Thoracic aortic diseases: Identification of diagnostic biomarkers using proteomic analysis

IF 1.9 4区医学 Q2 CARDIAC & CARDIOVASCULAR SYSTEMS

Cardiovascular Pathology Pub Date : 2026-01-01 Epub Date: 2025-10-07 DOI:10.1016/j.carpath.2025.107785

Nico Arndt , Thomas Mair , Maria Riedner , Ali Biabani , Hannah Voß , Hartmut Schlüter , Lukas Förster , Tim Knochenhauer , Marco Sachse , Martin Beyer , Maya Leonhardt , Yskert von Kodolitsch , Christian Schlein , Guido Sauter , Theresa Nauth , Shiho Naito , Evaldas Girdauskas , Hermann Reichenspurner , Christian Detter , Georg Rosenberger , Till Joscha Demal

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引用次数: 0

Abstract

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.

查看原文本刊更多论文

胸主动脉疾病：用蛋白质组学分析鉴定诊断性生物标志物。

引言：胸主动脉瘤通常不被发现，直到出现严重的并发症，如急性夹层或破裂。因此，本研究旨在确定潜在的血液循环生物标志物，使胸主动脉疾病的早期诊断变得容易。方法：通过两种不同的技术，非靶向和靶向蛋白质组学以及细胞外囊泡（EV）分析，鉴定潜在的生物标志物候选物。比较两组胸主动脉瘤患者和两组无胸主动脉瘤疾病的对照组的生物标志物水平。根据血液样本和切除主动脉组织的可用性，总共有80例患者（TAA组（n=40）对对照组（n=40））进行了非靶向和靶向蛋白质组分析，85例患者（TAA组（n=42）对对照组（n=43））进行了EV分析。使用线性和逻辑回归模型，候选生物标志物水平与主动脉直径、患者年龄和主动脉组织组织学改变相关。结果：非靶向蛋白质组学和EV分析分别鉴定出1037种和1077种蛋白质，其中11种和28种蛋白质在研究组之间的浓度存在显著差异。其中，9种蛋白与主动脉内径相关：ACTN1（回归系数B=1.633, p）。结论：本研究确定了9种与主动脉内径相关的候选生物标志物。为了使临床应用于诊断和预后评估，这些生物标志物需要在更大的外部队列中进行验证。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cardiovascular Pathology 医学-病理学

CiteScore

7.50

自引率

2.70%

发文量

审稿时长

18 days

期刊介绍： Cardiovascular Pathology is a bimonthly journal that presents articles on topics covering the entire spectrum of cardiovascular disease. The Journal''s primary objective is to publish papers on disease-oriented morphology and pathogenesis from clinicians and scientists in the cardiovascular field. Subjects covered include cardiovascular biology, prosthetic devices, molecular biology and experimental models of cardiovascular disease.