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. Author manuscript; available in PMC: 2024 May 7.
Published in final edited form as: Neurotoxicology. 2023 May 7;96:197–206. doi: 10.1016/j.neuro.2023.05.006

Fingolimod mitigates memory loss in a mouse model of Gulf War Illness amid decreasing the activation of microglia, protein kinase R, and NFκB

Isabel Carreras a,b,c,*, Younghun Jung a,b,d, Jonathan Lopez-Benitez a,b, Christina M Tognoni a,b, Alpaslan Dedeoglu a,b,e
PMCID: PMC10334821  NIHMSID: NIHMS1900968  PMID: 37160207

Abstract

Gulf War Illness (GWI) is an unrelenting multi-symptom illness with chronic central nervous system and peripheral pathology affecting veterans from the 1991 Gulf War and for which effective treatment is lacking. An increasing number of studies indicate that persistent neuroinflammation is likely the underlying cause of cognitive and mood dysfunction that affects veterans with GWI. We have previously reported that fingolimod, a drug approved for the treatment of relapsing-remitting multiple sclerosis, decreases neuroinflammation and improves cognition in a mouse model of Alzheimer’s disease. In this study, we investigated the effect of fingolimod treatment on cognition and neuroinflammation in a mouse model of GWI. We exposed C57BL/6J male mice to GWI-related chemicals pyridostigmine bromide, DEET, and permethrin, and to mild restraint stress for 28 days (GWI mice). Control mice were exposed to the chemicals’ vehicle only. Starting 3 months post-exposure, half of the GWI mice and control mice were orally treated with fingolimod (1mg/kg/day) for 1 month, and the other half were left untreated. Decreased memory on the Morris water maze test was detected in GWI mice compared to control mice and was reversed by fingolimod treatment. Immunohistochemical analysis of brain sections with antibodies to Iba1 and GFAP revealed that GWI mice had increased microglia activation in the hippocampal dentate gyrus, but no difference in reactive astrocytes was detected. The increased activation of microglia in GWI mice was decreased to the level in control mice by treatment with fingolimod. No effect of fingolimod treatment on gliosis in control mice was detected. To explore the signaling pathways by which decreased memory and increased neuroinflammation in GWI may be protected by fingolimod, we investigated the involvement of the inflammatory signaling pathways of protein kinase R (PKR) in the cerebral cortex of these mice. We found increased phosphorylation of PKR in the brain of GWI mice compared to controls, as well as increased phosphorylation of its most recognized downstream effectors: the α subunit of eukaryotic initiation factor 2 (eIF2α), IκB kinase (IKK), and the p65 subunit of nuclear factor-κB (NFκB-p65). Furthermore, we found that the increased phosphorylation level of these three proteins were suppressed in GWI mice treated with fingolimod. These results suggest that activation of PKR and NFκB signaling may be important for the regulation of cognition and neuroinflammation in the GWI condition and that fingolimod, a drug already approved for human use, may be a potential candidate for the treatment of GWI.

Keywords: GWI, cognition, neuroinflammation, microglia activation, PKR, integrated stress response, fingolimod

1. Introduction

Gulf War Illness (GWI) refers to the complex chronic symptoms that affects an estimated 25–35% of veterans of the 1991 Gulf War (White et al., 2016). Longitudinal studies consistently indicate that rates and symptom frequencies reported by veterans suffering from GWI have not declined with time (Hotopf et al., 2003; Ozakinci et al., 2006). Although disease presentation varies from person to person, symptoms include a combination of musculoskeletal pain, headache, cognitive dysfunction, fatigue, respiratory, gastrointestinal, and dermatological conditions (White et al., 2016). Neurological symptoms, a top complaint among veterans diagnosed with GWI, include cognitive impairment, attention deficits, depression and anxiety (Janulewicz et al., 2017; Jeffrey et al., 2019; Toomey et al., 2009). These symptoms are indicative of central nervous system (CNS) dysfunction, and indeed structural and functional brain changes have been reported in veterans with GWI (Abou-Donia et al., 2017; Cooper et al., 2016; Menon et al., 2004; Tillman et al., 2017; Turner et al., 2016). Effective treatment for GWI is lacking and most of ill veterans receive treatment for individual symptoms.

It has been hypothesized that GWI may be the result of neurotoxic chemical exposure that could have been aggravated by war-related stress. Unique to the 1991 GW, military personnel were exposed to a great number of neurotoxins: chemical warfare agents, such as sarin, and mustard gas; insecticides and pesticides such as permethrin (PER) and N, N-Diethyl-meta-toluamide (DEET) to prevent insect-borne diseases; the prophylactic drug pyridostigmine bromide (PB), a reversible cholinesterase inhibitor aimed to protect against exposure to nerve agents; and to multiple combustion products from burning oil wells. The chemical exposure hypothesis has been supported by multiple animal model studies showing that exposure to PB and pesticides, alone or in combination with other GW chemicals and stress, leads to persistent cognitive and mood dysfunction. Changes in behavior have been associated with increased neuroinflammation, mitochondrial dysfunction and oxidative stress, decreased neurogenesis, abnormal lipid metabolism, and neurodegeneration with anomalies in the GABAergic and cholinergic systems (Abdel-Rahman et al., 2004; Abdel-Rahman et al., 2001, 2002; Abdullah et al., 2011; Abdullah et al., 2012; Carreras et al., 2018; Hattiangady et al., 2014; Kodali et al., 2018; Madhu et al., 2019; Megahed et al., 2014; Ojo et al., 2014; Parihar et al., 2013; Shetty et al., 2020; Zakirova et al., 2015).

