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High-throughput quantification of circulating metabolites improves prediction of subclinical atherosclerosis
Citation
Wurtz, P and Raiko, JR and Magnussen, CG and Soininen, P and Kangas, AJ and Tynkkynen, T and Thomson, R and Laatikainen, R and Savolainen, MJ and Laurikka, J and Kuukasjarvi, P and Tarkka, M and Karhunen, PJ and Jula, A and Viikari, JS and Kahonen, M and Lehtimaki, T and Juonala, M and Ala-Korpela, M and Raitakari, OT, High-throughput quantification of circulating metabolites improves prediction of subclinical atherosclerosis, European Heart Journal, 33, (18) pp. 2307-2316. ISSN 1522-9645 (2012) [Refereed Article]
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Copyright Statement
Copyright 2012 Oxford University Press
DOI: doi:10.1093/eurheartj/ehs020
Abstract
Aims High-throughput metabolite quantification holds promise for cardiovascular risk assessment. Here, we evaluated whether metabolite quantification by nuclear magnetic resonance (NMR) improves prediction of subclinical atherosclerosis in comparison to conventional lipid testing.
Methods and results Circulating lipids, lipoprotein subclasses, and small molecules were assayed by NMR for 1595 individuals aged 24–39 years from the population-based Cardiovascular Risk in Young Finns Study. Carotid intima–media thickness (IMT), a marker of subclinical atherosclerosis, was measured in 2001 and 2007. Baseline conventional risk factors and systemic metabolites were used to predict 6-year incidence of high IMT (≥90th percentile) or plaque. The best prediction of high intima–media thickness was achieved when total and HDL cholesterol were replaced by NMR-determined LDL cholesterol and medium HDL, docosahexaenoic acid, and tyrosine in prediction models with risk factors from the Framingham risk score. The extended prediction model improved risk stratification beyond established risk factors alone; area under the receiver operating characteristic curve 0.764 vs. 0.737, P = 0.02, and net reclassification index 17.6%, P = 0.0008. Higher docosahexaenoic acid levels were associated with decreased risk for incident high IMT (odds ratio: 0.74; 95% confidence interval: 0.67–0.98; P = 0.007). Tyrosine (1.33; 1.10–1.60; P = 0.003) and glutamine (1.38; 1.13–1.68; P = 0.001) levels were associated with 6-year incident high IMT independent of lipid measures. Furthermore, these amino acids were cross-sectionally associated with carotid IMT and the presence of angiographically ascertained coronary artery disease in independent populations.
Conclusion High-throughput metabolite quantification, with new systemic biomarkers, improved risk stratification for subclinical atherosclerosis in comparison to conventional lipids and could potentially be useful for early cardiovascular risk assessment.Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | intima–media thickness, risk factors, lipoproteins, tyrosine, metabolomics |
| Research Division: | Medical and Health Sciences |
| Research Group: | Public Health and Health Services |
| Research Field: | Epidemiology |
| Objective Division: | Health |
| Objective Group: | Clinical Health (Organs, Diseases and Abnormal Conditions) |
| Objective Field: | Cardiovascular System and Diseases |
| UTAS Author: | Magnussen, CG (Dr Costan Magnussen) |
| UTAS Author: | Thomson, R (Dr Russell Thomson) |
| ID Code: | 77512 |
| Year Published: | 2012 |
| Web of Science® Times Cited: | 59 |
| Deposited By: | Menzies Institute for Medical Research |
| Deposited On: | 2012-04-24 |
| Last Modified: | 2017-11-03 |
| Downloads: | 0 |
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