Retinal pigment epithelial cell distribution in central retina of rhesus monkeys

D. Max Snodderly, Marita M. Sandstrom, Ivan Y.F. Leung, Charles L. Zucker, Martha Neuringer

Research output: Contribution to journalArticlepeer-review

63 Scopus citations


PURPOSE. To determine the cell density profile of the retinal pigment epithelium (RPE) in the central retina and relate it to the distribution of photoreceptors. METHODS. Wholemounts of rhesus monkey (Macaca mulatta) retinas with the choroid removed but the RPE attached were stained with the nuclear stain 4′,6-diamidine-2-phenylindole dihydrochloride (DAPI) and imaged with a fluorescence microscope. RPE cell nuclei were counted at the foveal center and at 0.4-mm intervals along the vertical meridian. The number of photoreceptors per RPE cell at each location was estimated by using previously published data on the distribution of rhesus photoreceptors. RESULTS. Data were collected from eight retinas. Mean RPE cell density increased from a relatively stable baseline of approximately 4000 RPE cells/mm2 beyond 2 mm (10°) eccentricity to more than 7000 cells/mm2 at the center of the fovea. The number of cones per RPE cell in the rhesus retina was approximately 20:1 in the foveal center (similar to the human retina) and only approximately 1.5:1 in the parafovea. However, when the rods were included, and the total number of photoreceptors per RPE cell were considered, the ratio of photoreceptors to RPE cells was lower in the fovea than in the remainder of the central retina. CONCLUSIONS. In spite of the high cone density, there is a relatively low number of photoreceptors per RPE cell in the fovea. This may limit the metabolic demands on foveal RPE cells and help to preserve their functions in the face of aging and disease.

Original languageEnglish (US)
Pages (from-to)2815-2818
Number of pages4
JournalInvestigative Ophthalmology and Visual Science
Issue number9
StatePublished - Sep 2002
Externally publishedYes

ASJC Scopus subject areas

  • Ophthalmology
  • Sensory Systems
  • Cellular and Molecular Neuroscience


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