Critical aspects of urine profiling for the selection of potential biomarkers using UPLC-TOF-MS

Abstract

Biomarker selection through the metabolomics approach involves the acquisition of non-targeted metabolic profiles. In this study, some critical factors that may affect this process were investigated using urine test samples and a UPLC-TOF system. Repeated injections of a single sample demonstrated that the percentage of undetected and poorly repeatable measurements (intensity RSD>15%) decreased from 22.5% to 5.8% and from 32.9% to 14.7%, respectively, as the scan time was increased up to 0.6 seconds (approximately 11 data points per peak). An additional critical factor was identified in the presence of broad concentration differences between the samples; the application of a dilution scheme that minimized these differences reduced the number of missing values in the final datasets by 36%. The impact of missing values was further investigated in the study of two groups of samples produced by using a spike as “artificial” marker. Missing values weakened the models used for the interpretation of the metabolic profiles, and greatly hindered the identification of possible markers. Finally, a simple strategy for an effective analysis of urine samples was outlined; it proved to limit the need for the post-acquisition elaboration of the data. The same strategy can easily be adapted to other matrices.