Diffusion and Relaxation Edited Proton NMR Spectroscopy of Plasma Reveals a High-Fidelity Supramolecular Biomarker Signature of SARS-CoV-2 Infection

Stratification of Sepsis Patients on Admission into the Intensive Care Unit According to Differential Plasma Metabolic Phenotypes

Delayed diagnosis of patients with sepsis or septic shock is associated with increased mortality and morbidity. UPLC-MS and NMR spectroscopy were used to measure panels of lipoproteins, lipids, biogenic amines, amino acids, and tryptophan pathway metabolites in blood plasma samples collected from 152 patients within 48 h of admission into the Intensive Care Unit (ICU) where 62 patients had no sepsis, 71 patients had sepsis, and 19 patients had septic shock. Patients with sepsis or septic shock had higher concentrations of neopterin and lower levels of HDL cholesterol and phospholipid particles in comparison to nonsepsis patients. Septic shock could be differentiated from sepsis patients based on different concentrations of 10 lipids, including significantly lower concentrations of five phosphatidylcholine species, three cholesterol esters, one dihydroceramide, and one phosphatidylethanolamine. The Supramolecular Phospholipid Composite (SPC) was reduced in all ICU patients, while the composite markers of acute phase glycoproteins were increased in the sepsis and septic shock patients within 48 h admission into ICU. We show that the plasma metabolic phenotype obtained within 48 h of ICU admission is diagnostic for the presence of sepsis and that septic shock can be differentiated from sepsis based on the lipid profile.

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.

Rapid and Self-Administrable Capillary Blood Microsampling Demonstrates Statistical Equivalence with Standard Venous Collections in NMR-Based Lipoprotein Analysis

We investigated plasma and serum blood derivatives from capillary blood microsamples (500 μL, MiniCollect tubes) and corresponding venous blood (10 mL vacutainers). Samples from 20 healthy participants were analyzed by 1H NMR, and 112 lipoprotein subfraction parameters; 3 supramolecular phospholipid composite (SPC) parameters from SPC1, SPC2, and SPC3 subfractions; 2 N-acetyl signals from α-1-acid glycoprotein (Glyc), GlycA, and GlycB; and 3 calculated parameters, SPC (total), SPC3/SPC2, and Glyc (total) were assessed. Using linear regression between capillary and venous collection sites, we explained that agreement (Adj. R2 ≥ 0.8, p < 0.001) was witnessed for 86% of plasma parameters (103/120) and 88% of serum parameters (106/120), indicating that capillary lipoprotein, SPC, and Glyc concentrations follow changes in venous concentrations. These results indicate that capillary blood microsamples are suitable for sampling in remote areas and for high-frequency longitudinal sampling of the majority of lipoproteins, SPCs, and Glycs.

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.

Exploring the Interactions between Obesity and Diabetes: Implications for Understanding Metabolic Dysregulation in a Saudi Arabian Adult Population

The rising prevalence of obesity in Saudi Arabia is a major contributor to the nation's high levels of cardiometabolic diseases such as type 2 diabetes. To assess the impact of obesity on the diabetic metabolic phenotype presented in young Saudi Arabian adults, participants (n = 289, aged 18-40 years) were recruited and stratified into four groups: healthy weight (BMI 18.5-24.99 kg/m2) with (n = 57) and without diabetes (n = 58) or overweight/obese (BMI > 24.99 kg/m2) with (n = 102) and without diabetes (n = 72). Distinct plasma metabolic phenotypes associated with high BMI and diabetes were identified using nuclear magnetic resonance spectroscopy and ultraperformance liquid chromatography mass spectrometry. Increased plasma glucose and dysregulated lipoproteins were characteristics of obesity in individuals with and without diabetes, but the obesity-associated lipoprotein phenotype was partially masked in individuals with diabetes. Although there was little difference between diabetics and nondiabetics in the global plasma LDL cholesterol and phospholipid concentration, the distribution of lipoprotein particles was altered in diabetics with a shift toward denser and more atherogenic LDL5 and LDL6 particles, which was amplified in the presence of obesity. Further investigation is warranted in larger Middle Eastern populations to explore the dysregulation of metabolism driven by interactions between obesity and diabetes in young adults.

