Magnetoencephalography-based approaches to epilepsy classification

Epilepsy is a chronic central nervous system disorder characterized by recurrent seizures. Not only does epilepsy severely affect the daily life of the patient, but the risk of premature death in patients with epilepsy is three times higher than that of the normal population. Magnetoencephalography (MEG) is a non-invasive, high temporal and spatial resolution electrophysiological data that provides a valid basis for epilepsy diagnosis, and used in clinical practice to locate epileptic foci in patients with epilepsy. It has been shown that MEG helps to identify MRI-negative epilepsy, contributes to clinical decision-making in recurrent seizures after previous epilepsy surgery, that interictal MEG can provide additional localization information than scalp EEG, and complete excision of the stimulation area defined by the MEG has prognostic significance for postoperative seizure control. However, due to the complexity of the MEG signal, it is often difficult to identify subtle but critical changes in MEG through visual inspection, opening up an important area of research for biomedical engineers to investigate and implement intelligent algorithms for epilepsy recognition. At the same time, the use of manual markers requires significant time and labor costs, necessitating the development and use of computer-aided diagnosis (CAD) systems that use classifiers to automatically identify abnormal activity. In this review, we discuss in detail the results of applying various different feature extraction methods on MEG signals with different classifiers for epilepsy detection, subtype determination, and laterality classification. Finally, we also briefly look at the prospects of using MEG for epilepsy-assisted localization (spike detection, high-frequency oscillation detection) due to the unique advantages of MEG for functional area localization in epilepsy, and discuss the limitation of current research status and suggestions for future research. Overall, it is hoped that our review will facilitate the reader to quickly gain a general understanding of the problem of MEG-based epilepsy classification and provide ideas and directions for subsequent research

Causal effect of psychiatric disorders on epilepsy: A two‐sample Mendelian randomization study

Abstract Background This study aims to explore the relationship between psychiatric disorders and the risk of epilepsy using Mendelian randomization (MR) analysis. Methods We collected summary statistics of seven psychiatric traits from recent largest genome‐wide association study (GWAS), including major depressive disorder (MDD), anxiety disorder, autism spectrum disorder (ASD), bipolar disorder (BIP), attention deficit hyperactivity disorder (ADHD), schizophrenia (SCZ), and insomnia. Then, MR analysis estimates were performed based on International League Against Epilepsy (ILAE) consortium data (ncase = 15,212 and ncontrol = 29,677), the results of which were subsequently validated in FinnGen consortium (ncase = 6260 and ncontrol = 176,107). Finally, a meta‐analysis was conducted based on the ILAE and FinnGen data. Results We found significant causal effects of MDD and ADHD on epilepsy in the meta‐analysis of the ILAE and FinnGen, with corresponding odds ratios (OR) of 1.20 (95% CI 1.08–1.34, p = .001) and 1.08 (95% CI 1.01–1.16, p = .020) by the inverse‐variance weighted (IVW) method respectively. MDD increases the risk of focal epilepsy while ADHD has a risk effect on generalized epilepsy. No reliable evidence regarding causal effects of other psychiatric traits on epilepsy was identified. Conclusions This study suggests that major depressive disorder and attention deficit hyperactivity disorder may causally increase the risk of epilepsy

Genetic and phenotypic analyses of PRRT2 positive and negative paroxysmal kinesigenic dyskinesia

Background: Paroxysmal kinesigenic dyskinesia (PKD) is a rare neurological disorder, characterized by attacks of involuntary movements triggered by sudden action. Variants in proline-rich transmembrane protein 2 ( PRRT2 ) are the most common genetic cause of PKD. Objective: The objective was to investigate the clinical and genetic characteristics of PKD and to establish genotype–phenotype correlations. Methods: We enrolled 219 PKD patients, documented their clinical information and performed PRRT2 screening using Sanger sequencing. Whole exome sequencing was performed on 49 PKD probands without PRRT2 variants. Genotype–phenotype correlation analyses were conducted on the probands. Results: Among 219 PKD patients (99 cases from 39 families and 120 sporadic cases), 16 PRRT2 variants were identified. Nine variants (c.879+4A>G, c.879+5G>A, c.856G>A, c.955G>T, c.884G>C, c.649C>T, c.649dupC, c.649delC and c.696_697delCA) were previously known, while seven were novel (c.367_403del, c.347_348delAA, c.835C>T, c.116dupC, c.837_838insC, c.916_937del and c.902G>A). The mean interval from onset to diagnosis was 7.94 years. Compared to patients without PRRT2 variants, patients with the variants were more likely to have a positive family history, an earlier age of onset and a higher prevalence of falls during pre-treatment attacks (27.14% versus 8.99%, respectively). Patients with truncated PRRT2 variants tend to have bilateral attacks. We identified two transmembrane protein 151A ( TMEM151A ) variants including a novel variant (c.368G>C) and a reported variant (c.203C>T) in two PRRT2-negative probands with PKD. Conclusion: These findings provide insights on the clinical characteristics, diagnostic timeline and treatment response of PKD patients. PKD patients with truncated PRRT2 variants may tend to have more severe paroxysmal symptoms. This study expands the spectrum of PRRT2 and TMEM151A variants. Carbamazepine and oxcarbazepine are both used as a first-line treatment choice for PKD patients

