Normalization to Specific Gravity Prior to Analysis Improves Information Recovery from High Resolution Mass Spectrometry Metabolomic Profiles of Human Urine

• Published in: Analytical chemistry (Washington) Vol. 86; no. 21; pp. 10925 - 10931
• Main Authors: Edmands, William M. B, Ferrari, Pietro, Scalbert, Augustin
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 04.11.2014
• Subjects: Analytical chemistry; biomarkers; Chromatography; Cohort Studies; data collection; Density; Diet; diet recall; Discriminant analysis; food intake; foods; Gravity; Humans; Lead; least squares; liquid chromatography; Mass spectrometry; Mass Spectrometry - methods; Metabolites; Metabolomics; Nutrition; prospective studies; Recall; Refractometry; Reproducibility of Results; selection criteria; Specific Gravity; Urine
• ISSN: 0003-2700; 1520-6882; 1520-6882
• DOI: 10.1021/ac503190m

Extraction of meaningful biological information from urinary metabolomic profiles obtained by liquid-chromatography coupled to mass spectrometry (MS) necessitates the control of unwanted sources of variability associated with large differences in urine sample concentrations. Different methods of normalization either before analysis (preacquisition normalization) through dilution of urine samples to the lowest specific gravity measured by refractometry, or after analysis (postacquisition normalization) to urine volume, specific gravity and median fold change are compared for their capacity to recover lead metabolites for a potential future use as dietary biomarkers. Twenty-four urine samples of 19 subjects from the European Prospective Investigation into Cancer and nutrition (EPIC) cohort were selected based on their high and low/nonconsumption of six polyphenol-rich foods as assessed with a 24 h dietary recall. MS features selected on the basis of minimum discriminant selection criteria were related to each dietary item by means of orthogonal partial least-squares discriminant analysis models. Normalization methods ranked in the following decreasing order when comparing the number of total discriminant MS features recovered to that obtained in the absence of normalization: preacquisition normalization to specific gravity (4.2-fold), postacquisition normalization to specific gravity (2.3-fold), postacquisition median fold change normalization (1.8-fold increase), postacquisition normalization to urinary volume (0.79-fold). A preventative preacquisition normalization based on urine specific gravity was found to be superior to all curative postacquisition normalization methods tested for discovery of MS features discriminant of dietary intake in these urinary metabolomic datasets.