Metabolomics reveals new metabolic perturbations in children with type 1 diabetes.

OBJECTIVE: Using an untargeted metabolomics approach we investigated the metabolome of children with type 1 diabetes (T1D) in comparison with healthy peers and explored the contribution of HbA1c and clinical features to the observed difference. RESEARCH DESIGN AND METHODS: We enrolled children with T1D aged 6-15 years, attending the pediatric diabetes clinic of University of Padova (Italy). Healthy controls were enrolled on voluntary basis and matched for age, sex, pubertal status, body mass index (BMI). We performed a liquid chromatography and mass spectrometry analysis (LC-MS) on fasting urinary samples of the 2 groups. RESULTS: A total of 56 patients with T1D aged (11.4 ± 2.2) years, and 30 healthy controls (10.7 ± 2.8) years were enrolled. We identified 59 urinary metabolites having a higher level in children with T1D, mainly represented by gluco- and mineralcorticoids, phenylalanine and tryptophan catabolites (kynurenine), small peptides, glycerophospholipids, fatty acids, and gut bacterial products. We did not find any association between HbA1c, pubertal status, disease duration, and metabolome profile within the case group. CONCLUSIONS: T1D profoundly disrupts the metabolome of pediatric patients. The excess of cortisol and aldosterone may contribute to the development of macrovascular complications in adulthood, while the increase of tryptophan derivates may have a role in neuronal damage associated to hyperglycemia. Determinants of such findings, other than HbA1c, should be explored.

Simultaneous quantitative determination of N(G),N(G)-dimethyl-L-arginine or asymmetric dimethylarginine and related pathway's metabolites in biological fluids by ultrahigh-performance liquid chromatography/electrospray ionization-tandem mass spectrometry.

BACKGROUND: Asymmetric dimethylarginine (ADMA), an endogenous nitric oxide (NO) formation inhibitor, has emerged as a promising biomarker of NO-associated endothelial dysfunction in cardiovascular diseases as well in chronic renal failure. The interest in potentially fundamental role of this metabolite, in basic and clinical research, led to the development of numerous analytical methods for the quantitative determination of ADMA and dimethylarginines in biological systems, notably plasma, serum and urine. OBJECTIVES: The aim of this work was to present a simple, fast and accurate UPLC-tandem-MS-based method for the simultaneous determination and quantification of arginine, ADMA, SDMA, NMMA, homo-arginine and citrulline. This method is designed for high sample throughput of only 10 µL of human plasma, serum or urine. METHODS: The analysis time is reduced to 1.9 min by an ultrahigh-performance liquid chromatography run coupled with electrospray ionization (ESI) in the positive mode tandem mass spectrometry detection. RESULTS: The method was validated in plasma, serum and urine. Correlation coefficients (r(2)) of the calibration curves in all matrices considered ranged from 0.9810 to 0.9993. Inter- and intra-assay precision, accuracy, recovery and carry-over were evaluated for validation. The LOD was 0.01 µM for all compounds in water, plasma and serum and 0.1 µM in urine. The LOQ was 0.05 µM for ADMA, SDMA, NMMA and H-Arg and 0.5 µM for Arg and Cit in water, plasma and serum; while in urine was 0.1 µM for ADMA, SDMA, NMMA and H-Arg and 0.5 µM for Arg and Cit. The precision was ranged from 1% to 15% expressed as CV% and the accuracy (bias %) was <±7% for all added concentrations with the exception of NMMA (-10%). ADMA mean plasma levels, measured in healthy adults and newborns, were in accord with literature data published: (M±SD) 0.56±0.10 µM and 0.84±0.21 µM, respectively, showing that ADMA levels in plasma decreased with age. In serum we have similar data (0.54±0.18 µM and 1.14±0.36 µM), while in neonatal urine ADMA was 11.98±7.13 µmol mmol(-1) creatinine. CONCLUSIONS: Data from calibration curves and method validation reveal that the method is accurate and precise. The fast run time, the feasibility of high sample throughput and the small amount of sample required make this method very suitable for routine analysis in the clinical setting.