Chronobiology of epilepsy and sudden unexpected death in epilepsy

MK-212 precipitates seizure-induced death in amygdala-kindled mice via a non-5-HT2C receptor-mediated mechanism

Epilepsy is a common neurological condition that affects over 65 million people worldwide. Despite an increasing number of anti-seizure medications being made available, many patients do not find seizure freedom with medication. The leading cause of death in this refractory population is sudden unexpected death in epilepsy (SUDEP). Both human and animal research has implicated serotonin (5-HT) in modulating seizure proclivity, severity, and mortality. More recently, evidence has pointed to the 5-HT2C receptor as a salient target for investigating the mechanisms of seizure facilitation and mortality. Various seizures models have been used previously to assess the role of the 5-HT2C receptor in seizure expression and morphology. However, limbic kindling models have been underutilized in this endeavor. We used the selective 5-HT2C receptor agonist MK-212 to examine the effect of 5-HT2C receptor activation in amygdala kindled mice. C57BL/6J mice were instrumented with an EEG/EMG headmount and a bipolar electrode in the basolateral amygdala (BLA). The animals then received vehicle or MK-212 (10, 30 mg/kg) prior to seizure induction. 12.5% of WT animals that received 10 mg/kg MK-212 experienced seizure-induced respiratory arrest and died following seizure induction. When the dose was raised to 30 mg/kg, 100% of the animals succumbed following a seizure. These fatal seizures persisted when the same doses of MK-212 were administered to mice lacking the 5-HT2C receptor. This suggests that a non-5-HT2C mediated effect of MK-212 facilitates seizure-induced death in a dose-dependent manner. While amygdala kindling is not a model that is traditionally associated with seizure-induced death, these results suggest that there are circuits that, when recruited, will cause death following kindled seizures. Uncovering these circuits will both deepen our understanding of the amygdala kindling model and provide a new technique for researchers to test novel therapeutic interventions to lessen SUDEP risk.

Chronobiological Spatial Clusters of Cortical Regions in the Human Brain

PURPOSE

We demonstrate that different regions of the cerebral cortex have different diurnal rhythms of spontaneously occurring high-frequency oscillations (HFOs).

METHODS

High-frequency oscillations were assessed with standard-of-care stereotactic electroencephalography in patients with drug-resistant epilepsy. To ensure generalizability of our findings beyond patients with drug-resistant epilepsy, we excluded stereotactic electroencephalography electrode contacts lying within seizure-onset zones, epileptogenic lesions, having frequent epileptiform activity, and excessive artifact. For each patient, we evaluated twenty-four 5-minute stereotactic electroencephalography epochs, sampled hourly throughout the day, and obtained the HFO rate (number of HFOs/minute) in every stereotactic electroencephalography channel. We analyzed diurnal rhythms of the HFO rates with the cosinor model and clustered neuroanatomic parcels in a standard brain space based on similarity of their cosinor parameters. Finally, we compared overlap among resting-state networks, described in the neuroimaging literature, and chronobiological spatial clusters discovered by us.

RESULTS

We found five clusters that localized predominantly or exclusively to the left perisylvian, left perirolandic and left temporal, right perisylvian and right parietal, right frontal, and right insular-opercular cortices, respectively. These clusters were characterized by similarity of the HFO rates according to the time of the day. Also, these chronobiological spatial clusters preferentially overlapped with specific resting-state networks, particularly default mode network (clusters 1 and 3), frontoparietal network (cluster 1), visual network (cluster 1), and mesial temporal network (cluster 2).

CONCLUSIONS

This is probably the first human study to report clusters of cortical regions with similar diurnal rhythms of electrographic activity. Overlap with resting-state networks attests to their functional significance and has implications for understanding cognitive functions and epilepsy-related mortality.

