The Temporal Dynamics of Pathological Profile and Functional Impairment in Neuromyelitis Optica Spectrum Disorders associated Optic Neuritis

doi:10.21203/rs.3.rs-4815097/v1

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The Temporal Dynamics of Pathological Profile and Functional Impairment in Neuromyelitis Optica Spectrum Disorders associated Optic Neuritis

https://doi.org/10.21203/rs.3.rs-4815097/v1

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Background

Optic neuritis (ON) linked to Neuromyelitis Optica Spectrum Disorders (NMOSD), particularly in Asians, causes irreversible vision loss. The lack of comprehensive analysis that tracks the progression of changes over time hinders the identification of optimal timeframes for observation and intervention of the disease. Our aim is to map disease progression histologically and functionally in an optimized Neuromyelitis Optica Spectrum Disorders associated Optic Neuritis (NMOSD-ON) animal model.

Materials and Methods

The animals in the NMOSD-ON group involved the injections of aquaporin-4-immunoglobulin G (AQP4-IgG) and human complement into the posterior optic nerve, separated by 24 hours, repeated twice. The control group received injections of normal immunoglobulin G (normal IgG) and human complement. Histological analyses examined the immunoreactivity of aquaporin-4 (AQP4) protein, glial fibrillary acidic protein (GFAP) protein (maker of astrocytes), microglial activation, myelin oligodendrocyte glycoprotein (MOG) (maker of myelin sheath), and degeneration of retinal ganglion cells (RGCs), along with gene expression profiling of inflammatory cytokines at various time points (Baseline, Day 2, Week 1, Week 2, Week 4). In-vivo visual functional and retinal structural assessments were performed weekly up to Week 4 to track disease progression.

Results

Administration of AQP4-IgG and human complement triggered a series of events in mice with NMOSD-ON, leading to early changes in astrocyte pathology (loss of AQP4 and GFAP staining), upregulation of tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), interleukin-1β (IL-1β), CXCL10, brain-derived neurotrophic factor (BDNF) and microglia activation in Week 1. This was followed by demyelination, culminating in damage to RGCs and nerve fibers in Week 2. Functionally, the delays of visual evoked potential N1 latency were detectable from Week 2, with reduced N1P1 amplitudes by Week 2. For the electroretinogram, the postive scotopic threshold response (pSTR) amplitude decreased at Week 2, while scotopic a- and b-wave amplitudes remained unchange, which corresponded to the retinal nerve fibre layer thinning in the in-vivo retinal structural scan commencing at Week 2.

Conclusion

This study outlines the progression timeline of NMOSD-ON disease and connects histological and molecular findings to retinal structural changes, in-vivo functional impariment following NMOSD-ON onset in an optimized animal model.

NMOSD-ON

animal model

dynamics

pathological profile

functional impairment

Neuromyelitis Optica Spectrum Disorders (NMOSD) is an autoimmune inflammatory disorder of the central nervous system (CNS) that mainly impacts the optic nerves and spinal cord. It is identified by severe, repetitive episodes of optic neuritis (ON) which always leads to irreversible vision loss and myelitis, particularly in the Asian population [1, 2]. NMOSD is frequently linked to the existence of pathogenic autoantibodies targeting aquaporin-4 (AQP4), a water channel protein abundantly found on the foot processes of astrocytes and activation of the complement system, characterized by deposition of complement components, such as C5b-9 [2–5]. AQP4 antigens express two isoforms (M1 and M23) on the astrocyte membrane. Met-1 peptide triggers translation of the longer isoform (M1), while Met-23 peptide initiates translation of the shorter one (M23) [6–8]. Residues in M23-AQP4 protein after Met-23 drive tetramer-tetramer interactions, forming orthogonal arrays of particles (OAPs). M23-AQP4 consistently arranges OAPs and is targeted by AQP4-IgG [9–12]. M1, limits the size of OAP by interfering with OAPs through residues before Met-23 [13]. The variation in the affinity of AQP4-IgG to the OAPs determinants M23 varies across various recombinant monoclonal antibodies like rAb53 and rAb58. It has been observed that the affinity to M23 is more pronounced in rAb53 than in rAb58 while the affinity to M1 is greater in rAb58 than in rAb53. Hence, rab53 induces greater impairment to AQP4 than rab58 [14–16]. Following the binding of aquaporin 4-immunoglobulin G (AQP4-IgG) to the AQP 4 protein expressed on astrocytes, microglia emerge as the primary responders to the signals released from astrocytes and complement system [17–20]. Various cytokines impact the development and activation of microglia, such as interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), interleukin-1 beta (IL-1β), and CXCL10. These cytokines can exert both autocrine and paracrine influences on microglia, as well as on other CNS cells [14, 21–26]. Activated microglia are associated with the secretion of proinflammatory cytokines, including IL-1β, IL-6, TNF-α, CXCL10 [27–30]. An overabundance of these factors due to persistent microglial activation can lead to harm to nearby neuronal cells [31–34]. In the Neuromyelitis Optica Spectrum Disorders associated Optic neuritis (NMOSD-ON), this inflammatory attack leads to the depletion of retinal ganglion cells (RGCs) (cell bodies) and optic nerve (axons) degeneration [31, 32, 35–40]. Additionally, Brain-derived neurotrophic factor (BDNF) and Nerve Growth Factor (NGF) play critical roles in managing neuroinflammation and ensuring neuroprotection. In autoimmune diseases, the protective effects of BDNF and NGF originate from their secretion by microglia and astrocytes within the central nervous system (CNS). Both BDNF and NGF enhance neuroplasticity and support neuronal survival. [41–44].

Previous studies had highlighted the impact of AQP4-IgG on astrocyte damage in the NMOSD-ON animal model. However, the cascading effects on other cell types, such as microglia, oligodendrocytes, and retinal ganglion cells, remain incompletely understood [45, 46]. The absence of a detailed time-sequence overview of these alterations, like AQP4 loss, astrocyte damage, microglial activation, demyelination, and RGCs degeneration, in NMOSD-ON restricts the capacity to forecast disease progression and identification of disease timeframe [21, 26, 35, 47–49].

