Not knowing when the next seizure will occur is a constant burden and a factual danger for patients suffering from epilepsy. If it becomes possible to anticipate times of high versus low risk for seizure at the individual level this will greatly impact the quality of life of people living with epilepsy.
Knowing the timing of seizures could change patients’ lives
Epilepsy is characterized by the recurrence of seizures caused by a sudden surge of abnormal brain activity. It is a hampering condition, especially for people with epilepsies that are resistant to medication (30-40% of cases) for whom it is currently impossible to predict the timing of the next seizure. In addition to the suffering and accident risk from the seizures, their unpredictability causes a permanent uncertainty often leading to a high stress level, anxiety, and depression.
With the help of constant, long-term measuring of the electrical signals of the brain (by electroencephalography, EEG), Maxime Baud and colleagues were able to detect a certain rhythmicity in the occurrence of seizures that was patient specific [1]. Seizures followed a circadian pattern, occurring at preferred day- or night-times or came in clusters with a few days’ interval (multidien pattern). As part of a bigger vision to understand the rhythmic recurrence of seizures at different time scales, this project seeks to identify the key factors (brain activity, hormonal cycles) underlying the day-night epileptic cycles at the individual level and use these measures to forecast the risk of seizure [2].
The project builds on outstanding prior science using several empirical techniques and involves different labs in order to address the desired question. The approach in this project will combine knowledge from neuroscience (electrophysiology, optogenetics), endocrinology, machine learning, statistical modelling, and has the potential to provide new directions and accelerate epilepsy research. The existing strong links to the Wyss Centre for Neurotechnology Geneva promise high potential for clinical translation of the long-term brain monitoring.
If the underlying mechanisms responsible for the cycles of seizure recurrence could be unravelled, this could lead to tools able to forecast individual risk for seizures and pave the road for new therapeutic options that help the people with the disorder to better manage their seizures. Patients informed about their individual seizure cycles are empowered to organize their daily life around the rare but life-threatening events.
[1] Baud, M.O., Kleen, J.K., Mirro, E.A. et al. Multi-day rhythms modulate seizure risk in epilepsy. Nat Commun 9, 88 (2018). DOI: 10.1038/s41467-017-02577-y
[2] Proix, T . , Truccolo W., Leguia, MG, Tcheng, TK, King-Stephens, D, Rao, V, Baud, MO. Forecasting seizure risk in adults with focal epilepsy: a development and validation study. The Lancet Neurology 20, 2, pp. 127-135 (2021). 10.1016/s1474-4422(20)30396-3
