An In Silica Model for RPE Loss Patterns in Choroideremia

Invest Ophthalmol Vis Sci. 2021 Nov 1;62(14):10. doi: 10.1167/iovs.62.14.10.

Abstract

Purpose: To use empirical data to develop a model of cell loss in choroideremia that predicts the known exponential rate of RPE loss and central, scalloped preservation pattern seen in this disease.

Methods: A computational model of RPE loss was created in Python 3.7, which constructed an array of RPE cells clusters, binarized as either live or atrophic. Two rules were applied to this model: the background effect gave each cell a chance of dying defined by a background function, and the neighbor effect increased the chance of RPE cell death if a neighbor were dead. The known anatomic distribution of rods, RPE, choriocapillaris density, amacrine, ganglion, and cone cells were derived from the literature and applied to this model. Atrophy growth rates were measured over arbitrary time units and fit to the known exponential decay model. The main outcome measures: included topography of atrophy over time and fit of simulated residual RPE area to exponential decay.

Results: A background effect alone can simulate exponential decay, but does not simulate the central island preservation seen in choroideremia. An additive neighbor effect alone does not simulate exponential decay. When the neighbor effect multiplies the background effect using the rod density function, our model follows an exponential decay, similar to previous observations. Also, our model predicts a residual island of RPE that resembles the topographic distribution of residual RPE seen in choroideremia.

Conclusions: The pattern of RPE loss in choroideremia can be predicted by applying simple rules. The RPE preservation pattern typically seen in choroideremia may be related to the underlying pattern of rod density. Further studies are needed to validate these findings.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Atrophy
  • Cell Count
  • Choroideremia / pathology*
  • Computer Simulation*
  • Humans
  • Retinal Pigment Epithelium / pathology*
  • Retinal Rod Photoreceptor Cells / pathology
  • Silicon Dioxide
  • Tomography, Optical Coherence
  • Visual Acuity

Substances

  • Silicon Dioxide