Tag Archives: ARVO 2017

Synaptic Inputs To A Gamma Ganglion Cell In Rabbit Retina

This abstract was presented today, May 8th at the 2017 Association for Research in Vision and Opthalmology (ARVO) meetings in Baltimore, Maryland by Andrea Bordt, Diego Perez, Robert E. Marc, James R. Anderson, Carl B. Watt, Bryan W. Jones, Crystal Sigulinsky, James S. Lauritzen, Danny Emrich, Noah Nelson, Luke Tseng, Weiley Liu, and David W. Marshak. Full resolution version here.

Purpose: There are at least 30 distinct types of mammalian retinal ganglion cells, each sensitive to different features of the visual environment, and these can be grouped according to their morphology. One such group, the gamma cells, was identified more than 40 years ago, but their synaptic inputs have never been described. That was the goal of this study.

Methods: The synaptic inputs to a subtype of gamma cell with dendrites ramifying in the outer sublamina of the inner plexiform layer (IPL) of the rabbit retina were identified in a retinal connectome developed using automated transmission electron microscopy.

Results: The gamma cell was always postsynaptic in the IPL, confirming its identity as a ganglion cell. The local synaptic input should produce relatively weak OFF reposnses to stimuli confined to the center of the gamma cell’s receptive field. It typically received only one synapse per bipolar cell from at least 4 types of OFF bipolar cells. Because bipolar cells vary in their response kinetics and contrast sensitivity. each type would provide a small, asynchronous excitatory input. The amacrine cells at the dyad synapses provided only a small amount presynaptic inhibition; reciprocal synapses were observed in only 3 of the 18 ribbon synapses. There was no glycinergic crossover inhibition, another local interaction that would enhance light responses. Local postsynaptic inhibition was somewhat more common; in 6 instances, the bipolar cells presynaptic to the gamma cell or their electrically coupled neighbors also provided input to an amacrine cell that inhibited the gamma cell. The other amacrine cell inputs to the gamma cell should have a much greater impact on the light responses because they are far more numerous. These are from axons and long dendrites of GABAergic amacrine cells, and they provide 60% of all the input. This finding suggests that many types of stimuli in the receptive field surround or outside of the classical receptive field would provide potent inhibition to the gamma cell.

Conclusions: The synaptic inputs rsuggest that gamma cells in rabbit retina would have light responses like their homologs in mouse retina, OFF responses to small stimuli in the receptive field center that are suppressed by a variety of larger stimuli. Thus, they would signal object motion selectively.

Predicting Age-related Changes with High Accuracy using a Pattern Recognition Derived Retinal Ganglion Cell Regression Model

This abstract was presented yesterday, May 7th at the 2017 Association for Research in Vision and Opthalmology (ARVO) meetings in Baltimore, Maryland by Nayuta Yoshioka, Barbara Zangerl, Lisa Nivison-Smith, Sieu Khuu, Bryan W. Jones, Rebecca Pfeiffer, Robert Marc, and Michael Kalloniatis.

Purpose: We recently used pattern recognition analysis to show macula areas can be classified into statistically distinct clusters in accordance to their age-related retinal ganglion cell layer (RGCL) thickness change in a normal population. The aim of this study was to perform a retrospective cross-sectional analysis utilizing a large cohort of patients to establish accuracy of this model and to develop a normative dataset using a 50-year-old equivalent cohort.

Methods: Data was collected from patients seen at the Centre for Eye Health for optic nerve assessment without posterior pole disease. The grid-wise RGCL thickness was obtained from a single eye of each patient via Spectralis OCT macular scan over an 8×8 measurement grid. Measurements for patients outside the 45-54 age range (training cohort) were converted to 50-year-old equivalent value utilizing pattern recognition derived regression model which, in brief, consists of 8×8 grid clustered into 8 distinct classes according to the pattern of RGCL thickness change with age. Accuracy of the predictions was assessed by comparing the training cohort’s measurements to the 45-54 year reference cohort using t-test and one-way ANOVA.

