Recent Developments in Diagnosis of Epilepsy: Scope of MicroRNA and Technological Advancements

Circulating miRNAs as Novel Clinical Biomarkers in Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) represents the most common form of refractory focal epilepsy. The identification of innovative clinical biomarkers capable of categorizing patients with TLE, allowing for improved treatment and outcomes, still represents an unmet need. Circulating microRNAs (c-miRNAs) are short non-coding RNAs detectable in body fluids, which play crucial roles in the regulation of gene expression. Their characteristics, including extracellular stability, detectability through non-invasive methods, and responsiveness to pathological changes and/or therapeutic interventions, make them promising candidate biomarkers in various disease settings. Recent research has investigated c-miRNAs in various bodily fluids, including serum, plasma, and cerebrospinal fluid, of TLE patients. Despite some discrepancies in methodologies, cohort composition, and normalization strategies, a common dysregulated signature of c-miRNAs has emerged across different studies, providing the basis for using c-miRNAs as novel biomarkers for TLE patient management.

Advances in understanding the pathogenesis of epilepsy: Unraveling the molecular mechanisms: A cross-sectional study

Introduction

Epilepsy is characterized by having two or more unprovoked seizures. Understanding the pathogenesis of epilepsy, requires deep investigation into the molecular mechanisms. This helps develop diagnostic techniques, treatments, and pharmacotherapy. It also enhances precision medicine and individualized treatment processes. This article reviews all the molecular mechanisms predisposing to epileptogenesis, presents the current diagnostic techniques and drug therapy, and suggests future perspectives in treating Epilepsy in a more comprehensive and holistic approach.

Methodology

Four authors searched keywords concerning epilepsy at a molecular level, Epilepsy diagnostic techniques and technologies, and antiepileptic drug therapy and precision medicine. Separate search strategies were conducted for each concern and retrieved articles were reviewed for relevant results.

Results

The traditional diagnostic techniques for Epilepsy and its pathogenesis are insufficient in highlighting dynamic brain changes. For this, emerging technologies including genetic sequencing and profiling, and functional neuroimaging techniques are prevailing. Concerning treatment, the current approach focuses on managing symptoms and stopping seizures using antiseizure medications. However, their usage is limited by developing resistance to such drugs. Some therapies show promise, although most antiseizure drugs do not prevent epilepsy.

Discussion

Understanding epileptogenesis at a molecular and genetic level aids in developing new antiepileptic pharmacotherapy. The aim is to develop therapies that could prevent seizures or modify disease course, decreasing the severity and avoiding drug resistance. Gene therapy and precision medicine are promising but applications are limited due to the heterogeneity in studying the Epileptic brain, dynamically. The dynamic investigation of the epileptic brain with its comorbidities works hand-in-hand with precision medicine, in developing personalized treatment plans.

Automatic epileptic seizure detection based on persistent homology

Epilepsy is a prevalent brain disease, which is quite difficult-to-treat or cure. This study developed a novel automatic seizure detection method based on the persistent homology method. In this study, a Vietoris-Rips (VR) complex filtration model was constructed based on the EEG data. And the persistent homology method was applied to calculate the VR complex filtration barcodes to describe the topological changes of EEG recordings. Afterward, the barcodes as the topological characteristics of EEG signals were fed into the GoogLeNet for classification. The persistent homology is applicable for multi-channel EEG data analysis, where the global topological information is calculated and the features are extracted by considering the multi-channel EEG data as a whole, without the multiple calculations or the post-stitching. Three databases were used to evaluate the proposed approach and the results showed that the approach had high performances in the epilepsy detection. The results obtained from the CHB-MIT Database recordings revealed that the proposed approach can achieve a segment-based averaged accuracy, sensitivity and specificity values of 97.05%, 96.71% and 97.38%, and achieve an event-based averaged sensitivity value of 100% with 1.22 s average detection latency. In addition, on the Siena Scalp Database, the proposed method yields averaged accuracy, sensitivity and specificity values of 96.42%, 95.23% and 97.6%. Multiple tasks of the Bonn Database also showed achieved accuracy of 99.55%, 98.63%, 98.28% and 97.68%, respectively. The experimental results on these three EEG databases illustrate the efficiency and robustness of our approach for automatic detection of epileptic seizure.

