The tryptophan catabolite or kynurenine pathway in COVID-19 and critical COVID-19: a systematic review and meta-analysis

Laboratory parameters related to disease severity and physical performance after reconvalescence of acute COVID-19 infection

Research into the molecular basis of disease trajectory and Long-COVID is important to get insights toward underlying pathophysiological processes. The objective of this study was to investigate inflammation-mediated changes of metabolism in patients with acute COVID-19 infection and throughout a one-year follow up period. The study enrolled 34 patients with moderate to severe COVID-19 infection admitted to the University Clinic of Innsbruck in early 2020. The dynamics of multiple laboratory parameters (including inflammatory markers [C-reactive protein (CRP), interleukin-6 (IL-6), neopterin] as well as amino acids [tryptophan (Trp), phenylalanine (Phe) and tyrosine (Tyr)], and parameters of iron and vitamin B metabolism) was related to disease severity and patients' physical performance. Also, symptom load during acute illness and at approximately 60 days (FU1), and one year after symptom onset (FU2) were monitored and related with changes of the investigated laboratory parameters: During acute infection many investigated laboratory parameters were elevated (e.g., inflammatory markers, ferritin, kynurenine, phenylalanine) and enhanced tryptophan catabolism and phenylalanine accumulation were found. At FU2 nearly all laboratory markers had declined back to reference ranges. However, kynurenine/tryptophan ratio (Kyn/Trp) and the phenylalanine/tyrosine ratio (Phe/Tyr) were still exceeding the 95th percentile of healthy controls in about two thirds of our cohort at FU2. Lower tryptophan concentrations were associated with B vitamin availability (during acute infection and at FU1), patients with lower vitamin B12 levels at FU1 had a prolonged and more severe impairment of their physical functioning ability. Patients who had fully recovered (ECOG 0) presented with higher concentrations of iron parameters (ferritin, hepcidin, transferrin) and amino acids (phenylalanine, tyrosine) at FU2 compared to patients with restricted ability to work. Persistent symptoms at FU2 were tendentially associated with IFN-γ related parameters. Women were affected by long-term symptoms more frequently. Conclusively, inflammation-mediated biochemical changes appear to be related to symptoms of patients with acute and Long Covid.

A supervised Bayesian factor model for the identification of multi-omics signatures

MOTIVATION

Predictive biological signatures provide utility as biomarkers for disease diagnosis and prognosis, as well as prediction of responses to vaccination or therapy. These signatures are identified from high-throughput profiling assays through a combination of dimensionality reduction and machine learning techniques. The genes, proteins, metabolites, and other biological analytes that compose signatures also generate hypotheses on the underlying mechanisms driving biological responses, thus improving biological understanding. Dimensionality reduction is a critical step in signature discovery to address the large number of analytes in omics datasets, especially for multi-omics profiling studies with tens of thousands of measurements. Latent factor models, which can account for the structural heterogeneity across diverse assays, effectively integrate multi-omics data and reduce dimensionality to a small number of factors that capture correlations and associations among measurements. These factors provide biologically interpretable features for predictive modeling. However, multi-omics integration and predictive modeling are generally performed independently in sequential steps, leading to suboptimal factor construction. Combining these steps can yield better multi-omics signatures that are more predictive while still being biologically meaningful.

RESULTS

We developed a supervised variational Bayesian factor model that extracts multi-omics signatures from high-throughput profiling datasets that can span multiple data types. Signature-based multiPle-omics intEgration via lAtent factoRs (SPEAR) adaptively determines factor rank, emphasis on factor structure, data relevance and feature sparsity. The method improves the reconstruction of underlying factors in synthetic examples and prediction accuracy of coronavirus disease 2019 severity and breast cancer tumor subtypes.

AVAILABILITY AND IMPLEMENTATION

SPEAR is a publicly available R-package hosted at https://bitbucket.org/kleinstein/SPEAR.

Significance of nitrosative stress and glycoxidation products in the diagnosis of COVID-19

Nitrosative stress promotes protein glycoxidation, and both processes can occur during an infection with the SARS-CoV-2 virus. Therefore, the aim of this study was to assess selected nitrosative stress parameters and protein glycoxidation products in COVID-19 patients and convalescents relative to healthy subjects, including in reference to the severity of COVID-19 symptoms. The diagnostic utility of nitrosative stress and protein glycoxidation biomarkers was also evaluated in COVID-19 patients. The study involved 218 patients with COVID-19, 69 convalescents, and 48 healthy subjects. Nitrosative stress parameters (NO, S-nitrosothiols, nitrotyrosine) and protein glycoxidation products (tryptophan, kynurenine, N-formylkynurenine, dityrosine, AGEs) were measured in the blood plasma or serum with the use of colorimetric/fluorometric methods. The levels of NO (p = 0.0480), S-nitrosothiols (p = 0.0004), nitrotyrosine (p = 0.0175), kynurenine (p < 0.0001), N-formylkynurenine (p < 0.0001), dityrosine (p < 0.0001), and AGEs (p < 0.0001) were significantly higher, whereas tryptophan fluorescence was significantly (p < 0.0001) lower in COVID-19 patients than in the control group. Significant differences in the analyzed parameters were observed in different stages of COVID-19. In turn, the concentrations of kynurenine (p < 0.0001), N-formylkynurenine (p < 0.0001), dityrosine (p < 0.0001), and AGEs (p < 0.0001) were significantly higher, whereas tryptophan levels were significantly (p < 0.0001) lower in convalescents than in healthy controls. The ROC analysis revealed that protein glycoxidation products can be useful for diagnosing infections with the SARS-CoV-2 virus because they differentiate COVID-19 patients (KN: sensitivity-91.20%, specificity-92.00%; NFK: sensitivity-92.37%, specificity-92.00%; AGEs: sensitivity-99,02%, specificity-100%) and convalescents (KN: sensitivity-82.22%, specificity-84.00%; NFK: sensitivity-82,86%, specificity-86,00%; DT: sensitivity-100%, specificity-100%; AGE: sensitivity-100%, specificity-100%) from healthy subjects with high sensitivity and specificity. Nitrosative stress and protein glycoxidation are intensified both during and after an infection with the SARS-CoV-2 virus. The levels of redox biomarkers fluctuate in different stages of the disease. Circulating biomarkers of nitrosative stress/protein glycoxidation have potential diagnostic utility in both COVID-19 patients and convalescents.