Our aim was to delineate the timeline of disease progression and correlate histological and molecular findings with functional outcomes post-initiation of NMOSD-ON in an optimized animal model. By establishing a comprehensive timeline, we aimed to identify critical windows of disease progression, thereby improving our understanding of NMOSD-ON development.

Neuromyelitis optica (anti-aquaporin-4, AQP4) antibodies

The recombinant monoclonal anti-AQP4 antibody rAb53 (Creative Biolabs Inc. USA), also known as aquaporin-4-immunoglobulin G (AQP4-IgG), was isolated from a clonally expanded population of plasma blasts originating from the cerebrospinal fluid (CSF) of a patient diagnosed with NMOSD, with its derivation and characteristics having been comprehensively documented in earlier studies [15, 16, 35]. The monoclonal recombinant antibodies targeting AQP4 exhibited a greater affinity for antigens compared to the polyclonal antibodies sourced from the sera of NMOSD patients [50]. Derived from plasmablasts that were clonally expanded from the CSF, the recombinant monoclonal NMOSD antibodies were created through the co-transfection of heavy and light chain constructs into HEK293 cells. Subsequently, the Fab fragment was obtained through papain digestion of the whole IgG, while the Fc fragment was acquired using protein A [15].

Establishment of an optimized NMOSD-ON animal model

Adult female C57BL/6 mice weighing 15–22 g (8–10 weeks) were kept in a controlled environment under a 12-hour light/dark cycle with food and water ad libitum, following standard operating procedures of centralized animal facilities (CAF) in The Hong Kong Polytechnics University (PolyU). In the NMOSD-ON group, the NMOSD-ON animal model was induced by intracranial injection of AQP4-IgG (5 µg, rAb53 variant) after mounting the animal onto the stereotaxic instrument (Portable Stereotaxic Instrument for Mouse, SGL M, Digital. RWD Life Science Co., Ltd., Shenzhen, China) [35], combined with human complement (5 µl, Innovative Research Company). In the control group, animals were administered injections of normal immunoglobulin G (normal IgG) (5 µg, Sigma Aldrich Company) with human complement (5 µl). The AQP4-IgG/ normal IgG and human complement components were combined in a syringe and transferred into a syringe pump (KDS Legato 130 Syringe Pump, RWD Life Science Co., Ltd., Shenzhen, China). The AQP4-IgG and complement were precisely administered utilizing stereotaxic coordinates (1 mm lateral, 1 mm anterior, 6 mm ventral) from the bregma landmark. The meticulous selection of these coordinates facilitated the accurate delivery of the substances in immediate proximity to the optic chiasm structure. The pump was set to infuse the contents slowly into the specific area of the posterior optic nerve at a defined rate, usually 1 µL/min. This gradual infusion imitated the slow buildup of AQP4-IgG and complement activation, rather than a sudden injection as suggested by previous study [35]. Dosage and volume of AQP4-IgG were determined based on preliminary investigations.

Experimental time course

After the initial assessments (Baseline) and intracranial injections of AQP4-IgG or normal IgG along with human complement, the mice in the NMOSD-ON group and the control group underwent additional evaluations during the subsequent months. Functional changes were assessed at Baseline (prior to induction) and at weekly intervals (Week 1, 2, 3, and 4 post-induction) using electroretinography (ERG), and visual evoked potential (VEP). In-vivo structural changes were monitored by optical coherence tomography (OCT) at Baseline, Week 1, Week 2, Week 3, and Week 4. Histological assessments were conducted at Baseline (before any injection), Day 2, Week 1, Week 2, and Week 4, as depicted in Figure. 1A

Immunostaining for histological assessment

Optic nerves and whole-mounted retinas were collected and preserved in 4% paraformaldehyde (PFA). The tissues were embedded in an optimal cutting temperature compound (O.C.T compound) from SAKURA Company and sectioned into 14 µm thick slices by the cryostat (Leica CM1950) from Leica Biosystems. For immunostaining, non-specific binding was blocked with 5% bovine serum albumin (BSA) in Phosphate-buffered saline (PBS) for 1 hour. The sections were then incubated overnight at 4°C with primary antibodies targeting AQP4 (1:200), GFAP (1:200) for astrocytes, CD68 (1:200) for activated microglial, Iba-1 (1:700) for microglia [51], MOG (1:200) for myelin [35], NF200 (1:200) and Brn3a (1:200) as a marker for RGCs axons and cell bodies [52]. Subsequently, the sections were washed in PBS, treated with Alexa Fluor-conjugated secondary antibodies (1:500) for 1 hour at room temperature, and nuclei were stained with 4′,6-diamidino-2-phenylindole (DAPI) (1:1000) for 15 minutes. Finally, the sections were mounted with an anti-fade mounting medium and observed under a fluorescence microscope with filters for DAPI, Alexa Fluor 488, and Alexa Fluor 555. Apart from the above secondary antibodies, the delivered AQP4-IgG and human complement were labeled and detected using anti-human antibodies (Alexa Fluor 488) and anti-C5b9 (1:200). Confocal images of fluorescent samples from cryosections and whole-mounted retina were taken using Zeiss LSM 800 Upright Confocal Microscope (Zeiss, USA). The 10x/0.45 and 20x/0.8 objectives were utilized for capturing images. The depositions of delivered AQP4-IgG and human complement were detected in 10x confocal images for evaluating both the percentage of the affected area over the total area and immunofluorescence intensity. Quantifying the intensity of AQP4, GFAP, MOG, and NF200 immunofluorescence in 20x confocal images were done collectively to measure the protein expression in arbitrary units (a.u.) [53, 54] by Image J software (The Laboratory for Optical and Computational Instrumentation, University of Wisconsin). Specifically, the confocal microscope settings were standardized, and the images were captured under the same acquisition parameters for one protein expression across all experimental groups and time points [55, 56]. To quantify the number of Brn3a + RGCs cells, three distinct areas in the superior, nasal, inferior, or temporal regions, each consisting of squares with 319.5µm x 319.5 µm along the retinal whole-mount axis (20x confocal images), were captured at distances of 200 µm (1 image for the central area) and 1 mm (2 images for the middle areas) from the optic nerve head as indicated in Figure. 3D. The quantities of RGCs) were computed using Image J software and averaged for a single sample (entire retina).