Improving the generalization of patient non-specific model for epileptic seizure detection

Epilepsy is the second most common neurological disorder characterized by recurrent and unpredictable seizures. Accurate seizure detection is important for diagnosis and treatment of epilepsy. Many researches achieved good performance on patient-specific seizure detection. However, they were tailored to each specific individual which are less applicable clinically than the patient non-specific detection, which lacked good performance. Despite several decades of research on automatic seizure detection, seizure detection is currently still based on visual inspection of video-EEG (Electroencephalogram) in clinical setting. It is time consuming and prone to human error and subjectivity. This study aims to improve patient non-specific seizure detection to assist neurologist with efficient and objective evaluation of epileptic EEG. The clinical data used was from the open access Siena Scalp EEG Database which consists of 14 patients. First the data were pre-processed to remove artifacts and noises. Second the features from time domain, frequency domain and entropy were extracted from each channel and then concatenated into a feature vector. Finally, a machine learning approach based on random forest was employed for seizure detection with leave-one-patient-out cross-validation scheme. Automatic seizure detection was carried out with the trained model. The study achieved a specificity of 99.38%, sensitivity of 81.43% and 3.61 FP/h (False Positives per hour), which outperformed some other patient non-specific detectors found in literature. The findings from the study shows the possibility of clinical application of automatic seizure detection and indicate that further work should focus on dealing with reducing false positives.

EpilepsyNet: Novel automated detection of epilepsy using transformer model with EEG signals from 121 patient population

BACKGROUND

Epilepsy is one of the most common neurological conditions globally, and the fourth most common in the United States. Recurrent non-provoked seizures characterize it and have huge impacts on the quality of life and financial impacts for affected individuals. A rapid and accurate diagnosis is essential in order to instigate and monitor optimal treatments. There is also a compelling need for the accurate interpretation of epilepsy due to the current scarcity in neurologist diagnosticians and a global inequity in access and outcomes. Furthermore, the existing clinical and traditional machine learning diagnostic methods exhibit limitations, warranting the need to create an automated system using deep learning model for epilepsy detection and monitoring using a huge database.

METHOD

The EEG signals from 35 channels were used to train the deep learning-based transformer model named (EpilepsyNet). For each training iteration, 1-min-long data were randomly sampled from each participant. Thereafter, each 5-s epoch was mapped to a matrix using the Pearson Correlation Coefficient (PCC), such that the bottom part of the triangle was discarded and only the upper triangle of the matrix was vectorized as input data. PCC is a reliable method used to measure the statistical relationship between two variables. Based on the 5 s of data, single embedding was performed thereafter to generate a 1-dimensional array of signals. In the final stage, a positional encoding with learnable parameters was added to each correlation coefficient's embedding before being fed to the developed EpilepsyNet as input data to epilepsy EEG signals. The ten-fold cross-validation technique was used to generate the model.

RESULTS

Our transformer-based model (EpilepsyNet) yielded high classification accuracy, sensitivity, specificity and positive predictive values of 85%, 82%, 87%, and 82%, respectively.

CONCLUSION

The proposed method is both accurate and robust since ten-fold cross-validation was employed to evaluate the performance of the model. Compared to the deep models used in existing studies for epilepsy diagnosis, our proposed method is simple and less computationally intensive. This is the earliest study to have uniquely employed the positional encoding with learnable parameters to each correlation coefficient's embedding together with the deep transformer model, using a huge database of 121 participants for epilepsy detection. With the training and validation of the model using a larger dataset, the same study approach can be extended for the detection of other neurological conditions, with a transformative impact on neurological diagnostics worldwide.

Usefulness of combined diffusion tensor imaging, arterial spin labelling and spectroscopic interictal analysis in refractory epilepsy

Background

Epilepsy is a common neurological disorder especially in pediatric population. Patients with non-lesional epilepsy have normal conventional MRI findings. In the recent era of advances in neuroimaging studies, diffusion tensor imaging (DTI) and MR spectroscopy (MRS) can assess the tissue microstructure. Also, arterial spin labeling (ASL) is a noninvasive modality that evaluates cerebral blood flow. Multiple recent publications aimed at use of single or two new modalities in lateralization of epileptogenic focus in epilepsy, but the current study aimed to evaluate the added value of combined (DTI, ASL and MRS) in vivo localization of interactable epilepsy with negative conventional MRI findings.