Cross-Validation of Metabolic Phenotypes in SARS-CoV-2 Infected Subpopulations Using Targeted Liquid Chromatography-Mass Spectrometry (LC-MS)

To ensure biological validity in metabolic phenotyping, findings must be replicated in independent sample sets. Targeted workflows have long been heralded as ideal platforms for such validation due to their robust quantitative capability. We evaluated the capability of liquid chromatography-mass spectrometry (LC-MS) assays targeting organic acids and bile acids to validate metabolic phenotypes of SARS-CoV-2 infection. Two independent sample sets were collected: (1) Australia: plasma, SARS-CoV-2 positive (n = 20), noninfected healthy controls (n = 22) and COVID-19 disease-like symptoms but negative for SARS-CoV-2 infection (n = 22). (2) Spain: serum, SARS-CoV-2 positive (n = 33) and noninfected healthy controls (n = 39). Multivariate modeling using orthogonal projections to latent structures discriminant analyses (OPLS-DA) classified healthy controls from SARS-CoV-2 positive (Australia; R2 = 0.17, ROC-AUC = 1; Spain R2 = 0.20, ROC-AUC = 1). Univariate analyses revealed 23 significantly different (p < 0.05) metabolites between healthy controls and SARS-CoV-2 positive individuals across both cohorts. Significant metabolites revealed consistent perturbations in cellular energy metabolism (pyruvic acid, and 2-oxoglutaric acid), oxidative stress (lactic acid, 2-hydroxybutyric acid), hypoxia (2-hydroxyglutaric acid, 5-aminolevulinic acid), liver activity (primary bile acids), and host-gut microbial cometabolism (hippuric acid, phenylpropionic acid, indole-3-propionic acid). These data support targeted LC-MS metabolic phenotyping workflows for biological validation in independent sample sets.

Dendritic Cell - Fibroblast Crosstalk via TLR9 and AHR Signaling Drives Lung Fibrogenesis

Idiopathic pulmonary fibrosis (IPF) is characterized by progressive scarring and loss of lung function. With limited treatment options, patients succumb to the disease within 2-5 years. The molecular pathogenesis of IPF regarding the immunologic changes that occur is poorly understood. We characterize a role for non-canonical aryl-hydrocarbon receptor signaling (ncAHR) in dendritic cells (DCs) that leads to production of IL-6 and IL-17, promoting fibrosis. TLR9 signaling in myofibroblasts is shown to regulate production of TDO2 which converts tryptophan into the endogenous AHR ligand kynurenine. Mice with augmented ncAHR signaling were created by crossing floxed AHR exon-2 deletion mice (AHR Δex2 ) with mice harboring a CD11c-Cre. Bleomycin was used to study fibrotic pathogenesis. Isolated CD11c+ cells and primary fibroblasts were treated ex-vivo with relevant TLR agonists and AHR modulating compounds to study how AHR signaling influenced inflammatory cytokine production. Human datasets were also interrogated. Inhibition of all AHR signaling rescued fibrosis, however, AHR Δex2 mice treated with bleomycin developed more fibrosis and DCs from these mice were hyperinflammatory and profibrotic upon adoptive transfer. Treatment of fibrotic fibroblasts with TLR9 agonist increased expression of TDO2. Study of human samples corroborate the relevance of these findings in IPF patients. We also, for the first time, identify that AHR exon-2 floxed mice retain capacity for ncAHR signaling.

Kynurenine Pathway in Respiratory Diseases

The kynurenine pathway is the primary route for tryptophan catabolism and has received increasing attention as its association with inflammation and the immune system has become more apparent. This review provides a broad overview of the kynurenine pathway in respiratory diseases, from the initial observations to the characterization of the different cell types involved in the synthesis of kynurenine metabolites and the underlying immunoregulatory mechanisms. With a focus on respiratory infections, the various attempts to characterize the kynurenine/tryptophan (K/T) ratio as an inflammatory marker are reviewed. Its implication in chronic lung inflammation and its exacerbation by respiratory pathogens is also discussed. The emergence of preclinical interventional studies targeting the kynurenine pathway opens the way for the future development of new therapies.

Possible temporal relationship between SARS-CoV-2 infection and anti-NMDA receptor encephalitis: a meta-analysis

The global impact of SARS-CoV-2 infection has raised concerns about secondary diseases beyond acute illness. This review explores the significance and potential underlying mechanisms of how SARS-CoV-2 infection might elicit an immune response targeting N-methyl-D-aspartate (NMDA) receptors, and its implications for autoimmune-driven neuropsychiatric manifestations. We identified 19 published case reports of NMDA receptor encephalitis associated with SARS-CoV-2 infection or vaccination by a systematic literature search. The significance of these reports was limited since it is not clear if a coincidental or causal relationship exists between SARS-CoV-2 infection or vaccination and manifestation of NMDA receptor encephalitis. The included studies were hampered by difficulties in establishing if these patients had pre-existing NMDA receptor antibodies which entered the brain by infection- or vaccination-associated transient blood-brain barrier leakage. In addition, four cases had comorbid ovarian teratoma, which is a known trigger for development of NMDA receptor encephalitis. Considering that billions of people have contracted COVID-19 or have been vaccinated against this virus, the publication of only 19 case reports with a possible link to NMDA receptor encephalitis, indicates that it is rare. In conclusion, these findings do not support the case that SARS-CoV-2 infection or vaccination led to an increase of existing or de novo encephalitis mediated by an autoimmune response targeting NMDA receptor function. Nevertheless, this work underscores the importance of ongoing vigilance in monitoring viral outbreaks and their potential impact on the central nervous system through basic, epidemiological and translational research.

Diabetes Mellitus, Energy Metabolism, and COVID-19

Obesity, diabetes mellitus (mostly type 2), and COVID-19 show mutual interactions because they are not only risk factors for both acute and chronic COVID-19 manifestations, but also because COVID-19 alters energy metabolism. Such metabolic alterations can lead to dysglycemia and long-lasting effects. Thus, the COVID-19 pandemic has the potential for a further rise of the diabetes pandemic. This review outlines how preexisting metabolic alterations spanning from excess visceral adipose tissue to hyperglycemia and overt diabetes may exacerbate COVID-19 severity. We also summarize the different effects of SARS-CoV-2 infection on the key organs and tissues orchestrating energy metabolism, including adipose tissue, liver, skeletal muscle, and pancreas. Last, we provide an integrative view of the metabolic derangements that occur during COVID-19. Altogether, this review allows for better understanding of the metabolic derangements occurring when a fire starts from a small flame, and thereby help reducing the impact of the COVID-19 pandemic.

