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Optimized Protocol for the Extraction of Proteins from the Human Mitral Valve
Published on: June 14, 2017
Thoracic aortic diseases: Identification of diagnostic biomarkers using proteomic analysis
Nico Arndt1, Thomas Mair2, Maria Riedner3
1Department of Cardiovascular Surgery, University Heart & Vascular Center Hamburg, Germany.
Introduction:
Thoracic aortic aneurysms frequently go undetected until serious complications like acute dissections or ruptures arise. Therefore, this study aims to identify potential blood circulating biomarkers enabling an easy and early diagnosis of thoracic aortic disease.
Methods:
Potential biomarker candidates were identified through two different techniques, untargeted and targeted proteomic as well as extracellular vesicle (EV) analyses. The biomarker levels were compared between two patient groups with thoracic aortic aneurysms and two control groups without thoracic aortic disease. In total, 80 patients (TAA group (n = 40) vs. control group (n = 40)) were matched for untargeted and targeted proteome analysis, and 85 for EV analysis (TAA group (n = 42) vs. control group (n = 43)), based on the availability of blood samples and excised aortic tissue. Levels of biomarker candidates were correlated with aortic diameter, patient age, and histological alterations in aortic tissue using linear and logistic regression models.
Results:
The untargeted proteomic and EV analysis identified 1,037 and 1,077 proteins, respectively, of which 11 and 28 proteins showed significant differences in concentration between the study groups. Of these, 9 proteins correlated with the aortic diameter: ACTN1 (Regression coefficient B = 1.633, p < 0.001), CRP (B = 0.001, p = 0.004), TGM3 (B=-0.293, p = 0.010), KRT84 (B=-0.477, p = 0.010), IGHG3 (-0.267, p = 0.018), DPYSL2 (B = 0.644, p = 0.020), TSPAN8 (B-0.838, p = 0.042), IGKV3D-11 (B=-0.242, p = 0.046), and VDAC1 (B=-0.491, p = 0.047). Moreover, IGKV3D-11 (B=-3.257, p = 0.029), IGHG3 (B=-0.003, p = 0.034), and APOC3 (B=-2.104, p = 0.037) showed significant correlations with the grade of aortic medial layer degeneration. None of the proteins correlated with patient age.
Conclusion:
The study identified 9 biomarker candidates correlating with the aortic diameter. To enable the clinical use for diagnosis and prognostic assessment, these biomarkers need to be validated in larger external cohorts.
