Epilepsy Subtypes Research Articles

Causal relationships between epilepsy and the microstructure of the white matter: A Mendelian randomization study.

To examine the causal bidirectional relationships between epilepsy and microstructural changes in the white matter (WM). A genome-wide association study meta-analysis of the International League Against Epilepsy Consortium on Epilepsy and 360 WM imaging-derived phenotypes (IDPs) from the UK Biobank was used for the analysis. Genetic correlation analyses were conducted based on summary statistics of various "IDP-epilepsy" pairs for 2-sample Mendelian randomization (MR) analysis to explore the causal relationships. We used the inverse variance weighted (IVW) method as the primary MR analysis approach, and conducted sensitivity analyses for pleiotropy and heterogeneity. Forward MR analysis revealed that alterations in the 16 WM IDPs increased the risk of epilepsy (q value < 0.05). Changes in the 38 WM IDPs were associated with a decreased risk of epilepsy (q value < 0.05). In the reverse analysis, seizures from all epilepsy types changed 5 WM IDPs, whereas seizures from juvenile myoclonic epilepsy altered 11 WM IDPs (q value < 0.05). This study revealed causal associations between changes in the WM microstructure and epilepsy subtypes. These findings offer new directions for early prevention and treatment of epilepsy.

Is Common Denominator Lead to Misdiagnosis of Dementia and Late-Life Depression

Significant cognitive impairments are found in late life depression. This situation brings to mind the question of what are the common and distinct mechanisms of late life depression and dementia. In this review, neural and psychological mechanism are discussed within the scope of denominator and hallmark for both disorders. It is searched several databases e.g. MEDLINE, Web of Science Core Collection from 1974 to 2024 by using variant terms for the focal epilepsy subtypes and social cognition constructs. The pathology of dementia was correlated with late-life depression Studies indicate that depression may be an etiological factor for dementia as well as an increased risk. Also, many life-related stressors can lead to results such as increased reactive oxygen species, inflammatory responses, suppression of neurogenesis, and apical dendritic atrophy and altered functional connectivity in the medial prefrontal cortex. Based on this, it is possible to say that psychological stress factors increase the incidence of the disease in the development of dementia, just like in depression. Late depression should not be labeled as dementia because of they share similar symptoms and should be evaluated clinically correct so that it is not misdiagnosed. Besides, it is substantial to comprehend the relationship between the aging population and the risk of depression and dementia for current and future studies, especially in terms of prevention and treatment.

The causal association between epilepsy and amyotrophic lateral sclerosis: A two-sample Mendelian randomization study.

Epilepsy and amyotrophic lateral sclerosis (ALS) are common neurological disorders. The association between the two disorders has been raised in observational studies. However, it is uncertain to what extent they have mutual causal effects. In this study, we aimed to investigate their causal association using a two-sample Mendelian randomization (MR) method. We performed a two-sample bidirectional MR analysis to evaluate the causal association of epilepsy with the risk of ALS. Publicly published genome-wide association study statistics for epilepsy and ALS were used in the study. The primary analysis included genetic variants with a p value of less than 1 × 10-5 as instrumental variables. We applied several alternative methods, including inverse variance weighting, weighted median, simple mode, weighted mode, MR-Egger regression and MR pleiotropy residual sum and outlier, and statistical graphs to assess the associations of epilepsy and its subtype with the risk of ALS. Reverse MR analyses were also performed to examine the association of ALS with the risk of epilepsy. The primary MR analysis found no causal effect of epilepsy on risk of ALS (odds ration [OR]: 1.133, 95% confidence interval [CI]: 0.964-1.332, p=.130). Among subtypes of epilepsy, it also failed to observe any causal association between general epilepsy and ALS (OR: 1.036, 95% CI: 0.969-1.108, P=.300). However, focal epilepsy contributed to an increase in the risk of ALS (OR: 1.177, 95% CI: 1.027-1.348, p=.019). Moreover, the investigation of reverse causalities did not reveal significant results. The current study supports a causal influence of focal epilepsy on ALS risk. Future studies are needed to explore its potential role in ALS.

Brain imaging traits and epilepsy: Unraveling causal links via mendelian randomization.

