Flecainide enhances blood-brain barrier function: Novel mode of action of sodium channel blocking in experimental autoimmune encephalomyelitis (EAE)

doi:10.21203/rs.3.rs-4835767/v1

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Research Article

Flecainide enhances blood-brain barrier function: Novel mode of action of sodium channel blocking in experimental autoimmune encephalomyelitis (EAE)

https://doi.org/10.21203/rs.3.rs-4835767/v1

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Introduction

Multiple Sclerosis (MS), an autoimmune disorder, is characterized by severe neuroinflammation, leading to demyelination and neuronal damage in the CNS, resulting in significant clinical impairment. MS progression involves complex pathological processes like immune cell invasion and cytokine-mediated recruitment to the CNS. Experimental autoimmune encephalomyelitis (EAE), a model for MS, has been crucial for identifying effective treatments. Recent studies have shown that sodium channel (Nav) blockers and monoamine oxidase- (MAO) B inhibitors can alleviate symptoms of EAE and optic neuritis (ON), but their mode of action remains partially unclear.

Methods

To evaluate the effects and understand the action mechanism of Nav blockers and MAO-B inhibitors (rasagiline ,safinamide, flecainide and phenytoin) in neurological conditions, various techniques were used, including optical coherence tomography (OCT), optomotor response measurement (OMR), flow cytometry, histological evaluations, Evans blue assay, blood-brain barrier (BBB) permeability assay and gene expression analyses.

Results

The study found that the primary therapeutic effect comes from inhibiting the Nav 1.5 sodium channel, not MAO-B inhibition. Flecainide, a Nav 1.5 channel blocker, significantly reduced EAE disability scores, mitigated neurodegeneration, preserved visual function, and restricted immune cell migration into the CNS. Importantly, blocking the Nav 1.5 channel had an effect on the BBB, limiting lymphocyte entry into the CNS.

Discussion/Conclusion

This research highlights sodium channel blockers' potential in treating neuroinflammatory diseases like MS. The findings demonstrate reduced disease progression and neuroprotection, suggesting a novel therapeutic approach. Crucially, it reveals for the first time that Nav 1.5 channel blockade leads to neuroprotection primarily by affecting the BBB, a key factor in controlling immune cell migration, thus addressing a critical aspect of MS pathology.

Flecainide

Rasagiline

Safinamide

Sodium-channel blocking

MAO-B inhibition

Neuroprotection

Multiple Sclerosis

Blood-Brain-Barrier

EAE

Multiple Sclerosis (MS) is an inflammatory autoimmune disorder characterized by inflammation, demyelination, oligodendrocyte loss, subsequent axonal damage, and neuronal degeneration within the central nervous system (Reich et al., 2018). The degenerative aspect primarily accounts for the persistent clinical disability in MS patients, which remains unresponsive to conventional immunosuppressants and most immunomodulatory therapies. MS-related pathological alterations are typically marked by infiltrates of lymphocytes and macrophages into the central nervous system (CNS) parenchyma, instigating the upregulation of adhesion molecules and promoting immune cell recruitment via inflammatory cytokines. This cascade results in glial and subsequent neuronal injury through a not yet fully elucidated mechanism. Increased oxidative stress has been hypothesized to play a significant role in neuronal damage (Fischer et al., 2012), as activated immune cells may release reactive oxygen or nitrogen species. While the exact underlying mechanism remains unclear, recent research has proposed that the Epstein-Barr virus infection might be prominently involved in the pathogenesis of MS (Bjornevik et al. (2022). Additionally, the MultipleMS Consortium (2023) highlighted that the varying severity of MS among patients could be due to distinct genetic variants, which act primarily independent of immune responses, suggesting that CNS resilience plays a crucial role in the progression of MS. In light of these findings, MS's intricate nature, influenced by genetic, environmental, and lifestyle factors, necessitates ongoing research for accurate diagnosis and effective treatment, with a primary aim to improve the quality of life for patients battling this disease.

Sodium channel blockers are distinguished by their varied pharmacological properties, primarily modulating membrane action potentials through different mechanisms. These agents are categorized into subclasses based on their specific effects, with some exhibiting dual inhibitory actions, such as targeting sodium channels and inhibiting monoamine oxidase (MAO)-B activity. Others demonstrate selective affinity, primarily inhibiting sodium channels. The specificity among these blockers ranges from compounds targeting particular sodium channel subtypes to those affecting multiple types indiscriminately. Recent research has sparked interest in these blockers due to preliminary evidence of their beneficial effects in EAE and Optic Neuritis (ON), though their underlying mechanisms remain largely unexplored.

The intricate nature of experimental autoimmune encephalomyelitis (EAE), an animal model of human MS, has prompted a myriad of investigations into its etiology and treatment. The non-selective MAO inhibitor, phenelzine, has been shown to attenuate the progression of EAE (Musgrave et al., 2011), indicative of the potential therapeutic efficacy of MAO inhibitors. Sodium channel (Nav) blockade, exemplified by non-selective Nav-blocker phenytoin, has also been proposed as a potential avenue for MS treatment, as it protects axons from degeneration by averting an energy deficit (Bechtold et al., 2004) and suppresses the activation of innate immune cells in the CNS (Hashiba et al., 2011). In addition, research points to direct effects on microglial cells (Craner et al., 2005) and a reduction in CD45 + infiltrates in the CNS upon phenytoin treatment. Safinamide, a combined MAO-B inhibitor and non-selective sodium channel blocker, has also shown promising results, as it diminished the formation of superoxide and increased GSH-level in microglia culture, leading to reduced CD68 + monocytes in the spinal cord of EAE mice (Morsali et al., 2013). Similarly, flecainide, a sodium channel blocker, has also been found to reduce CD68 + cell activation/infiltration (Morsali et al., 2013).

Beginning with evaluating their overall therapeutic benefits, we will progress to a detailed analysis of the most effective compound, focusing on its mechanism of action. This understanding is crucial for exploring their potential in treating diseases like MS. The findings from this research could significantly advance MS treatment strategies and contribute to the field.

