| Title |
Human metabolic profiles are stably controlled by genetic and environmental variation
|
|---|---|
| Published in |
Molecular Systems Biology, August 2011
|
| DOI | 10.1038/msb.2011.57 |
| Pubmed ID | |
| Authors |
George Nicholson, Mattias Rantalainen, Anthony D Maher, Jia V Li, Daniel Malmodin, Kourosh R Ahmadi, Johan H Faber, Ingileif B Hallgrímsdóttir, Amy Barrett, Henrik Toft, Maria Krestyaninova, Juris Viksna, Sudeshna Guha Neogi, Marc‐Emmanuel Dumas, Ugis Sarkans, Bernard W Silverman, Peter Donnelly, Jeremy K Nicholson, Maxine Allen, Krina T Zondervan, John C Lindon, Tim D Spector, Mark I McCarthy, Elaine Holmes, Dorrit Baunsgaard, Chris C Holmes |
| Abstract |
¹H Nuclear Magnetic Resonance spectroscopy (¹H NMR) is increasingly used to measure metabolite concentrations in sets of biological samples for top-down systems biology and molecular epidemiology. For such purposes, knowledge of the sources of human variation in metabolite concentrations is valuable, but currently sparse. We conducted and analysed a study to create such a resource. In our unique design, identical and non-identical twin pairs donated plasma and urine samples longitudinally. We acquired ¹H NMR spectra on the samples, and statistically decomposed variation in metabolite concentration into familial (genetic and common-environmental), individual-environmental, and longitudinally unstable components. We estimate that stable variation, comprising familial and individual-environmental factors, accounts on average for 60% (plasma) and 47% (urine) of biological variation in ¹H NMR-detectable metabolite concentrations. Clinically predictive metabolic variation is likely nested within this stable component, so our results have implications for the effective design of biomarker-discovery studies. We provide a power-calculation method which reveals that sample sizes of a few thousand should offer sufficient statistical precision to detect ¹H NMR-based biomarkers quantifying predisposition to disease. |
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|---|---|---|
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Demographic breakdown
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Mendeley demographics
Geographical breakdown
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|---|---|---|
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Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 58 | 26% |
| Researcher | 54 | 24% |
| Student > Master | 14 | 6% |
| Professor > Associate Professor | 14 | 6% |
| Professor | 13 | 6% |
| Other | 39 | 17% |
| Unknown | 33 | 15% |
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|---|---|---|
| Agricultural and Biological Sciences | 77 | 34% |
| Biochemistry, Genetics and Molecular Biology | 29 | 13% |
| Medicine and Dentistry | 28 | 12% |
| Chemistry | 23 | 10% |
| Mathematics | 6 | 3% |
| Other | 21 | 9% |
| Unknown | 41 | 18% |