COVID-19 infection results in alterations of the kynurenine pathway and fatty acid metabolism that correlate with IL-6 levels and renal status

Starve a cold or feed a fever? Identifying cellular metabolic changes following infection and exposure to SARS-CoV-2

Viral infections induce major shifts in cellular metabolism elicited by active viral replication and antiviral responses. For the virus, harnessing cellular metabolism and evading changes that limit replication are essential for productive viral replication. In contrast, the cellular response to infection disrupts metabolic pathways to prevent viral replication and promote an antiviral state in the host cell and neighboring bystander cells. This competition between the virus and cell results in measurable shifts in cellular metabolism that differ depending on the virus, cell type, and extracellular environment. The resulting metabolic shifts can be observed and analyzed using global metabolic profiling techniques to identify pathways that are critical for either viral replication or cellular defense. SARS-CoV-2 is a respiratory virus that can exhibit broad tissue tropism and diverse, yet inconsistent, symptomatology. While the factors that determine the presentation and severity of SARS-CoV-2 infection remain unclear, metabolic syndromes are associated with more severe manifestations of SARS-CoV-2 disease. Despite these observations a critical knowledge gap remains between cellular metabolic responses and SARS-CoV-2 infection. Using a well-established untargeted metabolomics analysis workflow, we compared SARS-CoV-2 infection of human lung carcinoma cells. We identified significant changes in metabolic pathways that correlate with either productive or non-productive viral infection. This information is critical for characterizing the factors that contribute to SARS-CoV-2 replication that could be targeted for therapeutic interventions to limit viral disease.

Neopterin and kynurenine in serum and urine as prognostic biomarkers in hospitalized patients with delta and omicron variant SARS-CoV-2 infection

OBJECTIVES

Currently, no biomarker or scoring system could clearly identify patients at risk of progression to a severe coronavirus disease (COVID)-19. Even in patients with known risk factors, the fulminant course cannot be predicted with certainty. Analysis of commonly determined clinical parameters (frailty score, age, or body mass index) together with routine biomarkers of host response (C-reactive protein and viral nucleocapsid protein) in combination with new biomarkers neopterin, kynurenine, and tryptophan, could aid in predicting the patient outcome.

METHODS

In 2021 and 2022, urine and serum samples were prospectively collected on 1st to 4th day after hospital admission in 108 consecutive COVID-19 patients hospitalized at the University Hospital Hradec Králové, Czech Republic. Delta and omicron virus variants were studied. Neopterin, kynurenine and tryptophan were determined by liquid chromatography.

RESULTS

A significant correlation was observed between urinary and serum biomarker concentrations. Urinary and serum neopterin, kynurenine and kynurenine/tryptophan ratio were significantly (p≤0.05) higher in patients who subsequently needed oxygen therapy vs. patients without oxygen therapy. These parameters were also significantly increased in patients who died during the hospitalization compared to survivors. Complex equations have been derived using the investigated biomarkers and other clinical or laboratory parameters to predict the risk of subsequent oxygen therapy or death during hospitalization.

CONCLUSIONS

Present data demonstrate that neopterin, kynurenine and kynurenine/tryptophan ratio in the serum or in the urine represent promising biomarkers in the management of COVID-19 that may help to guide important therapeutic decisions.

A metabolic readout of the urine metabolome of COVID-19 patients

Analysis of urine samples from COVID-19 patients by ¹H NMR reveals important metabolic alterations due to SAR-CoV-2 infection. Previous studies have identified biomarkers in urine that reflect metabolic alterations in COVID-19 patients. We have used ¹H NMR to better define these metabolic alterations since this technique allows us to obtain a broad profile of the metabolites present in urine. This technique offers the advantage that sample preparation is very simple and gives us very complete information on the metabolites present. To detect these alterations, we have compared urine samples from COVID-19 patients (n = 35) with healthy people (n = 18). We used unsupervised (Robust PCA) and supervised (PLS-LDA) multivariate analysis methods to evaluate the differences between the two groups: COVID-19 and healthy controls. The differences focus on a group of metabolites related to energy metabolism (glucose, ketone bodies, glycine, creatinine, and citrate) and other processes related to bacterial flora (TMAO and formic acid) and detoxification (hippuric acid). The alterations in the urinary metabolome shown in this work indicate that SARS-CoV-2 causes a metabolic change from a normal situation of glucose consumption towards a gluconeogenic situation and possible insulin resistance.