Nonsevere Burn Induces a Prolonged Systemic Metabolic Phenotype Indicative of a Persistent Inflammatory Response Postinjury

Globally, burns are a significant cause of injury that can cause substantial acute trauma as well as lead to increased incidence of chronic comorbidity and disease. To date, research has primarily focused on the systemic response to severe injury, with little in the literature reported on the impact of nonsevere injuries (<15% total burn surface area; TBSA). To elucidate the metabolic consequences of a nonsevere burn injury, longitudinal plasma was collected from adults (n = 35) who presented at hospital with a nonsevere burn injury at admission, and at 6 week follow up. A cross-sectional baseline sample was also collected from nonburn control participants (n = 14). Samples underwent multiplatform metabolic phenotyping using 1H nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry to quantify 112 lipoprotein and glycoprotein signatures and 852 lipid species from across 20 subclasses. Multivariate data modeling (orthogonal projections to latent structures-discriminate analysis; OPLS-DA) revealed alterations in lipoprotein and lipid metabolism when comparing the baseline control to hospital admission samples, with the phenotypic signature found to be sustained at follow up. Univariate (Mann-Whitney U) testing and OPLS-DA indicated specific increases in GlycB (p-value < 1.0e-4), low density lipoprotein-2 subfractions (variable importance in projection score; VIP > 6.83e-1) and monoacyglyceride (20:4) (p-value < 1.0e-4) and decreases in circulating anti-inflammatory high-density lipoprotein-4 subfractions (VIP > 7.75e-1), phosphatidylcholines, phosphatidylglycerols, phosphatidylinositols, and phosphatidylserines. The results indicate a persistent systemic metabolic phenotype that occurs even in cases of a nonsevere burn injury. The phenotype is indicative of an acute inflammatory profile that continues to be sustained postinjury, suggesting an impact on systems health beyond the site of injury. The phenotypes contained metabolic signatures consistent with chronic inflammatory states reported to have an elevated incidence postburn injury. Such phenotypic signatures may provide patient stratification opportunities, to identify individual responses to injury, personalize intervention strategies, and improve acute care, reducing the risk of chronic comorbidity.

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.

Stratification of hypertension and SARS-CoV-2 infection by quantitative NMR spectroscopy of human blood serum

BACKGROUND

Diagnostic approaches like the nuclear magnetic resonance spectroscopy (NMR) based quantification of metabolites, lipoproteins, and inflammation markers has helped to identify typical alterations in the blood serum of COVID-19 patients. However, confounders such as sex, and comorbidities, which strongly influence the metabolome, were often not considered. Therefore, the aim of this NMR study was to consider sex, as well as arterial hypertension (AHT), when investigating COVID-19-positive serum samples in a large age-and sex matched cohort.

METHODS

NMR serum data from 329 COVID-19 patients were compared with 305 healthy controls. 134 COVID-19 patients were affected by AHT. These were analyzed together with NMR data from 58 hypertensives without COVID-19. In addition to metabolite, lipoprotein, and glycoprotein data from NMR, common laboratory parameters were considered. Sex was considered in detail for all comparisons.

RESULTS

Here, we show that several differences emerge from previous NMR COVID-19 studies when AHT is considered. Especially, the previously described triglyceride-rich lipoprotein profile is no longer observed in COVID-19 patients, nor an increase in ketone bodies. Further alterations are a decrease in glutamine, leucine, isoleucine, and lysine, citric acid, HDL-4 particles, and total cholesterol. Additionally, hypertensive COVID-19 patients show higher inflammatory NMR parameters than normotensive patients.

CONCLUSIONS

We present a more precise picture of COVID-19 blood serum parameters. Accordingly, considering sex and comorbidities should be included in future metabolomics studies for improved and refined patient stratification. Due to metabolic similarities with other viral infections, these results can be applied to other respiratory diseases in the future.

Towards a Precise NMR Quantification of Acute Phase Inflammation Proteins from Human Serum

Nuclear Magnetic Resonance (NMR) spectra of human serum and plasma show, besides metabolites and lipoproteins, two characteristic signals termed GlycA and B arising from the acetyl groups of glycoprotein glycans from acute phase proteins, which constitute good markers for inflammatory processes. Here, we report a comprehensive assignment of glycoprotein glycan NMR signals observed in human serum, showing that GlycA and GlycB signals originate from Neu5Ac and GlcNAc moieties from N-glycans, respectively. Diffusion-edited NMR experiments demonstrate that signal components can be associated with specific acute phase proteins. Conventionally determined concentrations of acute phase glycoproteins correlate well with distinct features in NMR spectra (R2 up to 0.9422, p-value <0.001), allowing the simultaneous quantification of several acute phase inflammation proteins. Overall, a proteo-metabolomics NMR signature of significant diagnostic potential is obtained within 10-20 min acquisition time. This is exemplified in serum samples from COVID-19 and cardiogenic shock patients showing significant changes in several acute phase proteins compared to healthy controls.

