Metabolic Epilepsy

ALG13-Related Epilepsy: Current Insights and Future Research Directions

The ALG13 gene encodes a subunit of the uridine diphosphate-N-acetylglucosamine (UDP-GlcNAc) transferase enzyme, which plays a key role in the N-linked glycosylation pathway. This pathway involves the attachment of carbohydrate structures to asparagine (Asn) residues in proteins within the endoplasmic reticulum, by which N-glycosylated proteins produced participate a wide range of processes such as electrical gradients formation and neurotransmission. Mutations in the ALG13 gene have been identified as a causative factor for congenital disorders of glycosylation (CDG) and have been frequently associated with epilepsy in affected individuals. Several studies have demonstrated a strong correlation between abnormal N-glycosylation due to ALG13 deficiency and the onset of epilepsy. Despite these findings, the precise role of ALG13 in the pathogenesis of epilepsy remains unclear. This review provides a comprehensive overview of the current literature on ALG13-related disorders, with a focus on recent evidence regarding its role in epilepsy development and progression. Future research directions are also proposed to further elucidate the molecular mechanisms underlying this association.

Causal associations of ischemic stroke, metabolic factors, and related medications with epilepsy: a Mendelian randomization study

Background

Earlier researches have demonstrated that ischemic stroke, metabolic factors, and associated medications may influence the risk of epilepsy. Nevertheless, the causality between these elements and epilepsy remains inconclusive. This study aims to examine whether ischemic stroke, metabolic factors, and related medications affect the overall risk of epilepsy.

Methods

We used single nucleotide polymorphisms associated with ischemic stroke, hypothyroidism, hypertension, blood glucose levels, high cholesterol, serum 25-Hydroxyvitamin D levels, testosterone, HMG CoA reductase inhibitors, and beta-blocking agents as instrumental variables in a Mendelian randomization technique to investigate causality with epilepsy. Multiple sensitivity methods were performed to evaluate pleiotropy and heterogeneity.

Results

The IVW analysis revealed positive associations between ischemic stroke (OR = 1.29; p = 0.020), hypothyroidism (OR = 1.05; p = 0.048), high blood pressure (OR = 1.10; p = 0.028), high cholesterol (OR = 1.10; p = 0.024), HMG CoA reductase inhibitors (OR = 1.19; p = 0.003), beta-blocking agents (OR = 1.20; p = 0.006), and the risk of epilepsy. Conversely, blood glucose levels (OR = 0.79; p = 0.009), serum 25-Hydroxyvitamin D levels (OR = 0.75; p = 0.020), and testosterone (OR = 0.62; p = 0.019) exhibited negative associations with the risk of epilepsy. Sensitivity analyses confirmed the robustness of these findings (p > 0.05).

Conclusion

Our research suggests that ischemic stroke, hypothyroidism, high blood pressure, high cholesterol, HMG CoA reductase inhibitors, and beta-blockers may increase the risk of epilepsy, whereas serum 25-Hydroxyvitamin D levels and blood glucose levels may reduce the risk.

Transcriptional Signatures of a Dynamic Epilepsy Process Reveal Potential Immune Regulation

Epilepsy is a progression of development and advancement over time. However, the molecular features of epilepsy were poorly studied from a dynamic developmental perspective. We intend to investigate the key mechanisms in the process of epilepsy by exploring the roles of stage-specifically expressed genes. By using time-course transcriptomic data of epileptic samples, we first analyzed the molecular features of epilepsy in different stages and divided it into progression and remission stages based on their transcriptomic features. 34 stage-specifically expressed genes were then identified by the Tau index and verified in other epileptic datasets. These genes were then enriched for immune-related biological functions. Furthermore, we found that the level of immune infiltration and mechanisms at different stages were different, which may result from different types of immune cells playing leading roles in distinct stages. Our findings indicated an essential role of immune regulation as the potential mechanism of epilepsy development.

