Retinal Cell Map Could Advance Therapies for Blinding Diseases
Five subpopulations of RPE (P1-P5) were identified based on cell area, aspect ratio, hexagonality and number of neighbors. Foveal RPE (P1) are tightly packed hexagons. Peripheral RPE (P5) are spread out.
Photo: Davide Ortolan, Ph.D.
An NIH discovery is shedding light on tissue targeted by age-related macular degeneration and other eye diseases. Researchers have identified distinct differences among the cells comprising a tissue in the retina that is vital to human visual perception. NEI scientists discovered five subpopulations of retinal pigment epithelium (RPE)—a layer of tissue that nourishes and supports the retina’s light-sensing photoreceptors.
Using artificial intelligence (AI), the researchers analyzed images of RPE at single-cell resolution to create a reference map that locates each subpopulation within the eye. A report on this research is published in Proceedings of the National Academy of Sciences.
“These results provide a first-of-its-kind framework for understanding different RPE cell subpopulations and their vulnerability to retinal diseases, and for developing targeted therapies to treat them,” said NEI director Dr. Michael Chiang.
“The findings will help us develop more precise cell and gene therapies for specific degenerative eye diseases,” said the study’s lead investigator, Dr. Kapil Bharti, who directs the NEI ocular and stem cell translational research section.
Vision begins when light hits the rod and cone photoreceptors that line the retina in the back of the eye. Once activated, photoreceptors send signals through a complex network of other retinal neurons that converge at the optic nerve before traveling to various centers in the brain. The RPE sits beneath the photoreceptors as a monolayer, one cell deep.
Age and disease can cause metabolic changes in RPE cells that can lead to photoreceptor degeneration. The impact on vision from these RPE changes varies dramatically by severity and where the RPE cells reside within the retina.
Using AI, the team analyzed RPE cell morphometry, the external shape and dimensions of each cell. They trained a computer using fluorescently labelled images of RPE to analyze the entire human RPE monolayer from nine cadaver donors with no history of significant eye disease.
“Overall, the results suggest that AI can detect changes of RPE cell morphometry prior to the development of visibly apparent degeneration,” said NEI research fellow Dr. Davide Ortolan.
These findings could potentially be used to predict changes in RPE health in living patients.