Epilepsy, a complex neurological disorder, is closely linked with structural and functional irregularities in the brain. However, the causal relationship between brain imaging-derived phenotypes (IDPs) and epilepsy remains unclear. This study aimed to investigate this relationship by employing a two-sample bidirectional Mendelian randomization (MR) approach. The analysis involved 3935 cerebral IDPs from the UK Biobank and all documented cases of epilepsy (all epilepsies) cohorts from the International League Against Epilepsy, with further validation through replication and meta-analyses using epilepsy Genome-Wide Association Studies datasets from the FinnGen database. Additionally, a multivariate MR analysis framework was utilized to assess the direct impact of IDPs on all epilepsies. Furthermore, we performed a bidirectional MR analysis to investigate the relationship between the IDPs identified in all epilepsies and the 15 specific subtypes of epilepsy. The study identified significant causal links between four IDPs and epilepsy risk. Decreased fractional anisotropy in the left inferior longitudinal fasciculus was associated with a higher risk of epilepsy (odds ratio [OR]: 0.89, p=3.31×10-5). Conversely, increased mean L1 in the left posterior thalamic radiation (PTR) was independently associated with a heightened epilepsy risk (OR: 1.14, p=4.72×10-5). Elevated L3 in the left cingulate gyrus was also linked to an increased risk (OR: 1.09, p=.03), while decreased intracellular volume fraction in the corpus callosum was correlated with higher epilepsy risk (OR: 0.94, p=1.15×10-4). Subtype analysis revealed that three of these IDPs are primarily associated with focal epilepsy (FE). Notably, increased L1 in the left PTR was linked to an elevated risk of hippocampal sclerosis (HS) and lesion-negative FE, whereas elevated L3 in the left cingulate gyrus was associated with HS-related FE. Our research offers genetic evidence for a causal link between brain IDPs and epilepsy. These results enhance our understanding of the structural brain changes associated with the onset and progression of epilepsy.

Predicting the Path: How Machine Learning Can Identify Subtypes of Epilepsy and Predict Disease Progression

Predicting the Path: How Machine Learning Can Identify Subtypes of Epilepsy and Predict Disease Progression

Unraveling the shared genetics of common epilepsies and general cognitive ability

PurposeCognitive impairment is prevalent among individuals with epilepsy, and increasing evidence indicates that genetic factors can underlie this relationship. However, the extent to which epilepsy subtypes differ in their genetic relationship with cognitive function, and information about the specific genetic variants involved remain largely unknown. MethodsWe investigated the genetic relationship between epilepsies and general cognitive ability (COG) using complementary statistical tools, including linkage disequilibrium score (LDSC) regression, MiXeR and conjunctional false discovery rate (conjFDR). We analyzed genome-wide association study data on COG (n = 269,867) and common epilepsies (n = 27,559 cases, 42,436 controls), including the broad phenotypes ‘all epilepsy’, focal epilepsies and genetic generalized epilepsies (GGE), as well as specific subtypes. We functionally annotated the identified loci using several biological resources and validated the results in independent samples. ResultsUsing MiXeR, COG (11.2k variants) was estimated to be almost four times more polygenic than ‘all epilepsy’, GGE, juvenile myoclonic epilepsy (JME), and childhood absence epilepsy (CAE) (2.5k – 2.9k variants). The other epilepsy phenotypes were insufficiently powered for MiXeR analysis. We quantified extensive genetic overlap between COG and epilepsy types, but with varying negative genetic correlations (-0.23 to -0.04). COG was estimated to share 2.9k variants with both GGE and ‘all epilepsy’, and 2.3k variants with both JME and CAE. Using conjFDR, we identified 66 distinct loci shared between COG and epilepsies, including novel associations for GGE (27), ‘all epilepsy’ (5), JME (5) and CAE (5). The implicated genes were significantly expressed in multiple brain regions. The results were validated in independent samples (COG: p = 3.62 × 10–7; ‘all epilepsy’: p = 2.58 × 10–3). ConclusionOur study further dissects the substantial genetic basis shared between epilepsies and COG and identifies novel shared loci. An improved understanding of the genetic relationship between epilepsies and COG may lead to the development of novel comorbidity-targeted epilepsy treatments.

