Blood biomarkers predictive of epilepsy after an acute stroke event.

OBJECTIVE: Blood biomarkers have not been widely investigated in poststroke epilepsy. In this study, we aimed to describe clinical factors and biomarkers present during acute stroke and analyze their association with the development of epilepsy at long term. METHODS: A panel of 14 blood biomarkers was evaluated in patients with ischemic and hemorrhagic stroke. Biomarkers were normalized and standardized using Z-scores. Stroke and epilepsy-related variables were also assessed: stroke severity, determined by National Institutes of Health Stroke Scale (NIHSS) score, stroke type and cause, time from stroke to onset of late seizures, and type of seizure. Multiple Cox regression models were used to identify clinical variables and biomarkers independently associated with epilepsy. RESULTS: From a cohort of 1115 patients, 895 patients were included. Mean ± standard deviation (SD) age was 72.0 ± 13.1 years, and 57.8% of patients were men. Fifty-one patients (5.7%) developed late seizures, with a median time to onset of 232 days (interquartile range [IQR] 86-491). NIHSS score ≥8 (P < .001, hazard ratio [HR] 4.013, 95% confidence interval [CI] 2.123-7.586) and a history of early onset seizures (P < .001, HR 4.038, 95% CI 1.802-9.045) were factors independently associated with a risk of developing epilepsy. Independent blood biomarkers predictive of epilepsy were high endostatin levels >1.203 (P = .046, HR 4.300, 95% CI 1.028-17.996) and low levels of heat shock 70 kDa protein-8 (Hsc70) <2.496 (P = .006, HR 3.795, 95% CI 1.476-9.760) and S100B <1.364 (P = .001, HR 2.955, 95% CI 1.534-5.491). The risk of epilepsy when these biomarkers were combined increased to 17%. The area under the receiver-operating characteristic (ROC) curve of the predictive model was stronger when clinical variables were combined with blood biomarkers (74.3%, 95% CI 65.2%-83.3%) than when they were used alone (68.9%, 95% CI 60.3%-77.6%). SIGNIFICANCE: Downregulated S100B and Hsc70 and upregulated endostatin may assist in prediction of poststroke epilepsy and may provide additional information to clinical risk factors. In addition, these data are hypothesis-generating for the epileptogenic process.

Vascular risk factors as independent predictors of neurocognitive impairments in patients with late-onset epilepsy who have small-vessel disease.

RATIONALE: Late-onset epilepsy is often accompanied by underlying cerebrovascular disease and has been associated with neurocognitive deficits even dementia, but the interrelation between them remains unknown. In this study, we aimed to explore the contribution of vascular-related and epilepsy-related factors on neurocognitive outcomes in a sample of late-onset epilepsy with history of cerebral small vessel disease. METHODS: In this retrospective cross-sectional study, a comprehensive neurocognitive assessment was performed in 25 patients aged >60 years with one or more unprovoked seizures and history of small-vessel disease. Raw scores of cognitive tests were transformed in T-scores and were grouped in 6 cognitive domains. Regression models were performed to explore the contribution of vascular risk factors (diabetes mellitus, arterial hypertension, dyslipidemia, and smoking habit) and epilepsy-related factors (drug-resistance, number of antiepileptic drugs, age at epilepsy onset, and epileptic focus localization). RESULTS: Diabetes (p = 0.03) and smoking habit (p = 0.05) were the best independent factors to predict attention performance; diabetes also predicted visual memory function (p = 0.02); gender was related to verbal memory performance (p = 0.04) and speed processing (p = 0.02). Age at onset predicted that executive function (p = 0.05); age (p = 0.01) and gender (p = 0.03) were the major contributors to language performance. Epilepsy-related variables did not predict any cognitive outcomes. CONCLUSIONS: Vascular risk factors and sociodemographic characteristics were the best predictors of cognitive outcomes in a sample of late-onset epilepsy with cerebral small-vessel disease. Epilepsy did not show influence on cognitive function. Longitudinal studies are necessary to clarify the relationship between vascular risk factors and epilepsy on progression of cognitive deterioration in patients with late-onset epilepsy. This article is part of the Special Issue "Seizures & Stroke".

Correlation of blood biomarkers with early-onset seizures after an acute stroke event.