Identifying Metabolic Diseases That Precipitate Neonatal Seizures

Although a rare cause of neonatal seizures, inborn errors of metabolism (IEMs) remain an essential component of a comprehensive differential diagnosis for poorly controlled neonatal epilepsy. Diagnosing neonatal-onset metabolic conditions proves a difficult task for clinicians; however, routine state newborn screening panels now include many IEMs. Three in particular-pyridoxine-dependent epilepsy, maple syrup urine disease, and Zellweger spectrum disorders-are highly associated with neonatal epilepsy and neurocognitive injury yet are often misdiagnosed. As research surrounding biomarkers for these conditions is emerging and gene sequencing technologies are advancing, clinicians are beginning to better establish early identification strategies for these diseases. In this literature review, the authors aim to present clinicians with an innovative clinical guide highlighting IEMs associated with neonatal-onset seizures, with the goal of promoting quality care and safety.

Genetic causal role of body mass index in multiple neurological diseases

Body mass index (BMI) is a crucial health indicator for obesity. With the progression of socio-economic status and alterations in lifestyle, an increasing number of global populations are at risk of obesity. Given the complexity and severity of neurological diseases, early identification of risk factors is vital for the diagnosis and prognosis of such diseases. In this study, we employed Mendelian randomization (MR) analysis utilizing the most comprehensive genome-wide association study (GWAS) data to date. We selected single nucleotide polymorphisms (SNPs) that are unaffected by confounding factors and reverse causality as instrumental variables. These variables were used to evaluate the genetic and causal relationships between Body Mass Index (BMI) and various neurological diseases, including Parkinson's Disease (PD), Alzheimer's Disease (AD), Amyotrophic Lateral Sclerosis (ALS), Multiple Sclerosis (MS), Ischemic Stroke (IS), and Epilepsy (EP). The Inverse Variance Weighted (IVW) analysis indicated that there was no significant causal relationship between Body Mass Index (BMI) indicators and PD (P-value = 0.511), AD (P-value = 0.076), ALS (P-value = 0.641), EP (P-value = 0.380). However, a causal relationship was found between BMI indicators and MS (P-value = 0.035), and IS (P-value = 0.000), with the BMI index positively correlated with the risk of both diseases. The Cochran's Q test for MR-IVW showed no heterogeneity in the MR analysis results between the BMI index and the neurological diseases (P > 0.05). The Egger intercept test for pleiotropy revealed no horizontal pleiotropy detected in any of the neurological diseases studied (P > 0.05). It was found that there was no causal relationship between BMI and PD, AD, ALS, EP, and a genetic causal association with MS, and IS. Meanwhile, the increase in BMI can lead to a higher risk of MS and IS, which reveals the critical role of obesity as a risk factor for specific neurological diseases in the pathogenesis of the diseases.

Prevalence and risk factors of early postoperative seizures in patients with glioma: a systematic review and meta-analysis

Objective

This study aimed to explore the prevalence and risk factors of early postoperative seizures in patients with glioma through meta-analysis.

Methods

Case-control studies and cohort studies on the prevalence and risk factors of early postoperative seizures in glioma patients were retrieved from various databases including CNKI, Wanfang, VIP, PubMed, Embase, Cochrane Library, and Web of Science, and the retrieval deadline for the data was 1 April 2023. Stata15.0 was used to analyze the data.

Results

This review included 11 studies consisting of 488 patients with early postoperative seizures and 2,051 patients without early postoperative seizures. The research findings suggest that the prevalence of glioma is complicated by seizures (ES = 19%, 95% confidence interval [CI] [14%-25%]). The results also indicated a history of seizures (RR = 1.94, 95% CI [1.76, 2.14], P = 0.001), preoperative dyskinesia (RR = 3.13, 95% CI [1.20, 8.15], P = 0.02), frontal lobe tumor (RR = 1.45, 95% CI [1.16, 1.83], P = 0.001), pathological grade ≤2 (RR = 1.74, 95% CI [1.13, 2.67], P = 0.012), tumor≥ 3 cm (RR = 1.70, 95% CI [1.18, 2.45], P = 0.005), tumor resection (RR = 1.60, 95% CI [1.36, 1.88], P = 0.001), tumor edema ≥ 2 cm (RR = 1.77, 95% CI [1.40, 2.25], P = 0.001), and glioma cavity hemorrhage (RR=3.15, 95% CI [1.85, 5.37], P = 0.001). The multivariate analysis results showed that a history of seizures, dyskinesia, tumor ≥3 cm, peritumoral edema ≥2 cm, and glioma cavity hemorrhage were indicated as risk factors for glioma complicated with early postoperative seizures.