Quantitative Real-Time PCR (polymerase chain reaction) (qRT-PCR) for testing released cytokines

Optic nerves from sacrificed mice following transcardiac perfusion with ice-cold PBS were obtained at specific time points, namely Day 2, Week 1, Week 2, and Week 4 post NMOSD-ON induction. All collected tissues were snap-freezed in liquid nitrogen immediately after dissection and stored at -80°C until RNA extraction. All stored tissue samples were thawed on ice and they were homogenized by using a mechanical homogenizer (Bertin Technologies Precellys Evolution Homogenizer) in the 300 µl of TRIzol RNA Isolation Reagents (Thermo Fisher Scientific). Incubation persisted for 5 minutes to allow complete dissociation of the nucleoproteins complex. Chloroform (60 µl) was added per sample for lysis. All samples were centrifuged for 15 minutes at 12,000 × g at 4°C. The mixture was separated into a lower phenol-chloroform, an interphase, and a colourless upper aqueous phase. The aqueous phase containing the RNA was transferred to a new tube by angling the tube at 45° and pipetting the solution out. To quantify the RNA obtained, the NanoDrop Spectrophotometer (Thermo Fisher) was used. The ideal A260/A280 ratio should be around 2.0 for pure RNA. The RNA was reversely transcribed to cDNA by a reverse transcription kit (High-Capacity cDNA Reverse Transcription Kit from Applied Biosystems™). This procedure typically involved combining RNA with a reverse transcriptase enzyme, a primer (RT Random Primers), dNTPs, and a buffer. The reverse transcription reaction was performed in a thermal cycler with the recommended temperature condition, which usually included an initial primer annealing step, an extension step for reverse transcription, and a final inactivation step. The qRT-PCR was done by TB Green Premix Ex Taq II (Tli RNase H Plus) (Takara, RR420a). The housekeeping gene Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) was utilized as the internal endogenous control for gene expression analysis of the raw data (2^−ΔΔCT). The sequences of our primers were as follows:

GAPDH:

Forward primer: GGGTCCCAGCTTAGGTTCAT;

Reverse primer: CTCGTGGTTCACACCCATCA

IL-6:

Forward primer: TATGAAGTTCCTCTCTGCAAGAGA;

Reverse primer: CTGCAAGTGCATCATCGTTGTTC;

IL-1β:

Forward primer: GGCTGCTTCCAAACCTTTGA;

Reverse primer: GAAGACACGGATTCCATGGT

TNF-α:

Forward primer: CAGGCGGTGCCTATGTCTC;

Reverse primer: CGATCACCCCGAAGTTCAGTAG

CXCL10:

Forward primer: GCCGTCATTTTCTGCCTCAT

Reverse primer: GGCCCGTCATCGATATGG

BDNF:

Forward primer: TGA CAA CGA CAT CGC ATT AC

Reverse primer: TTC AGC CGG TCA GAG AAG

NGF:

Forward primer: CAA TAG CTG CCC GAG TGA CA

Reverse primer: TCC GGT GAG TCC TGT TGA AAG

Functional measurement

ERG recordings were conducted to assess retinal function, specifically measuring the positive scotopic threshold response (pSTR), a-wave, and b-wave amplitudes of scotopic ERG response [57]. The study utilized a full-field Ganzfeld stimulation (Q450; RETI Animal; Roland Consult, Brandenburg an der Havel, Germany). This method was used to elicit responses from the inner and outer retinal layers of experimental animals, as described in previous studies [58, 59]. Animals were dark-adapted for 12 hours prior to the procedure to ensure sensitivity to scotopic testing. Under dim red light, animals were anesthetized, pupils dilated, and electrodes placed. They were then placed on a temperature-controlled platform connected to a warm water bath set at 37.8°C. The animals' pupils were dilated, and a lubricating gel was applied to prevent corneal dehydration. Recording electrodes were placed on the corneal surface (active electrode) and needles were inserted into the lateral canthi of each eye (reference electrode) and the base of the tail (ground electrode). This setup allowed for simultaneous recordings from both eyes. The pSTR was measured by averaging 40 responses with an interstimulus interval of 2 seconds. The stimuli consisted of brief (2 microseconds) dim white light-emitting diode flashes with intensities ranging from − 5.1 to − 4.05 log cd.s/m2, in steps of 0.15 log cd.s/m². Scotopic (mixed rod and cone) responses were recorded using a single flash with an intensity of 1.3 log cd.s/m². The recorded signals were filtered with a bandpass filter of 0.1 to 1000 Hz. The amplitudes of pSTRs (at the level around − 4.8 log cd.s/m2) along with the amplitudes of a- and b-wave of scotopic responses were measured and extracted for additional analysis. These responses correspond to the function of RGCs, photoreceptors, and bipolar cells [57, 60], respectively. Full-field ERG was performed to assess retinal function in the NMOSD-ON group and control group at Baseline, Week 1, Week 2, Week 3, and Week 4.

