A Data-Driven Approach for the Development of a Time-informed Adverse Outcome Pathway-network for Cardiotoxicity of Environmental Chemicals

Abstract

We present a novel Adverse Outcome Pathway (AOP) network for environmental chemical-induced cardiotoxicity using a bottom-up, data-driven AOP development approach. Mechanistic endpoints were systematically extracted from 339 in vitro and in vivo studies, yielding 1,759 Key Event (KE) entries and 4,938 Key Event Relationship (KER) entries, including information on experimental methods, essentiality evidence (intervention experiments demonstrating upstream-downstream dependence), and study metadata. After quality filtering (high risk of bias, confounding cytotoxicity in vitro, excessive toxicity or animal well-being concerns in vivo, and low-frequency observations), 112 unique KEs and 829 unique KERs supported by at least three independent observations were retained for network construction. Network analysis identified oxidative stress and mitochondrial dysfunction as dominant hub processes linking diverse upstream perturbations to downstream cardiomyocyte injury, inflammation, cardiac remodelling (fibrosis and hypertrophy), decreased cardiac contractility, and reduced left ventricular function. Incorporating exposure duration at the KER level enabled time-resolved pathway interpretation and demonstrated that KE timing is relationship-dependent, revealing temporal patterns not apparent when analysing KEs in isolation. This evidence-weighted, time-resolved AOP network can support endpoint prioritisation and exposure-window selection for non-animal method (NAM) test batteries and mechanistically informed cardiotoxicity assessment. SynopsisEnvironmental chemicals converge on shared stress and injury pathways that drive cardiac remodelling and ventricular dysfunction. A time-resolved AOP network helps prioritise endpoints and exposure windows for non-animal cardiotoxicity testing.