Exome sequencing of 20,979 individuals with epilepsy reveals shared and distinct ultra-rare genetic risk across disorder subtypes.

Identifying genetic risk factors for highly heterogeneous disorders like epilepsy remains challenging. Here, we present the largest whole-exome sequencing study of epilepsy to date, with >54,000 human exomes, comprising 20,979 deeply phenotyped patients from multiple genetic ancestry groups with diverse epilepsy subtypes and 33,444 controls, to investigate rare variants that confer disease risk. These analyses implicate seven individual genes, three gene sets, and four copy number variants at exome-wide significance. Genes encoding ion channels show strong association with multiple epilepsy subtypes, including epileptic encephalopathies, generalized and focal epilepsies, while most other gene discoveries are subtype-specific, highlighting distinct genetic contributions to different epilepsies. Combining results from rare single nucleotide/short indel-, copy number-, and common variants, we offer an expanded view of the genetic architecture of epilepsy, with growing evidence of convergence among different genetic risk loci on the same genes. Top candidate genes are enriched for roles in synaptic transmission and neuronal excitability, particularly postnatally and in the neocortex. We also identify shared rare variant risk between epilepsy and other neurodevelopmental disorders. Our data can be accessed via an interactive browser, hopefully facilitating diagnostic efforts and accelerating the development of follow-up studies.

Causal associations between gut microbiota, circulating inflammatory proteins, and epilepsy: a multivariable Mendelian randomization study.

Previous studies have suggested that gut microbiota (GM) may be involved in the pathogenesis of epilepsy through the microbiota-gut-brain axis (MGBA). However, the causal relationship between GM and different epilepsy subtypes and whether circulating inflammatory proteins act as mediators to participate in epileptogenesis through the MGBA remain unclear. Therefore, it is necessary to identify specific GM associated with epilepsy and its subtypes and explore their underlying inflammatory mechanisms for risk prediction, personalized treatment, and prognostic monitoring of epilepsy. We hypothesized the existence of a pathway GM-inflammatory proteins-epilepsy. We found genetic variants strongly associated with GM, circulating inflammatory proteins, epilepsy and its subtypes, including generalized and partial seizures, from large-scale genome-wide association studies (GWAS) summary data and used Multivariate Mendelian Randomization to explore the causal relationship between the three and whether circulating inflammatory proteins play a mediating role in the pathway from GM to epilepsy, with inverse variance weighted (IVW) method as the primary statistical method, supplemented by four methods: MR-Egger, weighted median estimator (WME), Weighted mode and Simple mode. 16 positive and three negative causal associations were found between the genetic liability of GM and epilepsy and its subtypes. There were nine positive and nine negative causal associations between inflammatory proteins and epilepsy and its subtypes. Furthermore, we found that C-X-C motif chemokine 11 (CXCL11) levels mediated the causal association between Genus Family XIII AD3011 group and epilepsy. Our study highlights the possible causal role of specific GM and specific inflammatory proteins in the development of epilepsy and suggests that circulating inflammatory proteins may mediate epileptogenesis through the MGBA.

Differences in subcortical functional connectivity in patients with epilepsy.