VEP recordings (non-invasive) were utilized to evaluate the functional integrity of the visual pathway from the retina to the visual cortex [61]. Animals were anesthetized, and visual stimuli were presented while the active electrode (a steel needle) was inserted subdermally into the area of the head in the middle of two ears (Figure. 5A). This region corresponds to the area above the cortex where the responsive signals were processed. The non-stimulated eye was occluded by a dark patch. The reference electrode was put underneath the tongue (Figure. 5A), while the ground electrode was inserted to the tail [62–64]. Full-field (Ganzfeld) stimulation was employed along with a computation system (RETI port, Roland Consult GmbH, Brandenburg, Germany). N1P1 amplitude, N1, and P1 latencies of the VEP response were assessed to evaluate the functionality of the visual pathway, as described in previous studies [49, 62]. N1 wave refers to the primary negative peak that stands out the most. The P1 wave represents the initial positive peak. N1 latency indicates the latency of the N1, and reflects the demyelinating injury of the optic nerve [49, 62]. The N1-P1 amplitude was measured from the trough of the N1 wave to the peak of the P1 wave, indicating the integrity of the visual pathway, especially the RGCs. P1 latency refers to the time of signal transmitting from retina to visual cortex. The stimulus and recording parameters aligned with prior findings according to previous reports [62, 65, 66].

In-vivo structual retinal assessment

OCT was employed to measure the thickness of the retinal nerve fiber layer (RNFL), the Combined Ganglion Cell and Inner Plexiform Layer (GCIPL), and inner nuclear layer (INL), and Inner retina (Summing up the RNFL, IPL, and INL) providing an indirect in-vivo assessment of axonal integrity within the retina. Animals were anesthetized, pupils dilated, and the retina scanned using a high-resolution OCT device. Optical Coherence Tomography (OCT) was conducted with the Bioptigen Envisu ™ Spectral domain optical coherence tomography (SD-OCT) system (Model R2210, Leica Microsystems, Morrisville, NC, USA). Rectangular OCT scans were executed (a-scans/b-scans: 1000 lines; b-scans:100 scans; frame/b-scans: 10 frames), encompassing an area of 0.8 × 0.8 mm. The optic disc was centrally positioned within the scan to serve as a consistent reference point across various subjects and assessed time points. The analysis of retinal thickness was described as previously reported [67].. The averaged RNFL, GCIPL, INL, and Inner retina thicknesses were calculated to track structural changes of RGCs and axons over time (Baseline, Week 1, Week 2, Week 3, and Week 4).

Data Collection and Analysis

Data for each assessment (Intensity of immunostaining, ERG, VEP, OCT measurement) were collected at Baseline and post-induction weeks. Changes in intensity of immunostaining (AQP4, GFAP, MOG, and NF200), cell counted numbers of Iba-1 and CD68 labeled microglials, cell counted numbers of RGCs cell bodies in whole mount retina, ERG parameters (pSTR amplitude, amplitude and latencies of a- and b-wave), VEP parameters (N1-P1 amplitude and N1, P1 latency), and OCT measurements (RNFL, IPL, and INL thickness) were analyzed using repeated measures Two-way ANOVA to identify significant changes over time. Post-hoc analyses were conducted to pinpoint specific time points with notable differences of the NMOSD-ON group from Baseline values or the control group.

Temporal progression of pathological changes

Early Depletion of AQP4 and Astrocyte Impairment

The temporal changes in AQP4 immunoreactivity were assessed in the NMOSD-ON group at various post-induction time points (Day 2, Week 1, Week 2, and Week 4) as compared to both Baseline and control group. A notable decrease in AQP4 immunoreactivity was observed at the site of injection on Day 2, indicating an immediate reaction to the presence of AQP4-IgG compared to the control group (P = 0.015) and Baseline (P = 0.030). This loss of AQP4 immunoreactivity continued to worsen over time, with a reduction at Week 1 (P = 0.031 vs. control and P = 0.038 vs. Baseline), Week 2 (P = 0.044 vs. control and P = 0.031 vs. Baseline), and Week 4 (P = 0.015 vs. control, but not significant from the Baseline) (Figure. 1B, C, and D).

Concurrently, a decline in GFAP expression was noted, suggesting an acute damage to astrocytes. The temporal changes in GFAP immunoreactivity were observed in the NMOSD-ON group at various post-induction time points (Day 2, Week 1, Week 2, and Week 4). Quantification of the GFAP protein levels revealed a significant and progressive loss compared to both the control group and the Baseline (pre-induction) measurements. Brifely, at Day 2 post-induction, there was a moderate decrease in GFAP immunoreactivity as compared to Baseline (P = 0.0148), which was not statistically significant from the control group. However, this reduction in GFAP in Week 1 showed a significant decrease compared to both the control group (P = 0.048) and the Baseline (P = 0.016). The decline in GFAP levels persisted at Week 2, with a significant decrease compared to the control group (P = 0.043) and the Baseline (P = 0.008). Interestingly, by Week 4 post-induction, there was a slight increase in GFAP immunoreactivity, leading to the absence of a significant difference between the NMOSD-ON group and the control group as for GFAP expression. Despite this partial recovery, GFAP levels remained significantly lower at Week 4 compared to the Baseline (P = 0.001) (Figure. 1E, F, and G).

Progressive Demyelination

The mice in the NMOSD-ON group exhibited a substantial decrease in MOG immunoreactivity, a key indicator of oligodendrocytes, compared to the control group. Over the course from Week 2 to Week 4, there was a notable reduction in MOG protein levels (immunoreactivity) as compared to the control group (P < 0.001 and P < 0.001 at Week 2 and Week 4, respectively). Simultaneously, there was a significant decline in MOG protein levels from Week 2 to Week 4 when compared to the Baseline (P = 0.003 and P < 0.001 at Week 2 and Week 4, respectively) (Figure. 1H, I, and J).

Activation of microglial and pro-inflammatory cytokines

The mice in the NMOSD-ON group exhibited a temporal pattern of microglial activation and neuronal damage. CD68 is a marker for activated microglia, not exclusive to these cells. Iba-1, highly expressed in microglia, is a pan-microglial marker, identifying all microglia regardless of activation, while CD68 is linked to microglial phagocytic function. Analyzing the ratio of CD68/Iba-1 differentiates between resting and activated microglia [68–71]. CD68⁺ cell numbers significantly increased from Week 1 (P = 0.012) to Week 2 (P = 0.011) as compared to the control group in the current study. The ratio of CD68⁺/Iba-1⁺ cells also significantly increased from Week 1 to Week 2 (P = 0.001 and P = 0.009 at Week 1 and Week 2, respectively, as compared to the control group) (Figure. 2A and B).

