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Circulation. 2015 Mar 3;131(9):774-85. doi: 10.1161/CIRCULATIONAHA.114.013116. Epub 2015 Jan 8.

Metabolite profiling and cardiovascular event risk: a prospective study of 3 population-based cohorts.

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From Computational Medicine, Institute of Health Sciences, University of Oulu, Finland (P.W., P.S., T. Tynkkynen, Q.W., M.T., A.J.K., J. Kettunen, M.A.-K.); Department of Chronic Disease Prevention, National Institute for Health and Welfare, Finland (P.W., A.S.H., J. Kettunen, A.J., M.P., V.S.); Institute for Molecular Medicine Finland, University of Helsinki (P.W., A.S.H., M.P., S.P.); NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio (P.S., T. Tynkkynen, Q.W., M.T., M.A.-K.); Faculty of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, United Kingdom (D.P.-M., J.-P.C.); Institute of Cardiovascular Science, University College London, United Kingdom (T. Tillin, A.D.H., J.-P.C., N.C.); Framingham Heart Study of the National Heart, Lung, and Blood Institute and Boston University School of Medicine, Framingham, MA (A.G., R.S.V.); Genome Analysis Center, Institute of Experimental Genetics, Helmholtz Zentrum München, Neuherberg, Germany (A.A., J.A.); Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Finland (J. Kaikkonen, V.M., O.T.R.); Department of Food and Environmental Sciences, University of Helsinki, Finland (V.M.,); Department of Clinical Physiology, University of Tampere and Tampere University Hospital, Finland (M.K.); Department of Clinical Chemistry, Fimlab Laboratories, and School of Medicine, University of Tampere, Finland (T.L.); Medical Research Council Integrative Epidemiology Unit at the University of Bristol, United Kingdom (D.A.L., T.R.G., M.A.-K.); School of Social and Community Medicine, University of Bristol, United Kingdom (D.A.L., T.R.G., M.A.-K.); Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom (N.S.); Hannover Medical School, Hannover Unified Biobank, Germany (T.I.); Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany



High-throughput profiling of circulating metabolites may improve cardiovascular risk prediction over established risk factors.


We applied quantitative nuclear magnetic resonance metabolomics to identify the biomarkers for incident cardiovascular disease during long-term follow-up. Biomarker discovery was conducted in the National Finnish FINRISK study (n=7256; 800 events). Replication and incremental risk prediction was assessed in the Southall and Brent Revisited (SABRE) study (n=2622; 573 events) and British Women's Health and Heart Study (n=3563; 368 events). In targeted analyses of 68 lipids and metabolites, 33 measures were associated with incident cardiovascular events at P<0.0007 after adjusting for age, sex, blood pressure, smoking, diabetes mellitus, and medication. When further adjusting for routine lipids, 4 metabolites were associated with future cardiovascular events in meta-analyses: higher serum phenylalanine (hazard ratio per standard deviation, 1.18; 95% confidence interval, 1.12-1.24; P=4×10(-10)) and monounsaturated fatty acid levels (1.17; 1.11-1.24; P=1×10(-8)) were associated with increased cardiovascular risk, while higher omega-6 fatty acids (0.89; 0.84-0.94; P=6×10(-5)) and docosahexaenoic acid levels (0.90; 0.86-0.95; P=5×10(-5)) were associated with lower risk. A risk score incorporating these 4 biomarkers was derived in FINRISK. Risk prediction estimates were more accurate in the 2 validation cohorts (relative integrated discrimination improvement, 8.8% and 4.3%), albeit discrimination was not enhanced. Risk classification was particularly improved for persons in the 5% to 10% risk range (net reclassification, 27.1% and 15.5%). Biomarker associations were further corroborated with mass spectrometry in FINRISK (n=671) and the Framingham Offspring Study (n=2289).


Metabolite profiling in large prospective cohorts identified phenylalanine, monounsaturated fatty acids, and polyunsaturated fatty acids as biomarkers for cardiovascular risk. This study substantiates the value of high-throughput metabolomics for biomarker discovery and improved risk assessment.


amino acids; biological markers; fatty acids; metabolomics; risk factors

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