Metabolomics Fingerprint Predicts Risk of Death in Dilated Cardiomyopathy and Heart Failure

Abstract

Background: Heart failure (HF) is a leading cause of morbidity and mortality worldwide. Metabolomics may help refine risk assessment and potentially guide HF management, but dedicated studies are few. This study aims at stratifying the long-term risk of death in a cohort of patients affected by HF due to dilated cardiomyopathy (DCM) using serum metabolomics via nuclear magnetic resonance (NMR) spectroscopy.

Methods: A cohort of 106 patients with HF due to DCM, diagnosed and monitored between 1982 and 2011, were consecutively enrolled between 2010 and 2012, and a serum sample was collected from each participant. Each patient underwent half-yearly clinical assessments, and survival status at the last follow-up visit in 2019 was recorded. The NMR serum metabolomic profiles were retrospectively analyzed to evaluate the patient's risk of death. Overall, 26 patients died during the 8-years of the study.

Results: The metabolomic fingerprint at enrollment was powerful in discriminating patients who died (HR 5.71, p = 0.00002), even when adjusted for potential covariates. The outcome prediction of metabolomics surpassed that of N-terminal pro b-type natriuretic peptide (NT-proBNP) (HR 2.97, p = 0.005). Metabolomic fingerprinting was able to sub-stratify the risk of death in patients with both preserved/mid-range and reduced ejection fraction [hazard ratio (HR) 3.46, p = 0.03; HR 6.01, p = 0.004, respectively]. Metabolomics and left ventricular ejection fraction (LVEF), combined in a score, proved to be synergistic in predicting survival (HR 8.09, p = 0.0000004).

Conclusions: Metabolomic analysis via NMR enables fast and reproducible characterization of the serum metabolic fingerprint associated with poor prognosis in the HF setting. Our data suggest the importance of integrating several risk parameters to early identify HF patients at high-risk of poor outcomes.

Keywords: NMR spectroscopy; heart failure; metabolomics; precision medicine; prognosis.

Figure 1

Graphical overview of the study design to investigate differences between survived and deceased patients with HF. Patients were diagnosed at time t0, where t0 for each patient was in the range 1982–2011. Between 2010 and 2012 (t1), the patients were re-examined or examined for the first time, blood serum samples collected and analyzed via nuclear magnetic resonance (NMR). Survival status was evaluated in 2019 (t2). Patients were, then, retrospectively split in two groups according to the survival status (alive vs. deceased), and statistical analysis on NMR data was performed.

Figure 2

(A) score plot of the first two components of the partial least square discriminant analysis (PLS-DA) model discriminating survivor (80 green dots) and deceased (26 purple dots) patients. (B) The variable importance in projections (VIP) score plot indicating the most discriminating bins in descending order of importance; only the bins that showed a VIP score>1 are reported in the plot. For each bin the starting ppm is reported. Green dots represent bins with intensity higher in survivor patients, conversely purple dots represent bins with intensity higher in deceased patients. (C) Overall patients with HF, plotting actual survival over time (in years) according to estimated metabolomic risk [Kaplan-Meier (KM) curves]. Low metabolomic risk (green) and high metabolomic risk (purple) patients are significantly clustered with a p-value of 1.67·10⁻⁵ (calculated with the Log-Rank test) and an HR of 5.71. Censored events represent either the time of last recorded clinical follow-up, or the time of death. Number at risk: number of patients stratified according to the metabolomics classification at each time point. Cumulative number of events: total number of deceased patients at each time point for each metabolomics risk group. PLS_PRED = S, predicted by PLS as survivor; PLS_PRED = D, predicted by PLS as deceased.

Figure 3

Overall patients with HF, plotting actual survival over time (measured in years) according to risk estimated based on ejection fraction (Kaplan-Meier curves). High-risk (red) group is significantly clustered with respect to both intermediate (yellow) and low (blue) risk groups with HR of 4.26 and 7.47, respectively. Censored events represent either the time of last recorded clinical follow up, or time of death. Number at risk: number of patients stratified according to the left ventricular ejection fraction (LVEF) at each time point. Cumulative number of events: total number of deceased patients at each timepoint for each risk group based on the LVEF. The P-values are calculated with the Log-Rank test. EF_PRED = LR: predicted by EF at low risk of death; EF_PRED = IR: predicted by EF at intermediate risk; EF_PRED = HR: predicted by EF at high-risk.

Figure 4

Patients with HF divided according to LVEF subclasses (A) LVEF ≥ 40% (low risk), (B) LVEF < 40% (high-risk), plotting actual survival over time (measured in years) according to estimated risk based on metabolomics (KM curves). Low-risk patients are colored in green and high-risk in purple. The P-values are calculated using the Log-Rank test. Censored events represent either the time of last recorded clinical follow-up, or time of death. Number at risk: number of patients stratified according to metabolomics. Cumulative number of events: total number of deceased patients at each time point for each metabolomic group. (A) KM analysis on metabolomic classification of patients with LVEF ≥ 40%; (B) KM analysis on metabolomic classification of patients with LVEF < 40%. PLS_PRED = S, predicted by PLS as survivor; PLS_PRED = D, predicted by PLS as deceased.

Figure 5

Overall patients with HF, plotting actual survival over time (measured in years) according to risk estimated using a combination of metabolomics and ejection fraction (KM curves). Low metabolomic risk (green) and high metabolomic risk (purple) patients are significantly clustered with a p-value of 3.64·10⁻⁷ (calculated with the Log-Rank test) and an HR of 8.09. Censored events represent either the time of last recorded clinical follow-up, or the time of death. Number at risk: number of patients stratified according to the combined score at each time point. Cumulative number of events: total number of deceased patients at each time point for each risk group based on the combined score. MET_EF = S, predicted by the combined score of metabolomics and EF as survivor; MET_EF = D, predicted by the combined score of metabolomics and EF as deceased.