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. Author manuscript; available in PMC: 2026 Jul 18.
Published in final edited form as: Vision Res. 2024 Aug 28;224:108463. doi: 10.1016/j.visres.2024.108463

Age-related effects of optineurin deficiency in the mouse eye

Chien-Chia Su 1,2, Crystal Liu 3, Vishnu Adi 3, Kevin C Chan 3,4, Henry C Tseng 1,*
PMCID: PMC13379292  NIHMSID: NIHMS2020803  PMID: 39208752

Abstract

Optineurin (OPTN) is a gene associated with familial normal tension glaucoma (NTG). While NTG involves intraocular pressure (IOP)-independent neurodegeneration of the visual pathway that progresses with age, how OPTN dysfunction leads to NTG remains unclear. Here, we generated an OPTN knockout mouse (Optn−/−) model to test the hypothesis that a loss-of-function mechanism induces structural and functional eye deterioration with aging. Eye anatomy, visual function, IOP, retinal histology, and retinal ganglion cell survival were compared to littermate wild-type (WT) control mice. Consistent with OPTN’s role in NTG, loss of OPTN did not increase IOP or alter gross eye anatomy in young (2–3 months) or aged (12 months) mice. When retinal layers were quantitated, young Optn−/− mice had thinner retina in the peripheral regions than young WT mice, primarily due to thinner ganglion cell-inner plexiform layers. Despite this, visual function in Optn−/− mice was not severely impaired, even with aging. We also assessed relative abundance of retinal cell subtypes, including amacrine cells, bipolar cells, cone photoreceptors, microglia, and astrocytes. While many of these cellular subtypes were unaffected by Optn deletion, more dopaminergic amacrine cells were observed in aged Optn−/− mice. Taken together, our findings showed that complete loss of Optn resulted in mild retinal changes and less visual function impairment, supporting the possibility that OPTN-associated glaucoma does not result from a loss-of-function disease mechanism. Further research using these Optn mice will elucidate detailed molecular pathways involved in NTG and identify clinical or environmental risk factors that can be targeted for glaucoma treatment.

Keywords: glaucoma genetics, optineurin, normal tension glaucoma, mouse model, retina, visual function

1. Introduction

Mutations in the optineurin (OPTN) gene are associated with familial normal-pressure variant of primary open angle glaucoma (POAG) (Rezaie et al., 2002), which is a neurodegenerative disease of the visual pathway that progresses with increasing age (Shields, 2008; Gupta & Yucel, 2007). POAG is a leading cause of irreversible blindness worldwide, afflicting an estimated 44.7 million people worldwide and 2.8 million in the United States (Quigley & Broman, 2006). In POAG, progressive, age-dependent loss of retinal ganglion cells (RGCs) occurs without any clinical or gross ocular pathology (Weinreb et al., 2014). Although an increase in intraocular pressure (IOP) can exacerbate RGC degeneration, it is a clinical risk factor and not a cause of POAG. Indeed, over 50–60% of POAG patients exhibit progressive RGC loss despite low/normal IOP (Shields, 2008). The cause of the underlying neurodegenerative mechanism in NTG/POAG remains unknown. Recent discoveries of numerous genes identified in NTG/POAG patients offer hope to identify one or more molecular pathophysiological pathways for developing novel therapies. Understanding genetic disease mechanisms will also help establish glaucoma genes as potential biomarkers for clinical risk stratification and diagnosis.

Recent research from our lab and others have focused on elucidating how a disruption in optineurin’s normal function might lead to glaucomatous neurodegeneration and visual impairment (Tseng et al., 2015; Meng et al., 2012; Zhang et al., 2021). Interestingly, OPTN mutations are also found in patients with familial and sporadic amyotrophic lateral sclerosis (ALS) (Maruyama et al., 2010; Del Bo et al., 2011), frontotemporal dementia (FTD) (Fecto & Siddique, 2011), and Paget’s disease of the bone (Wong et al., 2020; Hu, Wong et al., 2023), which are age-dependent degenerative diseases of the spinal and skeletal systems, respectively. Mutations in the OPTN gene that lead to RGC degeneration and visual impairment have been thought to act through a gain-of-function mechanism (Minegishi et al., 2016; Toth & Atkin, 2018); but the possibility of a loss of function mechanism has not been directly tested. In contrast, a loss-of-function mechanism is generally thought to be involved with OPTN mutations in ALS and FTD (Markovinovic et al., 2017; Toth & Atkin, 2018). However, the distinction between gain-of-function and loss-of-function mechanisms appears less clear, especially given that both glaucoma and ALS result from loss of neurons with long projecting axons. Moreover, ocular findings such as axonal loss, thinner peripapillary retinal nerve fiber layer thickness, and macular thinning have been observed in ALS patients without glaucoma or other ocular diseases (Volpe et al., 2015; Mukherjee et al., 2017).

