Disease-modifying effects of sodium selenate in a model of drug-resistant, temporal lobe epilepsy

According to the World Health Organization (WHO), there are around 50 million people with epilepsy worldwide. Although drugs are available to control epileptic seizures, these only provide symptomatic relief. They cannot prevent the condition from worsening, and if people with epilepsy stop taking their medication, there is no lasting effect on the severity or frequency of their seizures.

Some epilepsy cases are also resistant to these drugs. This is particularly common in adults with temporal epilepsy, with 30% of people continuing to suffer with seizures despite receiving medication. Current treatments also have no effect on problems with learning, memory and mental health that sometimes accompany drug-resistant epilepsy.

Previous studies in animals have identified some potential treatments that could slow the progression of temporal epilepsy, but these have only been shown to work when used at a very early stage. Since most individuals with temporal epilepsy have already started having seizures when they are diagnosed (and it is difficult to predict who will develop the condition), these drugs are unlikely to be useful in practice.

Here, Casillas-Espinosa et al. set out to find if a novel drug called sodium selenate can stop the progression of epilepsy and reduce the severity of temporal epilepsy when the condition is fully advanced. To do this, they used an animal model of temporal epilepsy, where rats had been modified to develop spontaneous seizures, resistance to normal anti-seizure medications, and problems with learning and memory.

Casillas-Espinosa et al. found that sodium selenate not only reduced the number and severity of seizures in these model rats, but also improved their memory and learning ability. Several rats stopped having seizures altogether even after the treatment had stopped, indicating that sodium selenate had a long-lasting protective effect. Genetic analysis of the rats also revealed that shorter telomeres (special DNA sequences at the ends of chromosomes) correlated with increasing severity of the condition, suggesting that telomere length could help predict who might develop temporal epilepsy or respond best to treatment.

This study identifies sodium selenate as a potential treatment that could reverse the progression of temporal epilepsy, even in individuals with advanced symptoms. Later this year, sodium selenate will be trialled in people with drug-resistant temporal epilepsy to determine if the drug benefits humans in the same way. Casillas-Espinosa et al. hope that it will improve participants’ epilepsy and, ultimately, their quality of life.

Temporal lobe epilepsy (TLE) is the most common form of drug-resistant epilepsy in adults and is frequently accompanied by disabling neuropsychiatric and cognitive comorbidities (Hermann et al., 2008; Hermann et al., 2000; Kwan et al., 2011; Sharma et al., 2007; Tellez-Zenteno et al., 2007). People with epilepsy are often required to take multiple anti-seizure medications (ASMs) in an attempt to control their seizures. However, these treatments are ineffective at controlling seizures in more than 30% of cases (Hermann et al., 2008; Hermann et al., 2000; Kwan et al., 2011; Sharma et al., 2007; Tellez-Zenteno et al., 2007), and can cause significant adverse side effects (Alonso-Vanegas et al., 2013; Perucca and Gilliam, 2012; Taylor et al., 2011). Current ASMs are merely symptomatic and do not mitigate the severity, progression, or outcome of the epilepsy, and if the patient ceases the medication their seizures are just as severe and frequent as if the person has never taken the medication in the first place (Simonato et al., 2014). Despite decades of research and development, the more than 20 new ASMs that have been introduced to clinical practice have failed to reduce the proportion of people with epilepsy who have drug-resistant seizures (Chen et al., 2018). Moreover, the cognitive and neuropsychiatric comorbidities that are prevalent in these patients remain difficult to treat and are not improved by the ASM treatment (Hinnell et al., 2010; Valente and Busatto Filho, 2013).

