The mechanism of atorvastatin-induced sarcopenia elucidated based on network toxicology, single-cell RNA sequencing, and bulk transcriptomics data

Background Sarcopenia (SA) significantly affects the quality of life in the elderly. Atorvastatin (ATS), a lipid-lowering drug, may cause myopathy as a side effect. This study aimed to predict key genes involved in ATS-induced SA using network. Methods Public databases were used to obtain single-cell RNA sequencing (scRNA-seq) data, transcriptome data, and targets for SA and ATS toxicity. Toxicity prediction was conducted, and candidate genes were identified through differentially expressed genes (DEGs) associated with SA, as well as ATS toxicity targets. Machine learning and gene expression analyses were used to identify key genes, followed by functional enrichment and immune infiltration analysis. Molecular docking and dynamics simulations assessed the binding affinity between ATS and key genes. Key cell types were identified through scRNA-seq analysis. Results The toxicity prediction indicated that ATS exhibited relatively low toxicity in experimental animals. A total of 16 candidate genes were identified from the intersection of 2,402 DEGs, 101 toxicity targets, and 7,859 targets. BACE1 and PDE4A were selected as key genes. Functional enrichment analysis revealed their association with Parkinson's disease, oxidative phosphorylation, Alzheimer's disease, and Huntington's disease. Immune infiltration analysis showed that BACE1 and PDE4A were positively correlated with effector memory CD4 T cells. Molecular docking confirmed strong binding affinity between ATS and key genes, forming stable complexes. Myeloid cells were identified as key cells involved in SA. Conclusions This study provides insights into the molecular mechanisms of ATS-induced SA and supports strategies for preventing ATS-induced myopathy.