Epilepsy is a disease characterized by abnormal paroxysmal bioelectrical activity in the brain cortex and subcortical structures. Seizures per se change brain metabolism in epileptic focus and in distal parts of the brain. However, interictal phenomena can also affect functional connectivity (FC) and brain metabolism in other parts of the brain. We hypothesised that epilepsy affects functional connectivity not only among cortical, but also between subcortical, structures of the brain in a resting state condition. Investigating functional connectivity in patients with epilepsy could provide insights into the underlying pathophysiological mechanisms. Better understanding may lead to more effective treatment strategies. Functional connectivity was analysed in 35 patients with epilepsy and in 28 healthy volunteers. The group of patients was divided into generalised and focal epilepsy (temporal and extratemporal subgroups). Each patient and healthy volunteer underwent an fMRI resting-state session. During the study, EEG signals were simultaneously recorded with fMRI to facilitate the subsequent detection of potential interictal epileptiform discharges (IEDs). Their potential impact on BOLD signals was mitigated through linear regression. The data was processed and correlation coefficients (FC values) between the BOLD signal from selected structures of the central nervous system were determined and compared between study groups. The results were presented as significant differences in correlation coefficients between brain/subcortical structures in the epilepsy and control groups. Lower FC values for the epilepsy group compared to the control group were shown for connections related to the MPFC, hippocampus, thalamus, amygdala, and the parahippocampal gyrus. Epilepsy alters the functional connectivity of resting state subcortical networks. Patterns of pathological changes of FC differ between epilepsy subtypes, with predominant lower FC between the hippocampus, parahippocampal gyrus, amygdala and thalamus in patients with epilepsy. This study suggests that epilepsy affects subcortical structures. Identifying distinct patterns of altered FC in epilepsy subtypes may help to tailor treatment strategies. Changes in FC detected by fMRI may precede clinical symptoms, aiding in the early diagnosis of cognitive and emotional disorders in focal epilepsy.

Causal association between epilepsy and its DNA methylation profile and atrial fibrillation

BackgroundThe "epileptic heart" concept is emerging, but the causal relationship between epilepsy and atrial fibrillation (AF) remains unclarified. ObjectiveThis study explores the genetic correlations and bidirectional causality between various epilepsy phenotypes and AF. MethodsGenome-wide association study (GWAS) statistics for 10 epilepsy subtypes (29,944 cases, 52,538 controls) and AF (60,620 cases, 970,216 controls) were sourced from the International League Against Epilepsy (ILAE) and HGRI-EBI Catalog-GWAS, respectively. Linkage disequilibrium score regression (LDSC) and genome-wide Mendelian Randomization (MR) evaluated genetic correlations and bidirectional causal relationships. Epilepsy-related DNA methylation data (N= ∼800) from EWAS catalog were analyzed to identify causal CpG sites influencing AF risk through epigenetic MR. ResultsLDSC revealed significant genetic correlations between four epilepsy subtypes and AF (rg from 0.116 to 0.241). Forward MR suggested a significant causal effect of focal epilepsy with hippocampal sclerosis (FE with HS) on AF risk (IVW and MR-PRESSO: OR = 1.046, P ≤ 0.004), with results robust against heterogeneity, horizontal pleiotropy, and outliers. Epigenetic MR indicated that lower methylation at cg06222062 (OR = 0.994, P = 3.16E-04) mapped to PLA2G5 and cg08461451 mapped to SPPL2B gene (OR = 0.954, P = 1.19E-03), and higher cg10541930 in the C10orf143 promoter (OR = 1.043, P = 4.18E-22) increases AF risk. Sensitivity analyses affirmed no pleiotropic bias. ConclusionFE with HS significantly increases AF risk, highlighting the natural neural-cardiac connection and the need for cardiac monitoring in epilepsy patients. Specific methylated CpG sites may serve as biomarkers and preventive targets for AF susceptibility.

Elevated plasma neurofilament light and glial fibrillary acidic protein in epilepsy versus nonepileptic seizures and nonepileptic disorders.

Research suggests that recurrent seizures may lead to neuronal injury. Neurofilament light chain protein (NfL) and glial fibrillary acidic protein (GFAP) levels increase in cerebrospinal fluid and blood in response to neuroaxonal damage, and they have been hypothesized as potential biomarkers for epilepsy. We examined plasma NfL and GFAP levels and their diagnostic utility in differentiating patients with epilepsy from those with psychogenic nonepileptic seizures (PNES) and other nonepileptic disorders. We recruited consecutive adults admitted for video-electroencephalographic monitoring and formal neuropsychiatric assessment. NfL and GFAP levels were quantified and compared between different patient groups and an age-matched reference cohort (n = 1926) and correlated with clinical variables in patients with epilepsy. A total of 138 patients were included, of whom 104 were diagnosed with epilepsy, 22 with PNES, and 12 with other conditions. Plasma NfL and GFAP levels were elevated in patients with epilepsy compared to PNES, adjusted for age and sex (NfL p = .04, GFAP p = .04). A high proportion of patients with epilepsy (20%) had NfL levels above the 95th age-matched percentile compared to the reference cohort (5%). NfL levels above the 95th percentile of the reference cohort had a 95% positive predictive value for epilepsy. Patients with epilepsy who had NfL levels above the 95th percentile were younger than those with lower levels (37.5 vs. 43.8 years, p = .03). An elevated NfL or GFAP level in an individual patient may support an underlying epilepsy diagnosis, particularly in younger adults, and cautions against a diagnosis of PNES alone. Further examination of the association between NfL and GFAP levels and specific epilepsy subtypes or seizure characteristics may provide valuable insights into disease heterogeneity and contribute to the refinement of diagnosis, understanding pathophysiological mechanisms, and formulating treatment approaches.