Integrated NMR and MS Analysis of the Plasma Metabolome Reveals Major Changes in One-Carbon, Lipid, and Amino Acid Metabolism in Severe and Fatal Cases of COVID-19

Brazil has the second-highest COVID-19 death rate worldwide, and Rio de Janeiro is among the states with the highest rate in the country. Although vaccine coverage has been achieved, it is anticipated that COVID-19 will transition into an endemic disease. It is concerning that the molecular mechanisms underlying clinical evolution from mild to severe disease, as well as the mechanisms leading to long COVID-19, are not yet fully understood. NMR and MS-based metabolomics were used to identify metabolites associated with COVID-19 pathophysiology and disease outcome. Severe COVID-19 cases (n = 35) were enrolled in two reference centers in Rio de Janeiro within 72 h of ICU admission, alongside 12 non-infected control subjects. COVID-19 patients were grouped into survivors (n = 18) and non-survivors (n = 17). Choline-related metabolites, serine, glycine, and betaine, were reduced in severe COVID-19, indicating dysregulation in methyl donors. Non-survivors had higher levels of creatine/creatinine, 4-hydroxyproline, gluconic acid, and N-acetylserine, indicating liver and kidney dysfunction. Several changes were greater in women; thus, patients' sex should be considered in pandemic surveillance to achieve better disease stratification and improve outcomes. These metabolic alterations may be useful to monitor organ (dys) function and to understand the pathophysiology of acute and possibly post-acute COVID-19 syndromes.

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.

Bovine Serum Albumin-Protected Gold Nanoclusters for Sensing of SARS-CoV-2 Antibodies and Virus

An approach to assess severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (and past infection) was developed. For virus detection, the SARS-CoV-2 virus nucleocapsid protein (NP) was targeted. To detect the NP, antibodies were immobilized on magnetic beads to capture the NPs, which were subsequently detected using rabbit anti-SARS-CoV-2 nucleocapsid antibodies and alkaline phosphatase (AP)-conjugated anti-rabbit antibodies. A similar approach was used to assess SARS-CoV-2-neutralizing antibody levels by capturing spike receptor-binding domain (RBD)-specific antibodies utilizing RBD protein-modified magnetic beads and detecting them using AP-conjugated anti-human IgG antibodies. The sensing mechanism for both assays is based on cysteamine etching-induced fluorescence quenching of bovine serum albumin-protected gold nanoclusters where cysteamine is generated in proportion to the amount of either SARS-CoV-2 virus or anti-SARS-CoV-2 receptor-binding domain-specific immunoglobulin antibodies (anti-RBD IgG antibodies). High sensitivity can be achieved in 5 h 15 min for the anti-RBD IgG antibody detection and 6 h 15 min for virus detection, although the assay can be run in "rapid" mode, which takes 1 h 45 min for the anti-RBD IgG antibody detection and 3 h 15 min for the virus. By spiking the anti-RBD IgG antibodies and virus in serum and saliva, we demonstrate that the assay can detect the anti-RBD IgG antibodies with a limit of detection (LOD) of 4.0 and 2.0 ng/mL in serum and saliva, respectively. For the virus, we can achieve an LOD of 8.5 × 10⁵ RNA copies/mL and 8.8 × 10⁵ RNA copies/mL in serum and saliva, respectively. Interestingly, this assay can be easily modified to detect myriad analytes of interest.

Cardiometabolic disease risk markers are increased following burn injury in children

Introduction

Burn injury in children causes prolonged systemic effects on physiology and metabolism leading to increased morbidity and mortality, yet much remains undefined regarding the metabolic trajectory towards specific health outcomes.

Methods

A multi-platform strategy was implemented to evaluate the long-term immuno-metabolic consequences of burn injury combining metabolite, lipoprotein, and cytokine panels. Plasma samples from 36 children aged 4-8 years were collected 3 years after a burn injury together with 21 samples from non-injured age and sex matched controls. Three different ¹H Nuclear Magnetic Resonance spectroscopic experiments were applied to capture information on plasma low molecular weight metabolites, lipoproteins, and α-1-acid glycoprotein.

Results

Burn injury was characterized by underlying signatures of hyperglycaemia, hypermetabolism and inflammation, suggesting disruption of multiple pathways relating to glycolysis, tricarboxylic acid cycle, amino acid metabolism and the urea cycle. In addition, very low-density lipoprotein sub-components were significantly reduced in participants with burn injury whereas small-dense low density lipoprotein particles were significantly elevated in the burn injured patient plasma compared to uninjured controls, potentially indicative of modified cardiometabolic risk after a burn. Weighted-node Metabolite Correlation Network Analysis was restricted to the significantly differential features (q <0.05) between the children with and without burn injury and demonstrated a striking disparity in the number of statistical correlations between cytokines, lipoproteins, and small molecular metabolites in the injured groups, with increased correlations between these groups.

Discussion

These findings suggest a 'metabolic memory' of burn defined by a signature of interlinked and perturbed immune and metabolic function. Burn injury is associated with a series of adverse metabolic changes that persist chronically and are independent of burn severity and this study demonstrates increased risk of cardiovascular disease in the long-term. These findings highlight a crucial need for improved longer term monitoring of cardiometabolic health in a vulnerable population of children that have undergone burn injury.