Our examination also focused on the activation of cytokines in the mouse optic nerve under NMOSD-like conditions. This investigation involved conducting RT-qPCR following the induction of NMOSD-ON to evaluate gene expression of pro-inflammatory cytokines in Week 1 when the activation of microglial reaches a peak during the disease course. The results revealed a notable increase in the gene expression levels of IL-1β, IL-6, TNF-α, CXCL10, BDNF (P = 0.044, P = 0.047, P = 0.007, P < 0.001, P = 0.009 respectively) in the NMOSD-ON group in comparison to the control group (Figure. 2C). However, no notable variance in the expression of IL-1β, IL-6, TNF-α, CXCL10, and BDNF was detected at Day 2, Week 2, and Week 4 (Figure. 2C). Furthermore, no marked increase in NGF occurred at any of the assessed time points (Figure. 2C).

Loss of Retinal Ganglion Cells bodies and axons

The quantitative analysis of NF200 immunoreactivity, a key indicator of neuronal integrity, was conducted at different time intervals. Our results demonstrated a considerable decline in NF200 immunoreactivity between Week 2 and Week 4 (P = 0.013 at Week 2, P = 0.001 at Week 4 as compared to the control group; P < 0.001 at Week 2, P < 0.001 at Week 4 as compared to the Baseline) (Figure. 3A, B, and C).

Moreover, the survival rate (cell numbers) of RGCs in the whole-mounted retina over the course of the study was examined. Our data exhibited a notable decrease in averaged RGCs numbers within the NMOSD-ON group at Week 2 and Week 4 in comparison to the control group (P < 0.001 for both time points), indicating a time-related depletion of RGCs. No significant distinctions were observed between the NMOSD-ON group and the control group at Baseline or Week 1 (Figure. 3E, and F).

In-vivo retinal structural changes evaluated by OCT

Compared to the control group, the RNFL was significantly thinner in the NMOSD-ON group at Week 2, Week 3, and Week 4 (P = 0.018, P = 0.002, P = 0.021, respectively) (Figure. 4A and D). No significant differences were observed between the NMOSD-ON group and the control group for the INL, GCIPL, and Inner retina at any time point (Figure. 4B, C, and D).

Impairment of visual pathway assessed by VEP and ERG

The N1P1 wave amplitude in VEP response, indicative of optic nerve functionality, showed a significant decrease in the NMOSD-ON group compared to the control group at Week 2 (P < 0.001), Week 3 (P = 0.002), and Week 4 (P = 0.019) (Figure. 5B and D). Additionally, the NMOSD-ON groups showed delayed N1 latency at Week 2 (P = 0.017), Week 3 (P = 0.050), and Week 4 (P = 0.010). However, no significant variation is discernible in the P1 latency (Figure. 5C and D). ERG revealed progressive inner retinal dysfunction in the NMOSD-ON group. Compared to the control group, the NMOSD-ON group showed a significant decrease in pSTR amplitude at Week 2 (P < 0.001), Week 3 (P = 0.002), and Week 4 (P < 0.001) (Figure. 6A and D). In contrast, no significant differences of both amplitudes and latencies were observed between the NMOSD-ON group and control group for the a-wave, and the b-wave of the scotopic ERG response (Figure. 6B and C).

To integrate all results together, the protein expression and damage levels in the NMOSD-ON group are shown as a percentage of the control group values over time to observe the temporal changes throughout the disease progression. AQP4 protein expression decreased to 1.2% on Day 2 and then increased to 12.5% by Week 4. GFAP protein expression decreased to 2.3% at Week 2 and then increased to 30.9% by Week 4. The proportion of activated microglia increased by 2.43 times and then slightly decreased to 1.16 times by Week 4. However, MOG protein expression, NF200 expression, and RGCs cell numbers progressively decreased to 27.1%, 27.5%, and 76.7%, respectively, by Week 4. In VEP, the N1-P1 amplitude dropped to 47.7% in Week 2 but slightly recovered to 59.1% in Week 3 and 61.1% in Week 4. The N1 latency progressively increased to 1.18 times in Week 1, 1.15 times in Week 2, 1.28 times in Week 3, 1.30 times in Week 4. Furthermore, the pSTR amplitude in ERG decreased to 26.4% in Week 2 and then recovered to 59.4% and 54.8% in Week 3 and Week 4 (Figure. 7A, B).

Previous studies have indeed employed systemic induction of NMOSD as it can simulate blood-brain barrier disruption by involved pre-existing Experimental Autoimmune Encephalomyelitis (EAE) [15, 72–74]. However, as EAE might also play a role in demyelination, the presence of EAE complicates the isolation of AQP4-IgG's specific effects [15, 74]. The approach in the current study is able to specifically present the AQP4-IgG effects and fully capture the sequential process of AQP4 loss, astrocyte injury, and demyelination in the optic nerve. By isolating the AQP4-IgG effects, this method allows for a more targeted investigation of the pathogenic mechanisms underlying NMOSD-ON, without the confounding influences of EAE-related factors. This specificity enables a clearer understanding of the direct impact of AQP4-IgG on the observed disease progression and pathological changes in the optic nerve. In addition, we maintain consistency with prior research by utilizing female animals to better represent the gender disparity noted in human patients [75].

The findings in the current study show a sequence of events: initial loss of AQP4 expression within 2 days, followed by astrocytic damage, microglial activation, demyelination in one week, and neurodegeneration of RGCs over 2 weeks. The sequence of events converged and were depicted in a progressive manner (Figure. 7C). For the first time, retinal function and visual pathway function were assessed in a NMOSD-ON model using both ERG and VEP. The findings also firstly demonstrate that the N1 latency in VEP can identify demyelination concurrent with the loss of MOG proteins. This underscores the significance of utilizing functional evaluations to monitor the advancement of NMOSD-ON. In-vivo structural analysis using OCT complemented histopathological changes observed over time.