The mRNA expression patterns of OPTN in the heart, brain, kidney, lung, and skeletal muscle are consistent across humans and monkeys with high expression in the skeletal muscle and brain (Rezaie et al., 2005). The expression of the OPTN protein has also been demonstrated in various tissues, including non-ocular tissues such as the brain, spinal cord, heart, lung, bone marrow, and bones (Xue et al., 2021; Wong et al., 2020; Hu, Wong et al., 2023; Akizuki et al., 2013), as well as ocular tissues like the retina and optic nerve (Ito et al., 2016; Rezaie & Sarfarazi, 2005). OPTN’s unique protein structure enables its interactions with other proteins through multiple binding domains (Anborgh et al., 2005; Hattula & Peranen, 2000; Moreland et al., 2000; Morton et al., 2008; Park et al., 2010; Sahlender et al., 2005; Zhu et al., 2007). Through these diverse interactions, OPTN is known to play a role in critical cellular functions, such as ubiquitin binding (Shen et al., 2014; Fenner et l., 2009; Laplantine et al., 2009; Gleason et al., 2011), regulation of NF-kappaB activity (Sudhakar et al., 2009; Zhu et al., 2007; Nagabhushana et al., 2011), protein trafficking (Anborgh et al., 2005; Sahlender et al., 2005; Chibalina et al., 2008; del Toro et al., 2009; Nagabhushana et al., 2010), autophagy/mitophagy (Shen et al., 2014; Liu et al., 2014; Wong & Holzbaur (2014, 2015); Heo et al., 2015; Sirohi & Swarup, 2015; Slowicka et al., 2015; Ying et al., 2015), cytokinesis (Kachaner et al., 2012), antioxidant response (Hu, Wong, et al., 2023; Hu, Foster et al., 2023; Xue et al., 2021; Wong et al., 2020), and antiviral defense (Ames et al., 2021; Patil et al., 2022). OPTN knockdown through RNA interference resulted in loss of neuron-like cell lines in vitro (Akizuki et al., 2013). However, relatively little is known about OPTN’s role in vivo, the consequences of OPTN dysfunction, and how OPTN’s functions change with age.

Given OPTN’s role in multiple critical cellular pathways, we hypothesized that complete loss of OPTN will result in significant changes of retinal structures and visual function. This hypothesis supports a “loss-of-function” disease mechanism in NTG and suggests a possible shared pathogenesis with ALS, given that both diseases involve the loss of neurons with long projecting axons. Testing this hypothesis represents a key step toward elucidating a potential disease mechanism in OPTN-associated NTG in vivo. Due to the limited evidence of a loss-of-function mechanism in NTG in vivo, we generated a floxed (flanked with LoxP sites) OPTN mouse model that can be used to genetically remove the mouse Optn gene in the presence of Cre recombinase. Using these OPTN knockout (Optn−/−) mice, we investigated the age effects of optineurin deficiency on visual function, retinal structure, and specific cell subtypes in the retina.

2. Materials and Methods

2.1. Mouse models

The mice utilized in this study were produced according to methods already described in greater detail (Wong et al., 2020). Briefly, Optnflox/flox mice were generated on a C57BL/6 background using a targeting vector that incorporated a LoxP site flanking the first coding exon along with a neomycin selection cassette. These Optnflox/flox mice were then bred with CMV-Cre mice sourced from The Jackson Laboratory (Bar Harbor, ME, USA) resulting in offspring designated as CMV-Cre; Optnflox/+ mice, which served as breeding pairs. The progeny carrying a global knockout of Optn (CMV-Cre; Optnflox/flox) are henceforth referred to as Optn− /− mice. Floxed Optn founder mice were generated with the assistance of the Duke Neurotransgenic Laboratory, a core facility at the Duke University Medical Center. All mouse husbandry and experimental work were performed with approval from the Institutional Animal Care & Use Committee (IACUC) at Duke University and New York University Grossman School of Medicine. All experiments were conducted according to guidelines established by the Association for Research in Vision and Ophthalmology. Both male and female mice, either Optn−/− or Optn+/+, were included in this study. The mice utilized in this study were categorized into two distinct periods: those at 2–3 months old, classified as young, and those at about 12 months old, defined as aged.

2.2. Intraocular Pressure Measurement

Intraocular pressure (IOP) was measured with by a rebound tonometer (Icare TonoLab, Vantaa, Finland). Anesthesia was induced in the mice to prevent head and body movement as well as to minimize stress to the animal. Mice were first anesthetized by an intraperitoneal injection of an anesthetic mixture of 24% ketamine and 3.2% xylazine. Given that anesthesia can affect IOP in both humans and mice (Camras et al., 2010; Murphy, 1985), IOP measurements were taken immediately after the mice reached a level of sedation adequate for handling. The average IOP values were then compared between young and older periods, as well as between OPTN knockout mice and their nontransgenic littermate wild-type (WT) controls, using mixed-effects models with Sidak-adjusted multiple comparison tests.