Neuroinflammation is a common feature of virtually every animal model of GWI. Direct proof of neuroinflammation in patients with GWI was recently reported using positron emission tomography for translocator protein (TSPO), a surrogate marker of neuroinflammation (Alshelh et al., 2020). The study infers that microglia with persistent activation phenotype are the primary basis for neuroinflammation in GWI. Neuroinflammation is increasingly recognized as a potential mediator of cognitive impairments (Kumar, 2018), chronic fatigue (Omdal, 2020) and musculoskeletal pain (Vergne-Salle & Bertin, 2021) – the top complaints among veterans with GWI.

Fingolimod (FTY720, Gilenya®) is an analog of sphingosine that acts as a sphingosine 1-phosphate receptor modulator in vivo (Brinkmann, 2007). Fingolimod is approved for the treatment of relapsing-remitting multiple sclerosis (RRMS) where it signals the retention of lymphocytes in the lymph nodes, reducing the infiltration autoreactive lymphocytes into the CNS. After crossing the blood-brain barrier (BBB) fingolimod has direct anti-inflammatory and neuroprotective effects on neural cells (Hunter et al., 2016b). The beneficial effects of fingolimod have been shown in multiple models of neurological conditions (Aytan et al., 2016; Carreras et al., 2019; Fagan et al., 2022; Gao et al., 2012; Gol et al., 2017; Guo et al., 2020; Wu et al., 2017; Zhang et al., 2022). However, there are no reports on the effects of fingolimod on models of GWI.

In the present study, we expanded upon our previous report (Carreras et al., 2018) to investigate if fingolimod, an S1P modulator drug approved for the treatment of relapsing-remitting multiple sclerosis (RRMS) with proven anti-inflammatory and neurogenic properties (Bascunana et al., 2020), would be beneficial to GWI. To find early markers to the persistent and often latent symptoms of GWI that could be used to efficiently screen therapies in pre-clinical trials, we previously characterized a model of GWI 3 months post-exposure. This particular model is based on exposure to low and relevant doses of PB, PER, and DEET together with mild restraint stress for 28 days (Abdel-Rahman et al., 2002; Abdullah et al., 2012; Parihar et al., 2013). In this model, the chemicals’ dose and route of administration closely mimics the human exposure during the GW. Our previous study included behavioral, neuropathological, and neurochemical analysis and revealed multiple effects of GW-related exposures in all these domains. Here, we extended the 3 months post-exposure protocol to include a 1-month-long treatment with fingolimod. To explore the potential mechanisms by which fingolimod may decrease inflammation and restore cognition, we focused our efforts on protein kinase R (PKR), a protein that functions as a central sensor of cellular stress and its activation has been associated with neuroinflammation and impaired cognition (Gal-Ben-Ari et al., 2018). We investigated the effects of GWI-associated exposures on the activation/phosphorylation of PKR and its most well-known substrates, the α subunit of the eukaryotic initiation factor 2 (eIF2α), IκB kinase (IKK), and the p65 subunit of nuclear factor-κB (NFκB-p65). We also investigated whether fingolimod treatment could restore GW-induced changes in PKR, eIF2α and NFĸB signaling.

2. Material and Methods

2.1. Mice and GWI Exposure Protocol and Treatment

A total of 40 male C57BL/6J mice (Jackson Laboratories #0000664) were used. Mice were randomly assigned to 4 groups (n=10): mice to be exposed to GWI-related chemicals and stress (GWI mice), mice to be exposed to GWI-related chemicals and stress and treated with fingolimod (GWI+fingo mice), mice to be exposed with the chemical’s vehicle only (control mice), and mice to be exposed with the chemical’s vehicle and treated with fingolimod (control+fingo mice). Exposure to PB (1.3mg/kg/day orally via drinking water), PER (0.13mg/kg/day dermal application), and DEET (40mg/kg/day dermal application) and mild restraint stress was performed, as previously described (Carreras et al., 2018) except for 15min/day in the mouse restrainer instead of 5min/day. PB, PER and DEET were purchased from Sigma Aldrich. Control mice were exposed to a dermal application of 70% ethanol. For dermal applications, a small area of the mice’s anterior back was shaved to exposed the skin. Restraint stress was performed immediately after chemical exposure. For this, each mouse was gently guided into a plexiglass mouse restrainer (Thermofisher, 544-RR) with apertures for ventilation and a sliding door to facilitate the restraint and allowed to stay for 15 minutes with no mobility. At the end of 15 minutes, the mouse was withdrawn gently from the restrainer and placed back into its home cage. Exposure to chemicals and restraint stress lasted 28 days followed by a 3-month post-exposure period before half of the animals in the exposed and control groups were treated with fingolimod for 1 month. Fingolimod (Cayman Chemical) was dissolved in the mouse drinking water at a dose of 1mg/kg/day. During the last week of fingolimod treatment for half of the mice, all mice went through behavioral testing followed by euthanasia and tissue collection. Mouse water and food were changed weekly. We monitored mice for general well-being, and no side effects related to the exposure or treatment protocol were observed. Behavioral tests and analysis of brain samples were performed for all animal groups at the same time, blindly to the exposure/treatment regimen.

