? DESCRIPTION (provided by applicant): Retinal degeneration is the leading cause of blindness and costs society billions of dollars annually in disability and lost productivity, a burden that is predicted to worsen as baby-boomers age. All current treatments for retinal degeneration, including experimental therapeutics like stem cell or gene replacement therapy, are thought to be most effective when degeneration is caught in its earliest stages. Unfortunately, the earliest detectable symptom of degeneration is often visual impairment, which is only detectable after a large number of retinal cells have died and disappeared. The ability to discern the first signs of cell stress, prior to apoptosis and degeneration, could significantly improve the likelihood of delaying or preventing vision loss. One common early indication of pending degeneration is activation of retinal microglia, the resident retinal immune cells, which can proliferate, migrate to and phagocytose injured neurons. The proposed work will define the earliest changes in microglia during photoreceptor degeneration. Using high-resolution, adaptive optics imaging, we will determine the 3-dimensional morphology and dynamics of individual retinal microglia in vivo, both in healthy tissue and during the earliest stages of photoreceptor stress and degeneration (Aim 1). We will also determine the signals that trigger microglial migration to the outer retina and specify photoreceptor engulfment (Aim 2). Finally, we will determine the time course by which circulating macrophages infiltrate the outer retina, and evaluate the degree to which both of these cell types promote or undermine photoreceptor survival (Aim 3). This work will contribute to the long-term goal to monitor and manipulate microglial dynamics in vivo so as to provide earlier detection of and assessment of treatments for retinal degenerative disease.
|Effective start/end date||9/1/15 → 8/31/19|
- National Institutes of Health: $412,944.00
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.