Understanding Long COVID; Mitochondrial Health and Adaptation-Old Pathways, New Problems

Many people infected with the SARS-CoV-2 suffer long-term symptoms, such as "brain fog", fatigue and clotting problems. Explanations for "long COVID" include immune imbalance, incomplete viral clearance and potentially, mitochondrial dysfunction. As conditions with sub-optimal mitochondrial function are associated with initial severity of the disease, their prior health could be key in resistance to long COVID and recovery. The SARs virus redirects host metabolism towards replication; in response, the host can metabolically react to control the virus. Resolution is normally achieved after viral clearance as the initial stress activates a hormetic negative feedback mechanism. It is therefore possible that, in some individuals with prior sub-optimal mitochondrial function, the virus can "tip" the host into a chronic inflammatory cycle. This might explain the main symptoms, including platelet dysfunction. Long COVID could thus be described as a virally induced chronic and self-perpetuating metabolically imbalanced non-resolving state characterised by mitochondrial dysfunction, where reactive oxygen species continually drive inflammation and a shift towards glycolysis. This would suggest that a sufferer's metabolism needs to be "tipped" back using a stimulus, such as physical activity, calorie restriction, or chemical compounds that mimic these by enhancing mitochondrial function, perhaps in combination with inhibitors that quell the inflammatory response.

Kynurenines in the Pathogenesis of Peripheral Neuropathy During Leprosy and COVID-19

Inflammatory disorders are associated with the activation of tryptophan (TRYP) catabolism via the kynurenine pathway (KP). Several reports have demonstrated the role of KP in the immunopathophysiology of both leprosy and coronavirus disease 19 (COVID-19). The nervous system can be affected in infections caused by both Mycobacterium leprae and SARS-CoV-2, but the mechanisms involved in the peripheral neural damage induced by these infectious agents are not fully understood. In recent years KP has received greater attention due the importance of kynurenine metabolites in infectious diseases, immune dysfunction and nervous system disorders. In this review, we discuss how modulation of the KP may aid in controlling the damage to peripheral nerves and the effects of KP activation on neural damage during leprosy or COVID-19 individually and we speculate its role during co-infection.

Integration Analysis of Pharmacokinetics and Metabolomics to Predict Metabolic Phenotype and Drug Exposure of Remdesivir

Remdesivir has displayed pharmacological activity against SARS-CoV-2. However, no pharmacometabolomics (PM) or correlation analysis with pharmacokinetics (PK) was revealed. Rats were intravenously administered remdesivir, and a series of blood samples were collected before and after treatment. Comprehensive metabolomics profile and PK were investigated and quantitated simultaneously using our previous reliable HPLC-MS/MS method. Both longitudinal and transversal metabolic analyses were conducted, and the correlation between PM and PK parameters was evaluated using Pearson's correlation analysis and the PLS model. Multivariate statistical analysis was employed for discovering candidate biomarkers which predicted drug exposure or toxicity of remdesivir. The prominent metabolic profile variation was observed between pre- and posttreatment, and significant changes were found in 65 metabolites. A total of 15 metabolites-12 carnitines, one N-acetyl-D-glucosamine, one allantoin, and one corticosterone-were significantly correlated with the concentration of Nuc (active metabolite of remdesivir). Adenosine, spermine, guanosine, sn-glycero-3-phosphocholine, and l-homoserine may be considered potential biomarkers for predicting drug exposure or toxicity. This study is the first attempt to apply PM and PK to study remdesivir response/toxicity, and the identified candidate biomarkers might be used to predict the AUC and Cmax, indicating capability of discriminating good or poor responders. Currently, this study originally offers considerable evidence to metabolite reprogramming of remdesivir and sheds light on precision therapy development in fighting COVID-19.

