Retinal Ganglion Cells Thinning in Eyes With Nonproliferative Idiopathic Macular Telangiectasia Type 2A

Abstract

Purpose.: To analyze the changes in retinal ganglion cells (RGCs) in eyes with nonproliferative macular telangiectasia type 2A (MacTel), by evaluating macular ganglion cell-inner plexiform layer (GCIPL) thickness and macular retinal nerve fiber layer (RNFL) thickness in comparison to age-matched healthy volunteers.

Methods.: We performed a retrospective analysis of 99 eyes (53 subjects) with nonproliferative MacTel who underwent fundus fluorescein angiography and spectral domain optical coherence tomography using Cirrus HD-OCT. We also included 44 eyes of 33 age-matched healthy Indian volunteers as control group. Average, minimum, and sectoral GCIPL and RNFL thicknesses were collected. Comparison of GCIPL and RNFL thicknesses between MacTel and control groups was performed using Wilcoxon rank sum test.

Results.: Eighty-eight eyes of 47 MacTel subjects were included after ensuring good quality of the retinal layers' segmentation. Macular GCIPL thickness was constantly and diffusely reduced in MacTel eyes compared with controls (P < 0.0001 for each GCIPL sector). The mean reduction in “average” GCIPL thickness was 11%, and the mean reduction in “minimum” GCIPL thickness was 23%. Similarly, macular RNFL thickness was diffusely reduced in MacTel eyes compared with controls (P < 0.0001 for each RNFL sector), with 13% of mean reduction.

Conclusions.: Our study demonstrated that in eyes with nonproliferative MacTel type 2A there was significant and consistent RGCs degeneration, leading to diffuse thinning of RGCs' dendrites, cell bodies, and axons. These findings are suggestive of neurodegeneration in MacTel type 2A.

Introduction

Macular telangiectasia type 2A (MacTel) is a neurodegenerative retinal disease characterized by alterations in macular capillary network, neurosensory atrophy, and occasional subretinal neovascularization.^1–4 Characteristic phenotypic findings have been identified using a variety of imaging techniques, such as spectral-domain optical coherence tomography (SD-OCT), allowing an improved understanding of this disease.^5–8 Typical SD-OCT features include widening of the foveal pit, outer retinal damage, hyperreflective intra- or subretinal lesions, hyporeflective intraretinal cavities, and localized retinal thickening associated with subretinal neovascularization.^9,10 Although the condition appears to be primarily neurodegenerative in nature, its pathogenesis is still unclear. Progressive retinal thinning and macular pigment loss are known phenomena in MacTel. However, it is understood that the Müller cells degeneration plays an important role.¹¹ In addition, neural retinal degeneration may precede typical vascular changes seen in MacTel eyes.³ 

The ganglion cell layer is located near the surface of the retina and consists of the nuclei of retinal ganglion cells (RGCs). Retinal nerve fiber layer (RNFL) contains axons of the RGCs. The inner plexiform layer is deeper than the ganglion cell layer, and contains dendrites of the RGCs. Recent advances in SD-OCT technology have enabled intraretinal segmentation to better assess individual retinal layers compared with total macular thickness.¹² For example, the Cirrus HD-OCT ganglion cell analysis (GCA) algorithm (Carl Zeiss Meditec, Dublin, CA, USA) can successfully detect and measure the thickness of the macular ganglion cell-inner plexiform layer (GCIPL) without including the RNFL.¹³ The reproducibility of GCIPL thickness measurements using the Cirrus HD-OCT GCA algorithm has been reported to be highly satisfactory.^13,14 

Considering that neurodegeneration is a typical sign of MacTel, the present study was designed to specifically analyze morphologic changes in RGCs in eyes with MacTel in comparison with age-matched healthy volunteers. In particular, the study addressed the changes in macular GCIPL and RNFL thicknesses using the Cirrus HD-OCT. 

Methods

Study Population

We retrospectively reviewed charts and SD-OCT images from 53 patients (99 eyes) diagnosed with nonproliferative MacTel, seen between January 2013 and December 2013 at the L V Prasad Eye Institute, Hyderabad, India. Prior approval from the institutional review board of the Institute was taken and informed consent was obtained from each study subject. This study was conducted in accordance with the tenets of the Declaration of Helsinki. 