Animal studies have identified compounds potentially capable of delaying epileptogenesis (i.e. the process by which a non-epileptic brain turns into an epileptic one), but to date, these have only been demonstrated to be effective when the treatment is initiated early in the disease process (i.e. immediately after the brain insult) (Casillas-Espinosa et al., 2019b; Liu et al., 2016; Pauletti et al., 2019; Rizzi et al., 2019; Zeng et al., 2009; Huang et al., 2019). Because the majority of TLE patients already have established epilepsy when they present to the clinic (Foster et al., 2019), and there are no reliable biomarkers to predict who will develop TLE, this treatment strategy has limited clinical utility (Simonato et al., 2021). Surgical resection of the epileptogenic zone is currently the only effective disease-modifying intervention in patients with chronic drug-resistant TLE, but is only suitable in selected patients, is not always successful, and can have significant complications (Téllez-Zenteno et al., 2005). It is estimated that <5% of patients with drug-resistant epilepsy are suitable for resective epilepsy surgery (Téllez-Zenteno et al., 2005). Thus, there is a compelling need to identify pharmacological DMTs that are effective in patients with chronic TLE. (O’Brien et al., 2013; Sharma et al., 2007; Simonato et al., 2013).

Hyperphosphorylated tau (h-tau) is a neuropathological hallmark of several neurodegenerative conditions and has recently been implicated in epileptogenesis (Casillas-Espinosa et al., 2020; Ittner and Götz, 2011; Johnstone et al., 2015; Liu et al., 2016; Sen et al., 2007; Shultz et al., 2015; Thom et al., 2011; van Eersel et al., 2010). For example, h-tau is present in the brains of rodents with TLE, (Corcoran et al., 2010b; Jones et al., 2012; Shultz et al., 2015) ,and deposits of h-tau have been identified in surgically resected tissue from patients with drug-resistant epilepsy (Puvenna et al., 2016; Sánchez et al., 2018; Sen et al., 2007; Tai et al., 2016; Thom et al., 2011). The primary tau phosphatase in the brain (i.e. an enzyme that dephosphorylates tau) is protein phosphatase 2 A (PP2A) (Corcoran et al., 2010a), a heterotrimer consisting of a catalytic C subunit, a scaffold A subunit, and a regulatory B subunit with variable isoforms (Janssens and Goris, 2001). In several models of epilepsy, activation of PP2A with sodium selenate has been shown to reduce h-tau, and early treatment imparts anti-epileptogenic effects, while also reducing behavioral deficits associated with the epilepsy (Liu et al., 2016). However, whether pharmacological intervention with sodium selenate in chronic epileptic animals is a DMT remains to be determined. Therefore, this study investigated the effect of sodium selenate treatment on epileptic and behavioral outcomes, as well as multi-omics network medicine and bioinformatics approaches to uncover relevant molecular pathways, in chronically epileptic rats. We used the well-validated kainic acid (KA) post- post-status epilepticus (SE) model of TLE, where animals develop resistance to drug treatment, behavioral, cognitive, and sensorimotor comorbidities analogous to human drug-resistant TLE (Casillas-Espinosa et al., 2019b; Thomson et al., 2020).

This study evaluated the effect of sodium selenate on established TLE, using the post-SE model of drug-resistant TLE. Ten-weeks post-SE, chronically epileptic rats were randomly assigned to receive either sodium selenate (1 mg/kg/day), levetiracetam (200 /mg/kg/day, a commonly prescribed ASM for TLE) (Mbizvo et al., 2012), or vehicle (saline 0.9%) continuously for four weeks. To evaluate the sustained effects of the treatments, video-EEG was acquired before, during, and up to eight weeks post-treatment, followed by behavioral tests to assess cognitive, and sensorimotor comorbidities. Targeted and untargeted proteomics and metabolomics were performed on brain tissue to investigate potential pathways and molecules associated with modified disease outcomes. Telomere length was investigated as a surrogate marker of disease severity and treatment response. The experimental paradigm is shown in Figure 7 of the Methods section.