More variable circadian rhythms in epilepsy captured by long-term heart rate recordings from wearable sensors

OBJECTIVE

The circadian rhythm synchronizes physiological and behavioral patterns with the 24-h light-dark cycle. Disruption to the circadian rhythm is linked to various health conditions, although optimal methods to describe these disruptions remain unclear. An emerging approach is to examine the intraindividual variability in measurable properties of the circadian rhythm over extended periods. Epileptic seizures are modulated by circadian rhythms, but the relevance of circadian rhythm disruption in epilepsy remains unexplored. Our study investigates intraindividual circadian variability in epilepsy and its relationship with seizures.

METHODS

We retrospectively analyzed >70 000 h of wearable smartwatch data (Fitbit) from 143 people with epilepsy (PWE) and 31 healthy controls. Circadian oscillations in heart rate time series were extracted, daily estimates of circadian period, acrophase, and amplitude properties were produced, and estimates of the intraindividual variability of these properties over an entire recording were calculated.

RESULTS

PWE exhibited greater intraindividual variability in period (76 vs. 57 min, d = .66, p < .001) and acrophase (64 vs. 48 min, d = .49, p = .004) compared to controls, but not in amplitude (2 beats per minute, d = -.15, p = .49). Variability in circadian properties showed no correlation with seizure frequency nor any differences between weeks with and without seizures.

SIGNIFICANCE

For the first time, we show that heart rate circadian rhythms are more variable in PWE, detectable via consumer wearable devices. However, no association with seizure frequency or occurrence was found, suggesting that this variability might be underpinned by the epilepsy etiology rather than being a seizure-driven effect.

Sleep links hippocampal propensity for epileptiform activity to its viscerosensory inputs

The development of a seizure relies on two factors. One is the existence of an overexcitable neuronal network and the other is a trigger that switches normal activity of that network into a paroxysmal state. While mechanisms of local overexcitation have been the focus of many studies, the process of triggering remains poorly understood. We suggest that, apart from the known exteroceptive sources of reflex epilepsy such as visual, auditory or olfactory signals, there is a range of interoceptive triggers, which are relevant for seizure development in Temporal Lobe Epilepsy (TLE). The hypothesis proposed here aims to explain the prevalence of epileptic activity in sleep and in drowsiness states and to provide a detailed mechanism of seizures triggered by interoceptive signals.

The hidden rhythms of epilepsy: exploring biological clocks and epileptic seizure dynamics

Epilepsy, characterized by recurrent seizures, is influenced by biological rhythms, such as circadian, seasonal, and menstrual cycles. These rhythms affect the frequency, severity, and timing of seizures, although the precise mechanisms underlying these associations remain unclear. This review examines the role of biological clocks, particularly the core circadian genes Bmal1, Clock, Per, and Cry, in regulating neuronal excitability and epilepsy susceptibility. We explore how the sleep-wake cycle, particularly non-rapid eye movement sleep, increases the risk of seizures, and discuss the circadian modulation of neurotransmitters like gamma-aminobutyric acid and glutamate. We explore clinical implications, including chronotherapy which refers to the practice of timing medical treatments to align with the body's natural biological rhythms, such as the circadian rhythm. Chronotherapy aligns anti-seizure medication administration with biological rhythms. We also discuss rhythm-based neuromodulation strategies, such as adaptive deep brain stimulation, which may dynamically change stimulation in response to predicted seizures in patients, provide additional therapeutic options. This review emphasizes the potential of integrating biological rhythm analysis into personalized epilepsy management, offering novel approaches to optimize treatment and improve patient outcomes. Future research should focus on understanding individual variability in seizure rhythms and harnessing technological innovations to enhance seizure prediction, precision treatment, and long-term management.

The spectrum of indications for ultralong-term EEG monitoring

PURPOSE

We assessed clinical cases to investigate the spectrum of indications for ultra-longterm EEG monitoring using a subcutaneous implantable device in adult patients with focal epilepsy.

METHODS

Electronic charts were reviewed from patients undergoing ultra-longterm recordings at the European Epilepsy centers Barcelona, Freiburg and Vienna. Specific patient settings approached in the three centers were analyzed, and the main clinical question was extracted. Results from recordings were analyzed based on the specific results and information obtained.

