Serum biomarker discovery related to pathogenesis in acute coronary syndrome by proteomic approach

Abstract

Acute coronary syndrome (ACS) results from inadequate supply of blood flow from the coronary arteries to the heart or ischemia. ACS has an extremely high morbidity and mortality. The levels of biomarkers currently used for detection of ACS also increase in response to myocardial necrosis and other diseases and are not elevated immediately after symptoms appear, thus limiting their diagnostic capacity. Therefore, we aimed to discover new ACS diagnostic biomarkers with high sensitivity and specificity that are specifically related to ACS pathogenesis. Sera from 50 patients with ACS and healthy controls (discovery cohort) each were analyzed using mass spectrometry (MS) to identify differentially expressed proteins, and protein candidates were evaluated as ACS biomarkers in 120 people in each group (validation cohort). α-1-acid glycoprotein 1 (AGP1), complement C5 (C5), leucine-rich α-2-glycoprotein (LRG), and vitronectin (VN) were identified as biomarkers whose levels increase and gelsolin (GSN) as a biomarker whose levels decrease in patients with ACS. We concluded that these biomarkers are associated with the pathogenesis of ACS and can predict the onset of ACS prior to the appearance of necrotic biomarkers.

Keywords: acute coronary syndrome; biomarkers; pathogenesis; proteomics.

Figure 1. Flowchart of experiment set

Sera of 50 patients with ACS and 50 healthy controls consisted of pooled and individual serum samples, respectively, and the samples were prepared for MS. The pooled serum samples were analyzed in information-dependent acquisition (IDA) mode to generate a library of proteins. In addition, protein identification was performed by matching the data of individual serum samples analyzed with sequential window acquisition of all theoretical fragment-ion spectra (SWATH) mode to the library. Peptides from each protein were quantified using MRM acquisition mode for validation of biomarkers identified from candidate proteins.

Figure 2. Proteomic analysis of proteins from patients with ACS and healthy controls

(A) The PCA score plot showed clustering of patients with ACS and healthy control groups. Each dot indicates patients with ACS (red) and healthy controls (green). (B) The loading plot showed proteins from patients with ACS and healthy controls. The proteins helped distinguish each group of patients with ACS and healthy controls in the PCA score plot. (C) A total of 242 and 227 proteins were identified in patients with ACS and healthy controls, respectively, and 191 proteins were overlapped between the groups. Therefore, these 191 proteins were common to all subjects. Using t test, we identified 119 statistically significant proteins out of 191 differentially expressed proteins between patients with ACS and healthy controls (P-value < 0.05, fold change ≥1.2 or ≤1/1.2).

Figure 3. Heat map of the protein candidates between patients with ACS and healthy controls

The heat map showed the difference in expression of protein candidates between patients with ACS and healthy controls using Z-score. AGP1, complement C5, leucine-rich α-2-glycoprotein, and vitronectin were up-regulated proteins in patients with ACS. Apolipoprotein L1, gelsolin, and tetranectin were down-regulated proteins in patients with ACS; A1AG1, α-1-acid glycoprotein 1; A2GL, leucine-rich α-2-glycoprotein; CO5, complement C5; VTNC, vitronectin; APOL1, apolipoprotein L1; GELS, gelsolin; TETN, tetranectin.

Figure 4. Scatter plots of ACS early diagnostic biomarkers

Five biomarkers were selected as proteins showing the same expression in the discovery and validation set. The scatter plots indicate expression of biomarkers in patients with ACS and healthy controls. (A) AGP1, (B) complement C5, (C) leucine-rich α -2-glycoprotein, and (D) vitronectin were up-regulated proteins in patients with ACS. In contrast, (E) gelsolin was the down-regulated protein in patients with ACS. The difference in the expression of all biomarkers was statistically significant. Data are presented as mean ± SD. *P<0.001.

Figure 5. ROC curves of ACS early diagnostic biomarkers

The ROC curves showed the AUC of ACS early diagnostic biomarkers. (A) The AUC of AGP1 was 0.8744. (B) The AUC of complement C5 was 0.7765. (C) The AUC of leucine-rich α-2-glycoprotein was 0.8075. (D) The AUC of vitronectin was 0.7790. (E) The AUC of gelsolin was 0.7142. All ACS early diagnostic biomarkers had AUC higher than 0.7. (F) The AUC of all combined biomarkers was 0.9722, which displayed the highest result.