All animal experiments were approved by the VA Boston Healthcare System’s Institutional Animal Care and Use Committee and conducted in accordance with the ARRIVE guidelines and the Guide for the Care and Use of Laboratory Animals.

2.2. Neurobehavioral Testing

Mouse behavior was evaluated sequentially on the elevated plus maze and Morris water maze tests. Mice were brought in their home cage to the testing room at least 30min before testing for habituation to minimize effects of stress on behavior during testing. Testing was performed by a single investigator, familiar to the mice and blind to their experimental group. Elevated Plus Maze: The test was performed as we previously described (Carreras et al., 2018). Mice were placed in the center zone of the elevated plus apparatus and left to explore while they were videotaped for 5min. Videos were analyzed to record the following parameters: 1) number of open arm entries, 2) time spent in open arms, 3) number of closed arm entries, and 4) time spent in the closed arms. Entry to an arm was considered when all four paws were located within the arm. Morris Water Maze: The test was performed as we previously described (McKee et al., 2008). Briefly, a 122cm diameter white pool filled with water tinted with non-toxic white paint and maintained at 24°C±2°C was used together with a 14cm-diameter platform placed 0.5cm below the water surface. Walls around the pool had a variety of visual extramaze cues for navigation. Following a pre-training protocol mice’s learning capacity was tested during consecutive days, 4 training trials/day of a maximum of 60s each with an inter-trial interval of 15min, until mice reached an average escape latency of <25s. The pre-training protocol, performed the day before training trials started, consisted of three habituation trials with the platform located in the center of the pool and exposed 1cm above the water line: each mouse was placed on the platform for 10s, followed by placing the mouse in the water 10cm from the platform and immediately guided onto the platform for another 10s rest, followed by a third trial placed at a starting location not used in the training trials, in which the mouse was allowed to swim freely for 30s before being guided to the platform for another 10s rest. No data was collected during pre-training. For the testing, the pool was imaginarily divided into 4 quadrants in the HVS2020 tracking system (HVS Image, Hampton, UK), with north, west, south, and east positions located at the intersections of the quadrants. The platform was submerged in the west position, 20 cm from the wall. The starting positions were randomized among the north, east and south positions, such that over the 4 daily trials only one starting position was randomly repeated. If a mouse failed to find the platform in 60s, it was guided to the platform. All mice were given a 10s rest on the platform before being removed from the maze. A probe trial of 60s without the platform was performed 1h and 24h after the last training trial. Data were recorded using the HVS2020 system and used for analysis. Multiple measures were recorded during the training and probe trials that included: latency to reach platform, swim distance, swim speed, number of platform location crossings, latency to first cross the platform location, time spent in each quadrant, and proximity to platform location.

2.3. Tissue collection

Mice were euthanized by CO2 asphyxiation and brains were dissected out for post-mortem analysis. The right hemisphere was post-fixed with the 4 % paraformaldehyde for 24h and cryoprotected in 10% and 20% glycerol/2% DMSO solution for histological analysis, as described (Aytan et al., 2016). The left hemisphere was immediately dissected on ice and cortex was collected, frozen and stored at −80°C for protein analysis by Western blot.

2.4. Immunohistochemical Staining and Analysis

Immunohistochemistry (IHC) was performed in serial sections of 50μm thick, as we previously described (Carreras et al., 2018) with antibodies to Iba1 (Wako Chemicals, cat.019–19741; 1:5000) to stain microglia, and GFAP (Millipore, cat.MAB3402; 1:5000) for reactive astrocytes. Reactive astrocytes and activated microglia were quantified blindly to the treatment, in the dentate gyrus (DG) of 3 serial sections/subject 0.5mm apart. Immunostaining for Iba1 and GFAP were measured using the Area Fraction Fractionator probe (McNeal et al., 2016) in the Stereo Investigator software (MBF Bioscience). Increased percent area occupied by the specific immunostaining is a measure of glial cell activation. Using this probe, the DG was divided into 150×150μm grids with 10μm counting frames. These counting frames contain a grid of 25 ‘+’ marks. To measure the immunostained density of the grid, each + mark is counted full if the bottom right of the + signed is located on a cell body or thick process. A thin process (i.e., from a resting, ramified microglia) would not fully occupy one these sites and would not be counted. Thus, data from the AFF probe is an indication of the activated state of microglia.

