Kynurenic acid may underlie sex-specific immune responses to COVID-19

Validation of two LCHRMS methods for large-scale untargeted metabolomics of serum samples: Strategy to establish method fitness-for-purpose

Untargeted metabolomics by LCHRMS is a powerful tool to enhance our knowledge of pathophysiological processes. Whereas validation of a bioanalytical method is customary in most analytical chemistry fields, it is rarely performed for untargeted metabolomics. This study aimed to establish and validate an analytical platform for a long-term, clinical metabolomics study. Sample preparation was performed with an automated liquid handler and four analytical methods were developed and evaluated. The validation study spanned three batches with twelve runs using individual serum samples and various quality control samples. Data was acquired with untargeted acquisition and only metabolites identified at level 1 were evaluated. Validation parameters were set to evaluate key performance metrics relevant for the intended application: reproducibility, repeatability, stability, and identification selectivity, emphasizing dataset intrinsic variance. Concordance of semi-quantitative results between methods was evaluated to identify potential bias. Spearman rank correlation coefficients (rs) were calculated from individual serum samples. Of the four methods tested, two were selected for validation. A total of 47 and 55 metabolites (RPLC-ESI+- and HILIC-ESI--HRMS, respectively) met specified validation criteria. Quality assurance involved system suitability testing, sample release, run release, and batch release. The median repeatability and within-run reproducibility as coefficient of variation% for metabolites that passed validation on RPLC-ESI+- and HILIC-ESI--HRMS were 4.5 and 4.6, and 1.5 and 3.8, respectively. Metabolites that passed validation on RPLC-ESI+-HRMS had a median D-ratio of 1.91, and 89 % showed good signal intensity after ten-fold dilution. The corresponding numbers for metabolites with the HILIC-ESI--HRMS method was 1.45 and 45 %, respectively. The rs median ({range}) for metabolites that passed validation on RPLC-ESI+- was 0.93 (N = 9 {0.69-0.98}) and on HILIC-ESI--HRMS was 0.93 (N = 22 {0.55-1.00}). The validated methods proved fit-for-purpose and the laboratory thus demonstrated its capability to produce reliable results for a large-scale, untargeted metabolomics study. This validation not only bolsters the reliability of the assays but also significantly enhances the impact and credibility of the hypotheses generated from the studies. Therefore, this validation study serves as a benchmark in the documentation of untargeted metabolomics, potentially guiding future endeavors in the field.

Sex Differences in the Blood Metabolome During Acute Response to Ischemic Stroke

Introduction: Females suffer greater lifetime risk of stroke and greater morbidity and mortality from stroke compared with males. This study's objective was to identify differences in metabolomic profiling of females and males with stroke and which differences were associated with neurological outcome. Methods: Females and males with acute ischemic stroke enrolled in the Emergency Medicine Specimen Bank at a comprehensive stroke center provided whole blood samples upon arrival for mass spectrometry-based metabolomics. We used descriptive statistics to characterize the cohort. A linear regression model was fit for individual metabolites to determine differences in relative abundance between males and females while controlling for covariates (age, race/ethnicity, postmenopausal status, cardiovascular risk factors, depression, time between sample collection and last known well, and initial National Institutes of Health Stroke Scale [NIHSS] score). For each differentially expressed metabolite, a linear regression model was fit to determine the association between the metabolite and NIHSS at 24 hours after admission while controlling for the covariates and acute treatments. Results: After adjusting for covariates, eight metabolites differed in females and males with a stroke. These included amino acids or their metabolites (proline and tryptophan), nucleotides (guanosine diphosphate [GDP], and inosine-3',5'-cyclic monophosphate), citrate, dehydroascorbate, choline, and acylcarnitine-(5-OH). GDP and dehydroascorbate were significantly associated with 24-hour NIHSS (p = 0.0991). Conclusions: Few metabolites were differentially abundant in blood after a stroke when comparing females with males and controlling for confounders, but the interactions between biological sex and GDP, as well as biological sex and dehydroascorbate, were associated with 24-hour neurological function. This has important implications for future studies that evaluate the therapeutic potential of these metabolites in ischemic stroke.

The roles of the kynurenine pathway in COVID-19 neuropathogenesis

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of the highly contagious respiratory disease Corona Virus Disease 2019 (COVID-19) that may lead to various neurological and psychological disorders that can be acute, lasting days to weeks or months and possibly longer. The latter is known as long-COVID or more recently post-acute sequelae of COVID (PASC). During acute COVID-19 infection, a strong inflammatory response, known as the cytokine storm, occurs in some patients. The levels of interferon-γ (IFN-γ), interferon-β (IFN-β), interleukin-6 (IL-6) and tumour necrosis factor-alpha (TNF-α) are particularly increased. These cytokines are known to activate the enzyme indoleamine 2,3-dioxygenase 1 (IDO-1), catalysing the first step of tryptophan (Trp) catabolism through the kynurenine pathway (KP) leading to the production of several neurotoxic and immunosuppressive metabolites. There is already data showing elevation in KP metabolites both acutely and in PASC, especially regarding cognitive impairment. Thus, it is likely that KP involvement is significant in SARS-CoV-2 pathogenesis especially neurologically.

Metabolic predictors of COVID-19 mortality and severity: a survival analysis

Introduction

The global healthcare burden of COVID-19 pandemic has been unprecedented with a high mortality. Metabolomics, a powerful technique, has been increasingly utilized to study the host response to infections and to understand the progression of multi-system disorders such as COVID-19. Analysis of the host metabolites in response to SARS-CoV-2 infection can provide a snapshot of the endogenous metabolic landscape of the host and its role in shaping the interaction with SARS-CoV-2. Disease severity and consequently the clinical outcomes may be associated with a metabolic imbalance related to amino acids, lipids, and energy-generating pathways. Hence, the host metabolome can help predict potential clinical risks and outcomes.

Methods

In this prospective study, using a targeted metabolomics approach, we studied the metabolic signature in 154 COVID-19 patients (males=138, age range 48-69 yrs) and related it to disease severity and mortality. Blood plasma concentrations of metabolites were quantified through LC-MS using MxP Quant 500 kit, which has a coverage of 630 metabolites from 26 biochemical classes including distinct classes of lipids and small organic molecules. We then employed Kaplan-Meier survival analysis to investigate the correlation between various metabolic markers, disease severity and patient outcomes.

Results

A comparison of survival outcomes between individuals with high levels of various metabolites (amino acids, tryptophan, kynurenine, serotonin, creatine, SDMA, ADMA, 1-MH and carnitine palmitoyltransferase 1 and 2 enzymes) and those with low levels revealed statistically significant differences in survival outcomes. We further used four key metabolic markers (tryptophan, kynurenine, asymmetric dimethylarginine, and 1-Methylhistidine) to develop a COVID-19 mortality risk model through the application of multiple machine-learning methods.

Conclusions

Metabolomics analysis revealed distinct metabolic signatures among different severity groups, reflecting discernible alterations in amino acid levels and perturbations in tryptophan metabolism. Notably, critical patients exhibited higher levels of short chain acylcarnitines, concomitant with higher concentrations of SDMA, ADMA, and 1-MH in severe cases and non-survivors. Conversely, levels of 3-methylhistidine were lower in this context.

Urinary phenotyping of SARS-CoV-2 infection connects clinical diagnostics with metabolomics and uncovers impaired NAD+ pathway and SIRT1 activation

OBJECTIVES

The stratification of individuals suffering from acute and post-acute SARS-CoV-2 infection remains a critical challenge. Notably, biomarkers able to specifically monitor viral progression, providing details about patient clinical status, are still not available. Herein, quantitative metabolomics is progressively recognized as a useful tool to describe the consequences of virus-host interactions considering also clinical metadata.

METHODS

The present study characterized the urinary metabolic profile of 243 infected individuals by quantitative nuclear magnetic resonance (NMR) spectroscopy and liquid chromatography mass spectrometry (LC-MS). Results were compared with a historical cohort of noninfected subjects. Moreover, we assessed the concentration of recently identified antiviral nucleosides and their association with other metabolites and clinical data.

RESULTS

Urinary metabolomics can stratify patients into classes of disease severity, with a discrimination ability comparable to that of clinical biomarkers. Kynurenines showed the highest fold change in clinically-deteriorated patients and higher-risk subjects. Unique metabolite clusters were also generated based on age, sex, and body mass index (BMI). Changes in the concentration of antiviral nucleosides were associated with either other metabolites or clinical variables. Increased kynurenines and reduced trigonelline excretion indicated a disrupted nicotinamide adenine nucleotide (NAD+) and sirtuin 1 (SIRT1) pathway.

CONCLUSIONS

Our results confirm the potential of urinary metabolomics for noninvasive diagnostic/prognostic screening and show that the antiviral nucleosides could represent novel biomarkers linking viral load, immune response, and metabolism. Moreover, we established for the first time a casual link between kynurenine accumulation and deranged NAD+/SIRT1, offering a novel mechanism through which SARS-CoV-2 manipulates host physiology.