All participants included in the study underwent a comprehensive ophthalmic examination, as well as indirect ophthalmoscopy, fundus fluorescein angiography (FFA), and SD-OCT. Macular telangectasia type 2A was diagnosed based on typical clinical findings such as lack of foveolar reflex, reduced retinal transparency (graying), presence of superficial retinal crystalline deposits, and ectatic capillaries, predominantly in the perifoveal temporal side. Fundus fluorescein angiography was performed in all cases to confirm the diagnosis. Exclusion criteria included MacTel associated with subretinal neovascularization, high myopia greater than −6 diopters (D) or hyperopia greater than +3 D, poor image quality, history of retinal surgery, and any other associated retinal pathology. A control group of 44 eyes of 33 age-matched healthy volunteers with no ocular disease and no high refractive error (more than −6 D or +3 D) was included for comparison. 

OCT Image Acquisition and Processing

Spectral-domain OCT scans were obtained by using the Cirrus HD-OCT after pupillary dilation. The Macular Cube 512 × 128 scan protocol was used for all subjects. The protocol performs 512 horizontal B-scans comprising 200 A-scan per B-scan over 1024 samplings within a cube measuring 6 × 6 × 2 mm centered on the fovea. Images with signal strength less than six and those with visible eye motion or blinking artifacts were considered of poor quality and discarded. Any scan with an apparent segmentation failure detected during this process was excluded from the study. 

The GCA algorithm was applied to the Macular Cube scans. The GCA algorithm identifies the outer boundary of the RNFL and the outer boundary of the IPL and provides measurements of GCIPL thickness. The average, minimum (lowest GCIPL thickness over a single meridian crossing the annulus), and sectoral (superotemporal, superior, superonasal, inferonasal, inferior, inferotemporal) GCIPL thicknesses were measured in an elliptical annulus around the fovea (dimensions: vertical inner and outer radius of 0.5 and 2.0 mm, horizontal inner and outer radius of 0.6 and 2.4 mm, respectively; Fig. 1). The GCA algorithm measures the mean GCIPL thickness for each sector, compares them with the internal normative database of the device, and generates a thickness map, a deviation map, and a color-coded significance map. Measurements were displayed in green for normal range (P = 5%–95%), in yellow for borderline (1% < P < 5%), and in red for outside the normal range (P < 1%). Similar parameters were available for the macular RNFL thickness as well; because the internal database lacks normative data for macular RNFL thicknesses, data from the control group was used for comparison. Ganglion cell-inner plexiform layer and RNFL thicknesses data was exported as extensible markup language format using the built-in software for analysis. 

Figure 1

 

Macular GCIPL report shows thickness map (top), deviation map (middle), and color-coded map (center), in comparison to age-matched normative internal database, in various sectors. Bottom image shows the GCIPL segmentation on B scan.

Statistical Analysis

Descriptive statistics included mean and SD for normally distributed continuous variables and median and interquartile range (IQR) for nonnormally distributed variables. As both eyes of 41 subjects were included for analysis, the correlation between the two eyes of the same subject was adjusted using generalized estimating equations (GEE) during the calculation of parameters. Distribution of continuous variables was evaluated using Shapiro-Wilk test because of nonnormative distribution of data. Comparison of the GCIPL and RNFL thicknesses between MacTel and control groups was performed using Wilcoxon rank sum test. ANOVA was used to evaluate changes in GCIPL thickness in different stages of the disease. Statistical analyses were performed using commercial software (Stata data analysis and statistical software, version 12.1; StataCorp, College Station, TX, USA). A P value of less than 0.05 was considered statistically significant. 

Results

Out of 99 eyes (53 patients), 88 eyes of 47 patients with MacTel type 2A were included in the study; 11 eyes from six patients were excluded because of blinking or segmentation failures on SD-OCT analysis. Twenty-five were males and 22 were females, with mean age of 56 years (range, 41–73 years). Mean best-corrected visual acuity (BCVA) was 0.39 ± 0.37 logMAR (Snellen equivalent, 20/50), and mean spherical equivalent was 0.40 ± 1.36 D. According to Gass-Blodi classification of MacTel 2A,² 31 eyes were classified as stage 2, 37 eyes as stage 3, and 20 eyes as stage 4. The control group included 44 eyes of 33 Indian healthy volunteers (19 males and 14 females) with mean age of 53 years (range, 42–77 years). There was no significant difference in terms of age (P = 0.8), age-distribution (P = 0.22), sex (P = 0.63), or mean spherical equivalent (P = 0.2) between study and control groups. Mean signal strength of SD-OCT images for both groups was 7.7 ± 1.31. 

