Circadian distribution of epileptiform discharges in epilepsy: candidate mechanisms of variability

Isabella Marinelli*, Jamie J. Walker, Udaya Seneviratne, Wendyl D’Souza, Mark J. Cook, Clare Anderson, Andrew Bagshaw, Stafford L. Lightman, Wessel Woldman, John Terry

*Corresponding author for this work

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Abstract

Epilepsy is a serious neurological disorder characterised by a tendency to have recurrent, spontaneous, seizures. Classically, seizures are assumed to occur at random. However, recent research has uncovered underlying rhythms both in seizures and in key signatures of epilepsy—so-called interictal epileptiform activity—with timescales that vary from hours and days through to months. Understanding the physiological mechanisms that determine these rhythmic patterns of epileptiform discharges remains an open question. Many people with epilepsy identify precipitants of their seizures, the most common of which include stress, sleep deprivation and fatigue. To quantify the impact of these physiological factors, we analysed 24-hour EEG recordings from a cohort of 107 people with idiopathic generalized epilepsy. We found two subgroups with distinct distributions of epileptiform discharges: one with highest incidence during sleep and the other during day-time. We interrogated these data using a mathematical model that describes the transitions between background and epileptiform activity in large-scale brain networks. This model was extended to include a time-dependent forcing term, where the excitability of nodes within the network could be modulated by other factors. We calibrated this forcing term using independently-collected human cortisol (the primary stress-responsive hormone characterised by circadian and ultradian patterns of secretion) data and sleep-staged EEG from healthy human participants. We found that either the dynamics of cortisol or sleep stage transition, or a combination of both, could explain most of the observed distributions of epileptiform discharges. Our findings provide conceptual evidence for the existence of underlying physiological drivers of rhythms of epileptiform discharges. These findings should motivate future research to explore these mechanisms in carefully designed experiments using animal models or people with epilepsy.
Original languageEnglish
Article numbere1010508
Number of pages19
JournalPLoS Computational Biology
Volume19
Issue number10
Early online date5 Oct 2023
DOIs
Publication statusPublished - 5 Oct 2023

Bibliographical note

Funding:
I.M. acknowledges the financial support from the University of Birmingham Dynamic Investment Fund. W.W. acknowledges the financial support of Epilepsy Research UK through an Emerging Leader Fellowship (F2002). J.R.T. acknowledges the financial support of the Engineering and Physical Sciences Research Council via Fellowship EP/T027703/1 and the National Institute for Health and Care Research via grant AI01646. J.J.W. acknowledges the financial support from the Medical Research Council via grant MR/N008936/1. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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