Novel COVID-19 biomarkers identified through multi-omics data analysis: N-acetyl-4-O-acetylneuraminic acid, N-acetyl-L-alanine, N-acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate

This study aims to apply machine learning models to identify new biomarkers associated with the early diagnosis and prognosis of SARS-CoV-2 infection.Plasma and serum samples from COVID-19 patients (mild, moderate, and severe), patients with other pneumonia (but with negative COVID-19 RT-PCR), and healthy volunteers (control) from hospitals in four different countries (China, Spain, France, and Italy) were analyzed by GC-MS, LC-MS, and NMR. Machine learning models (PCA and PLS-DA) were developed to predict the diagnosis and prognosis of COVID-19 and identify biomarkers associated with these outcomes.A total of 1410 patient samples were analyzed. The PLS-DA model presented a diagnostic and prognostic accuracy of around 95% of all analyzed data. A total of 23 biomarkers (e.g., spermidine, taurine, L-aspartic, L-glutamic, L-phenylalanine and xanthine, ornithine, and ribothimidine) have been identified as being associated with the diagnosis and prognosis of COVID-19. Additionally, we also identified for the first time five new biomarkers (N-Acetyl-4-O-acetylneuraminic acid, N-Acetyl-L-Alanine, N-Acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate) that are also associated with the severity and diagnosis of COVID-19. These five new biomarkers were elevated in severe COVID-19 patients compared to patients with mild disease or healthy volunteers.The PLS-DA model was able to predict the diagnosis and prognosis of COVID-19 around 95%. Additionally, our investigation pinpointed five novel potential biomarkers linked to the diagnosis and prognosis of COVID-19: N-Acetyl-4-O-acetylneuraminic acid, N-Acetyl-L-Alanine, N-Acetyltriptophan, palmitoylcarnitine, and glycerol 1-myristate. These biomarkers exhibited heightened levels in severe COVID-19 patients compared to those with mild COVID-19 or healthy volunteers.

Scientific rationale for the use of α2A-adrenoceptor agonists in treating neuroinflammatory cognitive disorders

Neuroinflammatory disorders preferentially impair the higher cognitive and executive functions of the prefrontal cortex (PFC). This includes such challenging disorders as delirium, perioperative neurocognitive disorder, and the sustained cognitive deficits from "long-COVID" or traumatic brain injury. There are no FDA-approved treatments for these symptoms; thus, understanding their etiology is important for generating therapeutic strategies. The current review describes the molecular rationale for why PFC circuits are especially vulnerable to inflammation, and how α2A-adrenoceptor (α2A-AR) actions throughout the nervous and immune systems can benefit the circuits in PFC needed for higher cognition. The layer III circuits in the dorsolateral PFC (dlPFC) that generate and sustain the mental representations needed for higher cognition have unusual neurotransmission and neuromodulation. They are wholly dependent on NMDAR neurotransmission, with little AMPAR contribution, and thus are especially vulnerable to kynurenic acid inflammatory signaling which blocks NMDAR. Layer III dlPFC spines also have unusual neuromodulation, with cAMP magnification of calcium signaling in spines, which opens nearby potassium channels to rapidly weaken connectivity and reduce neuronal firing. This process must be tightly regulated, e.g. by mGluR3 or α2A-AR on spines, to prevent loss of firing. However, the production of GCPII inflammatory signaling reduces mGluR3 actions and markedly diminishes dlPFC network firing. Both basic and clinical studies show that α2A-AR agonists such as guanfacine can restore dlPFC network firing and cognitive function, through direct actions in the dlPFC, but also by reducing the activity of stress-related circuits, e.g. in the locus coeruleus and amygdala, and by having anti-inflammatory actions in the immune system. This information is particularly timely, as guanfacine is currently the focus of large clinical trials for the treatment of delirium, and in open label studies for the treatment of cognitive deficits from long-COVID.

Tumor Microenvironment Activated Photoacoustic-Fluorescence Bimodal Nanoprobe for Precise Chemo-immunotherapy and Immune Response Tracing of Glioblastoma

Synergistic therapy strategy and prognostic monitoring of glioblastoma's immune response to treatment are crucial to optimize patient care and advance clinical outcomes. However, current systemic temozolomide (TMZ) chemotherapy and imaging methods for in vivo tracing of immune responses are inadequate. Herein, we report an all-in-one theranostic nanoprobe (PEG/αCD25-Cy7/TMZ) for precise chemotherapy and real-time immune response tracing of glioblastoma by photoacoustic-fluorescence imaging. The nanoprobe was loaded with TMZ and targeted regulatory T lymphocyte optical dye αCD25-Cy7 encapsulated by glutathione-responsive DSPE-SS-PEG2000. The results showed that the targeted efficiency of the nanoprobe to regulatory T lymphocytes is up to 92.3%. The activation of PEG/αCD25-Cy7/TMZ by glutathione enhanced the precise delivery of TMZ to the tumor microenvironment for local chemotherapy and monitored glioblastoma's boundary by photoacoustic-fluorescence imaging. Immunotherapy with indoleamine 2,3-dioxygenase inhibitors after chemotherapy could promote immunological responses and reduce regulatory T lymphocyte infiltration, which could improve the survival rate. Photoacoustic imaging has in real-time and noninvasively depicted the dynamic process of immune response on a micrometer scale, showing that the infiltration of regulatory T lymphocytes after chemotherapy was up-regulated and would down-regulate after IDO inhibitor treatment. This all-in-one theranostic strategy is a promising method for precisely delivering TMZ and long-term dynamically tracing regulatory T lymphocytes to evaluate the immune response in situ for accurate tumor chemo-immunotherapy.

Metabolomics-directed nanotechnology in viral diseases management: COVID-19 a case study

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently regarded as the twenty-first century's plague accounting for coronavirus disease 2019 (COVID-19). Besides its reported symptoms affecting the respiratory tract, it was found to alter several metabolic pathways inside the body. Nanoparticles proved to combat viral infections including COVID-19 to demonstrate great success in developing vaccines based on mRNA technology. However, various types of nanoparticles can affect the host metabolome. Considering the increasing proportion of nano-based vaccines, this review compiles and analyses how COVID-19 and nanoparticles affect lipids, amino acids, and carbohydrates metabolism. A search was conducted on PubMed, ScienceDirect, Web of Science for available information on the interrelationship between metabolomics and immunity in the context of SARS-CoV-2 infection and the effect of nanoparticles on metabolite levels. It was clear that SARS-CoV-2 disrupted several pathways to ensure a sufficient supply of its building blocks to facilitate its replication. Such information can help in developing treatment strategies against viral infections and COVID-19 based on interventions that overcome these metabolic changes. Furthermore, it showed that even drug-free nanoparticles can exert an influence on biological systems as evidenced by metabolomics.

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.

Untargeted metabonomic analysis of a cerebral stroke model in rats: a study based on UPLC-MS/MS

Introduction

Brain tissue damage caused by ischemic stroke can trigger changes in the body's metabolic response, and understanding the changes in the metabolic response of the gut after stroke can contribute to research on poststroke brain function recovery. Despite the increase in international research on poststroke metabolic mechanisms and the availability of powerful research tools in recent years, there is still an urgent need for poststroke metabolic studies. Metabolomic examination of feces from a cerebral ischemia-reperfusion rat model can provide new insights into poststroke metabolism and identify key metabolic pathways, which will help reveal diagnostic and therapeutic targets as well as inspire pathophysiological studies after stroke.

Methods

We randomly divided 16 healthy adult pathogen-free male Sprague-Dawley (SD) rats into the normal group and the study group, which received middle cerebral artery occlusion/reperfusion (MCAO/R). Ultra-performance liquid chromatography-tandem mass spectrometry (UPLCMS/MS) was used to determine the identities and concentrations of metabolites across all groups, and filtered high-quality data were analyzed for differential screening and differential metabolite functional analysis.

Results

After 1 and 14 days of modeling, compared to the normal group, rats in the study group showed significant neurological deficits (p < 0.001) and significantly increased infarct volume (day 1: p < 0.001; day 14: p = 0.001). Mass spectra identified 1,044 and 635 differential metabolites in rat feces in positive and negative ion modes, respectively, which differed significantly between the normal and study groups. The metabolites with increased levels identified in the study group were involved in tryptophan metabolism (p = 0.036678, p < 0.05), arachidonic acid metabolism (p = 0.15695), cysteine and methionine metabolism (p = 0.24705), and pyrimidine metabolism (p = 0.3413), whereas the metabolites with decreased levels were involved in arginine and proline metabolism (p = 0.15695) and starch and sucrose metabolism (p = 0.52256).

Discussion

We determined that UPLC-MS/MS could be employed for untargeted metabolomics research. Moreover, tryptophan metabolic pathways may have been disordered in the study group. Alterations in the tryptophan metabolome may provide additional theoretical and data support for elucidating stroke pathogenesis and selecting pathways for intervention.

