Data sets implemented for analysis.

Disulfidptosis is a newly discovered method of cell death. However, no studies have fully elucidated the role of disulfidptosis-related genes (DSRGs) in acute myocardial infarction (AMI). The potential role of DSRGs in AMI was analyzed through a comprehensive bioinformatics approach. Finally, hub genes were verified in vitro by qPCR. Sixteen DE-DSRGs were in the AMI. Thereafter, seven hub genes were determined by machine learning algorithms, which had potential diagnostic value in AMI. The risk model showed a robust diagnostic value (area under curve, AUC = 0.940). Prognostic analysis revealed the potential prognostic value of INF2 and CD2AP. Immune landscape analysis showed that hub genes were closely related to the immune microenvironment. By predictive analysis, we obtained four miRNAs, thirteen small molecule drugs, and five TFs closely related to hub genes. Experimental verification revealed that Slc3a2 and Inf2 were significantly up-regulated and Dstn was significantly down-regulated in the hypoxic model. Our study demonstrated that DSRGs are disorderedly expressed in AMI and identified seven hub genes through machine learning. In addition, a diagnostic model was constructed based on hub genes, providing a new perspective for the early diagnosis of AMI.