Researchers Awarded $2.7 Million NIH Grant to Study Retinal Connections in Retinitis Pigmentosa
A collaborative team from the University of Southern California (USC) and the University of Utah has been awarded a $2.7 million grant from the National Institutes of Health (NIH) to investigate how retinitis pigmentosa (RP) disrupts the visual wiring in the retina. The study seeks to uncover critical insights that could lead to strategies for slowing or preventing vision loss caused by this incurable eye disease.
Understanding Retinitis Pigmentosa (RP)
Retinitis pigmentosa is a progressive inherited retinal disease that causes retinal cells to degenerate. It typically begins in childhood and progresses through four distinct stages, ultimately resulting in peripheral vision loss and blindness. Approximately 2 million people worldwide are affected by RP.
The disease leads to improper connections between retinal neurons as healthy cells attempt to compensate for cell death, exacerbating damage.
The Goal of the Study: Mapping the Retinal Connectome
The research team will create detailed maps of the retina's nerve connections—known as the "connectome"—to track how these networks deteriorate at each stage of RP. By correlating structural changes in the retina with functional disruptions, the team hopes to identify strategies to slow disease progression.
“We want to bring the entire network to life with functional models — showing what the disease does — that can be used by everybody working in this field,” said Gianluca Lazzi, PhD, principal investigator and USC Provost Professor of Ophthalmology, Electrical and Computer Engineering, Clinical Entrepreneurship, and Biomedical Engineering.
Lazzi further explained that understanding how neurons make improper connections will be key to guiding them toward better, healthier connections in the future.
Advanced Imaging Techniques and Key Contributions
The team is leveraging two complementary imaging techniques to visualize and analyze the retinal network:
1. Two-Photon Excitation Microscopy
Led by Michael Bienkowski, PhD, an assistant professor of physiology and neuroscience at USC, this technique allows researchers to:
• Peer deep into the retina without damaging tissue.
• Tag specific populations of neurons with fluorescent colors for detailed visualization.
• Selectively label neurons using a modified, non-infectious form of the rabies virus to deliver fluorescent dye.
“Mike’s technique allows us to image a precise layer of the retina,” Lazzi said. “We can capture the entire image of, say, all the ganglion cells, so there’s no confusion between different types of neurons. This is a huge advantage.”
2. Transmission Electron Microscopy
Led by Bryan Jones, PhD, of the University of Utah, this imaging technique captures ultra-detailed images of individual synapses where neurons connect, revealing changes at a microscopic level.
Computational Models and AI Integration
The research will incorporate computational analysis and AI to model the retina’s behavior, led by Lazzi and Jean-Marie Bouteiller, PhD, a USC research associate professor of biomedical engineering. This approach will help identify key features of healthy neurons and track changes caused by RP.
Validating the Models
Steven Walston, PhD, an electrophysiologist and assistant professor of research ophthalmology at USC, will validate the computational findings by analyzing electrical signaling in the retina.
“Steve’s contributions enable us to correlate the results of the computational models with experimental measurements,” Lazzi said.
Cross-Disciplinary Collaboration
The project unites expertise from diverse fields, including ophthalmology, neuroscience, biomedical engineering, and computational modeling. The team involves key contributions from:
• USC Viterbi School of Engineering
• Keck School of Medicine of USC
• USC Dornsife College of Letters, Arts and Sciences
• University of Utah School of Medicine
Lazzi described the project as true cross-fertilization:
“We’re working together on an entire mesh of activities. In that environment, you learn and adapt. You operate in areas that might push the borders of the box you’re used to. But that’s entirely the point — there shouldn’t be a box, right?”
Conclusion
This NIH-funded study represents a critical step in understanding the progression of retinitis pigmentosa and the deterioration of retinal networks. By integrating advanced imaging, computational modeling, and AI, the research team aims to develop groundbreaking insights that could inform future strategies to slow or prevent vision loss caused by RP.
Lazzi and his collaborators remain optimistic that their work will provide a strong foundation for future therapies and inspire innovative approaches to treating inherited retinal diseases.
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