The kynurenine pathway relates to post-acute COVID-19 objective cognitive impairment and PASC

OBJECTIVE

To determine the prevalence and natural history of post-acute COVID-19 objective cognitive impairment and function, and their relationship to demographic, clinical factors, post-acute sequelae of COVID-19 (PASC), and biomarkers.

METHODS

A total of 128 post-acute COVID-19 patients (age = 46 ± 15; 42% women, acute disease severity: not hospitalized: 38.6% mild: 0-1 symptoms, 52% 2+ symptoms; 9.4% hospitalized) completed standard cognition, olfaction, and mental health examinations 2-, 4-, and 12-month post diagnosis. Over the same time frame, WHO-defined PASC was determined. Blood cytokines, peripheral neurobiomarkers, and kynurenine pathway (KP) metabolites were measured. Objective cognitive function was demographically/practice corrected, and impairment prevalence was determined using the evidence-based Global Deficit Score method to detect at least mild cognitive impairment (GDS > 0.5). Linear mixed effect regression models with time effect (month post diagnosis) evaluated the relationships to cognition.

RESULTS

Across the 12-month study period, mild to moderate cognitive impairment ranged from 16% to 26%, and 46.5% were impaired at least once. Impairment associated with poorer work capacity (p < 0.05), and 2-month objectively tested anosmia (p < 0.05). PASC with (p = 0.01) and without disability (p < 0.03) associated with acute COVID-19 severity. KP measures showed prolonged activation (2 to 8 months) (p < 0.0001) linked to IFN-beta in those with PASC. Of the blood analytes, only the KP metabolites (elevated quinolinic acid, 3-hydroxyanthranilic acid, kynurenine, the kynurenine/tryptophan ratio) associated (p < 0.001) with poorer cognitive performance and greater likelihood of impairment. PASC, independent of disability associated with abnormal kynurenine/tryptophan (p < 0.03).

INTERPRETATION

The kynurenine pathway relates to post-acute COVID-19 objective cognitive impairment and PASC, thereby enabling biomarker and therapeutic possibilities.

Scientific Rationale for the Treatment of Cognitive Deficits from Long COVID

Sustained cognitive deficits are a common and debilitating feature of "long COVID", but currently there are no FDA-approved treatments. The cognitive functions of the dorsolateral prefrontal cortex (dlPFC) are the most consistently afflicted by long COVID, including deficits in working memory, motivation, and executive functioning. COVID-19 infection greatly increases kynurenic acid (KYNA) and glutamate carboxypeptidase II (GCPII) in brain, both of which can be particularly deleterious to PFC function. KYNA blocks both NMDA and nicotinic-alpha-7 receptors, the two receptors required for dlPFC neurotransmission, and GCPII reduces mGluR3 regulation of cAMP-calcium-potassium channel signaling, which weakens dlPFC network connectivity and reduces dlPFC neuronal firing. Two agents approved for other indications may be helpful in restoring dlPFC physiology: the antioxidant N-acetyl cysteine inhibits the production of KYNA, and the α2A-adrenoceptor agonist guanfacine regulates cAMP-calcium-potassium channel signaling in dlPFC and is also anti-inflammatory. Thus, these agents may be helpful in treating the cognitive symptoms of long COVID.

Neutrophil metabolomics in severe COVID-19 reveal GAPDH as a suppressor of neutrophil extracellular trap formation

Severe COVID-19 is characterized by an increase in the number and changes in the function of innate immune cells including neutrophils. However, it is not known how the metabolome of immune cells changes in patients with COVID-19. To address these questions, we analyzed the metabolome of neutrophils from patients with severe or mild COVID-19 and healthy controls. We identified widespread dysregulation of neutrophil metabolism with disease progression including in amino acid, redox, and central carbon metabolism. Metabolic changes in neutrophils from patients with severe COVID-19 were consistent with reduced activity of the glycolytic enzyme GAPDH. Inhibition of GAPDH blocked glycolysis and promoted pentose phosphate pathway activity but blunted the neutrophil respiratory burst. Inhibition of GAPDH was sufficient to cause neutrophil extracellular trap (NET) formation which required neutrophil elastase activity. GAPDH inhibition increased neutrophil pH, and blocking this increase prevented cell death and NET formation. These findings indicate that neutrophils in severe COVID-19 have an aberrant metabolism which can contribute to their dysfunction. Our work also shows that NET formation, a pathogenic feature of many inflammatory diseases, is actively suppressed in neutrophils by a cell-intrinsic mechanism controlled by GAPDH.

Plasma metabolomic characterization of SARS-CoV-2 Omicron infection

Omicron variants of SARS-CoV-2 have spread rapidly worldwide; however, most infected patients have mild or no symptoms. This study aimed to understand the host response to Omicron infections by performing metabolomic profiling of plasma. We observed that Omicron infections triggered an inflammatory response and innate immune, and adaptive immunity was suppressed, including reduced T-cell response and immunoglobulin antibody production. Similar to the original SARS-CoV-2 strain circulating in 2019, the host developed an anti-inflammatory response and accelerated energy metabolism in response to Omicron infection. However, differential regulation of macrophage polarization and reduced neutrophil function has been observed in Omicron infections. Interferon-induced antiviral immunity was not as strong in Omicron infections as in the original SARS-CoV-2 infections. The host response to Omicron infections increased antioxidant capacity and liver detoxification more than in the original strain. Hence, these findings suggest that Omicron infections cause weaker inflammatory alterations and immune responses than the original SARS-CoV-2 strain.

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.

COVID-19 severity and in-hospital mortality in an area with high HIV prevalence

Background

HIV infection causes immune dysregulation affecting T-cell and monocyte function, which may alter coronavirus disease 2019 (COVID-19) pathophysiology.

Objectives

We investigated the associations among clinical phenotypes, laboratory biomarkers, and hospitalisation outcomes in a cohort of people hospitalised with COVID-19 in a high HIV prevalence area.

Method

We conducted a prospective observational cohort study in Tshwane, South Africa. Respiratory disease severity was quantified using the respiratory oxygenation score. Analysed biomarkers included inflammatory and coagulation biomarkers, CD4 T-cell counts, and HIV-1 viral loads (HIVVL).

Results

The analysis included 558 patients, of whom 21.7% died during admission. The mean age was 54 years. A total of 82 participants were HIV-positive. People living with HIV (PLWH) were younger (mean age 46 years) than HIV-negative people; most were on antiretroviral treatment with a suppressed HIVVL (72%) and the median CD4 count was 159 (interquartile range: 66-397) cells/µL. After adjusting for age, HIV was not associated with increased risk of mortality during hospitalisation (age-adjusted hazard ratio = 1.1, 95% confidence interval: 0.6-2.0). Inflammatory biomarker levels were similar in PLWH and HIV-negative patients. Detectable HIVVL was associated with less severe respiratory disease. In PLWH, mortality was associated with higher levels of inflammatory biomarkers. Opportunistic infections, and other risk factors for severe COVID-19, were common in PLWH who died.

Conclusion

PLWH were not at increased risk of mortality and those with detectable HIVVL had less severe respiratory disease than those with suppressed HIVVL.

What this study adds

This study advances our understanding of severe COVID-19 in PLWH.

Comprehensive investigation of pathway enrichment methods for functional interpretation of LC-MS global metabolomics data

BACKGROUND

Global or untargeted metabolomics is widely used to comprehensively investigate metabolic profiles under various pathophysiological conditions such as inflammations, infections, responses to exposures or interactions with microbial communities. However, biological interpretation of global metabolomics data remains a daunting task. Recent years have seen growing applications of pathway enrichment analysis based on putative annotations of liquid chromatography coupled with mass spectrometry (LC-MS) peaks for functional interpretation of LC-MS-based global metabolomics data. However, due to intricate peak-metabolite and metabolite-pathway relationships, considerable variations are observed among results obtained using different approaches. There is an urgent need to benchmark these approaches to inform the best practices.

RESULTS

We have conducted a benchmark study of common peak annotation approaches and pathway enrichment methods in current metabolomics studies. Representative approaches, including three peak annotation methods and four enrichment methods, were selected and benchmarked under different scenarios. Based on the results, we have provided a set of recommendations regarding peak annotation, ranking metrics and feature selection. The overall better performance was obtained for the mummichog approach. We have observed that a ~30% annotation rate is sufficient to achieve high recall (~90% based on mummichog), and using semi-annotated data improves functional interpretation. Based on the current platforms and enrichment methods, we further propose an identifiability index to indicate the possibility of a pathway being reliably identified. Finally, we evaluated all methods using 11 COVID-19 and 8 inflammatory bowel diseases (IBD) global metabolomics datasets.