Integrative Molecular Structure Elucidation and Construction of an Extended Metabolic Pathway Associated with an Ancient Innate Immune Response in COVID-19 Patients

We present compelling evidence for the existence of an extended innate viperin-dependent pathway, which provides crucial evidence for an adaptive response to viral agents, such as SARS-CoV-2. We show the in vivo biosynthesis of a family of novel endogenous cytosine metabolites with potential antiviral activities. Two-dimensional nuclear magnetic resonance (NMR) spectroscopy revealed a characteristic spin-system motif, indicating the presence of an extended panel of urinary metabolites during the acute viral replication phase. Mass spectrometry additionally enabled the characterization and quantification of the most abundant serum metabolites, showing the potential diagnostic value of the compounds for viral infections. In total, we unveiled ten nucleoside (cytosine- and uracil-based) analogue structures, eight of which were previously unknown in humans allowing us to propose a new extended viperin pathway for the innate production of antiviral compounds. The molecular structures of the nucleoside analogues and their correlation with an array of serum cytokines, including IFN-α2, IFN-γ, and IL-10, suggest an association with the viperin enzyme contributing to an ancient endogenous innate immune defense mechanism against viral infection.

The Multisystem Impact of Long COVID: A Comprehensive Review

(1) Background: COVID-19 was responsible for the latest pandemic, shaking and reshaping healthcare systems worldwide. Its late clinical manifestations make it linger in medical memory as a debilitating illness over extended periods. (2) Methods: the recent literature was systematically analyzed to categorize and examine the symptomatology and pathophysiology of Long COVID across various bodily systems, including pulmonary, cardiovascular, gastrointestinal, neuropsychiatric, dermatological, renal, hematological, and endocrinological aspects. (3) Results: The review outlines the diverse clinical manifestations of Long COVID across multiple systems, emphasizing its complexity and challenges in diagnosis and treatment. Factors such as pre-existing conditions, initial COVID-19 severity, vaccination status, gender, and age were identified as influential in the manifestation and persistence of Long COVID symptoms. This condition is highlighted as a debilitating disease capable of enduring over an extended period and presenting new symptoms over time. (4) Conclusions: Long COVID emerges as a condition with intricate multi-systemic involvement, complicating its diagnosis and treatment. The findings underscore the necessity for a nuanced understanding of its diverse manifestations to effectively manage and address the evolving nature of this condition over time.

The tryptophan catabolite or kynurenine pathway in autism spectrum disorder; a systematic review and meta-analysis

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social communication and interaction, as well as rigid and unchanging interests and behaviors. Several studies have reported that activated immune-inflammatory and nitro-oxidative pathways are accompanied by depletion of plasma tryptophan (TRP), increased competing amino acid (CAAs) levels, and activation of the TRP catabolite (TRYCAT) pathway. This study aims to systematically review and meta-analyze data on peripheral TRP, CAAs, TRYCAT pathway activity, and individual TRYCATs, including kynurenine (KYN) and kynurenic acid (KA) levels, in the blood and urine of ASD patients. After extensively searching PubMed, Google Scholar, and SciFinder, a total of 25 full-text papers were included in the analysis, with a total of 6653 participants (3557 people with ASD and 3096 healthy controls). Our results indicate that blood TRP and the TRP/CAAs ratio were not significantly different between ASD patients and controls (standardized mean difference, SMD = -0.227, 95% confidence interval, CI: -0.540; 0.085, and SMD = 0.158, 95% CI: -0.042; 0.359), respectively. The KYN/TRP ratio showed no significant difference between ASD and controls (SMD = 0.001, 95% CI: -0.169; 0.171). Blood KYN and KA levels were not significantly changed in ASD. Moreover, there were no significant differences in urine TRP, KYN, and KA levels between ASD and controls. We could not establish increases in neurotoxic TRYCATs in ASD. In conclusion, this study demonstrates no abnormalities in peripheral blood TRP metabolism, indoleamine 2,3-dioxygenase enzyme (IDO) activity, or TRYCAT production in ASD. Reduced TRP availability and elevated neurotoxic TRYCAT levels are not substantial contributors to ASD's pathophysiology.

Systemic perturbations in amino acids/amino acid derivatives and tryptophan pathway metabolites associated with murine influenza A virus infection

BACKGROUND

Influenza A virus (IAV) is the only influenza virus causing flu pandemics (i.e., global epidemics of flu disease). Influenza (the flu) is a highly contagious disease that can be deadly, especially in high-risk groups. Worldwide, these annual epidemics are estimated to result in about 3 to 5 million cases of severe illness and in about 290,000 to 650,000 respiratory deaths. We intend to reveal the effect of IAV infection on the host's metabolism, immune response, and neurotoxicity by using a mouse IAV infection model.

METHODS

51 metabolites of murine blood plasma (33 amino acids/amino acid derivatives (AADs) and 18 metabolites of the tryptophan pathway) were analyzed by using Ultra-High-Performance Liquid Chromatography-Mass Spectrometry with Electrospray Ionization at the acute (7 days post-infection (dpi)), resolution (14 dpi), and recovery (21 dpi) stages of the virus infection in comparison with controls.

RESULTS

Among the 33 biogenic amino acids/AADs, the levels of five amino acids/AADs (1-methylhistidine, 5-oxoproline, α-aminobutyric acid, glutamine, and taurine) increased by 7 dpi, whereas the levels of ten amino acids/AADs (4-hydroxyproline, alanine, arginine, asparagine, cysteine, citrulline, glycine, methionine, proline, and tyrosine) decreased. By 14 dpi, the levels of one AAD (3-methylhistidine) increased, whereas the levels of five amino acids/AADs (α-aminobutyric acid, aminoadipic acid, methionine, threonine, valine) decreased. Among the 18 metabolites from the tryptophan pathway, the levels of kynurenine, quinolinic acid, hydroxykynurenine increased by 7 dpi, whereas the levels of indole-3-acetic acid and nicotinamide riboside decreased.

CONCLUSIONS

Our data may facilitate understanding the molecular mechanisms of host responses to IAV infection and provide a basis for discovering potential new mechanistic, diagnostic, and prognostic biomarkers and therapeutic targets for IAV infection.

HDL-Related Parameters and COVID-19 Mortality: The Importance of HDL Function

COVID-19, caused by the SARS-CoV-2 coronavirus, emerged as a global pandemic in late 2019, resulting in significant global public health challenges. The emerging evidence suggests that diminished high-density lipoprotein (HDL) cholesterol levels are associated with the severity of COVID-19, beyond inflammation and oxidative stress. Here, we used nuclear magnetic resonance spectroscopy to compare the lipoprotein and metabolic profiles of COVID-19-infected patients with non-COVID-19 pneumonia. We compared the control group and the COVID-19 group using inflammatory markers to ensure that the differences in lipoprotein levels were due to COVID-19 infection. Our analyses revealed supramolecular phospholipid composite (SPC), phenylalanine, and HDL-related parameters as key discriminators between COVID-19-positive and non-COVID-19 pneumonia patients. More specifically, the levels of HDL parameters, including apolipoprotein A-I (ApoA-I), ApoA-II, HDL cholesterol, and HDL phospholipids, were significantly different. These findings underscore the potential impact of HDL-related factors in patients with COVID-19. Significantly, among the HDL-related metrics, the cholesterol efflux capacity (CEC) displayed the strongest negative association with COVID-19 mortality. CEC is a measure of how well HDL removes cholesterol from cells, which may affect the way SARS-CoV-2 enters cells. In summary, this study validates previously established markers of COVID-19 infection and further highlights the potential significance of HDL functionality in the context of COVID-19 mortality.

