Imaging Retinal Ganglion Cell Death and Dysfunction in Glaucoma

Hemifield-based analysis of pattern electroretinography in normal subjects and patients with preperimetric glaucoma

This prospective cross-sectional study investigated the visual function of preperimetric glaucoma (PPG) patients based on hemifield (HF) pattern electroretinogram (PERG) amplitudes. Thirty-two (32) normal subjects and 33 PPG patients were enrolled in control and PPG groups, respectively. All of the participants had undergone full ophthalmic examinations, including spectral-domain optical coherence tomography (SD-OCT), visual field (VF) examination and pattern electroretinography (PERG). The PERG parameters along with the HF ratios of SD-OCT and PERG were compared between the control and PPG groups. Pairwise Pearson's correlation coefficients and linear regression models were fitted to investigate the correlations. The PERG N95 amplitudes were significantly lower in the PPG group (P < 0.001). The smaller/larger HF N95 amplitude ratio of the PPG group was found to be smaller than that of the control group (0.73 ± 0.20 vs. 0.86 ± 0.12; P = 0.003) and showed positive correlations with affected HF average ganglion cell-inner plexiform layer (GCIPL) thickness (r = 0.377, P = 0.034) and with average GCIPL thickness (r = 0.341, P = 0.005). The smaller/larger HF N95 amplitude ratio did not significantly change with age (β =  - 0.005, P = 0.195), whereas the full-field N95 amplitude showed a negative correlation with age (β =  - 0.081, P < 0.001). HF analysis of PERG N95 amplitudes might be particularly useful for patients with early glaucoma.

Associations between steady-state pattern electroretinography and estimated retinal ganglion cell count in glaucoma suspects

Purpose

To estimate retinal ganglion cell (RGC) count in glaucoma suspects (GS) and ascertain its relationships with steady-state pattern electroretinography (ssPERG) parameters.

Methods

In this prospective cross-sectional study, 22 subjects (44 eyes) were recruited at the Manhattan Eye, Ear, and Throat Hospital. Subjects underwent complete eye examinations, optical coherence tomography, standard automated perimetry, and ssPERG testing. Eyes were divided into two groups based upon clinical data: healthy subjects and GS. RGC count was estimated using the combined structure–function index.

Results

Estimated RGC count, average retinal nerve fiber layer thickness (ARNFLT), and average ganglion cell layer and inner plexiform layer thickness (GCIPLT) were reduced in GS eyes (p ≤ 0.001 for all parameters). Pearson correlations revealed that ssPERG magnitude and magnitudeD correlated with ARNFLT (r ≥ 0.53, p < 0.001), GCIPLT (r > 0.38, p < 0.011), and estimated RGC count (r > 0.46, p < 0.002). Six mediation analyses revealed that estimated RGC count mediated the relationships among ssPERG parameters, ARNFLT, and GCIPLT.

Conclusion

Steady-state PERG parameters demonstrated linear correlations with estimated RGC count. The associations among ssPERG parameters and structural measures were mediated by estimated RGC count.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10633-022-09869-9.

Differential susceptibility of retinal ganglion cell subtypes against neurodegenerative diseases

Retinal ganglion cells (RGCs) are essential to propagate external visual information from the retina to the brain. Death of RGCs is speculated to be closely correlated with blinding retinal diseases, such as glaucoma and traumatic optic neuropathy (TON). Emerging innovative technologies have helped refine and standardize the classification of RGCs; at present, they are classified into more than 40 subpopulations in mammals. These RGC subtypes are identified by a combination of anatomical morphologies, electrophysiological functions, and genetic profiles. Increasing evidence suggests that neurodegenerative diseases do not collectively affect the RGCs. In fact, which RGC subtype exhibits the strongest or weakest susceptibility is hotly debated. Although a consensus has not yet been reached, it is certain that assorted RGCs display differential susceptibility against irreversible degeneration. Interestingly, a single RGC subtype can exhibit various vulnerabilities to optic nerve damage in diverse injury models. Thus, elucidating how susceptible RGC subtypes are to various injuries can protect vulnerable RGCs from damage and improve the possibility of preventing and treating visual impairment caused by neurodegenerative diseases. In this review, we summarize in detail the progress and status quo of research on the type-specific susceptibility of RGCs and point out current limitations and the possible directions for future research in this field.