Patterns of postictal cerebral perfusion in idiopathic generalized epilepsy: a multi-delay multi-parametric arterial spin labelling perfusion MRI study.

The cerebral haemodynamic status of idiopathic generalized epilepsy (IGE) is a very complicated process. Little attention has been paid to cerebral blood flow (CBF) alterations in IGE detected by arterial spin labelling (ASL) perfusion magnetic resonance imaging (MRI). However, the selection of an optimal delay time is difficult for single-delay ASL. Multi-delay multi-parametric ASL perfusion MRI overcomes the limitations of single-delay ASL. We applied multi-delay multi-parametric ASL perfusion MRI to investigate the patterns of postictal cerebral perfusion in IGE patients with absence seizures. A total of 21 IGE patients with absence seizures and 24 healthy control subjects were enrolled. IGE patients exhibited prolonged arterial transit time (ATT) in the left superior temporal gyrus. The mean CBF of IGE patients was significantly increased in the left middle temporal gyrus, left parahippocampal gyrus and left fusiform gyrus. Prolonged ATT in the left superior temporal gyrus was negatively correlated with the age at onset in IGE patients. This study demonstrated that cortical dysfunction in the temporal lobe and fusiform gyrus may be related to epileptic activity in IGE patients with absence seizures. This information can play an important role in elucidating the pathophysiological mechanism of IGE from a cerebral haemodynamic perspective

Patterns of postictal cerebral perfusion in idiopathic generalized epilepsy: a multi-delay multi-parametric arterial spin labelling perfusion MRI study.

The cerebral haemodynamic status of idiopathic generalized epilepsy (IGE) is a very complicated process. Little attention has been paid to cerebral blood flow (CBF) alterations in IGE detected by arterial spin labelling (ASL) perfusion magnetic resonance imaging (MRI). However, the selection of an optimal delay time is difficult for single-delay ASL. Multi-delay multi-parametric ASL perfusion MRI overcomes the limitations of single-delay ASL. We applied multi-delay multi-parametric ASL perfusion MRI to investigate the patterns of postictal cerebral perfusion in IGE patients with absence seizures. A total of 21 IGE patients with absence seizures and 24 healthy control subjects were enrolled. IGE patients exhibited prolonged arterial transit time (ATT) in the left superior temporal gyrus. The mean CBF of IGE patients was significantly increased in the left middle temporal gyrus, left parahippocampal gyrus and left fusiform gyrus. Prolonged ATT in the left superior temporal gyrus was negatively correlated with the age at onset in IGE patients. This study demonstrated that cortical dysfunction in the temporal lobe and fusiform gyrus may be related to epileptic activity in IGE patients with absence seizures. This information can play an important role in elucidating the pathophysiological mechanism of IGE from a cerebral haemodynamic perspective

sj-tif-2-tan-10.1177_17562864231224110 – Supplemental material for Genetic and phenotypic analyses of PRRT2 positive and negative paroxysmal kinesigenic dyskinesia

Supplemental material, sj-tif-2-tan-10.1177_17562864231224110 for Genetic and phenotypic analyses of PRRT2 positive and negative paroxysmal kinesigenic dyskinesia by Yingying Zhang, Jiechuan Ren, Tianhua Yang, Weixi Xiong, Linyuan Qin, Dongmei An, Fayun Hu and Dong Zhou in Therapeutic Advances in Neurological Disorders</p

sj-docx-1-tan-10.1177_17562864231224110 – Supplemental material for Genetic and phenotypic analyses of PRRT2 positive and negative paroxysmal kinesigenic dyskinesia

Supplemental material, sj-docx-1-tan-10.1177_17562864231224110 for Genetic and phenotypic analyses of PRRT2 positive and negative paroxysmal kinesigenic dyskinesia by Yingying Zhang, Jiechuan Ren, Tianhua Yang, Weixi Xiong, Linyuan Qin, Dongmei An, Fayun Hu and Dong Zhou in Therapeutic Advances in Neurological Disorders</p