Metabolic Adaptations Correlated with Antibody Response after Immunization with Inactivated SARS-CoV-2 in Brazilian Subjects

The adsorbed vaccine SARS-CoV-2 (inactivated) produced by Sinovac (SV) was the first vaccine against COVID-19 to be used in Brazil. To understand the metabolic effects of SV in Brazilian subjects, NMR-based metabolomics was used, and the immune response was studied in Brazilian subjects. Forty adults without (group^-, n = 23) and with previous COVID-19 infection (group⁺, n = 17) were followed-up for 90 days postcompletion of the vaccine regimen. After 90 days, our results showed that subjects had increased levels of lipoproteins, lipids, and N-acetylation of glycoproteins (NAG) as well as decreased levels of amino acids, lactate, citrate, and 3-hydroxypropionate. NAG and threonine were the highest correlated metabolites with N and S proteins, and neutralizing Ab levels. This study sheds light on the immunometabolism associated with the use of SV in Brazilian subjects from Rio de Janeiro and identifies potential metabolic markers associated with the immune status.

Potential of in vitro nuclear magnetic resonance of biofluids and tissues in clinical research

Body fluids, cells, and tissues contain a wide variety of metabolites that consist of a mixture of various low-molecular-weight compounds, including amino acids, peptides, lipids, nucleic acids, and organic acids, which makes comprehensive analysis more difficult. Quantitative nuclear magnetic resonance (NMR) spectroscopy is a well-established analytical technique for analyzing the metabolic profiles of body fluids, cells, and tissues. It enables fast and comprehensive detection, characterization, a high level of experimental reproducibility, minimal sample preparation, and quantification of various endogenous metabolites. In recent times, NMR-based metabolomics has been appreciably utilized in diverse branches of medicine, including microbiology, toxicology, pathophysiology, pharmacology, nutritional intervention, and disease diagnosis/prognosis. In this review, the utility of NMR-based metabolomics in clinical studies is discussed. The significance of in vitro NMR-based metabolomics as an effective tool for detecting metabolites and their variations in different diseases are discussed, together with the possibility of identifying specific biomarkers that can contribute to early detection and diagnosis of disease.

A patient-centric modeling framework captures recovery from SARS-CoV-2 infection

The biology driving individual patient responses to severe acute respiratory syndrome coronavirus 2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data and covering a year after disease onset, from 215 infected individuals with differing disease severities. Our analyses revealed distinct 'systemic recovery' profiles, with specific progression and resolution of the inflammatory, immune cell, metabolic and clinical responses. In particular, we found a strong inter-patient and intra-patient temporal covariation of innate immune cell numbers, kynurenine metabolites and lipid metabolites, which highlighted candidate immunologic and metabolic pathways influencing the restoration of homeostasis, the risk of death and that of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool http://shiny.mrc-bsu.cam.ac.uk/apps/covid-19-systemic-recovery-prediction-app , designed to test our findings prospectively.

The Inflammation Biomarker GlycA Reflects Plasma N-Glycan Branching

BACKGROUND

GlycA is a nuclear magnetic resonance (NMR) signal in plasma that correlates with inflammation and cardiovascular outcomes in large data sets. The signal is thought to originate from N-acetylglucosamine (GlcNAc) residues of branched plasma N-glycans, though direct experimental evidence is limited. Trace element concentrations affect plasma glycosylation patterns and may thereby also influence GlycA.

METHODS

NMR GlycA signal was measured in plasma samples from 87 individuals and correlated with MALDI-MS N-glycomics and trace element analysis. We further evaluated the genetic association with GlycA at rs13107325, a single nucleotide polymorphism resulting in a missense variant within SLC39A8, a manganese transporter that influences N-glycan branching, both in our samples and existing genome-wide association studies data from 22 835 participants in the Women's Health Study (WHS).

RESULTS

GlycA signal was correlated with both N-glycan branching (r2 ranging from 0.125-0.265; all P < 0.001) and copper concentration (r2 = 0.348, P < 0.0001). In addition, GlycA levels were associated with rs13107325 genotype in the WHS (β [standard error of the mean] = -4.66 [1.2674], P = 0.0002).

CONCLUSIONS

These results provide the first direct experimental evidence linking the GlycA NMR signal to N-glycan branching commonly associated with acute phase reactive proteins involved in inflammation.

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.