Sodium selenate is disease-modifying with enduring effects that reduce the number of seizures in drug-resistant TLE rats

Video-electroencephalogram (vEEG) was used to examine the effects of the treatments before, during, and up to eight weeks post-treatment on the occurrence of spontaneous recurrent seizures (Figure 1). Vehicle and levetiracetam-treated animals showed a significant progressive increase in the number of seizures recorded over the course of the experiments [F (8, 124)=2.022, p<0.05]. vEEG analysis during continuous drug treatment (10–14 weeks post-SE) revealed that neither vehicle, sodium selenate, or levetiracetam significantly impacted the number [F (4, 62)=0.4781, p=0.751], duration [F (2, 43)=0.5030, p=0.608], or severity of the seizures [F (2, 43)=0.4563, p=0.636], experienced by post-SE rats, indicating that drug-resistant epilepsy is present 10 weeks after KA-induced SE (Figure 1A). However, following the cessation of treatment, one-way ANOVA showed a treatment effect reducing the number of seizures that the animal experienced [F (31, 31)=3.956, p<0.0001; Figure 1A]. Tukey’s post hoc analysis revealed that sodium selenate treatment significantly reduced the number of seizures eight weeks post-treatment in contrast to vehicle-treated animals (p<0.05). Interestingly, four of the twelve sodium selenate-treated animals did not manifest any seizures eight weeks after the drug washout, while all of the vehicle and levetiracetam-treated animals showed spontaneous seizures through the experiment. In contrast, Tukey’s post hoc showed that levetiracetam treatment did not significantly reduce the number of seizures in comparison to vehicle or selenate-treated animals. Average seizure duration [F (1, 15)=1.038, p=0.3243; Figure 1B] and seizure severity, assessed by the Racine scale (Racine, 1972) [F (1, 13)=0.4873, p=0.497; Figure 1C] were not significantly different between the three treatment groups. Figures showing the individual timepoints of the seizure analysis are found in Figure 1—figure supplement 1.

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Sodium selenate treatment improves spatial memory and recognition memory

Cognitive deficits are one of the most debilitating comorbidities seen in patients with TLE (Hermann et al., 2008; Hermann et al., 2000; Kwan et al., 2011; Sharma et al., 2007; Tellez-Zenteno et al., 2007). The novel object placement (NOP) evaluates spatial memory (Spanswick and Sutherland, 2010). Vehicle-treated animals had impaired spatial memory in comparison to shams, as they spent significantly less time in the novel location of the object (p<0.05, Figure 2A). Levetiracetam treatment did not improve spatial memory compared to vehicles. Animals that had been treated with sodium selenate, even after an eight week washout, spent significantly more time evaluating the novel location of the object than those treated with the vehicle, which is indicative of improved spatial memory (p<0.05). The novel object recognition (NOR) evaluates recognition memory (Spanswick and Sutherland, 2010). Both vehicle and levetiracetam-treated rats spent less time evaluating the novel object relative to sham rats (p<0.05, Figure 2B), which is indicative of impaired recognition memory. In contrast, sodium selenate treatment was also able to improve recognition memory in comparison to vehicle-treated rats (p<0.05). Interestingly, the performance of the sodium selenate-treated animals was comparable to shams in both the NOP and NOR. Figures showing the individual timepoints of the MWM are found in Figure 2—figure supplement 1.

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To further evaluate cognitive function, rats were tested in the Morris water maze (MWM) (Morris, 1984). During the acquisition session of the MWM, only the post-SE rats treated with vehicle and levetiracetam displayed significantly increased search times than their sham counterparts [subject x treatment effects: F(12, 164)=2.501, p<0.01; selenate animals p>0.05 Figure 2C]. One day after the water maze acquisition session, rats underwent MWM reversal session where the location of the escape platform was changed. Here, all of the post-SE rats cohorts took more time to find the hidden platform in comparison to shams [F(4, 157)=5.971 p<0.001 Figure 2D]. No differences in swim speed were observed between the different groups.

The protein phosphatase family is differentially expressed after treatment with sodium selenate