Causal links between serum micronutrients and epilepsy: a Mendelian randomization analysis.

Micronutrient levels play a critical role in epilepsy. This study investigates the impact of micronutrient levels on epilepsy via Mendelian randomization (MR). A two-sample MR framework evaluated the genetic association between 15 serum micronutrients and epilepsy phenotypes. The analysis included calcium, iron, zinc, selenium, copper, magnesium, potassium, folate, vitamins B6, B12, C, D, E, retinol, and carotene against all epilepsy, generalized epilepsy, childhood absence epilepsy (CAE), juvenile absence epilepsy (JAE), juvenile myoclonic epilepsy (JME), generalized tonic-clonic seizures alone and with spike-wave electroencephalography (GTCS), and various focal epilepsy phenotypes [with hippocampal sclerosis (HS), lesions other than HS, lesion-negative]. The random-effects inverse-variance weighted (IVW) model was the primary method used, supported by heterogeneity and pleiotropy assessments. Multivariable Mendelian randomization analyses (MVMR) were used to identify micronutrients that are significantly causally associated with different epilepsy subtypes and to confirm the most potential causal risk factors for these subtypes. Zinc conferred an increased risk of focal epilepsy with HS (OR = 1.01; p = 0.045). Carotene was similarly linked to higher risks of lesion-negative cases (OR = 1.129; p = 0.037). Conversely, vitamin B6 was associated with reduced risks of focal epilepsy with HS (OR = 0.949; p = 0.020), and vitamin D was linked to decreased risks of both CAE (OR = 0.976, 95% CI: 0.959-0.993, p = 0.006) and JAE (OR = 0.986, 95% CI: 0.973-0.999, p = 0.032). These associations were robust, showing minimal heterogeneity and no evidence of pleiotropy across various sensitivity analyses. After adjustment using MVMR, significant causal relationships between vitamin D and both CAE and JAE remained. Furthermore, the causal relationship between zinc and vitamin B6 on focal epilepsy with HS became non-significant, while carotene shifted from a risk factor to a protective factor for focal epilepsy lesion-negative after adjusting for vitamin D. MR estimates provide robust evidence for the causal effects of vitamin D on reducing the risk of CAE, and JAE, which might provide alternative treatment strategies.

Causal relations between ischemic stroke and epilepsy: A bidirectional Mendelian randomization study

BackgroundAlthough previous studies have reported a bidirectional relationship between ischemic stroke (IS) and epilepsy, the existence of a causal nexus and its directionality remains a topic of controversy. MethodsThe single nucleotide polymorphisms (SNPs) associated with IS were extracted from the Genome-Wide Association Study (GWAS) database. Pooled genetic data encompassing all epilepsy cases, as well as generalized and focal epilepsy subtypes, were acquired from the International League Against Epilepsy's GWAS study. In this study, the primary analysis approach utilized the inverse variance weighting (IVW) method as the main analytical technique. To enhance the robustness of the findings against potential pleiotropy, additional sensitivity analyses were conducted. ResultsIn the forward analysis, the IVW method demonstrated that IS was associated with an increased risk of all epilepsy (odds ratio (OR) = 1.127, 95 % confidence interval (CI) = 1.038–1.224, P = 0.004) and generalized epilepsy (IVW: OR = 1.340, 95 % CI = 1.162–1.546, P = 5.70 × 10–5). There was no substantial causal relationship observed between IS and focal epilepsy (P > 0.05). Furthermore, generalized epilepsy, focal epilepsy, and all epilepsy did not show a causal relationship with IS. ConclusionThis Mendelian randomization (MR) analysis demonstrates that IS increases the risk of developing epilepsy, especially generalized epilepsy. Conversely, no clear causal association was found between epilepsy and the onset of stroke. Therefore, the possible mechanisms of the effect of epilepsy on the pathogenesis of IS still need to be further investigated.

