Abstract
OBJECTIVE: Ferroptosis is a specific subtype of programmed cell death, which plays an essential role in the immune-associated disease, atherosclerosis (AS). The purpose of this study was to identify potential ferroptosis-related gene biomarkers and its association with immune infiltration characteristics in atherosclerosis with bioinformatics methods. METHODS: Differentially expressed genes (DEGs) between AS and control groups were screened from GSE40231, analyzed for functional enrichment and then intersected with ferroptosis-related genes. Then, a random forest model was constructed based on these differentially expressed ferroptosis-related genes (DE-FRGs) and validated with dataset GSE132651. The performance of the models was evaluated with the area under receiver operating characteristic curves (AUC). Finally, we analyzed the correlation between DE-FRGs above and the characteristics of immune infiltration via CIBERSORT method. RESULTS: Six DE-FRGs (IL6, ANGPTL7, CDKN1A, AKR1C3, NOX4 and VLDLR) were detected based on dataset of GSE40231. Furthermore, a random forest model was constructed based on them with a compelling diagnostic performance of AUC = 0.8974 in the validation dataset GSE132651. In addition, the proportion of follicular helper T (Tfh) cells was significantly higher in AS group (P < 0.001). And we found significant correlation relationship between Tfh and expression level of ANGPTL7 (R = 0.35, P < 0.01), CDKN1A (R = 0.4, P < 0.0001), AKR1C3 (R = 0.64, P < 0.0001), NOX4 (R = 0.32, P < 0.01) and VLDLR (R = -0.43, P < 0.0001). CONCLUSION: This study identified 6 DE-FRGs and validated a predicted model for the early prediction of AS, which also proved the close relationship between ferroptosis and immunity in the pathogenesis of AS.