2.3. Optokinetics

The OptoMotry virtual-reality optokinetic system (Cerebral-Mechanics Inc., Lethbridge, Alberta, Canada) was employed to evaluate visuomotor behavior by measuring the visual acuity (VA) and contrast sensitivity of each eye. During data collection, the spatial frequency was varied from 0.042 to 0.750 cycles per degree using a simple staircase method, while the rotation speed was maintained at 0.12 degrees per second. Sinusoidal gratings, presented at 100% contrast, had their spatial frequencies systematically increased in successive trials until the animals stopped tracking the moving stimulus. The highest spatial frequency that elicited a response was recorded as VA. Contrast sensitivity threshold (CST) was determined by presenting sinusoidal gratings at a fixed spatial frequency. The values of VA and CST were then compared between young and older periods, as well as between OPTN knockout mice and their WT controls. The statistical analysis was performed using mixed-effects models with Sidak multiple comparison test.

2.4. Western Blotting

The retinas and brains were quickly removed after the mouse was sacrificed, flash-frozen with chilled isopentane, and stored at −80°C. After the eyes were enucleated, the retinas were dissected in chilled PBS and cleared of any ciliary body or retinal pigment epithelium material before being flash-frozen with chilled isopentane and stored at −80°C. Cell lysates were prepared in RIPA buffer containing protease inhibitors (Roche). SDS-Polyacrylamide gel electrophoresis (SDS-PAGE) was performed utilizing Bis-tris precast gels using the NuPAGE electrophoresis system (Invitrogen) before Western blotting. A digital darkroom system (Fluorochem R, ProteinSimple) was used to image the blots together with infrared fluorescent secondary antibodies (Invitrogen). The following primary antibodies were used for Western blotting: rabbit anti-OPTN-C (1:1000, Cayman Chemical, Cat. 100000), goat anti-OPTN-N (1:250, Santa Cruz Biotechnology, sc-48903), mouse anti-GAPDH (1:3000, Life Technologies, AM4300).

2.5. Immunostaining of retina cryosection

Mice were perfused with a fresh, cold 4% paraformaldehyde fixative, after which their eyes were extracted for further processing. The eyes were cryoprotected using sucrose treatment and then embedded in OCT compound. Using a cryostat, 14-micron thick sections of the entire eye were prepared and subsequently stored at −80°C. For immunostaining, these sections were first allowed to equilibrate and dry at room temperature for 1–2 hours, followed by a 1-hour immersion in PBS. The section was permeabilized with 0.1% Triton in PBS for 10 minutes at room temperature. The sections were then blocked using 4% donkey serum and incubated with the primary antibody overnight at 4°C. The following antibodies and their respective dilutions were utilized for immunofluorescence staining: rabbit anti-OPTN antibody (1:200, Cayman, Cat. 100000), mouse anti-tyrosine hydroxylase (1:250, Millipore, AB152), goat anti-vesicular acetylcholine transferase (1:200, Millipore, AB144P), rabbit anti-GTP-binding protein α subunit Goα (1:500, Millipore, 07–634), rabbit anti-protein kinase C alpha (1:1000, Sigma-Aldrich, P4334), mouse anti-calretinin (1:1000, Millipore, MAB1568), chicken anti-GFAP (1:1000, Millipore, AB5541), rabbit anti-Iba-1 (1:1000, Wako, 019–19741), goat anti-Brn3a (1:1000, Santa Cruz Biotechnology, SC-31984), and rabbit anti-cone arrestin (1:1000, gift from Cheryl May Craft from University of Southern California). The next day, retina sections were incubated in secondary antibody, washed in PBS, and mounted in Vectashield with DAPI. The cells containing various markers were quantified in each section and compared between young and aged groups, as well as between OPTN knockout and WT mice, using t-tests with multiple comparisons adjusted by Bonferroni correction.

2.6. Evaluation of retinal layer thickness

Retina sections were imaged using a Nikon Eclipse C1 confocal fluorescence microscope and analyzed with Nikon EZ-C1 software. Measurements of individual retinal layers and overall retinal thickness were recorded at both central and peripheral locations. Only images showing central retina containing optic nerves were selected for thickness measurements to accurately determine the distance from the optic nerve. The central retina was defined as being 200 μm from the optic nerve, whereas peripheral retina measurements were taken 200 µm from the edge of the retina flatmount. The photoreceptor outer segment layer was not quantitated due to retinal detachment artifacts. Therefore, total retinal thickness included ganglion cell-inner plexiform layer (GCIPL), inner nuclear layer (INL), outer plexiform layer (OPL), and outer nuclear layer (ONL). The nuclear layers were defined by DAPI staining while the plexiform layers were defined as the region in between the DAPI staining. Measurements were performed while blinded to the genotype. Retinal thickness was compared between young and aged mice, as well as between OPTN knockout and WT groups, in both central and peripheral regions using t-tests with multiple comparisons adjusted by Bonferroni correction.