Structure-function models for estimating retinal ganglion cell count using steady-state pattern electroretinography and optical coherence tomography in glaucoma suspects and preperimetric glaucoma: an electrophysiological pilot study

PURPOSE

To derive and validate structure-function models for estimating retinal ganglion cell (RGC) count using optical coherence tomography (OCT) and steady-state pattern electroretinography (ssPERG) parameters in glaucoma suspects (GS) and preperimetric glaucoma (PPG).

METHODS

In this prospective cross-sectional study, 25 subjects (50 eyes) were recruited at the Manhattan Eye, Ear, and Throat Hospital. Subjects underwent comprehensive eye examinations, OCT, standard automated perimetry (SAP), and ssPERG testing. Eyes were divided into three groups based on the Global Glaucoma Staging System: healthy (N = 30), GS (N = 10), and PPG (N = 10) eyes. The combined structure-function index (CSFI), which estimates retinal ganglion cell count (eRGC_CSFI) from SAP and OCT parameters, was calculated in each study subject. Two prediction formulas were derived using a generalized linear mixed model (GLMM) to predict eRGC_CSFI from ssPERG parameters, age, and average retinal nerve fiber layer thickness (ARNFLT) in 30 eyes selected at random (training group). GLMM predicted values were cross-validated with the remaining 20 eyes (validation group).

RESULTS

The ARNFLT, ssPERG parameters magnitude (Mag) and magnitudeD (MagD), and eRGC_CSFI were significantly different among study groups (ANOVA p ≤ 0.001). Pearson correlations demonstrated significant associations among ARNFLT, ssPERG parameters, and eRGC_CSFI (r² ≥ 0.31, p < 0.001). Two GLMMs predicted eRGC_CSFI from Mag (eRGC_Mag) and MagD (eRGC_MagD), respectively, with significant equations (F(3,18), F(3,19) ≥  58.37, R² = 0.90, p < 0.001). eRGC_Mag and eRGC_MagD in the validation group (R² = 0.89) correlated with eRGC_CSFI similarly to the training group. Multivariate pairwise comparisons revealed that eRGC_Mag and eRGC_MagD distinguished between healthy, GS, and PPG eyes (p ≤ 0.035), whereas independent Mag, MagD, and ARNFLT measures did not distinguish between GS and PPG eyes.

CONCLUSION

This pilot study offers the first combined structure-function models for estimating RGC count using ssPERG parameters. RGC counts estimated with these models were generalizable, strongly associated with CSFI estimates, and performed better than individual ssPERG and OCT measures in distinguishing healthy, GS, and PPG eyes.

A Review of Potential Novel Glaucoma Therapeutic Options Independent of Intraocular Pressure

Glaucoma, a progressive optic neuropathy characterized by retinal ganglion cell degeneration and visual field loss, is the leading cause of irreversible blindness worldwide. Intraocular pressure (IOP) is presently the only modifiable risk factor demonstrated to slow or halt disease progression; however, glaucomatous damage persists in almost 50% of patients despite significant IOP reduction. Many studies have investigated the non-IOP-related risk factors that contribute to glaucoma progression as well as interventions that can prevent or delay glaucomatous neurodegeneration and preserve vision throughout life, independently of IOP. A vast number of experimental studies have reported effective neuroprotection in glaucoma, and clinical studies are ongoing attempting to provide strong evidence of effectiveness of these interventions. In this review, we look into the current understanding of the pathophysiology of glaucoma and explore the recent advances in non-IOP related strategies for neuroprotection and neuroregeneration in glaucoma.

Detecting retinal neurodegeneration in people with diabetes: Findings from the UK Biobank

Importance

Efforts are underway to incorporate retinal neurodegeneration in the diabetic retinopathy severity scale. However, there is no established measure to quantify diabetic retinal neurodegeneration (DRN).

Objective

We compared total retinal, macular retinal nerve fiber layer (mRNFL) and ganglion cell-inner plexiform layer (GC-IPL) thickness among participants with and without diabetes (DM) in a population-based cohort.

