Use of a pre-analysis osmolality normalisation method to correct for variable. urine concentrations and for improved metabolomic analyses

Abstract

Metabolomics analyses of urine have the potential to provide new information on the detection and progression of many disease processes. However, urine samples can vary significantly in total solute concentration and this presents a challenge to achieve high quality metabolomic datasets and the detection of biomarkers of disease or environmental exposures. This study investigated the efficacy of pre- and post-analysis normalisation methods to analyse metabolomic datasets obtained from neat and diluted urine samples from five individuals. Urine samples were extracted by solid phase extraction (SPE) prior to metabolomic analyses using a sensitive nanoflow/nanospray LC-MS technique and the data..