2.7. Quantitation of retinal ganglion cells in retinal flatmounts

After mice were perfused with paraformaldehyde, the cornea and lens were removed to create a posterior eye cup, which was post-fixed for an additional 30 minutes in 4% paraformaldehyde on ice. The retina was carefully dissected and utilized for staining as a free-floating retina cup. The retinas were washed three times in PBS followed by an overnight wash in PBS at 4°C. The retina was blocked in 4% donkey serum in 0.1% triton/PBS for one hour at room temperature and incubated in mouse SMI-32 antibody for neurofilament H (Biolegend, SMI-32R) at 1:1000 dilution to identify RGCs. After 5–7 days at 4°C, the retinas were washed with PBS, and incubated overnight with secondary antibody at 4°C. Four relaxing cuts were made in the retina cup before mounting in Vectashield with DAPI, forming four quadrants. Imaging of retina flat mounts was performed using Zeiss Axio Imager microscope with a motorized stage. Multiple tiled images were assembled into a mosaic image that covered the entire retina flat mount. RGC counts were performed as previously described (Tseng et al., 2015). The density differences of RGC between knockout and WT mice at young and aged periods were analyzed using t-tests with multiple comparisons adjusted by Bonferroni correction.

3. Results

3.1. Generation of OPTN knockout mice

As shown in Figure 1A, OPTN protein expression was assessed through Western immunoblotting of surgically isolated retinas. In the retinal lysates from the wildtype (WT) mice, OPTN expression was observed. In contrast, no OPTN expression was found in the retinas from OPTN knockout mice using an antibody against the N-terminus of the protein. Because Cre-mediated deletion was localized to the first exon of the mouse Optn gene, there might be aberrant expression of remaining exons that would result in a smaller, partial fragment of the OPTN protein containing an intact C-terminus region. To assess this possibility, we also utilized antibodies that recognize the C-terminus regions of OPTN protein and found no fragments of lower molecular sizes. Our data demonstrates the complete elimination of OPTN expression. For simplicity, these animals will be referred to as Optn−/− mice below.

Figure 1.

Figure 1.

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Normal eye anatomy and intraocular pressure (IOP) in optineurin knockout mice. (A) Western blot analysis of optineurin (OPTN) expression in mouse retinas using antibodies against both N- and C-termini of OPTN showed normal OPTN bands in wildtype (WT) retinas. In contrast, no OPTN protein bands were detected in Optn−/− mice, confirming the complete loss of OPTN expression. Notably, no bands under 74kDa were observed, indicating the lack of partially expressed OPTN protein fragments containing the C-terminus in Optn−/− mice. (B) Representative images of external eye photographs for WT and Optn−/− mice showing normal gross eye anatomy. (C) The mice were sacrificed at 2–3 or 12 months and processed for histological section of iridocorneal angle showing normal open angles. (D) Rodent IOP was measured by the TonoLab rebound tonometer in WT (n=7) and Optn−/− (n=5) mice when young and again after aging to 12 months old. Data was recorded from both right and left eyes and combined. Data is presented as mean ± SEM with ns: not significant. The statistical comparison was performed using mixed-effect models with Sidak-adjusted multiple comparison tests.

3.2. Normal Gross Eye Anatomy and Intraocular Pressure in optineurin knockout mice

We investigated whether the loss of optineurin would affect gross ocular anatomy and IOP in Optn−/− mice. The external eye photograph demonstrated that the cornea, iris, pupil, and anterior segment appeared normal (Figure 1B). The eyes of Optn−/− mice did not show obvious congenital or acquired defects in their gross anatomy. For example, we did not observe findings such as diffuse pigment dispersion, transillumination defects, corectopia, or iridocorneal adhesions that are found in the DBA/2J mouse model, which is a well-known genetic model for secondary glaucoma. The histological analysis of the iridocorneal angle revealed an open angle configuration in both WT and Optn−/− mice (Figure 1C), indicating that loss of OPTN did not result in narrow or closed angles.

The average IOP from both eyes were measured separately and combined for statistical analyses, as no asymmetry in IOP was observed between the left and right eyes (P = 0.864). The IOP was initially measured in young mice (2–3 months), revealing no significant differences between Optn−/− and WT littermates. The IOPs for WT mice were 10.32 ± 1.6 mmHg (mean ± SEM) when young and 10.38 ± 2 mmHg at an older age. For Optn−/− mice, IOPs were 11.09 ± 3.4 mmHg when young and 11.65 ± 1.5 mmHg after aging. Statistical analysis indicated that IOP values did not significantly differ either between young and aged animals or between the two genotypes (Figure 1D). Taken together, our data demonstrates that loss of the mouse OPTN protein does not result in IOP elevation, in alignment with the absence of congenital defect in ocular gross anatomy.

