The serum metabolome of COVID-19 patients is distinctive and predictive

Associations between blood nickel and lung function in young Chinese: An observational study combining epidemiology and metabolomics

Prior research has explored the relationship between occupational exposure to nickel and lung function. Nonetheless, there is limited research examining the correlation between blood nickel levels and lung function among young adults in the general population. The metabolomic changes associated with nickel exposure have not been well elucidated. On August 23, 2019, we enrolled 257 undergraduate participants from the Chinese Undergraduates Cohort to undergo measurements of blood nickel levels and lung function. The follow-up study was conducted in May 2021. A linear mixed-effects model was employed to assess the relationship between blood nickel levels and lung function. We also conducted stratified analyses by home address. In addition, in order to explore the biological mechanism of lung function damage caused by nickel exposure, we performed metabolomic analyses of baseline serum samples (N = 251). Both analysis of variance and mixed linear effect models were utilized to assess the impact of blood nickel exposure on metabolism. Our findings from cross-sectional and cohort analyses revealed a significant association between blood nickel levels and decreased forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) among young adults in the general population. Furthermore, we found stronger associations in urban areas. In metabolomics analysis, a total of nine metabolites were significantly changed under blood nickel exposure. The changed metabolites were mainly enriched in six pathways including carbohydrate, amino acid, and cofactor vitamin metabolism. These metabolic pathways involve inflammation and oxidative stress, indicating that high concentrations of nickel exposure can cause inflammation and oxidative stress by disrupting the above metabolism of the body.

Mass spectrometric approaches in discovering lipid biomarkers for COVID-19 by lipidomics: Future challenges and perspectives

Coronavirus disease 2019 (COVID-19) has emerged as a global health threat and has rapidly spread worldwide. Significant changes in the lipid profile before and after COVID-19 confirmed the significance of lipid metabolism in regulating the response to viral infection. Therefore, understanding the role of lipid metabolism may facilitate the development of new therapeutics for COVID-19. Owing to their high sensitivity and accuracy, mass spectrometry (MS)-based methods are widely used for rapidly identifying and quantifying of thousands of lipid species present in a small amount of sample. To enhance the capabilities of MS for the qualitative and quantitative analysis of lipids, different platforms have been combined to cover a wide range of lipidomes with high sensitivity, specificity, and accuracy. Currently, MS-based technologies are being established as efficient methods for discovering potential diagnostic biomarkers for COVID-19 and related diseases. As the lipidome of the host cell is drastically affected by the viral replication process, investigating lipid profile alterations in patients with COVID-19 and targeting lipid metabolism pathways are considered to be crucial steps in host-directed drug targeting to develop better therapeutic strategies. This review summarizes various MS-based strategies that have been developed for lipidomic analyzes and biomarker discoveries to combat COVID-19 by integrating various other potential approaches using different human samples. Furthermore, this review discusses the challenges in using MS technologies and future perspectives in terms of drug discovery and diagnosis of COVID-19.

High expression of oleoyl-ACP hydrolase underpins life-threatening respiratory viral diseases

Respiratory infections cause significant morbidity and mortality, yet it is unclear why some individuals succumb to severe disease. In patients hospitalized with avian A(H7N9) influenza, we investigated early drivers underpinning fatal disease. Transcriptomics strongly linked oleoyl-acyl-carrier-protein (ACP) hydrolase (OLAH), an enzyme mediating fatty acid production, with fatal A(H7N9) early after hospital admission, persisting until death. Recovered patients had low OLAH expression throughout hospitalization. High OLAH levels were also detected in patients hospitalized with life-threatening seasonal influenza, COVID-19, respiratory syncytial virus (RSV), and multisystem inflammatory syndrome in children (MIS-C) but not during mild disease. In olah-/- mice, lethal influenza infection led to survival and mild disease as well as reduced lung viral loads, tissue damage, infection-driven pulmonary cell infiltration, and inflammation. This was underpinned by differential lipid droplet dynamics as well as reduced viral replication and virus-induced inflammation in macrophages. Supplementation of oleic acid, the main product of OLAH, increased influenza replication in macrophages and their inflammatory potential. Our findings define how the expression of OLAH drives life-threatening viral disease.

