HIGH THROUGHPUT SINGLE CELL TRANSCRIPTOMIC APPROACH TO IDENTIFY SUSCEPTIBLE CELL TYPES AND GENE EXPRESSION CHANGES IN HUMAN GLAUCOMA

摘要 青光眼是全球不可逆性失明的主要原因，它是由视网膜丢失引起的 神经节细胞(RGC)，将视觉信息从眼睛传递到大脑的其他部分。 目前的治疗策略集中在降低眼压(IOP)，这是唯一已知的 青光眼的可改变危险因素。然而，大量未得到满足的需求依然存在，而且 直接针对青光眼视网膜节细胞的神经保护策略将提供强大的 辅助性方法。然而，到目前为止，还没有一种神经保护疗法成功 走进了诊所。一个主要的障碍是，人们对许多人类RGC中的哪一个知之甚少 类型是最敏感的，以及在RGC死亡之前发生了什么分子变化。 该项目使用单细胞转录图谱和综合计算分析来 填补我们知识中的这些空白。过去五年，我们帮助发展 高通量单细胞RNA测序方法(scRNA-seq)及其应用 视网膜--首先在小鼠身上，然后在非人类灵长类动物身上，然后在人类和小鼠身上 神经元损伤的模型。最近，我们实现了Single的相关方法 细胞核RNA-seq(SnRNA-seq)，这样我们就可以分析死后获得的组织，冷冻和 存入银行。我们现在建议获得和分析视网膜神经节细胞的单核转录本 特征明确的青光眼和正常人视网膜。样本数必须为 大，因为青光眼是一种具有不同遗传和非遗传风险的异质性疾病 各种因素。因此，重要的是要研究不同的群体，这样我们才能确定他们是否 汇聚在共同的分子模式上。具体地说，我们将分析至少2000个RGC 200只人类供体眼睛，150只来自确诊为青光眼的人，50只来自年龄-， 性别和种族相匹配的对照。根据我们获得的数据，我们将(A)确定是否有具体的 RGC类型在青光眼中选择性地有弹性或易受攻击，(B)识别不同的基因 在每种类型的青光眼和正常视网膜节细胞之间表达。最后，我们将表演 在高眼压小鼠青光眼模型上进行了类似的分析，帮助我们了解了 人类的哪些疾病过程是在老鼠身上准确建模的。我们的结果将为我们提供一个 强大的资源，有足够的力量来改变我们对这一普遍、复杂和 不完全了解致盲症。

ABSTRACT Glaucoma, the leading cause of irreversible blindness worldwide, results from loss of retinal ganglion cells (RGCs), which carry visual information from the eye to the rest of the brain. Current treatment strategies center on lowering intraocular pressure (IOP), the only known modifiable risk factor for glaucoma. However, significant unmet need persists, and a neuroprotective strategy targeting glaucomatous RGCs directly would offer a powerful complementary approach. To date, however, no neuroprotective therapies have successfully entered the clinic. One major obstacle is that little is known about which of many human RGC types are most susceptible, and what molecular changes occur in RGCs prior to their demise. This project uses single cell transcriptomic profiling and integrative computational analysis to address these gaps in our knowledge. Over the past five years, we have helped to develop methods for high throughput single cell RNA sequencing (scRNA-seq) and applied them to retina – first in mice, then in non-human primates, and subsequently in humans and in mouse models of neuronal injury. Most recently, we have implemented the related method of single nucleus RNA-seq (snRNA-seq) so that we can profile tissue obtained post-mortem, frozen and banked. We now propose to obtain and analyze single nucleus transcriptomes of RGCs from well-characterized glaucomatous and normal human retinas. The number of samples must be large, because glaucoma is a heterogeneous disease with diverse genetic and non-genetic risk factors. It is therefore important to study diverse groups, so we can determine whether they converge on common molecular patterns. Specifically, we will profile at least 2000 RGCs from each of 200 human donor eyes, 150 from individuals with verified glaucoma and 50 from age-, sex- and race-matched controls. From the data we obtain, we will (a) determine whether specific RGC types are selectively resilient or vulnerable in glaucoma and (b) identify genes differentially expressed between glaucomatous and normal RGCs of each type. Finally, we will perform similar analysis on a high-IOP mouse model of glaucoma, helping us understand the extent to which diseases processes in humans are accurately modeled in mice. Our results will provide a powerful resource of sufficient power to transform our view of this prevalent, complex and incompletely understood blinding disease.