BACKGROUND: Heart failure (HF) is becoming an increasingly prevalent issue, particularly among the elderly population. Lipids are closely associated with cardiovascular disease (CVD) pathology. Lipidomics as a comprehensive profiling tool is showing to be promising in the prediction of events and mortality due to CVD as well as identifying novel biomarkers. MATERIALS AND METHODS: In this study, eicosanoids and lipid profiles were measured in order to predict survival in patients with de novo or acute decompensated HF. Our study included 50 patients (16 females, mean age 73 years and 34 males, mean age 71 years) with de novo or acute decompensated chronic HF with a median follow-up of 7 months. Lipids were semiquantified using targeted lipidomic liquid chromatography-mass spectrometry (LC-MS/MS) analysis. Eicosanoid concentrations were determined using a commercially available sandwich ELISA assay. RESULTS: From 736 lipids and 3 eicosanoids, 39 significant lipids were selected (by using the Mann-Whitney U test after Benjamini-Hochberg correction) with the highest number of representatives belonging to the polyunsaturated (PUFA) phosphatidylcholines (PC). PC 42:10 (p = 1.44 × 10-4) was found to be the most statistically significantly elevated in the surviving group with receiver operating characteristics of AUC = 0.84 (p = 3.24 × 10-7). A multivariate supervised discriminant analysis based on the aforementioned lipid panel enabled the classification of the groups of surviving and non-surviving patients with 90 % accuracy. CONCLUSIONS: In the present study we describe a trend in PUFA esterified in PC that were systematically increased in surviving patients with HF. This trend in low-abundant and rarely identified PUFA PC (mainly very long chain PUFA containing PC such as PC 42:10 or PC 40:9 containing FA 22:6, FA 20:5 and FA 20:4) suggests candidate biomarkers.

• Keywords
• Atherosclerosis, Eicosanoids, HF survival, Heart failure, Lipidomics, PC, PUFA, Phosphatidylcholine, Survival rate,
• Publication type
• Journal Article MeSH