Discovery of plasma biomarkers with data-independent acquisition mass spectrometry and antibody microarray for diagnosis and risk stratification of pulmonary embolism

被引:10
|
作者
Han, Bingqing [1 ,2 ]
Li, Chuanbao [3 ]
Li, Hexin [4 ]
Li, Ying [2 ]
Luo, Xuanmei [2 ]
Liu, Ye [2 ]
Zhang, Junhua [2 ]
Zhang, Zhu [5 ]
Yu, Xiaobo [6 ]
Zhai, Zhenguo [5 ]
Xu, Xiaomao [7 ]
Xiao, Fei [1 ,2 ,4 ]
机构
[1] Peking Univ, Sch Clin Med 5, Beijing, Peoples R China
[2] Chinese Acad Med Sci, Beijing Hosp, Natl Ctr Gerontol,Key Lab Geriatr, Beijing Inst Geriatr,Natl Hlth Commiss,Inst Geria, Beijing, Peoples R China
[3] Chinese Acad Med Sci, Beijing Hosp, Natl Ctr Gerontol,Natl Hlth Commiss, Inst Geriatr Med,Dept Lab Med, Beijing, Peoples R China
[4] Chinese Acad Med Sci, Beijing Hosp, Natl Ctr Gerontol, Inst Geriatr Med,Clin Biobank,Natl Hlth Commiss, Beijing, Peoples R China
[5] Peking Univ, China Japan Friendship Hosp, Dept Resp & Clin Care Med, China Japan Friendship Sch Clin Med, Beijing, Peoples R China
[6] Beijing Proteome Res Ctr, Natl Ctr Prot Sci Beijing PHOENIX Ctr, Beijing Inst Life, State Key Lab Prote, Beijing, Peoples R China
[7] Chinese Acad Med Sci, Beijing Hosp, Natl Ctr Gerontol,Dept Resp & Crit Care Med, Inst Geriatr Med,Natl Hlth Commiss, Beijing, Peoples R China
基金
中国国家自然科学基金;
关键词
biomarkers; mass spectrometry; microarray analysis; proteomics; pulmonary embolism; HISTIDINE-RICH GLYCOPROTEIN; VENOUS THROMBOEMBOLISM; NATRIURETIC PEPTIDE; DENSITY-LIPOPROTEIN; TENASCIN-C; PROTEOMICS; DISEASE; THROMBOSIS; GLYCOSAMINOGLYCANS; GUIDELINES;
D O I
10.1111/jth.15324
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
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 ELISA 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.
引用
收藏
页码:1738 / 1751
页数:14
相关论文
共 50 条
  • [1] Data-independent acquisition mass spectrometry identification of extracellular vesicle biomarkers for gastric adenocarcinoma
    Gu, Lei
    Chen, Jin
    Yang, Yueying
    Zhang, Yunpeng
    Tian, Yuying
    Jiang, Jinhua
    Zhou, Donglei
    Liao, Lujian
    [J]. FRONTIERS IN ONCOLOGY, 2022, 12
  • [2] DIAmeter: matching peptides to data-independent acquisition mass spectrometry data
    Lu, Yang Young
    Bilmes, Jeff
    Rodriguez-Mias, Ricard A.
    Villen, Judit
    Noble, William Stafford
    [J]. BIOINFORMATICS, 2021, 37 : I434 - I442
  • [3] Novel circulating protein biomarkers for thyroid cancer determined through data-independent acquisition mass spectrometry
    Li, Dandan
    Wu, Jie
    Liu, Zhongjuan
    Qiu, Ling
    Zhang, Yimin
    [J]. PEERJ, 2020, 8
  • [4] Triqler for Protein Summarization of Data from Data-Independent Acquisition Mass Spectrometry
    Truong, Patrick
    The, Matthew
    Kall, Lukas
    [J]. JOURNAL OF PROTEOME RESEARCH, 2023, 22 (04) : 1359 - 1366
  • [5] Data-Independent Acquisition for the Detection of Mononucleoside RNA Modifications by Mass Spectrometry
    Janssen, Kevin A.
    Xie, Yixuan
    Kramer, Marianne C.
    Gregory, Brian D.
    Garcia, Benjamin A.
    [J]. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY, 2022, 33 (05) : 885 - 893
  • [6] A Comparative Analysis of Data Analysis Tools for Data-Independent Acquisition Mass Spectrometry
    Zhang, Fangfei
    Ge, Weigang
    Huang, Lingling
    Li, Dan
    Liu, Lijuan
    Dong, Zhen
    Xu, Luang
    Ding, Xuan
    Zhang, Cheng
    Sun, Yingying
    Jun, A.
    Gao, Jinlong
    Guo, Tiannan
    [J]. MOLECULAR & CELLULAR PROTEOMICS, 2023, 22 (09)
  • [7] Processing strategies and software solutions for data-independent acquisition in mass spectrometry
    Bilbao, Aivett
    Varesio, Emmanuel
    Luban, Jeremy
    Strambio-De-Castillia, Caterina
    Hopfgartner, Gerard
    Mueller, Markus
    Lisacek, Frederique
    [J]. PROTEOMICS, 2015, 15 (5-6) : 964 - 980
  • [8] Characterization of Cerebrospinal Fluid via Data-Independent Acquisition Mass Spectrometry
    Barkovits, Katalin
    Linden, Andreas
    Galozzi, Sara
    Schilde, Lukas
    Pacharra, Sandra
    Mollenhauer, Brit
    Stoepel, Nadine
    Steinbach, Simone
    May, Caroline
    Uszkoreit, Julian
    Eisenacher, Martin
    Marcus, Katrin
    [J]. JOURNAL OF PROTEOME RESEARCH, 2018, 17 (10) : 3418 - 3430
  • [9] New targeted approaches for the quantification of data-independent acquisition mass spectrometry
    Bruderer, Roland
    Sondermann, Julia
    Tsou, Chih-Chiang
    Barrantes-Freer, Alonso
    Stadelmann, Christine
    Nesvizhskii, Alexey I.
    Schmidt, Manuela
    Reiter, Lukas
    Gomez-Varela, David
    [J]. PROTEOMICS, 2017, 17 (09)
  • [10] Dedicated Software Enhancing Data-independent Acquisition Methods in Mass Spectrometry
    Bilbao, Aivett
    Lisacek, Frederique
    Hopfgartner, Gerard
    [J]. CHIMIA, 2016, 70 (04) : 293 - 293