Reinforcing the Evidence of Mitochondrial Dysfunction in Long COVID Patients Using a Multiplatform Mass Spectrometry-Based Metabolomics Approach

Despite the recent and increasing knowledge surrounding COVID-19 infection, the underlying mechanisms of the persistence of symptoms for a long time after the acute infection are still not completely understood. Here, a multiplatform mass spectrometry-based approach was used for metabolomic and lipidomic profiling of human plasma samples from Long COVID patients (n = 40) to reveal mitochondrial dysfunction when compared with individuals fully recovered from acute mild COVID-19 (n = 40). Untargeted metabolomic analysis using CE-ESI(+/-)-TOF-MS and GC-Q-MS was performed. Additionally, a lipidomic analysis using LC-ESI(+/-)-QTOF-MS based on an in-house library revealed 447 lipid species identified with a high confidence annotation level. The integration of complementary analytical platforms has allowed a comprehensive metabolic and lipidomic characterization of plasma alterations in Long COVID disease that found 46 relevant metabolites which allowed to discriminate between Long COVID and fully recovered patients. We report specific metabolites altered in Long COVID, mainly related to a decrease in the amino acid metabolism and ceramide plasma levels and an increase in the tricarboxylic acid (TCA) cycle, reinforcing the evidence of an impaired mitochondrial function. The most relevant alterations shown in this study will help to better understand the insights of Long COVID syndrome by providing a deeper knowledge of the metabolomic basis of the pathology.

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.

Total plasma N-glycomic signature of SARS-CoV-2 infection

Total plasma protein N-glycosylation (TPNG) changes are a hallmark of many diseases. Here, we analyzed the TPNG of 169 COVID-19 patients and 12 healthy controls, using mass spectrometry, resulting in the relative quantification of 85 N-glycans. We found a COVID-19 N-glycomic signature, with 59 glycans differing between patients and controls, many of them additionally differentiating between severe and mild COVID-19. Tri- and tetra-antennary N-glycans were increased in patients, showing additionally elevated levels of antennary α2,6-sialylation. Conversely, bisection of di-antennary, core-fucosylated, nonsialylated glycans was low in COVID-19, particularly in severe cases, potentially driven by the previously observed low levels of bisection on antibodies of severely diseased COVID-19 patients. These glycomic changes point toward systemic changes in the blood glycoproteome, particularly involvement of acute-phase proteins, immunoglobulins and the complement cascade. Further research is needed to dissect glycosylation changes in a protein- and site-specific way to obtain specific functional leads.

Dysregulated proteasome activity and steroid hormone biosynthesis are associated with mortality among patients with acute COVID-19

The persistence of coronavirus disease 2019 (COVID-19)-related hospitalization severely threatens medical systems worldwide and has increased the need for reliable detection of acute status and prediction of mortality. We applied a systems biology approach to discover acute-stage biomarkers that could predict mortality. A total 247 plasma samples were collected from 103 COVID-19 (52 surviving COVID-19 patients and 51 COVID-19 patients with mortality), 51 patients with other infectious diseases (IDCs) and 41 healthy controls (HCs). Paired plasma samples were obtained from survival COVID-19 patients within 1 day after hospital admission and 1-3 days before discharge. There were clear differences between COVID-19 patients and controls, as well as substantial differences between the acute and recovery phases of COVID-19. Samples from patients in the acute phase showed suppressed immunity and decreased steroid hormone biosynthesis, as well as elevated inflammation and proteasome activation. These findings were validated by enzyme-linked immunosorbent assays and metabolomic analyses in a larger cohort. Moreover, excessive proteasome activity was a prominent signature in the acute phase among patients with mortality, indicating that it may be a key cause of poor prognosis. Based on these features, we constructed a machine learning panel, including four proteins [C-reactive protein (CRP), proteasome subunit alpha type (PSMA)1, PSMA7, and proteasome subunit beta type (PSMB)1)] and one metabolite (urocortisone), to predict mortality among COVID-19 patients (area under the receiver operating characteristic curve: 0.976) on the first day of hospitalization. Our systematic analysis provides a novel method for the early prediction of mortality in hospitalized COVID-19 patients.

