MetaboLights

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identification was achieved using internal Biocrates database MetIDQMetaboLightsPublicFlow injection analysis MS - positiveLiquid Chromatography MS - positive - reverse-phase Mass spectrometric detection was performed using multiple reaction monitoring (MRM) according to the transitions provided by the kit manufacturer. Metabolites analyzed using the LC method were quantified using TargetLynx XS 4.1 (Waters, Milford, MA, USA) with isotope-labelled internal standards provided with the kit. Amino acids and biogenic amines were analyzed using LC-MS in positive mode. The analytes separation was performed using a Waters BEH C18 column (1.7 µm, 2.1 mm x 50 mm) (Cat No. 186002350) connected to a Waters BEH C18 guard column (1.7 µm, 2.1 mm x 5 mm) (Cat No. 186003975). The column temperature was maintained at 50 °C. The LC mobile phases consisted of solvent A (water with 0.2% formic acid) and solvent B (acetonitrile with 0.2% formic acid). The gradient elution program was as follows: 0% B at 0.25 min, increased to 12% B at 1.5 min, 17.5% B at 2.7 min, and 50% B at 4.0 min, followed by re-equilibration to 0% B at 4.5 min and maintained until 6.0 min. The flow rate was set to 0.8 mL/min until 4.5 min, increased to 1.0 mL/min at 4.7 min, maintained at 1.0 mL/min until 5.1 min, and then reduced to 0.8 mL/min at 5.8 min and maintained until 6.0 min.Serum metabolomic profile in children with type 1 diabetes mellitus: an exploratory targeted metabolomics study of candidate discriminatory features.Emilia SamborowskaEmilia Samborowska The FIA extract was analyzed in positive mode to capture acylcarnitines, glycerophospholipids, and sphingolipids, while hexoses were monitored in negative mode. FIA-MS method is a direct infusion without chromatographic separation, which allows rapid quantification of metabolites using mass spectrometry, as described in previous metabolomic workflows [19,20]. The FIA mobile phase consisted of methanol with a dedicated FIA mobile phase additive provided by the kit manufacturer (290 mL methanol and one ampule of FIA additive). The analysis was performed under isocratic conditions (100% solvent B) over a total run time of 2 minutes. The FIA flow rate program was as follows: 0.15 mL/min at 0.05 min, reduced to 0.03 mL/min at 0.06 min and maintained until 1.1 min, increased to 0.2 mL/min at 1.5 min, then to 0.8 mL/min at 1.6 min and maintained until 1.85 min, followed by reduction to 0.15 mL/min at 1.95 min and maintained until 2.0 min. Metabolites measured using the FIA method were quantified using MetIDQ™ software (Biocrates Life Sciences GmbH, Innsbruck, Austria; version Oxygen-DB110-3005) according to the manufacturer’s guidelines.blood serummass spectrometry assay Serum samples obtained from T1DM patients and non-diabetic individuals (controls) were collected after an overnight fast (at least 8 h) and stored at −80 °C until analysis. Before analysis, all serum samples were thawed, centrifuged at 2 750 g, 4°C for 5 minutes, and then vortexed for 15 minutes at 1200 RPM. The preparation procedure was as follows: 10 µl of internal standard (IS) was put onto each 96-well plate, and 10 µl of the respective sample was pipetted into the previously assigned well. The list of internal standards (IS) included in the kit and used for metabolite quantification is provided in Supplementary Table S2. Samples were dried under a nitrogen stream using a Positive Pressure-96 Processor for 30 minutes. Next, 50 µl of derivatization mixture was added to each well, and the plate was left to derivatize for 25 min at room temperature. The plate was dried using a positive pressure manifold for 60 minutes. 300 µl of extraction solvent was added to each well and vortexed at 450 RPM for 30 minutes, and then centrifuged at 500 g for 2 minutes to elute the analytes. The mixture was divided into two portions: 150 µl of the eluted extract was transferred to a 96-well liquid chromatography (LC) plate, diluted with 150 µl of pure water, and 10 µl of the mixture was transferred to a 96-well flow injection analysis (FIA) plate and diluted with 490 µl of FIA mobile phase. Plates were vortexed at 600 RPM for 5 and 10 minutes, respectively. Plates, both LC and FIA, were analyzed using mass spectrometry.Quality control (QC) was performed according to the manufacturer’s instructions using three levels of quality control samples (QC1, QC2, and QC3) provided with the kit. QC samples were included in each analytical batch to monitor analytical performance, reproducibility, and system stability. The analytical performance was considered acceptable when QC values were within the ranges specified by the manufacturer. A similar analytical workflow using the AbsoluteIDQ® p180 kit has been previously describeHomo sapienshttps://www.ebi.ac.uk/metabolights/MTBLS15768Filip Ambrożkiewicz. Charles University. filip.ambrozkiewicz@lfp.cuni.cz.Mariusz Radkiewicz. Institute of Biochemistry and Biophysics, Polish