Causal links between gut microbiomes, cytokines and risk of different subtypes of epilepsy: a Mendelian randomization study

ObjectiveRecent research suggests a potential link between the gut microbiome (GM) and epilepsy. We undertook a Mendelian randomization (MR) study to determine the possible causal influence of GM on epilepsy and its various subtypes, and explore whether cytokines act as mediators.MethodsWe utilized Genome-Wide Association Study (GWAS) summary statistics to examine the causal relationships between GM, cytokines, and four epilepsy subtypes. Furthermore, we assessed whether cytokines mediate the relationship between GM and epilepsy. Significant GMs were further investigated using transcriptomic MR analysis with genes mapped from the FUMA GWAS. Sensitivity analyses and reverse MR were conducted for validation, and false discovery rate (FDR) correction was applied for multiple comparisons.ResultsWe pinpointed causal relationships between 30 GMs and various epilepsy subtypes. Notably, the Family Veillonellaceae (OR:1.03, 95%CI:1.02–1.05, p = 0.0003) consistently showed a strong positive association with child absence epilepsy, and this causal association endured even after FDR correction (p-FDR &amp;lt; 0.05). Seven cytokines were significantly associated with epilepsy and its subtypes. A mediating role for cytokines has not been demonstrated. Sensitivity tests validated the primary MR analysis outcomes. Additionally, no reverse causality was detected between significant GMs and epilepsy. Of the mapped genes of notable GMs, genes like BLK, FDFT1, DOK2, FAM167A, ZSCAN9, RNGTT, RBM47, DNAJC21, SUMF1, TCF20, GLO1, TMTC1, VAV2, and RNF14 exhibited a profound correlation with the risk factors of epilepsy subtypes.ConclusionOur research validates the causal role of GMs and cytokines in various epilepsy subtypes, and there has been no evidence that cytokines play a mediating role between GM and epilepsy. This could provide fresh perspectives for the prevention and treatment of epilepsy.

Edge-wise analysis reveals white matter connectivity associated with focal to bilateral tonic-clonic seizures.

Focal to bilateral tonic-clonic seizures (FBTCS) represent a challenging subtype of focal temporal lobe epilepsy (TLE) in terms of both severity and treatment response. Most studies have focused on regional brain analysis that is agnostic to the distribution of white matter (WM) pathways associated with a node. We implemented a more selective, edge-wise approach that allowed for identification of the individual connections unique to FBTCS. T1-weighted and diffusion-weighted images were obtained from 22 patients with solely focal seizures (FS), 43 FBTCS patients, and 65 age/sex-matched healthy participants (HPs), yielding streamline (STR) connectome matrices. We used diffusion tensor-derived STRs in an edge-wise approach to determine specific structural connectivity changes associated with seizure generalization in FBTCS compared to matched FS and HPs. Graph theory metrics were computed on both node- and edge-based connectivity matrices. Edge-wise analyses demonstrated that all significantly abnormal cross-hemispheric connections belonged to the FBTCS group. Abnormal connections associated with FBTCS were mostly housed in the contralateral hemisphere, with graph metric values generally decreased compared to HPs. In FBTCS, the contralateral amygdala showed selective decreases in the structural connection pathways to the contralateral frontal lobe. Abnormal connections in TLE involved the amygdala, with the ipsilateral side showing increases and the contralateral decreases. All the FS findings indicated higher graph metrics for connections involving the ipsilateral amygdala. Data also showed that some FBTCS connectivity effects are moderated by aging, recent seizure frequency, and longer illness duration. Data showed that not all STR pathways are equally affected by the seizure propagation of FBTCS. We demonstrated two key biases, one indicating a large role for the amygdala in the propagation of seizures, the other pointing to the prominent role of cross-hemispheric and contralateral hemisphere connections in FBTCS. We demonstrated topographic reorganization in FBTCS, pointing to the specific WM tracts involved.