2.1 Animals, animal models, treatment

Female, 6-week-old C57BL/6J mice were purchased from Janvier Labs (Le Genest-Saint-Isle, France). The NOD/ShiLtJ mice (Female, 6 week old) originate from the internal breeding facility (ZETT) at the University of Düsseldorf. EAE mouse model: Mice were immunized with 200 µg of myelin oligodendrocyte glycoprotein fragment 35–55 (MOG35–55), purchased from BIOTREND emulsified in 200 µl of complete Freund’s adjuvant (CFA), supplemented with 800 µg of heat-killed Mt., H37Ra, both purchased from BD Difco (injected subcutaneous, distributed over four spots on the hind and front flank) and additional intraperitoneal injections of 200 ng of pertussis toxin (PTX) from Sigma-Aldrich on days 0 and 2 after immunization (p.i.). The sham control group (sham) also received PTX and CFA, but no MOG35–55 peptide. The substances used for treatment, their concentration, mode of action, treatment interval and treatment start are described in Table 1. The used concentrations for each substance were adapted from recent dose finding studies found in the literature investigating the optimal dose and are listed in Table 1 (Supplementary).

Table 1

Substance treatment details
Compound	Rasagiline	Safinamide	Flecainide	Phenytoin
Administration form	Oral administration	Oral administration	Subcutaneous injection	Subcutaneous injection
Concentration	5 mg/kg/bw	8 mg/kg/bw	30 mg/kg bw	50 mg/kg bw
Mode of action	-Selective MAO-B inhibition	-Reversible MAO-B inhibition -Sodium and calcium channel blocking -Glutamate release inhibition -Dopamine and serotonine reuptake inhibition	-Selective Nav1.5 sodium channel blocker	-unselective Nav1.1, Nav1.2, Nav1.3, Nav1.5 and Nav1.6 sodium channel blocker
Treatment interval	Daily	Daily	Daily	3 times / week (Hashiba et al., 2011)
Treatment start	Directly p.i.	Directly p.i.	Directly p.i.	Directly p.i.
CAS	161735-79-1 (Sigma Aldrich)	202825-46-5 (Sigma Aldrich)	54143-56-5 (Sigma Aldrich)	630-93-3 (Sigma Aldrich)

2.2 OCT measurements

Periodic OCT measurements were conducted using the Spectralis® HRA + OCT device (Heidelberg Engineering, Germany) with several adaptations for rodents, as previously described (Dietrich et al., 2017). Segmentation of retinal volume scans was performed using the Heidelberg Eye Explorer software, with manual control for segmentation errors. The volume of the parapapillary region was assessed using the ETDRS grid, excluding the center with the disc, as published previously (Dietrich et al., 2022). Inner retinal layer (IRL) thickness was examined at defined intervals after irradiation and compared with baseline measurements (IRL: NFL, GCL, and IPL layer)

For the measurements, the animals were anesthetized using isoflurane (Vaporizer from Harvard Apparatus Anesthetic Vaporizors; Isofluran from Piramal critical care). Specifically, induction was carried out at 3.5% isoflurane, followed by maintenance at 2% isoflurane, with a flow rate of 0.6 L/minute of oxygen. The gas was transferred through nose cones to the mice.

2.3 Optomotor response (OMR) measurements

OMR measurements were performed periodically, exclusively in C57Bl/6J mice, using the OptoMotry® device from Cerebral Mechanics, in parallel with OCT measurements. Spatial frequency was monitored as a parameter for visual function. The spatial frequency threshold was determined by randomly changing the spatial frequency to identify the threshold at which the mouse could track, as previously described (Dietrich et al., 2022, Hecker et al., 2020).

2.4 Histology (Optic nerves and retinal whole mounts)

Mice were euthanized using 100 mg/kg Ketamine und 20 mg Xylazin i.p. (in 250 µl NaCl 0,9%) followed by cardiac perfusion using phosphate-buffered saline (Gibco, Carlsbad, USA). The optic nerves were then isolated and fixated in 4% paraformaldehyde (Carl Roth, Karlsruhe, Germany) overnight. After fixation, the optic nerves were subjected to a sucrose gradient for dehydration and subsequently embedded in O.C.T. compound (Sakura™ Finetek, Alphen aan den Rijn, Netherlands). Longitudinal sections of five micrometers were cut and prepared for fluorescence staining. Longitudinal sections of the optic nerves were used for quantifying T-Lymphocytes (CD3 (Clone 17A2), 1:200, Biolegend), assessing the state of myelination (MBP (Clone 12), Merck Millipore, 1:200), and evaluating microglial activation (Iba1 (Clone GT10312), 1:200, Merck) using Leica HyD detector attached to a Leica DMi8 confocal microscope (63x objective lens magnification). Cy3 goat anti-mouse (1:500 Millipore), Cy3 goat anti-rat (1:500, Millipore) and Cy3 goat anti-rabbit (1:500, Invitrogen) were used as secondary antibodies. The numbers of cells stained with CD3 and Iba1 were analyzed using ImageJ software, applied by blinded raters, and expressed as a ratio to DAPI staining. The overall signal for MBP (positive total area in the red channel) was analyzed using ImageJ software. RGC count was calculated by a semi-automated count of Brn3a + cells on retinal flatmounts. Briefly, retinae were stained with Brn3a (1:200, Santa Cruz Biotechnology, cat# sc-31984) antibody and flat-mounted on glass slides. Each retina was then divided into four quadrants (three areas per quadrant: central, mid-periphery, and far-periphery). For each eye, Brn3a + cell count was summed up from all 12 areas imaged.

2.5 Evan´s Blue Dye assay

Evan's Blue Dye (EBD) is a diazo dye that binds to serum albumin, creating a large molecular complex that normally does not cross the intact blood-brain barrier (BBB). However, in pathological conditions leading to increased BBB permeability, the EBD-albumin complex can cross the BBB and accumulate in brain tissue, thus providing a measurable indication of barrier disruption. At the pre-determined time points of 18 days post-immunization, the mice were injected intravenously with 4% Evan's Blue Dye in saline at a dosage of 4 ml/kg body weight. The dye was allowed to circulate for 3 hours to ensure systemic distribution. After the circulation period, the mice were anesthetized and transcardially perfused with phosphate-buffered saline (PBS) to remove intravascular dye. The brains and spinal cords were then carefully extracted, weighed, and homogenized in N,N-dimethylformamide to extract the dye from the tissue. The samples were then centrifuged, and the supernatants were collected for spectrophotometric analysis. Quantification of the EBD was performed using a TECAN spectroscopic device. The absorption of the extracted solutions was measured at 620 nm, a wavelength at which EBD exhibits a distinct peak. EBD concentration was calculated from the absorbance values using a standard curve generated with known concentrations of EBD. The amount of EBD in the brain tissue was then expressed as µg of EBD per g of brain tissue. All data were collected and analyzed using appropriate statistical methods.

