Serum and urine samples from patients with type 2 diabetes mellitus and control samples were analyzed by UPLC-TOF-MS; fast and slow separation gradients were compared using both positive and negative ionization modes. The resulting data were analyzed using partial least squares discriminant analysis (PLS-DA), and models were developed to differentiate between patient and control samples. The models were evaluated using external test sets to classify their predictive ability. Under both fast and slow gradient conditions, the PLS-DA models generated using serum samples were more robust than those generated using urine samples, and the positive ionization mode produced better differentiation and higher classification rates than negative ionization mode. In addition, fast gradient conditions were found to have a comparable ability for differentiation to slow gradient conditions.

Ultra performance liquid chromatography (UPLC) coupled with orthogonal acceleration time-of-flight (oaTOF) mass spectrometry has showed great potential in diabetes research. In this paper, a UPLC–oaTOF-MS system was employed to distinguish the global serum profiles of 8 diabetic nephropathy (DN) patients, 33 type 2 diabetes mellitus (T2DM) patients and 25 healthy volunteers, and tried to find potential biomarkers. The UPLC system produced information-rich chromatograms with typical measured peak widths of 4 s, generating peak capacities of 225 in 15 min. Furthermore, principal component analysis (PCA) was used for group differentiation and marker selection. As shown in the scores plot, the distinct clustering between the patients and controls was observed, and DN and T2DM patients were also separated into two individual groups. Several compounds were tentatively identified based on accurate mass, isotopic pattern and MS/MS information. In addition, significant changes in the serum level of leucine, dihydrosphingosine and phytoshpingosine were noted, indicating the perturbations of amino acid metabolism and phospholipid metabolism in diabetic diseases, which having implications in clinical diagnosis and treatment.