Cardiac ion channels blockade leading to increased incidence of cardiovascular morbidity and mortality

Sun-Woong Kang^a, Myeong Hwa Song^b  ,Do-Sun Lim ^b and Kim Young Jun^c 

^aCenter for Biomimetic Research, Korea Institute of Toxicology, Daejeon 34114, Korea

^bCardiovascular Center, Department of Cardiology, Korea University Anam Hospital, Korea University College of Medicine, Seoul, South Korea

^cEnvironemental Safety Group, KIST Europe, campus E 71 Saarbruecken, Germany 

This Adverse Outcome Pathway (AOP) describes the mechanistic sequence of events linking cardiac ion channel blockade to increased incidence of cardiovascular morbidity and mortality . The Molecular Initiating Event (MIE) involves the blockade of key cardiac ion channels, such as hERG potassium channels, which disrupt ion currents critical for maintaining normal cardiac action potential. This triggers a cascade of Key Events (KEs), beginning with the prolongation of action potential duration (APD), which promotes early afterdepolarizations (EADs). These EADs lead to triggered activity, resulting in the onset of cardiac arrhythmias, such as Torsades de Pointes or ventricular fibrillation. Sustained arrhythmias impair cardiac output, culminating in sudden cardiac death. The Key Event Relationships (KERs) demonstrate strong biological plausibility and are supported by empirical evidence, including dose-response relationships, in vitro and in vivo studies, and clinical data linking QT prolongation to arrhythmic risk ( e.g.,Regulatory guidelines e.g., ICH S7B, E14). Despite some uncertainties, such as individual variability in repolarization reserve, this AOP provides a robust framework for predicting the cardiotoxicity of compounds, guiding risk assessment, drug development, and regulatory decision-making.

Sudden cardiac death caused by arrhythmias is a major concern in cardiotoxicity, especially in the context of pharmaceutical development and chemical safety assessment. Many drugs and chemicals can inadvertently block cardiac ion channels, such as the hERG potassium channel, leading to arrhythmogenic events. The ability to predict and mitigate such risks early in the development process is critical for ensuring patient safety and regulatory compliance.

This AOP, "Cardiac Ion Channel Blockade Leading to increased incidence of cardiovascular morbidity and mortality." provides a mechanistic understanding of how ion channel blockade initiates a series of cellular and tissue-level events, ultimately resulting in a fatal adverse outcome. By defining the sequence of molecular and physiological changes and their relationships, the AOP serves as a structured framework to guide the evaluation of cardiotoxic risks. It is particularly relevant in areas such as drug screening, environmental toxicology, and the development of computational models for safety assessment. The application of this AOP extends to identifying compounds with ion channel blocking properties, designing safer drugs, and supporting regulatory decision-making by incorporating mechanistic data into risk assessment frameworks. This approach aligns with the principles of evidence-based toxicology, offering a pathway to more predictive and reliable safety assessments.

1. Problem Formulation

Define the Scope: Establish the biological and regulatory significance of cardiac ion channel blockade in causing arrhythmias and sudden cardiac death.

Biological Scope: Focus on ion channels critical for cardiac electrophysiology (e.g., hERG, sodium, and calcium channels).

Regulatory Scope: Align with safety evaluation needs in pharmacology and toxicology, such as drug-induced QT prolongation, environmental toxicants, and cardiac risk assessments.

End Users: Identify the primary users of the AOP, including regulatory agencies (e.g., FDA, EMA), pharmaceutical developers, and environmental toxicologists.

2. Literature Review and Data Collection

Identify Key Events (KEs):

Search for peer-reviewed studies and datasets linking ion channel blockade to cardiac electrophysiological dysfunctions.

Include preclinical models, clinical data, and computational simulations.

Map Key Event Relationships (KERs):

Collect experimental evidence for causality between successive KEs.

Review dose-response data and time-course relationships to establish quantitative links.

Data Sources:

Databases like PubMed, TOXNET, and the AOP-Wiki platform.

High-throughput screening data and in vitro electrophysiology studies (e.g., patch-clamp assays for hERG).

3. Molecular Initiating Event (MIE) Identification

Pinpoint the blockade of specific cardiac ion channels as the MIE.

Focus on hERG channel inhibition due to its established link with QT prolongation.

Include other ion channels where evidence supports their involvement in arrhythmogenesis.

Assess potential co-factors, such as genetic predispositions (e.g., Long QT Syndrome) or electrolyte imbalances (e.g., hypokalemia).

4. Key Event (KE) Development

Define cellular, tissue, and organ-level KEs that lead to arrhythmia-associated sudden cardiac death.

