Differential network analysis reveals metabolic determinants associated with mortality in acute myocardial infarction patients and suggest potential mechanisms underlying different clinical scores used to predict death.

Acute myocardial infarction (AMI) is a leading worldwide cause of death. Risk stratification and management of AMI patients continue to be challenging despite considerable efforts made in the last decades. We present here differential analysis of metabolite-metabolite association networks constructed from an array of 24 serum metabolites identified and quantified via nuclear magnetic resonance spectroscopy in a cohort of 825 AMI patients of which 123 died within two years from the AMI event. We investigated differences in metabolite connectivity of patient who survived, at two years, the AMI event and we characterized metabolite-metabolite association networks specific for high and low risk of death according to four different risk parameters, namely Acute Coronary Syndrome classification, Killip, Global Registry of Acute Coronary Events risk score, and metabolomic NOESY RF risk score. We show significant differences in the connectivity patterns of several low molecular weight molecules implying variations in the regulation of several metabolic pathways, regarding branched chain amino acids, alanine, creatinine, mannose, ketone bodies and energetic metabolism. Our results demonstrate that the characterization of metabolite-metabolite association networks is a promising and powerful tool to investigate AMI patients according to their outcomes at a molecular level.