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Cross-platform analysis of longitudinal data in metabolomics

Type: Application

Scientific Paper

Metabolomics Studies
Number: Technology

10.1039/C1MB05280B

Year Products

2011

  Author
 

Ekaterina Nevedomskaya , Oleg A. Mayboroda and André M. Deelder

  Reference
 

Journal Cover:Mol. BioSyst., 2011, 7, 3214-3222 Molecular BioSystems Issue 12, 2011
 

Abstract
 

Metabolic profiling is considered to be a very promising tool for diagnostic purposes, for assessing nutritional status and response to drugs. However, it is also evident that human metabolic profiles have a complex nature, influenced by many external factors. This, together with the understanding of the difficulty to assign people to distinct groups and a general move in clinical science towards personalized medicine, raises the interest to explore individual and variable metabolic features for each individual separately in longitudinal study design. In the current paper we have analyzed a set of metabolic profiles of a selection of six urine samples per person from a set of healthy individuals by 1H NMR and reversed-phase UPLC-MS. We have demonstrated that the method for recovery of individual metabolic phenotypes can give complementary information to another established method for analysis of longitudinal data—multilevel component analysis. We also show that individual metabolic signatures can be found not only in 1H NMR data, as has been demonstrated before, but also even more strongly in LC-MS data.

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