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

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

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

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

When Our Best Friend Becomes Our Worst Enemy: The Mitochondrion in Trauma, Surgery, and Critical Illness

Common for major surgery, multitrauma, sepsis, and critical illness, is a whole-body inflammation. Tissue injury is able to trigger a generalized inflammatory reaction. Cell death causes release of endogenous structures termed damage associated molecular patterns (DAMPs) that initiate a sterile inflammation. Mitochondria are evolutionary endosymbionts originating from bacteria, containing molecular patterns similar to bacteria. These molecular patterns are termed mitochondrial DAMPs (mDAMPs). Mitochondrial debris released into the extracellular space or into the circulation is immunogenic and damaging secondary to activation of the innate immune system. In the circulation, released mDAMPS are either free or exist in extracellular vesicles, being able to act on every organ and cell in the body. However, the role of mDAMPs in trauma and critical care is not fully clarified. There is a complete lack of knowledge how they may be counteracted in patients. Among mDAMPs are mitochondrial DNA, cardiolipin, N-formyl peptides, cytochrome C, adenosine triphosphate, reactive oxygen species, succinate, and mitochondrial transcription factor A. In this overview, we present the different mDAMPs, their function, release, targets, and inflammatory potential. In light of present knowledge, the role of mDAMPs in the pathophysiology of major surgery and trauma as well as sepsis, and critical care is discussed.

Comprehensive blood metabolomics profiling of Parkinson's disease reveals coordinated alterations in xanthine metabolism

Parkinson's disease (PD) is a highly heterogeneous disorder influenced by several environmental and genetic factors. Effective disease-modifying therapies and robust early-stage biomarkers are still lacking, and an improved understanding of the molecular changes in PD could help to reveal new diagnostic markers and pharmaceutical targets. Here, we report results from a cohort-wide blood plasma metabolic profiling of PD patients and controls in the Luxembourg Parkinson's Study to detect disease-associated alterations at the level of systemic cellular process and network alterations. We identified statistically significant changes in both individual metabolite levels and global pathway activities in PD vs. controls and significant correlations with motor impairment scores. As a primary observation when investigating shared molecular sub-network alterations, we detect pronounced and coordinated increased metabolite abundances in xanthine metabolism in de novo patients, which are consistent with previous PD case/control transcriptomics data from an independent cohort in terms of known enzyme-metabolite network relationships. From the integrated metabolomics and transcriptomics network analysis, the enzyme hypoxanthine phosphoribosyltransferase 1 (HPRT1) is determined as a potential key regulator controlling the shared changes in xanthine metabolism and linking them to a mechanism that may contribute to pathological loss of cellular adenosine triphosphate (ATP) in PD. Overall, the investigations revealed significant PD-associated metabolome alterations, including pronounced changes in xanthine metabolism that are mechanistically congruent with alterations observed in independent transcriptomics data. The enzyme HPRT1 may merit further investigation as a main regulator of these network alterations and as a potential therapeutic target to address downstream molecular pathology in PD.

Using a targeted metabolomics approach to explore differences in ARDS associated with COVID-19 compared to ARDS caused by H1N1 influenza and bacterial pneumonia

RATIONALE

Acute respiratory distress syndrome (ARDS) is a life-threatening critical care syndrome commonly associated with infections such as COVID-19, influenza, and bacterial pneumonia. Ongoing research aims to improve our understanding of ARDS, including its molecular mechanisms, individualized treatment options, and potential interventions to reduce inflammation and promote lung repair.

OBJECTIVE

To map and compare metabolic phenotypes of different infectious causes of ARDS to better understand the metabolic pathways involved in the underlying pathogenesis.

METHODS

We analyzed metabolic phenotypes of 3 ARDS cohorts caused by COVID-19, H1N1 influenza, and bacterial pneumonia compared to non-ARDS COVID-19-infected patients and ICU-ventilated controls. Targeted metabolomics was performed on plasma samples from a total of 150 patients using quantitative LC-MS/MS and DI-MS/MS analytical platforms.

RESULTS

Distinct metabolic phenotypes were detected between different infectious causes of ARDS. There were metabolomics differences between ARDSs associated with COVID-19 and H1N1, which include metabolic pathways involving taurine and hypotaurine, pyruvate, TCA cycle metabolites, lysine, and glycerophospholipids. ARDSs associated with bacterial pneumonia and COVID-19 differed in the metabolism of D-glutamine and D-glutamate, arginine, proline, histidine, and pyruvate. The metabolic profile of COVID-19 ARDS (C19/A) patients admitted to the ICU differed from COVID-19 pneumonia (C19/P) patients who were not admitted to the ICU in metabolisms of phenylalanine, tryptophan, lysine, and tyrosine. Metabolomics analysis revealed significant differences between C19/A, H1N1/A, and PNA/A vs ICU-ventilated controls, reflecting potentially different disease mechanisms.