Hemoglobin normalization outperforms other methods for standardizing dried blood spot metabolomics: A comparative study

Dried blood spot (DBS) metabolomics has numerous applications in newborn health screening, exposomics, and biomonitoring of environmental chemicals in pregnant women and the elderly. However, accurate metabolite quantification is hindered by several challenges: notably the "hematocrit effect" and unknown blood-spotting volumes. Different techniques have been employed to overcome these issues but there is no consensus on the optimal normalization method for DBS metabolomics, and in some cases no normalization is used. We compared five normalization methods (hemoglobin (Hb), specific gravity (SG), protein, spot weight, potassium (K+)) to unnormalized data, and assessed sex-related differences in the DBS metabolome in 21 adults (group 1, n = 10 males, n = 11 females). The performance of each normalization method was evaluated using multiple criteria: (a) reduction of intragroup variation (pooled median absolute deviation, pooled estimate of variance, pooled coefficient of variation, NMDS and principal component analysis), (b) effect on differential metabolic analysis (dendrogram, heatmap, p-value distribution), and (c) influence on classification accuracy (partial least squares discriminant analysis, sparse partial least squares discriminant analysis error rates, receiver operating curve, random forest out of bag error rate). Our results revealed that Hb normalization outperformed all the other methods based on the three criteria and 13 different parameters; the performance of Hb was further demonstrated in an independent group of DBS from 18 neonates (group 2, n = 9 males, n = 9 females). Furthermore, we showed that SG and Hb are correlated in adults (rs = 0.86, p < 0.001), and validated this relationship in an independent group of 18 neonates and infants (group 3) (rs = 0.84, p < 0.001). Using the equation, SG = -0.4814Hb2 + 2.44Hb + 0.005, SG can be used as a surrogate for normalization by Hb. This is the first comparative study to concurrently evaluate multiple normalization methods for DBS metabolomics which will serve as a robust methodological platform for future environmental epidemiological studies.

Metabolomics as a powerful tool for diagnostic, pronostic and drug intervention analysis in COVID-19

COVID-19 currently represents one of the major health challenges worldwide. Albeit its infectious character, with onset affectation mainly at the respiratory track, it is clear that the pathophysiology of COVID-19 has a systemic character, ultimately affecting many organs. This feature enables the possibility of investigating SARS-CoV-2 infection using multi-omic techniques, including metabolomic studies by chromatography coupled to mass spectrometry or by nuclear magnetic resonance (NMR) spectroscopy. Here we review the extensive literature on metabolomics in COVID-19, that unraveled many aspects of the disease including: a characteristic metabotipic signature associated to COVID-19, discrimination of patients according to severity, effect of drugs and vaccination treatments and the characterization of the natural history of the metabolic evolution associated to the disease, from the infection onset to full recovery or long-term and long sequelae of COVID.

Saliva metabolomic profile of COVID-19 patients associates with disease severity

INTRODUCTION

Coronavirus disease 2019 (COVID-19) is strongly linked to dysregulation of various molecular, cellular, and physiological processes that change abundance of different biomolecules including metabolites that may be ultimately used as biomarkers for disease progression and severity. It is important at early stage to readily distinguish those patients that are likely to progress to moderate and severe stages.

OBJECTIVES

This study aimed to investigate the utility of saliva and plasma metabolomic profiles as a potential parameter for risk stratifying COVID-19 patients.

METHOD

LC-MS/MS-based untargeted metabolomics were used to profile the changes in saliva and plasma metabolomic profiles of COVID-19 patients with different severities.

RESULTS

Saliva and plasma metabolites were screened in 62 COVID-19 patients and 18 non-infected controls. The COVID-19 group included 16 severe, 15 moderate, 16 mild, and 15 asymptomatic cases. Thirty-six differential metabolites were detected in COVID-19 versus control comparisons. SARS-CoV-2 induced metabolic derangement differed with infection severity. The metabolic changes were identified in saliva and plasma, however, saliva showed higher intensity of metabolic changes. Levels of saliva metabolites such as sphingosine and kynurenine were significantly different between COVID-19 infected and non-infected individuals; while linoleic acid and Alpha-ketoisovaleric acid were specifically increased in severe compared to non-severe patients. As expected, the two prognostic biomarkers of C-reactive protein and D-dimer were negatively correlated with sphingosine and 5-Aminolevulinic acid, and positively correlated with L-Tryptophan and L-Kynurenine.

CONCLUSION

Saliva disease-specific and severity-specific metabolite could be employed as potential COVID-19 diagnostic and prognostic biomarkers.

Untargeted plasma metabolomic fingerprinting highlights several biomarkers for the diagnosis and prognosis of coronavirus disease 19

Objectives

The COVID-19 pandemic has been a serious worldwide public health crisis since 2020 and is still challenging healthcare systems. New tools for the prognosis and diagnosis of COVID-19 patients remain important issues.

Design

Here, we studied the metabolome of plasma samples of COVID-19 patients for the identification of prognosis biomarkers.

Patients

Plasma samples of eighty-six SARS-CoV-2-infected subjects and 24 healthy controls were collected during the first peak of the COVID-19 pandemic in France in 2020.

Main results

Plasma metabolome fingerprinting allowed the successful discrimination of healthy controls, mild SARS-CoV-2 subjects, and moderate and severe COVID-19 patients at hospital admission. We found a strong effect of SARS-CoV-2 infection on the plasma metabolome in mild cases. Our results revealed that plasma lipids and alterations in their saturation level are important biomarkers for the detection of the infection. We also identified deoxy-fructosyl-amino acids as new putative plasma biomarkers for SARS-CoV-2 infection and COVID-19 severity. Finally, our results highlight a key role for plasma levels of tryptophan and kynurenine in the symptoms of COVID-19 patients.

Conclusion

Our results showed that plasma metabolome profiling is an efficient tool for the diagnosis and prognosis of SARS-CoV-2 infection.

Influenza vaccination and single cell multiomics reveal sex dimorphic immune imprints of prior mild COVID-19

Viral infections can have profound and durable functional impacts on the immune system. There is an urgent need to characterize the long-term immune effects of SARS-CoV-2 infection given the persistence of symptoms in some individuals and the continued threat of novel variants. Here we use systems immunology, including longitudinal multimodal single cell analysis (surface proteins, transcriptome, and V(D)J sequences) from 33 previously healthy individuals after recovery from mild, non-hospitalized COVID-19 and 40 age- and sex-matched healthy controls with no history of COVID-19 to comparatively assess the post-infection immune status (mean: 151 days after diagnosis) and subsequent innate and adaptive responses to seasonal influenza vaccination. Identification of both sex-specific and -independent temporally stable changes, including signatures of T-cell activation and repression of innate defense/immune receptor genes (e.g., Toll-like receptors) in monocytes, suggest that mild COVID-19 can establish new post-recovery immunological set-points. COVID-19-recovered males had higher innate, influenza-specific plasmablast, and antibody responses after vaccination compared to healthy males and COVID-19-recovered females, partly attributable to elevated pre-vaccination frequencies of a GPR56 expressing CD8+ T-cell subset in male recoverees that are "poised" to produce higher levels of IFNγ upon inflammatory stimulation. Intriguingly, by day 1 post-vaccination in COVID-19-recovered subjects, the expression of the repressed genes in monocytes increased and moved towards the pre-vaccination baseline of healthy controls, suggesting that the acute inflammation induced by vaccination could partly reset the immune states established by mild COVID-19. Our study reveals sex-dimorphic immune imprints and in vivo functional impacts of mild COVID-19 in humans, suggesting that prior COVID-19, and possibly respiratory viral infections in general, could change future responses to vaccination and in turn, vaccines could help reset the immune system after COVID-19, both in an antigen-agnostic manner.

COVID-19 metabolism: Mechanisms and therapeutic targets

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) dysregulates antiviral signaling, immune response, and cell metabolism in human body. Viral genome and proteins hijack host metabolic network to support viral biogenesis and propagation. However, the regulatory mechanism of SARS‐CoV‐2‐induced metabolic dysfunction has not been elucidated until recently. Multiomic studies of coronavirus disease 2019 (COVID‐19) revealed an intensive interaction between host metabolic regulators and viral proteins. SARS‐CoV‐2 deregulated cellular metabolism in blood, intestine, liver, pancreas, fat, and immune cells. Host metabolism supported almost every stage of viral lifecycle. Strikingly, viral proteins were found to interact with metabolic enzymes in different cellular compartments. Biochemical and genetic assays also identified key regulatory nodes and metabolic dependencies of viral replication. Of note, cholesterol metabolism, lipid metabolism, and glucose metabolism are broadly involved in viral lifecycle. Here, we summarized the current understanding of the hallmarks of COVID‐19 metabolism. SARS‐CoV‐2 infection remodels host cell metabolism, which in turn modulates viral biogenesis and replication. Remodeling of host metabolism creates metabolic vulnerability of SARS‐CoV‐2 replication, which could be explored to uncover new therapeutic targets. The efficacy of metabolic inhibitors against COVID‐19 is under investigation in several clinical trials. Ultimately, the knowledge of SARS‐CoV‐2‐induced metabolic reprogramming would accelerate drug repurposing or screening to combat the COVID‐19 pandemic.

Multiplex protein profiling of bronchial aspirates reveals disease-, mortality- and respiratory sequelae-associated signatures in critically ill patients with ARDS secondary to SARS-CoV-2 infection

Introduction

Bronchial aspirates (BAS) obtained during invasive mechanical ventilation (IMV) constitutes a useful tool for molecular phenotyping and decision making.

