Personalized translational epilepsy research - Novel approaches and future perspectives: Part I: Clinical and network analysis approaches

Demographic and clinical characteristics, seizure disorders, and antiepileptic drug usage in different types of corpus callosum disorders: a comparative study in children

BACKGROUND

This study aimed to investigate the demographic and clinical characteristics, types of seizure disorders, and antiepileptic drug usage among individuals with different types of corpus callosum disorders.

METHODS

A total of 73 individuals were included in the study and divided into three groups based on the type of corpus callosum abnormality: hypoplasia (H), agenesis (A), and dysgenesis (D). Demographic data, including gender and preterm birth, as well as clinical characteristics such as seizure disorders, attention deficit hyperactivity disorder (ADHD), severe developmental delay/intellectual disability, and other brain malformations, were analyzed. The types of seizure disorders and antiepileptic drugs used were also examined.

RESULTS

The H group had the highest number of participants (n = 47), followed by the A group (n = 11) and the D group (n = 15). The A group had the highest percentage of males and preterm births, while the D group had the highest percentage of seizure disorders, other brain malformations, and severe developmental delay/intellectual disability. The A group also had the highest percentage of ADHD. Focal seizures were observed in all three groups, with the highest proportion in the A group. Focal impaired awareness seizures (FIAS) were present in all groups, with the highest proportion in the D group. Generalized tonic-clonic seizures (GTCS) were observed in all groups, with the highest proportion in the H group. Different types of antiepileptic drugs were used among the groups, with variations in usage rates for each drug.

CONCLUSION

This study provided insights into the demographic and clinical characteristics, seizure disorders, and antiepileptic drug usage among individuals with different types of corpus callosum disorders. Significant differences were found between the groups, indicating the need for tailored management approaches. However, the study has limitations, including a small sample size and a cross-sectional design. Further research with larger sample sizes and longitudinal designs is warranted to validate these findings and explore the relationship between corpus callosum abnormality severity and clinical outcomes.

Personalized dynamic network models of the human brain as a future tool for planning and optimizing epilepsy therapy

Epilepsy is a common neurological disorder, with one third of patients not responding to currently available antiepileptic drugs. The proportion of pharmacoresistant epilepsies has remained unchanged for many decades. To cure epilepsy and control seizures requires a paradigm shift in the development of new approaches to epilepsy diagnosis and treatment. Contemporary medicine has benefited from the exponential growth of computational modeling, and the application of network dynamics theory to understanding and treating human brain disorders. In epilepsy, the introduction of these approaches has led to personalized epileptic network modeling that can explore the patient's seizure genesis and predict the functional impact of resection on its individual network's propensity to seize. The application of the dynamic systems approach to neurostimulation therapy of epilepsy allows designing stimulation strategies that consider the patient's seizure dynamics and long-term fluctuations in the stability of their epileptic networks. In this article, we review, in a nontechnical fashion suitable for a broad neuroscientific audience, recent progress in personalized dynamic brain network modeling that is shaping the future approach to the diagnosis and treatment of epilepsy.

Computational modeling allows unsupervised classification of epileptic brain states across species

Current advances in epilepsy treatment aim to personalize and responsively adjust treatment parameters to overcome patient heterogeneity in treatment efficiency. For tailoring treatment to the individual and the current brain state, tools are required that help to identify the patient- and time-point-specific parameters of epilepsy. Computational modeling has long proven its utility in gaining mechanistic insight. Recently, the technique has been introduced as a diagnostic tool to predict individual treatment outcomes. In this article, the Wendling model, an established computational model of epilepsy dynamics, is used to automatically classify epileptic brain states in intracranial EEG from patients (n = 4) and local field potential recordings from in vitro rat data (high-potassium model of epilepsy, n = 3). Five-second signal segments are classified to four types of brain state in epilepsy (interictal, preonset, onset, ictal) by comparing a vector of signal features for each data segment to four prototypical feature vectors obtained by Wendling model simulations. The classification result is validated against expert visual assessment. Model-driven brain state classification achieved a classification performance significantly above chance level (mean sensitivity 0.99 on model data, 0.77 on rat data, 0.56 on human data in a four-way classification task). Model-driven prototypes showed similarity with data-driven prototypes, which we obtained from real data for rats and humans. Our results indicate similar electrophysiological patterns of epileptic states in the human brain and the animal model that are well-reproduced by the computational model, and captured by a key set of signal features, enabling fully automated and unsupervised brain state classification in epilepsy.