2.5. Western blot

Lysates from brain’s cortical region were prepared in cOmplete lysis M (Roche, Branchburg, NJ, cat. 04719956001) supplemented with Pierce™ Protease Inhibitor Mini Tablets, ethylenediaminetetraacetic acid (EDTA)-free (ThermoFisher, Waltham, MA, cat. A32955) and phosphatase inhibitor PhosSTOP EASYpack Tablets (Roche, cat. 04906837001). Protein concentration was calculated using Bio-Rad Protein Assay Dye (BioRad, Portland, ME, cat. 5000006). 20–40μg of total protein was added per lane to 4–20% reducing sodium dodecyl sulfate polyacrylamide Tris-Glycine gels after sample preparation in 4x Laemmli sample buffer (BioRad, cat. 1610747). The proteins were transferred to polyvinylidene fluoride (PVDF) membranes and blocked for 1h in 5% dry milk in Tris-buffered saline (TBS) with 0.1% Tween-20 (TBST). The primary antibodies were applied at 4°C overnight in 5% milk or 5% BSA in TBST. The primary antibodies used were as follows: p-PKR thr 451 (Invitrogen, Waltham, MA, cat. 44–668g; 1:1000 dilution), PKR (Cell Signaling, Danvers, MA, cat. 3072; 1:1000 dilution), p-IKKα/β (Ser 176/180) (Cell Signaling, cat. 2697; 1:1000 dilution), IKKα (Cell Signaling; cat. 61294, 1:1000 dilution), p-eIFα (Ser51) (Cell Signaling, cat. 3398; 1:1000 dilution), eIFα (Cell Signaling, cat. 9722; 1:1000 dilution), p-NFκB-p65 (Ser 536) (Cell Signaling, cat. 3033, 1:1000 dilution), and NFκB-p65 (Cell Signaling, cat. 8242; 1:1000 dilution). Blots were incubated with peroxidase-coupled anti-rabbit IgG secondary antibody (Cell Signaling; cat. 7074; 1:2000 dilution) for 1h, and protein expression was detected with SuperSignal West Dura Chemiluminescent Substrate (Thermo Scientific, Rockford, IL, cat. 34075). Images were acquired with ChemiDoc MP imaging system (BioRad). Membranes were re-probed with monoclonal anti-β-actin antibody (Cell Signaling, cat. 4970; 1:1000 dilution) to control for equal loading. Western blot images were quantified using ImageJ (NIH, Bethesda, MD) software. The direct expression level of the phosphorylated protein was normalized to the level of its correspondent total protein expression as well as to the levels of its correspondent β-actin expression. Final Western blot data are presented as a percent change of mean value of the GWI mice (GWI) and GWI+fingolimod treated mice (GWI+fingo) by normalizing to mean value of the control mice (Control).

2.6. Statistical analyses

We determined the sample size by performing a power analysis using G*Power 3 software. Our experience with behavioral and histopathological measurements indicates that a coefficient of variation of 10–15% within groups can be expected. Based on these analyses we calculated that a sample size of 10 per group would be adequate to have a 90% chance of detecting a difference between group means with p < 0.05. For Western blot analysis, 4 samples/group were randomly chosen. Statistical analyses of the data were performed using one-way ANOVA with Tukey HSD or Tukey Kramer post-hoc tests for between group comparisons, as appropriate. Values of p < 0.05 were considered significant. Results are presented as mean ± standard error of the mean (Bjorklund et al., 2020).

3. Results

3.1. Effect of exposure to GW chemicals/stress and fingolimod treatment on mice weight and well-being

During the entire protocol, encompassing exposure, latency and treatment periods, no significant differences on food and water consumption were detected among the four cohorts of mice. Likewise, no significant differences in body weight and mouse well-being were identified, and no deaths were recorded.