Aim

To identify the proteomic determinants associated with disease pathogenesis, all-cause mortality and respiratory sequelae in BAS samples from critically ill patients with SARS-CoV-2-induced ARDS.

Methods

Multicenter study including 74 critically ill patients with COVID-19 and non-COVID-19 ARDS. BAS were obtained by bronchoaspiration after IMV initiation. Three hundred sixty-four proteins were quantified using proximity extension assay (PEA) technology. Random forest models were used to assess predictor importance.

Results

After adjusting for confounding factors, CST5, NADK, SRPK2 and TGF-α were differentially detected in COVID-19 and non-COVID-19 patients. In random forest models for COVID-19, CST5, DPP7, NADK, KYAT1 and TYMP showed the highest variable importance. In COVID-19 patients, reduced levels of ENTPD2 and PTN were observed in nonsurvivors of ICU stay, even after adjustment. AGR2, NQO2, IL-1α, OSM and TRAIL showed the strongest associations with in-ICU mortality and were used to construct a protein-based prediction model. Kaplan-Meier curves revealed a clear separation in mortality risk between subgroups of PTN, ENTPD2 and the prediction model. Cox regression models supported these findings. In survivors, the levels of FCRL1, NTF4 and THOP1 in BAS samples obtained during the ICU stay correlated with lung function (i.e., D_LCO levels) 3 months after hospital discharge. Similarly, Flt3L and THOP1 levels were correlated with radiological features (i.e., TSS). These proteins are expressed in immune and nonimmune lung cells. Poor host response to viral infectivity and an inappropriate reparative mechanism seem to be linked with the pathogenesis of the disease and fatal outcomes, respectively.

Conclusion

BAS proteomics identified novel factors associated with the pathology of SARS-CoV-2-induced ARDS and its adverse outcomes. BAS-based protein testing emerges as a novel tool for risk assessment in the ICU.

Markers of fungal translocation are elevated during post-acute sequelae of SARS-CoV-2 and induce NF-κB signaling

Long COVID, a type of post-acute sequelae of SARS-CoV-2 (PASC), has been associated with sustained elevated levels of immune activation and inflammation. However, the mechanisms that drive this inflammation remain unknown. Inflammation during acute coronavirus disease 2019 could be exacerbated by microbial translocation (from the gut and/or lung) to blood. Whether microbial translocation contributes to inflammation during PASC is unknown. We did not observe a significant elevation in plasma markers of bacterial translocation during PASC. However, we observed higher levels of fungal translocation - measured as β-glucan, a fungal cell wall polysaccharide - in the plasma of individuals experiencing PASC compared with those without PASC or SARS-CoV-2-negative controls. The higher β-glucan correlated with higher inflammation and elevated levels of host metabolites involved in activating N-methyl-d-aspartate receptors (such as metabolites within the tryptophan catabolism pathway) with established neurotoxic properties. Mechanistically, β-glucan can directly induce inflammation by binding to myeloid cells (via Dectin-1) and activating Syk/NF-κB signaling. Using a Dectin-1/NF-κB reporter model, we found that plasma from individuals experiencing PASC induced higher NF-κB signaling compared with plasma from negative controls. This higher NF-κB signaling was abrogated by piceatannol (Syk inhibitor). These data suggest a potential targetable mechanism linking fungal translocation and inflammation during PASC.

Empagliflozin activates Wnt/β-catenin to stimulate FUNDC1-dependent mitochondrial quality surveillance against type-3 cardiorenal syndrome

Objectives

Cardiorenal syndrome type-3 (CRS-3) is an abrupt worsening of cardiac function secondary to acute kidney injury. Mitochondrial dysfunction is a key pathological mechanism of CRS-3, and empagliflozin can improve mitochondrial biology by promoting mitophagy. Here, we assessed the effects of empagliflozin on mitochondrial quality surveillance in a mouse model of CRS-3.

Methods

Cardiomyocyte-specific FUNDC1-knockout (FUNDC1^CKO) mice were subjected to CRS-3 prior to assessment of mitochondrial homeostasis in the presence or absence of empagliflozin.

Results

CRS-3 model mice exhibited lower heart function, increased inflammatory responses and exacerbated myocardial oxidative stress than sham-operated controls; however, empagliflozin attenuated these alterations. Empagliflozin stabilized the mitochondrial membrane potential, suppressed mitochondrial reactive oxygen species production, increased mitochondrial respiratory complex activity and restored the oxygen consumption rate in cardiomyocytes from CRS-3 model mice. Empagliflozin also normalized the mitochondrial morphology, mitochondrial dynamics and mitochondrial permeability transition pore opening rate in cardiomyocytes. Cardiomyocyte-specific ablation of FUN14 domain-containing protein 1 (FUNDC1) in mice abolished the protective effects of empagliflozin on mitochondrial homeostasis and myocardial performance. Empagliflozin activated β-catenin and promoted its nuclear retention, thus increasing FUNDC1-induced mitophagy in heart tissues; however, a β-catenin inhibitor reversed these effects.

Conclusions

In summary, empagliflozin activated Wnt/β-catenin to stimulate FUNDC1-dependent mitochondrial quality surveillance, ultimately improving mitochondrial function and cardiac performance during CRS-3. Thus, empagliflozin could be considered for the clinical management of heart function following acute kidney injury.

•

Empagliflozin reduces myocardial damage and improves myocardial function after CRS-3.

•

Empagliflozin normalizes the mitochondrial structure in cardiomyocytes during CRS-3.

•

Empagliflozin attenuates cardiomyocyte mitochondrial dysfunction during CRS-3.

•

Empagliflozin activates FUNDC1-dependent mitophagy and preserves mitochondrial integrity in the heart during CRS-3.

•

Loss of FUNDC1 abolishes the cardioprotective effects of empagliflozin during CRS-3.

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

Background

Coronavirus disease 2019 (COVID-19) is accompanied by activated immune-inflammatory pathways and oxidative stress, which both induce indoleamine-2,3-dioxygenase (IDO), a key enzyme of the tryptophan (TRP) catabolite (TRYCAT) pathway. The aim of this study was to systematically review and meta-analyze the status of the TRYCAT pathway, including the levels of TRP and kynurenine (KYN) and the activity of IDO, as measured by the ratio of KYN/TRP.

Methods

This systematic review searched PubMed, Google Scholar, and Web of Sciences and included 14 articles that compared TRP and tryptophan catabolites (TRYCATs) in COVID-19 patients versus non-COVID-19 controls, as well as severe/critical versus mild/moderate COVID-19. The analysis was done on a total of 1269 people, including 794 COVID-19 patients and 475 controls.

Results

The results show a significant (p < 0.0001) increase in the KYN/TRP ratio (standardized mean difference, SMD = 1.099, 95% confidence interval, CI: 0.714; 1.484) and KYN (SMD = 1.123, 95% CI: 0.730; 1.516) and significantly lower TRP (SMD = − 1.002, 95%CI: − 1.738; − 0.266) in COVID-19 versus controls. The KYN/TRP ratio (SMD = 0.945, 95%CI: 0.629; 1.262) and KYN (SMD = 0.806, 95%CI: 0.462; 1.149) were also significantly (p < 0.0001) higher and TRP lower (SMD = − 0.909, 95% CI: − 1.569; − 0.249) in severe/critical versus mild/moderate COVID-19. No significant difference was detected in kynurenic acid (KA) and the KA/KYN ratio between COVID-19 patients and controls.

Conclusions

Our results indicate increased activity of the IDO enzyme in COVID-19 and severe/critical patients. The TRYCAT pathway is implicated in the pathophysiology and progression of COVID-19 and may signal a worsening outcome of the disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07582-1.

An exploratory analysis of the response to ChAdOx1 nCoV-19 (AZD1222) vaccine in males and females

BACKGROUND

There are known differences in vaccine reactogenicity and immunogenicity by sex. Females have been shown to report greater reactogenicity and generate higher humoral and cellular immune responses than males following vaccination with several different vaccines. Whether this is also the case for COVID-19 vaccines is currently unknown, as COVID-19 vaccine study data disaggregated by sex are not routinely reported. Therefore, we have assessed the influence of sex on reactogenicity, immunogenicity and efficacy of COVID-19 vaccine ChAdOx1 nCoV-19.

METHODS

Vaccine efficacy was assessed in 15169 volunteers enrolled into single-blind randomised controlled trials of ChAdOx1 nCoV-19 in Brazil and the UK, with the primary endpoint defined as nucleic acid amplification test (NAAT)-positive symptomatic SARS-CoV-2 infection. All participants were electronically randomised to receive two standard doses of vaccine or the control product. Logistic regression models were fitted to explore the effect of age and sex on reactogenicity, and linear models fitted to log-transformed values for immunogenicity data. Reactogenicity data were taken from self-reported diaries of 788 trial participants. Pseudovirus neutralisation assay data were available from 748 participants and anti-SARS-CoV-2 spike IgG assay data from 1543 participants.

