Diabetes Exacerbates the Intraocular Pressure-Independent Retinal Ganglion Cells Degeneration in the DBA/2J Model of Glaucoma

Abstract

Purpose: Glaucoma is a multifactorial disease, causing retinal ganglion cells (RGCs) and optic nerve degeneration. The role of diabetes as a risk factor for glaucoma has been postulated but still not unequivocally demonstrated. The purpose of this study is to clarify the effect of diabetes in the early progression of glaucomatous RGC dysfunction preceding intraocular pressure (IOP) elevation, using the DBA/2J mouse (D2) model of glaucoma.

Methods: D2 mice were injected with streptozotocin (STZ) obtaining a combined model of diabetes and glaucoma (D2 + STZ). D2 and D2 + STZ mice were monitored for weight, glycemia, and IOP from 3.5 to 6 months of age. In addition, the activity of RGC and outer retina were assessed using pattern electroretinogram (PERG) and flash electroretinogram (FERG), respectively. At the end point, RGC density and astrogliosis were evaluated in flat mounted retinas. In addition, Müller cell reactivity was evaluated in retinal cross-sections. Finally, the expression of inflammation and oxidative stress markers were analyzed.

Results: IOP was not influenced by time or diabetes. In contrast, RGC activity resulted progressively decreased in the D2 group independently from IOP elevation and outer retinal dysfunction. Diabetes exacerbated RGC dysfunction, which resulted independent from variation in IOP and outer retinal activity. Diabetic retinas displayed decreased RGC density and increased glial reactivity given by an increment in oxidative stress and inflammation.

Conclusions: Diabetes can act as an IOP-independent risk factor for the early progression of glaucoma promoting oxidative stress and inflammation-mediated RGC dysfunction, glial reactivity, and cellular death.

Figure 1.

Longitudinal evaluation of glycemia (A) and weight (B) as parameters describing the progressive diabetic status in D2 (black dots) and D2 + STZ (red squares) mice. Data are expressed as mean ± SEM of n = 10 mice per group, spline-fitted (continuous line) with 95% confidence interval (fading area) and analyzed using RM-ANOVA. (C) Longitudinal assessment of individual IOP variations. Data are expressed as mean ± SEM of n = 10, and spline-fitted with 95% confidence interval (fading area). Data were analyzed using GEE including the effect of glycemia and weight as covariates.

Figure 2.

Longitudinal analysis of time-dependent variations in RGC activity measured with PERG and relative outer retinal activity using FERG. (A) Representative PERG and FERG waveforms of D2 (black) and D2 + STZ (red) mice deriving from baseline, intermediate, and end point recordings during the analyzed time-window. (B, C) Follow-up of PERG response over-time through the assessment of PERG amplitude and PERG latency in both groups. (D, E) Longitudinal assessment of FERG amplitude and FERG latency. Data are expressed as mean ± SEM of n = 10, considering the average of individual mice contralateral eyes recordings, and spline-fitted with 95% confidence interval (fading area). PERG response was analyzed using GEE including IOP and FERG response parameters as covariates.

Figure 3.

Immunofluorescence staining of RBPMS positive cells for the analysis of RGC density. (A) Representative images of RBPMS staining in peripheral and central areas of D2 and D2 + STZ mice retinas at the follow-up end point. Scale bar 100 µm. (B) Analysis of RBPMS-positive cell density in D2 (black box) and D2 + STZ (red box) groups, differentially sampled from the peripheral and central areas of the retina. Data derive from the average of four radial opposite sampling sites per area in each retina. Box plots describe the statistical distribution of n = 4 independent retinas. Data were analyzed using 2-way ANOVA with Bonferroni post hoc test. *P < 0.05.

Figure 4.

GFAP immunostaining in whole-mount retinas and retinal cross-sections for the analysis of astrocytes and Müller cells reactivity at the follow-up end point. (A) Representative images of whole-mount retina of D2 and D2 + STZ mice immunostained for GFAP showing retinal astrocytes. Scale bar 500 µm. Insets show higher magnifications of boxed areas for the evaluation of astrocyte morphology and branching. Scale bar 100 µm. (B) Densitometric analysis of GFAP immunostaining in D2 (black box) and D2 + STZ mice (red box). Mean gray levels derive from the average of four radial opposite sampling sites per area in each retina. Box plots describe the statistical distribution of n = 4 independent retinas. Data were normalized for D2 group and analyzed using two-tailed t-test. **P < 0.01. (C) Representative images of GFAP immunostaining in retinal cross- section of D2 and D2 + STZ mice retinas highlighting activated Müller cells. Scale bar 100 µm.

Figure 5.

Quantitative analysis of the expression of oxidative stress (HO-1 and SOD-2) (A) and inflammation-related (IL-6, TNFα, and IL-10) (B) markers in D2 (black box) and D2 + STZ mice (red box) retinas at the follow-up end point. Box plots describe the statistical distribution of n = 4 independent retinas. Differences between groups were tested using two-tailed t-test. *P < 0.05.