Significance

Based on the existing evidence, seizure history, dyskinesia, frontal lobe tumor, pathological grade ≤2, tumor ≥3 cm, partial tumor resection, edema around tumor ≥2 cm, and glioma cavity hemorrhage are indicated as risk factors for glioma complicated with early postoperative seizures.

The role of molecular chaperones in the mechanisms of epileptogenesis

Epilepsy is a group of neurological diseases which requires significant economic costs for the treatment and care of patients. The central point of epileptogenesis stems from the failure of synaptic signal transmission mechanisms, leading to excessive synchronous excitation of neurons and characteristic epileptic electroencephalogram activity, in typical cases being manifested as seizures and loss of consciousness. The causes of epilepsy are extremely diverse, which is one of the reasons for the complexity of selecting a treatment regimen for each individual case and the high frequency of pharmacoresistant cases. Therefore, the search for new drugs and methods of epilepsy treatment requires an advanced study of the molecular mechanisms of epileptogenesis. In this regard, the investigation of molecular chaperones as potential mediators of epileptogenesis seems promising because the chaperones are involved in the processing and regulation of the activity of many key proteins directly responsible for the generation of abnormal neuronal excitation in epilepsy. In this review, we try to systematize current data on the role of molecular chaperones in epileptogenesis and discuss the prospects for the use of chemical modulators of various chaperone groups' activity as promising antiepileptic drugs.

Charting the Progress of Epilepsy Classification: Navigating a Shifting Landscape

Epilepsy, a neurological disorder characterized by recurrent seizures, has witnessed a remarkable transformation in its classification paradigm, driven by advances in clinical understanding, neuroimaging, and molecular genetics. This narrative review navigates the dynamic landscape of epilepsy classification, offering insights into recent developments, challenges, and the promising horizon. Historically, epilepsy classification relied heavily on clinical observations, categorizing seizures based on their phenomenology and presumed etiology. However, the field has profoundly shifted from a symptom-based approach to a more refined, multidimensional system. One pivotal aspect of this evolution is the integration of neuroimaging techniques, particularly magnetic resonance imaging (MRI) and functional imaging modalities. These tools have unveiled the intricate neural networks implicated in epilepsy, facilitating the identification of distinct brain abnormalities and the categorization of epilepsy subtypes based on structural and functional findings. Furthermore, the role of genetics has become increasingly prominent in epilepsy classification. Genetic discoveries have not only unraveled the molecular underpinnings of various epileptic syndromes but have also provided valuable diagnostic and prognostic insights. This narrative review delves into the expanding realm of genetic testing and its impact on tailoring treatment strategies to individual patients. As the classification landscape evolves, there are accompanying challenges. The narrative review underscores the transformative potential of artificial intelligence and machine learning in epilepsy classification. These technologies hold promise in automating the analysis of complex neuroimaging and genetic data, offering enhanced accuracy and efficiency in epilepsy diagnosis and classification. In conclusion, navigating the shifting landscape of epilepsy classification is a journey marked by progress, complexity, and the prospect of improved patient care. We are charting a course toward more precise diagnoses and tailored treatments by embracing advanced neuroimaging, genetics, and innovative technologies. As the field continues to evolve, collaborative efforts and a holistic understanding of epilepsy's diverse manifestations will be instrumental in harnessing the full potential of this dynamic landscape.

Astrocyte metabolism and signaling pathways in the CNS

Astrocytes comprise half of the cells in the central nervous system and play a critical role in maintaining metabolic homeostasis. Metabolic dysfunction in astrocytes has been indicated as the primary cause of neurological diseases, such as depression, Alzheimer's disease, and epilepsy. Although the metabolic functionalities of astrocytes are well known, their relationship to neurological disorders is poorly understood. The ways in which astrocytes regulate the metabolism of glucose, amino acids, and lipids have all been implicated in neurological diseases. Metabolism in astrocytes has also exhibited a significant influence on neuron functionality and the brain's neuro-network. In this review, we focused on metabolic processes present in astrocytes, most notably the glucose metabolic pathway, the fatty acid metabolic pathway, and the amino-acid metabolic pathway. For glucose metabolism, we focused on the glycolysis pathway, pentose-phosphate pathway, and oxidative phosphorylation pathway. In fatty acid metabolism, we followed fatty acid oxidation, ketone body metabolism, and sphingolipid metabolism. For amino acid metabolism, we summarized neurotransmitter metabolism and the serine and kynurenine metabolic pathways. This review will provide an overview of functional changes in astrocyte metabolism and provide an overall perspective of current treatment and therapy for neurological disorders.

