title: Opening up the "Black Box": metabolic phenotyping and metabolome-wide association studies in epidemiology.
abstract: BACKGROUND
  Metabolic phenotyping of humans allows information to be captured on the interactions between dietary, xenobiotic, other lifestyle and environmental exposures, and genetic variation, which together influence the balance between health and disease risks at both individual and population levels.
  
  
  OBJECTIVE
  We describe here the main procedures in large-scale metabolic phenotyping and their application to metabolome-wide association (MWA) studies.
  
  
  METHODS
  By use of high-throughput technologies and advanced spectroscopic methods, application of metabolic profiling to large-scale epidemiologic sample collections, including metabolome-wide association (MWA) studies for biomarker discovery and identification.
  
  
  CONCLUSIONS
  Metabolic profiling at epidemiologic scale requires optimization of experimental protocol to maximize reproducibility, sensitivity, and quantitative reliability, and to reduce analytical drift. Customized multivariate statistical modeling approaches are needed for effective data visualization and biomarker discovery with control for false-positive associations since 100s or 1,000s of complex metabolic spectra are being processed.
  
  
  CONCLUSIONS
  Metabolic profiling is an exciting addition to the armamentarium of the epidemiologist for the discovery of new disease-risk biomarkers and diagnostics, and to provide novel insights into etiology, biological mechanisms, and pathways.
authors.affiliation: Biomolecular Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London, UK.
authors.forename: Magda
authors.initials: M
authors.lastname: Bictash
authors.forename: Timothy M
authors.initials: TM
authors.lastname: Ebbels
authors.forename: Queenie
authors.initials: Q
authors.lastname: Chan
authors.forename: Ruey Leng
authors.initials: RL
authors.lastname: Loo
authors.forename: Ivan K S
authors.initials: IK
authors.lastname: Yap
authors.forename: Ian J
authors.initials: IJ
authors.lastname: Brown
authors.forename: Maria
authors.initials: M
authors.lastname: de Iorio
authors.forename: Martha L
authors.initials: ML
authors.lastname: Daviglus
authors.forename: Elaine
authors.initials: E
authors.lastname: Holmes
authors.forename: Jeremiah
authors.initials: J
authors.lastname: Stamler
authors.forename: Jeremy K
authors.initials: JK
authors.lastname: Nicholson
authors.forename: Paul
authors.initials: P
authors.lastname: Elliott
mesh_terms: D015415:Biomarkers / Q000378:metabolism; D006801:Humans; D055442:Metabolome / Q000235:genetics*; D055432:Metabolomics / Q000379:methods* / Q000592:standards; D017720:Molecular Epidemiology / Q000592:standards*; D010641:Phenotype; D015203:Reproducibility of Results; D018570:Risk Assessment
chemical_list: D015415:Biomarkers