retinal diseases
Finding Better Ways to Image the Retina
Posted on by Dr. Francis Collins
Every day, all around the world, eye care professionals are busy performing dilated eye exams. By looking through a patient’s widened pupil, they can view the retina—the postage stamp-sized tissue lining the back of the inner eye—and look for irregularities that may signal the development of vision loss.
The great news is that, thanks to research, retinal imaging just keeps getting better and better. The images above, which show the same cells viewed with two different microscopic techniques, provide good examples of how tweaking existing approaches can significantly improve our ability to visualize the retina’s two types of light-sensitive neurons: rod and cone cells.
Specifically, these images show an area of the outer retina, which is the part of the tissue that’s observed during a dilated eye exam. Thanks to colorization and other techniques, a viewer can readily distinguish between the light-sensing, color-detecting cone cells (orange) and the much smaller, lowlight-sensing rod cells (blue).
These high-res images come from Johnny Tam, a researcher with NIH’s National Eye Institute. Working with Alfredo Dubra, Stanford University, Palo Alto, CA, Tam and his team figured out how to limit light distortion of the rod cells. The key was illuminating the eye using less light, provided as a halo instead of the usual solid, circular beam.
But the researchers’ solution hit a temporary snag when the halo reflected from the rods and cones created another undesirable ring of light. To block it out, Tam’s team introduced a tiny pinhole, called a sub-Airy disk. Along with use of adaptive optics technology [1] to correct for other distortions of light, the scientists were excited to see such a clear view of individual rods and cones. They published their findings recently in the journal Optica [2]
The resolution produced using these techniques is so much improved (33 percent better than with current methods) that it’s even possible to visualize the tiny inner segments of both rods and cones. In the cones, for example, these inner segments help direct light coming into the eye to other, photosensitive parts that absorb single photons of light. The light is then converted into electrical signals that stream to the brain’s visual centers in the occipital cortex, which makes it possible for us to experience vision.
Tam and team are currently working with physician-scientists in the NIH Clinical Center to image the retinas of people with a variety of retinal diseases, including age-related macular degeneration (AMD), a leading cause of vision loss in older adults. These research studies are ongoing, but offer hopeful possibilities for safe and non-intrusive monitoring of individual rods and cones over time, as well as across disease types. That’s obviously good news for patients. Plus it will help scientists understand how a rod or cone cell stops working, as well as more precisely test the effects of gene therapy and other experimental treatments aimed at restoring vision.
References:
[1] Noninvasive imaging of the human rod photoreceptor mosaic using a confocal adaptive optics scanning ophthalmoscope. Dubra A, Sulai Y, Norris JL, Cooper RF, Dubis AM, Williams DR, Carroll J. Biomed Opt Express. 2011 Jul 1;2(7):1864-76.
[1] In-vivo sub-diffraction adaptive optics imaging of photoreceptors in the human eye with annular pupil illumination and sub-Airy detection. Rongwen L, Aguilera N, Liu T, Liu J, Giannini JP, Li J, Bower AJ, Dubra A, Tam J. Optica 2021 8, 333-343. https://doi.org/10.1364/OPTICA.414206
Links:
Get a Dilated Eye Exam (National Eye Institute/NIH)
How the Eyes Work (NEI)
Eye Health Data and Statistics (NEI)
Tam Lab (NEI)
Dubra Lab (Stanford University, Palo Alto, CA)
NIH Support: National Eye Institute
Snapshots of Life: Lighting up the Promise of Retinal Gene Therapy
Posted on by Dr. Francis Collins
Caption: Large-scale mosaic confocal micrograph showing expression of a marker gene (yellow) transferred by gene therapy techniques into the ganglion cells (blue) of a mouse retina.
Credit: Keunyoung Kim, Wonkyu Ju, and Mark Ellisman, National Center for Microscopy and Imaging Research, University of California, San Diego
The retina, like this one from a mouse that is flattened out and captured in a beautiful image, is a thin tissue that lines the back of the eye. Although only about the size of a postage stamp, the retina contains more than 100 distinct cell types that are organized into multiple information-processing layers. These layers work together to absorb light and translate it into electrical signals that stream via the optic nerve to the brain.
In people with inherited disorders in which the retina degenerates, an altered gene somewhere within this nexus of cells progressively robs them of their sight. This has led to a number of human clinical trials—with some encouraging progress being reported for at least one condition, Leber congenital amaurosis—that are transferring a normal version of the affected gene into retinal cells in hopes of restoring lost vision.
To better understand and improve this potential therapeutic strategy, researchers are gauging the efficiency of gene transfer into the retina via an imaging technique called large-scale mosaic confocal microscopy, which computationally assembles many small, high-resolution images in a way similar to Google Earth. In the example you see above, NIH-supported researchers Wonkyu Ju, Mark Ellisman, and their colleagues at the University of California, San Diego, engineered adeno-associated virus serotype 2 (AAV2) to deliver a dummy gene tagged with a fluorescent marker (yellow) into the ganglion cells (blue) of a mouse retina. Two months after AAV-mediated gene delivery, yellow had overlaid most of the blue, indicating the dummy gene had been selectively transferred into retinal ganglion cells at a high rate of efficiency [1].
Creative Minds: Reverse Engineering Vision
Posted on by Dr. Francis Collins
Caption: Networks of neurons in the mouse retina. Green cells form a special electrically coupled network; red cells express a distinctive fluorescent marker to distinguish them from other cells; blue cells are tagged with an antibody against an enzyme that makes nitric oxide, important in retinal signaling. Such images help to identify retinal cell types, their signaling molecules, and their patterns of connectivity.
Credit: Jason Jacoby and Gregory Schwartz, Northwestern University
For Gregory Schwartz, working in total darkness has its benefits. Only in the pitch black can Schwartz isolate resting neurons from the eye’s retina and stimulate them with their natural input—light—to get them to fire electrical signals. Such signals not only provide a readout of the intrinsic properties of each neuron, but information that enables the vision researcher to deduce how it functions and forges connections with other neurons.
The retina is the light-sensitive neural tissue that lines the back of the eye. Although only about the size of a postage stamp, each of our retinas contains an estimated 130 million cells and more than 100 distinct cell types. These cells are organized into multiple information-processing layers that work together to absorb light and translate it into electrical signals that stream via the optic nerve to the appropriate visual center in the brain. Like other parts of the eye, the retina can break down, and retinal diseases, including age-related macular degeneration, retinitis pigmentosa, and diabetic retinopathy, continue to be leading causes of vision loss and blindness worldwide.
In his lab at Northwestern University’s Feinberg School of Medicine, Chicago, Schwartz performs basic research that is part of a much larger effort among vision researchers to assemble a parts list that accounts for all of the cell types needed to make a retina. Once Schwartz and others get closer to wrapping up this list, the next step will be to work out the details of the internal wiring of the retina to understand better how it generates visual signals. It’s the kind of information that holds the key for detecting retinal diseases earlier and more precisely, fixing miswired circuits that affect vision, and perhaps even one day creating an improved prosthetic retina.