The Effect of Antidepressant Treatment on Neurocognitive Functions, Redox and Inflammatory Parameters in the Context of COVID-19

Inflammation is an important component of the etiopathology of depression that uses oxidative and nitrosative stress (O&NS) and elevated inflammatory markers. SARS-CoV-2 infection is also associated with abnormal inflammatory processes, which may impair effective treatment of depression in COVID-19 survivors. In the presented study, thirty-three hospitalized patients with major depressive disorder (MDD) were started on antidepressant treatment, and twenty-one were re-evaluated after 4-6 weeks. The control group consisted of thirty healthy volunteers. All participants underwent neuropsychiatric evaluation, biochemical blood and urine analyses. The results of the research demonstrated positive correlations of the Hamilton Depression Rating Scale (HAM-D) scores with serum catalase (CAT) and urinary S-Nitrosothiols levels, and the Beck Depression Inventory (BDI) scores with serum reduced glutathione (GSH) and superoxide dismutase (SOD) levels. Depressed patients with a history of COVID-19 prior to the treatment had higher urinary nitric oxide (NO) levels and lower serum glutathione peroxidase (GPx) levels. In the control group, COVID-19 survivors had higher levels of urinary N-formylkynurenine (NFK). Our results suggest that the antidepressant treatment has a modulating effect on O&NS, reduces depressive symptoms and improves cognitive functions The present study does not indicate that clinical response to antidepressant treatment is associated with COVID-19 history and baseline SARS-CoV-2 antibody levels. Nevertheless, further research in this area is needed to systematize antidepressant treatment in COVID-19 survivors.

Reverse cholesterol transport and lipid peroxidation biomarkers in major depression and bipolar disorder: A systematic review and meta-analysis

BACKGROUND

Major depression (MDD) and bipolar disorder (BD) are linked to immune activation, increased oxidative stress, and lower antioxidant defenses.

OBJECTIVES

To systematically review and meta-analyze all data concerning biomarkers of reverse cholesterol transport (RCT), lipid-associated antioxidants, lipid peroxidation products, and autoimmune responses to oxidatively modified lipid epitopes in MDD and BD.

METHODS

Databases including PubMed, Google scholar and SciFinder were searched to identify eligible studies from inception to January 10th, 2023. Guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed.

RESULTS

The current meta-analysis included 176 studies (60 BD and 116 MDD) and examined 34,051 participants, namely 17,094 with affective disorders and 16,957 healthy controls. Patients with MDD and BD showed a) significantly decreased RCT (mainly lowered high-density lipoprotein cholesterol and paraoxonase 1); b) lowered lipid soluble vitamins (including vitamin A, D, and coenzyme Q10); c) increased lipid peroxidation and aldehyde formation, mainly increased malondialdehyde (MDA), 4-hydroxynonenal, peroxides, and 8-isoprostanes; and d) Immunoglobulin (Ig)G responses to oxidized low-density lipoprotein and IgM responses to MDA. The ratio of all lipid peroxidation biomarkers/all lipid-associated antioxidant defenses was significantly increased in MDD (standardized mean difference or SMD = 0.433; 95% confidence intervals (CI): 0.312; 0.554) and BD (SMD = 0.653; CI: 0.501-0.806). This ratio was significantly greater in BD than MDD (p = 0.027).

CONCLUSION

In MDD/BD, lowered RCT, a key antioxidant and anti-inflammatory pathway, may drive increased lipid peroxidation, aldehyde formation, and autoimmune responses to oxidative specific epitopes, which all together cause increased immune-inflammatory responses and neuro-affective toxicity.

Anxiety due to Long COVID is partially driven by activation of the tryptophan catabolite (TRYCAT) pathway

This study examines whether activation of the tryptophan catabolite (TRYCAT) pathway is associated with anxiety symptoms due to Long COVID. We selected 90 participants, 60 Long COVID patients and 30 individuals without any symptoms following acute COVID-19 infection. Using cluster analysis and the Hamilton Anxiety Rating scale (HAMA) score, the pure HAMA anxiety score, serum tryptophan (TRP) and kynurenine (KYN), the KYN/TRP ratio (all measured during Long COVID), and oxygen saturation (SpO2) (measured during the acute phase of COVID-19), we were able to classify Long COVID patients into two distinct clusters with an adequate silhouette cohesion and separation index (0.58): cluster 1 (n = 61) and cluster 2 (n = 29). Cluster 2 patients had lower SpO2 and TRP levels, as well as higher KYN, KYN/TRP ratio, and HAMA scores than cluster 1. Regression analysis revealed that the KYN/TRP ratio explained 14.4 % of the variance in the HAMA score (F = 14.81, df = 1/88, p = 0.001). In addition, regression analysis revealed that SpO2 partially explained the variance in serum TRP (r = 0.396, p = 0.005), KYN/TRP ratio (r = - 0.248, p = 0.018), and the HAMA score (r = - 0.279, p = 0.008). The current data imply that decreased SpO2 during the acute phase of COVID-19 infection is predictive of anxiety caused by Long COVID. Our data reveal that around 32 % of Long COVID patients have elevated IDO activity in association with elevated anxiety.

The value of prospective metabolomic susceptibility endotypes: broad applicability for infectious diseases

BACKGROUND

As new infectious diseases (ID) emerge and others continue to mutate, there remains an imminent threat, especially for vulnerable individuals. Yet no generalizable framework exists to identify the at-risk group prior to infection. Metabolomics has the advantage of capturing the existing physiologic state, unobserved via current clinical measures. Furthermore, metabolomics profiling during acute disease can be influenced by confounding factors such as indications, medical treatments, and lifestyles.

METHODS

We employed metabolomic profiling to cluster infection-free individuals and assessed their relationship with COVID severity and influenza incidence/recurrence.

FINDINGS

We identified a metabolomic susceptibility endotype that was strongly associated with both severe COVID (ORICUadmission = 6.7, p-value = 1.2 × 10-08, ORmortality = 4.7, p-value = 1.6 × 10-04) and influenza (ORincidence = 2.9; p-values = 2.2 × 10-4, βrecurrence = 1.03; p-value = 5.1 × 10-3). We observed similar severity associations when recapitulating this susceptibility endotype using metabolomics from individuals during and after acute COVID infection. We demonstrate the value of using metabolomic endotyping to identify a metabolically susceptible group for two-and potentially more-IDs that are driven by increases in specific amino acids, including microbial-related metabolites such as tryptophan, bile acids, histidine, polyamine, phenylalanine, and tyrosine metabolism, as well as carbohydrates involved in glycolysis.

