Gene Expression Data for Investigating Glaucoma Treatment Options and Pharmacology in the Anterior Segment, State-of-the-Art and Future Directions

Glaucoma treatment options as well as its etiology are far from understood. Gene expression (transcriptomics) data of the anterior segment of the eye can help by elucidating the molecular-mechanistic underpinnings, and we present an up-to-date description and discussion of what gene expression data are publicly available, and for which purposes these can be used. We feature the few resources covering all segments of the eye, and we then specifically focus on the anterior segment, and provide an extensive list of the Gene Expression Omnibus data that may be useful. We also feature single-cell data of relevance, particularly three datasets from tissues of relevance to aqueous humor outflow. We describe how the data have been used by researchers, by following up resource citations and data re-analyses. We discuss datasets and analyses pertaining to fibrosis following glaucoma surgery, and to glaucoma resulting from the use of steroids. We conclude by pointing out the current lack and underutilization of ocular gene expression data, and how the state of the art is expected to improve in the future.

Automated summary

This article discusses the treatment options and etiology of glaucoma, and introduces publicly available gene expression data and their applications. It provides an overview of resources covering different segments of the eye, with a specific focus on the anterior segment. The article also includes a comprehensive list of Gene Expression Omnibus data that may be useful. It highlights the use of single-cell data related to aqueous humor outflow, and describes how researchers have utilized the data through resource citations and re-analyses. Additionally, the article discusses datasets and analyses related to fibrosis after glaucoma surgery and glaucoma resulting from steroid use. It concludes by emphasizing the current lack and underutilization of ocular gene expression data, and predicts improvements in the future.