[Metabolome and mass spectrometry: new biomedical analysis perspectives]

Ann Biol Clin (Paris). 2015 Jan-Feb;73(1):126-30. doi: 10.1684/abc.2014.1020.
[Article in French]

Abstract

Metabolomics is defined as an integrative approach consisting in the comprehensive analysis of all of the small molecules of a biological system (the "metabolome"). The main objective of metabolomics in medecine is to discover metabolic biomarkers for diseases. Mass spectrometry (MS) coupled to liquid or gas chromatography is amongst major analytical tools used in metabolomics. However, the holistic approach used in metabolomics requires very good performances of the analytical system (chromatographic column and MS equipment) and the use of non-conventional validation strategies. Metabolomics workflow can be divided in three main steps: sample preparation, MS data acquisition and processing, and statistical analysis. Processing of the "raw" data (obtained after MS acquisition) is mostly required to normalise chromatographic conditions and to carry out accurate quantification of MS features. Features resulting from this processing may be identified later. The statistical analyses include typically multivariate techniques such as supervised and non-supervised methods. Supervised methods make use of the response variable (e.g., case/control) for model construction while non-supervised methods do not use this piece of information. When the study is focused on a particular set of metabolites, targeted metabolomics could be an interesting alternative to the holistic approach since it may allow absolute quantitation and be associated with a reduced cost.

Keywords: mass spectrometry; metabolome; metabolomics; statistical methods.

Publication types

  • English Abstract
  • Review

MeSH terms

  • Biomedical Technology / methods
  • Biomedical Technology / trends*
  • Humans
  • Mass Spectrometry / methods*
  • Metabolome*
  • Metabolomics / methods*
  • Metabolomics / trends
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Validation Studies as Topic