3.2. Effect of exposure to GW chemicals/stress and fingolimod treatment on mouse behavior

Four months after the 1-month-long daily exposure to GW-associated chemicals and stress that included the 1-month treatment with fingolimod we sequentially tested all 4 cohorts of mice for their level of anxiety-like behavior on the elevated plus maze and their learning and memory capacity using the Morris water maze paradigm. During the 5min trial on the elevated plus maze, we found no significant differences in the number of entries to open or closed arms nor in the time spent on open or closed arms between the cohorts, and no difference in moving speed was detected (Figure 1). On the water maze task, all 4 cohorts of mice learned to escape from the water onto the submerged platform at a similar pace, reaching an average latency of 25s by day 3 of training (Fig. 2A). One-way ANOVA of the average latency across all training trails revealed no significant differences among mouse groups [F(2,81) = 0.04, p = 0.96]. To detect changes in short- and long-term memory, probe trials were performed 1h and 24h after the last training trial on day 3. One-way ANOVA revealed significant differences for some of the measures on the 1h and 24h probes; however, post-hoc analysis showed no differences between the control and control+fingo groups on any of the probe measures. Therefore, we combined the probe data collected from control and control+fingo mice and re-analyze the probe measures using 3 groups (Figure 2B–E). One-way ANOVA showed significant differences among the groups in latency to cross the location where the platform was during training on the 1h probe [F(2,35) = 4.76, p < 0.05] and 24h probe [F(2,34) = 4.18, p < 0.05] (Figure 2C). On the 24h probe, we also found significant differences among the groups in the percent time spent in the target quadrant [F(2,35) = 3.31, p < 0.05] (Figure 2D) and in the average proximity to the platform location [F(2,35) = 4.87, p < 0.05] (Figure 2E); however, differences were not significant for these measures on the 1h probe. Post-hoc tests showed that GWI mice had significantly higher latencies to reach the platform location than the combined control mice on both the 1h (p < 0.05) and 24h (p < 0.05) probes, and, furthermore, GWI mice spent less time in the target quadrant (p < 0.05) and were more distant from the target location than controls (p < 0.05) on the 24h probe. GWI mice treated with fingolimod demonstrated significant lower latencies to reach the platform location during 1h probe trial (p’s < 0.05) and spent significantly more time in the target quadrant than untreated GWI mice on the 24h probe (p < 0.05). While GWI+fingo mice had a shorter latency, spent more time in the target quadrant, and swam closer to the target location than untreated GWI mice on average, post-hoc analysis of these parameters did not reach significance (p = 0.061, 0.108, and 0.078, respectively). Notably, GWI+fingo mice performed similarly to control mice on all measures of the 1h and 24h memory probes. Differences detected during probe trials were not related to differences swim speed, which was similar for all the groups. In composite, it appears that exposed mice have reduced memory that is ameliorated by fingolimod treatment.

Figure 1. Effect of exposure to GW-related chemicals and stress on the elevated plus maze test.

Figure 1.

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No effect of exposure or fingolimod treatment on anxiety-like behavior was detected in the elevated plus maze test. Mice from the 4 groups tested had similar number of entries and spent similar amount of time in closed and open arms. No differences in speed were detected in between groups either. N =10 mice/group. Data presented as ± SEM (one-way ANOVA with Tukey post-hoc).

Figure 2. Effect of exposure to GW-related chemicals and stress on learning and memory in the Morris water maze test.

Figure 2.

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(A) No significant differences in the escape latency to find the hidden platform were observed during the 3 days of training trials. All four cohorts of mice learned at a similar rate. N=9–10 mice/group (B) Probe trials without platform was performed 1h and 24h after the last training trial on day 3. Data from control and control+fingolimod mice were combined and results analyzed by one-way ANOVA with Tukey-Kramer post-hoc test. Data presented as ± SEM.

3.3. Effect of exposure to GW chemicals/stress and fingolimod treatment on the activation of microglia and astrocytes

Since microglia undergo morphological changes upon activation, characterized by increased cell body volume with shorter and thicker processes, brain sections immunostained with Iba1 were analyzed using the AFF probe as a measure of microglia activation, which estimated the percent area occupied by soma and thick processes, sparing thin processes from being included in the analysis. Similarly, hypertrophy of reactive astrocytes was quantified in GFAP immunostained brain sections. One-way ANOVA analysis showed that the estimated % area occupied by Iba1-immunostained microglia in the DG was significantly different among groups [F(3,36) = 7.51, p < 0.001] (Figure 3). However, for GFAP, no significant group differences were detected. Post-hoc comparisons indicated that the estimated % area occupied by activated microglia was significantly increased in GWI compared to control mice (p < 0.01) and that treatment of GWI with fingolimod significantly reduced the occupied area compared to untreated GWI mice (p < 0.01) to a level not different than that of control mice. No effect of fingolimod on microglia activation in control mice was detected. These results reveal that the exposure protocol causes a chronic neuroinflammation characterized by the increased activated state of microglia and that fingolimod treatment on GWI mice decreases the activated state of microglia to basal levels.

Figure 3. Increased level of activated microglia in GWI mice is restored to the level in control mice after treatment with fingolimod. No significant change in astrocyte reactivity is detected in GWI mice.

Figure 3.

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Brain sections of control and GWI mice with or without treatment with fingolimod were analyzed by immunohistochemistry with antibodies to Iba1 and GFAP to stain microglia and astrocytes, respectively. (A) Representative photomicrographs of the dentate gyrus (DG) section of the hippocampus immunostained with Iba1 (top) and GFAP (bottom). Original magnification, 200x and 400x. Scale bar = 100mm. (B). Percent area occupied by immunostaining, as a measure of glia activation, was quantified in the DG using the Area Fraction Fractionator probe and analyzed by one-way ANOVA with Tukey post-hoc. N =10mice/group. Data presented as ± SEM.

