Large-scale human metabolomics studies: a strategy for data (pre-) processing and validation.
A large metabolomics study was performed on 600 plasma samples taken at four time points before and after a single intake of a high fat test meal by obese and lean subjects. All samples were analyzed by a liquid chromatography-mass spectrometry (LC-MS) lipidomic method for metabolic profiling. A pragmatic approach combining several well-established statistical methods was developed for processing this large data set in order to detect small differences in metabolic profiles in combination with a large biological variation. Such metabolomics studies require a careful analytical and statistical protocol. The strategy included data preprocessing, data analysis, and validation of statistical models. After several data preprocessing steps, partial least-squares discriminant analysis (PLS-DA) was used for finding biomarkers. To validate the found biomarkers statistically, the PLS-DA models were validated by means of a permutation test, biomarker models, and noninformative models. Univariate plots of potential biomarkers were used to obtain insight in up- or downregulation. The strategy proposed proved to be applicable for dealing with large-scale human metabolomics studies.
Bijlsma
Sabina
S
Business Unit Analytical Sciences and Business Unit Physiological Sciences, TNO Quality of Life, P.O. Box 360, 3700 AJ Zeist, The Netherlands. bijlsma@voeding.tno.nl
Bobeldijk
Ivana
I
Verheij
Elwin R
ER
Ramaker
Raymond
R
Kochhar
Sunil
S
Macdonald
Ian A
IA
van Ommen
Ben
B
Smilde
Age K
AK
D002853:Chromatography, Liquid; D003627:Data Interpretation, Statistical; D004041:Dietary Fats / Q000008:administration & dosage* / Q000097:blood; D005060:Europe; D006801:Humans; D016018:Least-Squares Analysis; D008055:Lipids / Q000097:blood*; D013058:Mass Spectrometry; D009765:Obesity / Q000097:blood*; D019518:Postprandial Period / Q000502:physiology
D004041:Dietary Fats; D008055:Lipids