Serum Kynurenine Pathway Metabolites as Candidate Diagnostic Biomarkers for Pituitary Adenoma: A Case-Control Study

Abstract

Background and Objectives: Pituitary adenomas are common intracranial tumors lacking specific non-invasive biomarkers. This study aimed to determine whether key metabolites and enzymes of the kynurenine pathway-including indoleamine 2,3-dioxygenase (IDO), kynurenine (KYN), kynurenic acid (KYNA), kynurenine aminotransferase (KAT), quinolinic acid, and picolinic acid-can serve as diagnostic biomarkers distinguishing patients with pituitary adenomas from healthy controls. Materials and Methods: We conducted a single-center, cross-sectional, case-control study with 50 patients with pituitary adenomas and 35 healthy controls. Serum levels of IDO, KYN, KYNA, KAT, quinolinic acid, and picolinic acid were measured via enzyme-linked immunosorbent assay (ELISA). Statistical analyses included group comparisons (t-test/Mann-Whitney U), multivariate logistic regression to identify independent predictors, receiver operating characteristic (ROC) curve analysis to evaluate diagnostic performance (area under the curve, AUC), and partial least squares discriminant analysis (PLS-DA) for multivariate metabolic profiling. Results: Serum kynurenine, kynurenic acid, 3-hydroxykynurenine, picolinic acid, IDO and kynureninase were significantly higher in the pituitary adenoma group than in healthy controls (p < 0.001), while tryptophan, kynurenine aminotransferase, anthranilic acid and quinolinic acid showed no significant differences. ROC analysis demonstrated excellent diagnostic accuracy, with KAT (AUC = 0.923) and KYNA (AUC = 0.901) showing the highest discrimination. Multivariate logistic regression identified IDO, KYN, and KYNA as independent predictors of pituitary adenoma (p < 0.05). PLS-DA of the combined metabolite data also demonstrated clear separation between patients and controls, confirming distinct metabolic profiles between the groups. Conclusions: Kynurenine pathway metabolites and enzymes show strong potential as non-invasive biomarkers for pituitary adenomas. In particular, elevated KAT and KYNA levels demonstrated high diagnostic performance. These findings suggest that a panel of kynurenine pathway metabolites could aid in the early, non-invasive detection of pituitary adenomas.