# Relating Structure to Function in Optic Neuropathies

> **NIH NIH R01** · UNIVERSITY OF HOUSTON · 2020 · $382,500

## Abstract

DESCRIPTION
Glaucoma is a group of diseases that results in a pathological loss of retinal ganglion cells (RGC) and irreversible
vision loss. Although glaucoma is an optic neuropathy with characteristic optic nerve head (ONH) changes, risk
of developing disease is not based on ONH structure, but factors including intraocular pressure (IOP), central
corneal thickness, age, race and family history. In early disease, there is significant thinning of the optic nerve
head (ONH) rim tissue that precedes RGC loss. We hypothesize that the early thinning of the ONH neuroretinal
rim tissue (NRR) is related to changes in the glia and extracellular matrix, but not axonal content, which we will
investigate using immunohistochemistry and 3D serial block-face scanning electron microscopy in the non-
human primate experimental glaucoma model. We also hypothesize that the ONH NRR response to transient
changes in IOP is a reflection of the NRR tissue composition, and predictive of the rate of RGC loss (SA1).
Clinically, RGC content of the eye is assessed with non-invasive imaging using optical coherence tomography
(OCT), for structure, and visual thresholds, for function. OCT structural measures have low variability and have
revolutionized how glaucoma is assessed. However, the RGC correspondence to OCT measures is not known,
and cannot be estimated from in vivo measures. In fact, the linear relationship for all OCT derived RGC measures
is not correct. In SA2, the relationship between OCT derived measures of the circumpapillary retinal nerve fiber
layer and ganglion cell inner plexiform thickness will be related to RGC content at all stages of neuropathy using
rigorous histological methods. The goal of this aim is develop methods to estimate RGC content in the eye. For
a disease that results in irreversible vision loss, it is important that visual function is also assessed accurately.
In principal there should also be excellent correspondence between RGC content estimates from OCT measures
and that from visual thresholds. Because structural measures are objective and less variable, it would be ideal
to accurately predict vision using structural measures. However there is significant discrepancy between
structural and functional measures. Some of the reasons for this disjunction is that visual function tests do not
use appropriate spatial sampling and stimulus size. In these experiments we will investigate the relationship
between RGC content and visual thresholds using higher spatial density and varying stimulus sizes (SA3). Our
goal is to establish robust methods to predict visual function based on non-invasive structural imaging. Overall,
these studies are designed to improve our understanding of disease pathophysiology and the ability to accurately
monitor it in clinical practice.

## Key facts

- **NIH application ID:** 9843167
- **Project number:** 5R01EY029229-02
- **Recipient organization:** UNIVERSITY OF HOUSTON
- **Principal Investigator:** Nimesh Bhikhu Patel
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $382,500
- **Award type:** 5
- **Project period:** 2019-01-01 → 2023-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9843167

## Citation

> US National Institutes of Health, RePORTER application 9843167, Relating Structure to Function in Optic Neuropathies (5R01EY029229-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9843167. Licensed CC0.

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