3.3. Less visual function deterioration in optineurin knockout mice during aging

We examined visual function in optineurin knockout mice using the OptoMotry optokinetic system. The OptoMotry system utilizes a virtual-reality approach that tracks an animal’s head motor response following exposure to a 360-degree stimulus of varying grating patterns. With this approach, visual function is assessed by quantitating visual acuity (VA) and contrast sensitivity threshold (CST).

In this study, repeated measurements of VA in WT mice demonstrated a significant decline from an average of 0.41 cycles per degree (cpd) at a young age to 0.33 cpd at about 12 months old (P < 0.001). In contrast, VA in Optn−/− mice remained stable, measuring 0.43 cpd in young and 0.40 cpd in older 12-month animals, with no significant change (P = 0.438). When comparing between gentotypes, aged Optn−/− mice exhibited significantly better VA compared to aged WT mice (P = 0.033) (Figure 2A).

Figure 2.

Figure 2.

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Visual function preserved in aging optineurin knockout mice. Visual acuity and contrast sensitivity were compared longitudinally between WT (n =17) and Optn−/− (n=12) mice when young and then again after 12 months of age. All analyses of visual acuity (A) and contrast sensitivity threshold (B) were conducted using mixed-effect models with Sidak-adjusted multiple comparison tests. Data is presented as mean ± SEM. *, P < 0.05; **, P < 0.01; ***, P <0.001, ns: not significant.

Similarly, repeated measurements of contrast sensitivity in WT mice showed a significant increase in CST from an average of 5.39% in younger mice to 19.47% in aged mice (P < 0.001), whereby an increase in CST indicates worse contrast sensitivity visual function. CST in Optn−/− mice was 4.68% in younger and 15.18% in older mice (P = 0.012), which was comparable to WT mice (P = 0.382). (Figure 2B). Taken together, these results show that visual function in Optn−/− mice was not severely impaired in both young and aged animals despite loss of OPTN function.

3.4. Loss of optineurin does not alter abundance of retinal neuronal subtypes

To determine if the absence of OPTN results in congenital or age-related loss in neuronal subtypes, we first performed immunostaining of retinal sections from both young and aged Optn−/− mice and imaged the entire retina within the posterior eyecup for analyses (Figure 3A). We used antibodies for PKCα and calretinin to visualize bipolar and amacrine cells, respectively. Calretinin was used to also delineate three sublaminae layers within the inner plexiform layer (IPL) as well as displaced amacrine cells in the ganglion cell layer (Figure 3B, 3C). In conjunction with nuclear DAPI staining, the resultant staining patterns allowed specific retinal layers to be identified. Similar immunostaining patterns were observed between the two genotypes in young eyes.

Figure 3.

Figure 3.

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Normally appearing histology of central and peripheral retinas in optineurin knockout mice. (A) Representative mosaic images of the entire posterior segment containing the retina and anterior optic nerve are shown for WT and Optn−/− mice. The retinas were immunostained with calretinin (red) for amacrine and ganglion cells, PKCα (green) for bipolar cells, and DAPI (blue) for all cell nuclei. High-magnification views from Panel A highlighted the central retina (B) and peripheral retina (C). Scale bar, 50µm.

We next examined various markers to determine whether there are differences in various retinal subpopulations between genotypes and ages. We utilized tyrosine hydroxylase (TH) to identify dopaminergic amacrine cells. Both young WT and Optn−/− mice had similar numbers of TH-immunoreactive cells. However, in older animals, the number of TH-positive cells decreased in WT mice but not in aged Optn−/− mice (Figure 4A). Consequently, between the two genotypes, aged Optn−/− retinas had more TH-positive amacrine cells than aged WT retinas.

Figure 4.

Figure 4.

Figure 4.

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Loss of optineurin does not alter retinal cell subtypes in optineurin knockout mice except for an increase in dopaminergic amacrine cells. Qualitative assessment of vertical frozen sections through the retina of Optn−/− and WT mice in young (2–3 months old) and aged (12 months old) animals. The sections were stained for selective retinal neuronal subtypes for comparison. (A) Tyrosine hydroxylase (TH) for the dopaminergic amacrine cells, (B) vesicular acetylcholine transferase (VAchT) for cholinergic amacrine cells, (C) GTP-binding protein α (Goα) subunit for bipolar cells, (D) Calbindin for horizontal cells, (E) GFAP (green) for astrocytes and Iba1 (red) for microglia, and (F) cone arrestin for cone photoreceptors. Scale bar, 50 µm. Cells stained for the above markers were quantified per section and compared between young and aged groups and between genotypes using t-tests with Bonferroni-adjusted multiple comparisons. Data is presented as mean ± SEM. *, P < 0.05; **, P < 0.01; ns, not significant.