Increased Kynurenine Indicates a Fatal Course of COVID-19

(1) Background: An inefficient immune response accompanied by an overwhelming inflammatory reaction is involved in severe courses of COVID-19. Kynurenine (KYN) has important immune-modulatory functions and may contribute to a failure in controlling SARS-CoV-2. The present study aims to explore biomarkers that hint at a fatal outcome of COVID-19 early on. (2) Methods: We established a cohort of 148 hospitalized COVID-19 patients for this study. Thirty-one patients died due to a severe COVID-19 course, and 117 recovered within 90 days. We built a biobank by collecting left-over material from these patients whenever blood arrived at the central laboratory of our University hospital for analysis of routine markers. The scientific laboratory analysis comprised KYN, Tryptophan (TRP), KYN/TRP ratio, ferritin, interleukin-6 (IL-6), C-reactive protein (CRP), creatinine, N-terminal pro-natriuretic peptide (NTproBNP), troponin T (TnT), fibrinogen, D-Dimer, prothrombin time (PT), activated partial thromboplastin time (aPTT), antithrombin (AT), protein C, protein S, factor XIII, lupus aPTT, angiotensin-2, vitamin D metabolites, and telomeres in all COVID-19 patients. Basic clinical characteristics and anteceding diseases including cardiovascular, oncologic, renal, hypertension, pulmonary, metabolic (diabetes, obesity) were recorded in a database together with the laboratory data. (3) Results: At the time of diagnosis of SARS-CoV-2 infection those patients who deceased within 90 days afterwards due to COVID-19, had a significantly higher age, higher KYN, KYN/TRP ratio, ferritin, creatinine, and NTproBNP values than SARS-CoV-2 patients who survived COVID-19 along the same time span. In a Kaplan-Meier analysis the variables age, KYN, ferritin, D-Dimer, TnT, NTproBNP, and creatinine showed a significant influence on survival time. Gender, however, showed no influence. In a combined Cox regression analysis KYN had the highest hazard ratio (1.188, 95% CI: 1.071-1.319) followed by age (1.041, 95% CI: 1.011-1.073). In a ROC analysis, KYN values above the cut off limit of 4.82 nmol/l (as specified by Youden index) had a sensitivity of 82% (95% CI: 66-95%) and a specificity of 72% (95% CI: 65-82%) to predict COVID-19 related death within 90 days observation time. (4) Conclusions: Kynurenine is a promising blood biomarker to predict an increased risk of mortality in SARS-CoV-2 infected people already at the time of the first positive SARS-CoV-2 verification detected in these persons.

Eicosanoid Metabolomic Profile of Remdesivir Treatment in Rat Plasma by High-Performance Liquid Chromatography Mass Spectrometry

Remdesivir, a nucleotide analog prodrug, has displayed pharmacological activity against SARS-CoV-2. Recently, eicosanoids are widely involved in regulating immunity and inflammation for COVID-19 patients. Rats were intravenously administered remdesivir at a dose of 5 mg/kg, and series of blood samples were collected before and after treatment. Targeted metabolomics regarding the eicosanoid profile were investigated and quantitated simultaneously using the previously reported reliable HPLC-MS/MS method. Additionally, interplay relationship between metabolomics and pharmacokinetic parameters was performed using the Pearson correlation analysis and PLS model. For the longitudinal metabolomics of remdesivir, metabolic profiles of the same rat were comparatively substantial at discrete sampling points. The metabolic fingerprints generated by individual discrepancy of rats were larger than metabolic disturbance caused by remdesivir. As for the transversal metabolomics, the prominent metabolic profile variation was observed between the baseline and treatment status. Except for TXB2, the inflammatory- and immunology-related eicosanoids of resolvin D2, 5-HEPE, 5-HETE, and DHA were significantly disturbed and reduced after single administration of remdesivir (p < 0.05, p < 0.001). Moreover, the metabolite of PGE2 correlated with GS-441524 (active metabolite of remdesivir) concentration and pharmacokinetic parameters of Cmax, AUC0-t, AUC0-infinity, and CL significantly. Eicosanoid metabolic profiles of remdesivir at both longitudinal and transversal levels were first revealed using the robust HPLC-MS/MS method. This initial observational eicosanoid metabolomics may lighten the therapy for fighting COVID-19 and further provide mechanistic insights of SARS-CoV-2 virus infection.

Targeted metabolomics identifies high performing diagnostic and prognostic biomarkers for COVID-19

Research exploring the development and outcome of COVID-19 infections has led to the need to find better diagnostic and prognostic biomarkers. This cross-sectional study used targeted metabolomics to identify potential COVID-19 biomarkers that predicted the course of the illness by assessing 110 endogenous plasma metabolites from individuals admitted to a local hospital for diagnosis/treatment. Patients were classified into four groups (≈ 40 each) according to standard polymerase chain reaction (PCR) COVID-19 testing and disease course: PCR-/controls (i.e., non-COVID controls), PCR+/not-hospitalized, PCR+/hospitalized, and PCR+/intubated. Blood samples were collected within 2 days of admission/PCR testing. Metabolite concentration data, demographic data and clinical data were used to propose biomarkers and develop optimal regression models for the diagnosis and prognosis of COVID-19. The area under the receiver operating characteristic curve (AUC; 95% CI) was used to assess each models' predictive value. A panel that included the kynurenine: tryptophan ratio, lysoPC a C26:0, and pyruvic acid discriminated non-COVID controls from PCR+/not-hospitalized (AUC = 0.947; 95% CI 0.931-0.962). A second panel consisting of C10:2, butyric acid, and pyruvic acid distinguished PCR+/not-hospitalized from PCR+/hospitalized and PCR+/intubated (AUC = 0.975; 95% CI 0.968-0.983). Only lysoPC a C28:0 differentiated PCR+/hospitalized from PCR+/intubated patients (AUC = 0.770; 95% CI 0.736-0.803). If additional studies with targeted metabolomics confirm the diagnostic value of these plasma biomarkers, such panels could eventually be of clinical use in medical practice.