Design/setting/participants

Cross-sectional analysis, using the UK Biobank data resource. Separate general linear mixed models (GLMM) were created using DM and glycated hemoglobin as predictor variables for retinal thickness. Sub-analyses included comparing thickness measurements for patients with no/mild diabetic retinopathy (DR) and evaluating factors associated with retinal thickness in participants with and without diabetes. Factors found to be significantly associated with DM or thickness were included in a multiple GLMM.

Exposure

Diagnosis of DM was determined via self-report of diagnosis, medication use, DM-related complications or glycated hemoglobin level of ≥ 6.5%.

Main outcomes and measures

Total retinal, mRNFL and GC-IPL thickness.

Results

74,422 participants (69,985 with no DM; 4,437 with DM) were included. Median age was 59 years, 46% were men and 92% were white. Participants with DM had lower total retinal thickness (-4.57 μm, 95% CI: -5.00, -4.14; p<0.001), GC-IPL thickness (-1.73 μm, 95% CI: -1.86, -1.59; p<0.001) and mRNFL thickness (-0.68 μm, 95% CI: -0.81, -0.54; p<0.001) compared to those without DM. After adjusting for co-variates, in the GLMM, total retinal thickness was 1.99 um lower (95% CI: -2.47, -1.50; p<0.001) and GC-IPL was 1.02 μm lower (95% CI: -1.18, -0.87; p<0.001) among those with DM compared to without. mRNFL was no longer significantly different (p = 0.369). GC-IPL remained significantly lower, after adjusting for co-variates, among those with DM compared to those without DM when including only participants with no/mild DR (-0.80 μm, 95% CI: -0.98, -0.62; p<0.001). Total retinal thickness decreased 0.40 μm (95% CI: -0.61, -0.20; p<0.001), mRNFL thickness increased 0.20 μm (95% CI: 0.14, 0.27; p<0.001) and GC-IPL decreased 0.26 μm (95% CI: -0.33, -0.20; p<0.001) per unit increase in A1c after adjusting for co-variates. Among participants with diabetes, age, DR grade, ethnicity, body mass index, glaucoma, spherical equivalent, and visual acuity were significantly associated with GC-IPL thickness.

Conclusion

GC-IPL was thinner among participants with DM, compared to without DM. This difference persisted after adjusting for confounding variables and when considering only those with no/mild DR. This confirms that GC-IPL thinning occurs early in DM and can serve as a useful marker of DRN.

Three-dimensional Neuroretinal Rim Thickness and Visual Fields in Glaucoma: A Broken-stick Model

Supplemental Digital Content is available in the text.

Precis:

In open-angle glaucoma, when neuroretinal rim tissue measured by volumetric optical coherence tomography (OCT) scans is below a third of the normal value, visual field (VF) damage becomes detectable.

Purpose:

To determine the amount of neuroretinal rim tissue thickness below which VF damage becomes detectable.

Methods:

In a retrospective cross-sectional study, 1 eye per subject (of 57 healthy and 100 open-angle glaucoma patients) at an academic institution had eye examinations, VF testing, spectral-domain OCT retinal nerve fiber layer (RNFL) thickness measurements, and optic nerve volumetric scans. Using custom algorithms, the minimum distance band (MDB) neuroretinal rim thickness was calculated from optic nerve scans. “Broken-stick” regression was performed for estimating both the MDB and RNFL thickness tipping-point thresholds, below which were associated with initial VF defects in the decibel scale. The slopes for the structure-function relationship above and below the thresholds were computed. Smoothing curves of the MDB and RNFL thickness covariates were evaluated to examine the consistency of the independently identified tipping-point pairs.

Results:

Plots of VF total deviation against MDB thickness revealed plateaus of VF total deviation unrelated to MDB thickness. Below the thresholds, VF total deviation decreased with MDB thickness, with the associated slopes significantly greater than those above the thresholds (P<0.014). Below 31% of global MDB thickness, and 36.8% and 43.6% of superior and inferior MDB thickness, VF damage becomes detectable. The MDB and RNFL tipping points were in good accordance with the correlation of the MDB and RNFL thickness covariates.

Conclusions:

When neuroretinal rim tissue, characterized by MDB thickness in OCT, is below a third of the normal value, VF damage in the decibel scale becomes detectable.