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PLoS Genet. 2014 Dec 11;10(12):e1004801. doi: 10.1371/journal.pgen.1004801. eCollection 2014 Dec.

Large-scale metabolomic profiling identifies novel biomarkers for incident coronary heart disease.

Author information

1
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
2
Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University, Uppsala, Sweden.
3
Proteomics and Metabolomics Facility, Colorado State University, Fort Collins, Colorado, United States of America.
4
Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
5
Department of Medical Sciences, Biochemial structure and function, Uppsala University, Uppsala, Sweden.
6
Department of Medical Sciences, Coagulation and inflammation science, Uppsala University, Uppsala, Sweden.
7
Department of Biochemistry, Centre of Excellence for Translational Medicine, University of Tartu, Tartu, Estonia.
8
Proteomics and Metabolomics Facility, Colorado State University, Fort Collins, Colorado, United States of America; Department of Biochemistry and Molecular Biology, Colorado State University, Fort Collins, Colorado, United States of America.
9
Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden; School of Health and Social Studies, Dalarna University, Falun, Sweden.
10
Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom.

Abstract

Analyses of circulating metabolites in large prospective epidemiological studies could lead to improved prediction and better biological understanding of coronary heart disease (CHD). We performed a mass spectrometry-based non-targeted metabolomics study for association with incident CHD events in 1,028 individuals (131 events; 10 y. median follow-up) with validation in 1,670 individuals (282 events; 3.9 y. median follow-up). Four metabolites were replicated and independent of main cardiovascular risk factors [lysophosphatidylcholine 18∶1 (hazard ratio [HR] per standard deviation [SD] increment = 0.77, P-value<0.001), lysophosphatidylcholine 18∶2 (HR = 0.81, P-value<0.001), monoglyceride 18∶2 (MG 18∶2; HR = 1.18, P-value = 0.011) and sphingomyelin 28∶1 (HR = 0.85, P-value = 0.015)]. Together they contributed to moderate improvements in discrimination and re-classification in addition to traditional risk factors (C-statistic: 0.76 vs. 0.75; NRI: 9.2%). MG 18∶2 was associated with CHD independently of triglycerides. Lysophosphatidylcholines were negatively associated with body mass index, C-reactive protein and with less evidence of subclinical cardiovascular disease in additional 970 participants; a reverse pattern was observed for MG 18∶2. MG 18∶2 showed an enrichment (P-value = 0.002) of significant associations with CHD-associated SNPs (P-value = 1.2×10-7 for association with rs964184 in the ZNF259/APOA5 region) and a weak, but positive causal effect (odds ratio = 1.05 per SD increment in MG 18∶2, P-value = 0.05) on CHD, as suggested by Mendelian randomization analysis. In conclusion, we identified four lipid-related metabolites with evidence for clinical utility, as well as a causal role in CHD development.

PMID:
25502724
PMCID:
PMC4263376
DOI:
10.1371/journal.pgen.1004801
[Indexed for MEDLINE]
Free PMC Article
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