Beyond Circadian Patterns: Mechanistic Insights into Sleep–Epilepsy Interactions and Therapeutic Implications
Abstract
1. Introduction: The Bidirectional Sleep–Epilepsy Nexus
2. Thalamocortical Networks: The Battleground Between Spindles and Spikes
2.1. Sleep Spindles as Guardians of Memory Consolidation
2.2. Epileptic Spikes as Circuit Hijackers
2.3. TRN: The Critical Hub
3. Sleep State-Dependent Seizure Susceptibility: The REM Sleep Paradox
3.1. Protective Power of REM Sleep
3.2. GABA-Mediated Inhibition During REM Sleep
3.3. Sleep Architecture Disruption in Epilepsy
4. Molecular Clock Mechanisms in Epilepsy
4.1. Circadian Clock Genes as Seizure Modulators
4.2. Circadian Control of Neuronal Excitability
4.3. Metabolic Rhythms and Seizure Susceptibility
5. Clinical Syndrome Spotlight: Paradigmatic Disorders
5.1. SHE: A Model Disorder
5.2. Idiopathic Generalized Epilepsy and Sleep Disruption
6. Therapeutic Innovations: Chronobiological Approaches
6.1. Precision Timing of Antiseizure Medications
6.2. Sleep Optimization Strategies
6.3. Novel Molecular Targets
6.4. Biomarker-Guided Interventions: The Immense Gap Between Data and the Clinic
- Sleep Spindles: While elegant measure of thalamocortical integrity [28], the use of spindles as clinical biomarkers is fundamentally a niche concept. It requires expert-led polysomnography, which is a costly and labor-intensive procedure that is unavailable to the vast majority of patients. Furthermore, the development of automated spindle-detection algorithms that are robust to artifacts and epileptiform activity endemic to clinical EEG remains a significant computational challenge. Without an inexpensive, scalable, and reliable method of detection, sleep spindles remain a powerful research tool but do not represent a common clinical tool.
- Circadian Biomarkers: Using wearables to guide chronotherapy is technologically feasible [108,109,110], but clinically and commercially stalled. The primary barrier is the lack of clear business cases for developing and validating these strategies. This requires pharmaceutical companies to fund complex and expensive trials to prove that the tailored dosing of their existing drugs is superior to standard regimens, a high-risk, low-reward proposition that few have pursued.
- Neurostimulation: Integrating chronobiological data into responsive neurostimulation devices is at the frontier of personalized therapy [111]. However, its relevance is restricted to a small fraction of the most refractory patients owing to the extreme cost and invasive nature of the therapy. The computational burden of analyzing continuous data streams from such devices is also immense, requiring a dedicated data science infrastructure. This will not be a scalable solution for epilepsy care in the near future.
7. Future Directions: Emerging Horizons
7.1. Personalized Chronotherapy
7.2. Sleep-Based Seizure Prediction
7.3. Gene Therapy: A Distant and Uncertain Horizon
8. Conclusions: From Seizure Suppression to Rhythm Restoration
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Abbreviations
REM | Rapid eye movement |
TRN | Thalamic reticular nucleus |
EEG | Electroencephalography |
BDNF | Brain-derived neurotropic factor |
SHE | Sleep-Related Hypermotor Epilepsy |
JME | Juvenile Myoclonic Epilepsy |
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Feature | Wakefulness | Non-REM Sleep | REM Sleep |
---|---|---|---|
Cortical EEG (Electroencephalography) Activity | Desynchronized, high frequency | Synchronized oscillations | Desynchronized, high-frequency (wakeful-like) |
Dominant Neurotransmitters | High cholinergic and monoaminergic tone | Reduced cholinergic and monoaminergic activity | High cholinergic; noradrenergic and serotonergic neurons silent |
Seizure Susceptibility | Relative seizure vulnerability | High; promotes seizure generation and propagation | Dramatically reduced; natural anticonvulsant state |
Motor Activity | Normal muscle tone | Reduced muscle tone | Muscle atonia (sleep paralysis) |
Reference | [37] | [36,37] | [38] |
Gene | Normal Function in Circadian Rhythm | Dysregulation and Role in Epilepsy | Reference |
---|---|---|---|
BMAL1 | Core positive regulator; heterodimerizes with CLOCK to activate target gene transcription | Decreased in temporal lobe epilepsy. Knockout lowers seizure threshold; gene has direct protective role | [51,52] |
CLOCK | Core positive regulator; heterodimerizes with BMAL1 to drive clock-controlled genes, including BDNF | Dysregulation disrupts CLOCK-BMAL1 complex, causing loss of circadian BDNF regulation in epilepsy | [51,53] |
PER2 | Core negative regulator in transcriptional–translational feedback loop; inhibits CLOCK/BMAL1 activity | Dysregulated following status epilepticus. Knockout increases seizure susceptibility; overexpression is protective | [51,54] |
CRY1/2 | Core negative regulators; inhibit CLOCK/BMAL1 activity with PER proteins in feedback loop | Dysregulation creates permissive environment for seizure generation and disrupts epileptic activity patterns | [51] |
Syndrome | Key Clinical Features | Primary Sleep-Related Characteristics | Proposed Underlying Mechanism |
---|---|---|---|
Sleep-related Hypermotor Epilepsy (SHE) | Complex hypermotor seizures arising exclusively from sleep | Seizures emerge from Stage N2 non-REM sleep. Timing coincides with periods when sleep spindles are most prominent | Genetic mutations in nicotinic acetylcholine receptor subunits |
Juvenile Myoclonic Epilepsy (JME) | Most common idiopathic generalized epilepsy syndrome; characterized by morning seizure clustering | Patients exhibit profound sleep architecture abnormalities, including reduced slow-wave sleep and fragmented sleep continuity. Seizures correlate with sleep-to-wake transition. Sleep deprivation is a potent seizure trigger | Fundamental alterations in sleep regulatory mechanisms |
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Kwon, K.; Lee, Y.; Kim, M.S. Beyond Circadian Patterns: Mechanistic Insights into Sleep–Epilepsy Interactions and Therapeutic Implications. Cells 2025, 14, 1331. https://doi.org/10.3390/cells14171331
Kwon K, Lee Y, Kim MS. Beyond Circadian Patterns: Mechanistic Insights into Sleep–Epilepsy Interactions and Therapeutic Implications. Cells. 2025; 14(17):1331. https://doi.org/10.3390/cells14171331
Chicago/Turabian StyleKwon, Kanghyun, Yoonsung Lee, and Man S. Kim. 2025. "Beyond Circadian Patterns: Mechanistic Insights into Sleep–Epilepsy Interactions and Therapeutic Implications" Cells 14, no. 17: 1331. https://doi.org/10.3390/cells14171331
APA StyleKwon, K., Lee, Y., & Kim, M. S. (2025). Beyond Circadian Patterns: Mechanistic Insights into Sleep–Epilepsy Interactions and Therapeutic Implications. Cells, 14(17), 1331. https://doi.org/10.3390/cells14171331