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Aim: Thoracic aortic dissection (TAD) is a high-risk vascular disease. The mortality rate of untreated TADs in 24 h was as high as 50%. Thus, rapid diagnosis of TAD in the emergency department would get patients to the right treatments to save their lives.

Methods: We profiled the proteome of aortic tissues from TAD patients using a label-free quantification proteomics method. The differentially expressed proteins were screened and subjected to bioinformatics analysis. Candidate biomarkers were selected and validated in independent serum samples using enzyme-linked immunosorbent assays (ELISAs). The diagnostic values were further predicted via receiver operating characteristic (ROC) curve analysis.

Results: A total of 1,141 differentially expressed proteins were identified in aortic tissues from 17 TAD patients and eight myocardial infarction (MI) patients. Six proteins were selected as candidate biomarkers for ELISAs in an independent training set of 20 serum samples (TAD = 10, MI = 10). Of these proteins, four with a P-value < 0.01 were further validated in another independent set of 64 serum samples (TAD = 32, MI = 32) via ELISAs. ITGA2, COL2A1, and MIF had P-values < 0.0001, and their areas under the curve (AUCs) were 0.801 (95% CI: 0.691–0.911), 0.773 (95% CI: 0.660–0.887), and 0.701 (95% CI: 0.574–0.828), respectively.

Conclusion: ITGA2, COL2A1, and MIF were identified as promising biomarkers for discriminating TAD from emergency patients with severe chest pain. Biomarker-guided emergency triage could further shorten the time for patients to get more effective treatments.