Academy of Sciences. m.radkiewicz@ibb.waw.pl.Bożena Cukrowska. Children's Memorial Health Institute. bc@nordicbiotic.com.Jakub Karczmarski. Institute of Biochemistry and Biophysics, Polish Academy of Sciences. jkarczmarski@ibb.waw.pl.Marta Wysocka-Mincewicz. University of Siedlce. syndykatka@wp.pl.Emilia Samborowska. Emilia Samborowska. sambor@ibb.waw.pl.Jolanta Świderska. Children's Memorial Health Institute. J.SWIDERSKA@ipczd.pl.Damian Dyńka. University of Siedlce. damian.dynka24@gmail.com.Agnieszka Paziewska. Institute of Health Sciences, Faculty of Medical and Health Sciences, University of Siedlce. agnieszka.paziewska@uws.edu.pl.Agnieszka Ochocińska. Children's Memorial Health Institute. A.Ochocinska@ipczd.pl.Karolina Skubisz. University of Warsaw. karolina.skubisz@gmail.com.Katarzyna Kowalcze. University of Siedlce. katarzyna.kowalcze@uws.edu.pl.The RAW files were acquired using MassLynx and were analyzed using MetIDQDiabetes type isambor@ibb.waw.plSamples were collected in Centrum Zdrowia DzieckaMetabolomicsMetabolomicstype 1 diabetes mellitusWaters ACQUITY UPLC H-Class SystemWaters Xevo TQ-Stargeted analysismultiple reaction monitoringMassLynxHomo sapiensXevo TQ-Sexperimental sampleInstitute of Biochemistry and Biophysics, Polish Academy of Sciencesblood serumChildren's Memorial Health InstituteMetabolomicstype 1 diabetes mellitusWaters ACQUITY UPLC H-Class SystemWaters Xevo TQ-Stargeted analysismultiple reaction monitoringMassLynxHomo sapiensXevo TQ-Sexperimental sampleInstitute of Biochemistry and Biophysics, Polish Academy of Sciencesblood serumChildren's Memorial Health Institute Mass spectrometric detection was performed using multiple reaction monitoring (MRM) according to the transitions provided by the kit manufacturer. Metabolites analyzed using the LC method were quantified using TargetLynx XS 4.1 (Waters, Milford, MA, USA) with isotope-labelled internal standards provided with the kit. falseSerum metabolomic profile in children with type 1 diabetes mellitus: an exploratory targeted metabolomics study of candidate discriminatory featuresBackground: Type 1 diabetes mellitus (T1DM) is an increasingly common chronic disease caused by autoimmune damage to pancreatic beta cells. Metabolomic profiling may provide insights into metabolic disturbances associated with T1DM and identify candidate biomarkers. Methods: The study included 29 children with T1DM and 11 controls. Targeted serum metabolomic profiling was performed using the AbsoluteIDQ® p180 kit based on liquid chromatography-mass spectrometry. Differential metabolites were identified using statistical analysis with false discovery rate correction. Receiver operating characteristic (ROC) analysis was applied to evaluate the discriminatory performance of selected metabolites. Results: Significant metabolic alterations were observed in children with T1DM, particularly in glycerophospholipids, acylcarnitines, and selected amino acids. Among glycerophospholipids, 23 metabolites were significantly decreased, whereas one metabolite was increased in T1DM group. Four acylcarnitines differed significantly between groups, with higher concentrations of octadecenoylcarnitine (C18:1), acetylcarnitine, and malonylcarnitine (hydroxybutyrylcarnitine), and reduced free carnitine. In addition, three amino acids (alanine, arginine, and proline) were significantly decreased, while taurine was increased in T1DM patients. ROC analysis showed high apparent discriminatory performance for C18:1 (AUC = 0.925) and diacyl phosphatidylcholine (PC aa) C42:5 (AUC = 0.922) in this exploratory dataset; however, these findings require external validation. These AUC values were obtained from the same dataset used for metabolite discovery and therefore represent apparent in-sample discriminatory performance rather than externally validated diagnostic performance. Correlation analysis showed that higher HbA1c levels were associated with lower concentration of several amino acids and lipids, BMI z-score and disease duration were associated mainly with phosphatidylcholines and amino acids. However, none of these correlation-based associations remained significant after FDR correction and should therefore be considered hypothesis-generating. Exploratory multivariable analyses suggested associations of HbA1c, BMI z-score, and disease duration with selected metabolites; however, given the limited sample size and multiple model testing, these findings should be considered hypothesis-generating. Conclusion: Targeted metabolomic profiling revealed significant disturbances in lipid and amino acid metabolism in children with T1DM. In particular, increased C18:1 and decreased PC aa C42:5 may represent candidate metabolic features for distinguishing T1DM patients from non-diabetic individuals. Due to the exploratory study and limited sample size, our results should be interpreted with caution, and further studies in larger, independent cohorts are required to validate these findings.2026-09-222026-09-22MTBLS15768