Genetic causal association between physical activities and epilepsy: A Mendelian randomization study.

Despite numerous investigations into the relationship between physical activities (PA) and epilepsy, the causal effects remain contentious. Thus, we conducted a two-sample Mendelian randomization (MR) study to assess the potential causality. Single-nucleotide polymorphisms (SNPs) predisposed to self-reported moderate and vigorous physical activities (MPA and VPA) and overall acceleration average (OAA) calculated through wrist-worn accelerometers were selected as exposure instrumental variables. Five subtypes of epilepsy, including all epilepsy, focal epilepsy and generalized epilepsy (with or without each other), focal epilepsy-strict definition and generalized epilepsy-strict definition (without overlap), were chosen as the outcomes. The MR study utilized the inverse-variance weighted (IVW) method as the primary analytical tool, supplemented by MR-Egger, simple mode, weighted mode, and weighted median methods. Cochran's Q and MR-Egger intercept tests were employed to assess heterogeneity and pleiotropy, while MR pleiotropy residual sum and outlier and leave-one-out analyses were conducted to identify potential SNP outliers. The study indicated that OAA was genetically linked to a decreased risk of both focal epilepsy (OR=0.812, 95% CI: 0.687-0.960, p=.015, IVW) and focal epilepsy-strict definition (OR=0.732, 95% CI: 0.596-0.900, p=.003, IVW; OR=0.749, 95% CI: 0.573-0.979, p=.035, Weighted median). Genetically predicted MPA and VPA did not exhibit a causal association with all epilepsy or its subtypes (p>.05). No evidence of heterogeneity, pleiotropy, or SNP outlier was observed. Our findings suggested that PA with accelerometer monitoring may potentially reduce the risk of focal epilepsy, while there is no evidence supporting causal association between self-reported MPA or VPA and either focal or generalized epilepsy.

Dimeric structures of DNA ATTTC repeats promoted by divalent cations.

Structural studies of repetitive DNA sequences may provide insights why and how certain repeat instabilities in their number and nucleotide sequence are managed or even required for normal cell physiology, while genomic variability associated with repeat expansions may also be disease-causing. The pentanucleotide ATTTC repeats occur in hundreds of genes important for various cellular processes, while their insertion and expansion in noncoding regions are associated with neurodegeneration, particularly with subtypes of spinocerebellar ataxia and familial adult myoclonic epilepsy. We describe a new striking domain-swapped DNA-DNA interaction triggered by the addition of divalent cations, including Mg2+ and Ca2+. The results of NMR characterization of d(ATTTC)3 in solution show that the oligonucleotide folds into a novel 3D architecture with two central C:C+ base pairs sandwiched between a couple of T:T base pairs. This structural element, referred to here as the TCCTzip, is characterized by intercalative hydrogen-bonding, while the nucleobase moieties are poorly stacked. The 5'- and 3'-ends of TCCTzip motif are connected by stem-loop segments characterized by A:T base pairs and stacking interactions. Insights embodied in the non-canonical DNA structure are expected to advance our understanding of why only certain pyrimidine-rich DNA repeats appear to be pathogenic, while others can occur in the human genome without any harmful consequences.

Altered static and dynamic functional connectivity of the default mode network across epilepsy subtypes in children: A resting-state fMRI study

