# Müller glia in disease and stress

> **NIH NIH R01** · UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR · 2020 · $362,500

## Abstract

Vascular endothelial growth factor (VEGF) is a major pathogenic factor for wet age-related
macular degeneration (AMD) and diabetic retinopathy (DR), leading causes of blindness in the
US. Intensive studies on wet AMD and DR have led to the development of anti-VEGF strategy for
treating blood-retina barrier (BRB) breakdown in these diseases. To investigate the functional
significance of VEGF signaling in major retinal supporting cells, Müller glia, we disrupted VEGF
receptor-2 (VEGFR2) in mice and observed a significant loss of Müller cells, accelerated retinal
neuron degeneration, and a substantial reduction of two neurotrophins: brain-derived
neurotrophic factor (BDNF) and glial cell line-derived neurotrophic factor (GDNF) in the retina in
diabetes/hypoxia. In this study, we will determine the mechanism of VEGF signaling-mediated
Müller cell viability, evaluate the significance of VEGF signaling in the production of neurotrophins,
and explore therapeutic potential of supplying neurotrophins for neuroprotection in diabetic or
hypoxic animals. Our study will contribute to the basis for establishing a general strategy to treat
neuronal pathology in DR and other hypoxic retinal diseases and provide mechanistic insights for
Müller glia as a cellular source of neuro-protectants in these diseases.

## Key facts

- **NIH application ID:** 9942403
- **Project number:** 5R01EY026970-04
- **Recipient organization:** UNIVERSITY OF OKLAHOMA HLTH SCIENCES CTR
- **Principal Investigator:** YUN Zheng LE
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $362,500
- **Award type:** 5
- **Project period:** 2017-09-01 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9942403

## Citation

> US National Institutes of Health, RePORTER application 9942403, Müller glia in disease and stress (5R01EY026970-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9942403. Licensed CC0.

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