ABSTRACT: Background: 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.