3.4. Effect of exposure to GW chemicals/stress and fingolimod treatment on the phosphorylation of PKR and the phosphorylation of eIF2α

Since we found no effect of fingolimod treatment on behavioral tests or on the activation state of microglia and astrocytes in control mice, tissue from the control+fingo cohort of mice was not included in the protein analysis by Western blot.

Western blot analysis of whole protein homogenates from the cortex region of the brain from control, GWI, and GWI+fingolimod mice was performed using antibodies to p-PKR (Thr 451), p-eIF2α (Ser 51), PKR and eIF2α to determine if exposure to GW chemicals/stress and treatment with fingolimod have an effect in the phosphorylation/activation of PKR and the phosphorylation eIF-2α, the best-characterized substrate of PKR (Figure 4). At 4 months post-exposure, one-way ANOVA revealed significant differences in the levels of phosphorylated PKR among groups when normalized to total PKR [F(2,9) =29.81, p < 0.001] and to β-actin [F(2,9) = 65.42, p < 0.001] (Figure 4A). Significant differences were also found for phosphorylated eIF2α normalized to total eIF2α [F(2,9) = 30.02, p < 0.001] or to β-actin [F(2,9) = 32.71, p < 0.001] (Figure 4B). Post-hoc comparisons revealed that GWI exposure significantly increased phosphorylated PKR (p < 0.01), while fingolimod treatment significantly reduced phosphorylated PKR in GWI mice (p < 0.001), restoring it to a level similar to that detected in the unexposed control mice. Post-hoc analysis also showed that GWI mice had significantly increased phosphorylated eIF2α compared to controls (p < 0.05) and that treatment of GWI mice with fingolimod significantly decreased these levels (p < 0.001) to levels even lower than those measured in control mice (p < 0.05).

Figure 4. Level of phosphorylation of PKR and EIFa is increased in GWI mice compared to control mice and is reduced in fingolimod treated GWI mice.

Figure 4.

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(A) Immunoblot analyses showing the protein levels of p-PKR, PKR, p-EIFa, EIFa, and β-actin in control mice (Control), GWI mice (GWI), and GWI mice treated with fingolimod (GWI+fingo). (B) Quantification of Figure 3A. The direct expression levels of p-PKR/PKR, p-PKR/β-actin and p-EIFα/EIFα, p-EIFα/β-actin are presented (n=4/group) and final data are presented as a percent change of mean value of the GWI mice and GWI+fingo mice by normalizing to mean value of control mice. Data presented as ± SEM (one-way ANOVA with Tukey post-hoc test).

3.5. Effect of exposure to GW chemicals/stress and fingolimod treatment on the activation of NFκB signaling pathway

Next, we investigated changes in downstream pathway from PKR that includes the activation of NFκB. Activated PKR is known to phosphorylate IκB kinase (IKK). Phospho-IKK in turn phosphorylates IκB, the inhibitor of NFκB, and the NFκB p65 subunit. Once phosphorylated, IκB is processed for ubiquitination and degradation and NFκB is free to translocate into the nucleus where regulates transcription of genes involved predominantly in inflammatory and immune responses (Zamanian-Daryoush et al., 2000). The IKK-dependent phosphorylation of the NFκB p65 subunit results in increased NFκB transcriptional activity (Yang et al., 2003). The cerebral cortex region of the brain from control, GWI, and GWI+fingo mice were analyzed by Western blot using antibodies to p-IKK, IKK, p-NFκB p65 and NFκB p65 (Figure 5). Applying one-way ANOVA, we found significant differences among the three animal groups in the levels of phosphorylation for IKK and NFkB p65: for phosphorylated IKK normalized to total IKK [F(2,9) = 15.93, p < 0.01] and when normalized to β-actin [F(2,9) = 17.57, p < 0.001], for phosphorylated NFκB p65 we found [F(2,9) = 5.89, p < 0.01] and [F(2,9) = 8.76, p < 0.01]. Post-hoc comparisons demonstrated that the level of phosphorylated IKK (p < 0.05) and phosphorylated NFκB p65 (p < 0.05) were significantly increased in the brains of GWI mice compared to unexposed controls. Parallel to the effect of fingolimod on PKR phosphorylation, the level of phosphorylated IKK and that of phosphorylated NFκB p65 were significantly decreased in fingolimod treated GWI mice compared to the ones from GWI mice (p < 0.05) and their levels were no different than in control mice.

Figure 5. Level of phosphorylation of IKK and NFkB-p65 is increased in GWI mice compared to control mice and is reduced in fingolimod treated GWI mice.

Figure 5.

