Association of Circulating Metabolites With Risk of Coronary Heart Disease in a European Population: Results From the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE) Consortium

Importance: Risk stratification for coronary heart disease (CHD) remains challenging because of the complex causative mechanism of the disease. Metabolomic profiling offers the potential to detect new biomarkers and improve CHD risk assessment.

Objective: To evaluate the association between circulating metabolites and incident CHD in a large European cohort.

Design, Setting, and Participants: This population-based study used the Biomarkers for Cardiovascular Risk Assessment in Europe (BiomarCaRE) case-cohort to measure circulating metabolites using a targeted approach in serum samples from 10 741 individuals without prevalent CHD. The cohort consisted of a weighted, random subcohort of the original cohort of more than 70 000 individuals. The case-cohort design was applied to 6 European cohorts: FINRISK97 (Finland), Monitoring of Trends and Determinants in Cardiovascular Diseases/Cooperative Health Research in the Region of Augsburg (MONICA/KORA; Germany), MONICA-Brianza and Moli-Sani (Italy), DanMONICA (Denmark), and the Scottish Heart Health Extended Cohort (United Kingdom).

Main Outcomes and Measures: Associations with time to CHD onset were assessed individually by applying weighted and adjusted Cox proportional hazard models. The association of metabolites with CHD onset was examined by C indices.

Results: In 10 741 individuals (4157 women [38.7%]; median [interquartile range] age, 56.5 [49.2-62.2] years), 2166 incident CHD events (20.2%) occurred over a median (interquartile range) follow-up time of 9.2 (4.5-15.0) years. Among the 141 metabolites analyzed, 24 were significantly associated with incident CHD at a nominal P value of .05, including phosphatidylcholines (PCs), lysoPCs, amino acids, and sphingolipids. Five PCs remained significant after correction for multiple testing: acyl-alkyl-PC C40:6 (hazard ratio [HR], 1.13 [95% CI, 1.07-1.18]), diacyl-PC C40:6 (HR, 1.10 [95% CI, 1.04-1.15]), acyl-alkyl-PC C38:6 (HR, 1.11 [95% CI, 1.05-1.16]), diacyl-PC C38:6 (HR, 1.09 [95% CI, 1.04-1.14]) and diacyl-PC C38:5 (HR, 1.10 [95% CI, 1.05-1.16]). Lower levels of these metabolites were associated with increased risk of incident CHD. The strength of the associations competes with those of classic risk factors (C statistics: acyl-alkyl-PC C40:6, 0.756 [95% CI, 0.738-0.774], diacyl-PC C40:6, 0.754 [95% CI, 0.736-0.772], acyl-alkyl-PC C38:6, 0.755 [95% CI, 0.736-0.773], diacyl-PC C38:6, 0.754 [95% CI, 0.736-0.772]), diacyl-PC C38:5, 0.754 [95% CI, 0.736-0.772]). Adding metabolites to a base risk model including classic risk factors high-sensitivity C-reactive protein and high-sensitivity troponin I did not improve discrimination by C statistics.

Conclusions and Relevance: Five PCs were significantly associated with increased risk of incident CHD and showed comparable discrimination with individual classic risk factors. Although these metabolites do not improve CHD risk assessment beyond that of classic risk factors, these findings hold promise for an improved understanding of the pathophysiology of CHD.