Apr 10, 2020

Estimating the Probability of Cellular Arrhythmias with Simplified Statistical Models that Account for Experimentally Observed Uncertainty in Underlying Biophysical Mechanisms

BioRxiv : the Preprint Server for Biology
Q. JinRaimond L. Winslow

Abstract

Early afterdepolarizations (EADs) and ectopic beats (EBs) are cellular arrhythmias that can trigger cardiac arrhythmias. Simulations using biophysically-detailed cardiac myocyte models can reveal how cellular properties influence the probability of cellular arrhythmias, however such analyses often pose a huge computational burden. Here, we develop a simplified approach in which logistic regression models (LRMs) are used to define a mapping between cellular properties and the probability of cellular arrhythmias. Two LRMs are developed, one for predicting the probability of EADs (P(EAD)) as a function of IKs parameters and one for predicting the probability of EBs (P(EB)) as a function of Ca2+ dynamics, ryanodine receptor opening rate, and IK1 current density. These LRMs, which require negligible computational resources, are then used to demonstrate how uncertainties in experimentally measured model parameters influence P(EAD) and P(EB). We refer to this as arrhythmia sensitivity analysis. In the investigation of five different IKs parameters associated with Long QT syndrome 1 (LQTS1) mutations, the predicted P(EAD), when rank ordered for 6 LQTS1 mutations, matches the trend in risk from patients with the same mutations as measur...Continue Reading

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