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(A) Immunoblot analyses showing the protein levels of p-IKKα, IKKα, p-NFkB-p65, NFkB-p65, and β-actin in control mice (Control), GWI mice (GWI), and GWI mice treated with fingolimod (GWI+fingo). (B) Quantification of Figure 4A. The direct expression levels of the p-IKKα/IKKα, p-IKKα/β-actin and p-NFkB-p65/NFkB-p65, p-NFkB-p65/β-actin are presented (n=4/group) and final data are presented as a percent change of mean value of the GWI mice and GWI+fingo mice by normalizing to mean value of the control mice. Data presented as ± SEM (one-way ANOVA with Tukey post-hoc test).

4. Discussion

In this study, we investigated the effects of fingolimod on a well-established mouse model of GWI with a focus on two outcomes, cognition and glial cell activation, features that are prominent in GWI patients (Alshelh et al., 2020; White et al., 2016) and common to many animal models of the disease (Burzynski et al., 2022; Carreras et al., 2019; Madhu et al., 2019; O’Callaghan et al., 2015; Phillips & Deshpande, 2016). Furthermore, we investigated whether PKR and its downstream signaling, known to participate in neuroinflammation and cognition, are activated in GWI mice and affected by fingolimod treatment. Fingolimod is an immune and neuroimmune modulator that has been shown to reduce neuroinflammation by affecting microglia and astrocytes and multiple inflammatory pathways (Bascunana et al., 2020). The main pharmacologic effect of fingolimod is the retention of lymphocytes in lymph nodes, reducing their number in circulation (Brinkmann, 2007). In addition, fingolimod easily crosses the BBB and is directly involved in diverse functions in the CNS related to inflammation and cognition such as neurogenesis, microglial and astrocytic activation, and communication between astrocytes, neurons and the BBB (Bascunana et al., 2020). Fingolimod alleviates depressive symptoms in patients with RRMS (Hunter et al., 2016a). In animal models of various neurological diseases, fingolimod restores cognitive and mood dysfunction by affecting the activation of glial cells and inflammatory pathways such as the NLRP3 inflammasome and NFκB (Aytan et al., 2016; Carreras et al., 2019; Fagan et al., 2022; Gao et al., 2012; Gol et al., 2017; Guo et al., 2020; Wu et al., 2017; Zhang et al., 2022). In the present study, fingolimod treatment improved the short- and long-term memory of GWI mice and decreased the activated state of microglia measured in the dentate gyrus of the hippocampus.

Our data also show that there is increased activation of PKR and increased activation of its downstream signaling pathways, eIFα and NFκB, in the brain of GWI mice. PKR is an interferon (IFN)-inducible protein kinase and one of the four kinases of the integrated stress response (ISR) (Costa-Mattioli & Walter, 2020; Pakos-Zebrucka et al., 2016). Upon sensing cellular stress, these four kinases phosphorylate the α subunit of the eukaryotic initiation factor 2 (eIF2α) blocking general protein synthesis while promoting the translation of specific mRNAs associated with the recovery from or adaptation to the stressor (Pakos-Zebrucka et al., 2016). Pro-inflammatory signaling are often activated to manage the stress damaging effects (Chukwurah et al., 2021); however, if unresolved, pro-apoptotic signals are triggered (Pakos-Zebrucka et al., 2016). PKR activation results in its homodimerization and autophosphorylation (Taylor et al., 2001). Independent of eIF2 phosphorylation, activated PKR stimulates the production of pro-inflammatory cytokines through transcriptional regulatory signals such as the activation of the NFκB pathway (Gal-Ben-Ari et al., 2018). Activated PKR is significantly increased in several neurological disorders including Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and Creutzfeldt-Jakob’s disease (Bando et al., 2005; Hugon et al., 2017; Paquet et al., 2009; Peel & Bredesen, 2003; Peel et al., 2001). PKR also has been implicated in learning and memory. New protein synthesis is a prerequisite for the consolidation of labile, short-term memory into more stable, long-term memory (McGaugh, 2000). Thus, it is plausible that memory consolidation involves the eIF2a pathway. Activation of PKR correlates with cognitive decline in aging (Segev et al., 2015). Inhibition eIF2α phosphorylation enhance synaptic plasticity and memory in mice (Costa-Mattioli et al., 2007; Stern et al., 2013). Suppression of PKR using PKR knock-out mice or pharmacological inhibition of PKR activity with PKR inhibitor (PKRi, c16) promotes network hypersynchrony and enhances long term potentiation (LTP) and cognitive performance (Zhu et al., 2011). Acute treatment with PKRi c16 reverses deficits in LTP and memory in a mouse model of AD without affecting amyloid-β load in the hippocampus (Hwang et al., 2017). Taken together, the involvement of PKR in these functions provides strong support that the upregulated PKR signaling we observed in the GWI model mice may underlie GWI-related abnormalities in neuroinflammation and cognition.

