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Molecular and Cellular Mechanisms of Epilepsy—3rd Edition

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A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Neurobiology".

Deadline for manuscript submissions: 31 May 2025 | Viewed by 12175

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Dr. Aleksey Zaitsev

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Laboratory of Molecular Mechanisms of Neural Interactions, Sechenov Institute of Evolutionary Physiology and Biochemistry, 194223 Saint Petersburg, Russia
Interests: electrophysiology; neurophysiology; neurobiology and brain physiology; neurobiology; neuropharmacology; cellular neuroscience physiology; neuron; neuroscience; brain
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Special Issue Information

Dear Colleagues,

This is a continued collection of the hot topic on Epilepsy. We already have done two successful special issues which received interesting contributions and discussions (https://www.mdpi.com/journal/ijms/special_issues/molecular_cellular_epilepsy; https://www.mdpi.com/journal/ijms/special_issues/KLPQB5U741).

Despite the availability of many antiepileptic drugs, more than 30% of patients with epilepsy, especially temporal lobe epilepsy, continue to experience seizures. The most rational therapeutic option for drug-resistant epilepsy is the prevention of the development and progression of epilepsy. Prevention has to be grounded in the understanding of the pathophysiological mechanisms leading to epilepsy. In the case of temporal lobe epilepsy, our knowledge of the possible causes is still insufficient. In recent years, many breakthroughs have been made in identifying cellular and molecular alterations linked to severe epilepsy. These alterations include but are not limited to (1) loss of principal cells and interneurons and neurogenesis, including changes in morphology and neuronal firing patterns related with altered composition or expression of receptors and channels; (2) gliosis, including changes in the functioning of glial cells and neuron-astrocyte interactions; (3) loss of the integrity of blood–brain barrier and neuroinflammation. All these histopathological changes are suspected to contribute to epileptogenesis and could be important targets for preventive therapies.

This Special Issue “Molecular and Cellular Mechanisms of Epilepsy 3.0”, will comprise a selection of research papers and reviews covering various aspects of molecular and cellular biology of epilepsy models. Studies on bioactive molecules modulating epileptogenesis will also be considered.

Dr. Aleksey Zaitsev
Guest Editor

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Keywords

epilepsy
epilepsy models
epileptogenesis
preventing epilepsy
neuroinflammation
neuroprotection
synaptic plasticity
neuron–astrocyte interaction

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14 pages, 1295 KiB

Open AccessArticle

Resilience of Spontaneously Hypertensive Rats to Secondary Insults After Traumatic Brain Injury: Immediate Seizures, Survival, and Stress Response

by Ilia Komoltsev, Olga Kostyunina, Pavel Kostrukov, Daria Bashkatova, Daria Shalneva, Stepan Frankevich, Olga Salyp, Natalia Shirobokova, Aleksandra Volkova, Aleksandra Soloveva, Margarita Novikova and Natalia Gulyaeva

Int. J. Mol. Sci. 2025, 26(2), 829; https://doi.org/10.3390/ijms26020829 (registering DOI) - 19 Jan 2025

Abstract

Traumatic brain injury (TBI) is one of the primary causes of mortality and disability, with arterial blood pressure being an important factor in the clinical management of TBI. Spontaneously hypertensive rats (SHRs), widely used as a model of essential hypertension and vascular dementia, demonstrate dysfunction of the hypothalamic–pituitary–adrenal axis, which may contribute to glucocorticoid-mediated hippocampal damage. The aim of this study was to assess acute post-TBI seizures, delayed mortality, and hippocampal pathology in SHRs and normotensive Sprague Dawley rats (SDRs). Male adult SDRs and SHRs were subjected to lateral fluid-percussion injury. Immediate seizures were video recorded, corticosterone (CS) was measured in blood plasma throughout the study, and hippocampal morphology assessed 3 months post-TBI. Acute and remote survival rates were significantly higher in the SHRs compared to the SDRs (overall mortality 0% and 58%, respectively). Immediate seizure duration predicted acute but not remote mortality. TBI did not affect blood CS in the SHRs, while the CS level was transiently elevated in the SDRs, predicting remote mortality. Neuronal cell loss in the polymorph layer of ipsilateral dentate gyrus was found in both the SDRs and SHRs, while thinning of hippocampal pyramidal and granular cell layers were strain- and area-specific. No remote effects of TBI on the density of astrocytes or microglia were revealed. SHRs possess a unique resilience to TBI as compared with normotensive SDRs. SHRs show shorter immediate seizures and reduced CS response to the injury, suggesting the development of long-term adaptative mechanisms associated with chronic hypertension. Though remote post-traumatic hippocampal damage in ipsilateral dentate gyrus is obvious in both SHRs and SDRs, the data imply that physiological adaptations to high blood pressure in SHRs may be protective, preventing TBI-induced mortality but not hippocampal neurodegeneration. Understanding the mechanisms of resilience to TBI may also help improve clinical recommendations for patients with hypertension. Limitation: since more than a half of the SDRs with prolonged immediate seizures or elevated CS 3 days after TBI have died, survivorship bias might hamper correct interpretation of the data. Full article