2.6 Flow cytometry analysis

Flow cytometry was used to examine the lymphocyte subpopulations in spinal cord and spleen of the EAE mice at specified time points.

Spinal cords were carefully harvested and mechanically and enzymatically (Collagenase, DNAse) dissociated. Lymphocytes were then isolated from the suspension using a LymphoprepTM-gradient (Stemmcell technologies). Spleen was collected and mechanically dissociated by passing it through a 40 µm cell strainer. Red blood cells were lysed with ACK Lysis Buffer and suspension was again passed through a 40 µm cell strainer.

Lymphocytes from both organs were centrifuged and resuspended in PBS, containing 2 mM EDTA and 2% fetal calf serum. Cells were then stained with fluorochrome-conjugated monoclonal antibodies (Table 2) in the dark at room temperature for 15 minutes. The cells were then washed with staining buffer and prepared for analysis. Cells were analyzed on a CytoFLEX S (Beckman Coulter) and data was interpreted using Kaluza Analysis Software (Beckman Coulter). Lymphocytes were identified based on forward and side scatter properties, with specific populations determined by surface marker expression (representative gating strategy is stated in figure S1). Data are reported as the percentage of each cell type within the total lymphocyte population.

Table 2

Antibodies used for flow cytometry analysis
Fluorochrome	Antigen	Clone	Company
BrilliantViolet421	CD4	RM4-5	BD Biosciences
BrilliantViolet605	CD8	53 − 6.7	Biolegend
BrilliantViolet650	CD3	17A2	Biolegend
FITC	CD11b	M1/70	Biolegend
PE-Cy5.5	Ly6G	1A8	Biolegend
PE	CD11c	N418	Biolegend
ECD	CD19	6D5	Biolegend
PE Dazzle594	CD25	PC61	BD Biosciences
APC	NK1.1	S17016D	Biolegend
Alexa Fluor 700	Ly6C	HK1.4	Biolegend
APC-Cy7	CD45	30-F11	Biolegend

Table 3

List of primers used for qPCR analysis Supplementary data
V-CAM-1 Forward Sequence GCTATGAGGATGGAAGACTCTGG Reverse Sequence ACTTGTGCAGCCACCTGAGATC I-CAM-1 Forward Sequence AAACCAGACCCTGGAACTGCAC Reverse Sequence GCCTGGCATTTCAGAGTCTGCT I-CAM-2 Forward Sequence GACGGTCTCAACTTTTCCTGCC Reverse Sequence CCATTTGGTTGTCCTGCATCGG PECAM-1 Forward Sequence CCAAAGCCAGTAGCATCATGGTC Reverse Sequence GGATGGTGAAGTTGGCTACAGG N-CAM-1 Forward Sequence GGTTCCGAGATGGTCAGTTGCT Reverse Sequence CAAGGACTCCTGTCCAATACGG	JAM-1 Forward Sequence CACCTACTCTGGCTTCTCCTCT Reverse Sequence TGCCACTGGATGAGAAGGTGAC JAM-2 Forward Sequence CAGACTGGAGTGGAAGAAGGTG Reverse Sequence GCTGACTTCACAGCGATACTCTC JAM-3 Forward Sequence GCATTGCTTCCAATGACGCAGG Reverse Sequence GATGAAGCAGCCTCGTCTGTAC Occludin Forward Sequence TGGCAAGCGATCATACCCAGAG Reverse Sequence CTGCCTGAAGTCATCCACACTC Integrin β-3 Forward Sequence CCATGATCGGAAGGAGTTTGCT Reverse Sequence AAGGTGGATGTGGCCTCTTTATAC

2.7 Isolation of primary mouse brain microvascular endothelial cells (pMBMECs)

pMBMECs were isolated according to different protocols for performing the quantitative PCR or the permeability assay. In both procedures, the pMBMECs were never passaged between isolation and experiment.

pMBMECs for the quantitative PCR: We began by euthanizing six-week-old female C57BL/6 mice. After euthanasia, we carefully extracted the brains from the mice. Following the extraction, we gently placed the brain tissue on sterile filter paper. This method allowed us to effectively remove the meninges from the brain tissue. Next, we homogenized the brain tissue to a consistent texture, preparing it for further processing. At this point, we moved on to follow the procedure specified by the adult brain dissociation kit from Miltenyi Biotec. This kit was specifically designed to facilitate the effective dissociation of brain tissue in mice. Finally, we isolated the desired microvascular endothelial cells from the resulting cell mixture. We used Miltenyi magnetic beads coated with antibodies against CD31, a marker for endothelial cells, to capture our cells of interest. Simultaneously, we removed unwanted cells, such as leukocytes, by using beads coated with antibodies against CD45. The CD45 negative and CD31 positive cells were then collected, providing us with a pure population of pMBMECs.

pMBMECs for the permeability assay: Microvascular brain capillaries were isolated by the method of Coisne et al. (2005) as follows: for each preparation cortices from 6 to 10 weeks old gender matched mice were isolated and meninges were removed. Preparations were pooled and homogenized in Hank's balanced salt solution containing 0.1% bovine serum albumin. The homogenate was mixed with 30% dextran and centrifuged at 3000g for 25 mins at 10°C. The pellet containing the vascular fraction was collected. Centrifugation and pellet harvesting was repeated once. The collected vascular fraction was then filtered through a 60 µm nylon mesh. The capillary-enriched filtrate was digested in DNase I (10 mg/mL), TLCK (0.147 mg/mL), and collagenase/dispase (2 mg/mL) for 30 mins at 37°C. The digestion was stopped by an excess of wash buffer and filtered through a 20 µm nylon mesh. The crude cell preparation of pMBMECs were cultured for 48 hours in the presence of 4 µg/ml puromycin, which allowed selective growth of BBB ECs only.