Detecting and Characterizing Interactions of Metabolites with Proteins by Saturation Transfer Difference Nuclear Magnetic Resonance (STD NMR) Spectroscopy

Saturation transfer difference (STD) nuclear magnetic resonance (NMR) spectroscopy is an established technique for detecting and characterizing the binding of small molecules, such as metabolites, to biological macromolecules like proteins and nucleic acids. STD NMR allows detection of binding in complex mixtures of potential ligands, which is often used for library screening in the pharmaceutical industry but may also be beneficial for binding studies with metabolite mixtures. The nature of the ligand is normally restricted to small molecules in terms of NMR spectroscopy, and the size of the macromolecule on the other side should be larger than 10-15 kDa. This technique is especially applicable to detecting binders of intermediate to low affinity with the dissociation constant (K_D) above 1 μM. In this chapter, we focus on recent developments and the applications of STD NMR to studying interactions of natural products and metabolites, in particular. The reader is also referred to excellent reviews of the field and the literature cited therein. This chapter also provides a detailed experimental protocol for performing the STD NMR measurement based on the example of the subunit A of the Na⁺-transporting NADH/ubiquinone oxidoreductase (Na⁺-NQR) from V. cholerae interacting with its natural quinone substrate and inhibitors.

Quantitative Serum NMR Spectroscopy Stratifies COVID-19 Patients and Sheds Light on Interfaces of Host Metabolism and the Immune Response with Cytokines and Clinical Parameters

The complex manifestations of COVID-19 are still not fully decoded on the molecular level. We combined quantitative the nuclear magnetic resonance (NMR) spectroscopy serum analysis of metabolites, lipoproteins and inflammation markers with clinical parameters and a targeted cytokine panel to characterize COVID-19 in a large (534 patient samples, 305 controls) outpatient cohort of recently tested PCR-positive patients. The COVID-19 cohort consisted of patients who were predominantly in the initial phase of the disease and mostly exhibited a milder disease course. Concerning the metabolic profiles of SARS-CoV-2-infected patients, we identified markers of oxidative stress and a severe dysregulation of energy metabolism. NMR markers, such as phenylalanine, inflammatory glycoproteins (Glyc) and their ratio with the previously reported supramolecular phospholipid composite (Glyc/SPC), showed a predictive power comparable to laboratory parameters such as C-reactive protein (CRP) or ferritin. We demonstrated interfaces between the metabolism and the immune system, e.g., we could trace an interleukin (IL-6)-induced transformation of a high-density lipoprotein (HDL) to a pro-inflammatory actor. Finally, we showed that metadata such as age, sex and constitution (e.g., body mass index, BMI) need to be considered when exploring new biomarkers and that adding NMR parameters to existing diagnoses expands the diagnostic toolbox for patient stratification and personalized medicine.

A Time-Series Metabolomic Analysis of SARS-CoV-2 Infection in a Ferret Model

The global threat of COVID-19 has led to an increased use of metabolomics to study SARS-CoV-2 infections in animals and humans. In spite of these efforts, however, understanding the metabolome of SARS-CoV-2 during an infection remains difficult and incomplete. In this study, metabolic responses to a SAS-CoV-2 challenge experiment were studied in nasal washes collected from an asymptomatic ferret model (n = 20) at different time points before and after infection using an LC-MS-based metabolomics approach. A multivariate analysis of the nasal wash metabolome data revealed several statistically significant features. Despite no effects of sex or interaction between sex and time on the time course of SARS-CoV-2 infection, 16 metabolites were significantly different at all time points post-infection. Among these altered metabolites, the relative abundance of taurine was elevated post-infection, which could be an indication of hepatotoxicity, while the accumulation of sialic acids could indicate SARS-CoV-2 invasion. Enrichment analysis identified several pathways influenced by SARS-CoV-2 infection. Of these, sugar, glycan, and amino acid metabolisms were the key altered pathways in the upper respiratory channel during infection. These findings provide some new insights into the progression of SARS-CoV-2 infection in ferrets at the metabolic level, which could be useful for the development of early clinical diagnosis tools and new or repurposed drug therapies.

Serum N-glycomic profiling may provide potential signatures for surveillance of COVID-19

Disease development and progression are often associated with aberrant glycosylation, indicating that changes in biological fluid glycome may potentially serve as disease signatures. The corona virus disease-2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) represents a significant threat to global human health. However, the effect of SARS-CoV-2 infection on the overall serum N-glycomic profile has been largely unexplored. Here, we extended our 96-well-plate-based high-throughput, high-sensitivity N-glycan profiling platform further with the aim of elucidating potential COVID-19-associated serum N-glycomic alterations. Use of this platform revealed both similarities and differences between the serum N-glycomic fingerprints of COVID-19 positive and control cohorts. Although there were no specific glycan peaks exclusively present or absent in COVID-19 positive cohort, this cohort showed significantly higher levels of glycans and variability. On the contrary, the overall N-glycomic profiles for healthy controls were well-contained within a narrow range. From the serum glycomic analysis, we were able to deduce changes in different glycan subclasses sharing certain structural features. Of significance was the hyperbranched and hypersialylated glycans and their derived glycan subclass traits. T-distributed stochastic neighbour embedding (tSNE) and hierarchical heatmap clustering analysis were performed to identify 13 serum glycomic variables that potentially distinguished the COVID-19 positive from healthy controls. Such serum N-glycomic changes described herein may indicate or correlate to the changes in serum glycoproteins upon COVID-19 infection. Furthermore, mapping the serum N-glycome following SARS-CoV-2 infection may help us better understand the disease and enable "Long-COVID" surveillance to capture the full spectrum of persistent symptoms.

Profiling metabolites and lipoproteins in COMETA, an Italian cohort of COVID-19 patients

Metabolomics and lipidomics have been used in several studies to define the biochemical alterations induced by COVID-19 in comparison with healthy controls. Those studies highlighted the presence of a strong signature, attributable to both metabolites and lipoproteins/lipids. Here, 1H NMR spectra were acquired on EDTA-plasma from three groups of subjects: i) hospitalized COVID-19 positive patients (≤21 days from the first positive nasopharyngeal swab); ii) hospitalized COVID-19 positive patients (>21 days from the first positive nasopharyngeal swab); iii) subjects after 2–6 months from SARS-CoV-2 eradication. A Random Forest model built using the EDTA-plasma spectra of COVID-19 patients ≤21 days and Post COVID-19 subjects, provided a high discrimination accuracy (93.6%), indicating both the presence of a strong fingerprint of the acute infection and the substantial metabolic healing of Post COVID-19 subjects. The differences originate from significant alterations in the concentrations of 16 metabolites and 74 lipoprotein components. The model was then used to predict the spectra of COVID-19>21 days subjects. In this group, the metabolite levels are closer to those of the Post COVID-19 subjects than to those of the COVID-19≤21 days; the opposite occurs for the lipoproteins. Within the acute phase patients, characteristic trends in metabolite levels are observed as a function of the disease severity. The metabolites found altered in COVID-19≤21 days patients with respect to Post COVID-19 individuals overlap with acute infection biomarkers identified previously in comparison with healthy subjects. Along the trajectory towards healing, the metabolome reverts back to the “healthy” state faster than the lipoproteome.

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).

Solid-state 1H NMR-based metabolomics assessment of tributylin effects in zebrafish bone

Tributyltin (TBT), an endocrine disruptor is used globally in agribusiness and industries as biocides, heat stabilizers, and in chemical catalysis. It is known for its deleterious effects on bone by negatively impacting the functions of osteoblasts, osteoclasts and mesenchymal stem cells. However, the impact of TBT on the metabolomics profile in bone is not yet studied. Here, we demonstrate alterations in chemical metabolomics profiles measured by solid state ¹H nuclear magnetic resonance (¹H NMR) spectroscopy in zebrafish bone following tributyltin (TBT) treatment. TBT of 0, 100, 200, 300, 400 and 500 μg/L were exposed to zebrafish. From this, zebrafish bone has subjected for further metabolomics profiling. Samples were measured via one-dimensional (1D) solvent -suppressed and T₂- filtered methods with in vivo zebrafish metabolites. A dose dependent alteration in the metabolomics profile was observed and results indicated a disturbed aminoacid metabolism, TCA cycle, and glycolysis. We found a significant alteration in the levels of glutamate, glutamine, glutathione, trimethylamine N-oxide (TMAO), and other metabolites. This investigation hints us the deleterious effects of TBT on zebrafish bone enabling a comprehensive understanding of metabolomics profile and is expected to play a crucial role in understanding the deleterious effects of various endocrine disruptor on bone.

Direct low field J-edited diffusional proton NMR spectroscopic measurement of COVID-19 inflammatory biomarkers in human serum

A JEDI NMR pulse experiment incorporating relaxation, diffusion and J-modulation peak editing was implemented at a low field (80 MHz) spectrometer system to quantify two recently discovered plasma markers of SARS-CoV-2 infection and general inflammation.

Quantification of choline in serum and plasma using a clinical nuclear magnetic resonance analyzer

BACKGROUND

Choline, a gut microbiome metabolite, is associated with cardiovascular risk and other chronic illnesses. The aim was to develop a high-throughput nuclear magnetic resonance (NMR)-based assay to measure choline on the Vantera® Clinical Analyzer.

METHODS

A non-negative deconvolution algorithm was developed to quantify choline. Assay performance was evaluated using CLSI guidelines.