(This article belongs to the Special Issue Molecular and Cellular Mechanisms of Epilepsy—3rd Edition)

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Figure 1

Figure 1
Acute and remote mortality in SDRs and SHRs. (A) The proportion of acute and remote mortality in SDRs and SHRs; ###—p < 0.001, χ2 test. (B) Survival curves according to the Kaplan–Meier method; p = 0.001. SHRs: TBI group n = 15 and SDRs: TBI group n = 26. Full article ">Figure 2
Immediate seizures in SHRs and SDRs and prediction of acute mortality. The durations of seizures (A), apnea (B), and recovery of pose (C) were shorter in SHRs, while rats with paw cyanosis (D) were absent in the SHR group. (E) The duration of seizures immediately after TBI was longer in the SDRs that died within 10 min after LFPI. (F) The duration of apnea and (G) recovery of pain sensitivity was longer in the SDRs that died. (H) ROC analysis: the duration of immediate seizures predicted acute mortality. For (E–H), mixed SDRs + SHRs group was used. (A–G)—the data are presented as M ± SEM. *—p < 0.05; ***—p < 0.001 (Mann–Whitney test); and ##—p < 0.01 (χ2 test). SHRs: TBI group n = 15 and SDRs: TBI group n = 26. Full article ">Figure 3
Blood serum CS time course and late mortality prediction. (A) Changes in CS levels during the experiment in sham-operated and TBI groups of SDRs and SHRs. An increase in CS was revealed on day 3 after TBI in SDRs. (B) Three months after TBI or sham operation, a short forced-swim-test-induced increase in blood plasma CS in sham-operated and TBI groups of SHRs and SDRs qq. (C) ROC analysis: CS level on day 3 predicted late mortality. (D) ROC analysis: immediate seizure duration did not predict late mortality. (A,B)—the data are presented as M ± SEM. ***—p < 0.005; Mann–Whitney test; #—p < 0.05; and RM ANOVA for time factor. For (C,D), mixed SDRs + SHRs group was used. SHRs: TBI group n = 15 and sham group n = 10 and SDRs: TBI group n = 26 and sham group n = 16. Full article ">Figure 4
Neuronal and glial cell density in the hippocampus 3 months after TBI or sham operation. (A,B) Neuronal cell density in the DG of SDRs and SHRs, respectively. Neuronal cell density was lower in the polymorph layer of the ipsilateral hippocampus in both rat strains. (C) Representative microphotograph with neurodegeneration in the ipsilateral DG (polymorph layer is marked by the arrow), Nissl staining. (D,E) Astroglal cell density in the hippocampi of SDRs and SHRs, respectively. (F) Representative microphotograph (SHRs, ipsilateral DG), GFAP staining. (G,H) Microglial cell density in the hippocampi of SDRs and SHRs, respectively. Microglial activation was detected only in the contralateral DG of SDRs. (I) Representative microphotograph (SHR, ipsilateral DG), Iba1 staining. (A,B,D,E,G,H)—the data are presented as M ± SEM. *—p < 0.05, Mann–Whitney test. SHRs: TBI group n = 15 and sham group n = 10 and SDRs: TBI group n = 26 and sham group n = 16. Full article ">

17 pages, 7138 KiB

Open AccessArticle

Metabolic Adaptation in Epilepsy: From Acute Response to Chronic Impairment

by Agustin Liotta, Stefan Loroch, Iwona Wallach, Kristoffer Klewe, Katrin Marcus and Nikolaus Berndt

Int. J. Mol. Sci. 2024, 25(17), 9640; https://doi.org/10.3390/ijms25179640 - 6 Sep 2024

