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DOI 10.3389/ftox.2026.1781536

Медицинская библиотека · Frontiers in toxicology · 2026

Cardiotoxicity adverse outcome pathway network: towards mechanistic and quantitative modelling.

Ladeira Luiz, Barnes Devon A, Masereeuw Rosalinde, Geris Liesbet, Staumont Bernard

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Аннотация

INTRODUCTION

Chemical-induced heart toxicity remains a major challenge in drug development and environmental safety, largely because current testing often relies on narrow, late-stage endpoints that miss the complex biological progression of the toxicities. To address this, we developed a comprehensive Adverse Outcome Pathway (AOP) network that maps how early (bio) chemical triggers evolve into organ-level dysfunction.

METHODS

By integrating data from the OECD AOP-Wiki, we constructed a unified network of 64 biological events and 94 documented relationships that identifies the critical biological "crossroads" where different toxic chemicals converge to cause heart damage.

RESULTS/DISCUSSION: Our analysis reveals a compact core of central biological events, such as oxidative stress and mitochondrial dysfunction, which act as the primary drivers of cardiac injury. This network approach moves beyond single, linear pathways to show how systemic factors, including interactions with other organs like the kidneys, contribute to cardiotoxicity. To translate these findings into a practical resource for the broader scientific community, we developed a methods catalogue that links these biological events to specific laboratory assays. To ensure this work is accessible and actionable, we hosted the network on an interactive, FAIRaligned web platform. By providing a clear scaffold for understanding heart safety, this resource enables the design of more human-relevant, animal-free testing strategies and helps prioritise the most impactful biomarkers for future safety assessments.

Для цитирования: Ladeira Luiz, Barnes Devon A, Masereeuw Rosalinde, Geris Liesbet, Staumont Bernard. Cardiotoxicity adverse outcome pathway network: towards mechanistic and quantitative modelling.. Frontiers in toxicology. 2026. DOI: 10.3389/ftox.2026.1781536.
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