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Search Results (356)

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16 pages, 311 KiB  
Article
Assessment of Inflammatory and Oxidative Stress Biomarkers for Predicting of Patients with Asymptomatic Carotid Artery Stenosis
by Abdullah Burak Karaduman, Sinem Ilgın, Özlem Aykaç, Mehmetcan Yeşilkaya, Serkan Levent, Atilla Özcan Özdemir and Gozde Girgin
J. Clin. Med. 2025, 14(3), 755; https://doi.org/10.3390/jcm14030755 - 24 Jan 2025
Viewed by 247
Abstract
Background/Objectives: Asymptomatic carotid artery stenosis is usually detected by physicians in patients, coincidentally, during an ultrasound examination of the neck. Therefore, measurable biomarkers in blood are needed to define the presence and severity of atherosclerotic plaque in patients to identify and manage [...] Read more.
Background/Objectives: Asymptomatic carotid artery stenosis is usually detected by physicians in patients, coincidentally, during an ultrasound examination of the neck. Therefore, measurable biomarkers in blood are needed to define the presence and severity of atherosclerotic plaque in patients to identify and manage it. We hypothesized that biomarkers that indicate pathways related to the pathogenesis of atherosclerosis could be used to identify the presence and severity of atherosclerotic plaque. For this purpose, the levels of participants’ inflammatory and oxidative stress biomarkers were determined. Kynurenine/tryptophan and neopterin levels were measured as relatively new biomarkers of inflammation in this study. Methods: Our study included 57 patients diagnosed with asymptomatic carotid artery stenosis and 28 healthy volunteers. Blood kynurenine and tryptophan levels were measured with LCMS/MS. Blood catalase, total superoxide dismutase (t-SOD), glutathione peroxidase (GPx), malondialdehyde, and neopterin levels were measured using the ELISA assay method. Result: The kynurenine/tryptophan ratio reflecting IDO activity was higher in patients than in healthy volunteers. Decreased tryptophan levels and increased kynurenine and neopterin levels were observed in patients who underwent carotid endarterectomy. In patients, catalase, t-SOD, and malondialdehyde levels were higher, while GPx activity was lower. These differences were found to be more significant in patients who underwent carotid endarterectomy. Conclusions: Increased kynurenine/tryptophan ratio and neopterin levels in patients with asymptomatic carotid artery stenosis were associated with the inflammatory status of the patients. Oxidative stress and inflammatory biomarkers can be considered effective diagnostic and severity indicators for asymptomatic carotid artery stenosis. Full article
(This article belongs to the Section Cardiovascular Medicine)
24 pages, 7704 KiB  
Article
Plasma and Visceral Organ Kynurenine Metabolites Correlate in the Multiple Sclerosis Cuprizone Animal Model
by Helga Polyák, Zsolt Galla, Cecilia Rajda, Péter Monostori, Péter Klivényi and László Vécsei
Int. J. Mol. Sci. 2025, 26(3), 976; https://doi.org/10.3390/ijms26030976 - 24 Jan 2025
Viewed by 212
Abstract
The cuprizone (CPZ) model of multiple sclerosis (MS) is excellent for studying the molecular differences behind the damage caused by poisoning. Metabolic differences in the kynurenine pathway (KP) of tryptophan (TRP) degradation are observed in both MS and a CPZ mouse model. Our [...] Read more.
The cuprizone (CPZ) model of multiple sclerosis (MS) is excellent for studying the molecular differences behind the damage caused by poisoning. Metabolic differences in the kynurenine pathway (KP) of tryptophan (TRP) degradation are observed in both MS and a CPZ mouse model. Our goal was to analyze the kynurenine, serotonin, and indole pathways of TRP degradation on the periphery, in the neurodegenerative processes of inflammation. In our study, mice were fed with 0.2% CPZ toxin for 5 weeks. We examined the metabolites in the three pathways of TRP breakdown in urine, plasma, and relevant visceral organs with bioanalytical measurements. In our analyses, we found a significant increase in plasma TRP, 5-hydroxytryptophan (5-HTP), and indole-3-acetic acid (IAA) levels, while a decrease in the concentrations of 3-hydroxy-L-kynurenine (3-HK), xanthurenic acid (XA), kynurenic acid (KYNA), and quinaldic acid in the plasma of toxin-treated group was found. A marked decrease in the levels of 3-HK, XA, KYNA, quinaldic acid, and indole-3-lactic acid was also observed in the visceral organs by the end of the poisoning. Furthermore, we noticed a decrease in the urinary levels of the TRP, KYNA, and XA metabolites, while an increase in serotonin and 5-hydroxyindoleacetic acid in the CPZ group was noticed. The toxin treatment resulted in elevated tryptamine and indoxyl sulfate levels and reduced IAA concentration. Moreover, the urinary para-cresyl sulfate concentration also increased in the treated group. In the present study, we showed the differences in the three main metabolic pathways of TRP degradation in the CPZ model. We confirmed the relationship and correlation between the content of the kynurenine metabolites in the plasma and the tissues of the visceral organs. We emphasized the suppression of the KP and the activity of the serotonin and indole pathways with a particular regard to the involvement of the microbiome by the indole pathway. Consequently, this is the first study to analyze in detail the distribution of the kynurenine, serotonin, and indole pathways of TRP degradation in the periphery. Full article
(This article belongs to the Special Issue Molecular Insights into Multiple Sclerosis)
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Figure 1

Figure 1
<p>Three main pathways of tryptophan degradation. NAD+: nicotinamide adenine dinucleotide. The highlighted metabolites, in the case of which we observed discrepancies as a result of CPZ toxin treatment, in the three main pathways of TRP degradation that we investigated.</p>
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<p>Differences in the body weight of the animals during investigation. The control group is represented by gray bars, while CPZ-treated group is represented by blue bars in the demyelination period. CO: control group; CPZ: cuprizone-treated group, **: <span class="html-italic">p</span> &lt; 0.01 vs. CO, ***: <span class="html-italic">p</span> &lt; 0.001 vs. CO. The data are presented as mean ± SEM.</p>
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<p>Alterations of kynurenic acid (KYNA) and xanthurenic acid (XA) concentrations during intoxication. The KYNA and XA levels were significantly reduced in urine of the CPZ-treated group during the entire period of poisoning. CO: control group, CPZ: cuprizone-treated group, w: week, ***: <span class="html-italic">p</span> &lt; 0.001 vs. CO.</p>
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<p>Changes in urinary tryptamine levels during treatment. The concentration of tryptamine in the urine of the toxin-treated group increased, indicating poisoning. CO: control group, CPZ: cuprizone-treated group, w: week, *: <span class="html-italic">p</span> &lt; 0.05 vs. CO, **: <span class="html-italic">p</span> &lt; 0.01 vs. CO, ***: <span class="html-italic">p</span> &lt; 0.001 vs. CO.</p>
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<p>Increased serotonin and 5-hydroxyindoleacetic acid (5-HIAA) levels in the CPZ-treated group. By the third week of the intoxication, the concentrations of serotonin and 5-HIAA in the urine of the CPZ group were significantly higher compared to the CO group; these differences were also observed in the fifth week of treatment. CO: control group, CPZ: cuprizone-treated group, w: week, *: <span class="html-italic">p</span> &lt; 0.05 vs. CO, **: <span class="html-italic">p</span> &lt; 0.01 vs. CO.</p>
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<p>Alterations of indoxyl sulfate (IS) and para-cresyl sulfate (pCS) concentrations during CPZ poisoning. In the fourth week of treatment, the urinary IS level of the CPZ group was significantly increased compared to the CO group, while the level of pCS already differed markedly between the groups in the third week of intoxication. CO: control group, CPZ: cuprizone-treated group, w: week, *: <span class="html-italic">p</span> &lt; 0.05 vs. CO, **: <span class="html-italic">p</span> &lt; 0.01 vs. CO.</p>
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<p>Decreased tryptophan (TRP) and indole-3-acetic acid (IAA) levels at the end of treatment. The concentrations of TRP and IAA were markedly reduced in the urine of the toxin-treated group in the fifth week of poisoning. CO: control group, CPZ: cuprizone-treated group, w: week, *: <span class="html-italic">p</span> &lt; 0.05 vs. CO.</p>
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<p>Alterations of kynurenine metabolites in plasma during intoxication. In the fifth week of poisoning, the concentrations of 3-hydroxy-L-kynurenine (3-HK), kynurenic acid (KYNA), and xanthurenic acid (XA) were significantly decreased in the CPZ-treated group. CO: control group, CPZ: cuprizone-treated group, w: week, **: <span class="html-italic">p</span> &lt; 0.01 vs. CO, ***: <span class="html-italic">p</span> &lt; 0.001 vs. CO.</p>
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<p>Changes in plasma 5-hydroxytryptophan (5-HTP) and quinaldic acid levels at the end of treatment. After 5 weeks of intoxication, the concentration of 5-HTP increased in the CPZ-treated group while the level of quinaldic acid decreased in plasma. CO: control group, CPZ: cuprizone-treated group, w: week, *: <span class="html-italic">p</span> &lt; 0.05 vs. CO, **: <span class="html-italic">p</span> &lt; 0.01 vs. CO.</p>
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<p>Increased tryptophan (TRP) and indole-3-acetic acid (IAA) concentrations in the fifth week of treatment. At the end of the poisoning, the plasma levels of TRP and IAA were remarkably elevated in the CPZ group compared to the CO group. CO: control group, CPZ: cuprizone-treated group, w: week, **: <span class="html-italic">p</span> &lt; 0.01 vs. CO.</p>
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<p>Decreased kynurenine metabolites in the visceral organs at the end of the poisoning. In the fifth week of treatment, the kynurenic acid (KYNA), xanthurenic acid (XA), 3-hydroxy-L-kynurenine (3-HK), and quinaldic acid concentrations were markedly reduced in the liver, kidney, heart, and lungs. CO: control group, CPZ: cuprizone-treated group, w: week, *: <span class="html-italic">p</span> &lt; 0.05 vs. CO, **: <span class="html-italic">p</span> &lt; 0.01 vs. CO, ***: <span class="html-italic">p</span> &lt; 0.001 vs. CO.</p>
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<p>Reduced indole-3-lactic acid (ILA) level in the visceral organs of the CPZ group. As a result of poisoning, the ILA concentration was significantly decreased in the liver, kidney, and lungs as well as in the heart, where the difference was not significant. CO: control group, CPZ: cuprizone-treated group, w: week, *: <span class="html-italic">p</span> &lt; 0.05 vs. CO, **: <span class="html-italic">p</span> &lt; 0.01 vs. CO.</p>
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<p>Timeline of the experimental procedure used. CPZ: cuprizone group; n: represents the number of animals used in one group; UHPLC-MS/MS: ultra-high-performance liquid chromatography-tandem mass spectrometry; numbers (1–5) in the figure: experimental weeks (week 1 to week 5); * Plasma, liver, kidney, heart, and lung samples were used for bioanalytical measurements both from the CO and the CPZ-treated groups.</p>
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21 pages, 1491 KiB  
Review
Role of Kynurenine and Its Derivatives in Liver Diseases: Recent Advances and Future Clinical Perspectives
by Qiwen Tan, Shenghe Deng and Lijuan Xiong
Int. J. Mol. Sci. 2025, 26(3), 968; https://doi.org/10.3390/ijms26030968 - 24 Jan 2025
Viewed by 226
Abstract
Liver health is integral to overall human well-being and the pathogenesis of various diseases. In recent years, kynurenine and its derivatives have gradually been recognized for their involvement in various pathophysiological processes, especially in the regulation of liver diseases, such as acute liver [...] Read more.