Cited by 1 | Viewed by 1044

Abstract

Epilepsy is characterized by hypersynchronous neuronal discharges, which are associated with an increased cerebral metabolic rate of oxygen and ATP demand. Uncontrolled seizure activity (status epilepticus) results in mitochondrial exhaustion and ATP depletion, which potentially generate energy mismatch and neuronal loss. Many cells can adapt to increased energy demand by increasing metabolic capacities. However, acute metabolic adaptation during epileptic activity and its relationship to chronic epilepsy remains poorly understood. We elicited seizure-like events (SLEs) in an in vitro model of status epilepticus for eight hours. Electrophysiological recording and tissue oxygen partial pressure recordings were performed. After eight hours of ongoing SLEs, we used proteomics-based kinetic modeling to evaluate changes in metabolic capacities. We compared our findings regarding acute metabolic adaptation to published proteomic and transcriptomic data from chronic epilepsy patients. Epileptic tissue acutely responded to uninterrupted SLEs by upregulating ATP production capacity. This was achieved by a coordinated increase in the abundance of proteins from the respiratory chain and oxidative phosphorylation system. In contrast, chronic epileptic tissue shows a 25–40% decrease in ATP production capacity. In summary, our study reveals that epilepsy leads to dynamic metabolic changes. Acute epileptic activity boosts ATP production, while chronic epilepsy reduces it significantly. Full article

(This article belongs to the Special Issue Molecular and Cellular Mechanisms of Epilepsy—3rd Edition)

