The Metabolic Factor Kynurenic Acid of Kynurenine Pathway Predicts Major Depressive Disorder - Liu, Hongye; Ding, Lei; Zhang, Huifeng; Mellor, David; Wu, Haiyan; Zhao, Dongmei; Wu, Chuangxin; Lin, Zhiguang; Yuan, Jiaojian; Peng, Daihui (Frontiers in Psychiatry, 2018)
Background: Metabolic factors in the kynurenine pathway (KP) have been widely accepted as being a major mechanism in Major Depressive Disorder (MDD). However, the effects of these metabolites on the degree and pattern of MDD are still poorly understood, partly due to the elusiveness of the level of metabolites when diagnosing depression. This study aimed to explore a novel diagnostic method analyzing peripheral blood with mass spectrometry to assess metabolites from KP in patients with MDD and Bipolar Depression (BD). Methods: Thirty-three patients with MDD, 20 patients with BD and 23 healthy control participants were enrolled Metabolic factors of KP from plasma including tryptophan (TRP), kynurenine (KYN), kynurenic acid (KYNA) and quinolinic acid (QUIN) were analyzed by UPLC-3Q-MS, and levels compared across three groups. Correlation between HAMD scores and metabolite levels conducted. Receiver operating characteristic (ROC) curve was used to determine the diagnostic value of metabolic factors in MDD. Results: Levels of KYNA, QUIN, KYNA/QUIN and KYNA/KYN were statistically different across the three groups (P<0.05); HAMD scores and TRP, KYN, KYNA/QUIN levels were negatively correlated in the MDD group (r=-0.633, -0.477, -0.418, P<0.05); Accuracy of KYNA diagnosing MDD was 82.5% with the optimal diagnostic value being 15.48ng/ml. Diagnostic accuracy was increased to 83.6% when KYNA and QUIN levels were used in combination. Conclusion: This results indicate that metabolic factors of KP play a crucial role in the occurrence and development of MDD, supporting the metabolic imbalance hypothesis of MDD. Furthermore, our study also provides a new diagnostic method to study MDD based on plasma KYNA level, and suggests that KYNA would be a potential biomarker in diagnosing depression patients.