We also investigated other retinal neuronal subtypes with immunostaining for known protein markers and found no significant differences between the two genotypes or aging groups. Cells that we sampled included the following: vesicular acetylcholine transferase (VAchT) for cholinergic amacrine cells and two laminae in the IPL (Figure 4B), GTP-binding protein Go α subunit (Goα) antibody for bipolar cells in the INL and their neurites in both the IPL and outer plexiform layer (OPL) (Figure 4C), calbindin immunostaining identified horizontal cell bodies and their neuronal processes in the OPL (Figure 4D), and cone arrestin for cone photoreceptors from the outer segment to the cone pedicles (Figure 4F).

Apart from retinal neuronal subtypes, we assessed astrocytes and microglial cells using GFAP and Iba-1, respectively. GFAP immunostaining revealed a decrease in astrocytes in aged mice in both genotypes (Figure 4E). Iba-1 labeling showed sparse microglia across various retinal layers for both genotypes, with a slightly higher number of Iba-1 positive cells in Optn−/− young mice (Figure 4E). Taken together, with the exception that more TH-positive cells are found in aged Optn−/− mice than WT ones, our data revealed similar abundance of various retinal cell subtypes in the retina sections of Optn−/− and WT mice.

3.5. Similar age-related changes of retinal thickness in optineurin knockout mice

We measured the thicknesses of various retinal layers from histological sections of WT and Optn−/− retinas (Figure 5) in either central or peripheral retinal regions. In WT mice, the average central total retinal thickness apparently decreased from 164.44 μm in young to 140.86 μm in aged retinas. This trend was observed but not statistically significant likely due to the wide data spread. In contrast, Optn−/− mice maintained a more consistent thickness, measuring 153.11 μm in young and 153 μm in aged retinas. A similar trend in total retinal thickness was observed in the peripheral retina (Figure 5A). Therefore, WT retinas exhibited an insignificant and mild aging effect that was not seen in Optn−/− retinas for total retinal thickness.

Figure 5.

Figure 5.

Figure 5.

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Attenuated age-related structural alterations in optineurin knockout mice. Histological sections of WT (n=16) and Optn−/− (n=13) mice were processed and classified into young (2–3 months old) and aged (12 months old) groups. Segmentation of each layer were compared between young and aged groups and between genotypes using t-tests with Bonferroni-adjusted multiple comparisons. (A) Total retinal thickness, (B) ganglion cell–inner plexiform layer (GCIPL) thickness, (C) inner nuclear layer (INL) thickness, (D) outer plexiform layer (OPL) thickness, (E) outer nuclear layer (ONL) thickness were displayed. Data is presented as mean ± SEM. *, P < 0.05; **, P < 0.01; ***, P <0.001, ns, not significant.

We next examined inner retinal layers. Because the thin ganglion cell layer was hard to quantitate manually by itself, we quantitated both the ganglion cell and inner plexiform layers together (GCIPL) in combination. In the central region, the GCIPL thickness significantly decreased with aging in both WT and Optn−/− mice (P = 0.019 and P = 0.008, respectively). In contrast, in the peripheral retina, the GCIPL thickness was thinner in young Optn−/− retinas than WT retinas. However, during aging, GCIPL decreased significantly in WT retinas while GCIPL remained the same in Optn−/− retinas (P = 0.729) (Figure 5B). The age-dependent decrease in WT GCIPL reached a level similar to that of Optn−/− retinas. Thus, we observed primarily an aging effect in both WT and Optn−/− mice, but a genotype effect in the young Optn−/− mice.

The INL thickness remained unchanged between young and aged groups in both WT and Optn−/− mice (Figure 5C). This was observed for both central and peripheral retinas. These findings demonstrated no aging or genotype effect in the INL between WT and Optn−/− mice.

With respect to OPL, changes in its thickness patterns were different from the other retinal layers. Both young WT and Optn−/− mice had similar OPL thickness, which decreased to a similar level after aging (P = 0.04) in the central retina (Figure 5D). For ONL, there was an increase in central ONL thickness in aged Optn−/− mice (P = 0.01) when compared to young mice, but this was not different when compared to aged WT mice. (Figure 5E). Therefore, while OPL demonstrated an aging effect but not genotype effect, ONL was unaffected by genotype. In summary, both genotypes exhibited aging effects in the GCIPL and OPL layers, with the INL layer remaining unchanged. Optn−/− mice, but not WT mice, showed a slight increase in the ONL layer with aging. This led to an overall mild but statistically insignificant aging effect on the total retinal thickness in WT retinas, whereas no such effect was observed in Optn−/− retinas.

3.6. Comparable retinal ganglion cell loss rate in aged OPTN knockout mice

In addition to comparing retinal layers between the two genotypes, we also conducted a quantitative assessment of RGCs in flatmounts to evaluate RGC loss in both genotypes. RGCs were stained and morphologically-identified with an antibody for neurofilament. Representative immunolabeled flatmounts of WT and Optn−/− mice at both young and aged stages are displayed in Figure 6A. In young mice, there was no statistical difference in the number of RGCs between WT and Optn−/− mice (P = 0.354). Young WT mice had an RGC density of 236.6 cells/mm2 (n = 5) while it was 256.54 cells/mm2 in young Optn−/− mice (n = 8). Similar RGC counts were also found in aged WT and Optn−/− mice (P = 0.811). The RGC density was measured at 184.1 cells/mm2 for aged WT mice (n=10) and 184.33 cells/mm2 for aged Optn−/− mice (n = 3). These findings show that the absence of OPTN expression does not lead to a substantial reduction in RGC survival beyond that of the WT mice as they age.