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Figure 1
Epilepsy-related changes in cerebral metabolic rate of oxygen (CMRO2). (A) Graphical representation of the experimental protocol. Cortical slices from one Wistar rat were randomly separated into two groups (control slices maintained for at least 8 h in normal aCSF and slices maintained for the same amount of time in Mg2+-free aCSF). (B) Slices maintained in normal aCSF displayed spontaneous activity (left, blue background, field potential (f.p.) trace on the bottom in black and extracellular potassium ([K+]o) on top in blue) and slices treated with Mg2+-free aCSF displayed seizure-like events (SLEs, right, red background, field potential trace on the bottom in black and extracellular potassium on top in blue). Scales represent 1 mM in the [K+]o trace, 1 mV in the field potential trace, and 10 s, respectively. (C) Measurement of tissue O2 at different depths (in µm) in control and treated slices. The ptiO2 profiles show increased oxygen demand in slices with SLEs (right, red background) compared to control slices (left, blue background). In slices with SLEs, pO2 measurements display seizure-dependent increases in oxygen consumption, thus basal and SLE-associated CMRO2 were calculated (upper and lower red fit line, respectively). Inlet in (C): statistical comparison between the control slices and slices with SLE (colors correspond to the fit lines: blue = control, red = SLE). CMRO2 was significantly increased in epileptic tissue. * p-value < 0.05. Full article ">Figure 2
Biostatistics of the global proteome. (A) Volcano plot showing the log2 fold changes of all identified proteins (control/epilepsy) concerning the p-values. The left side corresponds to proteins that are downregulated, while the right side corresponds to proteins that are upregulated. Red/blue dots show significantly changed proteins (p-value < 0.05 and |log2-fold change| > 1/<−1). Only 0.5% of all proteins were significantly differently regulated by that definition. (B) Unbiased clustering of the protein abundances of the different samples. The two main clusters each contain four out of five clusters of one group (epilepsy or control), but cluster separation is small. The colors represent normalized values (z-scores) with blue indicating values below the mean and red above the mean. Full article ">Figure 3
Energy production capacity for control and epilepsy group. (A) Maximal ATP production capacity; (B) corresponding maximal O2 consumption rate; (C) corresponding ATP/O2 ratio; black dots show values for individual samples. The control group is depicted in blue; the epilepsy group is in orange. The center lines represent the median, the boxes represent the interquartile range, and the whiskers are defined by values within 1.5 times the interquartile range. Black bars indicate significant differences between groups with a p-value < 0.05 as assessed with a two-sided t-test. (D) Proton utilization for the different mitochondrial membrane processes given as currents. The size of the different colored bars indicates the magnitude of the different processes (light blue: calcium pumping; green: FOF1-ATPase; purple: phosphate transport; yellow: potassium pumping; red: sodium pumping; dark blue: proton leakage). (E) The mean relative share of the different processes on total proton flux for the two groups. Full article ">Figure 4
Exemplary relationship between abundance of respiratory chain proteins and maximal ATP production capacity. (A) Correlation between Ndufa9, a subunit of complex I, and maximal ATP production capacity; blue dots show abundance levels in individual samples of the control, and orange dots in the epilepsy group (p-value = 0.00006 according to the linear regression model with n = 10). Red dotted lines indicate 95% confidence intervals of the linear model. (B) Distribution of Ndufa9 abundance in the control and epilepsy group. Corresponding p-values = 0.012, based on two-sided t-test. The center lines represent the median, the boxes represent the interquartile range, and the whiskers are defined by values within 1.5 times the interquartile range. The black bar indicates a significant difference between groups with a p-value < 0.05 as assessed with a two-sided t-test. Full article ">Figure 5
Energy production capacity for control and epilepsy groups in a pilocarpine rat model [<a href="#B12-ijms-25-09640" class="html-bibr">12</a>]. (A) Maximal ATP production capacity; (B) corresponding maximal O2 consumption rate; (C) corresponding ATP/O2 ratio; black dots show values for individual samples. The control group is depicted in blue; the epilepsy group is depicted in orange. The center lines represent the median, the boxes represent the interquartile range, and the whiskers are defined by values within 1.5 times the interquartile range. Red bars indicate significant differences between groups with a p-value < 0.001 as assessed with a two-sided t-test. (D) Proton utilization for the different mitochondrial membrane processes given as currents. The size of the different colored bars indicates the magnitude of the different processes (light blue: calcium pumping; green: FOF1-ATPase; purple: phosphate transport; yellow: potassium pumping; red: sodium pumping; dark blue: proton leakage). (E) The mean relative share of the different processes on total proton flux for the two groups. Full article ">Figure 6
Metabolic alterations in patients with temporal lobe epilepsy (TLE) [<a href="#B13-ijms-25-09640" class="html-bibr">13</a>]. (A) Maximal ATP production capacity. The control group is depicted in blue, epilepsy group in orange. (B) Mean glucose utilization and lactate production rates are decreased in the epilepsy group vs. the control group. Positive values correspond to uptake rates, while negative values depict release rates. The values for the individual samples are given in <a href="#app1-ijms-25-09640" class="html-app">Supplementary Figure S4</a>A. (C) Mean mitochondrial proton utilization for control and epilepsy groups. The size of the different colored bars indicates the magnitude of the different processes (light blue: calcium pumping; green: FOF1-ATPase; purple: phosphate transport; yellow: potassium pumping; red: sodium pumping; dark blue: proton leakage). The values for the individual samples are given in <a href="#app1-ijms-25-09640" class="html-app">Supplementary Figure S4</a>B. (D,E) Example of a functional protein significantly associated with ATP production capacity. AT5F1, a subunit of ATP synthase, is significantly associated with ATP production capacity over all samples (p-value < 0.01 via linear regression) and is reduced in TLE. The values for the individual samples are given in <a href="#app1-ijms-25-09640" class="html-app">Table S3</a>. Full article ">Figure 7
Metabolic alterations in human epileptic tissue [<a href="#B14-ijms-25-09640" class="html-bibr">14</a>]. (A) Maximal glucose uptake; (B) maximal ATP production capacity; (C) maximal oxygen consumption rate; and (D) ATP/O2 ratio at maximal ATP production rate. The healthy group is depicted in blue, and the epilepsy group is in orange. Black and red crossbars indicate significant differences between groups with a p-value of <0.05 and <0.01, respectively, as assessed with a two-sided t-test. (E) The mean glucose utilization and lactate production in control and epilepsy groups at maximal ATP production. Blue bars represent the mean glucose uptake rate in ATP equivalents in each group, while red bars represent lactate efflux in ATP equivalents in each group. The values for the individual samples are given in <a href="#app1-ijms-25-09640" class="html-app">Supplementary Figure S5</a>A. (F) The mean mitochondrial proton utilization for healthy and epilepsy groups at maximal ATP production rate. The size of the different colored bars indicates the magnitude of the different processes (light blue: calcium pumping; green: FOF1-ATPase; purple: phosphate transport; yellow: potassium pumping; red: sodium pumping; dark blue: proton leakage). The values for the individual samples are given in <a href="#app1-ijms-25-09640" class="html-app">Supplementary Figure S5</a>B. Full article ">

21 pages, 6982 KiB

Open AccessArticle

Morphological and Functional Alterations in the CA1 Pyramidal Neurons of the Rat Hippocampus in the Chronic Phase of the Lithium–Pilocarpine Model of Epilepsy

by Tatyana Y. Postnikova, Georgy P. Diespirov, Sergey L. Malkin, Alexander S. Chernyshev, Elizaveta N. Vylekzhanina and Aleksey V. Zaitsev