INTRODUCTION: Blood biomarkers have not been widely studied in stroke-related seizures. In this study, we aimed to describe clinical factors and biomarkers present during acute stroke and to analyze their association with early-onset seizures. METHODS: We retrospectively evaluated a panel of 14 blood biomarkers in 1115 patients with ischemic and hemorrhagic stroke. Biomarkers were normalized and standardized using Z scores. We also recorded stroke and epilepsy-related variables, including stroke severity (National Institute of Health Stroke Scale [NIHSS] scores), type, and causes, time from onset of stroke to occurrence of early seizures, and type of seizure. Adjusted logistic regression models were built to identify clinical variables and biomarkers independently associated with early seizures. RESULTS: Mean ±â€¯standard deviation (SD) age was 72.3 ±â€¯13.2 years, and 56.8% of the patients were men. Thirty-eight patients (3.9%) developed early seizures with a median time to onset of 1 day (interquartile range (IQR), 0-4). A higher NIHSS score (odds ratio [OR] = 1.046; 95% confidence interval (CI): 1.001-1.094; p = 0.044) and hemorrhagic stroke (OR = 2.133; 95% CI: 1.010-4.504; p = 0.047) were independently associated with a greater risk of early seizures. Independent blood biomarkers predictive of early seizures were lower levels of tumor necrosis factor receptor 1 (TNF-R1) (<0.013) (p = 0.006; OR = 3.334; 95% CI: 1.414-7.864) and higher levels of neural cell adhesion molecule (NCAM) (>0.326) (p = 0.009; OR = 2.625; 95% CI: 1.271-5.420). The predictive power of the regression model was greater when clinical variables were combined with blood biomarkers (73.5%; 95% CI: 65.1%-81.9%) than when used alone (64%; 95% CI: 55%-72.9%). CONCLUSION: Higher NCAM and lower TNF-R1 levels may help predict the occurrence of early seizures. The combined use of these biomarkers and clinical variables could be useful for identifying patients at risk of seizures. This article is part of the Special Issue "Seizures & Stroke".

Effect of brivaracetam on the anger levels of epilepsy patients. A prospective open-labelled controlled study.

PURPOSE: The rate of brivaracetam-related behavioural adverse events is a current focus of discussion. This study aims to assess the effect of brivaracetam on anger levels in patients with epilepsy, adjusted by mood symptoms, history of psychiatric disorders and seizure response. METHOD: Prospective analysis of 37 patients assessed for anger levels (STAXI-2), depression-anxiety (HADS) and quality of life (QOLIE-10) before adjunctive brivaracetam treatment and reassessed 3-6 months later. A control group following the same protocol of assessment was used for 1:1 comparison. A high percentage of mood stabilisers were included in this control group. RESULTS: Brivaracetam was indicated for patients including focal onset (79%) and generalised epilepsies (21%). Nearly 60% of responders and no psychiatric adverse events were found. This was similar to controls. The overall results revealed that brivaracetam was assoiciated with better in anger levels, mood scores and quality of life at baseline. Prior use of levetiracetam or the presence of a psychiatric background did not influence the results. However, improvements in anger levels were seen in the brivaracetam responders. CONCLUSION: This study shows that brivaracetam is not associated with an increased level of anger in patients with either focal or generalised epilepsies in the absence of psychiatric comorbidity. However, an improvement in anger levels is possibly influenced by a good seizure response.

Study of the prevalence of familial autoimmune myasthenia gravis in a Spanish cohort.

BACKGROUND: Myasthenia gravis (MG) is an autoimmune disease caused by a failure of neuromuscular transmission. Familial clustering has been reported despiteMG usually manifesting as a sporadic condition presumed not to be inherited. Our study investigated the prevalence of FAMG in a Spanish cohort, characterizing their phenotype,antibody titres and thymus findings. MATERIAL/METHODS: We investigated the presence of familial cases in 462 MG patients, characterizing by age and MGFA class at debut, quantitative MG score, antibody titres, MGFA post-intervention status and thymus pathology. RESULTS: Sixteen cases from8 unrelated pedigrees were identified. The prevalence of FAMG caseswas 3.46%.Mean age at onset was 57.8 ± 17.4 years (range=23­82). Distribution at debut was: 6 ocular, 4 IIa, 4IIb, 1 IIIa and 1 IIIb. Thymoma was identified in two of the 7 thymectomized individuals. CONCLUSIONS: The prevalence of FAMG in Spain is similar to other populations. Post-intervention status did not differ from sporadic autoimmune MG. As in other neuromuscular disorders, phenotype and inheritance heterogeneity are present in FAMG. In addition to the interfamilial heterogeneity observed, members of the same family affected with FAMG may even present different ages of onset, severity and thymus involvement. Further studies are necessary to clarify the role of genetic risk factors in this form of autoimmune MG.

PFN1 mutations are also rare in the Catalan population with amyotrophic lateral sclerosis.

Evidence of genetic heterogeneity in ALS has been found, with at least 31 genes being identified to date as causing ALS, and other genes being suggested as risk factors for susceptibility to the disease and for phenotype modifications. In recent years, new molecular genetic methodologies, especially GWAS and exome sequencing, have contributed to the identification of new ALS genes. Some of these genes (SOD1, TARDBP, FUS, and C9orf72) have homogenous frequencies in different populations. However, a few genes are rare in populations other than those in which they were first identified. Here we investigate the frequency of the PFN1 gene in a Catalan ALS population. A mutational analysis of the PFN1 gene was carried out on a Catalan cohort of 42 ALS families (FALS) and 423 sporadic ALS patients (SALS). The screening included 600 healthy controls. No PFN1 mutations were identified in either the FALS or SALS group. We also found no mutations in the control group. Our results are consistent with those described in other populations with very low frequencies, suggesting that PFN1 is a very rare cause of ALS worldwide. Together with the absence of a distinctive phenotype associated with ALS18, these results mean that this gene should be a second or third line for inclusion in screening in patients requesting genetic counseling.