The relationship between memory and quality of life is mediated by trait anxiety in patients with temporal lobe epilepsy

PURPOSE

Memory deficits are very frequent in patients with drug-resistant epilepsy, but they predict a small proportion of variance of their quality of life (QOL) in previous studies, possibly due to the lack of consideration of mediating factors of this relationship. This study aimed to examine whether trait anxiety mediates the relationship between memory and QOL in this population, controlling the influence of demographic and seizure-related factors.

METHODS

In this cross-sectional study, 119 adults with drug-resistant temporal lobe epilepsy (TLE) underwent a neuropsychological evaluation, in which memory, anxiety, and QOL were assessed.

RESULTS

In the total sample, better delayed memory had an effect on better QOL indirectly through lower trait anxiety (B = 0.13, SE = 0.06, p = 0.04, ab_cs = 0.13; κ² = 0.18; PM_ind = 0.76). Additionally, delayed memory has not a direct association with QOL (B = 0.04, SE = 0.09, p = 0.64, Cohen's f ² = 0.005; PM_dir = 0.24), and the total effect of delayed memory on QOL tended to reach statistical significance (B = 0.17, SE = 0.10, p = 0.08). The proposed mediation model yielded excellent fit (CFI = 1.00, RMSEA = 0.0001, SRMR = 0.009, and χ² (1) = 0.50, p = 0.48) and explained 38% of the variance of QOL.

CONCLUSION

These findings suggest that trait anxiety is an important factor in understanding the relationship between memory and QOL in patients with TLE, considering the influence of demographic and seizure-related variables, and may have relevant implications for decision-making in this population.

The neurovasculature as a target in temporal lobe epilepsy

The blood-brain barrier (BBB) is a physiological barrier maintaining a specialized brain micromilieu that is necessary for proper neuronal function. Endothelial tight junctions and specific transcellular/efflux transport systems provide a protective barrier against toxins, pathogens, and immune cells. The barrier function is critically supported by other cell types of the neurovascular unit, including pericytes, astrocytes, microglia, and interneurons. The dysfunctionality of the BBB is a hallmark of neurological diseases, such as ischemia, brain tumors, neurodegenerative diseases, infections, and autoimmune neuroinflammatory disorders. Moreover, BBB dysfunction is critically involved in epilepsy, a brain disorder characterized by spontaneously occurring seizures because of abnormally synchronized neuronal activity. While resistance to antiseizure drugs that aim to reduce neuronal hyperexcitability remains a clinical challenge, drugs targeting the neurovasculature in epilepsy patients have not been explored. The use of novel imaging techniques permits early detection of BBB leakage in epilepsy; however, the detailed mechanistic understanding of causes and consequences of BBB compromise remains unknown. Here, we discuss the current knowledge of BBB involvement in temporal lobe epilepsy with the emphasis on the neurovasculature as a therapeutic target.

Trends in antiseizure medication prescription patterns among all adults, women, and older adults with epilepsy: A German longitudinal analysis from 2008 to 2020

INTRODUCTION

The prescription patterns of antiseizure medication (ASM) are subject to new scientific evidence and sociodemographic and practical aspects. This study analyzed trends in ASM prescription patterns among all adults with epilepsy, with special consideration for women of childbearing potential (WOCBP) and older adult (≥65 years old) patients.

METHODS

Data from four questionnaire-based cohort studies, conducted in 2008, 2013, 2016, and 2020, were analyzed for ASM prescription frequencies and common mono- and dual therapy regimens. Statistical comparisons were performed with the Chi-square test and one-way analysis of variance.

