期刊
ANALYST
卷 134, 期 9, 页码 1781-1785出版社
ROYAL SOC CHEMISTRY
DOI: 10.1039/b910205a
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资金
- Academy of Finland Research Funding
- Academy of Finland SALVE
- Emil Aaltonen Foundation
- Finnish Cardiovascular Research Foundation
- Finnish Cultural Foundation
- Finnish Foundation for Alcohol Studies
- Sigrid Juselius Foundation
- Social Insurance Institution of Finland
- Tampere University Hospital Medical Fund
A high-throughput proton (H-1) nuclear magnetic resonance (NMR) metabonomics approach is introduced to characterise systemic metabolic phenotypes. The methodology combines two molecular windows that contain the majority of the metabolic information available by H-1 NMR from native serum, e. g. serum lipids, lipoprotein subclasses as well as various low-molecular-weight metabolites. The experimentation is robotics-controlled and fully automated with a capacity of about 150-180 samples in 24 h. To the best of our knowledge, the presented set-up is unique in the sense of experimental high-throughput, cost-effectiveness, and automated multi-metabolic data analyses. As an example, we demonstrate that the NMR data as such reveal associations between systemic metabolic phenotypes and the metabolic syndrome (n = 4407). The high-throughput of up to 50 000 serum samples per year is also paving the way for this technology in large-scale clinical and epidemiological studies. In contradiction to single 'biomarkers', the application of this holistic NMR approach and the integrated computational methods provides a data-driven systems biology approach to biomedical research.
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