Stanozolol, a synthetic anabolic androgenic steroid (AAS) widely abused to enhance performance, has poorly defined toxicological mechanisms in atherosclerosis (AS). An AS model was established in ApoE-/- mice, followed by a 12-week stanozolol intervention. Effects on lipid metabolism, systemic inflammation, and plaque formation were assessed. Potential targets were predicted via database integration. Transcriptomic analyses included differential expression, WGCNA, GSEA, CIBERSORT, and single-cell RNA-seq. Core toxic targets were identified using LASSO, SVM-RFE, and random forest. Validation was performed by qRT-PCR, Western blotting, and immunofluorescence. Molecular docking and 100-ns MD simulations were conducted to assess binding affinity and stability. Stanozolol significantly aggravated AS progression, marked by increased lipid deposition, vascular remodeling, dyslipidemia, and systemic inflammation. Integration of multi-omics and machine learning identified three key targets-CSK, FBLN1, and BCHE-With stable binding to stanozolol. Functional assays showed CSK upregulation in macrophages and FBLN1 downregulation in vascular smooth muscle cells. Stanozolol accelerates atherosclerosis by activating inflammatory responses and disrupting vascular homeostasis. CSK and FBLN1 are core toxic mediators and potential therapeutic targets.
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