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Assessing the Cardiovascular Toxicity of Aspartame: An Integrated Approach from Computational Prediction to
Qiuhe Chen1, Hongjing You1, Hecai Wang1
1Chinese Medicine Guangdong Laboratory, State Key Laboratory of Traditional Chinese Medicine Syndrome, School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, Guangdong, China.
Abstract:
Artificial sweeteners, notably aspartame, are common food additives and merging environmental contaminants with potential cardiovascular risks. This study integrated network toxicology and experimental validation to explore aspartame's mechanisms in promoting cardiovascular disease (CVD). Initial toxicity prediction via ProTox 3.0 indicated cardiotoxicity among other toxicities. Potential targets of aspartame were identified using SwissTargetPrediction, ChEMBL, and SEA, while CVD associated targets were retrieved from GeneCards and OMIM and atherosclerosis related targets were obtained from GSE100927 dataset. Core targets were prioritized via STRING and Cytoscape. Functional enrichment analysis using Metascape highlighted key pathways. Molecular docking and dynamics simulations assessed binding affinity and stability. Microarray analysis, followed by in vivo and in vitro studies, validated findings. Results showed that aspartame-induced cardiovascular toxicity involves targeting IL1B, TNF, MMP9, CTSS, and CCR5, and activating cell adhesion molecules, NF-κB, and NOD-like receptor signaling pathways. In mice, aspartame reduced immune-related blood cells, impaired endothelium-dependent vasodilation, and increased vascular adhesion molecule expression. In HUVEC, the same pathways were activated. These findings suggest that aspartame promotes cardiovascular toxicity by targeting specific proteins and modulating inflammatory responses, cell migration, and adhesion via NF-κB and NOD-like receptor pathways. Collectively, this study provides mechanistic insights into aspartame-associated cardiovascular risk, providing a comprehensive mechanistic framework for a more accurate assessment.
