A Comparative Metabolomics Approach Reveals Early Biomarkers for Metabolic Response to Acute Myocardial Infarction

Abstract

Discovery of novel biomarkers is critical for early diagnosis of acute coronary syndrome (ACS). Serum metabolite profiling of ST-elevation myocardial infarction (STEMI), unstable angina (UA) and healthy controls was performed using gas chromatography mass spectrometry (GC/MS), solid-phase microextraction coupled to gas chromatography mass spectrometry (SPME-GC/MS) and nuclear magnetic resonance (¹H-NMR). Multivariate data analysis revealed a metabolic signature that could robustly discriminate STEMI patients from both healthy controls and UA patients. This panel of biomarkers consisted of 19 metabolites identified in the serum of STEMI patients. One of the most intriguing biomarkers among these metabolites is hydrogen sulfide (H₂S), an endogenous gasotransmitter with profound effect on the heart. Serum H₂S absolute levels were further investigated using a quantitative double-antibody sandwich enzyme-linked immunosorbent assay (ELISA). This highly sensitive immunoassay confirmed the elevation of serum H₂S in STEMI patients. H₂S level discriminated between UA and STEMI groups, providing an initial insight into serum-free H₂S bioavailability during ACS. In conclusion, the current study provides a detailed map illustrating the most predominant altered metabolic pathways and the biochemical linkages among the biomarker metabolites identified in STEMI patients. Metabolomics analysis may yield novel predictive biomarkers that will potentially allow for an earlier medical intervention.

Figure 1

Representative GC/MS chromatograms of serum derived from a healthy control (A) and a STEMI patient (B). Peak numbers correspond to those listed in (Supplementary Table ST1).

Figure 2

GC/MS based PCA of STEMI patients (▴), before stent samples of UA patients () and healthy controls (●) (A) Score plot of PC1 and PC2 scores (B) Loading plot for PC1 components contributing peaks and their assignments, with each metabolite denoted by its mass/rt (min) value. Peak numbers correspond to those listed in (Supplementary Table ST1).

Figure 3

GC/MS based OPLS-DA of STEMI patients (▴), before stent samples of UA patients () and healthy controls (●) (A) OPLS-DA score plot (B) loading plot derived from samples modeled against each other. Selected variables are highlighted in the loading plot with each metabolite denoted by its mass/rt (min) value. Peak numbers correspond to those listed in (Supplementary Table S1).

Figure 4

GC/MS based PCA of before stent () versus after stent samples (■) of UA patients.

Figure 5

(A) Reconstructed GC/MS chromatograms for serum H₂S in samples derived from a healthy control, UA patient and a STEMI patient illustrating the difference in H₂S peak (M3) among different groups. Peak numbers correspond to those listed in (Supplementary Table ST1) (B) ELISA measured absolute H₂S serum levels in samples from healthy controls, before stent samples of UA patients and STEMI patients. Results are expressed as mean ± SEM. Statistically significant difference was observed between UA patients and healthy controls (^*P ≤ 0.05), STEMI patients and healthy controls (^***P ≤ 0.001), and STEMI patients and UA patients (^###P ≤ 0.001).

Figure 6

¹H-NMR based PCA of STEMI patients (▲), before stent samples of UA patients () and healthy controls (●) (A) Score plot of PC1 and PC2 scores (B) Loading plot for PC1 components contributing bin numbers. Differential signals high in STEMI were assigned in each bin as follows: Bin 92, D-glucose, carnitine and betaine; bin 94, D-glucose; bin 96, choline and D-glucose; bin 97, D-glucose, glycerol and glycine;bin 102, D-glucose; bin 125, β-glucose; bin 135, α-glucose.

Figure 7. A detailed map illustrating the most predominant altered metabolic pathways and the biochemical linkages among the biomarker metabolites identified in the serum of STEMI patients.