Examples of KEs:

Prolongation of action potential duration (APD).

Formation of early afterdepolarizations (EADs).

Triggered activity.

Induction of cardiac arrhythmias.

Reduction in cardiac output.

Sudden cardiac death.

Ensure each KE is:

Observable: Measurable in experimental or clinical settings.

Biologically Plausible: Supported by mechanistic evidence.

Relevant: Tied directly to the adverse outcome.

5. Key Event Relationships (KERs)

Develop Evidence Chains: Establish how each KE leads to the next, based on experimental data.

Define Relationship Characteristics:

Biological plausibility.

Empirical support (dose-response, time course, etc.).

Quantitative understanding (e.g., thresholds for APD prolongation leading to EADs).

Address Uncertainties:

Investigate variability across species and individual susceptibility factors.

6. Integration of Quantitative Data

Develop models that link MIEs and KEs quantitatively, where possible.

Use computational tools, such as electrophysiological simulations, to predict arrhythmogenic risk.

Incorporate dose-response and temporal relationship data to build predictive frameworks.

Collaborate with databases like the OECD QSAR Toolbox for integrating chemical-specific data.

This AOP provides a structured and scientifically plausible framework to understand and predict the cardiotoxicity of compounds. Its assessment is based on biological plausibility, empirical evidence, applicability, and limitations, as summarized below:

Biological Plausibility

The AOP builds on well-established mechanisms of cardiac electrophysiology, where ion channel blockade (e.g., hERG potassium channel inhibition) leads to prolonged action potential duration (APD), early afterdepolarizations (EADs), and arrhythmogenesis.

Strong mechanistic understanding exists for key ion channels (potassium, sodium, and calcium) and their role in maintaining cardiac rhythm.

The causal relationships between key events, such as prolonged APD and EAD formation, are supported by experimental and clinical data.

Empirical Evidence

Robust dose-response relationships between ion channel inhibitors and QT prolongation, a measurable surrogate for APD prolongation.

In vitro studies (e.g., patch-clamp assays) demonstrate a clear link between ion channel inhibition and arrhythmogenic changes in cardiac cells.

In vivo and clinical studies provide evidence for the progression from arrhythmias to sudden cardiac death.

Applicability

The AOP is broadly applicable across drug safety assessment, environmental toxicology, and regulatory frameworks, particularly in screening for cardiotoxic risks of chemicals and pharmaceuticals. It supports the development of non-animal testing methods, such as high-throughput in vitro assays and computational models.

Utility

The AOP facilitates the identification of ion channel blocking liabilities early in drug discovery and development.

It can guide regulatory decision-making, aligning with international safety guidelines (e.g., ICH S7B and E14 for QT prolongation and cardiac safety).

2. Limitations and Uncertainties

Variability in Response

Individual susceptibility to arrhythmias varies due to factors such as genetic predispositions (e.g., Long QT Syndrome), electrolyte imbalances (e.g., hypokalemia), and comorbidities.

Species-specific differences in cardiac electrophysiology may complicate extrapolation of results from animal models to humans.

Data Gaps

Limited quantitative understanding of some Key Event Relationships (KERs), such as the thresholds for EAD formation leading to arrhythmias.

Insufficient data for certain compounds, particularly environmental toxicants, to establish their arrhythmogenic potential.

Complexity of the Outcome

Arrhythmias are influenced by multiple factors, including heart rate, autonomic nervous system regulation, and structural heart diseases, which are not fully captured in the AOP.

The transition from arrhythmias to sudden cardiac death can involve stochastic events, making prediction challenging.

Lack of High-Throughput Tools for Downstream KEs

While ion channel blockade and APD prolongation are measurable using in vitro assays, downstream events like arrhythmias and reduced cardiac output require more complex models.

This Adverse Outcome Pathway (AOP)  provides a mechanistic framework for understanding and predicting the cardiotoxic effects of chemicals and pharmaceuticals. The AOP outlines a sequence of key events (KEs), starting with the molecular initiating event (MIE) of cardiac ion channel blockade, which leads to prolonged action potential duration (APD), early afterdepolarizations (EADs), triggered activity, cardiac arrhythmias, and ultimately, sudden cardiac death. Strong biological plausibility, supported by empirical evidence, underpins the relationships between these events, although quantitative understanding remains moderate for certain transitions. The domain of applicability spans mammalian species, particularly humans, with broad relevance across life stages and both sexes. Modulating factors, including genetic predispositions (e.g., Long QT Syndrome), electrolyte imbalances, co-administration of drugs, and environmental stressors, significantly influence the progression of KEs and the likelihood of the adverse outcome. The AOP is well-suited for regulatory applications, such as drug safety assessment, chemical risk evaluation, and integration into frameworks like the OECD Integrated Approaches to Testing and Assessment (IATA). It also supports research applications, including mechanistic toxicology, the development of alternative testing methods, and personalized medicine. Despite its strengths, limitations such as inter-individual variability, species differences, and data gaps for certain chemical classes highlight the need for further refinement. By addressing these challenges, the AOP can enable more predictive risk assessments, guide regulatory decision-making, and facilitate the safe development of drugs and industrial chemicals. This comprehensive framework underscores the value of AOPs in advancing public health and improving safety evaluation processes.