RESULTS

Overall, the individual prescription patterns among 1,642 adult patients with epilepsy were analyzed. A significant increase in the prescription frequency of third-generation ASMs, from 59.3% to 84.2% (p = 0.004), was accompanied by a decrease in the frequency of first- and second-generation ASMs (5.4% to 2.1% and 34.9% to 12.6%, respectively). This trend was accompanied by a significant decrease in the use of enzyme-inducing ASMs, from 23.9% to 4.6% (p = 0.004). Among frequently prescribed ASMs, prescriptions of carbamazepine (18.6% to 3.1%, p = 0.004) and valproate (15.4% to 8.7%, p = 0.004) decreased, whereas prescriptions of levetiracetam (18.0% up to 32.4%, p = 0.004) increased significantly. The prescription frequency of lamotrigine remained largely constant at approximately 20% (p = 0.859). Among WOCBP, the prescription frequencies of carbamazepine (11.4% to 2.0%, p = 0.004) and valproate (16.1% to 6.1%, p = 0.004) decreased significantly. Levetiracetam monotherapy prescriptions increased significantly (6.6% to 30.4%, p = 0.004) for WOCBP, whereas lamotrigine prescriptions remained consistent (37.7% to 44.9%, p = 0.911). Among older adult patients, a significant decrease in carbamazepine prescriptions (30.1% to 7.8%, p = 0.025) was the only relevant change in ASM regimens between 2008 and 2020. In patients with genetic generalized epilepsies, levetiracetam was frequently used as an off-label monotherapy (25.0% to 35.3%).

CONCLUSION

These results show a clear trend toward the use of newer and less interacting third-generation ASMs, with lamotrigine, levetiracetam, and lacosamide representing the current ASMs of choice, displacing valproate and carbamazepine over the last decade. In WOCBP, prescription patterns shifted to minimize teratogenic effects, whereas, among older adults, the decrease in carbamazepine use may reflect the avoidance of hyponatremia risks and attempts to reduce the interaction potential with other drugs and ASMs. Levetiracetam is frequently used off-label as a monotherapy in patients with genetic generalized epilepsy.

EuroQOL-5D-3L does not adequately map quality-of-life deterioration in severely affected patients with epilepsy

INTRODUCTION

The steadily increasing impact of health-related quality of life (HRQOL) on reasonable diagnostic and therapeutic decisions makes the correct mapping of HRQOL indispensable in modern epileptology. The aim of this study was to address the reliability of the often-used generic HRQOL screening questionnaire EuroQOL 5-dimension, 3-level (EQ-5D-3L) by comparing its normalized index value (calculated via the time trade-off method) and visual analog scale (VAS) to the gold standard of the extensive Quality of Life in Epilepsy Inventory (QOLIE-31). QOLIE-10 scores were compared with the extensive QOLIE-31 and EQ-5D-3L TTO.

METHODS

We conducted a retrospective analysis of a monocentric study of 184 patients with epilepsy. Bivariate Spearman correlation analysis and Fisher's r-to-z transformation were used to compare the strengths of correlations of EQ-5D-3L, QOLIE-10 and QOLIE-31 with different epilepsy-specific domains (disease severity, drug interactions, emotional well-being, stigmatization, seizure-related anxiety, cognitive impairment).

RESULTS

The different metrics of EQ-5D-3L, QOLIE-10 and QOLIE-31 showed moderate to very strong intra- and inter-metric correlations for overall HRQOL. Quality of Life in Epilepsy Inventory-31 VAS and EQ-5D-3L VAS did not show any significantly different strengths of correlations with respect to the domains studied. In contrast, the correlation strength of the normalized EQ-5D-3L index value differed significantly from the QOLIE-31 T-score for several domains, for example, for drug-related adverse events, neuropsychological deficits, symptoms of depression and seizure worry. In seizure-free patients, EQ-5D-3L VAS and EQ-5D-3L index values correlated significantly less with the domain of "cognitive impairment" than the QOLIE-31 T-score. In patients without relevant neuropsychological deficits, the strengths of correlations with the assessed domains did not differ significantly between EQ-5D-3L metrics and the QOLIE-31 T-score. The HRQOL mapping probability of QOLIE-10 was inferior to QOLIE-31 and comparable to EQ-5D-3L regarding the analyzed domains.

CONCLUSION

In contrast to the EQ-5D-3L VAS, EQ-5D-3L index values do not adequately map health-related quality of life in severely affected patients with epilepsy and therefore should not be used as screening tools. The QOLIE-31 T-score remains the gold standard for HRQOL assessment in patients with epilepsy.