BackgroundEpilepsy is a chronic neurologic disorder characterized by abnormal functioning of brain networks, making it a complex research topic. Recent advancements in neuroimaging technology offer an effective approach to unraveling the intricacies of the human brain. Within different types of epilepsy, there is growing recognition regarding ongoing changes in the default mode network (DMN). However, little is known about the shared and distinct alterations of static functional connectivity (sFC) and dynamic functional connectivity (dFC) in DMN among epileptic subtypes, especially in children with epilepsy. MethodsHere, 110 children with epilepsy at a single center, including idiopathic generalized epilepsy (IGE), frontal lobe epilepsy (FLE), temporal lobe epilepsy (TLE), and parietal lobe epilepsy (PLE), as well as 84 healthy controls (HC) underwent resting-state functional magnetic resonance imaging (fMRI) scan. We investigated both sFC and dFC between groups of the DMN. ResultsDecreased static and dynamic connectivity within the DMN subsystem were shared by all subtypes. In each epilepsy subtype, children with epilepsy displayed significant and distinct patterns of DMN connectivity compared to the control group: the IGE group showed reduced interhemispheric connectivity, the FLE group consistently demonstrated disturbances in frontal region connectivity, the TLE group exhibited significant disruptions in hippocampal connectivity, and the PLE group displayed a notable decrease in parietal-temporal connectivity within the DMN. Some state-specific FC disruptions (decreased dFC) were observed in each epilepsy subtype that cannot detect by sFC. To determine their uniqueness within specific subtypes, bootstrapping methods were employed and found the significant results (IGE: between PCC and bilateral precuneus, FLE: between right middle frontal gyrus and bilateral middle temporal gyrus, TLE: between left Hippocampus and right fusiform, PLE: between left angular and cingulate cortex). Furthermore, only children with IGE exhibited dynamic features associated with clinical variables. ConclusionsOur findings highlight both shared and distinct FC alterations within the DMN in children with different types of epilepsy. Furthermore, our work provides a novel perspective on the functional alterations in the DMN of pediatric patients, suggesting that combined sFC and dFC analysis can provide valuable insights for deepening our understanding of the neuronal mechanism underlying epilepsy in children.

Choroid and Retinal Effects of Epilepsy and Epilepsy Subgroups.

The objective were to evaluate structural alterations in the retina and choroid tissue of epilepsy patients and subtypes using enhanced depth imaging optic coherence tomography (EDI-OCT). 46 epilepsy patients and 50 sex- and age-matched control patients were analyzed in the study. Patients' epilepsy types were recorded. The central macular thickness (CMT), retinal nerve fiber layer (RNFL), ganglion cell layer (GCL), and choroidal thickness (CT) were investigated through the Spectralis-OCT device (SD-OCT). Image-J program was used to calculate the total choroidal area (TCA), the luminal area (LA), stromal area (SA), and the choroidal vascularity index (CVI). CMT, TCA, LA, and SA outcomes were substantially reduced in epilepsy patients than in healthy controls. There was no significant difference between CT, RNFL, GCL, CVI results. There were no statistically significant differences between patients with partial and generalized epilepsy (p>0.05 for each). According to the results of our study, epilepsy disease has effects on the posterior segment of the eye. To the best of our knowledge, our study is the first to evaluate CVI in patients with epilepsy and the epilepsy subgroups.

Spatiotemporal Microstate Dynamics of Spike-free Scalp EEG Offer a Potential Biomarker for Refractory Temporal Lobe Epilepsy.

Refractory temporal lobe epilepsy (TLE) is one of the most frequently observed subtypes of epilepsy and endangers more than 50 million people world-wide. Although electroencephalogram (EEG) had been widely recognized as a classic tool to screen and diagnose epilepsy, for many years it heavily relied on identifying epileptic discharges and epileptogenic zone localization, which however, limits the understanding of refractory epilepsy due to the network nature of this disease. This work hypothesizes that the microstate dynamics based on resting-state scalp EEG can offer an additional network depiction of the disease and provide potential complementary evaluation tool for the TLE even without detectable epileptic discharges on EEG. We propose a novel framework for EEG microstate spatial-temporal dynamics (EEG-MiSTD) analysis based on machine learning to comprehensively model millisecond-changing whole-brain network dynamics. With only 100 seconds of resting-state EEG even without epileptic discharges, this approach successfully distinguishes TLE patients from healthy controls and is related to the lateralization of epileptic focus. Besides, microstate temporal and spatial features are found to be widely related to clinical parameters, which further demonstrate that TLE is a network disease. A preliminary exploration suggests that the spatial topography is sensitive to the following surgical outcomes. From such a new perspective, our results suggest that spatiotemporal microstate dynamics is potentially a biomarker of the disease. The developed EEG-MiSTD framework can probably be considered as a general tool to examine dynamical brain network disruption in a user-friendly way for other types of epilepsy.