FINDINGS

7619 participants received ChAdOx1 nCoV-19 and 7550 received the control. Vaccine efficacy in participants after two doses of ChAdOx1 nCoV-19 (4243 females and 3376 males) was 66.1% (95% CI 55.9-73.9%) in males and 59.9% (95% CI 49.8-67.9%) in females; with no evidence of a difference in efficacy between the sexes (vaccine by sex interaction term P=0.3359). A small, statistically significant difference in anti-spike IgG was observed (adjusted GMR 1.14; 95% CI 1.04-1.26), with higher titres in females than males, but there were no statistically significant differences in other immunological endpoints. Whilst the majority of individuals reported at least one systemic reaction following a first dose of ChAdOx1 nCoV-19, females were twice as likely as males to report any systemic reaction after a first dose (OR 1.95; 95% CI 1.37-2.77). Measured fever of 38°C or above was reported in 5% of females and 1% of males following first doses. Headache and fatigue were the most commonly reported reactions in both sexes.

INTERPRETATION

Our results show that there is no evidence of difference in efficacy of the COVID-19 vaccine ChAdOx1 nCoV-19 in males and females. Greater reactogenicity in females was not associated with any difference in vaccine efficacy.

FUNDING

Studies were registered with ISRCTN 90906759 (COV002) and ISRCTN 89951424 (COV003) and follow-up is ongoing. Funding was received from the UK Research and Innovation, Engineering and Physical Sciences Research Council, National Institute for Health Research, Coalition for Epidemic Preparedness Innovations, National Institute for Health Research Oxford Biomedical Research Centre, Chinese Academy of Medical Sciences Innovation Fund for Medical Science, Thames Valley and South Midlands NIHR Clinical Research Network, the Lemann Foundation, Rede D'Or, the Brava and Telles Foundation, the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior, Brazil, and AstraZeneca.

Urine metabolomics links dysregulation of the tryptophan-kynurenine pathway to inflammation and severity of COVID-19

SARS-CoV-2 causes major disturbances in serum metabolite levels, associated with severity of the immune response. Despite the numerous advantages of urine for biomarker discovery, the potential association between urine metabolites and disease severity has not been investigated in coronavirus disease 2019 (COVID-19). In a proof-of-concept study, we performed quantitative urine metabolomics in patients hospitalized with COVID-19 and controls using LC-MS/MS. We assessed whether metabolites alterations were associated with COVID-19, disease severity, and inflammation. The study included 56 patients hospitalized with COVID-19 (26 non-critical and 30 critical disease); 16 healthy controls; and 3 controls with proximal tubule dysfunction unrelated to SARS-CoV-2. Metabolomic profiling revealed a major urinary increase of tryptophan metabolites kynurenine (P < 0.001), 3-hydroxykynurenine (P < 0.001) and 3-hydroxyanthranilate (P < 0.001) in SARS-CoV-2 infected patients. Urine levels of kynurenines were associated with disease severity and systemic inflammation (kynurenine, r 0.43, P = 0.001; 3-hydroxykynurenine, r 0.44, P < 0.001). Increased urinary levels of neutral amino acids and imino acid proline were also common in COVID-19, suggesting specific transport defects. Urine metabolomics identified major alterations in the tryptophan-kynurenine pathway, consistent with changes in host metabolism during SARS-CoV-2 infection. The association between increased urinary levels of kynurenines, inflammation and COVID-19 severity supports further evaluation of these easily available biomarkers.

Unbalanced IDO1/IDO2 Endothelial Expression and Skewed Keynurenine Pathway in the Pathogenesis of COVID-19 and Post-COVID-19 Pneumonia

Despite intense investigation, the pathogenesis of COVID-19 and the newly defined long COVID-19 syndrome are not fully understood. Increasing evidence has been provided of metabolic alterations characterizing this group of disorders, with particular relevance of an activated tryptophan/kynurenine pathway as described in this review. Recent histological studies have documented that, in COVID-19 patients, indoleamine 2,3-dioxygenase (IDO) enzymes are differentially expressed in the pulmonary blood vessels, i.e., IDO1 prevails in early/mild pneumonia and in lung tissues from patients suffering from long COVID-19, whereas IDO2 is predominant in severe/fatal cases. We hypothesize that IDO1 is necessary for a correct control of the vascular tone of pulmonary vessels, and its deficiency in COVID-19 might be related to the syndrome’s evolution toward vascular dysfunction. The complexity of this scenario is discussed in light of possible therapeutic manipulations of the tryptophan/kynurenine pathway in COVID-19 and post-acute COVID-19 syndromes.

Sex differences in global metabolomic profiles of COVID-19 patients

Coronavirus disease (COVID-19), caused by SARS-CoV-2, leads to symptoms ranging from asymptomatic disease to death. Although males are more susceptible to severe symptoms and higher mortality due to COVID-19, patient sex has rarely been examined. Sex-associated metabolic changes may implicate novel biomarkers and therapeutic targets to treat COVID-19. Here, using serum samples, we performed global metabolomic analyses of uninfected and SARS-CoV-2-positive male and female patients with severe COVID-19. Key metabolic pathways that demonstrated robust sex differences in COVID-19 groups, but not in controls, involved lipid metabolism, pentose pathway, bile acid metabolism, and microbiome-related metabolism of aromatic amino acids, including tryptophan and tyrosine. Unsupervised statistical analysis showed a profound sexual dimorphism in correlations between patient-specific clinical parameters and their global metabolic profiles. Identification of sex-specific metabolic changes in severe COVID-19 patients is an important knowledge source for researchers striving for development of potential sex-associated biomarkers and druggable targets for COVID-19 patients.

Tryptophan Metabolism and COVID-19-Induced Skeletal Muscle Damage: Is ACE2 a Key Regulator?

The severity of coronavirus disease 2019 (COVID-19) is characterized by systemic damage to organs, including skeletal muscle, due to excessive secretion of inflammatory cytokines. Clinical studies have suggested that the kynurenine pathway of tryptophan metabolism is selectively enhanced in patients with severe COVID-19. In addition to acting as a receptor for severe acute respiratory syndrome coronavirus 2, the causative virus of COVID-19, angiotensin converting enzyme 2 (ACE2) contributes to tryptophan absorption and inhibition of the renin-angiotensin system. In this article, we review previous studies to assess the potential for a link between tryptophan metabolism, ACE2, and skeletal muscle damage in patients with COVID-19.

Functional analyses and single cell immunoprofiling uncover sex-specific differences in SARS-CoV2 immune memory development

SARS-CoV-2 infection leads to a broad range of outcomes and immune responses, with the development of neutralizing antibodies generally correlated with protection against reinfection. Here, we have characterized both neutralizing activity and T cell responses in a cluster of subjects with mild disease linked to a single spreading event. Surprisingly, we observed sex-specific associations between spike- and particularly nucleoprotein-specific T cell responses and neutralization, with pro-inflammatory cytokines being linked to higher titers only in males. Using single cell immunoprofiling, which provided matched transcriptome and T-cell receptor (TCR) profiles in restimulated CD4 + and CD8 + cells from these subjects, we identified differences in type I IFN signaling that may underlie this difference in antibody generation. Finally, we also identified several TCRs associated with cytokine producing T cells. Altogether, our work maps the breadth of immunological outcomes of SARS-CoV2 infections and highlight the potential role of sex-specific feedback loops during the generation of neutralizing antibodies.

Functional analyses and single cell immunoprofiling uncover sex-specific differences in SARS-CoV2 immune memory development

SARS-CoV-2 infection leads to a broad range of outcomes and immune responses, with the development of neutralizing antibodies generally correlated with protection against reinfection. Here, we have characterized both neutralizing activity and T cell responses in a cluster of subjects with mild disease linked to a single spreading event. Surprisingly, we observed sex-specific associations between spike- and particularly nucleoprotein-specific T cell responses and neutralization, with pro-inflammatory cytokines being linked to higher titers only in males. Using single cell immunoprofiling, which provided matched transcriptome and T-cell receptor (TCR) profiles in restimulated CD4 + and CD8 + cells from these subjects, we identified differences in type I IFN signaling that may underlie this difference in antibody generation. Finally, we also identified several TCRs associated with cytokine producing T cells. Altogether, our work maps the breadth of immunological outcomes of SARS-CoV2 infections and highlight the potential role of sex-specific feedback loops during the generation of neutralizing antibodies.

