ABSTRACT
AIMS: Identification of metabolic signatures in heart failure (HF) patients and evaluation of their diagnostic potential to discriminate HF patients from healthy controls during baseline and exercise conditions. METHODS: Plasma samples were collected from 22 male HF patients with non-ischemic idiopathic cardiomyopathy and left ventricular systolic dysfunction and 19 healthy controls before (t0), at peak (t1) and 1 h after (t2) symptom-limited cardiopulmonary exercise testing. Two hundred fifty-two metabolites were quantified by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography (LC)-MS/MS-based metabolite profiling. RESULTS: Plasma metabolite profiles clearly differed between HF patients and controls at t0 (P < 0.05). The metabolic signature of HF was characterized by decreased levels of complex lipids and fatty acids, notably phosphatidylcholines, cholesterol, and sphingolipids. Moreover, reduced glutamine and increased glutamate plasma levels, significantly increased purine degradation products, as well as signs of impaired glucose metabolism were observed. The metabolic differences increased strongly according to New York Heart Association functional class and the addition of three metabolites further improved prediction of exercise capacity (Q2 = 0.24 to 0.35). Despite a high number of metabolites changing significantly with exercise (30.2% at t1/t0), the number of significant alterations between HF and controls was almost unchanged at t1 and t2 (30.7 and 29.0% vs. 31.3% at t0) with a similar predictive group separation (Q2 = 0.50 for t0, 0.52 for t1, and 0.56 for t2, respectively). CONCLUSIONS: Our study identified a metabolic signature of non-ischemic HF with prominent changes in complex lipids including phosphatidylcholines, cholesterol, and sphingolipids. The metabolic changes were already evident at rest and largely preserved under exercise.
ABSTRACT
OBJECTIVES: In this study we aimed to identify novel metabolomic biomarkers suitable for improved diagnosis of heart failure with reduced ejection fraction (HFrEF). METHODS: We prospectively recruited 887 individuals consisting of HFrEF patients with either ischemic (ICMP, n = 257) or nonischemic cardiomyopathy (NICMP, n = 269), healthy controls (n = 327), and patients with pulmonary diseases (n = 34). A single-center identification (n = 238) was followed by a multicenter confirmation study (n = 649). Plasma samples from the single-center study were subjected to metabolite profiling analysis to identify metabolomic features with potential as HFrEF biomarkers. A dedicated analytical protocol was developed for the routine analysis of selected metabolic features in the multicenter cohort. RESULTS: In the single-center study, 92 of 181 metabolomic features with known chemical identity (51%) were significantly changed in HFrEF patients compared to healthy controls (P <0.05). Three specific metabolomic features belonging to the lipid classes of sphingomyelins, triglycerides, and phosphatidylcholines were selected as the cardiac lipid panel (CLP) and analyzed in the multicenter study using the dedicated analytical protocol. The combination of the CLP with N-terminal pro-B-type natriuretic peptide (NT-proBNP) distinguished HFrEF patients from healthy controls with an area under the curve (AUC) of 0.97 (sensitivity 80.2%, specificity 97.6%) and was significantly superior compared to NT-proBNP alone (AUC = 0.93, sensitivity 81.7%, specificity 88.1%, P <0.001), even in the subgroups with mildly reduced left ventricular EF (0.94 vs 0.87; P <0.001) and asymptomatic patients (0.95 vs 0.91; P <0.05). CONCLUSIONS: The new metabolomic biomarker panel has the potential to improve HFrEF detection, even in mild and asymptomatic stages. The observed changes further indicate lipid alterations in the setting of HFrEF.
