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Stress hormones are associated with multiday seizure cycles

Stirling, R. E.; Naim-Feil, J.; Grayden, D. B.; D'Souza, W. J.; Gordon, I.; Freestone, D.; Nurse, E. S.; Cook, M. J.; Karoly, P. J.

2025-06-13 neurology
10.1101/2025.06.11.25329394 medRxiv
Show abstract

It is well established that most people with epilepsy experience cyclical fluctuations in seizure susceptibility. These seizure patterns have been associated multiday oscillations in cortical excitability and autonomic changes, although the mechanistic drivers of these cycles are not well understood. In this study, we measured stress hormone levels at phases of seizure cycles to investigate the autonomic system as a possible co-oscillator with multiday cycles of seizure susceptibility. Thirteen participants with focal epilepsy were recruited for this longitudinal study. Participants reported seizures in an electronic diary for >6 months. 24 saliva samples were collected per person across two predicted high risk periods and two predicted low risk periods ("allocated risk"). Saliva samples were analysed for cortisol and dehydroepiandrosterone sulphate (DHEAS) levels. Linear mixed models were fitted to predict stress hormones with fixed effects: multiday seizure cycle (retrospective peak or trough), time of day, allocated risk, perceived stress scale score, and seizure occurrence around the saliva sample time. Participants recorded an average of 193 (SD = 158) seizures during the study period. 312 saliva samples were collected in total. Cortisol levels were significantly higher in the epilepsy cohort compared to the expected general population. On a group level, cortisol was significantly associated with fixed effects time of day and multiday seizure cycle, with cortisol levels heightened at multiday cycle peaks compared to troughs, particularly evident in the morning saliva samples. These results provide new insights into a possible mechanistic driver or co-oscillator of multiday seizure cycles in people with epilepsy, demonstrating that cortisol levels are higher at the peak of multiday cycles irrespective of seizure occurrence. The novel methodology presented in this work may be used to explore interactions between other biomolecules of interest and multiday seizure cycles.

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