Serum lipidomics reveals phosphatidylethanolamine and phosphatidylcholine disorders in patients with myocardial infarction and post-myocardial infarction-heart failure

Abstract

Abstract Background Myocardial infarction (MI) and post-MI-heart failure (pMIHF) are a major cause of death worldwide, however, the underlying mechanisms of pMIHF from MI are not well understood. This study sought to characterize early lipid biomarkers for the development of pMIHF disease. Methods Serum samples from 18 MI and 24 pMIHF patients were collected from the Affiliated Hospital of Zunyi Medical University and analyzed using lipidomics with Ultra High Performance Liquid Chromatography and Q-Exactive High Resolution Mass Spectrometer. The serum samples were tested by the official partial least squares discriminant analysis (OPLS-DA) to find the differential expression of metabolites between the two groups. Furthermore, the metabolic biomarkers of pMIHF were screened using the subject operating characteristic (ROC) curve and correlation analysis. Results The average age of the 18 MI and 24 pMIHF participants was 57.83 ± 9.28 and 64.38 ± 10.89 years, respectively. The B-type natriuretic peptide (BNP) level was 328.5 ± 299.842 and 3535.96 ± 3025 pg/mL, total cholesterol(TC) was 5.59 ± 1.51 and 4.69 ± 1.13 mmol/L, and blood urea nitrogen (BUN) was 5.24 ± 2.15 and 7.20 ± 3.49 mmol/L, respectively. In addition, 88 lipids, including 76 (86.36%) down-regulated lipids, were identified between the patients with MI and pMIHF. ROC analysis showed that phosphatidylethanolamine (PE) (12:1e_22:0) (area under the curve [AUC] = 0.9306) and phosphatidylcholine (PC) (22:4_14:1) (AUC = 0.8380) could be potential biomarkers for the development of pMIHF. Correlation analysis showed that PE (12:1e_22:0) was inversely correlated with BNP and BUN, but positively correlated with TC. In contrast, PC (22:4_14:1) was positively associated with both BNP and BUN, and was negatively associated with TC. Conclusions Several lipid biomarkers were identified that could potentially be used to predict and diagnose patients with pMIHF. PE (12:1e_22:0) and PC (22:4_14:1) could sufficiently differentiate between patients with MI and pMIHF.