High-performance liquid chromatography (LC) coupled to mass spectrometry (MS) is increasingly being used for urinary metabonomic studies. Most studies utilize reversed-phase separation techniques, which are not suited to retaining highly polar analytes. Metabonomic studies should encompass a representative "fingerprint" that contains the largest amount of information possible. In this work, we have analyzed human urine samples with LC-MS, comparing traditional reversed-phase separation with hydrophilic interaction chromatography (HILIC), using both positive and negative electrospray ionization modes. The resulting data were analyzed using principal components analysis and partial least-squares-discriminant analysis. Discriminant models were developed for the response variables gender, diurnal variation, and age and were evaluated using external test sets to classify their predictive ability. The developed models using both positive and negative ionization mode data for reversed-phase and HILIC separations were very comparable, indicating that HILIC is a suitable method for increasing the fingerprint coverage for LC-MS metabonomic studies.