RESULTS

24 patients in whom ultra-longterm recordings were available were analyzed. A total of 11 main indications for subcutaneous long-term EEG recordings were identified, including the identification of active epilepsy in patients with low seizure frequency, under- and overreporting of patients, differentiation of non-epileptic from epileptic events, assessment of seizure severity, circadian and multidian rhythms of seizure occurrence, validation of treatment efficacy, improvement of patient-based reporting and medicolegal evidence for seizure freedom. This is reported with patient-specific case vignettes.

CONCLUSION

Ultra-longterm monitoring using subcutaneous implantable EEG devices can provide relevant diagnostic and treatment information in a large spectrum of clinical situations. This is discussed considering the intrinsic limitations of the method related to spatial coverage, sensitivity and validity as a biomarker of ongoing seizures.

Neural signal data collection and analysis of Percept™ PC BrainSense recordings for thalamic stimulation in epilepsy

Deep brain stimulation (DBS) using Medtronic's Percept™ PC implantable pulse generator is FDA-approved for treating Parkinson's disease (PD), essential tremor, dystonia, obsessive compulsive disorder, and epilepsy. Percept™ PC enables simultaneous recording of neural signals from the same lead used for stimulation. Many Percept™ PC sensing features were built with PD patients in mind, but these features are potentially useful to refine therapies for many different disease processes. When starting our ongoing epilepsy research study, we found it difficult to find detailed descriptions about these features and have compiled information from multiple sources to understand it as a tool, particularly for use in patients other than those with PD. Here we provide a tutorial for scientists and physicians interested in using Percept™ PC's features and provide examples of how neural time series data is often represented and saved. We address characteristics of the recorded signals and discuss Percept™ PC hardware and software capabilities in data pre-processing, signal filtering, and DBS lead performance. We explain the power spectrum of the data and how it is shaped by the filter response of Percept™ PC as well as the aliasing of the stimulation due to digitally sampling the data. We present Percept™ PC's ability to extract biomarkers that may be used to optimize stimulation therapy. We show how differences in lead type affects noise characteristics of the implanted leads from seven epilepsy patients enrolled in our clinical trial. Percept™ PC has sufficient signal-to-noise ratio, sampling capabilities, and stimulus artifact rejection for neural activity recording. Limitations in sampling rate, potential artifacts during stimulation, and shortening of battery life when monitoring neural activity at home were observed. Despite these limitations, Percept™ PC demonstrates potential as a useful tool for recording neural activity in order to optimize stimulation therapies to personalize treatment.

Imaging biomarkers of sleep-related hypermotor epilepsy and sudden unexpected death in epilepsy: a review

In recent years, imaging has emerged as a promising source of several intriguing biomarkers in epilepsy, due to the impressive growth of imaging technology, supported by methodological advances and integrations of post-processing techniques. Bearing in mind the mutually influencing connection between sleep and epilepsy, we focused on sleep-related hypermotor epilepsy (SHE) and sudden unexpected death in epilepsy (SUDEP), aiming to make order and clarify possible clinical utility of emerging multimodal imaging biomarkers of these two epilepsy-related entities commonly occurring during sleep. Regarding SHE, advanced structural techniques might soon emerge as a promising source of diagnostic and predictive biomarkers, tailoring a targeted therapeutic (surgical) approach for MRI-negative subjects. Functional and metabolic imaging may instead unveil SHE's extensive and night-related altered brain networks, providing insights into distinctions and similarities with non-epileptic sleep phenomena, such as parasomnias. SUDEP is considered a storm that strikes without warning signals, but objective subtle structural and functional alterations in autonomic, cardiorespiratory, and arousal centers are present in patients eventually experiencing SUDEP. These alterations could be seen both as susceptibility and diagnostic biomarkers of the underlying pathological ongoing loop ultimately ending in death. Finally, given that SHE and SUDEP are rare phenomena, most evidence on the topic is derived from small single-center experiences with scarcely comparable results, hampering the possibility of performing any meta-analytic approach. Multicenter, longitudinal, well-designed studies are strongly encouraged.