Results

This prospective case control study was carried out in the period from January 1st, 2022 to October 1st, 2022 after approval of local ethical committee in our institution. Written informed consent was obtained from patients and healthy volunteers who were enrolled in this study. The current study included 46 patients with temporal lobe epilepsy and 20 age- and sex-matched healthy volunteers as a control group. The mean age in the patient group was 22.3 ± 12.2 years, and in the control group, it was 23.8 ± 15.1 years. The highest area under the curve (AUC) was for spectroscopy (0.913), the difference in NAA/Cr showed sensitivity of 94.1% and a specificity of 90%, while NAA/Cho + Cr showed a sensitivity of 91.8% and a specificity of 88%, the difference in rCBF showed an AUC of 0.89, with a cutoff value of 3.815 had a sensitivity of 80.4% and a specificity of 85%. As regards DTI, the changes in DTI parameters show sensitivity of 79.6% and a specificity of 80% in lateralization of the epileptic focus. The difference in FA only showed an AUC of 0.86, with a cutoff value of 0.01 had a sensitivity of 77% and a specificity of 75% and the difference in MD only showed an AUC of 0.771, with a cutoff value of 0.545 had a sensitivity of 67.4% and a specificity of 70%. The diagnostic performance of MRS in terms of the AUC was significantly higher than ASL parameters (difference in NAA/Cr, p = 0.033 and difference in NAA/Cho + Cr, p = 0.044), and MD (p = 0.02). No other statistically significant differences were shown between the studied parameters. When the three methods were combined, all patients’ epileptogenic foci were correctly localized and lateralized.

Conclusions

Combining ASL, DTI and H-MRS provided excellent diagnostic performance in localization and lateralization of the epileptogenic focus. If this combination is not applicable in clinical practice, ASL could provide a considerably accurate and feasible method in this context. The present study supported the value of the new noninvasive MRI techniques in the elaboration of hidden brain pathology.

Unmet needs of people with epilepsy: A qualitative study exploring their journey from presentation to long-term management across five European countries

Introduction

Epilepsy is a neurological disease that can negatively impact a person's physical, psychological, social, and emotional well-being. The aim of this study was to provide insights into the experiences of people with epilepsy on polytherapy (i.e., people on a combination of two or more anti-seizure medications [ASMs]), with an emphasis on their emotional journey.

Methods

Market research was conducted with 40 people with epilepsy from France, Germany, Italy, Spain, and the United Kingdom. Semi-structured interviews were analyzed using both a content and framework analysis approach. A content analysis of participants' expressed emotions was used to illustrate the changes of emotions experienced by people with epilepsy from presentation through to monitoring and follow-up stages.

Results

In each stage of the journey, themes and subthemes were identified under the overarching headings: Stage 1: Presentation - Life is turned upside down; Stage 2: Diagnosis - Period of learning; Stage 3: Treatment - Aspirations and experimentation; and Stage 4: Monitoring and follow-up - Feeling "out on a limb". The research identified key unmet needs and opportunities for people with epilepsy to improve their subjective experiences at different stages of their disease journey, namely: (1) establish and promote support networks from presentation through to monitoring and follow-up stages; (2) accelerate pathway to diagnosis; (3) provide opportunities to discuss the diagnosis with patients; (4) clarify treatment-change guidelines for patients; and (5) develop a shared treatment decision-making/empowerment tool.

Discussion

The research findings and recommendations have the potential to drive change at an individual level, as well as at a healthcare level.

