Variant to gene mapping for Alzheimer's Disease

摘要 阿尔茨海默病(AD)是一种破坏性的神经退行性疾病，影响超过500万人 65岁以上的美国人。广告会破坏记忆和认知能力，目前还没有 能够减缓或阻止其进展的有效治疗方法。尽管环境和生活方式因素一直是 AD被认为是一种复杂的疾病，具有明确的遗传成分，与其发病机制有关。 通过大规模合作，密集的全基因组关联研究(GWAS)工作已经完成 成功地发现了经典载脂蛋白E基因座以外与阿尔茨海默病密切相关的遗传基因座。然而， Gwas只报告了与给定性状相关的基因组信号，而不一定是对 罪犯的基因。因此，在过去的十年里，GWAS并没有严格地代表十年的基因靶标 相反，这只是十年的信号发现。 一个明显的例子是最近在确定肥胖症FTO基因座方面的进展。这个 驻留在FTO内含子区域内的Gwas信号实际上最近被证明主要是 影响附近的IRX3和IRX5基因的表达，而不是宿主基因本身，这表明 这种变异是嵌入在一个基因中的增强子，但会影响其他基因的表达。所以一把钥匙 问题仍然存在：AD关联信号也是这样吗？ 事实上，我们已经解决了迄今为止报告的在2型糖尿病中最重要的GWAS发现， 即转录因子7-样2(TCF7L2)基因内的遗传变异，P.I. 应用程序于2006年首次描述。通过使用染色质构象捕获和CRISPR/Cas9 基因组编辑技术，我们有证据表明，该基因座的罪魁祸首基因是ACSL5。 由于我们已经有了一个专门的基础设施来进行这种‘变异到基因图谱’的工作， 包括CHOP已建立的人类多能干细胞核心，我们的团队准备确定GWA是如何- AD基因座在神经退行性变中影响特定基因的表达和功能 相应的拓扑关联结构域(TADS)。基于“三维基因组学”和CRISPR的应用 IPSC来源的神经前体细胞及其终末相关细胞模型中的技术 分化的神经元特别及时，因为它将有助于精确定位已建立的AD GWAs的因果基因(S) 与转座酶可及染色质测序分析(ATAC-SEQ)相结合时的信号 确定一份假定的因果SNPs的候选名单，这些SNPs几乎完全是非编码的，这与 打开染色质。 只有通过发现与GWA识别的遗传变异相关的致病基因，并了解如何 如果他们开始运作，我们能否真正将这些高价值的Gwas报告转化为对患者护理有意义的好处。

ABSTRACT Alzheimer's disease (AD) is a devastating neurodegenerative disorder that impacts in excess of 5 million Americans over the age 65 years old. AD disrupts memory and cognitive abilities, and there are currently no effective therapies able to slow or halt its progression. Although environmental and lifestyle factors have been implicated in its pathogenesis, AD is considered a complex disorder with a clear genetic component. Intense genome wide association study (GWAS) efforts through large-scale collaborations have been successful in discovering genetic loci robustly associated with AD beyond the classic APOE locus. However, GWAS only reports genomic signals associated with a given trait and not necessarily the precise localization of culprit genes. As such, over the past ten years, GWAS has not strictly represented a decade of gene target discovery, rather it has simply been a decade of signal discovery. One clear example of this is highlighted by the recent progress in characterizing the FTO locus in obesity. The GWAS signal that resides within an intronic region of FTO has in fact been recently shown to primarily influence the expression of the IRX3 and IRX5 genes nearby rather than the `host' gene itself, suggesting that this variant is in an enhancer embedded in one gene but influencing the expression of others. So a key question remains: is this the case with AD association signals as well? Indeed, we have already addressed the most significant GWAS finding in type 2 diabetes reported to date, namely genetic variation within the transcription factor 7-like 2 (TCF7L2) gene, which the P.I. on this application first described in 2006. Through the use of chromatin conformation capture and CRISPR/Cas9 genome editing techniques, we have evidence that a culprit gene at this locus is ACSL5. Since we already have a dedicated infrastructure in place to conduct such `variant to gene mapping' efforts, including CHOP's established Human Pluripotent Stem Cell core, our team is poised to determine how GWAS- implicated AD loci affect the expression and function of specific genes during neurodegeneration within corresponding topologically associated domains (TADs). The application of `3D Genomics' and CRISPR based techniques in the relevant cellular models of iPSC-derived neural progenitor cells (NPCs) and terminally differentiated neurons is particularly timely, as it will aid in pinpointing causal gene(s) at established AD GWAS signals when combined with `Assay for Transposase Accessible Chromatin sequencing' (ATAC-seq) to ascertain a shortlist of putative causal SNPs, which will almost entirely be non-coding, and that coincide with open chromatin. Only by uncovering the causative genes related to GWAS-identified genetic variants, and understanding how they operate, can we truly translate these high value GWAS reports in to meaningful benefits for patient care.