Orthogonal Partial Least Squares - Discriminant Analysis in Metabolomic for Disease Characterization

Abstract

This study utilises univariate and multivariate statistical techniques to determine the differences in a targeted set of metabolites for healthy controls and two groups of diseased persons. Urine samples are collected from healthy controls and patients suffering from Chronic Kidney Disease. LC-MS/MS analysis is performed on each sample, and chromatographic and mass spectrometric data are obtained. After pre-processing the data through normalization and scaling, Principal Components Analysis and Orthogonal Partial Least Squares-Discriminant Analysis are used to visualise the differences in these two classes. Further statistical analysis is also employed to determine fluctuations in target metabolites to understand disease pathology, and also identify potential biomarker candidates for CKD. This same method was also employed for a separate cohort of patients suffering from an ocular disease in order to show the applicability of this method.