PUBLICATION
Systems assessment of statins hazard: Integrating in silico prediction, developmental toxicity profile and transcriptomics in zebrafish
- Authors
- Han, Y., Ma, Y., Tong, J., Zhang, J., Hu, C.
- ID
- ZDB-PUB-220828-2
- Date
- 2022
- Source
- Ecotoxicology and environmental safety 243: 113981 (Journal)
- Registered Authors
- Zhang, Jing-pu
- Keywords
- Developmental toxicity, Differentially expressed genes, RNA sequencing, Statins, Zebrafish
- MeSH Terms
-
- Animals
- Ecosystem
- Fatty Acids, Monounsaturated
- Hydroxymethylglutaryl-CoA Reductase Inhibitors*/toxicity
- Indoles
- Simvastatin
- Transcriptome
- Zebrafish/genetics
- PubMed
- 36029576 Full text @ Ecotoxicol. Environ. Saf.
Citation
Han, Y., Ma, Y., Tong, J., Zhang, J., Hu, C. (2022) Systems assessment of statins hazard: Integrating in silico prediction, developmental toxicity profile and transcriptomics in zebrafish. Ecotoxicology and environmental safety. 243:113981.
Abstract
Statins are prescribed widely as lipid-lowering agents. However, statins are associated with an increased harmful risk on public health and the ecosystem. Little is known about statins' toxicity on biological development and the underlying molecular mechanisms. We exposed zebrafish embryos to a series of statins to evaluate their development toxicity. Statins-induced embryonic developmental defects in a concentration-dependent manner. 72 h LC50 values for lovastatin, simvastatin, fluvastatin, atorvastatin, rosuvastatin, and pravastatin were 0.01 μM, 0.04 μM, 1.93 μM, 37.28 μM, 79.29 μM, and 2170 μM, respectively. Moreover, the expression of genes involved in heart contraction, calcium ion binding, transcription factors, nucleus, and G protein-coupled receptor signaling pathway was altered by statins. The early growth response gene (egr4) and transcription factor genes (fosab and fosb) were screened as potential toxicity targets due to their significant upregulation based on protein-protein interaction (PPI) and drug-gene interaction network analysis. Finally, the ecotoxicity profile of statins was predicted by in silico method, and statins were high or moderate risk to aquatic organisms. We provide a systems toxicology strategy to explore the toxicity of statins and illustrate the potential mechanisms of action.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping