The metabolites urobilin and sphingomyelin (30:1) are associated with incident heart failure in the general population

Abstract

Aims: We aimed to investigate whether metabolomic profiling of blood can lead to novel insights into heart failure pathogenesis or improved risk prediction.

Methods and results: Mass spectrometry-based metabolomic profiling was performed in plasma or serum samples from three community-based cohorts without heart failure at baseline (total n = 3924; 341 incident heart failure events; median follow-up ranging from 4.6 to 13.9 years). Cox proportional hazard models were applied to assess the association of each of the 206 identified metabolites with incident heart failure in the discovery cohorts Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) (n = 920) and Uppsala Longitudinal Study of Adult Men (ULSAM) (n = 1121). Replication was undertaken in the independent cohort TwinGene (n = 1797). We also assessed whether metabolites could improve the prediction of heart failure beyond established risk factors (age, sex, body mass index, low-density and high-density lipoprotein cholesterol, triglycerides, lipid medication, diabetes, systolic and diastolic blood pressure, blood pressure medication, glomerular filtration rate, smoking status, and myocardial infarction prior to or during follow-up). Higher circulating urobilin and lower sphingomyelin (30:1) were associated with incident heart failure in age-adjusted and sex-adjusted models in the discovery and replication sample. The hazard ratio for urobilin in the replication cohort was estimated to 1.29 per standard deviation unit, 95% confidence interval (CI 1.03-1.63), and for sphingomyelin (30:1) to 0.72 (95% CI 0.58-0.89). Results remained similar after further adjustment for established heart failure risk factors in meta-analyses of all three cohorts. Urobilin concentrations were inversely associated with left ventricular ejection fraction at baseline in the PIVUS cohort (β = -0.70, 95% CI -1.03 to -0.38). No major improvement in risk prediction was observed when adding the top 2 metabolites (C-index 0.787, 95% CI 0.752-0.823) or nine Lasso-selected metabolites (0.790, 95% CI 0.754-0.826) to a modified Atherosclerosis Risk in Communities heart failure risk score model (0.780, 95% CI 0.745-0.816).

Conclusions: Our metabolomic profiling of three community-based cohorts study identified associations of circulating levels of the haem breakdown product urobilin, and sphingomyelin (30:1), a cell membrane component involved in signal transduction and apoptosis, with incident heart failure.

Keywords: Biomarkers; Epidemiology; Heart failure; Metabolomics; Risk prediction.