2.8 Quantitative PCR analysis

For our qPCR analysis, we utilized the QuantStudio 3 from Thermo Fisher Scientific, employing SYBR Green as our detection chemistry. After preparing and loading our samples, we conducted the qPCR run. The machine's sophisticated technology measured DNA quantity using the fluorescence of the SYBR Green. Post-run, we processed and interpreted the data using the QuantStudio Design and Analysis Software from Thermo Fisher Scientific, enabling us to calculate relative gene expression levels using the ΔΔCt method.

2.9 Permeability assay

Permeability assays were performed in triplicates as published (Coisne et al., 2005), with minor adaptations: pMBMECs were grown on Matrigel-coated Transwell® filter inserts (0.4 µm pore size, 6.5 mm diameter; article number 662640, Greiner Bio-One Vacuette Schweiz GmbH, St. Gallen, Switzerland) for 6 to 8 days. Alexa Fluor 680-dextran (3 kDa, 10 µg/ml; LuBioScience, Luzerne, Switzerland) was used as permeability tracer. Diffused dextran was quantified using the Odyssey Imaging System (LI-COR, Bad Homburg, Germany) and the clearance value (Pe, in cm/min) of the pMBMECs calculated as published (Coisne et al. 2005). Flecainide treatment at 5 µM was for 24 hours and IL-1β treatment at 20 ng/ml was for 16 hours. After the experiment, each filter was examined for confluent growth of pMBMECs by staining with phalloidin-rhodamine and subsequent fluorescence microscopy. The inflammatory state of pMBMECs after IL-1β stimulation was monitored in parallel samples by staining with the homemade rat anti-mouse ICAM-1 monoclonal antibody 29G1 followed by a secondary donkey anti-rat Cy5 antibody (Jackson ImmunoResearch, Milan Analytica AG, Rheinfelden, Switzerland).

2.10 Statistics

Statistical analysis was performed using Prism (version 9, Graphpad Software, Inc.) and IBM SPSS Statistics (version 20, IBM Corporation, USA). Total and percent changes of the acquired retinal parameters (OCT and OMR) were analyzed using generalized estimation equation (GEE) models, accounting for within-subject inter-eye correlations, to test for differences between the two groups. For non-paired data, group means analyses were compared using a one-way ANOVA with the Dunnett´s post hoc test, utilizing one optic nerve per animal for the histological investigations.

The thickness of the inner retinal layers, ranging from the inner limiting membrane to the bottom of the inner plexiform layer, the total retinal thickness and outer retinal layers were assessed in volume scans around the optic disc as the primary OCT-based outcome parameters. The spatial frequency served as a functional primary readout. The other histology-derived parameters were assessed as secondary outcome criteria. The severity of EAE symptoms, extending from minor hind limb weakness to complete paralysis, was assessed through a standardized scoring system (ranging from 0 to 5), providing a quantitative outcome measure of neuroinflammation and neurodegeneration. The EAE scores served as an integral part of the study, illustrating the clinical manifestation and progression of the disease, offering a real-time evaluation of the neurological impairment. QPCR was deployed for the precise quantification of targeted gene expression changes. The relative changes in gene expression levels were examined as one of the primary outcome measures, offering key insights into the molecular mechanisms underlying neuroinflammation. The qPCR results not only helped gauge the extent of the inflammatory response at the molecular level, but also assisted in understanding the effects of potential therapeutic interventions on these genetic pathways. The permeability of the BBB was further evaluated by using the Evans Blue assay. This approach involved the systemic administration of Evans Blue dye, the penetration of which into the brain tissue served as a direct indicator of BBB disruption. The quantified extent of dye penetration, extracted and measured spectrophotometrically, offered a primary outcome measure of BBB integrity. The data derived from the Evans Blue assay yielded essential insights into the degree and timing of BBB permeability changes in response to neuroinflammation and following various therapeutic interventions.

3.1 Assessment of clinical disability (EAE-scoring)

We aimed at determining the most promising pure sodium channel blocker for extended EAE studies in various rodent strains by conducting a preliminary screening experiment to discern the more effective candidate between flecainide and phenytoin. Both these drugs have been previously noted for their beneficial effects in EAE models, with flecainide (Bechtold et al., 2004; Morsali et al., 2013) being a selective sodium channel blocker and phenytoin (Hashiba et al., 2011; Liu et al., 2014) an unselective one.

Figure 1 demonstrates our experiment comparing two drugs' effectiveness in alleviating EAE symptoms, guiding future long-term study decisions. Flecainide emerged as the more effective of the two, demonstrating a superior ability to alleviate EAE conditions. This was quantitatively reflected in the mean difference (MD) of 0.4551 (± 0.0854, P: 0.0003), favoring flecainide over phenytoin. This led us to our decision to prioritize it in subsequent, more comprehensive EAE studies across different rodent strains. Rasagiline demonstrated no positive effects, whereas safinamide slightly improved EAE outcomes compared to the MOG vehicle (MD: 0.3196 ± 0.1249, P: 0.0120).

C57Bl/6J and Non-obese-diabetic (NOD) mice exhibit distinct EAE progression patterns: the former develops a more chronic progression with a disease peak around day 18 post-immunization, while the latter shows a relapsing-remitting course with complete recovery phases. In the mentioned subsequent studies, the impact of flecainide, rasagiline, and safinamide on EAE progression in these mouse models was evaluated over a period of 90 days p.i.. EAE, induced by immunization with MOG35-55, was scored clinically over time. The treatment groups were compared to the MOG EAE vehicle group, with n = 9 per group. The treatments were initiated from day 0 of immunization.

Figure 2A depicts the EAE clinical scoring in the acute progressive C57Bl/6J mouse model. Both flecainide (30 mg/kg s.c.) and safinamide (8 mg/kg o.s.) administration led to a significant reduction in EAE disability. The flecainide treated group exhibited a MD of 0.7711 (± 0.0649, P: 0.0002), while the safinamide treated group showed a MD of 0.2930 (± 0.0753, P: 0.0251). This result suggests a substantial reduction in disability with both flecainide and safinamide treatment compared to the MOG EAE group. Similarly, Fig. 2B represents the EAE clinical scoring in the chronic progressive NOD mouse model. Remarkably, treatment with flecainide (MD: 0.3335 ± 0.0528, P: 0.0010) and safinamide (MD: 0.2437 ± 0.0545, P: 0.0126) also significantly decreased EAE disability compared to the MOG EAE group.

