LAUSR

The relevance between circulating metabolites and vascular events remains controversial and comprehensive studies are lacking. We sought to investigate the prospective associations of plasma metabolomics with risks of incident stroke, ischemic stroke (IS), hemorrhagic stroke (HS), and myocardial infarction (MI). Within the UK Biobank cohort, 249 circulating metabolites were measured in 90 438 participants without baseline vascular diseases. Cox proportional hazards regressions were applied to estimate adjusted hazard ratios (HRs) for per 1 standard deviation increment in metabolites. The least absolute shrinkage and selection operator algorithm was used for selecting metabolite subsets. During a median of 9.0 years of follow‐up, we documented 833 incident stroke and 1256 MI cases. Lipid constituents, comprising cholesterol, cholesteryl esters, free cholesterol, phospholipids, and total lipids, in very low‐ (VLDL), intermediate‐ (IDL), and low‐density lipoprotein (LDL) particles were positively associated with MI risk (HR = 1.12 to 1.36; 95% CI = 1.06 to 1.44), while in high‐density lipoprotein (HDL) particles showed inverse associations (HR = 0.68 to 0.81; 95% CI = 0.63 to 0.87). Similar association pattern with MI was also observed for VLDL, IDL, LDL, and HDL particles themselves. In contrast, triglycerides within all lipoproteins, including most HDL particles, were positively associated with MI risk (HR = 1.14 to 1.28; 95% CI = 1.08 to 1.35) and, to a slightly lesser extent, with stroke and IS. Unsaturation of fatty acids and albumin were inversely associated with risks of stroke, IS, and MI. In contrast, the linear association for HS is absent. When combining multiple metabolites, the metabolite risk score captured a drastically elevated risk of all vascular events, about twice that of any single metabolite. Taken together, circulating metabolites showed remarkably widespread associations with incident MI, but substantially weakened associations with risks of stroke and its subtypes. Exhaustive metabolomics profiling may shed light on vascular risk prediction and, in turn, guide pertinent strategies of intervention and treatment.