CONCLUSION

Different metabolic phenotypes characterize ARDS associated with different viral and bacterial infections.

MetaboliteCOVID: A manually curated database of metabolite markers for COVID-19

In the realm of unraveling COVID-19's intricacies, numerous metabolomic investigations have been conducted to discern the unique metabolic traits exhibited within infected patients. These endeavors have yielded a substantial reservoir of potential data pertaining to metabolic biomarkers linked to the virus. Despite these strides, a comprehensive and meticulously structured database housing these crucial biomarkers remains absent. In this study, we developed MetaboliteCOVID, a manually curated database of COVID-19-related metabolite markers. The database currently comprises 665 manually selected entries of significantly altered metabolites associated with early diagnosis, disease severity, prognosis, and drug response in COVID-19, encompassing 337 metabolites. Additionally, the database offers a user-friendly interface, containing abundant information for querying, browsing, and analyzing COVID-19-related abnormal metabolites in different body fluids. In summary, we believe that this database will effectively facilitate research on the functions and mechanisms of COVID-19-related metabolic biomarkers, thereby advancing both basic and clinical research on COVID-19. MetaboliteCOVID is free available at: https://cellknowledge.com.cn/MetaboliteCOVID.

COVID-19-associated liver injury: Adding fuel to the flame

COVID-19 is mainly characterized by respiratory disorders and progresses to multiple organ involvement in severe cases. With expansion of COVID-19 and SARS-CoV-2 research, correlative liver injury has been revealed. It is speculated that COVID-19 patients exhibited abnormal liver function, as previously observed in the SARS and MERS pandemics. Furthermore, patients with underlying diseases such as chronic liver disease are more susceptible to SARS-CoV-2 and indicate a poor prognosis accompanied by respiratory symptoms, systemic inflammation, or metabolic diseases. Therefore, COVID-19 has the potential to impair liver function, while individuals with preexisting liver disease suffer from much worse infected conditions. COVID-19 related liver injury may be owing to direct cytopathic effect, immune dysfunction, gut-liver axis interaction, and inappropriate medication use. However, discussions on these issues are infancy. Expanding research have revealed that angiotensin converting enzyme 2 (ACE2) expression mediated the combination of virus and target cells, iron metabolism participated in the virus life cycle and the fate of target cells, and amino acid metabolism regulated immune response in the host cells, which are all closely related to liver health. Further exploration holds great significance in elucidating the pathogenesis, facilitating drug development, and advancing clinical treatment of COVID-19-related liver injury. This article provides a review of the clinical and laboratory hepatic characteristics in COVID-19 patients, describes the etiology and impact of liver injury, and discusses potential pathophysiological mechanisms.

Analysis of clinical characteristics and risk factors between elderly patients with severe and nonsevere Omicron variant infection

BACKGROUND

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to millions of confirmed cases and deaths worldwide. Elderly patients are at high risk of developing and dying from COVID-19 due to advanced age, decreased immune function, intense inflammatory response, and comorbidities. Shanghai has experienced a wave of infection with Omicron, a new variant of SARS-CoV-2, since March 2022. There is a pressing need to identify clinical features and risk factors for disease progression among elderly patients with Omicron infection to provide solid evidence for clinical policy-makers, public health officials, researchers, and the general public.

AIM

To investigate clinical characteristic differences and risk factors between elderly patients with severe and nonsevere Omicron SARS-CoV-2 variant infection.

METHODS

A total of 328 elderly patients with COVID-19 admitted to the Ninth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from April 2022 to June 2022 were enrolled and divided into a severe group (82 patients) and a nonsevere group (246 patients) according to the diagnosis and treatment protocol of COVID-19 (version 7). The clinical data and laboratory results of both groups were collected and compared. A chi-square test, t test, Mann-Whitney U test, hierarchical log-rank test, univariate and multivariate logistic regression, and hierarchical analyses were used to determine significant differences.