The group treated with rasagiline did not show a significant reduction in disability in either of the mouse models when compared to the untreated MOG EAE group.

3.2 Evaluation of neurodegeneration and visual function via OCT and OMR

In addition to evaluating the impact of flecainide and safinamide on EAE disability, we also undertook a longitudinal evaluation of neurodegeneration and visual function via OCT (in C57BL/6J EAE and NOD EAE mice) and OMR (in C57BL/6J EAE mice) testing over 90 days post EAE induction (Fig. 3).

The OCT volume scans (Fig. 3A) evaluated the degeneration of the inner retinal layers (IRL). In C57BL/6J-EAE mice, flecainide treatment led to a significant reduction in IRL thickness change over 90 days post immunization, as depicted in Fig. 3B, with a MD of 1.940 (± 0.7879, P: 0.0004). However, no significant difference was observed in the safinamide and rasagiline treated groups compared to the MOG EAE vehicle group.

In NOD EAE mice, similar observations were made with flecainide treatment showing a significant reduction in IRL thickness change (MD: 1.844 ± 0.8840, P: 0.0162) as depicted in Fig. 3C. Moreover, safinamide also demonstrated significant reduction (MD: 1.473 ± 0.8223, P: 0.0061) in IRL thickness change in these mice.

The OMR test, measuring visual function in terms of spatial frequency (in cycles per degree), was performed only in the C57BL/6J-EAE mice due to the poor vision of NOD mice even in naïve conditions. In these tests, flecainide treatment resulted in a significant improvement in visual function compared to the MOG vehicle group (MD: 0.0458 ± 0.0347, P: 0.0111), as shown in Fig. 3E. No significant difference was observed in the safinamide and rasagiline treated groups.

In conclusion, these results indicate that flecainide significantly slows the neurodegeneration and preserves visual function in EAE mouse models. In NOD EAE mice, safinamide also showed significant protection against neurodegeneration. This supports the potential therapeutic benefits of these compounds in the context of neurodegenerative conditions like EAE.

3.3 Histological analyses of immunological markers in the optic nerve

We extended our investigation to the histological evaluation of immune cell markers, specifically focusing on CD3, a marker for T-cell infiltration, and Iba1 (ionized calcium-binding adaptor molecule 1) indicative of microglial activation. These markers were studied in longitudinal sections of optic nerves from C57Bl/6J and NOD mice, 90 days post-immunization. The quantitative analysis (A, B, D, and E) and representative illustrations (C) are shown in Fig. 4.

In C57Bl/6J mice, both flecainide and safinamide treatment showed significantly reduced infiltration of CD3 positive lymphocytes, compared to the MOG EAE group. Flecainide resulted in a MD of 1.8220 (± 0.4116, P: 0.0005), while safinamide showed a MD of 1.5323 (± 0.4317, P: 0.0048). In NOD mice, only flecainide treatment revealed a significant reduction in CD3 positive infiltrates (MD: 3.0239 ± 1.0146, P: 0.0228).

No significant difference in Iba1 expression was observed in C57Bl/6J mice across the treatment groups. However, in NOD mice, flecainide treatment led to a significant reduction in Iba1 positive cells compared to the vehicle treated EAE group (MD: 3.2844 ± 0.8723, P: 0.0036).

Taken together, our results suggest that both flecainide and safinamide treatment can significantly reduce T-cell infiltration in the C57Bl/6J EAE model. Additionally, flecainide significantly reduces both T-cell infiltration and microglial activation in the NOD-EAE model, implying potential anti-inflammatory and resulting neuroprotective effects in the context of EAE.

3.4 Histological analyses of neuronal and myelin markers in the optic nerve

In addition to immune cell markers, we also conducted histological evaluations of myelination and neuronal survival, using Myelin Basic Protein (MBP) and Brain-specific homeobox/POU domain protein 3A (Brn3a) markers respectively. The quantitative analysis (A, B, D, E) and representative illustrations (C) are shown in Fig. 5, with data obtained from longitudinal sections of optic nerves in C57Bl/6J and NOD mice, 90 days post-immunization.

MBP is a protein which is important in the process of myelination of nerves in the nervous system. This marker was used to assess the myelin status in the optic nerves. Brn3a, a member of the Brn3 family of POU-homeodomain transcription factors, is expressed in retinal ganglion cells (RGCs) and is commonly used to study RGC survival. In this study, it was used to evaluate the neuronal loss in the context of optic neuritis. However, no significant difference was observed in the abundance of either MBP or Brn3a across the treatment groups in both C57Bl/6J and NOD mice. Although not statistically significant, a trend was observed showing beneficial effects of flecainide on both myelination (MBP expression) and neuronal survival (Brn3a expression).

In summary, while significant effects were not observed with respect to myelination and neuronal survival, the observed trend in the flecainide group warrants further investigation.

3.5 Assessment of CNS immune cell infiltration

Further investigation focused on analyzing immune cell infiltration across the BBB using immunophenotyping via flow cytometry (CD45 + pre-gated). We scrutinized the spleen (Fig. 6A, B) and spinal cord (Fig. 6C, D) of C57Bl/6J- and NOD- EAE mice, 90 days post-immunization.

In the spleen of C57Bl/6J mice, a significant increase in B cells was observed in the flecainide (MD: 14.7039 ± 1.5572, P: <0.0001) and rasagiline (MD: 15.9590 ± 1.4776, P: <0.0001) groups. While not statistically significant, a trend was also observed towards increased cell counts of CD4 + T cells, NK cells, microglia, and dendritic cells with flecainide treatment. In NOD mice, flecainide treatment displayed a non-significant trend of overall immune cell increase in the spleen.

