The researchers from the National Eye Institute (NEI) discovered five subpopulations of retinal pigment epithelium (RPE) a layer of tissue that supports andnourishes the retinas light-sensing photoreceptors. Using artificial intelligence, they analyzed images of RPE at a single-cell resolution to create a reference map that can identify each subpopulation within the eye.
According to Michael F. Chiang, the National Institutes of Health''s first-of-its-kind assessment of different RPE cell populations and their vulnerability to retinal diseases, and for developing targeted therapies to treat them.
According to the study''s lead investigator, Kapil Bharti, Ph.D., who leads the NEI Ocular and Stem Cell Translational Research Section, these findings will help us develop more precise cell and gene therapies for specific degenerative eye diseases.
The lens 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 areas in the brain. The RPE sits beneath the photoreceptors as a monolayer, with one cell deep.
Age and disease may alter RPE cells, which may result in photoreceptor degeneration. The impact of these RPE changes on vision vary dramatically depending on severity and where the RPE cells reside within the retina. For example, late-onset retinal degeneration (L-ORD) is a leading cause of vision loss. RPE cells in the macula are primarily affected by age and disease, which is vital for central vision.
Bharti and his colleagues have sought to see if there are different RPE populations that might explain the wide spectrum of retinal disease phenotypes.
The team used artificial intelligence (AI) to evaluate RPE cell morphometry, the external shape and dimensions of each cell. They then trained a computer using fluorescently labeled RPE to investigate the entire human RPE monolayer from nine cadaver donors with no history of significant eye disease.
On average, 2.8 million people were surveyed for each RPE cell, according to a sample size, along with four hundred thousand people to determine each cell area, dimension, and hexagonality. Previous research suggests that RPE function is linked to the tightness of cell junctions; the more busy, the better for indicating cell health.
Five distinct RPE cell subpopulations, referred to as P1-P5, were identified in concentric circles around the fovea, which is the center of the macula and the most light-sensitive region of the retina. Compared to RPE in the periphery, foveal RPE tend to be perfectly hexagonal and more compactly located, with a greater number of adjacent cells.
Unexpectedly, they discovered that the peripheral retina contains a circle of RPE cells (P4) with a cell area similar to RPE in and around the macula.
The presence of the P4 subpopulation highlights the diversity within the retinal periphery, implying that there may be functional limitations among RPE, according to the first author, Davide Ortolan, a research fellow at the NEI Ocular and Stem Cell Translational Research Section. Future experiments are needed to help us understand the role of this subpopulation.
Next, they examined RPE from AMD cadavers. Foveal (P1) RPE tended to be absent due to disease damage, and the differences among cells in the P2-P5 subpopulations were not statistically significant. Overall, the AMD RPE populations were elongated relative to those that AMD not affected.
A combined analysis of ultrawide-field fundus autofluorescence images from patients affected by choroideremia, L-ORD, or a retinal degeneration with no known molecular mechanism has permisted the study. Despite this finding, different RPE subpopulations are susceptible to many types of retinal degenerative diseases.
According to Ortolan, AI may detect changes in RPE cell morphometry before the development of a visible degeneration.
Some RPE subpopulations may be identified before they will be seen in others, according to these findings. Noninvasive imaging techniques, such as adaptive optics, will resolve retinal cells in unprecedented detail and might be used to predict RPE health changes in living patients.
The project was funded by the NEI Intramural Research Program.