Liver health is integral to overall human well-being and the pathogenesis of various diseases. In recent years, kynurenine and its derivatives have gradually been recognized for their involvement in various pathophysiological processes, especially in the regulation of liver diseases, such as acute liver injury, non-alcoholic fatty liver disease, cirrhosis, and liver cancer. Kynurenine and its derivatives are derived from tryptophan, which is broken down by the enzymes indoleamine 2,3-dioxygenase (IDO) and tryptophan 2,3-dioxygenase (TDO), converting the essential amino acid tryptophan into kynurenine (KYN) and other downstream metabolites, such as kynurenic acid (KYNA), 3-hydroxykynurenine (3-HK), xanthurenic acid (XA), and quinolinic acid (QA). In liver diseases, kynurenine and its derivatives can promote the activity of the transcription factor aryl hydrocarbon receptor (AhR), suppress T cell activity for immune modulation, inhibit the activation of inflammatory signaling pathways, such as NF-κB for anti-inflammatory effects, and inhibit the activation of hepatic stellate cells to slow down fibrosis progression. Additionally, kynurenine and other downstream metabolites can influence the progression of liver diseases by modulating the gut microbiota. Therefore, in this review, we summarize and explore the mechanisms by which kynurenine and its derivatives regulate liver diseases to help develop new diagnostic or prognostic biomarkers and effective therapies targeting the kynurenine pathway for liver disease treatment. Full article
(This article belongs to the Section Biochemistry)
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Figure 1

Figure 1
<p>Overview of the kynurenine pathway (KP). This figure shows the main metabolites and enzymes of the KP. Abbreviations: NAD+, nicotinamide adenine dinucleotide; IDO, indoleamine 2,3-dioxygenase; TDO, Tryptophan 2,3-dioxygenase; KMO, kynurenine 3-monooxygenase; KAT, kynurenine aminotransferases; KMO, kynurenine 3-monooxygenase; 3-HAO, 3-hydroxyanthranilate 3,4-dioxygenase; QPRT, quinolinic acid phosphoribosyl transferase.</p>
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<p>The interaction between the gut and liver. Tryptophan is partially absorbed in the gut, while the rest is metabolized by gut microbiota through the indole pathway into various beneficial or harmful metabolites like IPA, IAA, indole, SCFAs, etc., which then enter the portal vein system and reach the liver, modulating the kynurenine pathway. On the other hand, kynurenine metabolites, such as KYN, KYNA, 3-HKK, IDO, etc., are also capable of returning to the gut to exert regulatory effects. Abbreviations: KYNA, kynurenic acid; NAD+, nicotinamide adenine dinucleotide; 3-HK, 3-hydrokynurenine; Trp, tryptophan; IPA, indole-3-propionic acid; IAA, indole-3-acetic acid; SCFAs, short-chain fatty acids.</p>
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<p>Molecular mechanisms of kynurenine pathway in liver diseases. (<b>a</b>) In acute liver injury, the metabolic migration of kynurenine pathway from kynurenine (Kyn) to nicotinamide adenine dinucleotide leads to endoplasmic reticulum stress and activation of NF-κB signaling pathway to induce hepatocyte apoptosis. (<b>b</b>) In metabolic dysfunction-associated steatotic liver disease, the kynurenine pathway activates Gpr35 and RGS to increase energy expenditure, regulate fatty acid metabolism, and improve inflammation. (<b>c</b>) In liver cirrhosis, IDO-1 can inhibit hepatic stellate cell activation and scavenge free radicals to reduce oxidative damage by decreasing nuclear factor E2-related factor 2 (Nrf2). (<b>d</b>) The kynurenine pathway activates AHR, thereby inhibiting tumor initiation and progression and promoting tumor cell apoptosis. Abbreviations: Trp, tryptophan; KYN, kynurenine; KYNA, kynurenic acid; 3-HAA, 3-hydroxyanthranilic acid; ROS, reactive oxygen species; NF-κB, nuclear factor-κB; NAD+, nicotinamide adenine dinucleotide; IDO, indoleamine 2,3-dioxygenase; TDO, tryptophan 2,3-dioxygenase; KMO, kynurenine 3-monooxygenase; RGS, regulator of G protein; GPR35, G protein-coupled receptor 35; AhR, aryl hydrocarbon receptor; CYP1A1, cytochrome P450, family 1, subfamily A, polypeptide 1.</p>
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24 pages, 4775 KiB  
Article
Sensitive Detection of Kynurenic Acid from Biological Fluids Using a Flexible Electrochemical Platform Based on Gold Nanoparticles and Reduced Graphene Oxide
by Diana-Gabriela Macovei, Mihaela Tertis, Diana Bogdan, Maria Suciu, Lucian Barbu-Tudoran and Cecilia Cristea
Int. J. Mol. Sci. 2025, 26(3), 913; https://doi.org/10.3390/ijms26030913 - 22 Jan 2025
Viewed by 446
Abstract
Kynurenic acid (KA), a key metabolite of tryptophan (TRP) via the kynurenine pathway, plays a significant role in various physiological and pathological conditions, including neurodegenerative diseases, depression, and schizophrenia. This study aims to develop a flexible and sensitive electrochemical sensor platform for the [...] Read more.
Kynurenic acid (KA), a key metabolite of tryptophan (TRP) via the kynurenine pathway, plays a significant role in various physiological and pathological conditions, including neurodegenerative diseases, depression, and schizophrenia. This study aims to develop a flexible and sensitive electrochemical sensor platform for the direct detection of KA in biological fluids. Custom carbon-based electrodes were fabricated using specialized inks and a flexible plastic substrate, followed by functionalization with a composite film of gold nanoparticles, graphene oxide (GO), and polyethyleneimine (PEI). The GO was electrochemically reduced to enhance conductivity and sensitivity for the target analyte. The sensor platform was characterized using cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), scanning electron microscopy (SEM), and atomic force microscopy (AFM). An optimized differential pulse voltammetry (DPV) method was employed for KA detection. The developed sensor demonstrated a detection limit of 0.3 nM and was effective across a concentration range of 1 nM to 500 µM. These findings highlight the potential of this electrochemical sensor as a reliable, rapid, and cost-effective tool for KA detection in various biological samples, offering significant advantages over traditional methods in terms of sensitivity and simplicity. Full article
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Figure 1

Figure 1
<p>(<b>a</b>) DPVs obtained for a carbon-printed platform functionalized with different composite layers, i.e., three layers (black), two layers (purple), and one layer (red), in the presence of 500 µM KA solution prepared in the B–R buffer (pH 7), compared to the unfunctionalized platform in the B–R buffer (blue) and 500 µM KA in the B–R buffer (green). (<b>b</b>) CVs recorded during the electrochemical reduction of GO to rGO for 10 cycles between 0.2 V and −1.5 V. CVs (<b>c</b>) and Nyquist plots of EIS (<b>d</b>) recorded in the presence of 5 mM K<sub>4</sub>[Fe(CN)<sub>6</sub>]/K<sub>3</sub>[Fe(CN)<sub>6</sub>] in 0.1 M KCl for unmodified carbon-based electrodes (black), after pretreatment (orange), composite film-functionalized electrodes (PEI/AuNPs/GO) before GO reduction (blue), and after reduction (purple). Inset: magnified high-frequency region for the EIS spectra.</p>
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<p>Comparative SEM images are presented for: (<b>a</b>) the unmodified carbon-based electrode surface; (<b>b</b>) the carbon electrode surface modified with the PEI/AuNPs/GO composite at different magnifications (scale bars: 5 μm (1); 1 μm (2); 500 nm (3)).</p>
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<p>EDX spectra provide elemental composition data. On the left, the EDX spectra illustrate the elemental profile of the samples, while, on the right, the corresponding elemental distribution maps are shown. (<b>a</b>) The unmodified carbon-based electrode surface; (<b>b</b>) the carbon electrode surface modified with the PEI/AuNPs/GO composite. Scale bar: 500 nm.</p>
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<p>2D (<b>left</b>) and 3D (<b>right</b>) topographic AFM images of the unmodified electrochemical surface (<b>a</b>) and of the surface modified with a composite film (<b>b</b>). Scan size 10 µm.</p>
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<p>(<b>a</b>) Dependence of the oxidation current intensity of KA on the pH values of the electrolytic medium obtained for 75 μM KA in the B–R buffer at different pH values in the range of 2 to 12 (bar chart—oxidation current values are displayed above each column, with error bars representing standard deviation values relative to the mean intensity value for each signal. (<b>b</b>) Variation of the oxidation peak potential of KA 100 μM with the pH values of the electrolyte medium—B–R buffer at different pH values (the tests were performed in triplicates, the corresponding mean is presented, and the error bars represent the standard deviation in relation to the mean corresponding to each pH value). (<b>c</b>) Overlay of DPVs obtained for 100 μM KA in the B–R buffer at pH 7, recorded at different scan rates. (<b>d</b>) Variation of the logarithm of the oxidation peak current with the logarithm of the scan rate for the electrochemical transformation of 200 μM KA, using scan rates ranging from 5 to 200 mV s<sup>−1</sup> (the graph includes the linear equation and error bars). Variation of the oxidation peak current intensity with the scan rate (<b>e</b>) and the square root of the scan rate (<b>f</b>) for the electrochemical transformation of 75 μM KA (the graph includes error bars, estimated as the standard deviation relative to the mean current values obtained from three individual measurements for each tested scan rate).</p>
