Ophthalmopathology in rats with MBP-induced experimental autoimmune encephalomyelitis

Gramlich, Oliver W.; Joachim, Stephanie C.; Gottschling, P. F.; Laspas, Panagoitis; Cuny, C.; Pfeiffer, Norbert; Grus, Franz H.

doi:10.1007/s00417-011-1633-9

Cited by 21 publications

(20 citation statements)

References 54 publications

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“…In mouse, the inner retinal surface consists primarily of neurons, glia, and a robust vasculature. As in other mammals (Stone and Fukuda 1974, Hughes 1975, Wassle, Levick et al 1975, Tiao and Blakemore 1976, Peichl 1992, Gellrich and Gellrich 1996, Gramlich, Joachim et al 2011), these populations have anatomic and histologic characteristics that help distinguish them (see Methods) (Drager and Olsen 1981). Light microscopy of H&E-stained retinal whole-mounts distinguishes among three categories of cells (Figure 1A, B): RGCs, which contain nuclei of diverse sizes that are consistently lightly-stained and have prominent nucleoli (categorized RGC ), vascular endothelial cells, which have elongated nuclei that delineate vessels (categorized VEC ), and a large number of cells containing small, round, and densely-stained nuclei, which represent mostly displaced amacrine cells, but likely also some astrocytes and microglia (hence categorized DAC + ).…”

Section: Resultsmentioning

confidence: 99%

Quantitative measurement of retinal ganglion cell populations via histology-based random forest classification

Hedberg-Buenz

Christopher

Lewis

et al. 2016

Experimental Eye Research

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The inner surface of the retina contains a complex mixture of neurons, glia, and vasculature, including retinal ganglion cells (RGCs), the final output neurons of the retina and primary neurons that are damaged in several blinding diseases. The goal of the current work was two-fold: to assess the feasibility of using computer-assisted detection of nuclei and random forest classification to automate the quantification of RGCs in hematoxylin/eosin (H&E)-stained retinal whole-mounts; and if possible, to use the approach to examine how nuclear size influences disease susceptibility among RGC populations. To achieve this, data from RetFM-J, a semi-automated ImageJ-based module that detects, counts, and collects quantitative data on nuclei of H&E-stained whole-mounted retinas, were used in conjunction with a manually curated set of images to train a random forest classifier. To test performance, computer-derived outputs were compared to previously published features of several well-characterized mouse models of ophthalmic disease and their controls: normal C57BL/6J mice; Jun-sufficient and Jun-deficient mice subjected to controlled optic nerve crush (CONC); and DBA/2J mice with naturally occurring glaucoma. The result of these efforts was development of RetFM-Class, a command-line-based tool that uses data output from RetFM-J to perform random forest classification of cell type. Comparative testing revealed that manual and automated classifications by RetFM-Class correlated well, with 83.2% classification accuracy for RGCs. Automated characterization of C57BL/6J retinas predicted 54,642 RGCs per normal retina, and identified a 48.3% Jun-dependent loss of cells at 35 days post CONC and a 71.2% loss of RGCs among 16-month-old DBA/2J mice with glaucoma. Output from automated analyses was used to compare nuclear area among large numbers of RGCs from DBA/2J mice (n=127,361). In aged DBA/2J mice with glaucoma, RetFM-Class detected a decrease in median and mean nucleus size of cells classified into the RGC category, as did an independent confirmation study using manual measurements of nuclear area demarcated by BRN3A-immunoreactivity. In conclusion, we have demonstrated that histology-based random forest classification is feasible and can be utilized to study RGCs in a high-throughput fashion. Despite having some limitations, this approach demonstrated a significant association between the size of the RGC nucleus and the DBA/2J form of glaucoma.

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Section: Resultsmentioning

confidence: 99%

Quantitative measurement of retinal ganglion cell populations via histology-based random forest classification

Hedberg-Buenz

Christopher

Lewis

et al. 2016

Experimental Eye Research

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“…Procedure for IgG autoantibody staining was performed as previously described [51], [52]. In detail, slices were dewaxed in xylene three times and rehydrated in a sequential ethanol gradient (100%, 100%, 96%, 96%, 70%, each 5 min) to Aqua dest.…”

Section: Methodsmentioning

confidence: 99%

Enhanced Insight into the Autoimmune Component of Glaucoma: IgG Autoantibody Accumulation and Pro-Inflammatory Conditions in Human Glaucomatous Retina

et al. 2013

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BackgroundThere is accumulating evidence that autoimmune components, such as autoantibodies and autoantibody depositions, play a role in the pathogenesis of neurodegenerative diseases like Alzheimeŕs disease or Multiple Sclerosis. Due to alterations of autoantibody patterns in sera and aqueous humor, an autoimmune component is also assumed in the pathogenesis of glaucoma, a common reason for irreversible blindness worldwide. So far there has been no convincing evidence that autoantibodies are accumulated in the retina of glaucoma patients and that the local immune homeostasis might be affected.Methods and ResultsSix human glaucomatous donor eyes and nine samples from donors with no recorded ocular disease were included. Antibody microarrays were used to examine the patterns of pro-inflammatory proteins and complement proteins. Analysis of TNF-α and interleukin levels revealed a slight up-regulation exclusively in the glaucomatous group, while complement protein levels were not altered. IgG autoantibody accumulations and/or cellular components were determined by immunohistology (n = 4 per group). A significantly reduced number of retinal ganglion cells was found in the glaucomatous group (healthy: 104±7 nuclei/mm, glaucoma: 67±9 nuclei/mm; p = 0.0007). Cell loss was accompanied by strong retinal IgG autoantibody accumulations, which were at least twice as high as in healthy subjects (healthy: 5.0±0.5 IgG deposits/100 cells, glaucoma: 9.4±1.9 IgG deposits/100 cells; p = 0.004). CD27+ cells and CD27+/IgG+ plasma cells were observed in all glaucomatous subjects, but not in controls.ConclusionThis work provides serious evidence for the occurrence of IgG antibody deposition and plasma cells in human glaucomatous retina. Moreover, the results suggest that these IgG deposits occurred in a pro-inflammatory environment which seems to be maintained locally by immune-competent cells like microglia. Thereby, glaucoma features an immunological involvement comparable to other neurodegenerative diseases, but also shows a multifactorial pathomechanism, which diverges and might be linked to the specific nature of both eye and retina.

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“…For this purpose, Lewis rats were systemically immunized with biomarkers coming from clinical studies. The animals developed antibodies against the proteins, for example HSP60 (heat shock protein 60) [91][92][93] or MBP (myelin basic protein), 94 and elevated antibody reactions caused a distinct RGC loss in the retina. The immunization with MBP not only causes neuron loss in the RGC layer, but also triggers antibody reactivity against ocular tissue (Gramlich OW, et al IOVS 2011;52:ARVO E-Abstract 2928 94 ).…”

Section: Pre-immune and Immune Events: Immunoproteomics And Its Possimentioning

confidence: 99%

Molecular Biomarkers for Glaucoma

Beykin

Goldberg

2019

Curr Ophthalmol Rep

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Ophthalmopathology in rats with MBP-induced experimental autoimmune encephalomyelitis

Cited by 21 publications

References 54 publications

Quantitative measurement of retinal ganglion cell populations via histology-based random forest classification

Quantitative measurement of retinal ganglion cell populations via histology-based random forest classification

Enhanced Insight into the Autoimmune Component of Glaucoma: IgG Autoantibody Accumulation and Pro-Inflammatory Conditions in Human Glaucomatous Retina

Molecular Biomarkers for Glaucoma

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