Circulating Metabolites Are Biomarker Candidates for Stroke Risk Prediction: Results From the BiomarCaRE Project

BACKGROUND: Stratification of stroke risk remains challenging, but metabolomic profiling offers the potential to detect new biomarkers and to improve early risk assessment of incident stroke. The objective of this study was to evaluate the association between circulating metabolites and the incidence of stroke in a case-cohort study conducted across several large population-based European cohorts. METHODS: Following the case-cohort design, a subset of 10 299 individuals, including all individuals with incident stroke, was selected from the original cohort of >70 000 individuals. The case-cohort design used a random subsample of the selected population cohorts, supplemented with cases not sampled in this random subcohort. A total of 141 circulating metabolites were measured from serum samples of the selected individuals, and associations of these metabolites with risk of incident stroke were estimated and compared with those of classic risk factors (sex, age at examination, systolic blood pressure, total cholesterol, body mass index, diabetes, daily smoking status, and antihypertensive treatment). Associations with time to stroke were assessed using weighted Cox proportional hazards models adjusted for the classic risk factors. Hazard ratios (HRs) for the log-transformed metabolites were reported per 1 SD increase. RESULTS: Of the 70 195 individuals in the original cohort, 1516 (2.2%) experienced incident strokes during a median follow-up time of 8.9 years (interquartile range, 4.4-14.7). Median age was 56.8 years (interquartile range, 49.5-62.4), and 39.5% were female. Six of the 141 metabolites (2 diacyl-phosphatidylcholines, 2 lyso-phosphatidylcholines, 1 hydroxysphingomyelin, and glutamic acid) remained significantly associated with incident stroke after correction for multiple comparisons (adjusted HRs [95% CIs] per SD: lyso-phosphatidylcholines a C18:2 HR, 0.88 [95% CI, 0.82-0.93], lyso-phosphatidylcholines a C17:0 HR, 0.88 [95% CI, 0.83-0.94], hydroxysphingomyelin C14:1 HR, 0.90 [95% CI, 0.85-0.94], diacyl-phosphatidylcholines C34:1 HR, 1.10 [95% CI 1.05-1.16], diacyl-phosphatidylcholines C32:1 HR, 1.14 [95% CI, 1.08-1.21], glutamic acid HR, 1.23 [95% CI 1.11-1.37]). The strengths of these associations were similar to those for classic cardiovascular risk factors (C statistics for 10-year prediction ranging from 0.782 to 0.785 for metabolites compared with 0.781 to 0.792 for classic cardiovascular risk factors). CONCLUSIONS: Among 10 299 individuals from the general European population, we identified 6 metabolites from 4 different metabolite classes that were associated with future risk of stroke. The application of specific circulating metabolites may improve early stroke risk prediction before the onset of potentially irreversible cerebrovascular pathological processes.