Among other stressors, PKR is activated by pro-inflammatory cytokines (e.g., TNF-a, IL-1, and IFN-g) and in turn, activates inflammation-related pathways (Gal-Ben-Ari et al., 2018). Thus, prolonged imbalance in PKR activation appears to create a feedforward loop where inflammatory cytokines play a central role. We found that fingolimod decreased the level of activated PKR in the brain of GWI mice to the low level found in control mice. It is possible that fingolimod decreases the activation of PKR by affecting multiple cell types both in the periphery and in the CNS. In the periphery, fingolimod not only modulates lymphocyte trafficking but also the composition of lymphocyte subsets, suppressing the differentiation of pro-inflammatory cytokine producing Th1 and Th17 lymphocytes while promoting Th2 lymphocytes. In the CNS, fingolimod down-regulates production of pro-inflammatory cytokines in activated microglial and reactive astrocytes (Noda et al., 2013; van Doorn et al., 2012). Furthermore, fingolimod treatment reduces the generation of ceramide, a pro-inflammatory lipid which can induce BBB dysfunction and lead to infiltration of immune cells (van Doorn et al., 2012). Future investigations may reveal the precise mechanism by which fingolimod modulate PKR signaling to regulate neuroinflammation.

Besides PKR there are three other ISR-kinases able to phosphorylate eIF2α in response to cellular stress: PKR-like ER kinase (PERK), heme-regulated eIF2α kinase (HRI), and general control non-derepressible 2 (GCN2). It is worth noting that although we detected a strong increase of PKR phosphorylation in GWI mice compared to control mice, the increased level of phosphorylation for eIFα was barely significant. Notably, the data show that treatment of GWI mice with fingolimod resulted in lowering the level of phosphorylated eIFα to below that of control mice. These results suggest that other ISR-kinases may be involved in GWI and that they may be affected by fingolimod.

Clinical presentation of GWI overlaps strongly with that of two other stress-mediated illnesses: chronic fatigue/myalgic encephalomyelitis syndrome (CFS/ME) and fibromyalgia (Costa-Mattioli et al., 2007) that, like GWI, are debilitating multi-systemic chronic illnesses of unknown etiology (Arnett & Clark, 2012; Wolfe et al., 2011). Like GWI, CFS/ME and fibromyalgia are accompanied by chronic sickness behavior, characterized by widespread musculoskeletal pain, fatigue, and cognitive difficulties (Arnett & Clark, 2012; Maule et al., 2018; Wolfe et al., 2011). The commonality between these diseases suggests that they may share pathological mechanisms. In fact, positron emission tomography of patients with fibromyalgia and CFS/ME have shown abnormal neuroinflammation that correlates with pain, cognitive impairment, and depression scores (Nakatomi et al., 2014; Seo et al., 2021). Multiple studies have reported elevated levels of PKR in blood samples of patients with CFS/ME (Bjorklund et al., 2020; Meeus et al., 2008; Suhadolnik et al., 1997; Vojdani et al., 1997; Vojdani & Lapp, 1999). Activation of PKR may be involved in the development of chronic sickness behavior.

The results from this study demonstrate for the first time the participation of PKR in GWI, uncovering a new molecule connecting environmental signals from exposure to GW-associated chemicals and stress to neuroinflammation and symptomatology in GWI. Moreover, the results indicate that PKR could be a therapeutic target for GWI and that fingolimod, a drug already approved for human use, is a strong candidate for treating GWI patients. Future studies using this and other animal models of GWI ought to investigate male-female differences, the contribution of the other three ISR-kinases in the activation of eIFα, changes in PKR signaling in the hippocampus to support its involvement in cognitive and memory function, as well as the effect of GWI and fingolimod on cytokines and other markers of peripheral and central inflammation, with in-depth analysis of microglia phenotype.

Highlights.

  • Neuroinflammation is common to veterans with GWI and GWI animal models

  • Neuroinflammation in GWI is associated with cognition/mood dysfunction

  • Increased activation of PKR and NFκB signaling occurs in the brain of a GWI mouse model

  • Fingolimod restores memory and microglia activation in a GWI mouse model

  • Fingolimod decreases activation of PKR and NFκB signaling in the brain of a GWI mouse model

Acknowledgements

We thank Anna Zheng and Jacob Lepre for writing assistance of the article and Dr. Bruce Jenkins for helpful advice on the statistical approach and data presentation.

Funding:

This work was supported by a VA Merit I21BX004957 and 5I01BX005180) to A. Dedeoglu, by the National Institute of Aging (1RF1AG056032) to A. Dedeoglu, and by the US Department of Defense (GW180173) to I. Carreras.

Footnotes

Declaration of 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.

Credit Author Statement

Alpaslan Dedeoglu, Isabel Carreras and Younghun Jung: Conceptualization and Methodology; Jonathan Lopez-Benitez, Isabel Carreras, Younhun Jung, Christina Tognoni: Investigation and Data Analysis; Isabel Carreras and Younghun Jung: Writing Preparation; Writing Review and Editing: Alpaslan Dedeoglu, Christina Tognoni, Jonathan Lopez-Benitez.

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