Sodium selenate has been described to activate PP2A subunit B and to reduce h-tau after traumatic brain injury and in different models of epilepsy (Liu et al., 2016; Shultz et al., 2015). However, to further understand the mechanism by which sodium selenate exerts its disease-modifying effects in our model of established chronic TLE, we utilized state-of-the-art, high-resolution data-independent acquisition mass-spectrometry (DIA-MS), untargeted proteomics and metabolomics analyzes were carried out in the somatosensory cortex and hippocampus to identify potential markers of TLE and on the proteome and metabolome. A total of 5615 and 5538 proteins have been identified and quantified across all samples in the somatosensory cortex and hippocampus, respectively, considering a false discovery rate (q-value) cut-off of 1%. Differential expression analyses using ANOVA revealed 24 proteins in the somatosensory cortex and 9 proteins in the hippocampus to be significantly dysregulated across all experimental conditions (Figure 3, Supplementary file 1 and Supplementary file 2). Notably, protein phosphatase 2 regulatory subunit B alpha (Ppp2r5a), heat shock protein family A member 2 (Hspa2), and lymphocyte cytosolic protein 1 (Lcp1) were differentially expressed between selenate and vehicle-treated post-SE groups in the somatosensory cortex (Tukey’s HSD, FDR <0.05, Figure 3A, Supplementary file 1). Heat shock protein family B member 1 (Hspb1), Ro690 Y RNA binding protein (Ro60), and DENN domain containing 11 (Dennd11) proteins were differentially expressed between selenate and vehicle treated groups in the hippocampus (Tukey’s HSD, FDR <0.05, Figure 3B, Supplementary file 2). To further examine the changes in the proteomic profile of selenate-treated rats we performed quantitative gene set enrichment analysis between all pairs of treatment groups. Figure 3—figure supplement 1 shows the top 25 differentially regulated pathways in the somatosensory cortex (Figure 3—figure supplement 1A) and hippocampus (Figure 3—figure supplement 1B). Interestingly in the somatosensory cortex of the selenate group, among the most significantly upregulated pathways were signaling cascades mediated by activated insulin-like growth factor receptors (IGFR) and fibroblast growth factor receptors (FGRF) such as the FGFR-mediated phosphatidylinositol 3-kinase (PI-3K) cascade activation and IGFR1 signaling cascades (FDR <0.05). Among the top downregulated pathways in the somatosensory cortex were beta-oxidation of fatty acids and iron uptake and transport.

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In addition to proteomic analyses, we also performed untargeted univariate metabolomic analyses on the same samples. However, we were not able to identify significant changes between the experimental groups in the somatosensory cortex, suggesting that selenate primarily induces proteomic alterations in this region whilst keeping the metabolome stable (Supplementary file 3). In contrast, six metabolites were significantly different in selenate-treated animals as shown in Supplementary file 4. Partial least squares-discriminant analysis (PLS-DA) and principal component analysis (PCA) for the proteomics and metabolomics analyses are shown in Figure 3—figure supplement 2.

Sodium selenate-treated animals have longer telomere lengths

Telomere length was investigated as a surrogate marker of epilepsy severity and response to pharmacological treatment (Chan et al., 2020; Galletly et al., 2017; Kang et al., 2020; Lukens et al., 2009). Ear biopsies were taken 25 weeks post-SE to evaluate the effects of chronic epilepsy on telomere length. We found that TLE resulted in telomere shortening in vehicle-treated rats (p<0.001), and this was not prevented by levetiracetam treatment (p<0.01). However, sodium selenate treatment was able to reverse telomere shortening seen in post-SE animals treated with the vehicle (p<0.01), with the treated rats having telomere lengths similar to sham animals (Figure 4).

Figure 4

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Network medicine integration highlights discrete protein-metabolite modules correlate with treatment and pre-clinical outcomes

Network medicine integration was performed to investigate pathways correlated with the TLE phenotype. We integrated the untargeted multi-omics (proteomics and metabolomics) datasets with the targeted proteomics and phosphoproteomics (PP2A, tau, and h-tau), TLE phenotype (seizures, cognitive, and sensorimotor outcomes), and telomere length studies to investigate protein-metabolite groups/pathways correlated with the response to selenate treatment. Weighted correlation network analysis identified 20 and 17 protein-metabolite modules, respectively, in the hippocampal and cortical multi-omic datasets. Several protein-metabolite modules showed significant positive and negative correlations with multiple treatment groups and various clinical measures (Figure 5). Figure 5C In the hippocampal network (Figure 5A), the Purple module shows significant inverse correlation with selenate treatment group, and is enriched for proteins and metabolites involved in aminoacyl-tRNA biosynthesis (FDR = 0.0059) and Lysine degradation (FDR = 0.021) pathways. This module is also inversely correlated with levetiracetam-treated group, but shows no correlation with the vehicle group. The Yellow module is significantly (p=0.02) correlated with the selenate-treated group and has no significant correlations with other groups. This module is enriched for proteins and metabolites involved in complement cascade, oxidative phosphorylation and other metabolic pathways.