RESULTS

The severe group was older (84 vs 74 years, P < 0.001), included more males (57.3% vs 43.9%, P = 0.037), had a lower vaccination rate (P < 0.001), and had a higher proportion of comorbidities, including chronic respiratory disease (P = 0.001), cerebral infarction (P < 0.001), chronic kidney disease (P = 0.002), and neurodegenerative disease (P < 0.001), than the nonsevere group. In addition, severe disease patients had a higher inflammatory index (P < 0.001), greater need for symptomatic treatment (P < 0.001), longer hospital stay (P = 0.011), extended viral shedding time (P = 0.014), and higher mortality than nonsevere disease patients (P < 0.001). No difference was observed in the application of Paxlovid in the severe and nonsevere groups (P = 0.817). Oxygen saturation, cerebral infarction, and D-dimer were predictive factors for developing severe disease in patients with COVID-19, with D-dimer having an excellent role (area under the curve: 90.1%, 95%CI: 86.1-94.0%). In addition, D-dimer was a risk factor for developing severe COVID-19 according to multivariate stratified analysis.

CONCLUSION

The clinical course of severe COVID-19 is complex, with a higher need for symptomatic treatment. D-dimer is a suitable biomarker for identifying patients at risk for developing severe COVID-19.

A comparative NMR-based metabolomics study of lung parenchyma of severe COVID-19 patients

COVID-19 was the most significant infectious-agent-related cause of death in the 2020-2021 period. On average, over 60% of those admitted to ICU facilities with this disease died across the globe. In severe cases, COVID-19 leads to respiratory and systemic compromise, including pneumonia-like symptoms, acute respiratory distress syndrome, and multiorgan failure. While the upper respiratory tract and lungs are the principal sites of infection and injury, most studies on the metabolic signatures in COVID-19 patients have been carried out on serum and plasma samples. In this report we attempt to characterize the metabolome of lung parenchyma extracts from fatal COVID-19 cases and compare them with that from other respiratory diseases. Our findings indicate that the metabolomic profiles from fatal COVID-19 and non-COVID-19 cases are markedly different, with the former being the result of increased lactate and amino acid metabolism, altered energy pathways, oxidative stress, and inflammatory response. Overall, these findings provide additional insights into the pathophysiology of COVID-19 that could lead to the development of targeted therapies for the treatment of severe cases of the disease, and further highlight the potential of metabolomic approaches in COVID-19 research.

Human blood metabolites and risk of severe COVID-19: A Mendelian randomization study

BACKGROUND

Evidence supports the observational associations of human blood metabolites with the risk of severe COVID-19. However, little is known about the potential pathological mechanisms and the analysis of blood metabolites may offer a better understanding of the underlying biological processes.

METHODS

We applied a two-sample Mendelian randomization (MR) analysis to evaluate relationships between 486 blood metabolites and the risk of severe COVID-19. The inverse-variance weighted (IVW) model was used as the primary two-sample MR analysis method to estimate the causal relationship of the exposure on the outcome. Sensitivity analyses were implemented with Cochran's Q test, MR-Egger intercept test, MR-PRESSO, leave-one-out analysis and the funnel plot.

RESULTS

Four hunderd and eighty six metabolites were included for MR analysis following rigorous genetic variants selection. After MR analyses and sensitivity analysis filtration, we found weak evidence of an association between 3-hydroxybutyrate (odds ratio [OR] = 1.21, 95% CI, 1.07-1.38, p = .0036) and the risk of severe COVID-19. A series of sensitivity analyses have been carried out to confirm the rigidity of the above results.

CONCLUSION

This study suggested a causal relationship between 3-hydroxybutyrate and the severity of COVID-19, thus providing novel insights into biomarkers and pathways for COVID-19 prevention and clinical interventions.

Serotonin reduction in post-acute sequelae of viral infection

Post-acute sequelae of COVID-19 (PASC, "Long COVID") pose a significant global health challenge. The pathophysiology is unknown, and no effective treatments have been found to date. Several hypotheses have been formulated to explain the etiology of PASC, including viral persistence, chronic inflammation, hypercoagulability, and autonomic dysfunction. Here, we propose a mechanism that links all four hypotheses in a single pathway and provides actionable insights for therapeutic interventions. We find that PASC are associated with serotonin reduction. Viral infection and type I interferon-driven inflammation reduce serotonin through three mechanisms: diminished intestinal absorption of the serotonin precursor tryptophan; platelet hyperactivation and thrombocytopenia, which impacts serotonin storage; and enhanced MAO-mediated serotonin turnover. Peripheral serotonin reduction, in turn, impedes the activity of the vagus nerve and thereby impairs hippocampal responses and memory. These findings provide a possible explanation for neurocognitive symptoms associated with viral persistence in Long COVID, which may extend to other post-viral syndromes.

