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Human metabolic profiles are stably controlled by genetic and environmental variation

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
The MolPAGE Consortium
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
Source :
Molecular Systems Biology, Vol 7, Iss 1, Pp 1-12 (2011)
Publication Year :
2011
Publisher :
Springer Nature, 2011.

Abstract

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.

Details

Language :
English
ISSN :
17444292
Volume :
7
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Molecular Systems Biology
Publication Type :
Academic Journal
Accession number :
edsdoj.f335db8f4a53437692b5541fc67ede7b
Document Type :
article
Full Text :
https://doi.org/10.1038/msb.2011.57