Exploration of Human Serum Lipoprotein Supramolecular Phospholipids Using Statistical Heterospectroscopy in n-Dimensions (SHY-n): Identification of Potential Cardiovascular Risk Biomarkers Related to SARS-CoV-2 Infection

SARS-CoV-2 infection causes a significant reduction in lipoprotein-bound serum phospholipids give rise to supramolecular phospholipid composite (SPC) signals observed in diffusion and relaxation edited ¹H NMR spectra. To characterize the chemical structural components and compartmental location of SPC and to understand further its possible diagnostic properties, we applied a Statistical HeterospectroscopY in n-dimensions (SHY-n) approach. This involved statistically linking a series of orthogonal measurements made on the same samples, using independent analytical techniques and instruments, to identify the major individual phospholipid components giving rise to the SPC signals. Thus, an integrated model for SARS-CoV-2 positive and control adults is presented that relates three identified diagnostic subregions of the SPC signal envelope (SPC₁, SPC₂, and SPC₃) generated using diffusion and relaxation edited (DIRE) NMR spectroscopy to lipoprotein and lipid measurements obtained by in vitro diagnostic NMR spectroscopy and ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). The SPC signals were then correlated sequentially with (a) total phospholipids in lipoprotein subfractions; (b) apolipoproteins B100, A1, and A2 in different lipoproteins and subcompartments; and (c) MS-measured total serum phosphatidylcholines present in the NMR detection range (i.e., PCs: 16.0,18.2; 18.0,18.1; 18.2,18.2; 16.0,18.1; 16.0,20.4; 18.0,18.2; 18.1,18.2), lysophosphatidylcholines (LPCs: 16.0 and 18.2), and sphingomyelin (SM 22.1). The SPC₃/SPC₂ ratio correlated strongly (r = 0.86) with the apolipoprotein B100/A1 ratio, a well-established marker of cardiovascular disease risk that is markedly elevated during acute SARS-CoV-2 infection. These data indicate the considerable potential of using a serum SPC measurement as a metric of cardiovascular risk based on a single NMR experiment. This is of specific interest in relation to understanding the potential for increased cardiovascular risk in COVID-19 patients and risk persistence in post-acute COVID-19 syndrome (PACS).

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.

Alzheimer's-like signaling in brains of COVID-19 patients

Introduction

The mechanisms that lead to cognitive impairment associated with COVID‐19 are not well understood.

Methods

Brain lysates from control and COVID‐19 patients were analyzed for oxidative stress and inflammatory signaling pathway markers, and measurements of Alzheimer’s disease (AD)‐linked signaling biochemistry. Post‐translational modifications of the ryanodine receptor/calcium (Ca2⁺) release channels (RyR) on the endoplasmic reticuli (ER), known to be linked to AD, were also measured by co‐immunoprecipitation/immunoblotting of the brain lysates.

Results

We provide evidence linking SARS‐CoV‐2 infection to activation of TGF‐β signaling and oxidative overload. The neuropathological pathways causing tau hyperphosphorylation typically associated with AD were also shown to be activated in COVID‐19 patients. RyR2 in COVID‐19 brains demonstrated a “leaky” phenotype, which can promote cognitive and behavioral defects.

Discussion

COVID‐19 neuropathology includes AD‐like features and leaky RyR2 channels could be a therapeutic target for amelioration of some cognitive defects associated with SARS‐CoV‐2 infection and long COVID.

Alterations in rat prefrontal cortex kynurenic acid levels are involved in the enduring cognitive dysfunctions induced by tetrahydrocannabinol exposure during the adolescence

INTRODUCTION

Cannabis abuse during adolescence is a risk factor for cognitive impairments in psychiatric disorders later in life. To date, the possible causal relationship between cannabinoids, kynurenic acid (KYNA; i.e., a neuroactive metabolite of tryptophan degradation) and cognition has not been investigated in adolescence. Early exposure to delta 9-tetrahydrocannabinol (THC; i.e., the main psychotropic component of cannabis) causes enduring cognitive deficits, which critically involve impaired glutamatergic function in the prefrontal cortex (PFC). In addition, prenatal cannabis exposure results in enduring increases in PFC KYNA levels. Based on these findings, the effects of chronic THC exposure in rats, during another critical period of neurodevelopment particularly sensitive to perturbation by exogenous stimuli, such as adolescence, have been investigated.

METHODS

Male Wistar rats were chronically treated with vehicle or ascending intraperitoneal (i.p.) doses of THC starting on postnatal day (PND) 35 until PND 45. In adulthood (PND 75), cognitive assessment (Y-maze) and extracellular KYNA/glutamate levels were measured in the PFC by in vivo microdialysis, before and after a challenge with KYN (5 mg/kg i.p., the biological precursor of KYNA). By using the selective, brain-penetrable KAT II inhibitor PF-04859989, we then examined whether blockade of KYNA neosynthesis prevents the cognitive impairment.

RESULTS

Compared to vehicle-treated controls, extracellular basal KYNA levels were higher in the PFC of adult rats chronically exposed to THC in adolescence (p < 0.01). No changes were observed in extracellular glutamate levels. Following a challenge with KYN, extracellular KYNA levels similarly increased in both groups (i.e., vehicle- and THC-treated; p < 0.001 and p < 0.01, respectively). Chronic adolescent THC exposure negatively affected short-term memory (reduced spontaneous alternation), in adult animals (p < 0.001), while PF-04859989 (30 mg/kg i.p.) restored the cognitive impairment (p < 0.05).

DISCUSSION

We propose that the observed alterations in PFC KYNA signaling might be involved in the cognitive dysfunction induced by the exposure to THC during the adolescence. In the translational realm, these experiments raise the prospect of prevention of KYNA neosynthesis as a possible novel approach to counteract some of the detrimental long-term effects of adolescence cannabis use.

Genomic, proteomic and metabolomic profiling of severe acute respiratory syndrome-Coronavirus-2

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) is one of the worst human health problems faced by humanity in recent centuries. An end to this health crisis relies on our ability to monitor viral transmission dynamics to check spread, develop therapeutics and preventatives for treatment of SARS-CoV-2 infection and understand the pathophysiology of the disease for better management of the patients. Omics technologies have played a crucial part in understanding the different aspects of COVID-19 disease. While whole-genome sequencing of SARS-CoV-2 isolates from across the globe has aided in the development of molecular diagnostic assays and informed about the viral evolution, knowledge of structure and function of viral proteome fueled the development of small molecule and biologicals therapeutics as well as vaccines. Concurrently, metabolomic profiling of samples from COVID-19 patients experiencing a varying level of disease severity has provided a snapshot of the pathophysiology of the disease helping device effective treatment regimen. This chapter deals with genomic, proteomic, and metabolomic profiling of SRAS-CoV-2.

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

INTRODUCTION

The diagnosis of COVID-19 is normally based on the qualitative detection of viral nucleic acid sequences. Properties of the host response are not measured but are key in determining outcome. Although metabolic profiles are well suited to capture host state, most metabolomics studies are either underpowered, measure only a restricted subset of metabolites, compare infected individuals against uninfected control cohorts that are not suitably matched, or do not provide a compact predictive model.

OBJECTIVES

Here we provide a well-powered, untargeted metabolomics assessment of 120 COVID-19 patient samples acquired at hospital admission. The study aims to predict the patient's infection severity (i.e., mild or severe) and potential outcome (i.e., discharged or deceased).

METHODS

High resolution untargeted UHPLC-MS/MS analysis was performed on patient serum using both positive and negative ionization modes. A subset of 20 intermediary metabolites predictive of severity or outcome were selected based on univariate statistical significance and a multiple predictor Bayesian logistic regression model was created.

RESULTS

The predictors were selected for their relevant biological function and include deoxycytidine and ureidopropionate (indirectly reflecting viral load), kynurenine (reflecting host inflammatory response), and multiple short chain acylcarnitines (energy metabolism) among others. Currently, this approach predicts outcome and severity with a Monte Carlo cross validated area under the ROC curve of 0.792 (SD 0.09) and 0.793 (SD 0.08), respectively. A blind validation study on an additional 90 patients predicted outcome and severity at ROC AUC of 0.83 (CI 0.74-0.91) and 0.76 (CI 0.67-0.86).

CONCLUSION

Prognostic tests based on the markers discussed in this paper could allow improvement in the planning of COVID-19 patient treatment.

Nicotinamide Adenine Dinucleotide Biosynthetic Impairment and Urinary Metabolomic Alterations Observed in Hospitalized Adults With COVID-19-Related Acute Kidney Injury

INTRODUCTION

Acute kidney injury (AKI) is common in COVID-19 and associated with increased morbidity and mortality. We investigated alterations in the urine metabolome to test the hypothesis that impaired nicotinamide adenine dinucleotide (NAD+) biosynthesis and other deficiencies in energy metabolism in the kidney, previously characterized in ischemic, toxic, and inflammatory etiologies of AKI, will be present in COVID-19-associated AKI.

METHODS

This is a case-control study among the following 2 independent populations of adults hospitalized with COVID-19: a critically ill population in Boston, Massachusetts, and a general population in Birmingham, Alabama. The cases had AKI stages 2 or 3 by Kidney Disease Improving Global Outcomes (KDIGO) criteria; the controls had no AKI. Metabolites were measured by liquid chromatography-mass spectrometry.

RESULTS

A total of 14 cases and 14 controls were included from Boston and 8 cases and 10 controls from Birmingham. Increased urinary quinolinate-to-tryptophan ratio (Q/T), found with impaired NAD+ biosynthesis, was present in the cases at each location and pooled across locations (median [interquartile range]: 1.34 [0.59-2.96] in cases, 0.31 [0.13-1.63] in controls, P = 0.0013). Altered energy metabolism and purine metabolism contributed to a distinct urinary metabolomic signature that differentiated patients with and without AKI (supervised random forest class error: 2 of 28 in Boston, 0 of 18 in Birmingham).

