Aim Ischemic stroke (IS) is caused by acute ischemia of cerebral blood vessels, leading to brain tissue damage and neuronal apoptosis. The pathogenesis is complex, involving multiple cell death modes such as pyroptosis, ferroptosis and disulfide death. Disulfide death is a newly discovered form of death that helps to explore the pathological mechanisms of various diseases from a new perspective. The aim of this study is to discover and validate the differential expression of disulfide death-related genes in blood samples of ischemic patients and their association with immune regulation. Methods The relevant datasets of clinical patients (GSE16561 and GSE37587) were obtained through online big data. Differentially expressed genes related to disulfide death were identified, and gene enrichment analysis was conducted to further explore the potential mechanisms. Subsequently, immune cell infiltration was analyzed to investigate the dysregulation of immune cells in the context of IS. Finally, the accuracy of key genes was verified through ROC curves, column charts, calibration curves, and decision curves, and a disease prediction model was constructed to predict the risk of stroke. Results Based on this dataset, significant differential expression of 9 genes related to disulfide death was identified. Independent external validation was conducted using the microarray dataset GSE58294. Single item comparisons were performed on these differentially expressed genes in blood samples from 69 IS patients and 23 normal individuals.The results showed that the trends of LRPPRC, MYH9, NDUFA11, PRDX1 and RPN1, the 5 differentially expressed genes, were consistent. Immune infiltration analysis found that differentially expressed genes such as TLN1, MYH9, PRDX1, LRPPRC, NDUFA11 were also strongly correlated with CD8＋T cells, activated NK cells, macrophages, and neutrophils in IS patients. Functional enrichment analysis emphasized the important role of pathways such as focal adhesion, platelet aggregation, and activation in the occurrence and development of diseases. By using a column chart model for risk prediction, it was shown that the accuracy of these differentially expressed genes was good, and the ROC curve AUC value of the optimized combination of disulfide death-related genes could reach 0.844. Further validation through an external dataset (GSE58294) revealed that the ROC curve AUC value optimized for disulfide death-related genes reached 0.989, which had good clinical guidance significance for the risk of IS. Conclusions This study confirmed the existence of 5 disulfide death-related genes in IS patients through a dataset, including upregulation of MYH9 and downregulation of LRPPRC, NDUFA11, PRDX1 and RPN1. These gene alterations are suggested to influence IS disease progression and prognosis through immune inflammation and bleeding risk.