Investigation of the Roles of New Antiepileptic Drugs and Serum BDNF Levels in Efficacy and Safety Monitoring and Quality of Life: A Clinical Research

Objective: We aimed to determine the therapeutic drug monitoring (TDM) features and the relation to Brain-Derived Neurotrophic Factor (BDNF) of frequently used new antiepileptic drugs (NADs) including lamotrigine (LTG), oxcarbazepine (OXC), zonisamide (ZNS) and lacosamide (LCM). Moreover, we investigated their effect on the quality of life (QoL).

Methods: Eighty epileptic patients who had been using the NADs, and thirteen healthy participants were included in this cross-sectional study. The participants were randomized into groups. The QOLIE-31 test was used for the assessment of QoL. We also prepared and applied “Safety Test”. HPLC method for TDM, and ELISA method for BDNF measurements were used consecutively.

Results: In comparison to healthy participants, epileptic participants had lower marriage rate (p=0.049), education level (p˂0.001), alcohol use (p=0.002). BDNF levels were higher in patients with focal epilepsy (p=0.013) and in those with higher education level (p=0.016). There were negative correlations between serum BDNF levels and serum ZNS levels (p=0.042) with LTG-polytherapy, serum MHD levels (a 10-monohydroxy derivative of OXC, p=0.041) with OXC-monotherapy. There was no difference in BDNF according to monotherapy-polytherapy, drug-resistant groups, regarding seizure frequency. There was a positive correlation between total health status and QoL (p˂0.001). QOLIE-31 overall score (OS) was higher in those with OXC-monotherapy (76.5±14.5). OS (p˂0.001), seizure worry (SW, p=0.004), cognition (C, p˂0.001), social function (SF, p˂0.001) were different in the main groups. Forgetfulness was the most common unwanted effect.

Conclusion: While TDM helps the clinician to use more effective and safe NADs, BDNF may assist in TDM for reaching the therapeutic target in epilepsy.

Wada test results contribute to the prediction of change in verbal learning and verbal memory function after temporal lobe epilepsy surgery

In recent years, the clinical usefulness of the Wada test (WT) has been debated among researchers in the field. Therefore, we aimed to assess its contribution to the prediction of change in verbal learning and verbal memory function after epilepsy surgery. Data from 56 patients with temporal lobe epilepsy who underwent WT and subsequent surgery were analyzed retrospectively. Additionally, a standard neuropsychological assessment evaluating attentional, learning and memory, visuospatial, language, and executive function was performed both before and 12 months after surgery. Hierarchical linear regression analyses were used to determine the incremental value of WT results over socio-demographic, clinical, and neuropsychological characteristics in predicting postsurgical change in patients' verbal learning and verbal memory function. The incorporation of WT results significantly improved the prediction models of postsurgical change in verbal learning (∆R2 = 0.233, p = .032) and verbal memory function (∆R2 = 0.386, p = .005). Presurgical performance and WT scores accounted for 41.8% of the variance in postsurgical change in verbal learning function, and 51.1% of the variance in postsurgical change in verbal memory function. Our findings confirm that WT results are of significant incremental value for the prediction of postsurgical change in verbal learning and verbal memory function. Thus, the WT contributes to determining the risks of epilepsy surgery and, therefore, remains an important part of the presurgical work-up of selected patients with clear clinical indications.

Everolimus als krankheitsspezifische Therapieoption bei mit tuberöser Sklerose assoziierter, therapierefraktärer Epilepsie – ein systematischer Überblick

Tuberöse Sklerose („tuberous sclerosis complex“ [TSC]) ist eine seltene genetische Erkrankung, die neben kutanen und viszeralen Organmanifestationen typischerweise bereits in einem sehr frühen Erkrankungsstadium mit einer schweren, meist therapierefraktären Epilepsie einhergeht. Aufgrund seiner direkten Wirkung am durch TSC dysregulierten mTOR-Signalweg sowie der synergistischen Effekte auf andere Organmanifestationen kommt das Rapamycin-Derivat Everolimus (EVE) zunehmend zur Anwendung. Ziel dieses systematischen Reviews ist, die Wirksamkeit, Sicherheit und Verträglichkeit von EVE bei Patienten mit TSC-assoziierter, therapierefraktärer Epilepsie aufzuarbeiten.