INTERPRETATIONS

These metabolites may be identified prior to infection to enable protective measures for these individuals.

FUNDING

The Longitudinal EMR and Omics COVID-19 Cohort (LEOCC) and metabolomic profiling were supported by the National Heart, Lung, and Blood Institute and the Intramural Research Program of the National Center for Advancing Translational Sciences, National Institutes of Health.

A supervised Bayesian factor model for the identification of multi-omics signatures

MOTIVATION

Predictive biological signatures provide utility as biomarkers for disease diagnosis and prognosis, as well as prediction of responses to vaccination or therapy. These signatures are iden-tified from high-throughput profiling assays through a combination of dimensionality reduction and machine learning techniques. The genes, proteins, metabolites, and other biological analytes that compose signatures also generate hypotheses on the underlying mechanisms driving biological responses, thus improving biological understanding. Dimensionality reduction is a critical step in signature discovery to address the large number of analytes in omics datasets, especially for multi-omics profiling studies with tens of thousands of measurements. Latent factor models, which can account for the structural heterogeneity across diverse assays, effectively integrate multi-omics data and reduce dimensionality to a small number of factors that capture correlations and associations among measurements. These factors provide biologically interpretable features for predictive model-ing. However, multi-omics integration and predictive modeling are generally performed independent-ly in sequential steps, leading to suboptimal factor construction. Combining these steps can yield better multi-omics signatures that are more predictive while still being biologically meaningful.

RESULTS

We developed a supervised variational Bayesian factor model that extracts multi-omics signatures from high-throughput profiling datasets that can span multiple data types. Signature-based multiPle-omics intEgration via lAtent factoRs (SPEAR) adaptively determines factor rank, emphasis on factor structure, data relevance and feature sparsity. The method improves the recon-struction of underlying factors in synthetic examples and prediction accuracy of COVID-19 severity and breast cancer tumor subtypes.

AVAILABILITY

SPEAR is a publicly available R-package hosted at https://bitbucket.org/kleinstein/SPEAR.

Meta-Analysis of COVID-19 Metabolomics Identifies Variations in Robustness of Biomarkers

The global COVID-19 pandemic resulted in widespread harms but also rapid advances in vaccine development, diagnostic testing, and treatment. As the disease moves to endemic status, the need to identify characteristic biomarkers of the disease for diagnostics or therapeutics has lessened, but lessons can still be learned to inform biomarker research in dealing with future pathogens. In this work, we test five sets of research-derived biomarkers against an independent targeted and quantitative Liquid Chromatography-Mass Spectrometry metabolomics dataset to evaluate how robustly these proposed panels would distinguish between COVID-19-positive and negative patients in a hospital setting. We further evaluate a crowdsourced panel comprising the COVID-19 metabolomics biomarkers most commonly mentioned in the literature between 2020 and 2023. The best-performing panel in the independent dataset-measured by F1 score (0.76) and AUROC (0.77)-included nine biomarkers: lactic acid, glutamate, aspartate, phenylalanine, β-alanine, ornithine, arachidonic acid, choline, and hypoxanthine. Panels comprising fewer metabolites performed less well, showing weaker statistical significance in the independent cohort than originally reported in their respective discovery studies. Whilst the studies reviewed here were small and may be subject to confounders, it is desirable that biomarker panels be resilient across cohorts if they are to find use in the clinic, highlighting the importance of assessing the robustness and reproducibility of metabolomics analyses in independent populations.

The kynurenine pathway of tryptophan metabolism: a neglected therapeutic target of COVID-19 pathophysiology and immunotherapy

SARS-CoV-2 (COVID-19) exerts profound changes in the kynurenine (Kyn) pathway (KP) of tryptophan (Trp) metabolism that may underpin its pathophysiology. The KP is the main source of the vital cellular effector NAD+ and intermediate metabolites that modulate immune and neuronal functions. Trp metabolism is the top pathway influenced by COVID-19. Sixteen studies established virus-induced activation of the KP mediated mainly by induction of indoleamine 2,3-dioxygenase (IDO1) in most affected tissues and of IDO2 in lung by the increased release of proinflammatory cytokines but could additionally involve increased flux of plasma free Trp and induction of Trp 2,3-dioxygenase (TDO) by cortisol. The major Kyn metabolite targeted by COVID-19 is kynurenic acid (KA), the Kyn metabolite with the greatest affinity for the aryl hydrocarbon receptor (AhR), which is also activated by COVID-19. AhR activation initiates two important series of events: a vicious circle involving IDO1 induction, KA accumulation and further AhR activation, and activation of poly (ADP-ribose) polymerase (PARP) leading to NAD+ depletion and cell death. The virus further deprives the host of NAD+ by inhibiting its main biosynthetic pathway from quinolinic acid, while simultaneously acquiring NAD+ by promoting its synthesis from nicotinamide in the salvage pathway. Additionally, the protective effects of sirtuin 1 are minimised by the PARP activation. KP dysfunction may also underpin the mood and neurological disorders acutely and during 'long COVID'. More studies of potential effects of vaccination therapy on the KP are required and exploration of therapeutic strategies involving modulation of the KP changes are proposed.

Plasma metabolomics profiling identifies new predictive biomarkers for disease severity in COVID-19 patients

Recently, numerous studies have reported on different predictive models of disease severity in COVID-19 patients. Herein, we propose a highly predictive model of disease severity by integrating routine laboratory findings and plasma metabolites including cytosine as a potential biomarker of COVID-19 disease severity. One model was developed and internally validated on the basis of ROC-AUC values. The predictive accuracy of the model was 0.996 (95% CI: 0.989 to 1.000) with an optimal cut-off risk score of 3 from among 6 biomarkers including five lab findings (D-dimer, ferritin, neutrophil counts, Hp, and sTfR) and one metabolite (cytosine). The model is of high predictive power, needs a small number of variables that can be acquired at minimal cost and effort, and can be applied independent of non-empirical clinical data. The metabolomics profiling data and the modeling work stemming from it, as presented here, could further explain the cause of COVID-19 disease prognosis and patient management.

Integrative Plasma Metabolic and Lipidomic Modelling of SARS-CoV-2 Infection in Relation to Clinical Severity and Early Mortality Prediction

An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff's delta 0.91-0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff's delta = -0.98 and PE.P 16:0/18:1, Cliff's delta = -0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these "high risk" patients in the early disease stages.