While comparing study data with the internal normative database of the device, we found that the average GCIPL thickness was within normal limits (5%–100%) in 52%, borderline (1%–5%) in 14%, and outside normal limits (<1%) in 34% of MacTel eyes (Fig. 2). In addition, the minimal GCIPL thickness was within normal limits in 28%, borderline in 14%, and outside normal limits in 58% of MacTel eyes. Sectoral subanalysis showed variability in GCIPL thickness in all sectors compared with the internal normative database. Abnormal GCIPL thickness was present in all sectors in almost one-third of the eyes; however, the most affected sectors were the superotemporal and the inferotemporal with 45% and 36% of abnormality rate, respectively. 

Figure 2

 

Distribution of average, minimum, and sectoral retinal GCIPL thickness among eyes with idiopathic macular telangiectasia in comparison to internal normative database. Values within the normal range in green (P = 5%–95%), borderline values in yellow (1% < P <5%), and values outside the normal range in red (P < 1%). Average and minimal GCIPL thicknesses were outside the normal range (red, P < 1%) in 34% and 58% of the subjects, respectively. Abnormal GCIPL thickness was present in all sectors in almost one-third of the subjects; however, the most affected sectors were the superotemporal and the inferotemporal, with 45% and 36% of abnormality rate, respectively. STQ, superotemporal quadrant; ITQ, inferotemporal quadrant; INQ, inferonasal quadrant; SNQ, superonasal quadrant.

While comparing study data with the control group of normal Indian volunteers, we found that average, minimum, and sectoral GCIPL thicknesses were constantly reduced in MacTel eyes (P < 0.0001, Table 1). The mean reduction in “average” and “minimum” GCIPL thickness in MacTel group was 11%, and 23%, respectively. ANOVA did not show any significant difference (P > 0.05) in GCIPL thickness among different stages of MacTel 2A. In addition, average, minimum, and sectoral RNFL thicknesses were reduced in MacTel eyes compared with controls (P < 0.0001) with 13% of average median reduction (Table 2). 

Table 1

 

Comparison of GCIPL Thickness Between Study Group and Age-Matched Control Group

GCIPL Location	Study Group, μm	Control Group, μm	Difference, μm	Difference	P Value
Average	73 (63.5, 80)	82 (76, 88)	−9.0	−11.0%	<0.0001
Minimum	60 (36.5, 72.5)	78 (68, 85)	−18.0	−23.1%	<0.0001
Superotemporal	71 (63.5, 77)	79 (76, 85.5)	−8.0	−10.1%	<0.0001
Superior	71.5 (61.5, 82)	83 (77, 88)	−11.5	−13.9%	<0.0001
Superonasal	74 (69, 83)	85.5 (79, 91)	−11.5	−13.6%	<0.0001
Inferonasal	75 (68, 82)	85.5 (80, 89)	−9.5	−11.1%	<0.0001
Inferior	71.5 (60.5, 79)	82 (75, 87)	−11.5	−14.0%	<0.0001
Inferotemporal	72.5 (64, 79)	79 (75, 89)	−6.5	8.2%	<0.0001

 All values are shown as median (first quartile, third quartile).

Table 2

 

Comparison of RNFL Between Study Group and Age-Matched Group

RNFL Location	Study Group, μm	Control Group, μm	Difference, μm	Difference	P Value
Average	26 (22, 31)	30 (29, 33)	−4.0	−13.3%	<0.0001
Minimum	11 (8, 13)	13 (12, 16)	−2.0	−15.4%	<0.0001
Superotemporal	19 (18, 23)	21 (20, 24)	−2.0	−9.5%	<0.0001
Superior	25 (21, 33)	32.5 (30, 37)	−7.5	−23.4%	<0.0001
Superonasal	26 (23, 33)	34 (31, 39)	−8	−23.5%	<0.0001
Inferonasal	29 (25, 35)	33.5 (33, 40)	−4.5	−13.4%	<0.0001
Inferior	29.5 (25, 36)	35 (33, 39)	−5.5	−15.7%	<0.0001
Inferotemporal	22 (20, 25)	25 (23, 27)	−3	−12.0%	<0.0001

 All values are shown as median (first quartile, third quartile).