Vigilance and circadian function in daytime and nocturnal epilepsy compared to controls

BACKGROUND

People with epilepsy often experience daytime vigilance problems and fatigue. This may be related to disturbed sleep due to nocturnal seizures.

AIM

To compare subjective and objective markers of vigilance and circadian function in adults with epilepsy with nocturnal seizures to those with daytime seizures and healthy controls and to identify determinants of impaired daytime vigilance in epilepsy in an explorative study.

METHODS

We included 30 adults with epilepsy (15 with daytime seizures and 15 with nocturnal seizures), and 15 healthy controls. All participants filled out the Epworth sleepiness scale (ESS), fatigue severity scale (FSS), Pittsburgh sleep quality index (PSQI) and the Munich chronotype questionnaire (MCTQ). Each participant performed two trials of the sustained attention to response task (SART) as a measure of vigilance, and had a post-illumination pupil response (PIPR) assessment as a marker for the circadian function.

RESULTS

Both epilepsy groups reported more fatigue on the FSS than healthy controls (p < .001) and had higher SART error scores (p = .026). The poorer FSS and SART scores were most prominent among those with nocturnal seizures. The ESS, PSQI, MCTQ and the primary PIPR outcome did not differ between groups. Having nocturnal seizures (p = .010) and using more antiseizure medications (p = .004) were related to increased SART error scores.

CONCLUSIONS

Nocturnal epilepsy is associated with poorer vigilance, indicating lower quality of wake time. We could not relate this to circadian dysfunction. Further studies should focus on vigilance problems in people with nocturnal epilepsy and explore interventions to improve the quality of wake time.

Cyclical underreporting of seizures in patient-based seizure documentation

OBJECTIVE

Circadian and multidien cycles of seizure occurrence are increasingly discussed as to their biological underpinnings and in the context of seizure forecasting. This study analyzes if patient reported seizures provide valid data on such cyclical occurrence.

METHODS

We retrospectively studied if circadian cycles derived from patient-based reporting reflect the objective seizure documentation in 2003 patients undergoing in-patient video-EEG monitoring.

RESULTS

Only 24.1% of more than 29000 seizures documented were accompanied by patient notifications. There was cyclical underreporting of seizures with a maximum during nighttime, leading to significant deviations in the circadian distribution of seizures. Significant cyclical deviations were found for focal epilepsies originating from both, frontal and temporal lobes, and for different seizure types (in particular, focal unaware and focal to bilateral tonic-clonic seizures).

INTERPRETATION

Patient seizure diaries may reflect a cyclical reporting bias rather than the true circadian seizure distributions. Cyclical underreporting of seizures derived from patient-based reports alone may lead to suboptimal treatment schemes, to an underestimation of seizure-associated risks, and may pose problems for valid seizure forecasting. This finding strongly supports the use of objective measures to monitor cyclical distributions of seizures and for studies and treatment decisions based thereon.

Sudden unexpected death in epilepsy

PURPOSE OF REVIEW

Sudden unexpected death in epilepsy (SUDEP) is a leading cause of death in patients with epilepsy. This review highlights the recent literature regarding epidemiology on a global scale, putative mechanisms and thoughts towards intervention and prevention.

RECENT FINDINGS

Recently, numerous population-based studies have examined the incidence of SUDEP in many countries. Remarkably, incidence is quite consistent across these studies, and is commensurate with the recent estimates of about 1.2 per 1000 patient years. These studies further continue to support that incidence is similar across the ages and that comparable factors portend heightened risk for SUDEP. Fervent research in patients and animal studies continues to hone the understanding of potential mechanisms for SUDEP, especially those regarding seizure-induced respiratory dysregulation. Many of these studies and others have begun to lay out a path towards identification of improved treatment and prevention means. However, continued efforts are needed to educate medical professionals about SUDEP risk and the need to disclose this to patients.

SUMMARY

SUDEP is a devastating potential outcome of epilepsy. More is continually learned about risk and mechanisms from clinical and preclinical studies. This knowledge can hopefully be leveraged into preventive measures in the near future.