的多能干细胞衍生的神经元的伴随的功能性细胞改变， 小胶质细胞和转分化神经元。我们的综合分子和细胞生物学表型分析方法 旨在确定聚合内体遗传风险可能导致AD的生物学途径 发病机制和阐明细胞亚型最直接影响的内体功能障碍。 了解候选的生物学途径和它们被破坏的细胞类型将提供 为更有效的治疗AD提供有价值的信息。

Alzheimer disease (AD) is a complex phenotype influenced by the cumulative impact of many genetic elements. While environmental factors and age certainly contribute to phenotypic expression, we hypothesize that the underlying biological process of AD is driven by the burden of genetic variants influencing risk. Understanding how genetic burden causes disease can inform efforts to develop more effective AD therapeutics. Furthermore, the spectrum of known AD genetic risk variants implicates numerous cell types and thus knowing how variants impact biological networks and in which cell type is critical to directing therapeutic target design. In this proposal we leverage our collaborative and interdisciplinary AD research programs at the University of Washington and SAGE Bionetworks to create a cell-type specific systems biology program in AD. We hypothesize that non-coding variants confer AD risk through disruption of cellular pathways which can be identified by molecular phenotyping of AD patient brain tissue and assayed in vitro. Specifically, we focus on endosome biology given the link between endosome pathways and neural cell function and the known association with endosomal genetic variant risk and AD. Through the use of an endosome pathway specific polygenic risk score we can enrich our AD cohort for those more likely to manifest AD driven by endosomal dysfunction. We will employ single nuclei transcriptomics and functional studies in reprogrammed neural cells derived from the same cohort to investigate the impact of genetic risk in endosomal pathways on AD pathophysiology. We will 1) determine if a high endosome pathway polygenic risk score predicts endosome dysfunction in neurons and 2) determine how high endosome polygenic risk influences microglia function. Through development of these datasets, which will be available as open-source through SAGE Bionetworks, we can begin to identify the cell type specific transcriptomic changes in AD associated with endosomal variant load as well as the concomitant functional cell alterations using induced pluripotent stem cell derived neurons, microglia and transdifferentiated neurons. Our integrated molecular and cell biology phenotyping approach seeks to identify biological pathways by which aggregate endosomal genetic risk may contribute to AD pathogenesis and elucidate the cellular subtypes most directly impacted by endosomal dysfunction. Understanding candidate biological pathways and the cell types in which they are disrupted will provide valuable information for more effective therapeutic targeting in AD.