Distribution of average, minimum, and sectoral GCIPL thicknesses of the control group compared with the internal normative database is shown in Figure 3. Ganglion cell-inner plexiform layer thicknesses were within normal limits in the majority of the cases (69%–83%), while in approximately 10% of the cases they were outside normal limit. Considering that the internal normative database included only 11 Indian subjects, such differences among control group and internal normative database may be related to ethnic variation. 

Figure 3

 

Distribution of average, minimum, and sectoral retinal GCIPL thickness among control group of 44 eyes of 33 age-matched healthy volunteers in comparison to internal normative database. Values within the normal range in green (P = 5%–95%), borderline values in yellow (1% < P < 5%), and values outside the normal range in red (P < 1%). The figure shows that GCIPL thicknesses were within normal range in the majority of the cases (69%–83%), while in approximately 10% of the cases they were outside normal limit. This was likely related to ethnic variation between the two groups.

The average retinal thickness had a median value of 263 and 271 μm in the study and control groups, respectively (P = 0.008); median value of the first quartile was 251 and 262 μm in the study and control groups, respectively; median value of the third quartile was 272 and 281 μm in the study and control groups, respectively. In terms of average, minimum, and sectoral outer retinal thicknesses, there were no significant differences between the study and control groups (Table 3). 

Table 3

 

Comparison of Outer Retinal Thickness Between Study Group and Age-Matched Control Group

Outer Retinal Location	Study Group, μm	Control Group, μm	Difference, μm	Difference	P Value
Average	120.5 (116, 130)	124 (119, 126)	−3.5	−2.8%	0.18
Minimum	111 (106, 116)	118 (113, 123)	−7.0	−5.9%	0.04
Superotemporal	122 (116, 131)	123 (118, 126)	−1.0	−0.8%	0.6
Superior	124 (119, 134)	124 (121, 129)	0.0	0%	0.15
Superonasal	121 (114, 127)	125 (118, 129)	−4.0	−3.2%	0.15
Inferonasal	118 (113, 125)	124 (115, 128)	−6.0	−4.8%	0.03
Inferior	118 (113, 126)	122 (117, 126)	−4.0	−3.2%	0.09
Inferotemporal	121 (114, 127)	122 (118, 126)	−1.0	−0.8%	0.39

 All values are shown as median (first quartile, third quartile).

Discussion

In the present study, the eyes with nonproliferative stage of MacTel had significant RGCs thinning in comparison with both internal normative database of the device and age-matched healthy Indian controls. Ganglion cell bodies and dendrites were abnormally thinned in all sectors within the elliptical annulus around the fovea; the average GCIPL reduction was 11% and the thinnest point was on average 23% thinner compared with controls. More than one-third of the eyes had abnormal GCIPL thinning within the macula, especially in the temporal sector (54% of the cases). In addition, we also found diffuse thinning of ganglion cell axons within the macula, with a 13% average RNFL reduction compared with controls. 

Retinal ganglion cells encompass three layers of the retina: the RNFL with ganglion cell axons, the ganglion cell layer with ganglion cell bodies, and the IPL with cell dendrites. After an insult to RGCs a progressive dendritic shrinkage happens first, followed by loss of axons and cell bodies.¹⁵ Therefore, as RGCs die, the GCIPL (which includes dendrites and cell bodies) becomes thinner. With advanced OCT technologies and software, it is now possible to measure GCIPL thickness in vivo and also estimate the loss of RGCs quantitatively.¹⁶ So far, the GCA algorithm of the Cirrus HD-OCT has been used for diagnosing and monitoring loss of RGCs in glaucoma^17,18 and optic neuropathies.^19,20 There is also evidence of RGCs degeneration in retinal dystrophies. For example, in animal models of light-induced retinal degeneration, it has been documented that RGCs loss is a consequence of RGC axonal compression by the inner retinal vessels, which were displaced and surrounded by retinal pigment epithelial cells.²¹ The death of RGCs in retinal pathologies is still a topic for discussion; for example, transneuronal degeneration after photoreceptor loss or vascular occlusion has been proposed as the possible mechanism in retinitis pigmentosa.²² Although MacTel shares structural features with retinal dystrophies, it is considered as a neurodegenerative disease rather than a retinal dystrophy. In MacTel, photoreceptor loss occurs later in the disease course, while the primary degeneration involves Müller cells, affecting the neurosensory retina. After describing Müller's cell depletion by histopathology in the macula of a MacTel type 2A case in 2010,¹¹ Powner et al.²³ recently correlated histopathologic changes with clinical data in a second MacTel case. They found that macular pigment depletion closely matched the loss of Müller cells, and speculated that the two features might be clinically related. 