Mitochondrial dysfunction, lipids metabolism, and amino acid biosynthesis are key pathways for COVID-19 recovery

The metabolic alterations caused by SARS-CoV-2 infection reflect disease progression. To analyze molecules involved in these metabolic changes, a multiomics study was performed using plasma from 103 patients with different degrees of COVID-19 severity during the evolution of the infection. With the increased severity of COVID-19, changes in circulating proteomic, metabolomic, and lipidomic profiles increased. Notably, the group of severe and critical patients with high HRG and ChoE (20:3) and low alpha-ketoglutaric acid levels had a high chance of unfavorable disease evolution (AUC = 0.925). Consequently, patients with the worst prognosis presented alterations in the TCA cycle (mitochondrial dysfunction), lipid metabolism, amino acid biosynthesis, and coagulation. Our findings increase knowledge regarding how SARS-CoV-2 infection affects different metabolic pathways and help in understanding the future consequences of COVID-19 to identify potential therapeutic targets.

COVID-19 and cholesterol biosynthesis: Towards innovative decision support systems

With COVID-19 becoming endemic, there is a continuing need to find biomarkers characterizing the disease and aiding in patient stratification. We studied the relation between COVID-19 and cholesterol biosynthesis by comparing 10 intermediates of cholesterol biosynthesis during the hospitalization of 164 patients (admission, disease deterioration, discharge) admitted to the University Medical Center of Ljubljana. The concentrations of zymosterol, 24-dehydrolathosterol, desmosterol, and zymostenol were significantly altered in COVID-19 patients. We further developed a predictive model for disease severity based on clinical parameters alone and their combination with a subset of sterols. Our machine learning models applying 8 clinical parameters predicted disease severity with excellent accuracy (AUC = 0.96), showing substantial improvement over current clinical risk scores. After including sterols, model performance remained better than COVID-GRAM. This is the first study to examine cholesterol biosynthesis during COVID-19 and shows that a subset of cholesterol-related sterols is associated with the severity of COVID-19.

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.

Dynamics of Organic Acids during the Droplet-Vitrification Cryopreservation Procedure Can Be a Signature of Oxidative Stress in Pogostemon yatabeanus

Cryopreservation in liquid nitrogen (LN, -196 °C) is a unique option for the long-term conservation of threatened plant species with non-orthodox or limitedly available seeds. In previous studies, a systematic approach was used to develop a droplet-vitrification (DV) cryopreservation protocol for Postemon yatabeanus shoot tips that includes preculture with 10% sucrose, osmoprotection with C4-35%, cryoprotection with A3-80% vitrification solution, and a three-step regrowth starting with the ammonium-free medium. The tricarboxylic acid (TCA) cycle is a crucial component of plant cell metabolism as it is involved in redox state regulation and energy provision. We hypothesized that organic acids (OAs) associated with the TCA and its side reactions indirectly indicate metabolism intensity and oxidative stress development in shoot tips under the cryopreservation procedure. In this study, the contents of 14 OAs were analyzed using gas chromatography-tandem mass spectrometry (GC-MS/MS) in P. yatabeanus shoot tips in a series of treatments including individual steps of the DV procedure, additional stress imposed by non-optimum protocol conditions (no preculture, no osmoprotection, various vitrification solution composition, using vials instead of aluminum foils, etc.) and regrowth on different media with or without ammonium or growth regulators. The possible relation of OA content with the total cryoprotectant (CPA) concentration and shoot tips regeneration percentage was also explored. Regeneration of cryopreserved shoot tips reduced in descending order as follows: standard protocol condition (91%) > non-optimum vitrification solution (ca. 68%) > non-optimum preculture (60-62%) > regrowth medium (40-64%) > no osmoprotection, cryopreservation in vials (28-30%). Five OAs (glycolic, malic, citric, malonic, and lactic) were the most abundant in the fresh (control) shoot tips. The dynamic pattern of OAs during the DV procedure highly correlated (r = 0.951) with the total CPA concentration employed: it gradually increased through the preculture, osmoprotection, and cryoprotection, peaked at cooling/rewarming (6.38-fold above control level), and returned to the fresh control level after 5 days of regrowth (0.89-fold). The contents of four OAs (2-hydroxybutyric, 3-hydroxypropionic, lactic, and glycolic) showed the most significant (10-209-fold) increase at the cooling/rewarming step. Lactic and glycolic acids were the major OAs at cooling/rewarming, accounting for 81% of the total OAs content. The OAs were categorized into three groups based on their dynamics during the cryopreservation protocol, and these groups were differently affected by protocol step modifications. However, there was no straightforward relationship between the dynamics of OAs and shoot tip regeneration. The results suggest that active modulation of OAs metabolism may help shoot tips to cope with osmotic stress and the chemical cytotoxicity\ of CPAs. Further intensive studies are needed to investigate the effect of cryopreservation on cell primarily metabolism and identify oxidative stress-related biomarkers in plant materials.

