Chapter 17: Metabolomics as a tool for precision medicine
by Edoardo Saccenti, Leonardi Tenori
Abstract
Metabolomics is one of the many tools of systems biology and has the penitential of becoming a fundamental tools of systems medicine since metabolites are the endpoint output of the genome and the profiles of variation of their concentrations and the patterns of metabolite-metabolite relationships offer a dynamic and actual information of the status of a system. In this chapter we introduce the reader to the individual metabolic phenotypes as described by metabolomics profiling using high throughput techniques like Nuclear Magnetic Resonance and illustrate some successful application to health and disease.
Edoardo Saccenti
Edoardo Saccenti received a MSc degree in Physics and a PhD degree in Structural Biology from the University of Florence, Italy. His main research is multivariate statistics in particular: Principal components analysis and related methods with a focus on the problem of dimensionality assessment and its relationships with inferential statistics in the frame of Random Matrix Theory; power analysis and sample size determination in the context of PCA, PLS-DA and network inference; sparse component methodologies for data exploration and interpretation.
Leonardi Tenori
Leonardo Tenori received a MSc degree in Chemistry and a PhD degree in Structural Biology from the University of Florence, Italy. After the PhD, his primary interest turned to the applications of metabolomics via magnetic resonance spectroscopy (NMR) for the study of complex biological mixtures, both in the biomedicine field (analysis of human biofluids), and in the agri-food area (analysis of food matrices such as oil, wine, milk, coffee). He performs his research in the framework of the CERM/CIRMMP infrastructure, one of the largest and best equipped NMR facilities in word. Dr. Tenori's research interest is focused on the use of NMR spectroscopy to identify metabolites that vary in response to physio-pathological states. In the medical field, this mainly translates into identifying biomarkers (or marker panels, or metabolic fingerprints) that can be used for diagnosis, prognosis, patient stratification, or to investigate the molecular mechanisms underlying the onset of diseases.