Neurostimulation stabilizes spiking neural networks by disrupting seizure-like oscillatory transitions

An improved understanding of the mechanisms underlying neuromodulatory approaches to mitigate seizure onset is needed to identify clinical targets for the treatment of epilepsy. Using a Wilson–Cowan-motivated network of inhibitory and excitatory populations, we examined the role played by intrinsic and extrinsic stimuli on the network’s predisposition to sudden transitions into oscillatory dynamics, similar to the transition to the seizure state. Our joint computational and mathematical analyses revealed that such stimuli, be they noisy or periodic in nature, exert a stabilizing influence on network responses, disrupting the development of such oscillations. Based on a combination of numerical simulations and mean-field analyses, our results suggest that high variance and/or high frequency stimulation waveforms can prevent multi-stability, a mathematical harbinger of sudden changes in network dynamics. By tuning the neurons’ responses to input, stimuli stabilize network dynamics away from these transitions. Furthermore, our research shows that such stabilization of neural activity occurs through a selective recruitment of inhibitory cells, providing a theoretical undergird for the known key role these cells play in both the healthy and diseased brain. Taken together, these findings provide new vistas on neuromodulatory approaches to stabilize neural microcircuit activity.

Ceftriaxone Treatment Affects EAAT2 Expression and Glutamatergic Neurotransmission and Exerts a Weak Anticonvulsant Effect in Young Rats

Epilepsy is a common neurological disorder. Despite the availability of a wide range of antiepileptic drugs, these are unsuccessful in preventing seizures in 20–30% of patients. Therefore, new pharmacological strategies are urgently required to control seizures. Modulation of glutamate uptake may have potential in the treatment of pharmacoresistant forms of epilepsy. Previous research showed that the antibiotic ceftriaxone (CTX) increased the expression and functional activity of excitatory amino acid transporter 2 (EAAT2) and exerted considerable anticonvulsant effects. However, other studies did not confirm a significant anticonvulsant effect of CTX administration. We investigated the impacts of CTX treatment on EAAT expression and glutamatergic neurotransmission, as well its anticonvulsant action, in young male Wistar rats. As shown by a quantitative real-time polymerase chain reaction (qPCR) assay and a Western blot analysis, the mRNA but not the protein level of EAAT2 increased in the hippocampus following CTX treatment. Repetitive CTX administration had only a mild anticonvulsant effect on pentylenetetrazol (PTZ)-induced convulsions in a maximal electroshock threshold test (MEST). CTX treatment did not affect the glutamatergic neurotransmission, including synaptic efficacy, short-term facilitation, or the summation of excitatory postsynaptic potentials (EPSPs) in the hippocampus and temporal cortex. However, it decreased the field EPSP (fEPSP) amplitudes evoked by intense electrical stimulation. In conclusion, in young rats, CTX treatment did not induce overexpression of EAAT2, therefore exerting only a weak antiseizure effect. Our data provide new insight into the effects of modulation of EAAT2 expression on brain functioning.

Predicting verbal memory decline following temporal lobe resection for epilepsy

OBJECTIVES

The aim of the study was to develop a prediction model for verbal memory decline after temporal lobe resection (TLR) for epilepsy. The model will be used in the preoperative counselling of patients to give individualized information about risk for verbal memory decline.

MATERIALS AND METHODS

A sample of 110 consecutive patients who underwent TLR for epilepsy at Sahlgrenska University Hospital between 1987 and 2011 constituted the basis for the prediction model. They had all gone through a formal neuropsychological assessment before surgery and 2 years after. Penalized regression and 20 × 10-fold cross-validation were used in order to build a reliable model for predicting individual risks.

RESULTS

The final model included four predictors: side of surgery; inclusion or not of the hippocampus in the resection; preoperative verbal memory function; and presence/absence of focal to bilateral tonic-clonic seizures (TCS) the last year prior to the presurgical investigation. The impact of a history of TCS is a new finding which we interpret as a sign of a more widespread network disease which influences neuropsychological function and the cognitive reserve. The model correctly identified 82% of patients with post-operative decline in verbal memory, and the overall accuracy was 70%-85% depending on choice of risk thresholds.