Figure 5

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In the somatosensory cortex correlation network (Figure 5B), the Tan (p=0.002), Magenta (p=0.002), Yellow (p=0.02), and Light-cyan (p=0.02) modules were significantly correlated with the selenate treated group and showed no correlation with the vehicle-treated group (Figure 5B). The magenta module does not annotate to any significant pathways; however, the Yellow module is enriched for proteins and metabolites involved in oxidative phosphorylation and other metabolic pathways, and the Tan module annotates to the insulin signaling pathway. Lastly, proteins and metabolites in the Light-cyan module are enriched for fatty acid biosynthesis pathways.

Current pharmacological treatments for TLE, ASMs, are merely symptomatic, attenuating seizures when taken on an ongoing basis without any sustained disease-modifying effects on the propensity to have seizures, or on its disabling associated neuropsychiatric, cognitive, and sensorimotor comorbidities (Brooks-Kayal et al., 2013; Pitkänen et al., 2013; Saletti et al., 2019). Once these treatments are discontinued (or the patient fails to take doses), the seizures relapse to at least the same severity and frequency as pre-treatment (Coan and Cendes, 2013; Kwan et al., 2011). Here, we report for the first time a pharmacological treatment that has persistent disease-modifying effects in an animal model of chronic drug-resistant TLE. Sodium selenate treatment was shown to have an enduring effect, mitigating the established epileptic state, and reducing the frequency of seizures and cognitive comorbidities. Our group has previously shown that treatment with sodium selenate in epilepsy models reduces h-tau, increases PP2A, and mitigates the development of epilepsy when delivered immediately after an epileptogenic brain injury before the occurrence of spontaneous recurrent seizures (i.e. an anti-epileptogenic effect) (Jones et al., 2012; Liu et al., 2016). However, the most common clinical scenario is that patients present to the clinic with established TLE, weeks to years after the epileptogenic brain insult, and in some patients, there is no identifiable brain insult (Foster et al., 2019).

The data from this study demonstrates that four weeks of sodium selenate treatment is associated with an enduring effect on mitigating the chronic epileptic state, reducing the frequency of seizures, neurocognitive, sensorimotor and neurobehavioral comorbidities, and biomarkers of disease severity. Strikingly, 4 of 12 animals (33%), did not have any seizures at all at this final timepoint eight weeks following the cessation of the treatment. In contrast, all levetiracetam and vehicle-treated animals showed spontaneous seizures at the end of the study. It is important to note that, analogous to human chronic TLE, spontaneous remission of seizures is not part of the natural history of the post-KA SE rat model of chronic TLE (Van Nieuwenhuyse et al., 2015a; Williams et al., 2009).

Behavioral comorbidities are considered an integral part of the TLE disease (Brooks-Kayal et al., 2013; Mazarati et al., 2018). Patients with chronic and drug-resistant TLE have an increased prevalence of psychiatric conditions, memory, and learning disabilities (Kandratavicius et al., 2012; Ott et al., 2003; Stafstrom et al., 1993; Stores, 1971; Tellez-Zenteno et al., 2007). Cognitive impairment is the most common comorbidity that afflicts people with TLE and tends to resist treatment, even after epilepsy surgery (Hermann et al., 2000). In fact, in a proportion of cases, the cognitive dysfunction progresses despite successful seizure control (Amlerova et al., 2014; Berg et al., 2012; Smith et al., 2014; Taylor et al., 2010). In keeping with the human condition, cognitive deficits have been demonstrated as a comorbidity in the post-SE animal model (Detour et al., 2005; Pearson et al., 2014; Chauvière et al., 2009). Here, we found that animals treated with sodium selenate had improved spatial memory and recognition memory, comparable to non-epileptic controls. This is the first time that a treatment has been described to reverse memory deficits in established chronic TLE.