Int. J. Mol. Sci. 2024, 25(14), 7568; https://doi.org/10.3390/ijms25147568 - 10 Jul 2024

Viewed by 1308

Abstract

Epilepsy is known to cause alterations in neural networks. However, many details of these changes remain poorly understood. The objective of this study was to investigate changes in the properties of hippocampal CA1 pyramidal neurons and their synaptic inputs in a rat lithium–pilocarpine model of epilepsy. In the chronic phase of the model, we found a marked loss of pyramidal neurons in the CA1 area. However, the membrane properties of the neurons remained essentially unaltered. The results of the electrophysiological and morphological studies indicate that the direct pathway from the entorhinal cortex to CA1 neurons is reinforced in epileptic animals, whereas the inputs to them from CA3 are either unaltered or even diminished. In particular, the dendritic spine density in the str. lacunosum moleculare, where the direct pathway from the entorhinal cortex terminates, was found to be 2.5 times higher in epileptic rats than in control rats. Furthermore, the summation of responses upon stimulation of the temporoammonic pathway was enhanced by approximately twofold in epileptic rats. This enhancement is believed to be a significant contributing factor to the heightened epileptic activity observed in the entorhinal cortex of epileptic rats using an ex vivo 4-aminopyridine model. Full article

(This article belongs to the Special Issue Molecular and Cellular Mechanisms of Epilepsy—3rd Edition)

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19 pages, 2068 KiB

Open AccessArticle

by Flora Rider, Alexander Turchinets, Tatyana Druzhkova, Georgii Kustov, Alla Guekht and Natalia Gulyaeva

Int. J. Mol. Sci. 2024, 25(13), 7387; https://doi.org/10.3390/ijms25137387 - 5 Jul 2024

Viewed by 1466

Abstract

The hypothalamic–pituitary–adrenal axis is known to be involved in the pathogenesis of epilepsy and psychiatric disorders. Epileptic seizures (ESs) and psychogenic non-epileptic seizures (PNESs) are frequently differentially misdiagnosed. This study aimed to evaluate changes in serum cortisol and prolactin levels after ESs and PNESs as possible differential diagnostic biomarkers. Patients over 18 years with ESs (n = 29) and PNESs with motor manifestations (n = 45), captured on video-EEG monitoring, were included. Serum cortisol and prolactin levels as well as hemograms were assessed in blood samples taken at admission, during the first hour after the seizure, and after 6, 12, and 24 h. Cortisol and prolactine response were evident in the ES group (but not the PNES group) as an acute significant increase within the first hour after seizure. The occurrence of seizures in patients with ESs and PNESs demonstrated different circadian patterns. ROC analysis confirmed the accuracy of discrimination between paroxysmal events based on cortisol response: the AUC equals 0.865, with a prediction accuracy at the cutoff point of 376.5 nmol/L 0.811 (sensitivity 86.7%, specificity 72.4%). Thus, assessments of acute serum cortisol response to a paroxysmal event may be regarded as a simple, fast, and minimally invasive laboratory test contributing to differential diagnosis of ESs and PNESs. Full article

(This article belongs to the Special Issue Molecular and Cellular Mechanisms of Epilepsy—3rd Edition)