In contrast, immune cell infiltration in the central nervous system (CNS), specifically the spinal cord, showed different dynamics. In C57Bl/6J mice, all treatment groups presented a significant reduction in B cells (flecainide: MD: 55.5006 ± 9.5138 and P: <0.0001, safinamide: MD: 43.6541 ± 9.0240 and P: <0.0001, rasagiline: MD: 35.8577 ± 11.3321 and P: 0.0005). Additionally, both safinamide (MD: 16.2063 ± 9.0249, P: 0.0020) and flecainide (MD: 17.5004 ± 9.5138, P: 0.0093) showed significant reductions in CD4 + T cells. Remarkably, flecainide also showed a significant reduction in CD8 + T cells (MD: 24.2563 ± 3.2195, P: 0.0193) and microglia (MD: 9.5011 ± 1.4139, P: 0.0215).In NOD mice, flecainide led to significant reductions of B cells (MD: 0.3559 ± 0.0549, P: 0.0395), CD4 + T cells (MD: 1.3310 ± 0.0916, P: 0.0007), CD8 + T cells (MD: 1.1782 ± 0.1873, P: 0.0004), and NK cells (MD: 0.2775 ± 0.0230, P: 0.0049). Safinamide showed a significant reduction in CD8 + T cells (MD: 0.5181 ± 0.0294, P: 0.0394). Rasagiline treatment led to significant reductions in CD4 + T cells (MD: 0.8432 ± 0.3520, P: 0.0452), CD8 + T cells (MD: 0.7590 ± 0.1819, P: 0.0207), and NK cells (MD: 0.2569 ± 0.0036, P: 0.0069).

Taken together, our findings suggest that the treatment compounds, particularly flecainide, resulted in increased numbers of immune cells in spleen and reduced numbers in the spinal cord.

3.6 Comprehensive analysis of BBB modulation through in vitro gene expression and permeability assay in pMBMECs and in vivo Evan's Blue Dye Assay.

Based on these flow cytometry results, which showed reduced lymphocyte infiltration into the CNS after flecainide treatment, we hypothesized that flecainide might exert its effects on the endothelial cells, thereby enhancing the integrity of the BBB. To investigate this, we employed the Evan's Blue (EB) assay (Fig. 7). Quantification revealed a significant increase in EB perfusion in the CNS of the MOG EAE mice. However, upon flecainide treatment, there was a noticeable reduction (MD: 0.0315 ± 0.0113, P: 0.0167) compared to untreated MOG EAE animals.

To evaluate flecainide's impact on gene expression in pMBMECs, we examined the RNA expression of key genes (Fig. 8). V-CAM, facilitating leukocyte adhesion; I-CAM-1 and I-CAM-2, involved in leukocyte trafficking; PECAM-1 (CD31), essential for angiogenesis and BBB integrity; N-CAM-1, important for neuronal development; JAM-1, JAM-2, JAM-3, critical for tight junctions and barrier function; Occludin, a tight junction component in endothelial cells; and Integrin β-3, key in cell adhesion and signal transduction. (Bazzoni, 2003; Luo et al., 2007; Ohtsuki & Terasaki, 2007). In the cells treated with 2µM of flecainide, no significant differences were observed in the relative expression of these genes of interest compared to the vehicle-treated controls. However, in cells treated with 5µM flecainide, significant increases in the relative expression of several genes were noted. PECAM-1 demonstrated a substantial increase with a MD of 0.8305 (± 0.0059, P: 0.0004), and JAM-2 had an elevated expression with a MD of 0.7141 (± 0.0168, P: 0.0003). Additionally, JAM-3 expression significantly increased with a MD of 1.416 (± 0.0401, P: 0.0002), and Integrin β-3 showed the most substantial increase with a MD of 3.111 (± 0.0348, P: 0.0001). In conclusion, treatment with 5µM flecainide led to a significant upregulation of PECAM, JAM-2, JAM-3, and Integrin β-3 in pMBMECs, which we illustrated in Fig. 8.

In addition, permeability experiments were performed to investigate the effect of flecainide on BBB permeability in an inflamed state, modeled in vitro by IL-1β stimulated pMBMECs (Fig. 9). As shown before, IL-1β significantly compromised the barrier properties of the pMBMECs (MD: 0.07833, P: <0.0001) (Abadier et al., 2015). However, flecainide treatment demonstrated no significant impact on the permeability of IL-1β stimulated pMBMECs compared to DMSO vehicle (MD: 0.003333 ± 0.037925, P: 0.9946) or IL-1β treatment alone, as shown in Fig. 9. Thus, flecainide did not alter the passive permeability of the inflamed BBB under the in vitro conditions tested.

EAE, a widely recognized model for Multiple Sclerosis, is hallmarked by neuroinflammation, demyelination, and neurodegeneration (Reich et al., 2018). In this study, we explored the therapeutic impact of MAO-B inhibition and/or sodium channel blocking in in EAE progression using different murine models. Flecainide, a class Ic antiarrhythmic agent and Nav 1.5 channel blocker, is predominantly employed in the treatment of ventricular arrhythmias. Safinamide and flecainide have shown beneficial effects in EAE, a well-established model for Multiple Sclerosis (Bechtold et al., 2004; Morsali et al., 2013). However, the exact mechanisms by which these ion channel targeting compounds exert their effects in EAE remain somewhat ambiguous due to the wide expression of these channels on neurons, glia, and infiltrating immune cells. Phenytoin, classified as a Class Ib and another sodium channel blocker, exhibits notable EAE beneficial characteristics. Research has indicated its efficacy in protection of central axons, thereby positioning it as a promising therapeutic candidate for neuroinflammatory disorders (Black et al., 2006) and a positive clinical trial on patients with acute optic neuritis has been conducted (Raftopoulos et al., 2016). However, in a direct contrast drawn from our preliminary experimental data, the beneficial effects of flecainide seemed to be superior to phenytoin (Fig. 1). Consequently, we chose to proceed with the Class Ic sodium channel blocker, flecainide. In this study, we propose a novel hypothesis, suggesting a direct influence of sodium channel blockers on the integrity of the BBB. We believe that our data indicates that flecainide enhances the BBB integrity, reducing the penetration of lymphocyte into the CNS.