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<p>(<b>a</b>) Overlay of voltammograms corresponding to different concentrations of KA (1 nM, 10 nM, 100 nM, 1 µM, 10 µM, 25 µM, 100 µM, 200 µM, 400 µM, 500 µM) prepared in 0.1 M PBS buffer, pH 7. The test conducted in the buffer using the optimized sensor is represented in black). (<b>b</b>) Logarithmic dependence of the oxidation peak current intensity on the KA concentration. (<b>c</b>) Calibration curve illustrating the linear dependence of the oxidation current intensity on KA concentration (within the range of 1 nM–100 µM) obtained via DPV (tests were performed in triplicates). (<b>d</b>) Recoveries calculated for the KA signal following a selectivity study conducted in PBS buffer at pH 7 with (TRP)and other metabolites from the kynurenine pathway (bar chart—recovery percentages are displayed above each column, with error bars representing standard deviation values relative to the mean recovery for each signal). (<b>e</b>) Recoveries calculated for the KA signal following intra-assay stability testing. (<b>f</b>) Long-term stability study of the PEI/AuNPs/GO platform. KA signal recovery tested via DPV on days 1, 2, 7, and 14.</p>
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<p>(<b>a</b>) The correlation between KA concentrations in human saliva, measured using DPV and the HPLC-UV control method, analyzed for 10 patients and five controls (n = 15). (<b>b</b>) The Bland–Altman plot evaluating the agreement between the two methods. Each point represents the difference in KA concentrations (nM) measured by DPV and HPLC-UV relative to their mean. The horizontal green line shows a mean bias of −0.254 nM KA, while the dashed purple and blue lines indicate the 95% confidence interval (±2.19 nM), highlighting a strong agreement between the two methods.</p>
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<p>Schematic representation of the main steps in the protocol for developing the electrochemical sensor for KA direct detection (illustration created using the Biorender software (<a href="https://www.biorender.com/" target="_blank">https://www.biorender.com/</a>)).</p>
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13 pages, 1977 KiB  
Article
The Aryl Hydrocarbon Receptor (AhR) Is a Novel Gene Involved in Proper Physiological Functions of Pancreatic β-Cells
by Shuhd Bin Eshaq, Jalal Taneera, Shabana Anjum, Abdul Khader Mohammed, Mohammad H. Semreen, Karem H. Alzoubi, Mohamed Eladl, Yasser Bustanji, Eman Abu-Gharbieh and Waseem El-Huneidi
Cells 2025, 14(1), 57; https://doi.org/10.3390/cells14010057 - 6 Jan 2025
Viewed by 665
Abstract
The Kynurenine pathway is crucial in metabolizing dietary tryptophan into bioactive compounds known as kynurenines, which have been linked to glucose homeostasis. The aryl hydrocarbon receptor (AhR) has recently emerged as the endogenous receptor for the kynurenine metabolite, kynurenic acid (KYNA). However, the [...] Read more.
The Kynurenine pathway is crucial in metabolizing dietary tryptophan into bioactive compounds known as kynurenines, which have been linked to glucose homeostasis. The aryl hydrocarbon receptor (AhR) has recently emerged as the endogenous receptor for the kynurenine metabolite, kynurenic acid (KYNA). However, the specific role of AhR in pancreatic β-cells remains largely unexplored. This study aimed to investigate the expression of AhR in human pancreatic islets using publicly available RNA-sequencing (RNA-seq) databases and to explore its correlations with various metabolic parameters and key β-cell markers. Additionally, functional experiments were conducted in INS-1 cells, a rat β-cell line, to elucidate the role of Ahr in β-cell biology. RNA-seq data analysis confirmed the expression of AHR in human islets, with elevated levels observed in pancreatic islets obtained from diabetic and obese donors compared to non-diabetic or lean donors. Furthermore, AHR expression showed an inverse correlation with the expression of key β-cell functional genes, including insulin, PDX-1, MAFA, KCNJ11, and GCK. Silencing Ahr expression using siRNA in INS-1 cells decreased insulin secretion, insulin content, and glucose uptake efficiency, while cell viability, apoptosis rate, and reactive oxygen species (ROS) production remained unaffected. Moreover, Ahr silencing led to the downregulation of major β-cell regulator genes, Ins1, Ins2, Pdx-1, and Glut2, at both the mRNA and protein levels. In summary, this study provides novel insights into the role of AhR in maintaining proper β-cell function. These findings suggest that AhR could be a potential target for future therapeutic strategies in treating type 2 diabetes (T2D). Full article
(This article belongs to the Special Issue Molecular Mechanisms of Signal Transduction in the Islet Cells)
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<p>Expression analysis of AHR in human pancreatic islets. (<b>A</b>) RNA-seq expression of AHR, KCNJ11, PDX1, INSR, MAFA, GCK, and GLUT1 in human islets obtained from non-diabetic donors (n = 49). (<b>B</b>). AHR expression levels in human islets obtained from diabetic/hyperglycemic donors (n = 25) compared to nondiabetic/normoglycemic islet (n = 49) donors. (<b>C</b>) AHR expression levels in human islets obtained from lean donors (n = 18; BMI below 24) compared to obese donors (n = 19; BMI above 29). (<b>D</b>) AHR expression levels in human islets obtained from male donors (n = 53) compared to female donors (n = 33). Correlation of AHR expression with HbA1c% (n = 66) (<b>E</b>), BMI (n = 87) (<b>F</b>), or age (n = 87) (<b>G</b>). *; <span class="html-italic">p</span> &gt; 0.05, ns; not significant. Bars represent mean ± SEM. Nonparametric Mann–Whitney <span class="html-italic">t</span>-tests were used in (<b>B</b>–<b>D</b>). Nonparametric Spearman’s correlation test was used in (<b>E</b>–<b>G</b>).</p>
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<p>Expression correlations of AHR with key pancreatic β-cell markers. Expression of AHR was correlated with INS (<b>A</b>), PDX1 (<b>B</b>), MAFA (<b>C</b>), KCNJ11 (<b>D</b>), GCK (<b>E</b>), and GLUT1 (<b>F</b>) using nonparametric Spearman’s correlation. (<b>G</b>) Expression levels of AHR in human fat tissue (n = 12), pancreatic islets (n = 12), liver (n = 12), and skeletal muscle tissues (n = 12), obtained from the same donors. (<b>H</b>) Expression levels of AHR in sorted pancreatic cells, ductal, acinar, or PSC as obtained from Islet Gene View (IGV) web tool.</p>
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<p>Silencing of Ahr and its impact on INS-1 cell function. (<b>A</b>) Analysis of mRNA expression of AhR 48 h after siRNA transfection as determined by qPCR in Ahr-silenced or control cells. (<b>B</b>) Confocal images of immunofluorescent staining of AHR protein in INS-1 with or without Ahr silencing. Blue is DAPI nuclear staining and green is AHR protein staining. The overlay of two markers is shown in the merged image. Magnification 60× (n. of experiments = 1). (<b>C</b>) Cell viability assay using MTT test. (<b>D</b>,<b>E</b>) Apoptosis analyzed by flow cytometry analysis using Annexin V-PI staining (<b>D</b>). The left panel denotes a summary of the apoptosis results (<b>E</b>). (<b>F</b>) ROS production measurements determined by luminescence-based analysis. (<b>G</b>) Normalized insulin secretion was stimulated in control or Ahr-silenced cells at 2.8 mM glucose, 16.7 mM glucose, and 2.8 mM glucose with KCL or αKIC. (<b>H</b>) Insulin content measurements relative to the total protein concentration. (<b>I</b>) Glucose uptake efficiency evaluated by flow cytometry. Data were acquired from three independent experiments unless otherwise mentioned. Bars display the mean ± SD. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, *** <span class="html-italic">p</span> &lt; 0.001, ns; not significant.</p>
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<p>Impact of Ahr silencing on key β-cell function genes. (<b>A</b>) mRNA expression of Ins1, Ins2, Glut2, Insrβ, Pdx-1, and Gck in Ahr-silenced cells compared to control cells. Protein expression of (<b>B</b>) Pro/Insulin, (<b>C</b>) PDX-1, (<b>D</b>) GLUT2, (<b>E</b>) GCK, and (<b>F</b>) INSRβ relative to β-actin endogenous protein. Bars indicate mean ± SD fold changes in protein expression from three independent experiments. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, ns; not significant.</p>
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22 pages, 2065 KiB  
Review
Tryptophan Kynurenine Pathway-Based Imaging Agents for Brain Disorders and Oncology—From Bench to Bedside
by Erik Stauff, Wenqi Xu, Heidi H. Kecskemethy, Sigrid A. Langhans, Vinay V. R. Kandula, Lauren W. Averill and Xuyi Yue
Biomolecules 2025, 15(1), 47; https://doi.org/10.3390/biom15010047 - 1 Jan 2025
Viewed by 650
Abstract
Tryptophan (Trp)-based radiotracers have excellent potential for imaging many different types of brain pathology because of their involvement with both the serotonergic and kynurenine (KYN) pathways. However, radiotracers specific to the kynurenine metabolism pathway are limited. In addition, historically Trp-based radiopharmaceuticals were synthesized [...] Read more.