Combinatorial Analysis of Phenotypic and Clinical Risk Factors Associated With Hospitalized COVID-19 Patients

Characterization of the risk factors associated with variability in the clinical outcomes of COVID-19 is important. Our previous study using genomic data identified a potential role of calcium and lipid homeostasis in severe COVID-19. This study aimed to identify similar combinations of features (disease signatures) associated with severe disease in a separate patient population with purely clinical and phenotypic data. The PrecisionLife combinatorial analytics platform was used to analyze features derived from de-identified health records in the UnitedHealth Group COVID-19 Data Suite. The platform identified and analyzed 836 disease signatures in two cohorts associated with an increased risk of COVID-19 hospitalization. Cohort 1 was formed of cases hospitalized with COVID-19 and a set of controls who developed mild symptoms. Cohort 2 included Cohort 1 individuals for whom additional laboratory test data was available. We found several disease signatures where lower levels of lipids were found co-occurring with lower levels of serum calcium and leukocytes. Many of the low lipid signatures were independent of statin use and 50% of cases with hypocalcemia signatures were reported with vitamin D deficiency. These signatures may be attributed to similar mechanisms linking calcium and lipid signaling where changes in cellular lipid levels during inflammation and infection affect calcium signaling in host cells. This study and our previous genomics analysis demonstrate that combinatorial analysis can identify disease signatures associated with the risk of developing severe COVID-19 separately from genomic or clinical data in different populations. Both studies suggest associations between calcium and lipid signaling in severe COVID-19.

A Missing Link: Engagements of Dendritic Cells in the Pathogenesis of SARS-CoV-2 Infections

Dendritic cells (DC) connect the innate and adaptive arms of the immune system and carry out numerous roles that are significant in the context of viral disease. Their functions include the control of inflammatory responses, the promotion of tolerance, cross-presentation, immune cell recruitment and the production of antiviral cytokines. Based primarily on the available literature that characterizes the behaviour of many DC subsets during Severe acute respiratory syndrome (SARS) and coronavirus disease 2019 (COVID-19), we speculated possible mechanisms through which DC could contribute to COVID-19 immune responses, such as dissemination of Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to lymph nodes, mounting dysfunctional inteferon responses and T cell immunity in patients. We highlighted gaps of knowledge in our understanding of DC in COVID-19 pathogenesis and discussed current pre-clinical development of therapies for COVID-19.

Evidence of Structural Protein Damage and Membrane Lipid Remodeling in Red Blood Cells from COVID-19 Patients

The SARS-CoV-2 beta coronavirus is the etiological driver of COVID-19 disease, which is primarily characterized by shortness of breath, persistent dry cough, and fever. Because they transport oxygen, red blood cells (RBCs) may play a role in the severity of hypoxemia in COVID-19 patients. The present study combines state-of-the-art metabolomics, proteomics, and lipidomics approaches to investigate the impact of COVID-19 on RBCs from 23 healthy subjects and 29 molecularly diagnosed COVID-19 patients. RBCs from COVID-19 patients had increased levels of glycolytic intermediates, accompanied by oxidation and fragmentation of ankyrin, spectrin beta, and the N-terminal cytosolic domain of band 3 (AE1). Significantly altered lipid metabolism was also observed, in particular, short- and medium-chain saturated fatty acids, acyl-carnitines, and sphingolipids. Nonetheless, there were no alterations of clinical hematological parameters, such as RBC count, hematocrit, or mean corpuscular hemoglobin concentration, with only minor increases in mean corpuscular volume. Taken together, these results suggest a significant impact of SARS-CoV-2 infection on RBC structural membrane homeostasis at the protein and lipid levels. Increases in RBC glycolytic metabolites are consistent with a theoretically improved capacity of hemoglobin to off-load oxygen as a function of allosteric modulation by high-energy phosphate compounds, perhaps to counteract COVID-19-induced hypoxia. Conversely, because the N-terminus of AE1 stabilizes deoxyhemoglobin and finely tunes oxygen off-loading and metabolic rewiring toward the hexose monophosphate shunt, RBCs from COVID-19 patients may be less capable of responding to environmental variations in hemoglobin oxygen saturation/oxidant stress when traveling from the lungs to peripheral capillaries and vice versa.