To study the NMOSD-ON animal model more accurately, the animal model-induced protocol was optimized by utilizing mice. While acknowledging that mice may not fully replicate the activation observed in human NMOSD, various studies suggest the value of using mice as a model for studying this disease [35, 76–79]. The single injection was unsuccessful in creating the NMOSD-ON animal model as it failed to trigger the depletion of AQP4 protein in a previous study [35]. The use of a syringe pump plays a crucial role in replicating the gradual buildup of AQP4-IgG and complement activation seen in NMOSD patients. As part of our initial investigation, we conducted a pilot study to refine our animal model induction. In a pilot study, a comparison between the effects of single and double injections (two conjunctive injections with a 24-hour interval) of AQP4-IgG was conducted to improve and optimize the animal model. The double injections resulted in increased significant accumulation of AQP4-IgG (P < 0.001 as compared to both control group and single injection protocol for both mean grey value and percentage of affected area over total area), significant recruitment of C5b9 (P = 0.030 vs. single injection and P = 0.005 vs. control group) observed 48 hours post administration (Figure. 8A, B, and C). The pilot study indicates that the use of a double intracranial injection technique with a syringe pump protocol in the NMOSD-ON model more efficiently induces the buildup of autoantibodies and activation of complement. This underscores the significance of accurate and controlled delivery of AQP4-IgG through repetitive infusion along with a syringe pump to establish the NMOSD-ON animal model as previously described [35]. The present model also emphasizes the significance of AQP4-IgG and complement exposure to the posterior part of the optic nerve while previous NMOSD models have typically targeted the anterior optic nerve [49, 80], as posterior optic neuritis that affects the optic chiasm and the posterior segment of the optic nerve is a notable and common symptom of NMOSD-ON [81, 82]. This condition can lead to serious and permanent loss of vision [33, 35, 49, 75, 81, 83–86].

The observed loss of AQP4 protein at day 2 in our model corresponds with the pathological characteristic of NMOSD in human autopsy samples [17, 87]. Similar findings have been reported in other NMOSD animal models [10, 80]. That is an interesting observation about the differences in the timing of AQP4 loss reported in the literature [35, 49, 88, 89]. The timing of AQP4 loss may be influenced by the route of administration. Direct approaches, like intracranial [56, 90], intrathecal injections [26], and injection underneath the optic nerve sheath [49, 80] could lead to quicker AQP4 loss, demyelination, and axonal loss manifestation as compared to systemical administration [15, 91, 92]. Additionally, the choice of using recombinant AQP4-IgG purified from patient sera could indeed lead to differences in the temporal dynamics of AQP4 loss in the NMOSD-ON animal model. Recombinant AQP4-IgG can be engineered to have higher binding affinity and specificity for the AQP4 antigen compared to the heterogeneous population of antibodies found in patient-derived AQP4-IgG [10, 93]. The homogeneity of the recombinant antibodies can lead to a more consistent and efficient activation of the complement system, speeding up the process of AQP4 loss [3, 10]. The early reduction of AQP4 in NMOSD suggests that optic nerve involvement begins earlier than previously thought, altering the disease timeline [26, 74]. This sheds light on the potential role of AQP4 loss as a key factor in initiating inflammatory processes in NMOSD-ON. Further research on early molecular events in NMOSD-ON is now possible, leading to the discovery of new biomarkers and insights into disease progression mechanisms.

The findings of the current research reveal the temporal fluctuations in GFAP immunoreactivity in the NMOSD-ON animal model. The documented decrease in Week 1, followed by a partial recovery in Week 4, in GFAP expression aligns with the established astrocyte pathology in NMOSD [10, 17, 35, 49, 88, 94]. This reduction indicates that the peak of astrocyte injury or loss occurs in Week 1, which may be a critical window for therapeutic intervention to prevent irreversible astrocyte loss and subsequent neuronal damage. The partial recovery of GFAP levels in Week 4 could imply a degree of astrocytic resilience or a regenerative attempt within the optic nerve, although it is unlikely to represent a full recover to normal function. The body's natural repair mechanisms are important for recovery and limiting damage in diseases. Studying these processes could enhance our understanding of disease progression and recovery patterns. Clarifying these mechanisms may uncover crucial biological processes essential for recovery in this condition [17, 49, 95].

Specifically, microglial upregulation was not immediately apparent but became pronounced by Week 1 post-induction in this study. Interestingly, the heightened microglial activation did not endure; instead, a gradual decrease in microglial presence was noted in Week 2 and Week 4. This reduction in microglial activity may suggest a resolution phase of the inflammatory response [96]. The early and intense activation of microglia could be associated with the removal of damaged cells and debris, but it might also exacerbate neuronal and astrocyte injury through the release of pro-inflammatory cytokines and other neurotoxic substances (e.g., TNF-α, IL-1β, IL-6, CXCL10) [18, 34, 97, 98]. The upregulation of cytotoxic cytokines, like IL-1β, TNFα, IL-6, and CXCL10 and neurotrophic cytokines BDNF in the optic nerve tissue of the NMOSD-ON animal model in this study at Week 1 does indeed provide strong evidence that the peak of inflammation occurs during this early time point [23, 24, 29, 41, 99]. The subsequent weakening of microglial activation from its peak towards Week 4 indicates a shift in the inflammatory environment of the optic nerve. Reduction in inflammation may indicate CNS recovery from acute phase towards a less intense chronic state. Peak microglial activation is a crucial disease stage with potential harm. Weakening microglial activation indicates disease progression transition, possibly towards repair phase. Understanding inflammation fluctuations is a key to identifying different disease phases. Post-peak activation may signify transition to restoration phase. Changes in biomarkers could indicate disease progression and resolution mechanisms. [18, 19, 100].

