Large-Scale Human Metabolomics Studies: A Strategy for Data (Pre-) Processing and Validation

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• 作者：Sabina Bijlsma ; Ivana Bobeldijk ; Elwin R. Verheij ; Raymond Ramaker ; Sunil Kochhar ; Ian A. Macdonald ; Ben van Ommen ; and Age K. Smilde
• 刊名：Analytical Chemistry
• 出版年：2006
• 出版时间：January 15, 2006
• 年：2006
• 卷：78
• 期：2
• 页码：567 - 574
• 全文大小：145K
• 年卷期：v.78,no.2(January 15, 2006)
• ISSN：1520-6882

文摘

A large metabolomics study was performed on 600plasma samples taken at four time points before and aftera single intake of a high fat test meal by obese and leansubjects. All samples were analyzed by a liquid chromatography-mass spectrometry (LC-MS) lipidomic methodfor metabolic profiling. A pragmatic approach combiningseveral well-established statistical methods was developedfor processing this large data set in order to detect smalldifferences in metabolic profiles in combination with alarge biological variation. Such metabolomics studiesrequire a careful analytical and statistical protocol. Thestrategy included data preprocessing, data analysis, andvalidation of statistical models. After several data preprocessing steps, partial least-squares discriminant analysis(PLS-DA) was used for finding biomarkers. To validatethe found biomarkers statistically, the PLS-DA modelswere validated by means of a permutation test, biomarkermodels, and noninformative models. Univariate plots ofpotential biomarkers were used to obtain insight in up-or downregulation. The strategy proposed proved to beapplicable for dealing with large-scale human metabolomics studies.