Sanguinetti, M. C., & Tristani-Firouzi, M. (2006). hERG potassium channels and cardiac arrhythmia. Nature, 440(7083), 463–469.

Roden, D. M. (2004). Drug-induced prolongation of the QT interval. New England Journal of Medicine, 350(10), 1013–1022.

Curran, M. E., et al. (1995). A molecular basis for cardiac arrhythmia: HERG mutations cause long QT syndrome. Cell, 80(5), 795–803.

Vandenberg, J. I., et al. (2012). hERG K+ channels: Structure, function, and role in cardiac arrhythmia. Physiological Reviews, 92(3), 1393–1478.

Kannankeril, P., Roden, D. M., & Darbar, D. (2010). Drug-induced long QT syndrome. Pharmacological Reviews, 62(4), 760–781.

Clancy, C. E., & Rudy, Y. (1999). Linking a genetic defect to its cellular phenotype in a cardiac arrhythmia. Nature, 400(6744), 566–569.

International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH). (2005). ICH S7B: Nonclinical evaluation of the potential for delayed ventricular repolarization (QT interval prolongation) by human pharmaceuticals.

International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH). (2005). ICH E14: Clinical evaluation of QT/QTc interval prolongation and proarrhythmic potential for non-antiarrhythmic drugs.

Villeneuve, D. L., et al. (2014). Adverse outcome pathway (AOP) development I: Strategies and principles. Toxicological Sciences, 142(2), 312–320.

OECD. (2018). Users' Handbook Supplement to the Guidance Document for Developing and Assessing Adverse Outcome Pathways. OECD Series on Adverse Outcome Pathways, No. 1. Paris: OECD Publishing.

Cheng, H., et al. (2012). Cardiomyocytes derived from human pluripotent stem cells: A model for studying the cardiac channelopathy long-QT syndrome. Science Translational Medicine, 4(130), 130ra49.

Milnes, J. T., et al. (2010). hERG K+ channel pharmacology: Insights into mechanisms of drug-induced QT prolongation and arrhythmia. Journal of Pharmacological and Toxicological Methods, 61(3), 171–180.

Zipes, D. P., & Wellens, H. J. (1998). Sudden cardiac death. Circulation, 98(21), 2334–2351.

Di Diego, J. M., & Antzelevitch, C. (2009). Cellular basis for the electrocardiographic manifestations of the long QT syndrome: Insights from modeling and experimental studies. Circulation Research, 105(7), 707–721.

Schwartz, P. J., et al. (2013). Clinical aspects of inherited long-QT syndrome: A changing paradigm. Journal of the American College of Cardiology, 62(20), 2017–2022.

Tester, D. J., & Ackerman, M. J. (2007). Postmortem long QT syndrome genetic testing for sudden unexplained death in the young. Journal of the American College of Cardiology, 49(2), 240–246.

O’Hara, T., Virág, L., & Rudy, Y. (2011). Simulation of the undiseased human cardiac ventricular action potential: Model formulation and experimental validation. PLoS Computational Biology, 7(5), e1002061.

Mirams, G. R., et al. (2011). Simulation of multiple ion channel block provides improved early prediction of compounds’ clinical torsadogenic risk. Cardiovascular Research, 91(1), 53–61.

Roden, D. M. (2008). Cellular basis of drug-induced torsades de pointes: From ion channel to clinical disorder. Cardiovascular Research, 68(1), 137–146.

Moss, A. J., & Kass, R. S. (2005). Long QT syndrome: From channels to cardiac arrhythmias. Journal of Clinical Investigation, 115(8), 2018–2024.

Ankley, G. T., et al. (2010). Adverse outcome pathways: A conceptual framework to support ecotoxicology research and risk assessment. Environmental Toxicology and Chemistry, 29(3), 730–741.

Perkins, E. J., et al. (2015). Adverse outcome pathways for regulatory applications: Examining North American and European experience. Environmental Toxicology and Chemistry, 34(9), 1957–1973.