Purpose: we aimed to identify potential candidate biomarkers in aorta tissue from AAD patients. Methods: We used 4D label-free quantification (4D-LFQ) mass spectrometry to screen differentially expressed proteins in aorta tissues of AAD patients. Then we performed protein annotation, unsupervised hierarchical clustering, functional classification, functional enrichment and cluster, and protein-protein interaction analyses. Parallel Reaction Monitoring (PRM) technology was used to accurately and quantitatively confirm the selected target proteins. Results: A total of 3350 proteins were identified. Taking 1.5 times as the differential expression threshold, 139 were upregulated and 108 were downregulated as compared to the control groups. Bioinformatics analysis showed that the differential proteins were mainly distributed in extracellular matrix and cytoplasm. And their functions mainly involve cell migration and proliferation, inflammatory cell activation, cell contraction, muscle organ development and other processes. PRM technology accurately quantified the selected 20 target proteins, and found SAA1, LBP, MPO, and ENG were confirmed to be enriched in the aorta tissue of AAD patients. Conclusions: This is the first application of a 4D-LFQ-PRM workflow to identify and validate biomarkers in AAD patients. SAA1, LBP, MPO, and ENG represent novel biomarkers for the pathogenesis of AAD and might be a therapeutic target in the future.