Molecular analysis and prenatal diagnosis of seven Chinese families with genetic epilepsy

Introduction

Genetic epilepsy is a large group of clinically and genetically heterogeneous neurological disorders characterized by recurrent seizures, which have a clear association with genetic defects. In this study, we have recruited seven families from China with neurodevelopmental abnormalities in which epilepsy was a predominant manifestation, aiming to elucidate the underlying causes and make a precise diagnosis for the cases.

Methods

Whole-exome sequencing (WES) combined with Sanger sequencing was used to identify the causative variants associated with the diseases in addition to essential imaging and biomedical examination.

Results

A gross intragenic deletion detected in MFSD8 was investigated via gap-polymerase chain reaction (PCR), real-time quantitative PCR (qPCR), and mRNA sequence analysis. We identified 11 variants in seven genes (ALDH7A1, CDKL5, PCDH19, QARS1, POLG, GRIN2A, and MFSD8) responsible for genetic epilepsy in the seven families, respectively. A total of six variants (c.1408T>G in ALDH7A1, c.1994_1997del in CDKL5, c.794G>A in QARS1, c.2453C>T in GRIN2A, and c.217dup and c.863+995_998+1480del in MFSD8) have not yet been reported to be associated with diseases and were all evaluated to be pathogenic or likely pathogenic according to the American College of Medical Genetics and Genomics (ACMG) guidelines.

Methods

Based on the molecular findings, we have associated the intragenic deletion in MFSD8 with the mutagenesis mechanism of Alu-mediated genomic rearrangements for the first time and provided genetic counseling, medical suggestions, and prenatal diagnosis for the families. In conclusion, molecular diagnosis is crucial to obtain improved medical outcomes and recurrence risk evaluation for genetic epilepsy.

Rodent Models of Audiogenic Epilepsy: Genetic Aspects, Advantages, Current Problems and Perspectives

Animal models of epilepsy are of great importance in epileptology. They are used to study the mechanisms of epileptogenesis, and search for new genes and regulatory pathways involved in the development of epilepsy as well as screening new antiepileptic drugs. Today, many methods of modeling epilepsy in animals are used, including electroconvulsive, pharmacological in intact animals, and genetic, with the predisposition for spontaneous or refractory epileptic seizures. Due to the simplicity of manipulation and universality, genetic models of audiogenic epilepsy in rodents stand out among this diversity. We tried to combine data on the genetics of audiogenic epilepsy in rodents, the relevance of various models of audiogenic epilepsy to certain epileptic syndromes in humans, and the advantages of using of rodent strains predisposed to audiogenic epilepsy in current epileptology.

Detection of IEMs by Mass Spectrometry Techniques in High-Risk Children: A Pilot Study

OBJECTIVES

To determine the incidence and types of inborn errors of metabolism (IEMs) in high-risk children using mass spectrometry techniques.

METHODS

Children considered high-risk for IEM were screened for metabolic diseases during a 3-y period. Dried blood spots and urine samples were analyzed by tandem mass spectrometry (LC-MS/MS) and gas chromatograph-mass spectrometry (GCMS). Samples with abnormal amino acids were confirmed by high-performance liquid chromatography (HPLC).

RESULTS

Eight hundred and twenty-two suspected cases were evaluated; of which, 87 possible cases of IEMs were identified. Homocystinuria (n = 51) was the most common IEM detected followed by biotinidase deficiency (n = 7), glutaric aciduria type 1 (n = 7), and carnitine uptake defect (n = 6). Overall, there were 45 (51.7%) cases of organic acidemia, 31 cases (35.6%) of amino acid defect, 9 (10.3%) cases of fatty-acid oxidation disorders, and 2 (2.3%) cases of probable mitochondrial disorder.

CONCLUSION

IEMs are common in India, with a hospital-based incidence of 1 in approximately 6642 among high-risk children. Screening of high-risk children by mass spectrometry techniques is a valuable strategy for early diagnosis of IEMs where universal newborn screening is not yet available.

