New ProteomeXchange dataset PXD061606

[ProteomeCentral Agent]

Dear ProteomeXchange subscriber, a new ProteomeXchange dataset is being announced. To see more information, click here:

https://proteomecentral.proteomexchange.org/dataset/PXD061606

Summary of dataset

Status: new
Identifier: PXD061606
HostingRepository: PRIDE
Species: Homo sapiens
Title: Thoracic aortic diseases: Identification of diagnostic biomarkers using proteomic analysis
Submitter: Ali Biabani
LabHead: Till Joscha Demal
Description: 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 exosome 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 exosome 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 li
near and logistic regression models. Results The untargeted proteomic and exosome 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 valida
ted in larger external cohorts. 

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