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

点击翻译按钮获取中文摘要

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.