Persistent Symptoms and IFN-γ-Mediated Pathways after COVID-19

After COVID-19, patients have reported various complaints such as fatigue, neurological symptoms, and insomnia. Immune-mediated changes in amino acid metabolism might contribute to the development of these symptoms. Patients who had had acute, PCR-confirmed COVID-19 infection about 60 days earlier were recruited within the scope of the prospective CovILD study. We determined the inflammatory parameters and alterations in tryptophan and phenylalanine metabolism in 142 patients cross-sectionally. Symptom persistence (pain, gastrointestinal symptoms, anosmia, sleep disturbance, and neurological symptoms) and patients' physical levels of functioning were recorded. Symptoms improved in many patients after acute COVID-19 (n = 73, 51.4%). Still, a high percentage of patients had complaints, and women were affected more often. In many patients, ongoing immune activation (as indicated by high neopterin and CRP concentrations) and enhanced tryptophan catabolism were found. A higher phenylalanine to tyrosine ratio (Phe/Tyr) was found in women with a lower level of functioning. Patients who reported improvements in pain had lower Phe/Tyr ratios, while patients with improved gastrointestinal symptoms presented with higher tryptophan and kynurenine values. Our results suggest that women have persistent symptoms after COVID-19 more often than men. In addition, the physical level of functioning and the improvements in certain symptoms appear to be associated with immune-mediated changes in amino acid metabolism.

Advances in kynurenine analysis

Kynurenine, the first product of tryptophan degradation via the kynurenine pathway, has become one of the most frequently mentioned biomarkers in recent years. Its levels in the body indicate the state of the human physiology. Human serum and plasma are the main matrixes used to evaluate kynurenine levels and liquid chromatography is the dominant technique for its determination. However, their concentrations in blood do not always correspond to the levels in other matrixes obtained from the affected individuals. It is therefore important to decide when it is appropriate to analyse kynurenine in alternative matrices. However, liquid chromatography may not be the best option for the analysis. This review presents alternatives that can be used and summarizes the features that need to be considered prior to kynurenine determination. Possible approaches to kynurenine analysis in a variety of human matrixes, their challenges, and limitations are critically discussed.

Tryptophan catabolites, inflammation, and insulin resistance as determinants of chronic fatigue syndrome and affective symptoms in long COVID

Critical COVID-19 disease is accompanied by depletion of plasma tryptophan (TRY) and increases in indoleamine-dioxygenase (IDO)-stimulated production of neuroactive tryptophan catabolites (TRYCATs), including kynurenine (KYN). The TRYCAT pathway has not been studied extensively in association with the physiosomatic and affective symptoms of Long COVID. In the present study, we measured serum TRY, TRYCATs, insulin resistance (using the Homeostatic Model Assessment Index 2-insulin resistance, HOMA2-IR), C-reactive protein (CRP), physiosomatic, depression, and anxiety symptoms in 90 Long COVID patients, 3-10 months after remission of acute infection. We were able to construct an endophenotypic class of severe Long COVID (22% of the patients) with very low TRY and oxygen saturation (SpO2, during acute infection), increased kynurenine, KYN/TRY ratio, CRP, and very high ratings on all symptom domains. One factor could be extracted from physiosomatic symptoms (including chronic fatigue-fibromyalgia), depression, and anxiety symptoms, indicating that all domains are manifestations of the common physio-affective phenome. Three Long COVID biomarkers (CRP, KYN/TRY, and IR) explained around 40% of the variance in the physio-affective phenome. The latter and the KYN/TRY ratio were significantly predicted by peak body temperature (PBT) and lowered SpO2 during acute infection. One validated latent vector could be extracted from the three symptom domains and a composite based on CRP, KYN/TRY, and IR (Long COVID), and PBT and SpO2 (acute COVID-19). In conclusion, the physio-affective phenome of Long COVID is a manifestation of inflammatory responses during acute and Long COVID, and lowered plasma tryptophan and increased kynurenine may contribute to these effects.

Lowered oxygen saturation and increased body temperature in acute COVID-19 largely predict chronic fatigue syndrome and affective symptoms due to Long COVID: A precision nomothetic approach

BACKGROUND

Long coronavirus disease 2019 (LC) is a chronic sequel of acute COVID-19. The exact pathophysiology of the affective, chronic fatigue and physiosomatic symptoms (labelled as "physio-affective phenome") of LC has remained elusive.

OBJECTIVE

The current study aims to delineate the effects of oxygen saturation (SpO2) and body temperature during the acute phase on the physio-affective phenome of LC.

METHOD

We recruited 120 LC patients and 36 controls. For all participants, we assessed the lowest SpO2 and peak body temperature during acute COVID-19, and the Hamilton Depression and Anxiety Rating Scale (HAMD/HAMA) and Fibro Fatigue (FF) scales 3-4 months later.

RESULTS

Lowered SpO2 and increased body temperature during the acute phase and female sex predict 60.7% of the variance in the physio-affective phenome of LC. Using unsupervised learning techniques, we were able to delineate a new endophenotype class, which comprises around 26.7% of the LC patients and is characterised by very low SpO2 and very high body temperature, and depression, anxiety, chronic fatigue, and autonomic and gastro-intestinal symptoms scores. Single latent vectors could be extracted from both biomarkers, depression, anxiety and FF symptoms or from both biomarkers, insomnia, chronic fatigue, gastro-intestinal and autonomic symptoms.

CONCLUSION

The newly constructed endophenotype class and pathway phenotypes indicate that the physio-affective phenome of LC is at least in part the consequence of the pathophysiology of acute COVID-19, namely the combined effects of lowered SpO2, increased body temperature and the associated immune-inflammatory processes and lung lesions.

Diagnostic, Prognostic and Mechanistic Biomarkers of COVID-19 Identified by Mass Spectrometric Metabolomics

A number of studies have assessed the impact of SARS-CoV-2 infection and COVID-19 severity on the metabolome of exhaled air, saliva, plasma, and urine to identify diagnostic and prognostic biomarkers. In spite of the richness of the literature, there is no consensus about the utility of metabolomic analyses for the management of COVID-19, calling for a critical assessment of the literature. We identified mass spectrometric metabolomic studies on specimens from SARS-CoV2-infected patients and subjected them to a cross-study comparison. We compared the clinical design, technical aspects, and statistical analyses of published studies with the purpose to identify the most relevant biomarkers. Several among the metabolites that are under- or overrepresented in the plasma from patients with COVID-19 may directly contribute to excessive inflammatory reactions and deficient immune control of SARS-CoV2, hence unraveling important mechanistic connections between whole-body metabolism and the course of the disease. Altogether, it appears that mass spectrometric approaches have a high potential for biomarker discovery, especially if they are subjected to methodological standardization.