Epilepsy in Pediatric Patients—Evaluation of Brain Structures’ Volume Using VolBrain Software

Epilepsy is one of the most frequent serious brain disorders. Approximately 30,000 of the 150,000 children and adolescents who experience unprovoked seizures are diagnosed with epilepsy each year. Magnetic resonance imaging is the method of choice in diagnosing and monitoring patients with this condition. However, one very effective tool using MR images is volBrain software, which automatically generates information about the volume of brain structures. A total of 57 consecutive patients (study group) suffering from epilepsy and 34 healthy patients (control group) who underwent MR examination qualified for the study. Images were then evaluated by volBrain. Results showed atrophy of the brain and particular structures—GM, cerebrum, cerebellum, brainstem, putamen, thalamus, hippocampus and nucleus accumbens volume. Moreover, the statistically significant difference in the volume between the study and the control group was found for brain, lateral ventricle and putamen. A volumetric analysis of the CNS in children with epilepsy confirms a decrease in the volume of brain tissue. A volumetric assessment of brain structures based on MR data has the potential to be a useful diagnostic tool in children with epilepsy and can be implemented in clinical work; however, further studies are necessary to enhance the effectiveness of this software.

Metabolic epilepsy in hyperprolinemia type II due to a novel nonsense ALDH4A1 gene variant

Hyperprolinemia type II (HPII) is a rare autosomal recessive disorder of proline degradation pathway due to deficiency of delta-1-pyrroline-5-carboxylate dehydrogenase. Pathogenic variants in the ALDH4A1 gene are responsible for this disorder. We here describe an 11-month-old infant with recurrent seizures refractory to multiple antiepileptic drugs. She was hospitalized in view of acute-onset encephalopathy, exacerbation of generalized seizures following an upper respiratory infection. Laboratory investigation revealed significantly elevated proline levels in dried blood spots. DNA sample of the child was subjected to a targeted next-generation sequencing gene panel for hyperprolinemias. We detected a novel nonsense homozygous variant in the ALDH4A1 gene in the child and the heterozygous variant of the same in both the parents. Based on the location of the variant i.e. in the last exon, truncated protein is expected to be expressed by skipping nonsense-mediated decay and such point-nonsense variants could be an ideal target for readthrough drugs to correct genetic defects.

Comparison of Long-Term Outcomes of Monotherapy and Polytherapy in Seizure-Free Patients With Epilepsy Following Antiseizure Medication Withdrawal

Objective: The objectives of this study were to compare the risk and timing of seizure relapse in seizure-free patients with epilepsy following the withdrawal of monotherapy or polytherapy and to identify relevant influencing factors.

Methods: Patients who had achieved at least a 2-year seizure remission and started the withdrawal of antiseizure medication (ASM) were enrolled in this study. All patients were followed for at least 3 years or until seizure relapse. According to the number of ASMs at the time of withdrawalwas about twice than that, patients were divided into two groups: monotherapy group and polytherapy group. The Cox proportional hazards model was used to compare the recurrence risk of the two groups. Univariate analysis and multiple logistic regression analysis were used to analyze potential confounding variables between patients treated with monotherapy and polytherapy.

Results: A total of 188 patients (119 males and 69 females) were included. The average prescribed daily dose of most ASMs at the time of withdrawal was moderate or low (30–50% defined daily dose). The recurrence of most patients (89.2%) occurred within the first 3 years after withdrawal. The recurrence risk in patients treated with polytherapy at the time of withdrawal was about twice than that of the monotherapy group [p = 0.001, hazard ratio (HR) = 2.152, 95% confidence interval (CI) = 1.350–3.428]. Multivariate analysis showed that patients treated with polytherapy were significantly older at seizure onset [p = 0.024, odd ratio (OR) = 1.027, 95% CI = 1.004–1.052] and had a significantly longer duration of epilepsy before treatment (p = 0.004, OR = 1.009, 95% CI = 1.003–1.015) compared to patients in the monotherapy group. In addition, a history of perinatal injury was found to be an independent risk factor of seizure relapse in patients with ASM withdrawal.

Conclusion: The average prescribed daily dose of most ASMs at the time of withdrawal was moderate or low. Patients who received polytherapy at the time of withdrawal, particularly those with later seizure onset age and longer epilepsy duration before treatment, had a higher recurrence risk after ASMs withdrawal compared to patients treated with monotherapy.