Zmienny wpływ neurotransmiterów na epilepsję w zależności od stanu mózgu: model wyjaśniający dynamikę napadów i zmienność biomarkerów
State-Dependent Modulation of Neurotransmitter Systems in Epilepsy: A Mechanistic Framework for Seizure Dynamics and Biomarker Variability
W skrócie
Epilepsja to nie tylko stały zanik równowagi między pobudzeniem i hamowaniem w mózgu, ale zaburdzenie dynamiczne, w którym wiele czynników - sen, stres, stan zapalny i metabolizm - wpływa na skłonność do napadów. Badania pokazują, że działanie neurotransmiterów zmienia się w zależności od stanu mózgu pacjenta, co wyjaśnia, dlaczego te same objawy mogą przebiegać u różnych osób różnie i dlaczego leczenie nie zawsze działa tak samo. Takie podejście może pomóc lekarzom w opracowaniu lepszych sposobów monitorowania i leczenia epilepsji dostosowanych do indywidualnego pacjenta.
Oryginalny abstract (angielski)
Epilepsy is increasingly conceptualized as a disorder of dynamic network instability rather than a static imbalance between excitation and inhibition. However, substantial variability in seizure occurrence, clinical expression, and treatment response remains insufficiently explained by existing models. This narrative review examines how neurotransmitter systems contribute to seizure dynamics within a state-dependent framework, in which factors such as sleep-wake cycles, stress, inflammation, and metabolic conditions modulate network excitability. The review identified four key findings: neurotransmitter function in epilepsy is state-dependent rather than fixed; multiple physiological state modifiers shape seizure susceptibility; seizure termination is an active state-sensitive process; and biomarker performance depends on the prevailing brain state. Evidence from experimental and clinical studies indicates that neurotransmitter function is context-sensitive and interacts with molecular pathways, including ion channel function, synaptic plasticity, and neuromodulatory signaling. These interactions influence key stages of seizure dynamics, including initiation, propagation, and termination, and may differ across etiological categories of epilepsy. This perspective also helps explain the limited performance of static biomarkers, as they do not capture temporal variability in network states. Instead, state-sensitive markers and context-aware interpretations of electrophysiological and clinical data may provide more informative insights. Overall, integrating neurotransmitter mechanisms with dynamic brain states offers a more precise perspective on seizure variability and may support the development of individualized, state-aware approaches to epilepsy management.