Sensorimotor deficits are another significant comorbidity in people with TLE (Girardi-Schappo et al., 2021; Gandelman-Marton et al., 2006), and are not necessarily associated with the presence of seizures or with the use of ASMs (Gandelman-Marton et al., 2006; Petty et al., 2010; Shiek Ahmad et al., 2015). A study in patients with drug-resistant TLE found abnormal postural instability and an increased risk of falls than healthy controls (Gandelman-Marton et al., 2006). Interestingly, transgenic mouse models that expressed h-tau have been described to not only present cognitive dysfunction but also sensorimotor impairments (Kreilaus et al., 2021; Leroy et al., 2007; Lewis et al., 2000). Here, we found that sodium selenate treatment mitigated the sensorimotor deficits in chronically epileptic rats in the post-KA SE model of TLE.

The results from this study add to the growing literature that indicates that pathological h-tau is a key pathophysiological driver of drug-resistant TLE and associated comorbidities. To further test this hypothesis, we performed untargeted proteomics using DIA-MS and targeted h-tau and PP2A protein analysis using Western Blots. Our data indicate that the persistent disease-modifying effects of sodium selenate in drug-resistant TLE correlate to the increased the expression of the B catalytic subunit of PP2A and the reduction of h-tau. Evidence has shown that the PP2A B subunit is specifically involved in the dephosphorylation of tau (Barnes et al., 1995; Corcoran et al., 2010a) and PP2A expression and activity are potentiated by sodium selenate (Corcoran et al., 2010a; Jones et al., 2012; Shultz et al., 2015).

In accordance with animal models (Corcoran et al., 2010b; Jones et al., 2012; Shultz et al., 2015), increased levels and deposits of h-tau have been described in surgically resected tissue from patients with drug-resistant TLE (Puvenna et al., 2016; Sánchez et al., 2018; Sen et al., 2007; Tai et al., 2016; Thom et al., 2011). In resected tissue from patients with drug-resistant TLE, PP2A protein expression is also significantly decreased, but remains unchanged in Alzheimer’s disease patients, indicating that PP2A alterations may be an epilepsy-specific pathology (Gourmaud et al., 2020). There is also building evidence that tau-based mechanisms enhance neuronal excitability. Alterations in tau phosphorylation have been implicated in changing the excitation/inhibition balance in the neurons (Palop et al., 2007). Unstable microtubule assembly at axonal segments, as seen with the presence of h-tau, dysregulates the resting membrane potential and thereby generations of action potentials (Matsumoto and Sakai, 1979). Tau is transported into the cell via Fyn kinase where it influences N-methyl-D-aspartate (NMDA) receptor-mediated excitotoxicity (van Eersel et al., 2010) and changes in tau has been correlated with dysfunction of axonal NMDA receptors which are all considered mechanisms that promote the expression of seizures (Liu et al., 2017).

Pathological h-tau, has been proposed as one of the main culprits underlying cognitive deficits across different neurodegenerative disorders such as Alzheimer’s disease, TBI, and epilepsy (Casillas-Espinosa et al., 2020). Accumulation of h-tau in temporal lobe brain tissue from patients with drug-resistant TLE is associated with cognitive decline (Gourmaud et al., 2020; Thom et al., 2011). Furthermore, tau pathology has been associated with a decline in verbal learning, recall, and graded naming test scores in different neurodegenerative disorders (Tai et al., 2016) and in animal models that overexpressed h-tau (Kreilaus et al., 2021; Leroy et al., 2007; Lewis et al., 2000).

It is interesting that for some of the animals, the effects of sodium selenate were only observed several weeks after cessation of treatment, and the magnitude of the decrease in seizure expression progressively increased over the eight weeks of follow-up post-treatment. One possibility could be that the processes required to mitigate epileptic activity in neurons take time, particularly in chronically epileptic animals. However, it is also possible that the effects of sodium selenate extend beyond the described modification of h-tau and PP2A.