RESULTS

Deming regression analysis comparing choline concentrations by NMR and mass spectrometry (n = 28) exhibited a correlation coefficient of 0.998 (intercept = -9.216, slope = 1.057). The LOQ were determined to be 7.1 µmol/L in serum and 5.9 µmol/L in plasma. The coefficients of variation (%CV) for intra- and inter-assay precision ranged from 6.2 to 14.8% (serum) and 5.4-11.3% (plasma). Choline concentrations were lower in EDTA plasma by as much as 38% compared to serum, however, choline was less stable in serum compared to plasma. In a population of apparently healthy adults, the reference interval was <7.1-20.0 µmol/L (serum) and <5.9-13.1 µmol/L (plasma). Linearity was demonstrated well beyond these intervals. No interference was observed for a number of substances tested.

CONCLUSIONS

The newly developed, high-throughput NMR-based assay exhibited good performance characteristics enabling quantification of choline in serum and plasma for clinical use.

Metabolomic diferences between COVID-19 and H1N1 influenza induced ARDS

BACKGROUND

Acute respiratory distress syndrome (ARDS) is a type of respiratory failure characterized by lung inflammation and pulmonary edema. Coronavirus disease 2019 (COVID-19) is associated with ARDS in the more severe cases. This study aimed to compare the specificity of the metabolic alterations induced by COVID-19 or Influenza A pneumonia (IAP) in ARDS.

METHODS

Eighteen patients with ARDS due to COVID-19 and twenty patients with ARDS due to IAP, admitted to the intensive care unit. ARDS was defined as in the American-European Consensus Conference. As compared with patients with COVID-19, patients with IAP were younger and received more often noradrenaline to maintain a mean arterial pressure > 65 mm Hg. Serum samples were analyzed by Nuclear Magnetic Resonance Spectroscopy. Multivariate Statistical Analyses were used to identify metabolic differences between groups. Metabolic pathway analysis was performed to identify the most relevant pathways involved in ARDS development.

RESULTS

ARDS due to COVID-19 or to IAP induces a different regulation of amino acids metabolism, lipid metabolism, glycolysis, and anaplerotic metabolism. COVID-19 causes a significant energy supply deficit that induces supplementary energy-generating pathways. In contrast, IAP patients suffer more marked inflammatory and oxidative stress responses. The classificatory model discriminated against the cause of pneumonia with a success rate of 100%.

CONCLUSIONS

Our findings support the concept that ARDS is associated with a characteristic metabolomic profile that may discriminate patients with ARDS of different etiologies, being a potential biomarker for the diagnosis, prognosis, and management of this condition.

Molecular Phenomic Approaches to Deconvolving the Systemic Effects of SARS-CoV-2 Infection and Post-acute COVID-19 Syndrome

SARS COV-2 infection causes acute and frequently severe respiratory disease with associated multi-organ damage and systemic disturbances in many biochemical pathways. Metabolic phenotyping provides deep insights into the complex immunopathological problems that drive the resulting COVID-19 disease and is also a source of novel metrics for assessing patient recovery. A multiplatform metabolic phenotyping approach to studying the pathology and systemic metabolic sequelae of COVID-19 is considered here, together with a framework for assessing post-acute COVID-19 Syndrome (PACS) that is a major long-term health consequence for many patients. The sudden emergence of the disease presents a biological discovery challenge as we try to understand the pathological mechanisms of the disease and develop effective mitigation strategies. This requires technologies to measure objectively the extent and sub-phenotypes of the disease at the molecular level. Spectroscopic methods can reveal metabolic sub-phenotypes and new biomarkers that can be monitored during the acute disease phase and beyond. This approach is scalable and translatable to other pathologies and provides as an exemplar strategy for the investigation of other emergent zoonotic diseases with complex immunological drivers, multi-system involvements and diverse persistent symptoms.

Integrative Modeling of Plasma Metabolic and Lipoprotein Biomarkers of SARS-CoV-2 Infection in Spanish and Australian COVID-19 Patient Cohorts

Quantitative plasma lipoprotein and metabolite profiles were measured on an autonomous community of the Basque Country (Spain) cohort consisting of hospitalized COVID-19 patients (n = 72) and a matched control group (n = 75) and a Western Australian (WA) cohort consisting of (n = 17) SARS-CoV-2 positives and (n = 20) healthy controls using 600 MHz ¹H nuclear magnetic resonance (NMR) spectroscopy. Spanish samples were measured in two laboratories using one-dimensional (1D) solvent-suppressed and T₂-filtered methods with in vitro diagnostic quantification of lipoproteins and metabolites. SARS-CoV-2 positive patients and healthy controls from both populations were modeled and cross-projected to estimate the biological similarities and validate biomarkers. Using the top 15 most discriminatory variables enabled construction of a cross-predictive model with 100% sensitivity and specificity (within populations) and 100% sensitivity and 82% specificity (between populations). Minor differences were observed between the control metabolic variables in the two cohorts, but the lipoproteins were virtually indistinguishable. We observed highly significant infection-related reductions in high-density lipoprotein (HDL) subfraction 4 phospholipids, apolipoproteins A1 and A2,that have previously been associated with negative regulation of blood coagulation and fibrinolysis. The Spanish and Australian diagnostic SARS-CoV-2 biomarkers were mathematically and biologically equivalent, demonstrating that NMR-based technologies are suitable for the study of the comparative pathology of COVID-19 via plasma phenotyping.