Tryptophan (Trp)-based radiotracers have excellent potential for imaging many different types of brain pathology because of their involvement with both the serotonergic and kynurenine (KYN) pathways. However, radiotracers specific to the kynurenine metabolism pathway are limited. In addition, historically Trp-based radiopharmaceuticals were synthesized with the short-lived isotope carbon-11. A newer generation of Trp-based imaging agents using the longer half-lived and commercially available isotopes, such as fluorine-18 and iodine-124, are being developed. The newly developed amino acid-based tracers have been demonstrated to have favorable radiochemical and imaging characteristics in pre-clinical studies. However, many barriers still exist in the clinical translation of KYN pathway-specific radiotracers. Full article
(This article belongs to the Special Issue Tryptophan-Kynurenine Pathway in Health and Disease)
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<p>Results from literature search and included journal articles.</p>
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<p>Major metabolism pathways: serotonin and kynurenine pathways. TPH, tryptophan hydroxylase; IDO, indoleamine 2,3-dioxygenase; TDO, tryptophan 2,3-dioxygenase; AADC, aromatic amino acid decarboxylase; KFO, kynurenine formylase; MAO A/B, monoamine oxidases A and B; ALDH, aldehyde dehydrogenase; KAT, kynurenine aminotransferase; KMO, kynurenine-3-monooxygenase; KYNU, L-kynurenine hydrolase; HAAO, 3-hydroxyanthranilic acid dioxygenase; NAD<sup>+</sup>, nicotinamide adenine dinucleotide.</p>
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<p>Chemical structures of [<sup>11</sup>C]AMT, 5-[<sup>18</sup>F]F-AMT, 6-[<sup>18</sup>F]F-AMT, and 5-[<sup>124</sup>I]I-AMT. The numbers in [<sup>11</sup>C]AMT denote possible radiolabeling sites on the indole ring.</p>
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<p>Chemical structure of [<sup>11</sup>C]HTP.</p>
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<p>Chemical structure of 5-<sup>18</sup>FEHTP.</p>
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<p>Chemical structures of racemic 4-<sup>18</sup>F-FEHTrp, 6-<sup>18</sup>F-FEHTrp, and 7-<sup>18</sup>F-FEHTrp.</p>
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<p>Chemical structure of [<sup>18</sup>F]-L-FPTP.</p>
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<p>Chemical structure of <sup>18</sup>F-FETrp.</p>
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<p>Chemical structures of racemic [<sup>18</sup>F]2-FPTRP and [<sup>18</sup>F]5-FPTRP.</p>
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<p>Chemical structures of racemic 5-OH-2-[<sup>18</sup>F]FPTRP and 5-OH-2-[<sup>18</sup>F]FETRP.</p>
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<p>Chemical structures of [<sup>18</sup>F]fluorotryptophan with a fluorine-18 directly attached to the indole rings. * Designate as racemic or optically pure amino acids.</p>
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19 pages, 3309 KiB  
Article
The Mediating Role of Gut Microbiota on the Association Between Dietary Quality and Cancer-Related Fatigue Among Breast Cancer Patients: A Cross-Sectional Study
by Jianyun He, Lan Cheng, Xinxin Cheng, Yuting Wang, Xiaoxia Lin and Shufang Xia
Nutrients 2024, 16(24), 4371; https://doi.org/10.3390/nu16244371 - 18 Dec 2024
Viewed by 699
Abstract
Objectives: Cancer-related fatigue (CRF) is highly prevalent in patients with breast cancer, resulting in undesirable outcomes and even reduced survival rates. This cross-sectional study investigated the relationship between dietary quality and CRF in patients with breast cancer, and the potential role of gut [...] Read more.
Objectives: Cancer-related fatigue (CRF) is highly prevalent in patients with breast cancer, resulting in undesirable outcomes and even reduced survival rates. This cross-sectional study investigated the relationship between dietary quality and CRF in patients with breast cancer, and the potential role of gut microbiota (GM) in this association. Methods: Dietary intake and CRF were evaluated in 342 patients, with 64 fecal samples collected for 16sRNA sequencing and 106 plasma samples for tryptophan (TRP) metabolite determination. Results: A total of 149 (43.6%) patients experienced CRF, which was significantly associated with low intakes of protein, vitamin A, vitamin E, dietary fiber, phosphorus, magnesium, potassium, iron, and copper (p < 0.05), and a remarkably low Chinese Healthy Eating Index (CHEI) score (p < 0.05). CRF patients had decreased GM diversity, an unhealthier GM composition, lower TRP concentrations, and a higher kynurenine (KYN)/TRP ratio (p < 0.05). Mediation analyses revealed that both the Sobs index (ACME = −0.0005; 95% CI −0.0051, −0.0001; p = 0.034) and the Chao index (ACME = −0.0005; 95% CI −0.0050, −0.0001; p = 0.033) were significant mediators of the correlation between total CHEI score and CRF. Conclusions: The presence of CRF in patients with breast cancer might be correlated with inadequate nutrient intake and low dietary quality via GM-dependent pathways. Full article
(This article belongs to the Section Nutrition and Public Health)
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<p>Gut microbiota structure in breast cancer patients with NCRF and CRF. (<b>A</b>) Rarefaction curves. (<b>B</b>) Venn diagram displaying the shared number of operational taxonomic units (OTUs). (<b>C</b>) Chao index, Shannon index, Sobs index, and Simpson index. The Wilcoxon rank-sum test was used. (<b>D</b>) Weighted UniFrac distance-based principal coordinate analysis (PCoA). The statistical significance was assessed with analysis of similarities (ANOSIM). CRF, cancer-related fatigue (<span class="html-italic">n</span> = 25); NCRF, non-cancer-related fatigue (<span class="html-italic">n</span> = 39). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Gut microbiota structure in breast cancer patients with NCRF and CRF. (<b>A</b>) Rarefaction curves. (<b>B</b>) Venn diagram displaying the shared number of operational taxonomic units (OTUs). (<b>C</b>) Chao index, Shannon index, Sobs index, and Simpson index. The Wilcoxon rank-sum test was used. (<b>D</b>) Weighted UniFrac distance-based principal coordinate analysis (PCoA). The statistical significance was assessed with analysis of similarities (ANOSIM). CRF, cancer-related fatigue (<span class="html-italic">n</span> = 25); NCRF, non-cancer-related fatigue (<span class="html-italic">n</span> = 39). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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<p>Gut microbiota composition in breast cancer patients with NCRF and CRF. The community structures at the phylum (<b>A</b>) and genus (<b>B</b>) levels. CRF, cancer-related fatigue (<span class="html-italic">n</span> = 25); NCRF, non-cancer-related fatigue (<span class="html-italic">n</span> = 39).</p>
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<p>Differentiated microbes between breast cancer patients with CRF and NCRF. Differentiated microbes at the phylum (<b>A</b>) and genus (<b>B</b>) levels. (<b>C</b>) Linear discriminatory analysis effect size (LEfSe) was used to distinguish the differential microbes between the CRF and NCRF patients. (<b>D</b>) Linear discriminant analysis (LDA) was performed, and only the microbiota with LDA scores of &gt;4 are shown. CRF, cancer-related fatigue (<span class="html-italic">n</span> = 25); NCRF, non-cancer-related fatigue (<span class="html-italic">n</span> = 39). * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01.</p>
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15 pages, 1533 KiB  
Article
Modulation of Brain Kynurenic Acid by N-Acetylcysteine Prevents Cognitive Impairment and Muscular Weakness Induced by Cisplatin in Female Rats
by Teminijesu Dorcas Aremu, Daniela Ramírez Ortega, Tonali Blanco Ayala, Dinora Fabiola González Esquivel, Benjamín Pineda, Gonzalo Pérez de la Cruz, Alelí Salazar, Itamar Flores, Karla F. Meza-Sosa, Laura Sánchez Chapul, Edgar Rangel-López, Saúl Gómez-Manzo, Adrián Márquez Navarro, Gabriel Roldán Roldán and Verónica Pérez de la Cruz
Cells 2024, 13(23), 1989; https://doi.org/10.3390/cells13231989 - 2 Dec 2024
Viewed by 915
Abstract
Cisplatin (CIS) is a potent chemotherapeutic agent primarily used to treat hematologic malignancies and solid tumors, including lymphomas, sarcomas, and some carcinomas. Patients receiving this treatment for tumors outside the nervous system develop cognitive impairment. Alterations in the kynurenine pathway (KP) following CIS [...] Read more.
Cisplatin (CIS) is a potent chemotherapeutic agent primarily used to treat hematologic malignancies and solid tumors, including lymphomas, sarcomas, and some carcinomas. Patients receiving this treatment for tumors outside the nervous system develop cognitive impairment. Alterations in the kynurenine pathway (KP) following CIS treatment suggest that certain KP metabolites may cross the blood–brain barrier, leading to increased production of the neuromodulator kynurenic acid (KYNA), which is associated with cognitive impairment. This study aimed to evaluate the effects of modulating brain KYNA levels by the administration of N-acetylcysteine (NAC), an inhibitor of kynurenine aminotransferase II (KATII), an enzyme responsible for KYNA biosynthesis on the cognitive and neuromuscular deficits induced by CIS. Female Wistar rats were divided into four groups: control, NAC (300 mg/day/8 days), CIS (3 mg/kg i.p/5 days), and NAC + CIS (both treatments co-administered in parallel). Seven days after the last CIS administration, cognitive performance, muscle strength, brain KYNA levels, KATII activity, and brain tissue redox profile (lipid peroxidation and oxidized/reduced glutathione (GSH/GSSG) ratio) were assessed. CIS did not affect short-term memory but induced long-term memory deficits and reduced muscle strength, effects which were prevented by NAC co-administration. CIS decreased the GSH/GSSG ratio and the number of cells in the brain cortex while it increased lipid peroxidation, KYNA levels, and marginal KATII activity. All these effects were attenuated by the co-administration of NAC. These findings suggest that NAC mitigates the side effects of CIS, such as chemo-brain and muscle weakness, by improving the redox imbalance and modulating KYNA levels by limiting its non-enzymatic production by reactive oxygen species (ROS). Full article
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<p>Changes in body weight of rats administered with CIS and NAC. The body weight (g) of rats was monitored from the beginning of CIS administration until one day before the start of cognitive testing. The experimental groups included control (0.9% saline), CIS (3 mg/kg/5 days), NAC (300 mg/day/8 days), and NAC + CIS (NAC for 8 days, with concurrent CIS administration from days 3 to 7). Data are represented as the mean ± SEM of 10 animals per group. * <span class="html-italic">p</span> &lt; 0.01 vs. the initial body weight within each group, based on the Friedman test with Wilcoxon signed-rank test for multiple pairwise comparisons.</p>
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<p>Effect of N-acetylcysteine (NAC) administration on short-term memory (STM) and long-term memory (LTM) impairments induced by sub-chronic cisplatin (CIS) administration. Cognitive performance was assessed using the novel object recognition test (B: a novel object in STM; C: a novel object in LTM) 7 days after the last CIS administration. The recognition index was calculated to evaluate STM and LTM using 9–10 animals per group. Data are shown as the mean ± SEM, based on the Kruskal–Wallis test followed by Dunn’s test.</p>
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<p>Effect of N-acetylcysteine (NAC) administration on muscle performance induced by sub-chronic administration of cisplatin (CIS). Grip strength was calculated as the average time of three different trials separated by 1 min for each animal per group (n = 10). Data are represented as the mean ± SEM, based on the Kruskal–Wallis test followed by Dunn’s test.</p>
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<p>Effect of simultaneous administration of NAC and CIS on KATII activity and KYNA levels. The brain cortex was analyzed to evaluate KATII activity (<b>A</b>) and KYNA levels (<b>B</b>). Data represented as the mean ± SEM of 7 animals per group. Based on the Kruskal–Wallis test, with Dunn’s test for multiple pairwise comparisons.</p>
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<p>Effect of co-administration of CIS and N-acetylcysteine (NAC) on lipid peroxidation (<b>A</b>) and the GSH/GSSG ratio (<b>B</b>) induced by sub-chronic administration of cisplatin. The brain cortex was used to evaluate the redox environment. Data are represented by the mean ± SEM of 7 animals per group. Based on the Kruskal–Wallis test, followed by Dunn’s tests for multiple pairwise comparisons (in brown when comparing only vs. control).</p>
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<p>Correlation between KYNA levels, KATII activity, the GSH/GSSG ratio, long-term memory, and muscle strength. The matrix in the lower left quadrant contains the scatter plot of all parameters, and the upper right quadrant contains Spearman’s coefficient (r) and is associated with a <span class="html-italic">p</span>-value (n = 7, per group).</p>
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<p>Effect of N-acetylcysteine and cisplatin co-administration on the number of astrocytes and neurons in the cerebral cortex. (<b>A</b>) Representative images show immunofluorescence detection of neurons (NeuN, red), astrocytes (GFAP, green), and nuclei (DAPI, blue) within the cerebral cortex across the four experimental groups. Images were captured at 20× magnification.</p>
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45 pages, 1847 KiB  
Review
Redefining Roles: A Paradigm Shift in Tryptophan–Kynurenine Metabolism for Innovative Clinical Applications
by Masaru Tanaka, Ágnes Szabó and László Vécsei
Int. J. Mol. Sci. 2024, 25(23), 12767; https://doi.org/10.3390/ijms252312767 - 27 Nov 2024
Cited by 1 | Viewed by 3534
Abstract
The tryptophan–kynurenine (KYN) pathway has long been recognized for its essential role in generating metabolites that influence various physiological processes. Traditionally, these metabolites have been categorized into distinct, often opposing groups, such as pro-oxidant versus antioxidant, excitotoxic/neurotoxic versus neuroprotective. This dichotomous framework has [...] Read more.