Histopathology findings supported the emerging view that MacTel is not primarily a vascular disease, as the name suggests, but rather a degenerative condition affecting primarily glial cells and neurons. In 1980, Green et al.²⁴ published a light and electron microscopic study of an eye with confirmed MacTel type 2A. Besides reporting vascular changes and edema in the temporal neurosensory retina, they also reported that some RGCs were undergoing degeneration. However, their findings were questionable since they did not compare the data with age-matched controls. Unfortunately, the latest histopathology studies of MacTel eyes did not specifically analyze the status of RGCs, and therefore it is still unclear if RGCs are histologically affected in MacTel. Nevertheless, the present study showed that RGCs degenerate in MacTel eyes; GCIPL thinning was consistently diffuse within the macular and especially in its temporal sector, which is the most commonly affected area in MacTel.²⁵ Furthermore, RNFL was also found to be diffusely and consistently thinned compared with age-matched controls; this suggests that all structures of the RGCs get damaged in MacTel. These findings further support the theory that MacTel 2A is a neurodegenerative retinal disease. 

The reason for RGCs loss in MacTel type 2A is unclear. As the primary degeneration in MacTel involves Müller cells, we may speculate that RGCs degeneration is secondary to Müller cells loss. Through the extensive arborization of their processes, Müller cells provide nutritional and regulatory support to both retinal neurons and vascular cells. Neurons, glia (Müller cells and astrocytes), and blood vessels interact during all aspects of metabolic function to form a functional energy unit.²⁶ The ordered functioning of the metabolic unit may arguably be critical for the RGCs; impaired functioning secondary to Müller cells loss may lead to structural alterations and degeneration of the neurosensory retina, including RGCs, leading to progressive thinning. This causes increased light scatter and eventually loss of macular transparency on indirect ophthalmoscopy. Other causes of neuronal degeneration may be oxygen and substrate deprivation during ischemia, and also reperfusion injury. Retinal ischemia reperfusion promotes activation of microglial cells, which leads to a rapid degeneration of the inner retina. On histopathology, this degeneration shows thinning of the IPL and loss of RGCs and other inner retinal neurons.^27,28 

There are a number of limitations to this study. First, it's retrospective nature. Second limitation is that, only 11 Indian subjects were included in the internal database of the Cirrus HD-OCT device. As reported before, various SD-OCT parameters such as RNFL thickness, retinal thickness, and choroidal thickness vary in different age-matched ethnic groups.^29–32 Therefore, we compared our study population with age-matched healthy Indian volunteers to confirm the results of our study. Third, one could argue that GCIPL thinning in MacTel eyes could be related to a possible segmentation issue of the GCA algorithm in thin maculae. However, considering that macular RNFL thickness was diffusely thinned as well, it is unlikely that the results were due to defects in study methods or to a relatively small sample size. In addition, the reduced overall macular thickness with unremarkable outer retinal thickness indirectly confirmed the presence of inner retinal thinning in MacTel eyes. Finally, the study was focused only on eyes with nonproliferative MacTel; therefore, it is difficult to comment upon a possible difference in GCIPL thickness between proliferative and nonproliferative MacTel. 

In conclusion, the study showed significant and consistent RGC degeneration in eyes with nonproliferative MacTel. All RGC structures degenerate, leading to diffuse GCIPL and RNFL thinning. The data supports the emerging view that MacTel type 2A is not primarily a vascular disease, but rather a degenerative condition affecting primarily Müller cells and then neurons. Further studies analyzing longitudinal changes in RGCs and other neuroretinal layers using new segmentation software may clarify the exact sequence of neurodegeneration in MacTel type 2A, and may also further improve the understanding of this unique disease. 

Acknowledgments

The authors thank Sailaja Bondalapati and Banu S (librarian at LV Prasad Eye Institute, Hyderabad, India) for proofreading the paper. 

Disclosure: J. Chhablani, None; H.B. Rao, None; V.U. Begum, None; G.B. Jonnadulla, None; A. Goud, None; G. Barteselli, None