Ferulic acid inhibits catamenial epilepsy through modulation of female hormones

Approximately 40% of women with epilepsy experience perimenstrual seizure exacerbation, referred to as catamenial epilepsy. These seizures result from cyclic changes in circulating progesterone and estradiol levels and there is no effective treatment for this form of intractable epilepsy. We artificially increased progesterone levels and neurosteroid levels (pseudo-pregnancy) in adult Swiss albino female mice (19-23 g) by injecting them with pregnant mares' serum gonadotropin (5 IU s.c.), followed by human chorionic gonadotropin (5 IU s.c.) after 46 h. After this, ferulic acid (25, 50, 100 mg/kg i.p.) treatment was given for 10 days. During treatment, progesterone, estradiol, and corticosterone levels were estimated in blood on days 1, 5, and 10. Neurosteroid withdrawal was induced by finasteride (50 mg/kg, i.p.) on treatment day 9. Twenty-four hours after finasteride administration (day 10 of treatment), seizure susceptibility was evaluated with the sub-convulsant pentylenetetrazol (PTZ) dose (40 mg/kg i.p.). Four to six hours after PTZ, animals were assessed for depression like phenotypes using tail-suspension test (TST). Four to six hours following TST, animals were euthanized, and discrete brain parts (cortex and hippocampus) were separated for estimation of norepinephrine, serotonin, and dopamine as well as glutamic acid decarboxylase (GAD) enzyme activity. PMSG and HCG treatment elevated progesterone and estradiol levels, assessed on days 1, 5, and 10 causing a state of pseudo-pregnancy. Treatment with finasteride increased seizure susceptibility and depression-like characteristics possibly due to decreased progesterone and elevated estrogen levels coupled with decreased monoamine and elevated corticosterone levels. Ferulic acid treatment, on the other hand, significantly decreased seizure susceptibility and depression like behavior, possibly because of increased progesterone, restored estradiol, corticosterone, monoamines, and GAD enzyme activity. We concluded anticonvulsant effect of ferulic acid in a mouse model of catamenial epilepsy, evidenced by favourable seizure attenuation and curative effect on the circulating progesterone, estradiol, and corticosterone levels along with restorative effect on GAD enzyme activity and monoamine levels.

Neuronal nitric oxide synthase/reactive oxygen species pathway is involved in apoptosis and pyroptosis in epilepsy

Dysfunction of neuronal nitric oxide synthase contributes to neurotoxicity, which triggers cell death in various neuropathological diseases, including epilepsy. Studies have shown that inhibition of neuronal nitric oxide synthase activity increases the epilepsy threshold, that is, has an anticonvulsant effect. However, the exact role and potential mechanism of neuronal nitric oxide synthase in seizures are still unclear. In this study, we performed RNA sequencing, functional enrichment analysis, and weighted gene coexpression network analysis of the hippocampus of tremor rats, a rat model of genetic epilepsy. We found damaged hippocampal mitochondria and abnormal succinate dehydrogenase level and Na⁺-K⁺-ATPase activity. In addition, we used a pilocarpine-induced N2a cell model to mimic epileptic injury. After application of neuronal nitric oxide synthase inhibitor 7-nitroindazole, changes in malondialdehyde, lactate dehydrogenase and superoxide dismutase, which are associated with oxidative stress, were reversed, and the increase in reactive oxygen species level was reversed by 7-nitroindazole or reactive oxygen species inhibitor N-acetylcysteine. Application of 7-nitroindazole or N-acetylcysteine downregulated the expression of caspase-3 and cytochrome c and reversed the apoptosis of epileptic cells. Furthermore, 7-nitroindazole or N-acetylcysteine downregulated the abnormally high expression of NLRP3, gasdermin-D, interleukin-1β and interleukin-18. This indicated that 7-nitroindazole and N-acetylcysteine each reversed epileptic cell death. Taken together, our findings suggest that the neuronal nitric oxide synthase/reactive oxygen species pathway is involved in pyroptosis of epileptic cells, and inhibiting neuronal nitric oxide synthase activity or its induced oxidative stress may play a neuroprotective role in epilepsy.

Poly (ADP-ribose) polymerase: An Overview of Mechanistic Approaches and Therapeutic Opportunities in the Management of Stroke

Stroke is one of the leading causes of morbidity and mortality accompanied by blood supply loss to a particular brain area. Several mechanistic approaches such as inhibition of poly (ADP-ribose) polymerase, therapies against tissue thrombosis, and neutrophils lead to stroke's therapeutic intervention. Evidence obtained with the poly (ADP-ribose) polymerase (PARP) inhibition and animals having a deficiency of PARP enzymes; represented the role of PARP in cerebral stroke, ischemia/reperfusion, and neurotrauma. PARP is a nuclear enzyme superfamily with various isoforms, each with different structural domains and functions, and out of all, PARP-1 is the best-characterized member. It has been shown to perform multiple physiological as well as pathological processes, including its role in inflammation, oxidative stress, apoptosis, and mitochondrial dysfunction. The enzyme interacts with NF-κB, p53, and other transcriptional factors to regulate survival and cell death and modulates multiple downstream signaling pathways. Clinical trials have also been conducted using PARP inhibitors for numerous disorders and have shown positive results. However, additional information is yet to be established for the therapeutic intervention of PARP inhibitors in stroke. These agents' utilization appears to be challenging due to their unknown potential long-term side effects. PARP activity increased during ischemia, but its inhibition provided significant neuroprotection. Despite the increased interest in PARP as a pharmacological modulator for novel therapeutic therapies, the current review focused on stroke and poly ADP-ribosylation.

