A plasma N-acetyl amino acid panel for type 2 diabetes discrimination built by targeted LC-MS/MS: A case-control study.

Background: Type 2 diabetes (T2D) is characterized by profound metabolic disturbances, yet clinically actionable biomarkers beyond conventional glycaemic indices remain limited. N-acetyl amino acids (NAcAAs) are emerging metabolites linked to amino acid metabolism and acetylation status, but their quantitative profile and diagnostic relevance in T2D have not been systematically defined. Objectives: To characterize the plasma NAcAA profile in T2D using a targeted LC-MS/MS approach, to evaluate associations between individual NAcAAs and clinical traits, and to develop a metabolite-based panel for T2D discrimination. Methods: In this case-control study, we developed and validated a targeted LC-MS/MS assay for the absolute quantification of 19 plasma NAcAAs. The assay was applied to 174 individuals with T2D and 68 non-diabetic controls. Global metabolic differences were assessed by principal component analysis and hierarchical clustering. Associations between NAcAAs and clinical traits were examined by correlation analysis and multivariable logistic regression. Least absolute shrinkage and selection operator (LASSO) logistic regression was used to construct a compact diagnostic signature. Model performance was evaluated by receiver operating characteristic (ROC) analysis, calibration, and decision curve analysis. Results: The plasma NAcAA landscape differed substantially between T2D and controls, with coordinated increases in metabolites such as N-acetyltryptophan and decreases in several others, including N-acetylproline, N-acetylglutamine, and N-acetyllysine. Differential NAcAAs were significantly associated with glycaemic traits, particularly fasting glucose and HbA1c, as well as renal-related markers including urea nitrogen and creatinine. In adjusted logistic regression models, N-acetyltryptophan was positively associated with T2D (OR = 9.452, 95% CI 4.421-20.211). In contrast, several NAcAAs showed inverse associations, including N-acetylproline (OR = 0.041, 95% CI 0.015-0.111) and N-acetyllysine (OR = 0.088, 95% CI 0.038-0.203). An 8-metabolite panel derived by LASSO achieved excellent discriminatory performance (AUC = 0.963, 95% CI 0.942-0.984), with good calibration and favorable net clinical benefit. Conclusion: Targeted quantitative profiling of plasma NAcAAs identifies a distinct metabolic signature associated with T2D. A compact NAcAA-based panel shows strong potential for T2D discrimination and may serve as a complementary tool for metabolic risk characterization and translational biomarker development.