Abstract 13601: Distinct Proteomic Profiles in Human Thoracic Aortic Aneurysm by Segment May Drive Prognostic Differences: Conventional & Machine Learning Analysis

Background: Acute Type A Aortic Dissection (ATAD) is a surgical emergency with 18% mortality. Anatomic segment (root, ascending, arch, descending) impacts aneurysm natural history but mechanisms remain unclear. Aim: To compare proteomic profiles of human thoracic aortic segments that could account for distinct phenotypes and clinical outcomes; to analyze the largest cohort to date with enhanced depth of coverage. Methods: Aortic tissues were collected (N=148) from 82 unique individuals and analyzed using our customized proteomics protocol ( Figure 1A ). Conventional statistics, machine learning (t-distributed Stochastic Neighbour Embedding, t-SNE), and functional enrichment analyses were used to characterize significant phenotypic differences by segment. Differential protein expression was validated using immunofluorescence. Results: From all samples, 7251 proteins were identified (5660 quantified), exceeding literature (by 100s-1000s). Significant differences were greatest in comparisons of root, ascending, and descending aorta ( Figure 1B-C ). Root vs descending and ascending vs descending comparisons had clear separation in t-SNE analysis; root and ascending samples also clustered modestly ( Figure 1D ). MFAP4, a cellular-binding protein previously associated with descending thoracic dissection in Marfan patients, was significantly elevated in ascending aortic segments compared to root and descending. This was validated by immunofluorescence ( Figure 1E ). Conclusions: We extensively profiled thoracic aneurysm tissue using enhanced coverage, customized proteomics from the largest known cohort of human samples. Thoracic aneurysm phenotype differs by aortic segment as a function of intrinsic biochemical (proteomic) processes. Potential thoracic aneurysm biomarkers likely must account for aortic segment. Multiomic integrative analysis (DNA, RNA, post-translational data) are underway.