Lipid Biomarkers in Acute Myocardial Infarction Before and After Percutaneous Coronary Intervention by Lipidomics Analysis

Abstract

BACKGROUND Reperfusion injury is one of the leading causes of myocardial cell death and heart failure. This study was performed to identify new candidate lipid biomarkers for the purpose of optimizing the diagnosis of myocardial ischemia reperfusion (I/R) injury, assessing the severity of myocardial I/R injury and trying to find the novel mechanism related to lipids. MATERIAL AND METHODS Forty patients who were diagnosed with ST-segment elevation myocardial infarction (STEMI) were randomly selected for this study. Serum samples from all the patients with STEMI were collected at 3 time periods: after STEMI diagnosis but prior to reperfusion (T0); and then at 2 hours (T2) and 24 hours (T24) after the end of the percutaneous coronary intervention procedure. Plasma lipidomics profiling analysis was performed to identify the lipid metabolic signatures of myocardial I/R injury using lipidomics. RESULTS Sixteen types of potential lipid biomarkers at different time periods (T0, T2, T24) were identified by using lipidomics technology. The T0 time periods exhibited 16 differentially metabolized lipid peaks in the patients after STEMI diagnosis but prior to reperfusion. With the increase of reperfusion times, the contents of these 16 lipid biomarkers decreased gradually, but there was a 1.5- to 2-fold increase of those 16 lipid biomarkers contents at T2 compared with T24. CONCLUSIONS Lipidomics analysis demonstrated differential change before and after reperfusion, suggesting a potential role of some of these lipids as biomarkers for optimizing the diagnosis of myocardial I/R, as well as for therapeutic targets against myocardial I/R injury.

Figure 1

A slice of data containing a contiguous m/z range extending across all RT is called an extracted ion chromatogram (XIC). Representative XIC from T₀ time periods (A), T₂ time periods (B), and T₂₄ time periods (C). The different lipid metabolites detected were as follows: myristic acid, palmitic acid, palmitoleic acid, heptadecanoic acid, stearic acid, oleic acid, linoleic acid, γ-linolenic acid, eicosanoic acid, eicosadienoic acid, eicosatrienoic acid, arachidonic acid, eicosapentaenoic acid, hexadecyl azelaoyl phosphatidylcholine, docosapentaenoic acid, and docosahexaenoic acid.

Figure 2

PCA score plot for T₀ time periods, T₂ time periods, and T₂₄ time periods; score plots displaying discrimination regarding T₀ time periods (blue circles), T₂ time periods (green circles), and T₂₄ time periods (red circles) (R2=0.54861; Q2=0.30092).

Figure 3

Score plot of PLS-DA for T₀ time periods T₂ time periods, and T₂₄ time periods, score plots indicated the separation degree between T₀ time periods (blue circles), T₂ time periods (green circles), and T₂₄ time periods (red circles) (R2X=0.419, R2Y=0.899, Q2=0.751).

Figure 4

Validation of PLS-DA: a permutation test was conducted with 200 randomly initiated permutations in a PLS-DA model showing R 2 (green rounds) and Q 2 (blue rounds) values from the permuted analysis (left-bottom corner), and these are far lower than the associated initial values (right-top corner).