Current Status of Our Understanding for Brain Integrated Functions and its Energetics

Human/animal brain is a unique organ with substantially high metabolism but it contains no energy reserve that is the reason it requires continuous supply of O₂ and energy fluxes through CBF. The main source of energy remains glucose as the other biomolecules do not able to cross the blood-brain barrier. The speed of glucose metabolism is heterogeneous throughout the brain. One of the major flux consumption is Neuron-astrocyte cycling of glutamate and glutamine in glutamatergic neurons (approximately 80% of glucose metabolism in brain). The quantification of cellular glucose and other related substrate in resting, activated state can be analyzed through [¹⁸ F]FDG -positron-emission tomography (studying CMRglc) and [¹³ C/³¹P -MRS: for neuroenergetics & neurotransmitter cycling &³¹P-MRS: for energy induction & redox state). Merging basic in vitro studies with these techniques will help to develop new treatment paradigms for human brain diseased conditions.

Reconnoitering the transformative journey of minocycline from an antibiotic to an antiepileptic drug

Minocycline, a second-generation tetracycline antibiotic is being widely tested in animals as well as clinical settings for the management of multiple neurological disorders. The drug has shown to exert protective action in a multitude of neurological disorders including spinal-cord injury, stroke, multiple sclerosis, amyotrophic lateral sclerosis, Huntington's disease, and Parkinson's disease. Being highly lipophilic, minocycline easily penetrates the blood brain barrier and is claimed to have excellent oral absorption (~100% bioavailability). Minocycline possesses anti-inflammatory, immunomodulatory, and anti-apoptotic properties, thereby supporting its use in treating neurological disorders. The article henceforth reviews all the recent advances in the transformation of this antibiotic into a potential antiepileptic/antiepileptogenic agent. The article also gives an account of all the clinical trials undertaken till now validating the antiepileptic potential of minocycline. Based on the reported studies, minocycline seems to be an important molecule for treating epilepsy. However, the practical therapeutic implementations of this molecule require extensive mechanism-based in-vitro (cell culture) and in-vivo (animal models) studies followed by its testing in randomized, placebo controlled and double-blind clinical trials in large population as well as in different form of epilepsies.

A Multimodal MR Imaging Study of the Effect of Hippocampal Damage on Affective and Cognitive Functions in a Rat Model of Chronic Exposure to a Plateau Environment

Prolonged exposure to high altitudes above 2500 m above sea level (a.s.l.) can cause cognitive and behavioral dysfunctions. Herein, we sought to investigate the effects of chronic exposure to plateau hypoxia on the hippocampus in a rat model by using voxel-based morphometry, creatine chemical exchange saturation transfer (CrCEST) and dynamic contrast-enhanced MR imaging techniques. 58 healthy 4-week-old male rats were randomized into plateau hypoxia rats (H group) as the experimental group and plain rats (P group) as the control group. H group rats were transported from Chengdu (500 m a.s.l.), a city in a plateau located in southwestern China, to the Qinghai-Tibet Plateau (4250 m a.s.l.), Yushu, China, and then fed for 8 months there, while P group rats were fed in Chengdu (500 m a.s.l.), China. After 8 months of exposure to plateau hypoxia, open-field and elevated plus maze tests revealed that the anxiety-like behavior of the H group rats was more serious than that of the P group rats, and the Morris water maze test revealed impaired spatial memory function in the H group rats. Multimodal MR imaging analysis revealed a decreased volume of the regional gray matter, lower CrCEST contrast and higher transport coefficient Ktrans in the hippocampus compared with the P group rats. Further correlation analysis found associations of quantitative MRI parameters of the hippocampus with the behavioral performance of H group rats. In this study, we validated the viability of using noninvasive multimodal MR imaging techniques to evaluate the effects of chronic exposure to a plateau hypoxic environment on the hippocampus.