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Background: This study assessed the alternations of kynurenine pathway (KP) and neopterin in type 2 diabetes mellitus (T2DM) and explored possible differential metabolites., Methods: A fresh residual sera panel was collected from 80 healthy control (HC) individuals and 72 T2DM patients. Metabolites/ratios of interest including tryptophan (TRP), kynurenine (KYN), 5-hydroxytryptamine (5HT), kynurenic acid (KA), xanthurenic acid (XA), neopterin (NEO), KA/KYN ratio and KYN/TRP ratio were determined using a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) metabolomics approach, and the difference between groups was assessed. Supervised orthogonal partial least squares-discriminant analysis and differential metabolite screening with fold change (FC) were performed to identify distinct biomarkers. The diagnostic performance of KP metabolites in T2DM was evaluated., Results: Significant decreases of TRP, 5HT, KA, XA, and KA/KYN and increases of KYN/TRP and NEO in T2DM compared to HC group were observed (P < 0.05). The KP metabolites panel significantly changed between T2DM and HC groups (Q 2 : 0.925, P < 0.005). 5HT (FC: 0.63, P < 0.01) and NEO (FC: 3.27, P < 0.01) were proven to be distinct differential metabolites. A combined testing of fasting plasma glucose and KYN/TRP showed good value in the prediction of T2DM (AUC: 0.904, 95% CI 0.843-0.947)., Conclusions: The targeted LC-MS/MS metabolomics study is a powerful tool for evaluating the status of T2DM. This study facilitated the application of KP metabolomics into future clinical practice. 5HT and NEO are promising biomarkers in T2DM. KYN/TRP was highly associated with the development of T2DM and may serve as a potential treatment target., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: This study aims to investigate serological characteristics of kynurenine pathway (KP) metabolites in healthy controls (HC) and gout patients and explore possible differential metabolites., Methods: A total of 191 individual fresh residual sera was collected from 129 HC and 62 gout patients. A liquid chromatography-tandem mass spectrometry method was fully validated to measure 6 metabolites, including tryptophan (TRP), kynurenine (KYN), 5-hydroxytryptamine (5HT), kynurenic acid (KA), xanthurenic acid (XA), and neopterin (NEO). Supervised orthogonal partial least squares-discriminant analysis (OPLS-DA) and differential metabolite screening with fold change (FC) were performed to identify intrinsic variations and differential levels of KP metabolites between the HC and gout groups. Logistic regression was used to assess the contributions of KP metabolites to gout., Results: There were significant decreases of TRP, 5HT, XA, and NEO and increases of KYN, KA, KA/KYN, and KYN/TRP in gout patients compared to the HC group (all p < 0.05). KP metabolites of the gout group showed good discrimination from those of the HC group (Q 2 : 0.892). Two distinct different metabolites were identified in gout, i.e., XA (FC: 0.56, p < 0.01) and NEO (FC: 0.34, p < 0.01). Of the KP metabolites, KYN was strongly associated with gout (OR: 7.91, p < 0.01)., Conclusions: Abnormal levels of serum KP metabolites were observed in gout. XA and NEO are promising biomarkers that were relevant to the status of gout. The level of KYN could be an attractive checkpoint for the management of gout. Continuous monitoring of KP metabolism in gout provides new opportunities to predict therapeutic efficacy and prognosis., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Little known about folates status in folate deficiency patients. This study aims to establish liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay-specific reference intervals (RIs) for serum 5-Methyltetrahydrofolate (5MeTHF), folic acid (FA), 5-Formyltetrahydrofolate (5FoTHF), and total folate (TFOL), and investigate the folates status in FA-supplemented folate deficient patients., Methods: Sera from 120 reference subjects were selected and measured. An LC-MS/MS method for serum 5MeTHF, FA, and 5FoTHF was employed. RIs were derived based on the CLSI C28-A3. Serum folate levels of 38 FA-supplemented folate deficiency patients were analyzed., Results: RIs (median) for 5MeTHF, FA, 5FoTHF, and TFOL were 3.83-62.33 nmol/L (12.27 nmol/L), 0.30-0.92 nmol/L (0.49 nmol/L), <0.73 nmol/L (0.00 nmol/L), and 4.17-63.47 nmol/L (12.66 nmol/L), respectively. Approximately 53 % (20/38), 74 % (28/38), and 63 % (24/38) of patients presented high levels of 5MeTHF, FA, and TFOL, respectively, which far exceeded the upper reference limit (URL) of the corresponding RIs. A half (18/38) of patients showed simultaneously higher 5MeTHF and FA levels which were beyond the URLs of RIs. Near one-third (11/38) of patients exhibited extremely high FA levels which exceeded the 100-fold URL of RIs. The highest levels can be 539 nmol/L for FA, 364 nmol/L for 5MeTHF, and 686 nmol/L for TFOL., Conclusions: LC-MS/MS assay-specific RIs were established for folates vitamers without age or gender partitioning. Abnormally high levels of unmetabolized FA and 5MeTHF were observed in quite a few FA-supplemented patients. Considering the adverse risks caused by folates excess, we appeal for a justifiable and individualized FA supplementation. We also recommend establishing LC-MS/MS assay-specific RIs for routine monitoring of folates status., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

Background: Down syndrome (DS) is the most common human chromosomal abnormality. About 1200 laboratories carry out antenatal screening for DS in second trimester pregnancies in China. Their prenatal assessment of DS pregnancy risk is based on biometric calculations conducted on maternal serum biochemical markers and ultrasonic markers of fetal growth. However, the performance of this triple test for DS in second trimester pregnancies has a false positive rate of 5%, and a detection rate of about 60%∼65%., Method: A total of 58,972 pregnant women, including 49 DS cases, who had undergone DS screening in the second trimester were retrospectively included and a machine learning (ML) model based on random forest was built to predict DS. In addition, the model was applied to another hospital data set of 27,170 pregnant women, including 27 DS cases, to verify the predictive efficiency of the model., Results: The ML model gave a DS detection rate of 66.7%, with a 5% false positive rate in the model data set. In the external verification data set, the ML model achieved a DS detection rate of 85.2%, with a 5% false positive rate . In comparison with the current laboratory risk model, the ML model improves the DS detection rate with the same false positive rate, while the difference has no significance., Conclusions: The ML model for DS detection described here has a comparable detection rate with the same false positive rate as the DS risk screening software currently used in China. Our ML model exhibited robust performance and good extrapolation, and could function as an alternative tool for DS risk assessment in second trimester maternal serum., (Copyright © 2021 The Authors. Published by Elsevier B.V. All rights reserved.)