The results of our study provide valuable insights into the mode of action of safinamide in EAE. As the MAO-B blocker rasagiline showed no protective effects we think that the beneficial effects of safinamide in EAE rely mainly on sodium channel blockage. We observed significant beneficial effects on disability progression, neurodegeneration, visual function, immune cell infiltration and BBB integrity. The significant positive in-vivo data in EAE disability, visual function and retinal neurodegeneration observed under the administration of both flecainide (major effect) and safinamide (minor effect) is a crucial finding. This suggests that a) the substances could be good candidates for a clinical trial on acute optic neuritis using OCT and visual function as outcome parameters, b) positive findings in optic neuritis are also relevant to other parts of the CNS (Albrecht et al., 2012; Dietrich et al., 2018, 2020; Hecker et al., 2020), such as the spinal cord resulting in mitigated EAE scores and c) may thus impact long term disability resulting from acute inflammatory attacks in the CNS. This is of particular interest as current treatment options for inflammatory CNS diseases are mainly effective in preventing inflammatory attacks rather than preventing neurodegeneration resulting from inflammation. It is important to note that EAE is only model for autoimmune CNS disorders and does not mirror all aspects of human disease. However, the fact that positive effects of sodium channel blocking have been demonstrated in a clinical optic neuritis trial with phenytoin support the hypothesis that our data may indeed be transferable to the human situation and our preclinical results suggest that flecainide may be an even better candidate than phenytoin.

In terms of immune response, both flecainide and safinamide significantly reduced T-cell infiltration in the C57Bl/6J EAE model as optic nerve histological evaluations revealed. This is important as T-cell infiltration contributes to the pathological process in neurodegenerative conditions such as Multiple Sclerosis. Flecainide also significantly reduced both T-cell infiltration and microglial activation in the NOD-EAE model. This finding is in harmony with previous studies that suggested both safinamide´s and flecainide's capacity to reduce microglial activation in models of Multiple Sclerosis (Morsali et al., 2013). Interestingly, our study indicates that both treatments, particularly flecainide, result in increased immune cells in the spleen and reduced numbers in the spinal cord. This suggests a potential modulatory effect of these treatments on immune cell infiltration across the BBB.

This dichotomy aligns with the gene expression analysis conducted in pMBMECs treated with flecainide. Treatment with 5µM flecainide led to a significant upregulation of genes key for maintaining the integrity of the BBB, suggesting flecainide may modulate this barrier in neurodegenerative conditions. Despite these changes in the gene expression pattern, permeability assays using IL-1 β -stimulated pMBMECs did not exhibit significant changes in barrier function. This suggests that in the in vivo situation, other cellular players may contribute to modulating the permeability of the inflamed BBB. This complexity includes multifactorial challenges to the BBB, such as immune cell infiltration and cytokine release, influence on other factors of the BBB such as astroglia, microglia and neurons (Abbott et al., 2006). Moreover, the temporal dynamics of gene expression and subsequent functional outcomes may vary, with in vivo conditions potentially allowing a more extended period for these changes in gene expression to manifest to their full extent. This hypothesis is supported by our in vivo Evan's Blue dye assay results, which indicated a significant reduction in BBB permeability upon flecainide treatment in MOG EAE mice. The Evan's Blue assay results underscored the potential of flecainide in reinforcing BBB integrity. The diminished Evan's Blue penetration aligns with the reduced immune cell infiltration observed in the flow cytometry analyses. These findings suggest that flecainide enhances BBB integrity through mechanisms that are not immediately apparent in in vitro permeability tests on isolated pMBMECs but only become evident in a more physiologically relevant context and may involve other cellular or structural targets beyond the BBB endothelial cells.

Histologically, no significant differences were observed in myelination and neuronal survival across treatment groups. While there were trends towards benefits from flecainide treatment, this aspect of our findings warrants further investigation.

The interplay of various mechanisms, as elucidated by prior research, and the novel contributions of current findings, paint a comprehensive picture of the potential therapeutic avenues in this field. The hypothesis put forth by Bechtold et al., emphasized the correlation between axonal degeneration in MS and the extent of inflammation. They proposed that inflammatory mediators might initiate a cascade of intraaxonal sodium and calcium accumulation, leading to axonal degeneration. This concept paved the way for considering sodium channel blockers as potential mitigators of this degenerative process. Furthermore, (Craner et al., 2005) shed light on the critical role of microglia and macrophages in neuroinflammation. They discussed how sodium influx through sodium channels might contribute to elevated intracellular calcium in microglia, driving inflammatory functions. This aspect is crucial in understanding the broader implications of sodium channel blockers in neuroinflammatory conditions. The work of Morsali et al., on safinamide (and flecainide), a sodium channel blocker, highlighted its dual role in axonal protection. Despite uncertainties about its precise mechanism, their findings hinted at the significance of sodium channel blockade in safeguarding white matter.

Building on these foundational studies, our research offers a novel perspective by suggesting a significant role of sodium channel blockers in modulating the BBB. This new insight is not contradictory to existing knowledge but rather a potential unifying theory explaining the observed therapeutic effects in neuroinflammatory conditions. The extensive data collected in this study indicates that sodium channel blockers might, to a very relevant part, exert their beneficial effects by modulation of the BBB. This mechanism, alongside the direct impacts on axons and immune cells previously noted, underscores the multifaceted nature of sodium channel blockers in neuroinflammatory disease management. The observed modulation of the BBB by these blockers could be an attractive target for reducing neuroinflammation and subsequent neural damage.

In summary, the therapeutic promise of flecainide, phenytoin and, to some extent, safinamide appears significant, especially regarding disability progression, neuroprotection, visual function, immune modulation, and BBB integrity. Although these sodium channel blockers are thought to protect neurons by enhancing anti-oxidative factors, reducing superoxide production in microglia, and boosting glutathione levels, their full mode of action is not fully understood (Morsali et al., 2013). Our research provides compelling evidence that flecainide, a sodium channel 1.5 blocker, offers additional beneficial effects by modulating the BBB. The interplay of these mechanisms - the direct effects on axons and immune cells, and the novel role in BBB modulation - highlights the potential of sodium channel blockers as a comprehensive therapeutic strategy in EAE and, possibly the human disease, MS. This integrated understanding not only aligns with the existing hypotheses but also expands the therapeutic horizon, emphasizing the need for further research to fully harness the potential of these agents in patients with multiple sclerosis.

