Quantitative LC-MS study of compounds found predictive of COVID-19 severity and outcome.

Since the beginning of the SARS-CoV-2 pandemic in December 2019 multiple metabolomics studies have proposed predictive biomarkers of infection severity and outcome. Whilst some trends have emerged, the findings remain intangible and uninformative when it comes to new patients. In this study, we accurately quantitate a subset of compounds in patient serum that were found predictive of severity and outcome. A targeted LC-MS method was used in 46 control and 95 acute COVID-19 patient samples to quantitate the selected metabolites. These compounds included tryptophan and its degradation products kynurenine and kynurenic acid (reflective of immune response), butyrylcarnitine and its isomer (reflective of energy metabolism) and finally 3',4'-didehydro-3'-deoxycytidine, a deoxycytidine analogue, (reflective of host viral defence response). We subsequently examine changes in those markers by disease severity and outcome relative to those of control patients' levels. Finally, we demonstrate the added value of the kynurenic acid/tryptophan ratio for severity and outcome prediction and highlight the viral detection potential of ddhC.

Roberts I ，Wright Muelas M ，Taylor JM ，Davison AS ，Winder CL ，Goodacre R ，Kell DB ... -  《-》

Simultaneous measurement of kynurenine metabolites and explorative metabolomics using liquid chromatography-mass spectrometry: A novel accurate method applied to serum and plasma samples from a large healthy cohort.

Kynurenine metabolites are emerging as promising clinical biomarkers in several diseases, especially within psychiatry. Unfortunately, they are difficult to detect, particularly the challenging neurotoxic metabolite quinolinic acid (QUIN). The aim of this study was twofold: First, to develop a liquid chromatography-mass spectrometry method (LC-MS) for simultaneous targeted quantification of key kynurenine metabolites together with untargeted metabolomics, and second, to demonstrate the feasibility of the method by exploring serum/plasma and gender differences in 120 healthy young adults between 18 and 30 years of age. A range of analytical columns (C18 and biphenyl columns) and mobile phases (acidic and alkaline) were systematically evaluated. The optimized LC-MS method was based on a biphenyl column, a water-methanol gradient with 0.2% formic acid, and authentic isotope-labeled standards for each kynurenine metabolite. Precision and accuracy of targeted quantification of the key kynurenine metabolites tryptophan (TRP), kynurenine (KYN), kynurenic acid (KYNA), 3-hydroxykynurenine (3-HK), and QUIN were excellent, far exceeding the acceptance criteria specified by international guidelines. Median inter- and intra-day precision were < 6% in serum and plasma; the median accuracy was 2.4% in serum and 8% in plasma. Serum concentrations were ≤ 10% different from the corresponding concentrations in plasma for all kynurenine metabolites in healthy young adults. Men had higher levels (8-18%) of TRP, KYN, and KYNA than women (p ≤ 0.009), while no differences were observed for 3-HK and QUIN (p > 0.70). Incurred sample reanalysis of 10% of the samples yielded a median difference < 5% from the initial measurement, demonstrating the robustness of the method. Besides the targeted quantification of key kynurenine metabolites, our method was found to be suitable for simultaneous untargeted metabolomics analyses of hundreds of metabolites. A range of compound classes could be detected including amino acids, nucleic acids, dipeptides, antioxidants, and acylcarnitines, making explorative studies highly feasible. For example, we identified an additional kynurenine metabolite, 2-Quinolinecarboxylic acid, which was 47% higher in males than females (adjusted p-value = 0.001). In conclusion, in this study, we present a reliable and robust LC-MS method for simultaneous targeted and untargeted metabolomics ready for both research and clinical use. We show that both serum and plasma can be used for kynurenine studies, and the reported gender differences are in accordance with the literature. Future studies should consider using biphenyl-based LC-MS columns to successfully detect QUIN.

Eggertsen PP ，Hansen J ，Andersen ML ，Nielsen JF ，Olsen RKJ ，Palmfeldt J ... -  《-》

Altered neopterin and IDO in kynurenine metabolism based on LC-MS/MS metabolomics study: Novel therapeutic checkpoints for type 2 diabetes mellitus.

This study assessed the alternations of kynurenine pathway (KP) and neopterin in type 2 diabetes mellitus (T2DM) and explored possible differential metabolites. 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. 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 (Q2: 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). 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.

Liu Z ，Ma Z ，Jin L ，Nizhamuding X ，Zeng J ，Zhang T ，Zhang J ，Wang J ，Zhao H ，Zhou W ，Zhang C ... -  《-》

LC-MS/MS-based quantification of tryptophan, kynurenine, and kynurenic acid in human placental, fetal membranes, and umbilical cord samples.

Tryptophan breakdown metabolites formed along the kynurenine pathway play a significant role in pregnancy and fetal development. To understand their involvement, it is crucial to quantify the levels of tryptophan (TRP), kynurenine (KYN), and kynurenic acid (KYNA) in relevant biological samples such as the placenta, fetal membranes, and umbilical cord. This study used liquid chromatography-tandem mass spectrometry (LC-MS/MS) to determine TRP, KYN, and KYNA levels. The LC-MS/MS method was optimized for high sensitivity and specificity, demonstrating good reproducibility with a precision of < 10% CV and an accuracy of 85-115%. The lower limit of quantification for both TRP and KYN was 0.5 µg/ml, while for KYNA, it was 0.5 ng/mL. The method exhibited linearity within the examined range of concentrations in the homogenate, ranging from 0.5 to 30 µg/ml for TRP and KYN and from 0.5 to 25 ng/ml for KYNA. Using this method, we found significant differences in the concentrations of these substances in investigated maternal-fetal compartments. Placenta samples exhibited higher KYN and lower KYNA concentrations than the umbilical cord and fetal membrane, indicating a potentially important role for kynurenines in late pregnancy. Collectively, this finding may facilitate further research and provide inside into the involvement of the kynurenine pathway of TRP metabolism in fetal development.

Pedraz-Petrozzi B ，Marszalek-Grabska M ，Kozub A ，Szalaj K ，Trzpil A ，Stachniuk A ，Lamadé EK ，Gilles M ，Deuschle M ，Turski WA ，Fornal E ... -  《Scientific Reports》

Untargeted metabolomics of COVID-19 patient serum reveals potential prognostic markers of both severity and outcome.

Roberts I ，Wright Muelas M ，Taylor JM ，Davison AS ，Xu Y ，Grixti JM ，Gotts N ，Sorokin A ，Goodacre R ，Kell DB ... -  《-》