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Figure 1

Figure 1
Scatter plots showing the distribution of basic cortisol, prolactin, and lymphocyte levels in patients with epileptic seizures (ES, n = 29) and psychogenic non-epileptic seizures (PNES, n = 45). The colored line represents the mean. The difference between the baseline levels of lymphocytes in patients with ESs and PNESs is statistically significant (p = 0.01, Mann–Whitney U-test). Full article ">Figure 2
Frequency distribution of seizure occurrence time in groups with epileptic seizures (ESs) and psychogenic non-epileptic seizures (PNESs). (A) Distribution of the episodes by periods of the day: 1—morning, 2—day, 3—evening–night. PNESs were significantly skewed towards the evening–night time group (p = 0.004, 3 × 2 χ2 test). (B,C) Distribution by hours during the day in the epileptic seizures ES (B) and PNES (C) groups. The occurrence rate of seizures at different periods of the day for ESs and PNESs, respectively, were as follows: morning, 13 and 5; day, 5 and 16; evening–night, 11 and 24. Full article ">Figure 3
Changes in serum cortisol (A), prolactin (B), and lymphocyte (C) levels after a paroxysmal episode. Green symbols represent psychogenic non-epileptic seizures (PNESs), purple symbols represent epileptic seizures (ESs). M ± SD are presented. There are statistically significant differences in cortisol (A) and prolactin (B) levels between the two groups within the first hour after the seizure (p < 0.001, Tukey’s test). Within one hour following an ES, a transient increase in the number of lymphocytes occurs, as compared to baseline levels (C). The lymphocyte count after ES returns to baseline by the 6 h time point where it is lower than the lymphocyte count in the PNES group (p = 0.03, Tukey’s test). Full article ">Figure 4
The response of serum cortisol to epileptic seizures (ESs) or psychogenic non-epileptic seizures (PNESs) depending on the time of paroxysmal event onset: morning (A), day (B), evening–night (C). Green symbols represent psychogenic non-epileptic seizures (PNESs), purple symbols represent epileptic seizures (ESs). Points represent the mean values, and vertical bars represent standard deviations. The circadian fluctuations in cortisol levels were attenuated in both groups; however, an acute increase in cortisol levels during the first hour following the seizure was revealed in the ES group. Full article ">Figure 5
Correlations of serum cortisol level and prolactin level (A), and cortisol level and lymphocyte count (B) during the acute period after seizures in patients with epileptic seizures (ESs), assessed by the Spearman method. The solid line represents the best approximation, the dashed lines represent the 95% confidence interval. Yellow symbols, morning seizures; green symbols, daytime seizures; purple symbols, evening–night seizures. Full article ">Figure 6
ROC analysis of the serum cortisol levels during the first hour after the seizure. Full article ">

12 pages, 1749 KiB

Open AccessArticle

Matrix Metalloproteinase-9 Contributes to Epilepsy Development after Ischemic Stroke in Mice

by Barbara Pijet, Agnieszka Kostrzewska-Księzyk, Maja Pijet-Kucicka and Leszek Kaczmarek

Int. J. Mol. Sci. 2024, 25(2), 896; https://doi.org/10.3390/ijms25020896 - 11 Jan 2024

Cited by 2 | Viewed by 1428

Abstract

Epilepsy, a neurological disorder affecting over 50 million individuals globally, is characterized by an enduring predisposition and diverse consequences, both neurobiological and social. Acquired epilepsy, constituting 30% of cases, often results from brain-damaging injuries like ischemic stroke. With one third of epilepsy cases being resistant to existing drugs and without any preventive therapeutics for epileptogenesis, identifying anti-epileptogenic targets is crucial. Stroke being a leading cause of acquired epilepsy, particularly in the elderly, prompts the need for understanding post-stroke epileptogenesis. Despite the challenges in studying stroke-evoked epilepsy in rodents due to poor long-term survival rates, in this presented study the use of an animal care protocol allowed for comprehensive investigation. We highlight the role of matrix metalloproteinase-9 (MMP-9) in post-stroke epileptogenesis, emphasizing MMP-9 involvement in mouse models and its potential as a therapeutic target. Using a focal Middle Cerebral Artery occlusion model, this study demonstrates MMP-9 activation following ischemia, influencing susceptibility to seizures. MMP-9 knockout reduces epileptic features, while overexpression exacerbates them. The findings show that MMP-9 is a key player in post-stroke epileptogenesis, presenting opportunities for future therapies and expanding our understanding of acquired epilepsy. Full article

(This article belongs to the Special Issue Molecular and Cellular Mechanisms of Epilepsy—3rd Edition)