Figure 6.

Figure 6.

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Comparable rate of age-related loss of retinal ganglion cells (RGCs) in optineurin knockout and wild type mice. (A) Representative retinal flatmounts of Optn−/− and WT retinas from young (2–3 months old) and aged (12 months old) animals. Immunostaining for neurofilament-H was performed to identify RGCs morphologically. RGCs were defined as cells showing immunostaining and possessing axons extending towards the optic nerve. The images presented were created by compiling mosaics from high-magnification images. Scale bar, 500 µm. (B) Quantitative comparison of RGC counts in retinal flatmounts between WT (n=5) and Optn−/− (n=8) retinas from young mice, and between WT (n=10) and Optn−/− (n=3) retinas from aged animals were performed using t-tests with Bonferroni-adjusted multiple comparisons. Data is presented as mean ± S.E.M. *, P < 0.05; ns, not significant.

4. Discussion

To elucidate the in vivo function of OPTN, we have successfully generated a floxed Optn mouse that allows the genetic deletion of OPTN expression using LoxP-Cre technology. Following ubiquitous OPTN knockout, we did not observe gross ocular pathology or changes in IOP. However, given OPTN’s role in many critical molecular pathways and genetic associations with age-dependent degenerative diseases, we hypothesized that loss of OPTN function disrupts retina structures and visual function. Interestingly, we did not detect severe disruptions in retina structure or increased RGC loss upon complete loss of OPTN. The GCIPL and OPL layers were more sensitive to aging than the INL and ONL, suggesting increased susceptibility to age-dependent loss of neurites and synaptic connections compared to cell bodies. These effects are more pronounced in the central and less in peripheral retinal regions. However, loss of OPTN did not seem to contribute substantially to structural disruptions or altered thickness of retinal layers in the aged mice. In summary, our data suggest that synaptic connections are more susceptible to age-dependent influences while bipolar and photoreceptor layers are stable with respect to aging and loss of OPTN. Also, Optn−/− mice did not suffer severe visual impairment, but instead demonstrated less VA deterioration compared to WT controls upon aging to 12 months of age.

Our findings provide an important clue toward elucidating the mechanism of how OPTN-associated mutations might lead to glaucoma. To date, it was unclear whether glaucoma-associated E50K mutations in OPTN result in a “gain-of-function” or “loss-of-function” disease mechanism. In general, proteins encoded by a mutant gene can either result in decreased normal protein function (“loss of function) or in protein misfolding or detrimental hyperfunction (e.g. toxic “gain-of-function’). If the E50K OPTN mutation leads to a loss of function mechanism, then we expect that deletion of OPTN will also lead to RGC loss and visual impairment. This was not observed in our Optn−/− mice. Therefore, our data support the possibility that glaucoma associated with OPTN E50K mutation is the result of a toxic gain-of-function disease mechanism.

Our findings can help understand the mechanism related to previous research on mice expressing glaucoma-associated E50K OPTN mutation. We previously generated a different transgenic mouse strain, BAC-hOPTNE50K, which expresses human E50K OPTN at physiological levels using a bacterial artificial chromosome. This strain exhibited age-related RGC damage, axonal damage, and functional visual impairment with age (Tseng et al., 2015). Chi et al. also reported that high-overexpression of E50K OPTN using the chicken β-actin promoter resulted in diffuse loss of all retinal neurons (Chi et al., 2010). Ying et al. intravitreally injected a recombinant adeno-associated type 2 viral (AAV2) vector carrying OPTNE50K-GFP to infect RGCs in Norway Brown rats. Eyes expression E50K OPTN mutation exhibited retinal thinning, increased RGC apoptosis, and axonal loss compared to GFP controls (Ying et al., 2015). Results from these studies support a toxic gain-of-function mechanism for OPTN-associated glaucoma.

While we did not detect differences in RGC survival between WT and Optn−/− animals, a major limitation of RGC quantitation is the lack of definitive RGC histological markers. Although >20 RGC subtypes have been described electrophysiologically or morphologically, no definitive antibody markers are established to immunolabel 100% of RGCs as a class (Coombs et al., 2006; Sun et al., 2002). While many RGC markers have been reported (e.g. Brn3a, RBPMS), antibodies for these markers also stain non-RGC cells. We utilized a well-established approach of neurofilament immunostaining with the SMI-32 antibody (Coombs et al., 2006) which stains not just the cell body but also neuronal axons. This allowed us to identify representative RGCs with both neurofilament-immunoreactivity and the morphological characteristic of long projecting RGC axons coursing toward the optic nerve head (Lin & Peng, 2013; Jakobs et al., 2005). Our RGC density measurement in WT retinas are consistent with 80–110 RGCs per mm2 in other reports (Lin & Peng, 2013; Lin et al., 2004).

