The long-term goal of this research is to identify SUDEP risk biomarkers and the brain-heart-lungs
pathways mediating SUDEP pathophysiology. People with epilepsy are 16 times more likely than the general
population to die suddenly for unknown pathological reasons; these deaths are classified as SUDEP and
represent the leading cause of epilepsy-related mortality. Predictive SUDEP risk biomarkers still do not exist and
the exact mechanisms and pathways involved are poorly understood. Overcoming these barriers would enable
accurate patient risk stratification and monitoring, and the development of effective preventive strategies.
In this work, we propose to employ a new multidisciplinary bioengineering systems approach (termed
“inter-organ directed connectivity analysis”) to identify the type and nature of directional interactions between the
brain (electroencephalography), heart (electrocardiography), and lungs (plethysmography) that underlie
susceptibility to SUDEP and that could be utilized as reliable biomarkers of SUDEP risk, beginning with
examination of Kcna1 global knockout (KO) mice in Aim 1. We will measure how these dynamics change over
time when seizures occur and as the time to SUDEP approaches. Kcna1 global KO mice, which lack Kv1.1
channels, are one of the best characterized genetic channelopathy models of SUDEP, exhibiting essential
features of SUDEP observed in patients. In Aim 2, we will employ brain- and heart-specific Kcna1 conditional
KO (cKO) models and pharmacology to begin to identify the underlying biological basis of the observed
impairment of dynamics in the directional connectivities between brain, heart and lungs. In Aim 3, we will then
examine a different model of SUDEP due to sodium channelopathy, the Scn8aN1768D mouse, which carries a
gain-of-function mutation in Nav1.6 channels, to determine whether the same patterns of abnormal brain-heart-
lung connectivity can be generalized across models.
We hypothesize that our analyses will reveal pathological functional interactions between the brain, heart,
and lungs that are associated with SUDEP susceptibility in mice. Such patterns of faulty brain-heart-lung
connectivity have translational potential as new and more reliable biomarkers for monitoring SUDEP risk and
disease progression in epilepsy patients, while also shedding light on potential pathophysiological mechanisms.
Evaluation of brain-heart-lungs connectivity across two accepted mouse models of SUDEP in this proposal will
lay the foundation for future clinical application of this bioengineering technique in epilepsy patients with the hope
of providing individualized SUDEP risk assessment that can be used to aid preventative strategies.