Metabonomics as a clinical tool of analysis: LC-MS approaches

Metabolic differences between test and control groups (i.e. metabonomics) are
routinely accomplished by using multivariate analysis for data obtained commonly from NMR, GC-MS and LC-MS. Multivariate analysis (e.g. principal component analysis PCA) is commonly used to extract potential metabolites responsible for clinical observations. Metabonomics applied to the clinical field is challenging because the physiological variabilities like gender, age, race…etc might govern the cluster pattern obtained by multivariate analysis instead of the tested differences. This review focuses on the challenges facing the clinical applications of metabonomics and introduces their possible solutions as mentioned in the literature.