Metabolic Profile for Prediction of Ischemic Stroke in Chinese Hypertensive Population

Background: Stroke burden is extremely high in Chinese hypertensive population. Novel biomarkers for cardiovascular diseases can be detected by metabolomic profiling of human fluids. We aim to find a panel of distinctive plasma metabolites for predicting incident ischemic stroke in hypertensive patients. Methods: This is a nested case-control study from a prospective cohort design. Baseline plasma samples were collected from 66 newly developed ischemic stroke cases and 66 matched controls. Untargeted metabolomics was performed by ultra-high performance liquid chromatography-tandem mass spectrometry, and data were analyzed by multi-variate and univariate statistics. Results: Plasma metabolite profiles clearly differed between hypertensive patients with incident ischemic stroke and without. A total of 12 metabolites were screened and identified as potential biomarkers. The altered metabolic pathways included retinol metabolism, sphingolipid metabolism, glycerophospholipid metabolism, lysine degradation, tyrosine metabolism, and tryptophan metabolism. For prediction of hypertensive ischemic stroke, the panel of specific metabolomics-based biomarkers provided area under the curve of 0.848 (95% confidence interval: 0.783-0.913). Conclusions: Our study identified a metabolic signature of incident ischemic stroke in hypertension. Differences in small-molecule metabolites hold translational value in prediction and provide insights into potential new mechanisms of this condition.