Association between Gut Microbiota and SARS-CoV-2 Infection and Vaccine Immunogenicity

Gut microbiota is increasingly recognized to play a pivotal role in various human physiological functions and diseases. Amidst the COVID-19 pandemic, research has suggested that dysbiosis of the gut microbiota is also involved in the development and severity of COVID-19 symptoms by regulating SARS-CoV-2 entry and modulating inflammation. Previous studies have also suggested that gut microbiota and their metabolites could have immunomodulatory effects on vaccine immunogenicity, including influenza vaccines and oral rotavirus vaccines. In light of these observations, it is possible that gut microbiota plays a role in influencing the immune responses to COVID-19 vaccinations via similar mechanisms including effects of lipopolysaccharides, flagellin, peptidoglycan, and short-chain fatty acids. In this review, we give an overview of the current understanding on the role of the gut microbiota in COVID-19 manifestations and vaccine immunogenicity. We then discuss the limitations of currently published studies on the associations between gut microbiota and COVID-19 vaccine outcomes. Future research directions shall be focused on the development of microbiota-based interventions on improving immune response to SARS-CoV-2 infection and vaccinations.

Activities of plasma indoleamine-2, 3-dioxygenase (IDO) enzyme in Nigerian patients with lung diseases: basis for tryptophan supplementation or IDO inhibitor use

Background

Clinical trial of IDO inhibitor or uses of micro-nutrient supplements during management of diseases is commonly done without having adequate basis for the practise. Tryptophan (Trp) is an essential amino acid needed for T-lymphocyte function, and indoleamine-2,3-dioxygenase (IDO) is a potent immunoregulatory molecule that catalyses the rate-limiting step of Trp degradation in the kynurenine (Kyn) pathway.

Materials and methods

Human IDO in the plasma samples was measured using ELISA in patients with non-infectious (asthma) and infectious diseases (pulmonary tuberculosis and COVID-19) compared with corresponding un-infected controls.

Results

Mean IDO activity in COVID-19 patients was significantly higher compared with corresponding control (p = 0.001) while mean IDO activity in pulmonary tuberculosis patients was non-significantly higher compared with corresponding control (p = 0.520), and mean IDO activity in asthma patients was non-significantly lower compared with corresponding control (p = 0.102).

Conclusion

Our data suggest that IDO activity as an innate immune factor is increased in infectious lung diseases (COVID-19 and pulmonary tuberculosis) but reduced in non-infectious disease (asthma) and that use of tryptophan supplementation or IDO inhibitor may not be necessary in all lung diseases.

Signatures of Mitochondrial Dysfunction and Impaired Fatty Acid Metabolism in Plasma of Patients with Post-Acute Sequelae of COVID-19 (PASC)

Exercise intolerance is a major manifestation of post-acute sequelae of severe acute respiratory syndrome coronavirus infection (PASC, or "long-COVID"). Exercise intolerance in PASC is associated with higher arterial blood lactate accumulation and lower fatty acid oxidation rates during graded exercise tests to volitional exertion, suggesting altered metabolism and mitochondrial dysfunction. It remains unclear whether the profound disturbances in metabolism that have been identified in plasma from patients suffering from acute coronavirus disease 2019 (COVID-19) are also present in PASC. To bridge this gap, individuals with a history of previous acute COVID-19 infection that did not require hospitalization were enrolled at National Jewish Health (Denver, CO, USA) and were grouped into those that developed PASC (n = 29) and those that fully recovered (n = 16). Plasma samples from the two groups were analyzed via mass spectrometry-based untargeted metabolomics and compared against plasma metabolic profiles of healthy control individuals (n = 30). Observational demographic and clinical data were retrospectively abstracted from the medical record. Compared to plasma of healthy controls or individuals who recovered from COVID-19, PASC plasma exhibited significantly higher free- and carnitine-conjugated mono-, poly-, and highly unsaturated fatty acids, accompanied by markedly lower levels of mono-, di- and tricarboxylates (pyruvate, lactate, citrate, succinate, and malate), polyamines (spermine) and taurine. Plasma from individuals who fully recovered from COVID-19 exhibited an intermediary metabolic phenotype, with milder disturbances in fatty acid metabolism and higher levels of spermine and taurine. Of note, depletion of tryptophan-a hallmark of disease severity in COVID-19-is not normalized in PASC patients, despite normalization of kynurenine levels-a tryptophan metabolite that predicts mortality in hospitalized COVID-19 patients. In conclusion, PASC plasma metabolites are indicative of altered fatty acid metabolism and dysfunctional mitochondria-dependent lipid catabolism. These metabolic profiles obtained at rest are consistent with previously reported mitochondrial dysfunction during exercise, and may pave the way for therapeutic intervention focused on restoring mitochondrial fat-burning capacity.

The tryptophan catabolite or kynurenine pathway in major depressive and bipolar disorder: A systematic review and meta-analysis

Background

There is now evidence that affective disorders including major depressive disorder (MDD) and bipolar disorder (BD) are mediated by immune-inflammatory and nitro-oxidative pathways. Activation of these pathways may be associated with activation of the tryptophan catabolite (TRYCAT) pathway by inducing indoleamine 2,3-dioxygenase (IDO, the rate-limiting enzyme) leading to depletion of tryptophan (TRP) and increases in tryptophan catabolites (TRYCATs).

Aims

To systematically review and meta-analyze central and peripheral (free and total) TRP levels, its competing amino-acids (CAAs) and TRYCATs in MDD and BD.

Methods

This review searched PubMed, Google Scholar and SciFinder and included 121 full-text articles and 15470 individuals, including 8024 MDD/BD patients and 7446 healthy controls.

Results

TRP levels (either free and total) and the TRP/CAAs ratio were significantly decreased (p < 0.0001) in MDD/BD as compared with controls with a moderate effect size (standardized mean difference for TRP: SMD = -0.513, 95% confidence interval, CI: -0.611; -0.414; and TRP/CAAs: SMD = -0.558, CI: -0.758; -0.358). Kynurenine (KYN) levels were significantly decreased in patients as compared with controls with a small effect size (p < 0.0001, SMD = -0.213, 95%CI: -0.295; -0.131). These differences were significant in plasma (p < 0.0001, SMD = -0.304, 95%CI: -0.415, -0.194) but not in serum (p = 0.054) or the central nervous system (CNS, p = 0.771). The KYN/TRP ratio, frequently used as an index of IDO activity, and neurotoxicity indices based on downstream TRYCATs were unaltered or even lowered in MDD/BD.

Conclusions

Our findings suggest that MDD and BD are accompanied by TRP depletion without IDO and TRYCAT pathway activation. Lowered TRP availability is probably the consequence of lowered serum albumin during the inflammatory response in affective disorders.