The significant decrease in MOG protein, a key indicator of oligodendrocytes, in the NMOSD-ON animal model indicates that the disease results in demyelination [101]. Oligodendrocytes play a critical role in producing and upkeeping myelin, which is essential for the effective conduction of electrical impulses in the CNS [102]. Unlike in multiple sclerosis, demyelination in NMOSD is considered a consequence of astrocyte injury and the pro-inflammatory milieu [103, 104]. The findings of this study are consistent with the pathological hallmarks of NMOSD-ON in humans, which involve the targeting and destruction of oligodendrocytes by autoimmune mechanisms [17, 49, 101]. The significant decrease in MOG protein levels from Week 2 to Week 4 compared to the Baseline suggests that the destruction of oligodendrocytes continues to progress over time in the NMOSD-ON animal model [103].

The observed reduction in NF200 expression and the concomitant decrease in RGCs counts in our NMOSD-ON model are consistent with the pathological features of NMOSD-ON in the reported animal model, where axonal damage and cell bodies loss of RGCs are hallmarks of the retinal involvement [17, 35, 74, 105]. The temporal progression of these changes aligns with the clinical course of NMOSD, where optic neuritis leads to visual impairment [17, 105–107]. The lack of significant differences at Day 2 and Week 1 suggests that the initial phase of the disease may not involve overt neuronal damage, which is in agreement with previous studies indicating a delayed onset of neurodegeneration following inflammatory attacks [35, 49].

The progressive loss of MOG, NF200 proteins, and RGCs cell bodies in whole-mounted retina up to Week 4, without any signs of recovery, has profound implications for understanding the potential long-term outcomes in NMOSD-ON. Together, the progressive depletion of MOG, NF200, and RGCs cell bodies underscores the severity of myelin and RGCs injury in NMOSD-ON, pointing to a continuous degenerative process affecting both the myelin sheath and the neurons themselves. The lack of protein level recovery by Week 4 indicates that the damage experienced during the initial phases of NMOSD-ON could be irreversible, potentially resulting in lasting neurological impairments in advanced stages. This study highlights the critical importance of understanding late NMOSD-ON stages to gain insights into myelin and axonal damage progression mechanisms. A multi-faceted approach is essential, focusing on inflammation, myelin regeneration, and neuroprotection processes.

The progressive thinning of the RNFL observed in OCT scans of the NMOSD-ON group aligns with findings of RNFL reduction in NMOSD-ON patients during OCT assessment [2, 32, 108–110]. The RNFL thinning, with significant changes emerging as early as 2 weeks, aligns with the reported degeneration of RGCs in the previous NMOSD-ON animal model and the pathological alteration of RGCs in our model [33, 74]. This suggests that RNFL loss may be a structural biomarker of the retinal pathology in NMOSD-ON. Interestingly, the inner retinal layers, such as the INL and GCIPL, exhibited no notable variances between the NMOSD-ON group and the control group. This selective vulnerability of the RNFL compared to the inner retinal layers has also been observed in human NMOSD studies [38, 110, 111]. The comprehensive characterization of structural changes in retina provided by this multimodal approach, combining OCT and histological findings, highlights the value of OCT as a non-invasive imaging technique for monitoring disease progression in the NMOSD-ON animal model.

Furthermore, the functional impairment documented through ERG and VEP tests correlated with the observed pathological changes. The progressive decline in visual function corresponds with RGCs degeneration and optic nerve pathology, highlighting the relevance of these tests in assessing disease progression and treatment effectiveness in NMOSD-ON models [103]. These ERG findings, demonstrating selective impairment of the pSTR without alterations in the a-wave or b-wave, suggest that the inner retinal neurons, particularly RGCs, are preferentially affected in this NMOSD-ON model. This study represents a pioneering effort in the exploration of retinal function within the context of the NMOSD-ON animal model. The utilization of these electrophysiological measures provides a comprehensive assessment of retinal integrity and function, offering insights into the early and subtle changes that occur in the retina as a result of NMOSD-ON. [59, 112–115]. The temporal pattern of pSTR amplitude reduction aligns with the structural and functional deficits observed in the OCT and VEP analyses, providing converging evidence of progressive inner retinal pathology in this disease model. The animals in NMOSD-ON group in our study did not show any significant delay in the a- and b-waves in scotopic ERG responses. This lack of delay may be attributed to the secondary injury condition of demyelination after astrocyte damage in NMOSD-ON, rather than the primary injury of the myelin sheath seen in typical ON conditions like multiple sclerosis-associated optic neuritis (MS-ON) [17, 116]. The temporal pattern of VEP alterations, with amplitude reductions and latency delays emerging at the same time points as the beginning of demyelination (loss of MOG protein) and axonal degeneration (loss of NF200 protein), offers insights into the dynamic nature of the visual functional impairment in this disease model. In a prior investigation [49], a notable decrease in amplitude was observed, reaching statistical significance when compared to the control group by the first week. This suggests an accelerated decline in visual function as compared to our findings. However, the extent of this reduction at Week 1 (approximately 10 µV) aligns closely with our findings [49]. The detection of changes in N1 latency lining with the pathological demyelination within our model not only reinforces its relevance as a pivotal marker for demyelination but also emphasizes the potential for in-vivo monitoring of demyelination processes [66]. Such monitoring is invaluable, as it opens avenues for timely medical interventions aimed at promoting remyelination, thereby mitigating the progression of demyelinating diseases [66, 117, 118]. The correlation between functional deficits in VEP and ERG responses and structural changes in OCT and histological analyses provides a comprehensive view of NMOSD-ON pathology in this animal model. This integration of electrophysiological and structural assessments offers a holistic understanding of disease progression.

