Establishing Genotype-to-Phenotype Relationships Between Alzheimer’s Related BIN1 Variants

项目摘要 全基因组关联研究（GWAS）已经确定了几个与概率改变相关的风险因素 晚发性阿尔茨海默病（LOAD）在这方面，桥接积分器1（BIN 1）中的变化已经被 与AD风险增加密切相关。为此，一些初步研究已经 提示BIN 1不仅调节淀粉样蛋白和tau蛋白病理学，而且还调节各种炎性 和细胞内稳态途径。尽管如此，BIN 1和AD之间的机制联系仍然不清楚。 此外，缺乏研究BIN 1变异对表现或 AD相关表型的增加。在这个提案中，我们将利用我们在干细胞方面的集体专长， 生物工程、神经退行性疾病建模和基因组工程，以研究 BIN 1变异与AD风险之间的关系。在第一个目标中，我们将使用我们高效的基因编辑， 将BIN 1变体引入来自健康非痴呆对照（NDC）和AD的同基因hiPSC的方法 患者在第二个目标中，我们将在3-D共培养模型中使用等基因hiPSC系来检验假设 这些BIN变体通过（i）调节淀粉样前体蛋白， (APP)加工和Aβ分泌以及（ii）tau蛋白过度磷酸化和内化的改变。此外，本发明还提供了一种方法， 我们将使用RNA-seq分析来识别信号通路、基因调控网络和转录调控。 受BIN变异和疾病状态独立影响的靶点。此外，本发明还提供了一种方法， 通过使用BIN 1敲除的hiPSC，我们将能够确定这些BIN 1变体是否诱导它们的作用， 通过功能获得或丧失机制发生。总的来说，更深入地了解机制 BIN 1的变化对AD发病可能性的贡献将对设计产生重大影响 治疗干预。

PROJECT SUMMARY ABSTRACT Genome-wide association studies (GWAS) have identified several risk factors associated with altered probability of late onset Alzheimer’s disease (LOAD). In this regard, variation in bridging integrator 1 (BIN1) have been identified as being strongly associated with increased risk of AD. To that end, several preliminary studies have suggested that BIN1 not only modulates amyloid and tau pathology but also modulates various inflammatory and cell homeostatic pathways. Nonetheless, the mechanistic links between BIN1 and AD remain poorly defined. Moreover, there is a paucity of research examining the effects of BIN 1 variation on the manifestation or augmentation of AD-related phenotypes. In this proposal, we will use our collective expertise in stem cell bioengineering, neurodegenerative disease modeling, and genome engineering to investigate the relationship between specific BIN 1 variants and AD risk. In the first aim, we will using our highly efficient gene editing approach to introduce BIN1 variants into isogenic hiPSCs from healthy non-demented control (NDC) and AD patients. In the second aim, we will employ isogenic hiPSC lines in a 3-D co-culture model to test the hypothesis that these BIN variants exert their risk-modifying effects through (i) modulation of amyloid precursor protein (APP) processing and Aβ secretion and (ii) alteration in tau hyperphosphorylation and internalization. In addition, we will use RNA-seq analysis to identify signaling pathways, gene regulatory networks, and transcriptional targets that are independently influenced by the presence of BIN variation and disease status. In addition, through the use of BIN1 knockout hiPSCs we will be able to determine if these BIN1 variants induce their effects occur through gain- or loss-of-function mechanisms. Overall, a more thorough understanding of the mechanisms by which variation in BIN1 contributes to the likelihood of AD onset will have a significant impact on the design of therapeutic interventions.