Is SARS-CoV-2 a Risk Factor of Bipolar Disorder?-A Narrative Review

For 2.5 years we have been facing the coronavirus disease (COVID-19) and its health, social and economic effects. One of its known consequences is the development of neuropsychiatric diseases such as anxiety and depression. However, reports of manic episodes related to COVID-19 have emerged. Mania is an integral part of the debilitating illness-bipolar disorder (BD). Due to its devastating effects, it is therefore important to establish whether SARS-CoV-2 infection is a causative agent of this severe mental disorder. In this narrative review, we discuss the similarities between the disorders caused by SARS-CoV-2 and those found in patients with BD, and we also try to answer the question of whether SARS-CoV-2 infection may be a risk factor for the development of this affective disorder. Our observation shows that disorders in COVID-19 showing the greatest similarity to those in BD are cytokine disorders, tryptophan metabolism, sleep disorders and structural changes in the central nervous system (CNS). These changes, especially intensified in severe infections, may be a trigger for the development of BD in particularly vulnerable people, e.g., with family history, or cause an acute episode in patients with a pre-existing BD.

The Tryptophan Catabolite or Kynurenine Pathway in a Major Depressive Episode with Melancholia, Psychotic Features and Suicidal Behaviors: A Systematic Review and Meta-Analysis

Major depressive disorder (MDD) and bipolar disorder (BD) with melancholia and psychotic features and suicidal behaviors are accompanied by activated immune-inflammatory and oxidative pathways, which may stimulate indoleamine 2,3-dioxygenase (IDO), the first and rate-limiting enzyme of the tryptophan catabolite (TRYCAT) pathway resulting in increased tryptophan degradation and elevated tryptophan catabolites (TRYCTAs). The purpose of the current study is to systematically review and meta-analyze levels of TRP, its competing amino acids (CAAs) and TRYCATs in patients with severe affective disorders. Methods: PubMed, Google Scholar and SciFinder were searched in the present study and we recruited 35 studies to examine 4647 participants including 2332 unipolar (MDD) and bipolar (BD) depressed patients and 2315 healthy controls. Severe patients showed significant lower (p < 0.0001) TRP (standardized mean difference, SMD = −0.517, 95% confidence interval, CI: −0.735; −0.299) and TRP/CAAs (SMD = −0.617, CI: −0.957; −0.277) levels with moderate effect sizes, while no significant difference in CAAs were found. Kynurenine (KYN) levels were unaltered in severe MDD/BD phenotypes, while the KYN/TRP ratio showed a significant increase only in patients with psychotic features (SMD = 0.224, CI: 0.012; 0.436). Quinolinic acid (QA) was significantly increased (SMD = 0.358, CI: 0.015; 0.701) and kynurenic acid (KA) significantly decreased (SMD = −0.260, CI: −0.487; −0.034) in severe MDD/BD. Patients with affective disorders with melancholic and psychotic features and suicidal behaviors showed normal IDO enzyme activity but a lowered availability of plasma/serum TRP to the brain, which is probably due to other processes such as low albumin levels.

Kynurenine serves as useful biomarker in acute, Long- and Post-COVID-19 diagnostics

Introduction

In patients with SARS-CoV-2, innate immunity is playing a central role, depicted by hyperinflammation and longer lasting inflammatory response. Reliable inflammatory markers that cover both acute and long-lasting COVID-19 monitoring are still lacking. Thus, we investigated one specific inflammatory marker involved as one key player of the immune system, kynurenine (Kyn), and its use for diagnosis/detection of the Long-/Post-COVID syndrome in comparison to currently used markers in both serum and saliva samples.

Material and methods

The study compromised in total 151 inpatients with a SARS-CoV-2 infection hospitalized between 03/2020 and 09/2021. The group NC (normal controls) included blood bank donors (n=302, 144f/158m, mean age 47.1 ± 18.3 years (range 18-75)). Two further groups were generated based on Group A (n=85, 27f/58m, mean age 63.1 ± 18.3 years (range 19-90), acute admission to the hospital) and Group B (n=66, 22f/44m, mean age 66.6 ± 17.6 years (range 17-90), admitted either for weaning or for rehabilitation period due to Long-COVID symptoms/syndrome). Plasma concentrations of Kyn, C-Reactive Protein (CRP) and interleukin-6 (IL-6) were measured on admission. In Group B we determined Kyn 4 weeks after the negative PCR-test. In a subset of patients (n=11) concentrations of Kyn and CRP were measured in sera and saliva two, three and four months after dismission. We identified 12 patients with Post-COVID symptoms >20 weeks with still significant elevated Kyn-levels.

Results

Mean values for NC used as reference were 2.79 ± 0.61 µM, range 1.2-4.1 µM. On admission, patients showed significantly higher concentrations of Kyn compared to NC (p-values < 0.001). Kyn significantly correlated with IL-6 peak-values (r=0.411; p-values <0.001) and CRP (r=0.488, p-values<0.001). Kyn values in Group B (Long-/Post-COVID) showed still significant higher values (8.77 ± 1.72 µM, range 5.5-16.6 µM), whereas CRP values in Group B were in the normal range.

Conclusion

Serum and saliva Kyn are reflecting the acute and long-term pathophysiology of the SARS-CoV-2 disease concerning the innate immune response and thus may serve a useful biomarker for diagnosis and monitoring both Long- and Post-COVID syndrome and its therapy.

Lowered Quality of Life in Long COVID Is Predicted by Affective Symptoms, Chronic Fatigue Syndrome, Inflammation and Neuroimmunotoxic Pathways

The physio-affective phenome of Long COVID-19 is predicted by (a) immune-inflammatory biomarkers of the acute infectious phase, including peak body temperature (PBT) and oxygen saturation (SpO2), and (b) the subsequent activation of immune and oxidative stress pathways during Long COVID. The purpose of this study was to delineate the effects of PBT and SpO2 during acute infection, as well as the increased neurotoxicity on the physical, psychological, social and environmental domains of health-related quality of life (HR-QoL) in people with Long COVID. We recruited 86 participants with Long COVID and 39 normal controls, assessed the WHO-QoL-BREF (World Health Organization Quality of Life Instrument-Abridged Version, Geneva, Switzerland) and the physio-affective phenome of Long COVID (comprising depression, anxiety and fibromyalgia-fatigue rating scales) and measured PBT and SpO2 during acute infection, and neurotoxicity (NT, comprising serum interleukin (IL)-1β, IL-18 and caspase-1, advanced oxidation protein products and myeloperoxidase, calcium and insulin resistance) in Long COVID. We found that 70.3% of the variance in HR-QoL was explained by the regression on the physio-affective phenome, lowered calcium and increased NT, whilst 61.5% of the variance in the physio-affective phenome was explained by calcium, NT, increased PBT, lowered SpO2, female sex and vaccination with AstraZeneca and Pfizer. The effects of PBT and SpO2 on lowered HR-QoL were mediated by increased NT and lowered calcium yielding increased severity of the physio-affective phenome which largely affects HR-QoL. In conclusion, lowered HR-Qol in Long COVID is largely predicted by the severity of neuro-immune and neuro-oxidative pathways during acute and Long COVID.