期刊
MOLECULAR MEDICINE REPORTS
卷 19, 期 5, 页码 3972-3988出版社
SPANDIDOS PUBL LTD
DOI: 10.3892/mmr.2019.10088
关键词
biomarker; myocardial infarction; urinary proteomics
资金
- National Basic Research Program of China [2013CB530805, 2014CBA02005]
- National Key Research and Development Program of China [2016 YFC 1306300]
- Key Basic Research Program of the Ministry of Science and Technology of China [2013FY114100]
- National Natural Science Foundation of China [30970650, 31200614, 31400669, 81371515, 81170665, 81560121]
- Science and Technology Yuanjiang Project of The Xinjiang Uygur Autonomous Region [2013911114]
- CAMS Innovation Fund for Medical Sciences [2017-I2M-1-009]
- National Scientific Data Sharing Platform for Population and Health
- Biologic Medicine Information Center of China
Myocardial infarction (MI) is a disease characterized by high morbidity and mortality rates. MI biomarkers are frequently used in clinical diagnosis; however, their specificity and sensitivity remain unsatisfactory. Urinary proteome is an easy, efficient and noninvasive source to examine biomarkers associated with various diseases. The present study, to the best of the authors' knowledge, is the first to examine the urinary proteome using the isobaric tags for relative and absolute quantitation (iTRAQ) technology to identify potential diagnostic biomarkers of MI. The urinary proteome was analyzed within 12 h following the first symptoms of early-onset MI and at day 7 following percutaneous coronary intervention via iTRAQ labeling and two-dimensional liquid chromatography-tandem mass spectrometry. Candidate biomarkers were validated by multiple reaction monitoring (MRM) analysis. A total of 233 urinary proteins were differentially expressed. Gene enrichment analysis identified that the urinary proteome in patients with MI was associated with atherosclerosis, abnormal coagulation and abnormal cell metabolism. In total, 12 differentially expressed urinary proteins were validated by MRM analysis, five of which were associated with MI for the first time in the present study. Binary logistic regression analysis suggested that the combination of five urinary proteins (antithrombin-III, complement C3, -1-acid glycoprotein 1, serotransferrin and cathepsin Z) may be used to diagnose MI with 94% sensitivity and 93% specificity. In addition, the protein expression levels of three proteins were significantly restored to normal levels following surgical treatment. The verified candidate biomarkers may be used for the diagnosis of MI, and for monitoring the disease status and the effects of treatments for MI. The present results may facilitate future clinical applications of the urinary proteome to diagnose MI.
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