Indeed, the systemic induction of the NMOSD-ON animal model in the previous study represents a significant strength. It acknowledges NMOSD as a systemic disorder, providing a more holistic approach to understanding the disease. However, it failed to accurately mimic retinal involvement as seen in human NMOSD-ON [45, 119, 120]. The successful induction of retinal involvement in our NMOSD-ON animal model through direct delivery of AQP4-IgG to the optic nerve allows for the study of progressive retinal pathological profiles in the context of NMOSD-ON. By combining pathological evaluation with functional evaluation (ERG, VEP), in-vivo structural measurement (OCT), and targeted induction of the disease, our study contributes to a more comprehensive understanding of the structural and potential cellular changes in NMOSD-ON.

The primary limitation of our study lies in its cross-sectional design of pathological evaluation, which may not adequately capture the dynamic progression of NMOSD-ON pathology over time. While NMOSD-ON evolves, a snapshot approach could overlook crucial transitional stages or variations in disease progression among animals and patients. Although OCT is useful for in-vivo follow-up by measuring retinal layer thickness, it does not directly observe cellular bodies. The present study has another limitation in not exploring the interactions among different proteins and the interplay among various cell types associated with NMOSD-ON. Subsequent research should delve into these intricate inter-protein and intercellular relationships to achieve a more thorough comprehension profile.

The detailed characterization of the temporal progression of pathological changes, from initial AQP4 reduction to subsequent astrocyte damage, microglial activation, demyelination, and neurodegeneration, provides a comprehensive profile of the NMOSD-ON animal model. The VEP and ERG findings highlight the utility of sensitive functional readouts for monitoring demyelinating and axonal degeneration events in this preclinical model. Thinning of the RNFL in OCT measurement serves as a precise and responsive biomarker for monitoring the progression of the disease.

Financial Disclosures:

The work was partially supported by the General Research Fund (GRF) from the Research Grants Council (RGC) of the Hong Kong SAR, China (Project No. 15103522 to S.Tan), the Internal Research Grant from the Hong Kong Polytechnic University 2021-23 (P0035512 to S.Tan and P0035375 to HHL.Chan), the Innovation and Technology Commission of the HKSAR Government (ITC InnoHK CEVR Project), and PolyU Research Center for Sharp Vision (P0039595).

The Echic approval and consent to participate

This study was conducted in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. The research protocol was reviewed and approved by the Animal Subjects Ethics Sub-committee in The Hong Kong Polytechnic University with the approval number 20-21/127-SO-R-GRF. All animal procedures were performed in accordance with the guidelines and regulations set forth by the Centralised Animal Facilities (CAF).

Author Contributions

Conceptualization, Shaoying, Tan; methodology, Xiayin Yang, Shi-Qi Yao; software, Xiayin Yang; validation, Shaoying, Tan, Henry Ho-lung Chan; formal analysis, Shaoying, Tan, Shi-Qi Yao; investigation, Shaoying, Tan, Henry Ho-lung Chan; resources, Shaoying, Tan; data curation, Xiayin Yang; writing—original draft preparation, Xiayin Yang; writing—review and editing, Shaoying, Tan; visualization, Shaoying, Tan, Henry Ho-lung Chan; supervision, Shaoying, Tan, Henry Ho-lung Chan; project administration, Shaoying, Tan; funding acquisition, Shaoying, Tan. All authors have read and agreed to the published version of the manuscript.

Funding

The work was partially supported by the General Research Fund (GRF) from the Research Grants Council (RGC) of the Hong Kong SAR, China (Project No. 15103522 to S.Tan), the Internal Research Grant from the Hong Kong Polytechnic University 2021-23 (P0035512 to S.Tan and P0035375 to HHL.Chan), the Internal Research Grant from the Hong Kong Polytechnic University 2021-23 (P0035512 to S.Tan and P0035375 to HHL.Chan), and the Innovation and Technology Commission of the HKSAR Government (ITC InnoHK CEVR Project), and PolyU Research Center for Sharp Vision (P0039595).

Consent for publication

The manuscript/study is original and unpublished elsewhere. All authors have contributed significantly and agree with the content. Data and materials have proper permissions. No copyright infringement. Reviewed and approved for publication.

Availability of data and material

The datasets that back the discoveries of this study can be obtained from the corresponding author upon a reasonable request.

Acknowledgments

We are grateful to all participants in the preparation of this research article. We would like to thanks the research students and staff at the School of Optometry in the Hong Kong Polytechnic University for their assistance.

Competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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No competing interests reported.

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The Temporal Dynamics of Pathological Profile and Functional Impairment in Neuromyelitis Optica Spectrum Disorders associated Optic Neuritis

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Abstract

Figures

Introduction

Methods

Neuromyelitis optica (anti-aquaporin-4, AQP4) antibodies

Establishment of an optimized NMOSD-ON animal model

Experimental time course

Immunostaining for histological assessment

Quantitative Real-Time PCR (polymerase chain reaction) (qRT-PCR) for testing released cytokines

GAPDH:

Reverse primer: CTCGTGGTTCACACCCATCA

IL-6:

IL-1β:

Reverse primer: GAAGACACGGATTCCATGGT

TNF-α:

Reverse primer: CGATCACCCCGAAGTTCAGTAG

CXCL10:

Forward primer: GCCGTCATTTTCTGCCTCAT

BDNF:

Forward primer: TGA CAA CGA CAT CGC ATT AC

Reverse primer: TTC AGC CGG TCA GAG AAG

Forward primer: CAA TAG CTG CCC GAG TGA CA

Reverse primer: TCC GGT GAG TCC TGT TGA AAG

Functional measurement

In-vivo structual retinal assessment

Data Collection and Analysis

Results

Temporal progression of pathological changes

Early Depletion of AQP4 and Astrocyte Impairment

Progressive Demyelination

Activation of microglial and pro-inflammatory cytokines

Loss of Retinal Ganglion Cells bodies and axons

In-vivo retinal structural changes evaluated by OCT

Impairment of visual pathway assessed by VEP and ERG

Discussion

Conclusion

Declarations

References

Additional Declarations

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