Author: Han, Bingqing; Li, Chuanbao; Li, Hexin; Li, Ying; Luo, Xuanmei; Liu, Ye; Zhang, Junhua; Zhang, Zhu; Yu, Xiaobo; Zhai, Zhenguo; Xu, Xiaomao; Xiao, Fei
Title: Discovery of plasma biomarkers with data-independent acquisition mass spectrometry and antibody microarray for diagnosis and risk stratification of pulmonary embolism. Cord-id: mpyg0sqq Document date: 2021_4_7
ID: mpyg0sqq
Snippet: BACKGROUND Pulmonary embolism (PE) is a leading cause of cardiovascular mortality worldwide. Rapid and accurate diagnosis and risk stratification are crucial for timely treatment options, especially in high-risk PE. OBJECTIVES The study aims to profile the comprehensive changes of plasma proteomes in PE patients and identify the potential biomarkers for both diagnosis and risk stratification. PATIENTS/METHODS Based on the data-independent acquisition mass spectrometry and antibody array proteomi
Document: BACKGROUND Pulmonary embolism (PE) is a leading cause of cardiovascular mortality worldwide. Rapid and accurate diagnosis and risk stratification are crucial for timely treatment options, especially in high-risk PE. OBJECTIVES The study aims to profile the comprehensive changes of plasma proteomes in PE patients and identify the potential biomarkers for both diagnosis and risk stratification. PATIENTS/METHODS Based on the data-independent acquisition mass spectrometry and antibody array proteomic technology, we screened the plasma samples (13 and 32 proteomes, respectively) in two independent studies consisting of high-risk PE patients, non-high-risk PE patients, and healthy controls. Some significantly differentially expressed proteins were quantified by enzyme-linked immunosorbent assay in a new study group with 50 PE patients and 26 healthy controls. RESULTS We identified 207 and 70 differentially expressed proteins in PE and high-risk PE. These proteins were involved in multiple thrombosis-associated biological processes including blood coagulation, inflammation, injury, repair, and chemokine-mediated cellular response. It was verified that five proteins including SAA1, S100A8, TNC, GSN and HRG had significant change in PE and/or in high-risk PE. The Receiver Operating Characteristic curve analysis based on binary Logistic regression showed that the area under the curve (AUC) of SAA1, S100A8, and TNC in PE diagnosis were 0.882, 0.788, and 0.795, and AUC of S100A8 and TNC in high-risk PE diagnosis were 0.773 and 0.720. CONCLUSION As predictors of inflammation or injury repair, SAA1, S100A8, and TNC are potential plasma biomarkers for the diagnosis and risk stratification of PE.
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