The tryptophan–kynurenine (KYN) pathway has long been recognized for its essential role in generating metabolites that influence various physiological processes. Traditionally, these metabolites have been categorized into distinct, often opposing groups, such as pro-oxidant versus antioxidant, excitotoxic/neurotoxic versus neuroprotective. This dichotomous framework has shaped much of the research on conditions like neurodegenerative and neuropsychiatric disorders, as well as cancer, where metabolic imbalances are a key feature. The effects are significantly influenced by various factors, including the concentration of metabolites and the particular cellular milieu in which they are generated. A molecule that acts as neuroprotective at low concentrations may exhibit neurotoxic effects at elevated levels. The oxidative equilibrium of the surrounding environment can alter the function of KYN from an antioxidant to a pro-oxidant. This narrative review offers a comprehensive examination and analysis of the contemporary understanding of KYN metabolites, emphasizing their multifaceted biological functions and their relevance in numerous physiological and pathological processes. This underscores the pressing necessity for a paradigm shift in the comprehension of KYN metabolism. Understanding the context-dependent roles of KYN metabolites is vital for novel therapies in conditions like Alzheimer’s disease, multiple sclerosis, and cancer. Comprehensive pathway modulation, including balancing inflammatory signals and enzyme regulation, offers promising avenues for targeted, effective treatments. Full article
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<p>Timeline of tryptophan (Trp)–kynurenine (KYN) metabolic pathway. This timeline highlights key discoveries in the Trp-KYN pathway, beginning with the identification of kynurenate in 1853 by Justus von Liebig, preceding Trp’s isolation by nearly 50 years [<a href="#B18-ijms-25-12767" class="html-bibr">18</a>]. In 1901, Frederick Hopkins identified Trp as an essential amino acid [<a href="#B19-ijms-25-12767" class="html-bibr">19</a>,<a href="#B20-ijms-25-12767" class="html-bibr">20</a>]. In 1904, Alexander Ellinger first identified Trp as a source of kynurenic acid (KYNA) [<a href="#B21-ijms-25-12767" class="html-bibr">21</a>]. In 1925, Matsuoka and Yoshimatsu detected KYNA as a Trp metabolite, and in the 1930s [<a href="#B22-ijms-25-12767" class="html-bibr">22</a>], Kotake and colleague established KYN as an intermediate and kynurenate precursor [<a href="#B23-ijms-25-12767" class="html-bibr">23</a>,<a href="#B24-ijms-25-12767" class="html-bibr">24</a>]. Finally, in 1949, Heidelberger and colleagues confirmed the conversion of radiolabeled Trp to kynurenate [<a href="#B25-ijms-25-12767" class="html-bibr">25</a>]. The enzymes that convert KYN to nicotinamide adenine dinucleotide (NAD) were characterized by Saito in 1957 [<a href="#B27-ijms-25-12767" class="html-bibr">27</a>], Soda in 1979 [<a href="#B28-ijms-25-12767" class="html-bibr">28</a>], Long in 1954 [<a href="#B29-ijms-25-12767" class="html-bibr">29</a>], and Nishizuka in 1963 [<a href="#B30-ijms-25-12767" class="html-bibr">30</a>]. 3-HAA: 3-hydroxyanthranilic acid: KYNA: kynurenic acid; KYN: kynurenine; 3-HK: 3-hydroxykinurenine; NAD: nicotinamide adenine dinucleotide; QUIN: quinolinic acid; Trp: tryptophan.</p>
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<p>The tryptophan metabolic pathways. Tryptophan (Trp) is catabolized via the serotonin pathway (over 2% of L-Trp), the kynurenine (KYN) pathway (more than 90% of L-Trp), and the gut microbial indole pyruvate pathway (over 5% of L-Trp). (<b>a</b>) In the KYN pathway, L-Trp is converted into several key metabolites, including N-formyl-L-kynurenine, KYN, kynurenic acid, anthranilic acid, 3-hydroxykynurenine, xanthurenic acid, 3-hydroxyanthranilic acid, quinolinic acid, picolinic acid, and nicotinamide adenine dinucleotide (NAD<sup>+</sup>). These conversions occur via the action of various enzymes: tryptophan 2,3-dioxygenase (TDO), indoleamine 2,3-dioxygenases (IDOs), kynurenine formamidase (KFA), kynurenine 3-monooxygenase (KMO), kynurenine aminotransferases (KATs), kynureninase (KYNU), 3-hydroxyanthranilate oxidase (3-HAO), quinolinate phosphoribosyl transferase (QPRT), nicotinamide mononucleotide adenylyltransferase (NMNAT), NAD synthetase, amino-β-carboxy-muconate-semialdehyde-decarboxylase (ACMSD), and 2-aminomuconic-6-semialdehyde dehydrogenase (AMSD). KYNA is also further metabolized by the gut microbiome, resulting in quinaldic acid and 8-hydroxyquinaldic acid, which may be dehydroxylated from xanthurenic acid [<a href="#B5-ijms-25-12767" class="html-bibr">5</a>,<a href="#B8-ijms-25-12767" class="html-bibr">8</a>,<a href="#B62-ijms-25-12767" class="html-bibr">62</a>]. Notably, the gut microbiota contributes to the KYN pathway [<a href="#B70-ijms-25-12767" class="html-bibr">70</a>]. (<b>b</b>) In the gut microbial indole pyruvate pathway, L-Trp metabolism occurs via four distinct pathways: the indoxyl sulfate pathway, the indole-3-acetamide (IAM) pathway, the tryptamine pathway, and the indole-3-propionic acid (IPA) pathway. In the indoxyl sulfate (INS) pathway, the rate-limiting enzyme is tryptophanase (TNA), which requires pyridoxal phosphate. It converts Trp to indole, which passes through the gut lining before being hydroxylated into 3-hydroxyindole (indoxyl), which is then converted to INS in the liver by p450 cytochrome and sulfonation [<a href="#B71-ijms-25-12767" class="html-bibr">71</a>]. The IAM pathway starts with tryptophan-2-monooxygenase (TMO), which converts Trp to IAM, which is then converted to indole-3-acetic acid (IAA) by indole-3-acetamide hydrolase (IaaH). IAA can then be metabolized into indole-3-aldehyde or decarboxylated into 3-methylindole (skatole) [<a href="#B72-ijms-25-12767" class="html-bibr">72</a>,<a href="#B73-ijms-25-12767" class="html-bibr">73</a>]. In the tryptamine pathway, tryptophan decarboxylase (TrD) converts Trp to tryptamine via amino acid decarboxylase (AAD), which is then converted into indole-3-acetaldehyde (IAAld). IAAld can be converted into IAA or reversibly into indole-3-ethanol (tryptophol) [<a href="#B74-ijms-25-12767" class="html-bibr">74</a>,<a href="#B75-ijms-25-12767" class="html-bibr">75</a>]. Finally, in the IPA pathway, aromatic amino acid aminotransferase (ArAT) converts Trp to indole-3-pyruvic acid, which yields indole-3-lactic acid by phenyllactate dehydrogenase (fldH), 3-indole acrylic acid by phenyllactate dehydratase (fldBC), and, eventually, indole 3-propionic acid by acyl-coenzyme A dehydrogenase (acdA) [<a href="#B75-ijms-25-12767" class="html-bibr">75</a>,<a href="#B76-ijms-25-12767" class="html-bibr">76</a>,<a href="#B77-ijms-25-12767" class="html-bibr">77</a>]. Black arrows: host pathway; white arrows: gut microbial pathway; yellow arrows: both host and microbial pathways; dashed arrow: intermediate metabolites catalyzed by three enzymes.</p>
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<p>Integration of body-brain axes via the kynurenine (KYN) pathway. The KYN pathway is an important integrative hub that connects peripheral systems to the central nervous system via multiple body-brain axes. These include the gut-brain axis, where gut microbes control metabolites of KYN that affect mood and neuroinflammation; the muscle-brain axis, where kynurenine aminotransferases (KATs) upregulated by exercise transform neurotoxic KYN into neuroprotective kynurenic acid; the cardiovascular-brain axis, where inflammation and vascular health modulate the neuroactive effects of KYN; the renal-brain axis, where kidney function influences the clearance of KYN and systemic inflammation; the endocrine-brain axis, where hormonal regulation affects the production of KYN; and the liver-brain and immune-brain axes, where immunological responses and hepatic metabolism influence neuroinflammatory outcomes. These axes collectively highlight the part the KYN pathway plays in the etiology of mental health conditions, neurodegenerative diseases, and possible treatment approaches.</p>
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24 pages, 11090 KiB  
Article
Longitudinal Metabolomics Reveals Metabolic Dysregulation Dynamics in Patients with Severe COVID-19
by Ryo Uchimido, Kenjiro Kami, Hiroyuki Yamamoto, Ryo Yokoe, Issei Tsuchiya, Yoko Nukui, Yuki Goto, Mariko Hanafusa, Takeo Fujiwara and Kenji Wakabayashi
Metabolites 2024, 14(12), 656; https://doi.org/10.3390/metabo14120656 - 25 Nov 2024
Viewed by 1174
Abstract
Background/Objective: A dysregulated metabolism has been studied as a key aspect of the COVID-19 pathophysiology, but its longitudinal progression in severe cases remains unclear. In this study, we aimed to investigate metabolic dysregulation over time in patients with severe COVID-19 requiring mechanical ventilation [...] Read more.