CONCLUSION

Urinary metabolites spanning multiple biochemical pathways differentiate AKI versus non-AKI in patients hospitalized with COVID-19 and suggest a conserved impairment in NAD+ biosynthesis, which may present a novel therapeutic target to mitigate COVID-19-associated AKI.

Kynurenine and Hemoglobin as Sex-Specific Variables in COVID-19 Patients: A Machine Learning and Genetic Algorithms Approach

Differences in clinical manifestations, immune response, metabolic alterations, and outcomes (including disease severity and mortality) between men and women with COVID-19 have been reported since the pandemic outbreak, making it necessary to implement sex-specific biomarkers for disease diagnosis and treatment. This study aimed to identify sex-associated differences in COVID-19 patients by means of a genetic algorithm (GALGO) and machine learning, employing support vector machine (SVM) and logistic regression (LR) for the data analysis. Both algorithms identified kynurenine and hemoglobin as the most important variables to distinguish between men and women with COVID-19. LR and SVM identified C10:1, cough, and lysoPC a 14:0 to discriminate between men with COVID-19 from men without, with LR being the best model. In the case of women with COVID-19 vs. women without, SVM had a higher performance, and both models identified a higher number of variables, including 10:2, lysoPC a C26:0, lysoPC a C28:0, alpha-ketoglutaric acid, lactic acid, cough, fever, anosmia, and dysgeusia. Our results demonstrate that differences in sexes have implications in the diagnosis and outcome of the disease. Further, genetic and machine learning algorithms are useful tools to predict sex-associated differences in COVID-19.

Estimating the viral loads of SARS-CoV-2 in the oral cavity when complicated with periapical lesions

Background

The oral cavity represents a main entrance of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Angiotensin-converting enzyme 2 (ACE-2), neuropilin-1 (NRP-1), and transmembrane serine protease 2 (TMPRSS2) are essential for the entry of SARS-CoV-2 to the host cells. Both ACE-2 and NRP-1 receptors and TMPRSS2 have been identified in the oral cavity. However, there is limited knowledge about the impact of periapical lesions and their metabolites on the expression of these critical genes. This study aims to measure the impact of periapical lesions and their unique fatty acids (FAs) metabolites on the expression of the aforementioned genes, in addition to interleukin 6 (IL-6) gene and hence SARS-CoV-2 infection loads can be estimated.

Methods

Gene expression of ACE-2, NRP-1, TMPRSS2, and IL-6 was performed in periapical lesions in comparison to healthy oral cavity. Since FAs are important immunomodulators required for the lipid synthesis essential for receptors synthesis and viral replication, comparative FAs profiling was determined in oral lesions and healthy pulp tissues using gas chromatography–mass spectrometry (GC–MS). The effect of major identified and unique FAs was tested on mammalian cells known to express ACE-2, NRP-1, and TMPRSS2 genes.

Results

Gene expression analysis indicated that ACE-2, NRP-1, and TMPRSS2 were significantly upregulated in healthy clinical samples compared to oral lesions, while the reverse was true with IL-6 gene expression. Saturated and monounsaturated FAs were the major identified shared and unique FAs, respectively. Major shared FAs included palmitic, stearic and myristic acids with the highest percentage in the healthy oral cavity, while unique FAs included 17-octadecynoic acid in periapical abscess, petroselinic acid and l-lactic acid in periapical granuloma, and 1-nonadecene in the radicular cyst. Computational prediction showed that the binding affinity of identified FAs to ACE-2, TMPRSS2 and S protein were insignificant. Further, FA-treated mammalian cells showed significant overexpression of ACE-2, NRP-1 and TMPRSS2 genes except with l-lactic acid and oleic acid caused downregulation of NRP-1 gene, while 17-octadecynoic acid caused insignificant effect.

Conclusion

Collectively, a healthy oral cavity is more susceptible to viral infection when compared to that complicated with periapical lesions. FAs play important role in viral infection and their balance can affect the viral loads. Shifting the balance towards higher levels of palmitic, stearic and 1-nonadecene caused significant upregulation of the aforementioned genes and hence higher viral loads. On the other hand, there is a reverse correlation between inflammation and expression of SARS-CoV-2 receptors. Therefore, a mouth preparation that can reduce the levels of palmitic, stearic and 1-nonadecene, while maintaining an immunomodulatory effect can be employed as a future protection strategy against viral infection.

Pathogenic mitochondrial dysfunction and metabolic abnormalities

Herein we trace links between biochemical pathways, pathogenesis, and metabolic diseases to set the stage for new therapeutic advances. Cellular and acellular microorganisms including bacteria and viruses are primary pathogenic drivers that cause disease. Missing from this statement are subcellular compartments, importantly mitochondria, which can be pathogenic by themselves, also serving as key metabolic disease intermediaries. The breakdown of food molecules provides chemical energy to power cellular processes, with mitochondria as powerhouses and ATP as the principal energy carrying molecule. Most animal cell ATP is produced by mitochondrial synthase; its central role in metabolism has been known for >80 years. Metabolic disorders involving many organ systems are prevalent in all age groups. Progressive pathogenic mitochondrial dysfunction is a hallmark of genetic mitochondrial diseases, the most common phenotypic expression of inherited metabolic disorders. Confluent genetic, metabolic, and mitochondrial axes surface in diabetes, heart failure, neurodegenerative disease, and even in the ongoing coronavirus pandemic.

Hyperinflammatory Immune Response and COVID-19: A Double Edged Sword

The coronavirus disease-19 (COVID-19) elicited by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused devastating health, economic and social impact worldwide. Its clinical spectrum ranges from asymptomatic to respiratory failure and multi-organ failure or death. The pathogenesis of SARS-CoV-2 infection is attributed to a complex interplay between virus and host immune response. It involves activation of multiple inflammatory pathways leading to hyperinflammation and cytokine storm, resulting in tissue damage, acute respiratory distress syndrome (ARDS) and multi-organ failure. Accumulating evidence has raised concern over the long-term health effects of COVID-19. Importantly, the neuroinvasive potential of SARS-CoV-2 may have devastating consequences in the brain. This review provides a conceptual framework on how the virus tricks the host immune system to induce infection and cause severe disease. We also explore the key differences between mild and severe COVID-19 and its short- and long-term effects, particularly on the human brain.

The prefrontal cortex in a pandemic: Restoring functions with system-, family-, and individual-focused interventions

The COVID-19 pandemic is an unanticipated and uncontrollable chronic stressor that is detrimental to the mental and behavioral health of children and families, particularly those from disadvantaged and marginalized backgrounds. Chronic stress impairs a myriad of prefrontal cortical functions, important for coping with the COVID-19 pandemic, and has consequences on dyadic parent-child functioning. Informed by neuroscience and clinical evidence, sensitive parenting is a vital avenue of intervention that buffers against the toxic effects of COVID-19 on parent-child mental health. In the context of the COVID-19 pandemic, we first discuss the neurobiological, psychological, and behavioral mechanisms behind exacerbated mental health risks in families. We then highlight the role of sensitive parenting as a buffer against stress-related mental health problems, and conclude with recommendations for systemic-, family-, and individual-interventions to most effectively address stress-related mental health problems and their impact on children and families during the COVID-19 pandemic. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Biological and Clinical Factors contributing to the Metabolic Heterogeneity of Hospitalized Patients with and without COVID-19

The Corona Virus Disease 2019 (COVID-19) pandemic represents an ongoing worldwide challenge. Exploratory studies evaluating the impact of COVID-19 infection on the plasma metabolome have been performed, often with small numbers of patients, and with or without relevant control data; however, determining the impact of biological and clinical variables remains critical to understanding potential markers of disease severity and progression. The present large study, including relevant controls, sought to understand independent and overlapping metabolic features of samples from acutely ill patients (n = 831), testing positive (n = 543) or negative (n = 288) for COVID-19. High-throughput metabolomics analyses were complemented with antigen and enzymatic activity assays on 831 plasma samples from acutely ill patients while in the emergency department, at admission, and during hospitalization. We then performed additional lipidomics analyses of the 60 subjects with the lowest and highest body mass index, either COVID-19 positive or negative. Omics data were correlated to detailed data on patient characteristics and clinical laboratory assays measuring coagulation, hematology and chemistry analytes. Significant changes in arginine/proline/citrulline, tryptophan/indole/kynurenine, fatty acid and acyl-carnitine metabolism emerged as highly relevant markers of disease severity, progression and prognosis as a function of biological and clinical variables in these patients. Further, machine learning models were trained by entering all metabolomics and clinical data from half of the COVID-19 patient cohort and then tested on the other half yielding ~ 78% prediction accuracy. Finally, the extensive amount of information accumulated in this large, prospective, observational study provides a foundation for follow-up mechanistic studies and data sharing opportunities, which will advance our understanding of the characteristics of the plasma metabolism in COVID-19 and other acute critical illnesses.