CONCLUSIONS

The model makes it possible to provide patients with individualized prediction regarding the risk of verbal memory decline following TLR. This will help them make more informed decisions regarding treatment, and it will also enable the epilepsy surgery team to prepare them better for the rehabilitation process.

General Trends in Prices and Prescription Patterns of Anticonvulsants in Germany between 2000 and 2017: Analysis of National and Cohort-Based Data

OBJECTIVE

Our aim was to explore trends in price evolution and prescription volumes of anticonvulsants (AEDs, antiepileptic drugs) in Germany between 2000 and 2017.

METHOD

This study used data from annual reports on mean prescription frequency and prices of defined daily doses (DDD) of AEDs in Germany to analyze nationwide trends. Interrupted time series (ITS) analysis was employed to test for significant effects of several statutory healthcare reforms in Germany on AED price evolution. These data were compared to cohort-based prescription patterns of four German cohort studies from 2003, 2008, 2013, and 2016 that included a total of 1368 patients with focal and generalized epilepsies.

RESULTS

Analysis of national prescription data between 2000 and 2017 showed that mean prices per DDD of third-generation AEDs decreased by 65% and mean prices of second-generation AEDs decreased by 36%, whereas mean prices of first-generation AEDs increased by 133%. Simultaneously, mean prescription frequency of third- generation AEDs increased by 2494%, while there was a substantial decrease in the use of first- (- 55%) and second- (- 16%) generation AEDs. ITS analysis revealed that in particular the introduction of mandatory rebates on drugs in 2003 affected prices of frequently used newer AEDs. These findings are consistent with data from cohort studies of epilepsy patients showing a general decrease of prices for frequently used AEDs in monotherapy by 62% and in combination therapies by 68%. The analysis suggests that overall expenses for AEDs remained stable despite an increase in the prescription of "newer" and "non-enzyme-inducing" AEDs for epilepsy patients.

CONCLUSION

Between 2000 and 2017, a distinct decline in AED prices can be observed that seems predominately caused by a governmentally obtained price decline of third- and second-generation drugs. These observations seem to be the result of a German statutory cost containment policy applied across all health-care sectors. The increasing use of third-generation AEDs to the disadvantage of "old" and "enzyme-inducing" AEDs reflects the preferences of physicians and patients with epilepsy and follows national treatment guidelines.

Analysis of EEG networks and their correlation with cognitive impairment in preschool children with epilepsy

OBJECTIVE

Cognitive impairment (CI) is common in children with epilepsy and can have devastating effects on their quality of life. Early identification of CI is a priority to improve outcomes, but the current gold standard of detection with psychometric assessment is resource intensive and not always available. This paper proposes exploiting network analysis techniques to characterize routine clinical electroencephalography (EEG) to help identify CI in children with early-onset epilepsy (CWEOE) (0-5 years old).

METHODS

Functional networks from routinely acquired EEGs of 51 newly diagnosed CWEOE were analyzed. Combinations of connectivity metrics with subnetwork analysis identified significant correlations between network properties and cognition scores via rank correlation analysis (Kendall's τ). Predictive properties were investigated using a cross-validated classification model with healthy cognition, mild/moderate CI, and severe CI classes.

RESULTS

Network analysis revealed phase-dependent connectivity having higher sensitivity to CI and significant functional network changes across EEG frequencies. Nearly 70.5% of CWEOE were aptly classified as having healthy cognition, mild/moderate CI, or severe CI using network features. These features predicted CI classes 55% better than chance and halved misclassification penalties.

CONCLUSIONS

Cognitive impairment in CWEOE can be detected with sensitivity at 85% (in identifying mild/moderate or severe CI) and specificity of 84%, by network analysis.

SIGNIFICANCE

This study outlines a data-driven methodology for identifying candidate biomarkers of CI in CWEOE from network features. Following additional replication, the proposed method and its use of routinely acquired EEG forms an attractive proposition for supporting clinical assessment of CI.