No abstract

Metabolomics demonstrate powerful diagnostic value in estimating HF-related metabolic disturbance. The profile of metabolites provides better prognostic value versus conventional biomarkers.

In heart failure (HF), metabolic disturbances represent functional perturbations in peripheral tissues and also predict patient outcomes. This study developed a simplified essential amino acid-based profile and tested whether it could improve prognostication. Plasma essential amino acids and lipidomics were measured on 1084 participants. The initial cohort included 94 normal controls and 599 patients hospitalized due to acute/decompensated HF. The validation cohort included 391 HF patients. Patients were followed for composite events (death/HF related re-hospitalization) and were categorized into three groups: high risk type 1 (leucine ≥145 μM and phenylalanine ≥ 88.9 μM), high risk type 2 (leucine < 81.2 μM), and low risk (other). Types 1 and 2 were associated with higher event rates [hazard ratio (95% confidence intervals) = 1.88 (1.27-2.79) and 7.71 (4.97-11.9), respectively, p < 0.001]. Compared to the low-risk group, both types of high-risk patients were older and had lower blood pressure and estimated glomerular filtration rates, but higher B-type natriuretic peptides (BNP). In addition, type 1 was associated with more incompletely metabolized lipids in the blood; type 2 patients had lower body mass indexes, rates of using guideline-based medications, and levels of cholesterol, hemoglobin, and albumin. The prognostic value of types 1 and 2 remained significant after adjusting for age, BNP and other risk factors. The value of using high-risk types for prognosis was confirmed in the validation cohort. In conclusion, simplified essential amino acid-based profiling identified two high-risk populations and provided metabolic information and prognostic value additive to traditional risk factors.