Biology subjects

Heitmann, S.

Publications and source records attributed to Heitmann, S..

7 recordsLinked to original sources

bioRxiv2024

Independent derivations of the axis of arrhythmia for predicting drug-induced torsades de pointes

Torsades de pointes is a potentially lethal ventricular arrhythmia that may be caused by many classes of drugs. The likelihood of arrhythmia depends upon the particular combination of cardiac ion-channels that the drug targets. The risk for a given drug can be measured against the axis of arrhythmia, which is a conceptual line in the parameter space of ventricular cardiomyocyte electrophysiology. The axis describes the most potent combination of ion-channel blocks that is theoretically possible. It thus serves as a convenient yardstick for quantifying the pro-arrhythmic risk of novel drugs from their channel-blocking profiles. To date, the axis of arrhythmia has only been derived from biophysical computer simulations. Here, we derive the axis directly from the response profiles of selected ion-channels to known drugs (n=109). The new method provides an independent line of evidence for estimating the axis of arrhythmia. Using step-wise reduction, the two methods were found to converge to identical estimates of the axis in two ion-currents (ICaL and IKr). The resulting axis predicted the pro-arrhythmic risk of the test drugs with 89.9% to 91.7% accuracy, depending on the dose at which the drug was assessed. The axis of arrhythmia offers a practical method for predicting the pro-arrhythmic risk of novel drugs without the need for drug-specific computer simulations. It is the only metric of pro-arrhythmic risk that has been derived from both a biophysical model and a purely statistical model. It thus combines the benefits of biophysical interpretation and computational efficiency in assessing the torsadogenic risk of new drugs prior to clinical trials. Significance StatementMany classes of drugs can cause lethal cardiac arrhythmias by blocking ion-channels that are needed by heart cells for normal rhythm. International safety guidelines thus require all new drugs be tested in animal hearts or cell cultures prior to undertaking clinical trials in humans. Computer models offer an ethical alternative for drug testing that is gaining acceptance in the safety pharmacology community. However, the current corpus of models are usually too complex to apply outside of specialist computing laboratories. We recently proposed a new approach that eliminates the need for drug-specific computer simulations by using a large one-off computer simulation to identify the most pro-arrhythmic drug that is theoretically possible. Thereafter, that hypothetical drug can be used to assess the pro-arrhythmic risk of real drugs using only pen-and-paper calculations. In that study, the hypothetical drug was described by the axis of arrhythmia in the cardiac cell model. In the present study, we propose an alternative method for deriving the axis of arrhythmia directly from drug datasets. The two derivations are independent, yet they arrive at the same result. Together, they provide converging lines of evidence in support of this new approach to drug testing in safety pharmacology.

pharmacology and toxicology↗

bioRxiv2023

Assessing drug safety by identifying the axis of arrhythmia in cardiomyocyte electrophysiology

Many classes of drugs can induce fatal cardiac arrhythmias by disrupting the electrophysiology of cardiomyocytes. Safety guidelines thus require all new drugs to be assessed for pro-arrhythmic risk prior to conducting human trials. The standard safety protocols primarily focus on drug blockade of the delayed-rectifier potassium current (IKr). Yet the risk is better assessed using four key ion currents (IKr, ICaL, INaL, IKs). We simulated 100,000 phenotypically diverse cardiomyocytes to identify the underlying relationship between the blockade of those currents and the emergence of ectopic beats in the action potential. We call that relationship the axis of arrhythmia. It serves as a yardstick for quantifying the arrhythmogenic risk of any drug from its profile of multi-channel block alone. We tested it on 109 drugs and found that it predicted the clinical risk labels with an accuracy of 88.1% to 90.8%. Pharmacologists can use our method to assess the safety of novel drugs without resorting to animal testing or unwieldy computer simulations. Significance StatementMany classes of drugs interfere with the electrical signaling of the heart, leading to arrhythmias and cardiac arrest. Newly developed drugs must therefore undergo mandatory safety testing in animals prior to human trials. Computational models of cardiac electrophysiology offer an ethical alternative, but the current methods are difficult to apply beyond specialist computing laboratories. This study uses such models to identify the underlying relationship between drugs and cardiac arrhythmias. Those findings are then translated into a compact metric that can be applied using simple pen and paper calculations. The new metric allows pharmacology laboratories to assess the safety of novel drugs without using animals or unwieldy computer simulations.

pharmacology and toxicology↗

bioRxiv2020

Arrhythmogenesis as the failure of repolarization

Contemporary theories of cardiac fibrillation typically rely on the emergence of rotors to explain the transition from regular sinus rhythm to disordered electrophysiological activity. How those rotors spontaneously arise in the absence of re-entrant anatomical circuits is not fully understood. Here we propose a novel mechanism where arrhythmias are initiated by cardiac cells that fail to repolarize following a normal heartbeat. Those cells subsequently act as a focal ectopic source that drive the ensuing fibrillation. We used a simple computational model to investigate the impact of such cells in both homogeneous and heterogeneous excitable media. We found that heterogeneous media can tolerate a surprisingly large number of abnormal cells and still support normal rhythmic activity. At a critical limit the medium becomes chronically arrhythmogenic. Numerical analysis revealed that the critical threshold for arrhythmogenesis depends on both the strength of the coupling between cells and the extent to which the abnormal cells resist repolarization. Arrhythmogenesis was also found to emerge first at tissue boundaries where cells naturally have fewer neighbors to influence their behavior. These findings may explain why atrial fibrillation typically originates from the cuff of the pulmonary vein.Author summary Cardiac fibrillation is a medical condition where normal heart function is compromised as electrical activity becomes disordered. How fibrillation arises spontaneously is not fully understood. It is generally thought to be triggered by premature depolarization of the cardiac action potential in one or more cells. Those premature beats, known as early-afterdepolarizations, subsequently initiate a self-sustaining rotor in the otherwise normal heart tissue. In this study, we propose an alternative mechanism whereby arrhythmias are initiated by cardiac cells that fail to repolarize of their own accord but still operate normally when embedded in functional heart tissue. We find that such cells can act as focal ectopic sources under appropriate conditions of inter-cellular coupling. Moreover, cells on natural tissue boundaries are more susceptible to arrhythmia because they are coupled to fewer cells. This may explain why the pulmonary vein is often implicated as a source of atrial fibrillation.Competing Interest StatementThe authors have declared no competing interest.View Full Text

