Original Article
Discovery of potential plasma protein biomarkers for acute myocardial infarction via proteomics
Abstract
Background: Acute myocardial infarction (AMI) is an acute disease with high mortality and seriously threatens human health. The identification of new effective biological markers for AMI is a prerequisite for treatment. Most proteomic studies have focused on atherosclerotic plaques, vascular cells, monocytes and platelets in the blood; however, the concentration of these factors in plasma is low, making it difficult to measure the complexity of plasma components. Moreover, some studies have examined the plasma protein of patients with acute coronary syndrome with histochemistry; however, the results are not consistent. Therefore, it is necessary to further investigate the differential proteins in the plasma of patients with AMI via proteomics to identify new biomarkers of AMI.
Methods: In this study, immunodepletion of high-abundance plasma proteins followed by an isobaric tagging for relative and absolute quantitation (iTRAQ)-based quantitative proteomic approach was used to analyze plasma samples from 5 control individuals and 10 AMI patients.
Results: Four hundred sixty-eight proteins were identified from two samples, and 33 proteins were differentially expressed in AMI patients compared to the controls. Among the 33 proteins, 12 proteins showed a ≥1.5-fold change between AMI and control samples. These proteins included fatty acid binding protein 3 (FABP3, ratio =6.36), creatine kinase-MB (CK-MB ratio =4.89), adenylate kinase1 (AK1 ratio =4.16), pro-platelet basic protein (PPBP ratio =3.29), creatine kinase (CK ratio =2.88), platelet factor 4 (PF4 ratio =2.62), peptidyl prolyl isomerase Cyclophilin A (PPIA ratio =2.05), Cofilin-1 (CFL1 ratio =1.81), coronin1A (CORO1A ratio =1.71), protein kinase M (PKM ratio =1.63), ribonuclease inhibitor (RNH1, ratio =1.67), and triose phosphate isomerase (TPI1 ratio =1.56). By contrast, there was a decrease of 19 proteins, such as adiponectin (ADIPOQ ratio =0.70), insulin-like growth factor binding protein6 (IGFBP6 ratio =0.70), Dickkopf-related protein 3 (DKK3 ratio =0.70) and complement 4B (C4B ratio =0.68). The most over-represented term was regulation of cell proliferation in the cellular component category of Gene Ontology (GO). The top 3 biological process terms were regulation of cell proliferation, response to wounding and wound healing. These proteins included immune proteins, blood coagulation proteins, lipid metabolism proteins, cytoskeleton proteins, energy metabolism proteins, gene regulation proteins, myocutaneous proteins, and myocardial remodeling proteins and were highly connected with each other, which indicates that the functional network of these processes contribute to the pathophysiology of AMI.
Conclusions: In conclusion, the present quantitative proteomic study identified novel AMI biomarker candidates and might provide fundamental information for the development of an AMI biomarker.
Methods: In this study, immunodepletion of high-abundance plasma proteins followed by an isobaric tagging for relative and absolute quantitation (iTRAQ)-based quantitative proteomic approach was used to analyze plasma samples from 5 control individuals and 10 AMI patients.
Results: Four hundred sixty-eight proteins were identified from two samples, and 33 proteins were differentially expressed in AMI patients compared to the controls. Among the 33 proteins, 12 proteins showed a ≥1.5-fold change between AMI and control samples. These proteins included fatty acid binding protein 3 (FABP3, ratio =6.36), creatine kinase-MB (CK-MB ratio =4.89), adenylate kinase1 (AK1 ratio =4.16), pro-platelet basic protein (PPBP ratio =3.29), creatine kinase (CK ratio =2.88), platelet factor 4 (PF4 ratio =2.62), peptidyl prolyl isomerase Cyclophilin A (PPIA ratio =2.05), Cofilin-1 (CFL1 ratio =1.81), coronin1A (CORO1A ratio =1.71), protein kinase M (PKM ratio =1.63), ribonuclease inhibitor (RNH1, ratio =1.67), and triose phosphate isomerase (TPI1 ratio =1.56). By contrast, there was a decrease of 19 proteins, such as adiponectin (ADIPOQ ratio =0.70), insulin-like growth factor binding protein6 (IGFBP6 ratio =0.70), Dickkopf-related protein 3 (DKK3 ratio =0.70) and complement 4B (C4B ratio =0.68). The most over-represented term was regulation of cell proliferation in the cellular component category of Gene Ontology (GO). The top 3 biological process terms were regulation of cell proliferation, response to wounding and wound healing. These proteins included immune proteins, blood coagulation proteins, lipid metabolism proteins, cytoskeleton proteins, energy metabolism proteins, gene regulation proteins, myocutaneous proteins, and myocardial remodeling proteins and were highly connected with each other, which indicates that the functional network of these processes contribute to the pathophysiology of AMI.
Conclusions: In conclusion, the present quantitative proteomic study identified novel AMI biomarker candidates and might provide fundamental information for the development of an AMI biomarker.