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Figure 1

Figure 1
MCAO model and experimental design. (A)—Schematic presentation of brain arterial physiology and Middle Cerebral Artery (MCA) occlusion site. Route of the MCAO insertion proceeds from the Common Carotid Artery (CCA) to the occlusion area indicated in grey. The surgery area is located at the bottom of the figure (dotted line). (B)—Representative laser Doppler flow; a sharp reduction in cortical blood flow (around 80%) after filament insertion to Internal Carotid Artery (ICA), which occludes the MCA. The occlusion is sustained for the period of 60 min. Infracted area (in white) stained with TTC 24 h after surgery. (C)—representative TTC staining sections 24 h after occlusion; (D)—Study design; animal condition after surgery was monitored within the first 30 days after ischemia; cortical and hippocampal electrodes were implanted 10 weeks after MCAO; PTZ-threshold test with subthreshold dose of PTZ (30 mg/kg b.w.) was performed 3 months postMCAO (1 h vEEG monitoring). Full article ">Figure 2
Cerebral ischemia increases MMP-9 activity in ipsi- and contralateral hemisphere. (A)—Time-dependent MMP-9 activity in the brain cortex and the hippocampus after MCAO; gel zymography from ipsi- and contralateral cortex (left panel), and the hippocampus (right panel) performed 10, 30, 60 min, 2, 6 h, 7, 14, 30, 60 and 90 days post-MCAO. MCAO mice after focal Middle Cerebral Occlusion model; sham mice (without artery occlusion). Pictures show representative zymograms. (B)—Statistical analysis from MMP-9 opitcal density was performed from each time point group (contained 3 MCAO animals and 3 shams; MMP-9 level measured for each sample separately). Data are presented as the mean ± SEM. Statistical analysis was carried out using One-way ANOVA followed by Tuckey post hoc test. **** p < 0.0001; data expressed as mean values ± SEM. Full article ">Figure 3
MMP-9 overexpression increases while MMP-9 deficiency diminishes neuronal excitability affected by ischemic stroke. Experiment with use of sub-threshold dose of pentylenetetrazol (PTZ-threshold test) performed 12 weeks after cerebral ischemia. (A)—scheme of skull/hippocampal electrodes placement: 2x recording electrodes above the left/right prefrontal cortex, reference/grounding electrodes over the cerebellum, hippocampal electrode position: AP—2.0 mm; ML +1.3 mm; DV −1.7 mm according the bregma; Tables (B,E) describing the latency time to 1st epileptiform spike (seconds), latency time to the 1st electrographic seizures (seconds) number of epileptiform spikes during 60 min after PTZ injection, % of animals with seizure electographic seizures (%) and PTZ-induced mortality (%); (B–D)—effect of lack of MMP-9 on neuronal excitability of the animals after ischemic stroke in PTZ-threshold test; (E–G)—effect of MMP-9 overexpression on neuronal excitability of the animals after ischemic stroke in PTZ-threshold test. Black asterisks indicate statistical significance between the MCAO and sham groups, while red asterisks indicate statistical difference between genotypes. Number of animals in MCAO groups was 9–10, while in sham groups was 5–10. Statistical analysis was carried out using One-way ANOVA followed by Tuckey multiple comparisons post-hoc test * p < 0.05; ** p < 0.01; *** p < 0.001 and **** p < 0.0001; ns—not significant; data are expressed as mean values ± SEM. Full article ">

Review

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31 pages, 895 KiB

Open AccessReview

Adeno-Associated Viral Vectors in the Treatment of Epilepsy

by Aysilu I. Mullagulova, Elena E. Timechko, Valeriya V. Solovyeva, Alexey M. Yakimov, Ahmad Ibrahim, Diana D. Dmitrenko, Albert A. Sufianov, Galina Z. Sufianova and Albert A. Rizvanov

Int. J. Mol. Sci. 2024, 25(22), 12081; https://doi.org/10.3390/ijms252212081 - 11 Nov 2024

Viewed by 1156

Abstract

Epilepsy is a brain disorder characterized by a persistent predisposition to epileptic seizures. With various etiologies of epilepsy, a significant proportion of patients develop pharmacoresistance to antiepileptic drugs, which necessitates the search for new therapeutic methods, in particular, using gene therapy. This review discusses the use of adeno-associated viral (AAV) vectors in gene therapy for epilepsy, emphasizing their advantages, such as high efficiency of neuronal tissue transduction and low immunogenicity/cytotoxicity. AAV vectors provide the possibility of personalized therapy due to the diversity of serotypes and genomic constructs, which allows for increasing the specificity and effectiveness of treatment. Promising orientations include the modulation of the expression of neuropeptides, ion channels, transcription, and neurotrophic factors, as well as the use of antisense oligonucleotides to regulate seizure activity, which can reduce the severity of epileptic disorders. This review summarizes the current advances in the use of AAV vectors for the treatment of epilepsy of various etiologies, demonstrating the significant potential of AAV vectors for the development of personalized and more effective approaches to reducing seizure activity and improving patient prognosis. Full article

(This article belongs to the Special Issue Molecular and Cellular Mechanisms of Epilepsy—3rd Edition)

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40 pages, 2520 KiB

Open AccessReview

Virus-Induced Epilepsy vs. Epilepsy Patients Acquiring Viral Infection: Unravelling the Complex Relationship for Precision Treatment

by Bárbara Costa and Nuno Vale

Int. J. Mol. Sci. 2024, 25(7), 3730; https://doi.org/10.3390/ijms25073730 - 27 Mar 2024