biophysics↗

bioRxiv2020

Direction-selective motion discrimination by traveling waves in visual cortex

The majority of neurons in primary visual cortex respond selectively to bars of light that have a specific orientation and move in a specific direction. The spatial and temporal responses of such neurons are non-separable. How neurons accomplish that computational feat without resort to explicit time delays is unknown. We propose a novel neural mechanism whereby visual cortex computes non-separable responses by generating endogenous traveling waves of neural activity that resonate with the space-time signature of the visual stimulus. The spatiotemporal characteristics of the response are defined by the local topology of excitatory and inhibitory lateral connections in the cortex. We simulated the interaction between endogenous traveling waves and the visual stimulus using spatially distributed populations of excitatory and inhibitory neurons with Wilson-Cowan dynamics and inhibitory-surround coupling. Our model reliably detected visual gratings that moved with a given speed and direction provided that we incorporated neural competition to suppress false motion signals in the opposite direction. The findings suggest that endogenous traveling waves in visual cortex can impart direction-selectivity on neural responses without resort to explicit time delays. They also suggest a functional role for motion opponency in eliminating false motion signals. Author summaryIt is well established that the so-called simple cells of the primary visual cortex respond preferentially to oriented bars of light that move across the visual field with a particular speed and direction. The spatiotemporal responses of such neurons are said to be non-separable because they cannot be constructed from independent spatial and temporal neural mechanisms. Contemporary theories of how neurons compute non-separable responses typically rely on finely tuned transmission delays between signals from disparate regions of the visual field. However the existence of such delays is controversial. We propose an alternative neural mechanism for computing non-separable responses that does not require transmission delays. It instead relies on the predisposition of the cortical tissue to spontaneously generate spatiotemporal waves of neural activity that travel with a particular speed and direction. We propose that the endogenous wave activity resonates with the visual stimulus to elicit direction-selective neural responses to visual motion. We demonstrate the principle in computer models and show that competition between opposing neurons robustly enhances their ability to discriminate between visual gratings that move in opposite directions.

neuroscience↗

bioRxiv2019

Co-expression of calcium channels and delayed rectifier potassium channels protects the heart from proarrhythmic events

Cardiac electrical activity is controlled by the carefully orchestrated activity of more than a dozen different ion conductances. Yet, there is considerable variability in cardiac ion channel expression levels both within and between subjects. In this study we tested the hypothesis that variations in ion channel expression between individuals are not random but rather there are modules of co-expressed genes and that these modules make electrical signaling in the heart more robust. Meta-analysis of 3653 public RNA-Seq datasets identified a strong correlation between expression of CACNA1C (L-type calcium current, ICaL) and KCNH2 (rapid delayed rectifier K+ current, IKr), which was verified in mRNA extracted from human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM). In silico modeling, validated with functional measurements in hiPSC-CM, indicates that the co-expression of CACNA1C and KCNH2 limits the variability in action potential duration and reduces susceptibility to early afterdepolarizations, a surrogate marker for pro-arrhythmia. Impact StatementCoexpressed levels of potassium and calcium ion channel genes in the heart encode more robust cardiac electrophysiology and provide insights into genetic basis of arrhythmic risk

biophysics↗

bioRxiv2017

The Brain Dynamics Toolbox for Matlab

The Brain Dynamics Toolbox provides a graphical tool for simulating user-defined dynamical systems in O_SCPLOWMATLABC_SCPLOW. It supports three classes of differential equations commonly used in computational neuroscience: Ordinary Differential Equations, Delay Differential Equations and Stochastic Differential Equations. The design of the graphical interface fosters intuitive exploration of the dynamics, yet there is no barrier to scripting large-scale simulations and parameter explorations. System variables and parameters may range in size from simple scalars to large vectors or matrices. The toolbox is intended for dynamical models in computational neuroscience but it can be applied to continuous dynamical systems from any domain.

neuroscience↗

bioRxiv2017

Putting the "dynamic" back into dynamic functional connectivity

The study of fluctuations in time-resolved functional connectivity is a topic of substantial current interest. As the term \"dynamic functional connectivity\" implies, such fluctuations are believed to arise from dynamics in the neuronal systems generating these signals. While considerable activity currently attends to methodological and statistical issues regarding dynamic functional connectivity, less attention has been paid toward its candidate causes. Here, we review candidate scenarios for dynamic (functional) connectivity that arise in dynamical systems with two or more subsystems; generalized synchronization, itinerancy (a form of metastability), and multistability. Each of these scenarios arise under different configurations of local dynamics and inter-system coupling: We show how they generate time series data with nonlinear and/or non-stationary multivariate statistics. The key issue is that time series generated by coupled nonlinear systems contain a richer temporal structure than matched multivariate (linear) stochastic processes. In turn, this temporal structure yields many of the phenomena proposed as important to large-scale communication and computation in the brain, such as phase-amplitude coupling, complexity and flexibility. The code for simulating these dynamics is available in a freeware software platform, the \"Brain Dynamics Toolbox\".

neuroscience↗