Although OPTN plays a role in many critical molecular pathways, the lack of substantial deterioration in visual function in young Optn−/− mice was observed, even after aging Optn−/− mice to 12 months of age. Indeed, our results of visual function is consistent with another study, which reported that 6-month-old C57BL/6 mice had a VA of 0.48 cpd which declined to 0.38 cpd in one-year-old mice (Wong & Brown, 2007). Even though mice are considered old after 12 months of age, mice can live up to 24 months of age. It has been thought that 12-month-old mice correlate to 40-year-old humans (Flurkey & Harrison, 2007). In the clinic, NTG/POAG are less commonly seen in 40-year-old patients but are higher in prevalence in patients older than 60–70 years of age. As such, 12-month-old mice might not be old enough to see significant deterioration in visual function resulting from OPTN deletion. Because 24-month-old mice are thought to correlate to 70-years of age in humans, future studies with older mice will test if Optn−/− mice exhibit preservation of visual function, less RGC thinning, and a higher number of dopaminergic amacrine cells compared to WT mice at ages greater than 12 months. These future studies will also help determine whether WT optineurin may be deleterious with age.

Our assessment of Optn−/− retinas revealed possible in vivo roles in specific neuronal subpopulations. For example, we found that Optn−/− mice exhibit a higher amount of TH-positive dopaminergic amacrine cells compared to aged WT controls. It is known that dopaminergic neurons develop early, become functional before an animal can see, and die as the animal ages (Witkovsky, 2004). Impairment of the dopamine system during retinal degeneration in Parkinson's disease can lead to various visual abnormalities, including reduced contrast sensitivity, decreased VA and deficits in color vision (Djamgoz et al., 1997; Indrieri et al., 2020). Preservation of TH-amacrine cells might be a possible mechanism to explain how Optn−/− mice maintained relatively good VA during aging. The maintenance of dopaminergic amacrine cells during aging in Optn−/− mice suggests a role for OPTN in attenuating loss of dopaminergic neuronal cells. In our study, a slightly higher number of Iba-1 positive cells in Optn−/− young mice was found. However, overall number of microglia is low in both groups and prevents a clear assessment on how loss OPTN impacts microglial cells. Future studies focusing on more detailed microglial experiments are warranted.

OPTN might possibly play a role for stress response, and may not be critical for cellular homeostasis at baseline without stressors. This would explain our data showing that complete genetic deletion of OPTN does not lead to significant visual impairment and cellular loss. However, if exposed to clinical risk factors or environmental stressors without OPTN, cells may fail to cope or survive. For example, our experiments did not subject Optn−/− mice to mildly elevated IOP, which is a known glaucoma risk factor (Gordon et al., 2002). An alternative possibility is that other proteins or biochemical pathways may partially compensate for the loss of OPTN function in vivo. These will need to be identified through future structural or functional experiments. For example, OPTN was recently found to be a mitophagy contact site for TBK1 activation. Monobodies engineered to bind OPTN impaired its accumulation at contact sites and subsequent activation of TBK1, thus decreased mitochondrial degradation (Yamano et al., 2024). Because this process is different than that mediated by another autophagy receptor called NDP52, loss of OPTN function might possibly be compensated by NDP52. Identifying and studying these compensatory mechanisms may yield further insight into OPTN’s in vivo role, and reveal novel molecular and cellular processes involved in neurodegenerative pathophysiology. Within this context, our Optn−/− mouse will be useful for identifying clinical risk factors, environmental stressors, and compensatory mechanisms that might be utilized to minimize visual impairment and disease progression in glaucoma patients.

Acknowledgements

We thank Michael Ehlers and the Duke Neurotransgenic Laboratory for assistance in generating floxed optineurin mice, as well as Howard Bomze and Carrie Marean-Reardon for technical support with mouse genotyping and Celia McKee for technical support with immunostaining. We would also like to thank Cheryl Craft at the Doheny Eye Institute for the cone arrestin antibody, and members of the Neuroimaging and Visual Science Laboratory at New York University Grossman School of Medicine for their technical support We acknowledge funding from: K12-EY016333 (HCT), K08-EY021520 (HCT), Butler Pioneer Award (HCT), Holland-Trice Award (HCT), Alcon Research Institute Award (HCT), and an NEI core grant P30-EY005722 to the Duke Eye Center, and unrestricted funds from Research to Prevent Blindness (New York, New York) to NYU Langone Health Department of Ophthalmology, and Taiwan National Science and Technology Council grant 112-2314-B-002 -066 (CCS).

Footnotes

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