Background/Objective: A dysregulated metabolism has been studied as a key aspect of the COVID-19 pathophysiology, but its longitudinal progression in severe cases remains unclear. In this study, we aimed to investigate metabolic dysregulation over time in patients with severe COVID-19 requiring mechanical ventilation (MV). Methods: In this single-center, prospective, observational study, we obtained 236 serum samples from 118 adult patients on MV in an ICU. The metabolite measurements were performed using capillary electrophoresis Fourier transform mass spectrometry, and we categorized the sampling time points into three time zones to align them with the disease progression: time zone 1 (T1) (the hyperacute phase, days 1–3 post-MV initiation), T2 (the acute phase, days 4–14), and T3 (the chronic phase, days 15–30). Using volcano plots and enrichment pathway analyses, we identified the differential metabolites (DMs) and enriched pathways (EPs) between the survivors and non-survivors for each time zone. The DMs and EPs were further grouped into early-stage, late-stage, and consistent groups based on the time zones in which they were detected. Results: With the 566 annotated metabolites, we identified 38 DMs and 17 EPs as the early-stage group, which indicated enhanced energy production in glucose, amino acid, and fatty acid metabolisms in non-survivors. As the late-stage group, 84 DMs and 10 EPs showed upregulated sphingolipid, taurine, and tryptophan–kynurenine metabolisms with downregulated steroid hormone synthesis in non-survivors. Three DMs and 23 EPs in the consistent group showed more pronounced dysregulation in the dopamine and arachidonic acid metabolisms across all three time zones in non-survivors. Conclusions: This study elucidated the temporal differences in metabolic dysregulation between survivors and non-survivors of severe COVID-19, offering insights into its longitudinal progression and disease mechanisms. Full article
(This article belongs to the Section Endocrinology and Clinical Metabolic Research)
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<p>Workflow of the metabolomics analysis. N represents the number of patients, and n represents the number of samples. PLS-ROG: partial least square with ranking of groups; T1: time zone 1; T2: time zone 2; T3: time zone 3.</p>
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<p>Partial least squares with rank order of groups (PLS−ROG) analysis revealed the association between the metabolic profiles and time−dependent subclasses. (<b>a</b>) PLS−ROG analysis illustrating the distribution of the first and second PLS−ROG scores for the metabolite levels as the explanatory variables in the model, with the coloring based on the ICU outcomes. (<b>b</b>) PLS−ROG analysis demonstrating the distribution of the first and second PLS−ROG scores, with the colors representing the time−dependent subclasses. (<b>c</b>,<b>d</b>) Box plots displaying the first and second PLS−ROG scores across the different time−dependent subclasses, respectively. (<b>e</b>) Dot plot with arrows showing the trajectories of the mean metabolic profiles with each time−dependent subclass.</p>
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<p>Change in differences in metabolic dysregulation between survivors and non−survivors over time. (<b>a</b>) Three volcano plots displaying significantly differential metabolites (DMs) between survivors and non−survivors with the red color at each time zone, wherein each dot represents a metabolite. (<b>b</b>) Bar charts showing the number of DMs at each time zone: 17 in time zone 1 (T1), 74 in time zone 2 (T2), and 93 in time zone 3 (T3). (<b>c</b>) Venn diagram illustrating the distribution of DMs identified across different time zone combinations: only in T1; in both T1 and T2; in both T1 and T3; only in T2; in both T2 and T3; only in T3; and in all three time zones (T1, T2, and T3). (<b>d</b>) Bar plots presenting the number of DMs across the different time zone combinations, categorized into early−stage, late−stage, and consistent DMs. The 38 early−stage DMs were found either only in T1 (n = 6), in both T1 and T2 (n = 2), or only in T2 (n = 30); 84 late−stage DMs were identified either only in T2 (n = 38) or in both T2 and T3 (n = 46); and four consistent DMs were detected across all three time zones: T1, T2, and T3 (n = 4).</p>
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<p>Heatmaps depicting the log2 fold changes (log2FCs) in the metabolite values when comparing non−survivors to survivors for (<b>a</b>) early−stage DMs (n = 38), (<b>b</b>) late−stage DMs (n = 84), and (<b>c</b>) consistent DMs (n = 4).</p>
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<p>Time−series box plots showing the longitudinal changes in the scaled values of the early−stage differential metabolites and the temporal variation in the significant differences between the survivors and non-survivors across all three time zones. (<b>a</b>) The γ−glutamyl dipeptides γ−Glu−Asn, γ−Glu−Gly, and γ−Glu−Glu. (<b>b</b>) Metabolites related to nucleic acid metabolism, such as 3-methylcytidine, orotidine, and succinyl adenosine. (<b>c</b>) FA (24:5) and FA (17:3) involved in lipid metabolism. All <span class="html-italic">p</span>−values were adjusted using the Benjamini−Hochberg method. Underlined numbers met both criteria for differential metabolites: (1) a BH−adjusted <span class="html-italic">p</span>−value of &lt;0.05 and (2) an absolute log2 fold change of &gt;1.</p>
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<p>Time−series box plots showing the longitudinal changes in the scaled values of the late−stage differential metabolites and the temporal variation in the significant differences between the survivors and non−survivors across all three time zones. (<b>a</b>) Metabolites from the kynurenine pathway, including kynurenine, kynurenic acid, anthranilic acid, 3−hydroxy kynurenine, 3−hydroxy anthranilic acid, quinolinic acid, and picolinic acid. (<b>b</b>) Bile acid metabolism metabolites, such as deoxycholic acid, taurine, glycodeoxycholic acid, and isochenodeoxycholic acid. (<b>c</b>) Hormones, including serotonin, testosterone, and corticosterone. All <span class="html-italic">p</span>−values were adjusted using the Benjamini−Hochberg method. Underlined numbers met both criteria for differential metabolites: (1) a BH−adjusted <span class="html-italic">p</span>−value of &lt;0.05 and (2) an absolute log2 fold change of &gt;1.</p>
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<p>Time−series box plots showing the longitudinal changes in the scaled values of the consistent differential metabolites and the temporal variation in the significant differences between the survivors and non−survivors across all three time zones. The plots show homovanillic acid, <span class="html-italic">N</span>′−formyl kynurenine, and thromboxane B2. All <span class="html-italic">p</span>−values were adjusted using the Benjamini−Hochberg method. Underlined numbers met both criteria for differential metabolites: (1) a BH−adjusted <span class="html-italic">p</span>−value of &lt;0.05 and (2) an absolute log2 fold change of &gt;1.</p>
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<p>Linear mixed models displaying the <span class="html-italic">p</span>−values of the regression coefficients for the time zones, ICU outcomes (survival or not), and interaction terms between the time zones and ICU outcomes. (<b>a</b>) Two early−stage differential metabolites with significant <span class="html-italic">p</span>−values for the interaction term. (<b>b</b>) The top five metabolites with significant <span class="html-italic">p</span>-values for the interaction term among the late−stage differential metabolites. All <span class="html-italic">p</span>−values were adjusted using the Benjamini–Hochberg method.</p>
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<p>Correlation heatmap depicting the Spearman’s correlations between the differential metabolites and clinical laboratory data. All <span class="html-italic">p</span>−values were adjusted using the Benjamini−Hochberg method. Significance levels are indicated as follows: *** <span class="html-italic">p</span> &lt; 0.001, ** <span class="html-italic">p</span>  &lt; 0.01, and * <span class="html-italic">p</span>  &lt; 0.05.</p>
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<p>The prognostic abilities of homovanillic acid, N′-formylkynurenine, and thromboxane B2 demonstrated by the areas under the curves (AUCs) of their receiver operating characteristic (ROC) curves across all three time zones: (<b>a</b>) homovanillic acid AUCs: 0.87, 0.90, and 0.89; (<b>b</b>) N′-formylkynurenine AUCs: 0.84, 0.83, and 0.92; and (<b>c</b>) thromboxane B2 AUCs: 0.70, 0.77, and 0.64. (<b>d</b>) The logistic regression model, which incorporated these three metabolites along with the age and sex, showed AUCs of 0.89, 0.95, and 0.87 for time zones 1, 2, and 3, respectively.</p>
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<p>Enriched pathway analysis identified metabolic pathways enriched between survivors and non-survivors in each time zone. (<b>a</b>) Bar charts showing the number of enriched pathways (EPs) in each time zone: 30 in time zone 1 (T1), 44 in time zone 2 (T2), and 34 in time zone 3 (T3). (<b>b</b>) Venn diagram illustrating the distribution of EPs identified in the different time zone combinations: only in T1; in both T1 and T2; in both T1 and T3; only in T2; in both T2 and T3; only in T3; and in all three time zones (T1, T2, and T3). (<b>c</b>) Bar plots presenting the numbers of EPs across the different time zone combinations, categorized into early-stage, late-stage, and consistent EPs. The 17 early-stage EPs were found only in T1 (n = 3), in both T1 and T2 (n = 3), or only in T2 (n = 11); the 10 late-stage EPs were identified only in T2 (n = 7) or in both T2 and T3 (n = 3); and the 23 consistent EPs were detected across all three time zones: T1, T2, and T3 (n = 23).</p>
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<p>Enrichment ratios and false discovery rates of enriched pathways in early-stage, late-stage, and consistent categories. This figure was generated using MetaboAnalyst 6.0 (<a href="http://www.metaboanalyst.ca" target="_blank">www.metaboanalyst.ca</a>, accessed on 20 July 2024). Enrichment ratios were calculated as the number of observed metabolites divided by the number of expected metabolites within a specific metabolic pathway. The size of each circle represents the enrichment ratio, and the color indicates the false discovery rate.</p>
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22 pages, 1348 KiB  
Review
Galantamine-Memantine Combination in the Treatment of Parkinson’s Disease Dementia
by Emma D. Frost, Swanny X. Shi, Vishnu V. Byroju, Jamir Pitton Rissardo, Jack Donlon, Nicholas Vigilante, Briana P. Murray, Ian M. Walker, Andrew McGarry, Thomas N. Ferraro, Khalid A. Hanafy, Valentina Echeverria, Ludmil Mitrev, Mitchel A. Kling, Balaji Krishnaiah, David B. Lovejoy, Shafiqur Rahman, Trevor W. Stone and Maju Mathew Koola
Brain Sci. 2024, 14(12), 1163; https://doi.org/10.3390/brainsci14121163 - 21 Nov 2024
Viewed by 1531
Abstract
Parkinson’s disease (PD) is a progressive neurodegenerative disorder that affects over 1% of population over age 60. It is defined by motor and nonmotor symptoms including a spectrum of cognitive impairments known as Parkinson’s disease dementia (PDD). Currently, the only US Food and [...] Read more.
