Large-scale human metabolomics studies: A strategy for data (pre-) processing and validation

被引:781
作者
Bijlsma, S
Bobeldijk, L
Verheij, ER
Ramaker, R
Kochhar, S
Macdonald, IA
van Ommen, B
Smilde, AK
机构
[1] TNO, Business Unit Analyt Sci, NL-3700 AJ Zeist, Netherlands
[2] TNO, Business Unit Physiol Sci, NL-3700 AJ Zeist, Netherlands
[3] Nestle Res Ctr, BioAnalyt Sci Dept, CH-1000 Lausanne 26, Switzerland
[4] Univ Nottingham, Sch Med, Queens Med Ctr, Sch Biomed Sci, Nottingham NG7 2UH, England
关键词
D O I
10.1021/ac051495j
中图分类号
O65 [分析化学];
学科分类号
070302 [分析化学]; 081704 [应用化学];
摘要
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.
引用
收藏
页码:567 / 574
页数:8
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