Dimension reduction is crucial for hypothesis generation to elucidate pathological mechanisms and changes in biological pathways as a response to treatment. To further explore sodium selenate’s mechanism of action, we performed a network medicine integration of our untargeted/targeted multi-omics datasets, TLE outcomes (seizures and behavior), and molecular studies (western blots and telomere length analyses) to evaluate the correlation coefficients of single modules between the different treatment groups (e.g. Selenate and Vehicle). By mapping significant genes/proteins together with metabolites to biological pathways, our network integration approach allowed for the reduction in experimental and biological noise and higher confidence levels, thereby generating potential new disease modules (proteins and metabolites and the cellular pathways they are involved in). We found modules that constitute the ‘healthy state,’ which operate in a concerted fashion in a healthy brain but are lost in the setting of TLE. For example, the Green Module is positively correlated to epilepsy phenotype, poor cognitive performance, poor balance, shorter telomeres, decreased PP2A, increased h-tau expression, and cardiomyopathies, which are associated with several epilepsy syndromes (Devinsky et al., 2018; Gilchrist, 1963; Naggar et al., 2014; Stöllberger et al., 2011; Surges and Sander, 2012). Of particular interest are the Yellow Module in both the hippocampal and somatosensory cortex correlation networks as well as Tan and Light-cyan Modules in the somatosensory cortex. All of the above-mentioned modules positively correlated with selenate treatment. The Yellow Module is enriched for pathways involved in ATP metabolism, oxidative phosphorylation, and several inflammatory systems. The Tan Module is enriched for insulin signaling pathways and the Light-cyan Module annotates to fatty acid metabolism pathways. It is important to note that ‘enrichment’ does not mean ‘increase’ or ‘upregulation.’ The enrichment in insulin signaling, for example, highlights the involvement of this pathway in the epilepsy phenotype and selenate treatment, but unfortunately provides no information about the direction of change (upregulation or downregulation). In an attempt to capture changes in the regulation of biological pathways that may be influenced by sodium selenate treatment, we conducted a quantitative enrichment analysis on a pathway level (PADOG) between the selenate and vehicle groups, utilizing the Reactome pathway database resource. Based on the PADOG analysis results, there is significant upregulation of IGFR1 and FGFR signaling cascades and FGFR-mediated PI-3K cascade activation in the selenate-treated group compared to the vehicle. Given the neuroprotective role of PI-3K signaling in several epilepsy syndromes, it is conceivable that this is one of the potential mechanisms by which sodium selenate exerts its long-term disease-modifying effect. The strong correlation of the Tan Module, which annotates to insulin signaling pathways to selenate treatment only further highlights the involvement of insulin signaling in the potential mechanism of action of this treatment. The downregulation of fatty acid oxidation processes in the selenate group suggests a shift from hyperactive neurons with high-energy demand (like in epileptic seizures) towards neurons with lower energy demand.

To our knowledge, this analysis is the first attempt at the integration of metabolomic and proteomic data in an epilepsy network medicine paradigm. We demonstrate that multi-omic, data-driven correlation networks can be used for agnostic, hypothesis-free examination of disease states as well as the identification of specific protein-metabolite modules associated with different states and treatments. Further investigation of these pathways as potential mechanisms involved in the mode of action of sodium selenate can be instrumental in understanding and reversing the drug resistance of TLE.

Prognostic biomarkers are used to predict disease characteristics and identify disease recurrence or progression in patients who have the disease of interest. Unfortunately, no such prognostic biomarkers for TLE currently exist (Simonato et al., 2021). Telomere length has emerged as a potential prognostic biomarker of chronic neurodegenerative conditions (Chan et al., 2020; Kang et al., 2020; Galletly et al., 2017; Lukens et al., 2009). Telomeres are repetitive non-coding DNA-tandem sequences of TTAGGG found at the end of eukaryotic chromosomes (Hehar and Mychasiuk, 2016). Telomere length has been used as a biological marker for cellular aging and has been described in many neurological disorders (Hehar and Mychasiuk, 2016; Koppelstaetter et al., 2009; Sun et al., 2019; Wright et al., 2018), including TLE (Miranda et al., 2020). Here, we analyzed telomere length from ear biopsies, as previous evidence has shown a strong correlation between telomere length in the brain and peripheral skin cells (Hehar and Mychasiuk, 2016). We found that telomere length was significantly reduced in TLE animals treated with vehicle or levetiracetam, and sodium selenate-treated animals had longer telomeres. The magnitude of the reduced telomere length was strongly associated with the number of seizures and more pronounced cognitive deficits in our drug-resistant TLE model. Overall, our data highlights the potential of telomere length as a prognostic biomarker of disease severity, treatment response, and TLE disease modification, which has the potential to be used in further trials of DMT.

