Plasma amino acid profiling improves predictive accuracy of adverse events in patients with heart failure

Abstract Aims The clinical outcome of heart failure (HF) is complicated by the presence of multiple comorbidities including malnutrition and cachexia, and prediction of the outcome is still difficult in each patient. Metabolomics including amino acid profiling enables detection of alterations in whole body metabolism. The aim of this study was to determine whether plasma amino acid profiling improves prediction of clinical outcomes in patients with HF. Methods and results We retrospectively examined 301 HF patients (70 ± 15 years old; 59% male). Blood samples for measurements of amino acid concentrations were collected in a fasting state after stabilization of HF. Plasma amino acid concentrations were measured using ultraperformance liquid chromatography. Clinical endpoint of this study was adverse event defined as all‐cause death and unscheduled readmission due to worsening HF or lethal arrhythmia. During a mean follow‐up period of 380 ± 214 days, 40 patients (13%) had adverse events. Results of analyses of variable importance in projection score, a measure of a variable's importance in partial least squares–discriminant analysis (PLS‐DA) showed that the top five amino acids being associated with adverse events were 3‐methylhistidine (3‐Me‐His), β‐alanine, valine, hydroxyproline, and tryptophan. Multivariate Cox‐proportional hazard analyses indicated that a high 3‐Me‐His concentration and low β‐alanine and valine concentrations were independently associated with adverse events. When HF patients were divided according to the cut‐off values of amino acids calculated from receiver operating characteristic curves, Kaplan–Meier survival curves showed that event‐free survival rates were lower in HF patients with high 3‐Me‐His than in HF patients with low 3‐Me‐His (68% vs. 91%, P