P5361Novel biomarkers predict congestive heart failure in 10,106 finnish men

Abstract

Background: Predicting heart failure (HF) remains an important challenge in health care. Purpose: We applied metabolomics to identify biomarkers predicting HF in the large prospective population-based METSIM study. Methods: Serum metabolites and lipoprotein lipids were determined by a highthroughput serum nuclear magnetic resonance (NMR) platform in 10,106 men of the METSIM study who did not have HF at baseline. Incident HF cases during the 6.9-year follow-up were identified from the medical records of the university hospital, which is the only hospital and cardiology outpatient clinic in the living area of the study subjects. Cox regression analysis was applied to identify biomarkers predicting incident HF. Principal components analysis was used to analyse the clustering of baseline variables. Results: Of the 10,106 men (age 57.6±7.1 years, body mass index 27.3±4.1 kg/m2), a total of 172 (1.7%) developed incident HF during the mean follow-up of 6.9 years. Of those who had incident heart failure, a total of 36 (20.9%) had suffered a myocardial infarction prior to the baseline study, and 65 (37.8%) had reimbursement for hypertension. Subjects with incident HF had higher baseline concentrations of plasma adiponectin, IL-1 receptor antagonist, glycoprotein acetyls, glycerol and pyruvate compared to those without incident HF. In Cox regression analysis, adiponectin (9.08±6.09 μg/ml vs 7.81±4.32 μg/ml, HR 1.19 (1.10-1.26), P=1.7E-06) and pyruvate (0.081±0.027 mmol/l vs 0.067±0.023 mmol/l, HR 1.38 (1.28-1.50), P=9.4E-08) predicted HF. There was a J-shaped distribution of incident cases of HF across the quintiles of adiponectin. In principal components analysis, we identified a novel cluster of biomarkers, consisting of alanine, glycoprotein acetyls, pyruvate, glycerol and phenylalanine, which predicted HF independently of other clusters of baseline variables (OR 1.39 (1.20-1.60), P=9.0E-06). Conclusions: Plasma adiponectin and pyruvate predicted HF during the 6.9-year follow-up of the METSIM study. In addition, we identified a novel cluster of biomarkers independently predicting heart failure. New biomarkers might help to identify subjects at high risk of heart failure.