Future studies should incorporate multi-omics and telomere length analysis integration performed at different timepoints from brain tissue and biofluids (blood and CSF) to map out the development, progression of epilepsy, and treatment response in this model. Unlike individual markers, pathway/network-based prognostic markers should be inherently more reliable since they provide the biological interpretation for the association between multiple molecules and the disease characteristics (seizures, behavior comorbidities, development of TLE) (Zou et al., 2013). Similarly, this approach could help to increase our understanding of the mechanism of action of sodium selenate as a disease-modifying treatment for established drug-resistant TLE.

All the metrodology and results form this work have been included in the manuscrit or as part of the supplementary material. Data has been deposited in Dryad https://doi.org/10.5061/dryad.37pvmcvnd.

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Author details

1. Pablo M Casillas-Espinosa

   1. Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia
   2. Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
   3. Monash Proteomics & Metabolomics Facility and Monash Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia

   Contribution

   Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Writing – original draft, Writing – review and editing

   For correspondence

   pablo.casillas-espinosa@monash.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6199-9415

2. Alison Anderson

   1. Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia
   2. Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia

   Contribution

   Data curation, Formal analysis, Writing – review and editing

   Competing interests

   No competing interests declared

3. Anna Harutyunyan

   1. Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia
   2. Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia

   Contribution

   Formal analysis, Methodology, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6165-5639

4. Crystal Li

   Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia

   Contribution

   Data curation, Investigation

   Competing interests

   No competing interests declared

5. Jiyoon Lee

   Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia

   Contribution

   Data curation

   Competing interests

   No competing interests declared

6. Emma L Braine

   1. Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia
   2. Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia

   Contribution

   Data curation

   Competing interests

   No competing interests declared

7. Rhys D Brady

   1. Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia
   2. Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia

   Contribution

   Data curation, Writing – review and editing

   Competing interests

   No competing interests declared

8. Mujun Sun

   Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia

   Contribution

   Investigation

   Competing interests

   No competing interests declared

9. Cheng Huang

   Department of Neurology, The Alfred Hospital, Commercial Road,, Melbourne, Victoria, Australia

   Contribution

   Data curation, Investigation

   Competing interests

   No competing interests declared

10. Christopher K Barlow

    Department of Neurology, The Alfred Hospital, Commercial Road,, Melbourne, Victoria, Australia

    Contribution

    Data curation

    Competing interests

    No competing interests declared

11. Anup D Shah

    Department of Neurology, The Alfred Hospital, Commercial Road,, Melbourne, Victoria, Australia

    Contribution

    Data curation, Methodology

    Competing interests

    No competing interests declared

12. Ralf B Schittenhelm

    Department of Neurology, The Alfred Hospital, Commercial Road,, Melbourne, Victoria, Australia

    Contribution

    Formal analysis, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

13. Richelle Mychasiuk

    Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia

    Contribution

    Data curation, Investigation, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

14. Nigel C Jones

    1. Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia
    2. Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia

    Contribution

    Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

15. Sandy R Shultz

    1. Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia
    2. Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia

    Contribution

    Data curation, Methodology, Writing – review and editing

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-2525-8775

16. Terence J O'Brien

    1. Department of Medicine, The Royal Melbourne Hospital, The University of Melbourne, Melbourne, Australia
    2. Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
    3. Monash Proteomics & Metabolomics Facility and Monash Biomedicine Discovery Institute, Monash University, Clayton, Victoria, Australia

    Contribution

    Conceptualization, Supervision, Visualization, Writing – review and editing

    For correspondence

    Terence.OBrien@monash.edu

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-7198-8621

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