Incomplete Systemic Recovery and Metabolic Phenoreversion in Post-Acute-Phase Nonhospitalized COVID-19 Patients: Implications for Assessment of Post-Acute COVID-19 Syndrome

We present a multivariate metabotyping approach to assess the functional recovery of nonhospitalized COVID-19 patients and the possible biochemical sequelae of "Post-Acute COVID-19 Syndrome", colloquially known as long-COVID. Blood samples were taken from patients ca. 3 months after acute COVID-19 infection with further assessment of symptoms at 6 months. Some 57% of the patients had one or more persistent symptoms including respiratory-related symptoms like cough, dyspnea, and rhinorrhea or other nonrespiratory symptoms including chronic fatigue, anosmia, myalgia, or joint pain. Plasma samples were quantitatively analyzed for lipoproteins, glycoproteins, amino acids, biogenic amines, and tryptophan pathway intermediates using Nuclear Magnetic Resonance (NMR) spectroscopy and mass spectrometry. Metabolic data for the follow-up patients (n = 27) were compared with controls (n = 41) and hospitalized severe acute respiratory syndrome SARS-CoV-2 positive patients (n = 18, with multiple time-points). Univariate and multivariate statistics revealed variable patterns of functional recovery with many patients exhibiting residual COVID-19 biomarker signatures. Several parameters were persistently perturbed, e.g., elevated taurine (p = 3.6 × 10-3 versus controls) and reduced glutamine/glutamate ratio (p = 6.95 × 10-8 versus controls), indicative of possible liver and muscle damage and a high energy demand linked to more generalized tissue repair or immune function. Some parameters showed near-complete normalization, e.g., the plasma apolipoprotein B100/A1 ratio was similar to that of healthy controls but significantly lower (p = 4.2 × 10-3) than post-acute COVID-19 patients, reflecting partial reversion of the metabolic phenotype (phenoreversion) toward the healthy metabolic state. Plasma neopterin was normalized in all follow-up patients, indicative of a reduction in the adaptive immune activity that has been previously detected in active SARS-CoV-2 infection. Other systemic inflammatory biomarkers such as GlycA and the kynurenine/tryptophan ratio remained elevated in some, but not all, patients. Correlation analysis, principal component analysis (PCA), and orthogonal-partial least-squares discriminant analysis (O-PLS-DA) showed that the follow-up patients were, as a group, metabolically distinct from controls and partially comapped with the acute-phase patients. Significant systematic metabolic differences between asymptomatic and symptomatic follow-up patients were also observed for multiple metabolites. The overall metabolic variance of the symptomatic patients was significantly greater than that of nonsymptomatic patients for multiple parameters (χ2p = 0.014). Thus, asymptomatic follow-up patients including those with post-acute COVID-19 Syndrome displayed a spectrum of multiple persistent biochemical pathophysiology, suggesting that the metabolic phenotyping approach may be deployed for multisystem functional assessment of individual post-acute COVID-19 patients.

Systemic Perturbations in Amine and Kynurenine Metabolism Associated with Acute SARS-CoV-2 Infection and Inflammatory Cytokine Responses

We performed quantitative metabolic phenotyping of blood plasma in parallel with cytokine/chemokine analysis from participants who were either SARS-CoV-2 (+) (n = 10) or SARS-CoV-2 (-) (n = 49). SARS-CoV-2 positivity was associated with a unique metabolic phenotype and demonstrated a complex systemic response to infection, including severe perturbations in amino acid and kynurenine metabolic pathways. Nine metabolites were elevated in plasma and strongly associated with infection (quinolinic acid, glutamic acid, nicotinic acid, aspartic acid, neopterin, kynurenine, phenylalanine, 3-hydroxykynurenine, and taurine; p < 0.05), while four metabolites were lower in infection (tryptophan, histidine, indole-3-acetic acid, and citrulline; p < 0.05). This signature supports a systemic metabolic phenoconversion following infection, indicating possible neurotoxicity and neurological disruption (elevations of 3-hydroxykynurenine and quinolinic acid) and liver dysfunction (reduction in Fischer's ratio and elevation of taurine). Finally, we report correlations between the key metabolite changes observed in the disease with concentrations of proinflammatory cytokines and chemokines showing strong immunometabolic disorder in response to SARS-CoV-2 infection.