Atherosclerosis (AS) is the most common cause of cardiovascular and cerebrovascular diseases. However, the mechanisms underlying atherosclerotic plaque progression remain unclear. This study aimed to investigate the genes associated with the development of atherosclerosis in the aorta of ApoE-/- male mice, which could serve as novel biomarkers and therapeutic targets in interventions to halt plaque progression. Eight-week-old ApoE-/- mice were fed a normal purified laboratory diet or a Western Diet (WD) for 6 or 22 weeks. High-throughput sequencing technology was used to analyze the transcriptomes of the aortas of four groups of mice that were exposed to different dietary conditions. We retrieved and downloaded the human Arteriosclerosis Disease Chip dataset GSE100927 from the Gene Expression Omnibus (GEO) database and selected 29 cases of carotid atherosclerotic lesions and 12 cases of normal carotid tissues as the experimental and control groups, respectively, to further verify our dataset. In addition, we used quantitative reverse transcription polymerase chain reaction (QT-PCR) to verify the expression levels of the core genes in an atherosclerosis mouse model. There were 265 differentially expressed genes (DEGs) between the ApoE-/- Male mice AS22W group and Sham22W group. In addition to the well-known activation of inflammation and immune response, t the autophagy-lysosome system is also an important factor that affects the development of atherosclerosis. We identified five core genes (Atp6ap2, Atp6v0b, Atp6v0d2, Atp6v1a, and Atp6v1d) in the protein-protein interaction (PPI) network that were closely related to autophagosomes. Hub genes were highly expressed in the carotid atherosclerosis group in the GSE100927 dataset (P < 0.001). QT-PCR showed that the RNA level of Atp6v0d2 increased significantly during the development of atherosclerotic plaque in ApoE-/- male mice. Five core genes which affect the development of aortic atherosclerosis through the autophagy-lysosome system, especially Atp6v0d2, were screened and identified using bioinformatic techniques.
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