Evidence map›Paper›PMID 40668822›Full record

ArticlePLoS computational biology2025

Cardiogenic and chronobiological mechanisms in seizure-induced sinus arrhythmias.

Pan Li, Sangbo Lee, Kwang-Yeon Choi, Jonathan E Rubin, Jae Kyoung Kim

Abstract read
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Article in PLoS computational biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Pan LiBiomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, Republic of Korea.
Sangbo LeeDivision of Pediatric Neurology, Department of Pediatrics, Severance Children's Hospital, Epilepsy Research Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.
Kwang-Yeon ChoiDepartment of Psychiatry, College of Medicine, Chungnam National University, Daejeon, Republic of Korea.
Jonathan E RubinDepartment of Mathematics, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
Jae Kyoung KimBiomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon, Republic of Korea.ORCID 0000-0001-7842-2172

Funding

Institute for Basic Science IBS-R029-C3National Science Foundation DMS1951095
6 · The paper itself

Abstract

Seizure-induced cardiac arrhythmias, such as ictal (during seizure) or postictal (post-seizure) sinus arrhythmias, are potential triggers for sudden unexpected death in epilepsy. Traditionally, these arrhythmias have been attributed to changes in autonomic balance during ictal or postictal phases, as per the neurogenic mechanism. However, it remains unclear if these arrhythmias may involve intrinsic cardiogenic mechanisms. Furthermore, while circadian and sleep-wake patterns influence both neurogenic and cardiogenic mechanisms, a direct mechanistic link to seizure-induced arrhythmias remains to be established. In this study, we utilized a mathematical model of mouse sinoatrial nodal cell pacemaking and an autonomic clamping protocol, to dissect neurocardiogenic mechanisms in seizure-induced sinus arrhythmias and to test the hypothesis that circadian and sleep-wake rhythms directly modulate cellular susceptibility to these arrhythmias. Our simulations revealed that, in the context of altered autonomic levels associated with seizure progression, diverse seizure-induced sinoatrial nodal cell firing patterns during ictal or postictal phases can be triggered directly by intrinsic cardiac dynamics, without the need for dynamical changes in within-phase autonomic activities. This finding highlights the distinct roles of neurogenic and cardiogenic mechanisms in shaping sinoatrial nodal cell firing patterns, challenging the predominance of the neurogenic mechanism. This neurocardiogenic framework also successfully captures distinct circadian and vigilance state patterns of seizure-induced arrhythmias. Specifically, while daytime sleep predisposed sinoatrial nodal cells to postictal sinus arrhythmias, nighttime wakefulness promotes ictal sinus arrhythmias. However, these circadian patterns can be disrupted when sleep-wake cycles are decoupled from circadian rhythms, supporting the hypothesis that sleep-wake patterns can directly be a key determinant of seizure-induced sinus arrhythmias. Our findings may facilitate the development of novel therapeutic strategies for managing the risk of sudden unexpected death in epilepsy.

Indexed as

Arrhythmias, CardiacArrhythmia, SinusModels, CardiovascularSeizuresAnimalsCircadian RhythmComputational BiologyMiceSinoatrial NodeSleep

Identifiers

PMID40668822
PMCPMC12286331

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.