Metabolite Profiling and Cardiovascular Event Risk
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Published:2015-03-03
Issue:9
Volume:131
Page:774-785
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ISSN:0009-7322
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Container-title:Circulation
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language:en
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Short-container-title:Circulation
Author:
Würtz Peter1, Havulinna Aki S.1, Soininen Pasi1, Tynkkynen Tuulia1, Prieto-Merino David1, Tillin Therese1, Ghorbani Anahita1, Artati Anna1, Wang Qin1, Tiainen Mika1, Kangas Antti J.1, Kettunen Johannes1, Kaikkonen Jari1, Mikkilä Vera1, Jula Antti1, Kähönen Mika1, Lehtimäki Terho1, Lawlor Debbie A.1, Gaunt Tom R.1, Hughes Alun D.1, Sattar Naveed1, Illig Thomas1, Adamski Jerzy1, Wang Thomas J.1, Perola Markus1, Ripatti Samuli1, Vasan Ramachandran S.1, Raitakari Olli T.1, Gerszten Robert E.1, Casas Juan-Pablo1, Chaturvedi Nish1, Ala-Korpela Mika1, Salomaa Veikko1
Affiliation:
1. 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.,...
Abstract
Background—
High-throughput profiling of circulating metabolites may improve cardiovascular risk prediction over established risk factors.
Methods and Results—
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).
Conclusions—
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.
Publisher
Ovid Technologies (Wolters Kluwer Health)
Subject
Physiology (medical),Cardiology and Cardiovascular Medicine
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