Parkinson’s disease (PD) is a progressive neurodegenerative disorder that affects over 1% of population over age 60. It is defined by motor and nonmotor symptoms including a spectrum of cognitive impairments known as Parkinson’s disease dementia (PDD). Currently, the only US Food and Drug Administration-approved treatment for PDD is rivastigmine, which inhibits acetylcholinesterase and butyrylcholinesterase increasing the level of acetylcholine in the brain. Due to its limited efficacy and side effect profile, rivastigmine is often not prescribed, leaving patients with no treatment options. PD has several derangements in neurotransmitter pathways (dopaminergic neurons in the nigrostriatal pathway, kynurenine pathway (KP), acetylcholine, α7 nicotinic receptor, and N-methyl-D-aspartate (NMDA) receptors) and rivastigmine is only partially effective as it only targets one pathway. Kynurenic acid (KYNA), a metabolite of tryptophan metabolism, affects the pathophysiology of PDD in multiple ways. Both galantamine (α7 nicotinic receptor) and memantine (antagonist of the NMDA subtype of the glutamate receptor) are KYNA modulators. When used in combination, they target multiple pathways. While randomized controlled trials (RCTs) with each drug alone for PD have failed, the combination of galantamine and memantine has demonstrated a synergistic effect on cognitive enhancement in animal models. It has therapeutic potential that has not been adequately assessed, warranting future randomized controlled trials. In this review, we summarize the KYNA-centric model for PD pathophysiology and discuss how this treatment combination is promising in improving cognitive function in patients with PDD through its action on KYNA. Full article
(This article belongs to the Section Neuropharmacology and Neuropathology)
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<p>Kynurenine pathway. An abbreviated depiction of the kynurenine pathway showing the major steps.</p>
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<p>Overview of the kynurenine pathway in the brain and its effects. Depiction of the differential expression of the KP in cells of the central nervous system. Astrocytes lack the full complement of KP enzymes, hence KP activation in astrocytes terminates in the production of neuroprotective KYNA. However, as microglia fully express KP enzymes, KP activation in microglia can result in the production of neurotoxic metabolites 3-HK and QUIN. KP = Kynurenine Pathway; TRP = Tryptophan; KYNA = Kynurenic Acid; IDO = Indoleamine 2,3-dioxygenase; TDO = Tryptophan-2,3-dioxygenase; QUIN = Quinolinic Acid; 3-HAA = 3 Hydroxyanthranilic Acid; 3-HK = 3-hydroxykynurenine; KMO = Kynurenin-3-monooxygenase; KYN = Kynurenine.</p>
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<p>Kynurenine pathway-centric pathophysiology model. Depiction of some of the receptors, pathways, and processes affected by increased levels of major kynurenine pathway metabolites KYN, KYNA, 3-HK, and QUIN after pathway activation. AhR = aryl hydrocarbon receptor; α7nAChR = Alpha7 nicotinic receptor; BCL-2 = B-cell Lymphoma 2; GABA = γ-aminobutyric acid; KYN = Kynurenine; KYNA = Kynurenic Acid; NMDA = N-methyl-D-aspartate; QUIN = Quinolinic Acid; 3-HK = 3-hydroxykynurenine. ↑, increased process; ↓, decreased process.</p>
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<p>Magic Bullet Versus Shotgun Approach. The magic bullet approach has long been thought to be the answer to treating complex medical conditions. Pharmaceutical companies hoped that they would be able to develop a single drug to treat many conditions. However, this has failed countless times. We argue that the shotgun approach is more effective. Using multiple drugs (shotgun approach) to target multiple pathways implicated in a disease is likely to a more effective treatment approach [<a href="#B225-brainsci-14-01163" class="html-bibr">225</a>].</p>
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17 pages, 5080 KiB  
Article
Tryptophan Metabolites in the Progression of Liver Diseases
by Maria Reshetova, Pavel Markin, Svetlana Appolonova, Ismail Yunusov, Oksana Zolnikova, Elena Bueverova, Natiya Dzhakhaya, Maria Zharkova, Elena Poluektova, Roman Maslennikov and Vladimir Ivashkin
Biomolecules 2024, 14(11), 1449; https://doi.org/10.3390/biom14111449 - 15 Nov 2024
Viewed by 1052
Abstract
The aim of this study was to investigate the levels of various tryptophan metabolites in patients with alcoholic liver disease (ALD) and metabolic-associated fatty liver disease (MAFLD) at different stages of the disease. The present study included 44 patients diagnosed with MAFLD, 40 [...] Read more.
The aim of this study was to investigate the levels of various tryptophan metabolites in patients with alcoholic liver disease (ALD) and metabolic-associated fatty liver disease (MAFLD) at different stages of the disease. The present study included 44 patients diagnosed with MAFLD, 40 patients diagnosed with ALD, and 14 healthy individuals in the control group. The levels of tryptophan and its 16 metabolites (3-OH anthranilic acid, 5-hydroxytryptophan, 5-methoxytryptamine, 6-hydroxymelatonin, indole-3-acetic acid, indole-3-butyric, indole-3-carboxaldehyde, indole-3-lactic acid, indole-3-propionic acid, kynurenic acid, kynurenine, melatonin, quinolinic acid, serotonin, tryptamine, and xanthurenic acid) in the serum were determined via high-performance liquid chromatography and tandem mass spectrometry. In patients with cirrhosis resulting from MAFLD and ALD, there are significant divergent changes in the serotonin and kynurenine pathways of tryptophan catabolism as the disease progresses. All patients with cirrhosis showed a decrease in serotonin levels (MAFLDp = 0.038; ALDp < 0.001) and an increase in kynurenine levels (MAFLDp = 0.032; ALDp = 0.010). A negative correlation has been established between serotonin levels and the FIB-4 index (p < 0.001). The decrease in serotonin pathway metabolites was associated with manifestations of portal hypertension (p = 0.026), the development of hepatocellular insufficiency (p = 0.008) (hypoalbuminemia; hypocoagulation), and jaundice (p < 0.001), while changes in the kynurenine pathway metabolite xanthurenic acid were associated with the development of hepatic encephalopathy (p = 0.044). Depending on the etiological factors of cirrhosis, disturbances in the metabolic profile may be involved in various pathogenetic pathways. Full article
(This article belongs to the Section Molecular Medicine)
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<p>The main pathways of tryptophan catabolism in the human body. Kynurenine pathway in host immune cells and liver. Indole pyruvate pathway performed by gut microbiota. Serotonin pathway performed by enterochromaffin cells. *—metabolites whose levels were statistically highly correlated in our study with the etiology of the disease, the type of liver damage, and clinical manifestations of the disease.</p>
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<p>Tryptophan metabolites’ correlation analysis depending on laboratory test for MAFLD.</p>
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<p>Tryptophan metabolites’ correlation analysis depending on laboratory test for ALD.</p>
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<p>Metabolite levels in the group of patients with cirrhosis of various etiologies (MAFLD and ALD) with and without ascites. (<b>a</b>) Level of 5-hydroxytryptophan; (<b>b</b>) level of serotonin.</p>
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<p>Level of 5-methoxytryptamine in the group of patients with cirrhosis of various etiologies (MAFLD and ALD) with and without the clinical syndrome of jaundice.</p>
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<p>Level of 5-methoxytryptamine in the group of patients with cirrhosis of various etiologies (MAFLD and ALD) with signs of portal hypertension based on EGD data (GVs and/or EVs) and without signs of portal hypertension.</p>
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<p>Levels of metabolites in the group of patients with cirrhosis of various etiologies (MAFLD and ALD) with and without hepatic failure syndrome (hypocoagulation, hypoalbuminemia). (<b>a</b>) Level of 5-methoxytryptamine; (<b>b</b>) level of serotonin; (<b>c</b>) level of indole-3-butyric acid.</p>
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<p>Receiver operating characteristic (ROC) analysis for and metabolic panel of 17 tryptophan metabolites (MAFLD vs. ALD).</p>
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<p>Changes in the tryptophan metabolite levels in patients with MAFLD compared to the control group.</p>
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<p>Changes in the tryptophan metabolites levels in patients with ALD compared to the control group.</p>
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<p>Changes in the tryptophan metabolites levels in patients with MAFLD compared to ALD.</p>
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15 pages, 965 KiB  
Review
Impact of Substance Use Disorder on Tryptophan Metabolism Through the Kynurenine Pathway: A Narrative Review
by Lindsey Contella, Christopher L. Farrell, Luigi Boccuto, Alain H. Litwin and Marion L. Snyder
Metabolites 2024, 14(11), 611; https://doi.org/10.3390/metabo14110611 - 10 Nov 2024
Viewed by 988
Abstract
Background/Objectives: Substance use disorder is a crisis impacting many people in the United States. This review aimed to identify the effect addictive substances have on the kynurenine pathway. Tryptophan is an essential amino acid metabolized by the serotonin and kynurenine pathways. The [...] Read more.