Cited by 4 | Viewed by 4589

Abstract

The intricate relationship between viruses and epilepsy involves a bidirectional interaction. Certain viruses can induce epilepsy by infecting the brain, leading to inflammation, damage, or abnormal electrical activity. Conversely, epilepsy patients may be more susceptible to viral infections due to factors, such as compromised immune systems, anticonvulsant drugs, or surgical interventions. Neuroinflammation, a common factor in both scenarios, exhibits onset, duration, intensity, and consequence variations. It can modulate epileptogenesis, increase seizure susceptibility, and impact anticonvulsant drug pharmacokinetics, immune system function, and brain physiology. Viral infections significantly impact the clinical management of epilepsy patients, necessitating a multidisciplinary approach encompassing diagnosis, prevention, and treatment of both conditions. We delved into the dual dynamics of viruses inducing epilepsy and epilepsy patients acquiring viruses, examining the unique features of each case. For virus-induced epilepsy, we specify virus types, elucidate mechanisms of epilepsy induction, emphasize neuroinflammation’s impact, and analyze its effects on anticonvulsant drug pharmacokinetics. Conversely, in epilepsy patients acquiring viruses, we detail the acquired virus, its interaction with existing epilepsy, neuroinflammation effects, and changes in anticonvulsant drug pharmacokinetics. Understanding this interplay advances precision therapies for epilepsy during viral infections, providing mechanistic insights, identifying biomarkers and therapeutic targets, and supporting optimized dosing regimens. However, further studies are crucial to validate tools, discover new biomarkers and therapeutic targets, and evaluate targeted therapy safety and efficacy in diverse epilepsy and viral infection scenarios. Full article

(This article belongs to the Special Issue Molecular and Cellular Mechanisms of Epilepsy—3rd Edition)

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Figure 1

Figure 1
Illustrative image of the interplay of viral infection, epilepsy, neuroinflammation and treatment management of disease. Neuroinflammation can be induced under several conditions, including viral infections. The main immune cells in the brain, microglia, play a pivotal role in neuroinflammation by responding to invading pathogens (viral DNA/RNA) through toll-like receptors (TLRs). Chronic activation of microglia caused by sustained viral infection leads to the persistent release of pro-inflammatory molecules. This is different from their beneficial functions under physiological conditions. The release of these pro-inflammatory factors, including tumor necrosis factor-α (TNFα) and interleukin-1β (IL-1β), free radicals such as nitric oxide (NO) and superoxide, is initially a defensive strategy of the immune system. However, sustained exposure of neurons to these inflammatory factors can result in neuronal dysfunction and cell degeneration, contributing to the pathogenesis of aging-related neurodegenerative disease. Viral infection in the CNS is a common cause of seizures and epilepsy. Sustained exposure of neurons to these inflammatory conditions can result in neuronal dysfunction and cell degeneration, contributing to the pathogenesis of several neurological disorders. Neuroprotection is a therapeutic strategy aimed at preventing or reducing damage to the nervous system caused by various pathological conditions, including neuroinflammation. Anti-inflammatory drugs can be used to treat CNS-related diseases by reducing the release of pro-inflammatory molecules, including TNFα and IL-1β, and free radicals such as NO and superoxide, which can contribute to neuronal dysfunction and cell degeneration. Adapted from BioRender.com, accessed on 7 December 2023. Full article ">Figure 2
Schematic representation of the treatment options for viral infection and epilepsy. Anticonvulsant drugs are the most common treatment for epilepsy. Some patients may require surgery to remove a small part of the brain that is causing the seizures, or a small electrical device may be used inside the body to help control seizures. A special diet (ketogenic diet) may help control seizures. Antiviral drugs are available to treat some viral infections. Some medications, such as interferons and cytokines, even mimic the body’s natural immune system stimulation signals. Vaccines are usually given to prevent infection, but some can also be used to treat people who have recently been infected. Both types of conditions often require a long-term treatment approach and may require adjustments in treatment over time. Treatments for both conditions often focus on managing symptoms and improving the patient’s quality of life. Adapted from BioRender.com, accessed on 7 December 2023. Full article ">Figure 3
Aspects considered for the interplay of viral infection, neuroinflammation, and anticonvulsant drug pharmacokinetics in precision therapy in epilepsy. Full article ">

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