Global metabolomics analysis of serum from humans at risk of thrombotic stroke

Abstract

We aimed to determine the serum concentrations of altered compounds to understand the changes in metabolism and pathophysiology that occur prior to thrombotic stroke. In this prospective cohort study, high-resolution metabolomics (HRM) was employed to analyze serum samples obtained from patients at risk of stroke (n = 99) and non-risk controls (n = 301). Partial least-squares discriminant analysis (PLS-DA), along with univariate analysis using a false discovery rate (FDR) of q = 0.05 were employed to identify the discriminant metabolic profiles and to determine significantly different metabolites between healthy control and stroke risk groups. PLS-DA satisfactorily separated the stroke risk sera from control sera. Additionally, these discriminant metabolic profiles were not related to hypertension, smoking, diabetes mellitus, or insulin sensitivity. A group of 35 metabolites, most of them amino acids, that were capable of discriminating stroke risk sera from controls were identified using untargeted metabolomics. Further, the targeted metabolomics approach confirmed that the quantified concentrations of L-tryptophan, 3-methoxytyramine, methionine, homocysteinesulfinic acid, cysteine, isoleucine, carnitine, arginine, linoleic acid, and sphingosine were specifically elevated in the sera of patients who were later diagnosed with stroke. Our untargeted and targeted metabolomics approaches support investigating these compounds as novel biomarkers for early and non-invasive detection of thrombotic stroke.