Background/Objectives: Substance use disorder is a crisis impacting many people in the United States. This review aimed to identify the effect addictive substances have on the kynurenine pathway. Tryptophan is an essential amino acid metabolized by the serotonin and kynurenine pathways. The metabolites of these pathways play a role in the biological reward system. Addictive substances have been shown to cause imbalances in the ratios of these metabolites. With current treatment and therapeutic options being suboptimal, identifying biochemical mechanisms that are impacted during the use of addictive substances can provide alternative options for treatment or drug discovery. Methods: A systematic literature search was conducted to identify studies evaluating the relationship between substance use disorder and tryptophan metabolism through the kynurenine pathway. A total of 32 articles meeting eligibility criteria were used to review the relationship between the kynurenine pathway, tryptophan breakdown, and addictive substances. Results: The use of addictive substances dysregulates tryptophan metabolism and kynurenine metabolite concentrations. This imbalance directly affects the dopamine reward system and is thought to promote continued substance use. Conclusions: Further studies are needed to fully evaluate the metabolites of the kynurenine pathway, along with other options for treatment to repair the metabolite imbalance. Several possible therapeutics have been identified; drugs that restore homeostasis, such as Ro 61-8048 and natural products like Tinospora cordifolia or Decaisnea insignis, are promising options for the treatment of substance use disorder. Full article
(This article belongs to the Section Animal Metabolism)
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<p>Metabolism of TRP by the KP. The KP has two main branches: the neurotoxic pathway and the neuroprotective pathway. The impacts addictive substances have on KP metabolites in the blood are shown in grey boxes: + indicates an increase, − decrease, = no change, and § mixed results. Enzymes involved in the pathway are shown in shaded boxes. Abbreviations: EtOH: alcohol; METH: methamphetamine; TRP: tryptophan hydroxylase; AA: aromatic acid; IDO1: indoleamine 2,3-dioxygenase-1; IDO2: indoleamine 2,3-dioxygenase-2; TDO: tryptophan 2,3-dioxygenase; KATs: kynurenine aminotransferases; KMO: kynurenine 3-monooxygenase; KYNU: kynureninase; NE: Nonenzymatic; HAAO: 3-hydroxy anthranilate 3,4-dioxygenase; AFMID: arylformamidase; ACMSD: α-amino-β-carboxymuconate-ε-semialdehyde-decarboxylase; AADAT: aminoadipate aminotransferase; NAD+: nicotinamide adenine dinucleotide.</p>
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<p>Flow diagram depicting selection of literature included in systematic search using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).</p>
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17 pages, 1555 KiB  
Review
The Connection Between the Oral Microbiota and the Kynurenine Pathway: Insights into Oral and Certain Systemic Disorders
by Rita Kis-György, Tamás Körtési, Alexandra Anicka and Gábor Nagy-Grócz
Curr. Issues Mol. Biol. 2024, 46(11), 12641-12657; https://doi.org/10.3390/cimb46110750 - 7 Nov 2024
Viewed by 1149
Abstract
The oral microbiome, comprising bacteria, fungi, viruses, and protozoa, is essential for maintaining both oral and systemic health. This complex ecosystem includes over 700 bacterial species, such as Streptococcus mutans, which contributes to dental caries through acid production that demineralizes tooth enamel. [...] Read more.
The oral microbiome, comprising bacteria, fungi, viruses, and protozoa, is essential for maintaining both oral and systemic health. This complex ecosystem includes over 700 bacterial species, such as Streptococcus mutans, which contributes to dental caries through acid production that demineralizes tooth enamel. Fungi like Candida and pathogens such as Porphyromonas gingivalis are also significant, as they can lead to periodontal diseases through inflammation and destruction of tooth-supporting structures. Dysbiosis, or microbial imbalance, is a key factor in the development of these oral diseases. Understanding the composition and functions of the oral microbiome is vital for creating targeted therapies for these conditions. Additionally, the kynurenine pathway, which processes the amino acid tryptophan, plays a crucial role in immune regulation, neuroprotection, and inflammation. Oral bacteria can metabolize tryptophan, influencing the production of kynurenine, kynurenic acid, and quinolinic acid, thereby affecting the kynurenine system. The balance of microbial species in the oral cavity can impact tryptophan levels and its metabolites. This narrative review aims to explore the relationship between the oral microbiome, oral diseases, and the kynurenine system in relation to certain systemic diseases. Full article
(This article belongs to the Section Molecular Microbiology)
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<p>Key microbial components of the oral microbiome.</p>
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<p>Main substances of the kynurenine system. This is a schematic summary figure of the KP and potential modulation points influenced by dysbiosis. A detailed description of the KP is available in these publications [<a href="#B32-cimb-46-00750" class="html-bibr">32</a>,<a href="#B33-cimb-46-00750" class="html-bibr">33</a>]. The abbreviations represent the individual components of the kynurenine system. Abbreviations: 3-HA—3-hydroxyanthranilic acid, 3-HK—3-hydroxykynurenine, ANA—anthranilic acid, KYNA—kynurenic acid, L-KYN—L-kynurenine, NAD+—nicotinamide adenine dinucleotide, QUIN—quinolinic acid, Trp—tryptophan, XA—xanthurenic acid. the black arrows indicate the steps of the kynurenine pathway, the red arrows show the potential influences of dysbiosis on the kynurenine pathway.</p>
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<p>Periodontal diseases are strongly associated with the kynurenine pathway [<a href="#B31-cimb-46-00750" class="html-bibr">31</a>,<a href="#B50-cimb-46-00750" class="html-bibr">50</a>,<a href="#B51-cimb-46-00750" class="html-bibr">51</a>]. Abbreviations: IDO—indolamine 2,3-dioxygenase, QUIN—quinolinic acid, Trp—tryptophan.</p>
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<p>A comprehensive overview of the oral microbiome and kynurenine pathway, highlighting their contributions to the pathogenesis of various diseases.</p>
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<p>The bidirectional relationship between oral dysbiosis and the kynurenine system influences several processes that have been shown to play a role in the pathomechanism of various systemic disorders. Abbreviations: 3-HA—3-hydroxyanthranilic acid, 3-HK—3-hydroxykynurenine, ANA—anthranilic acid, KYNA—kynurenic acid, L-KYN—L-kynurenine, NAD+—nicotinamide adenine dinucleotide, QUIN—quinolinic acid, Trp—tryptophan, XA—xanthurenic acid.</p>
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15 pages, 2481 KiB  
Article
No Effects of Omega-3 Supplementation on Kynurenine Pathway, Inflammation, Depressive Symptoms, and Stress Response in Males: A Placebo-Controlled Trial
by Monika Bidzan-Wiącek, Maja Tomczyk, Magdalena Błażek, Adriana Mika and Jędrzej Antosiewicz
Nutrients 2024, 16(21), 3744; https://doi.org/10.3390/nu16213744 - 31 Oct 2024
Viewed by 895
Abstract
Background: Increased inflammation and heightened physiological stress reactivity have been associated with pathophysiology of depressive symptoms. The underlying biological mechanisms by which inflammation and stress may influence neurogenesis are changes in the kynurenine (KYN) pathway, which is activated under stress. Supplementation with n [...] Read more.
Background: Increased inflammation and heightened physiological stress reactivity have been associated with pathophysiology of depressive symptoms. The underlying biological mechanisms by which inflammation and stress may influence neurogenesis are changes in the kynurenine (KYN) pathway, which is activated under stress. Supplementation with n-3 polyunsaturated fatty acids (n-3 PUFAs) has anti-inflammatory properties and can increase stress resilience. Whether n-3 PUFAs alter KYN stress response is unknown. Objectives: This placebo-controlled study investigated the effect of n-3 PUFAs on KYN metabolism, inflammation, depressive symptoms, and mood. Moreover, stress-induced changes following a laboratory stressor have been assessed. Methods: In this placebo-controlled study, 47 healthy male adults received either 4 g n-3 PUFAs per day (Omega-3 group) or a placebo (Placebo group) for 12 weeks. Results: A significant group-by-time interaction was found for the inflammatory markers gp130 (F = 7.07, p = 0.011), IL-6R alpha (F = 10.33, p = 0.003), and TNF_RI (F= 10.92, p = 0.002). No significant group-by-time interactions were found for KYN metabolites, depressive symptoms, and mood (except for Hedonic tone (F = 6.50, p = 0.014)), nor for stress-induced changes in KYN metabolites and mood following a laboratory stressor. Conclusions: Overall, increased n-3 PUFA levels in healthy men ameliorate inflammatory markers but do not ameliorate KYN metabolism, depressive symptoms, mood, or KYN metabolism and mood following a stress induction. This study was registered at ClinicalTrials.gov with the identifier NCT05520437 (30/08/2022 first trial registration). Full article
(This article belongs to the Section Nutritional Immunology)
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<p>Distributions of the group x time interaction effect on the fatty acids profiles in the Placebo (black) and Omega-3 (blue) groups at times t0 (before supplementation) and t1 (after supplementation). Large points represent mean values, with error bars representing a 95% confidence interval around the mean value. Small points represent single observations.</p>
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<p>Distributions of the group x time interaction effect on the kynurenine pathway in the Placebo (black) and Omega-3 (blue) groups at times t0 (before supplementation) and t1 (after supplementation). Large points represent mean values, with error bars representing a 95% confidence interval around the mean value. Small points represent single observations.</p>
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<p>Distributions of the group x time interaction effect on the KYN pathway in the Placebo (black) and Omega-3 (blue) groups at times t1 (after supplementation), t2 (straight after stress induction), and t3 (one hour after stress induction). Large points represent mean values, with error bars representing a 95% confidence interval around the mean value. Small points represent single observations.</p>
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<p>Distributions of the group x time interaction effect on inflammation markers in the Placebo (black) and Omega-3 (blue) groups at times t0 (before supplementation) and t1 (after supplementation). Large points represent mean values, with error bars representing a 95% confidence interval around the mean value. Small points represent single observations.</p>
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<p>Distributions of the group x time interaction effect on mood and depressive symptoms in the Placebo (black) and Omega-3 (blue) groups at times t0 (before supplementation) and t1 (after supplementation). Large points represent means, with error bars representing a 95% confidence interval around the mean. Small points represent single observations.</p>
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