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 nontargeted 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 s (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.

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

“…Some authors used MSTUS and osmolality to normalize signal intensities after data acquisition. 16 Both methods showed an improved discrimination of urine samples when compared to normalization over urine volume. 12 In the present work, we also found that urine MSTUS was poorly correlated to urine volume (r = 0.55) but strongly correlated with specific gravity (r = 0.96) easily measured at limited cost with a refractometer.…”

Preconcentration based on paramagnetic microparticles for the separation of sarcosine using hydrophilic interaction liquid chromatography coupled with coulometric detection

“…Prior to instrumental analysis, there is often a requirement for the isolation and preconcentration of the analyte. Urine is one of the most accessible body fluids for metabolomics applications , nevertheless, urine volume and composition vary widely . Urine still acts as biological matrix containing interferents able to reduce the effectiveness of analytical assays, thus a preconcentration of sarcosine may play crucial role in the analysis of real sample.…”

The great importance of normalization of LC–MS data for highly‐accurate non‐targeted metabolomics

“…Normalization of the total useful MS signal is one of the better methods for the non‐targeted metabolomic and proteomic analysis of the biological fluid samples (Chen et al, ; Mattarucchi & Guillou, ; Peralbo‐Molina, Calderon‐Santiago, Priego‐Capote, Jurado‐Gamez, & Luque de Castro, ; Warrack et al, ). For normalization, this method uses the total useful signal meaning the total peak intensity of the commonly detected peaks in all the samples, thus avoiding xenobiotic and artifact peaks, which are not in the biological samples (Warrack et al, ).…”