Brn3a: Brain-specific homeobox/POU domain protein 3A,

BW: Body weight,

CC: Cell count,

CFA: Complete Freund´s adjuvants,

CNS: Central nervous system,

EBD: Evan's Blue Dye,

EAE: Experimental autoimmune encephalomyelitis,

EDSS: Expanded disability status scale,

ELM: External limiting membrane,

GCL: Ganglion cell layer,

GEE: Generalized estimation equation,

IBA1: Ionized calcium-binding adaptor molecule 1,

I-CAM-1 and I-CAM-2: Intercellular Adhesion Molecules 1 and 2,

INL: Inner nuclear layer,

IPL: Inner plexiform layer,

IRL: Inner retinal layer,

IS: Inner segment,

JAM-1, JAM-2, and JAM-3: Junctional Adhesion Molecules -1, -2 and -3,

MAO: Monoamine Oxidase,

pMBMECs: primary mouse brain microvascular endothelial cells,

MBP: Myelin basic protein,

MD: Mean Difference,

MOG: Myelin oligodendrocyte glycoprotein,

MOG35-55: Myelin oligodendrocyte glycoprotein fragment 35-55,

MS: Multiple Sclerosis,

N-CAM-1: Neural Cell Adhesion Molecule 1,

NFL: Nerve fiber layer,

NOD: Non-obese diabetic,

OCT: Optical coherence tomography,

OMR: Optomotor response,

ON: Optic neuritis,

ONL: Outer nuclear layer,

OPL: Outer plexiform layer,

ORL: Outer retinal layer,

OS: Outer segment,

P: Probability value

PECAM-1: Platelet Endothelial Cell Adhesion Molecule,

PTX: Pertussis toxin,

RPE: Retinal pigment epithelium,

TRT: Total retinal thickness,

V-CAM: Vascular Cell Adhesion Molecule 1.

Conflict of Interest

The work was funded by a research grant from the Forschungskommission of the Heinrich-Heine-University Düsseldorf to Michael Dietrich. Mustafa Sindi is funded by a DFG grant to Philipp Albrecht, number AL 1769/6-1. Apart from this, the authors declare that they have no additional conflict of interest related to the work presented. The following financial disclosures are unrelated to the work: SGM received honoraria for lecturing and travel expenses for attending meetings from Almirall, Amicus Therapeutics Germany, Bayer Health Care, Biogen, Celgene, Diamed, Genzyme, MedDay Pharmaceuticals, Merck Serono, Novartis, Novo Nordisk, ONO Pharma, Roche, Sanofi-Aventis, Chugai Pharma, QuintilesIMS, and Teva. His research is funded by the German Ministry for Education and Research (BMBF), Deutsche Forschungsgemeinschaft (DFG), Else Kröner Fresenius Foundation, German Academic Exchange Service, Hertie Foundation, Interdisciplinary Center for Clinical Studies (IZKF) Muenster, German Foundation Neurology, and by Almirall, Amicus Therapeutics Germany, Biogen, Diamed, Fresenius Medical Care, Genzyme, Merck Serono, Novartis, ONO Pharma, Roche, and Teva. MD received speaker honoraria from Merck and Novartis. PA received compensation for serving on Scientific Advisory Boards for Ipsen, Novartis, Biogen; he received speaker honoraria and travel support from Novartis, Teva, Biogen, Merz Pharmaceuticals, Ipsen, Allergan, Bayer Healthcare, Esai, UCB and Glaxo Smith Kline; he received research support from Novartis, Biogen, Teva, Merz Pharmaceuticals, Ipsen, Bristol-Myers Squibb and Roche. The other authors report no disclosures. TR reports grants from German Ministry of Education, Science, Research and Technology, during the conduct of the study; grants and personal fees from Sanofi-Genzyme; personal fees from Biogen; personal fees and nonfinancial support from Merck Serono; personal fees from Roche, Teva, Alexion, Argenx, UCB, and BMS outside the submitted work. Author Philipp Albrecht is employed by Maria Hilf Clinics GmbH, Mönchengladbach. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Author Contributions

MS, MD, CH, AI, TM, RR, DK and VD performed the experiments and/or analyzed the data; MS, MD and PA wrote the manuscript; SGM, TR, HPH, PK, PA, HS, RL, BE and MD were involved in revising the manuscript critically for important intellectual content and made substantial contributions to interpretation of data. PA and MD conceived the study and supervised experiments. All authors read and approved the final manuscript.

Funding

This work was supported by grants from the „Research commission of the medical faculty of the Heinrich-Heine-University Düsseldorf” (Forschungskommission der Medizinischen Fakultät der Heinrich-Heine-Universität Düsseldorf) to Michael Dietrich.

Acknowledgments

This project was funded by the “Forschungskommission” of the Heinrich-Heine University Düsseldorf; Graphic 8 was created by tools of biorender.com.

Data Availability Statement

All data can be made available upon request by a qualified researcher.

Ethics declaration

All animal experiments were conducted in accordance with the ethical guidelines and regulations set forth by the local Animal Ethics Committee of the Landesamt für Natur, Umwelt und Verbraucherschutz Nordrhein-Westfalen (LANUV North Rhine-Westphalia, Germany). The study protocol was reviewed and approved under the approval number Az. 81-02.04.2019.A063. Mice used in this study were provided with ad libitum access to chow and drinking water to ensure their well-being throughout the experimental procedures. For experimental studies involving client-owned animals, the authors have obtained informed consent from the respective owners, ensuring their awareness and agreement to the participation of their animals in the study.

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No competing interests reported.

Supplementaryfigure1.tiff
Figure S1: Flow cytometry: Gating strategy. Living cells were first identified based on side scatter (SSC) and forward scatter (FSC) properties. Subsequent gates identified cells based on CD45 expression (SSC vs. CD45). From the CD45+ population, lymphocytes were distinguished by gating CD3 vs. CD19. CD3+ T-cells were further identified within the lymphocyte population based on CD4 and CD8 expression (CD4 vs. CD8). For non-B and non-T cells, we used a gating strategy with CD11b vs. NK1.1 followed by SSC vs. CD11b. CD11b+ cells were further differentiated based on NK1.1 and Ly6G (NK1.1 vs. Ly6G) and SSC vs. Ly6C, allowing identification of monocytes.

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Flecainide enhances blood-brain barrier function: Novel mode of action of sodium channel blocking in experimental autoimmune encephalomyelitis (EAE)

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