Results: Data were collected from a total 248 patients aged 20 to 78.1 years. 80 patients within this group were aged 45 – 54 and formed the reference cohort (average±SD 49.6±2.83) and the remaining 168 eyes formed the training cohort (average age±SD 50.7±17.34). Converted values for the training set matched those of the reference cohort (average disparity±SD 0.10±0.42µm, range -0.74-1.34µm) and were not significantly different (p > 0.9). Most variability was observed with patients above 70 years of age (average disparity±SD -0.09±1.73µm, range -3.67 to 6.16µm) and central grids corresponding to the fovea (average disparity±SD 0.47±0.72µm, range -0.22 to 1.34µm).

Conclusions: Our regression model for normal age-related RGCL change can accurately convert and/or predict RGCL thickness for individuals in comparison to 50-year-equivalent reference cohort and could allow for more accurate assessment of RGCL thickness and earlier detection of significant loss in the future. Caution may be needed when applying the model in the foveal area or for patients older than 70 years.

Metabolic Impacts of Cigarette Smoke On The Retina of Complement-Compromised Mice

This abstract was presented today, May 8th at the 2017 Association for Research in Vision and Opthalmology (ARVO) meetings in Baltimore, Maryland by Felix Vazquez-Chona, Alex Butler, Emile McKinnon, Baerbel Rohrer, and Bryan W. Jones. Full resolution version here.

Purpose: The interaction between metabolism and the immune system is hypothesized as playing a central role in the pathology of neural diseases including Age-Related Macular Degeneration (AMD). We investigated the effects of cigarette-smoke exposure (CSE) on metabolism of retinal cells in wild-type (wt) mice, and mice deficient for the alternative pathway (complement factor B, CfB) or common terminal pathway (complement component 3, C3).

Methods: Mice were exposed to CSE or room filtered-air (controls) for 6 h/d, 5 d/wk for 6 months. We visualized the metabolism of retinal cells using Computational Molecular Phenotyping (CMP). Retinal cell classification and metabolic adaptation were interrogated using arginine (R), aspartate (D), GABA (γ), glutamate (E), glycine (G), glutathione (J), glutamine (Q), taurine (τ), glutamine synthetase (GS), and cellular retinaldehyde binding protein (CRALBP). Electron microscope mosaics were instrumental in phenotyping metabolic profiles.

Results: CSE C3-/- animals show more severe degenerative indices than CSE WT: retinal pigment epithelium (RPE) exhibited a decreased basalateral infolding area and increased vacuolization; photoreceptors show increased mitochondrial swelling and pyknosis; Müller glia displayed hypertrophy; and the amacrine layer was affected by increased vacuolization. The CfB-/- retina was more resilient to the negative effects of CSE when compared to the WT retina. At the metabolic level, RPE and inner segments of CSE CfB-/- mice displayed modest changes. In contrast, changes in CSE C3-/- and WT retina were dramatic: RPE exhibited decreased CRALBP and elevated R-E-J-τ-γ levels; inner segments showed increased R-D-E-G-J-Q-τ-γ-CRALBP; and Müller glia were found to have decreased levels along the R-D-E-G-J-Q-τ-γ-GS-CRALBP axis.

Conclusions: Increased GABA levels in RPE and photoreceptors are consistent with Müller glia dysfunction. Our metabolic profiling suggests that RPE and Müller glia are vulnerable to CSE-induced oxidative stress. We also find that the potential complement activation status of the retina-RPE-choroid unit highly influences the metabolic response of retinal cells to CSE. As complete blockade of the complement system in the C3-/- model has a more dramatic impact on metabolism of RPE, Müller glia, and photoreceptors than observed in the CfB-/- model, it can be proposed that downstream signaling of the complement system is required for retina health.

Layman Abstract: Metabolism involves a complex circuitry of metabolic pathways, intermediates, and cell-cell interactions. Thus, mapping metabolism with cellular resolution and quantitative power is key to identifying robust biomarkers of disease progression.