Differential abundance of lipids and metabolites related to SARS-CoV-2 infection and susceptibility

The mechanisms driving SARS-CoV-2 susceptibility remain poorly understood, especially the factors determining why unvaccinated individuals remain uninfected despite high-risk exposures. To understand lipid and metabolite profiles related with COVID-19 susceptibility and disease progression. We collected samples from an exceptional group of unvaccinated healthcare workers heavily exposed to SARS-CoV-2 but not infected ('non-susceptible') and subjects who became infected during the follow-up ('susceptible'), including non-hospitalized and hospitalized patients with different disease severity providing samples at early disease stages. Then, we analyzed their plasma metabolomic profiles using mass spectrometry coupled with liquid and gas chromatography. We show specific lipids profiles and metabolites that could explain SARS-CoV-2 susceptibility and COVID-19 severity. More importantly, non-susceptible individuals show a unique lipidomic pattern characterized by the upregulation of most lipids, especially ceramides and sphingomyelin, which could be interpreted as markers of low susceptibility to SARS-CoV-2 infection. This study strengthens the findings of other researchers about the importance of studying lipid profiles as relevant markers of SARS-CoV-2 pathogenesis.

Systematic Mendelian randomization study of the effect of gut microbiome and plasma metabolome on severe COVID-19

Background

COVID-19 could develop severe respiratory symptoms in certain infected patients, especially in the patients with immune disorders. Gut microbiome and plasma metabolome act important immunological modulators in the human body and could contribute to the immune responses impacting the progression of COVID-19. However, the causal relationship between specific intestinal bacteria, metabolites and severe COVID-19 remains not clear.

Methods

Based on two-sample Mendelian randomization (MR) framework, the causal effects of 131 intestinal taxa and 452 plasma metabolites on severe COVID-19 were evaluated. Single nucleotide polymorphisms (SNPs) strongly associated with the abundance of intestinal taxa and the concentration of plasma metabolites had been utilized as the instrument variables to infer whether they were causal factors of severe COVID-19. In addition, mediation analysis was conducted to find the potential association between the taxon and metabolite, and further colocalization analysis had been performed to validate the causal relationships.

Results

MR analysis identified 13 taxa and 53 metabolites, which were significantly associated with severe COVID-19 as causal factors. Mediation analysis revealed 11 mediated relationships. Myo-inositol, 2-stearoylglycerophosphocholine, and alpha-glutamyltyrosine, potentially contributed to the association of Howardella and Ruminiclostridium 6 with severe COVID-19, respectively. Butyrivibrio and Ruminococcus gnavus could mediate the association of myo-inositol and N-acetylalanine, respectively. In addition, Ruminococcus torques abundance was colocalized with severe COVID-19 (PP.H4 = 0.77) and the colon expression of permeability related protein RASIP1 (PP.H4 = 0.95).

Conclusions

Our study highlights the potential causal relationships between gut microbiome, plasma metabolome and severe COVID-19, which potentially serve as clinical biomarkers for risk stratification and prognostication and benefit the mechanism mechanistic investigation of severe COVID-19.

Neurological Sequelae of COVID-19: A Biochemical Perspective

Exogenous factors can induce protein expression and modify the proteome which sustains for a certain period of time. The proteins of SARS-CoV-2 are high in valine plus glycine, which possess potent affinity to divalent cations such as calcium. Calcium buildup changes the protein expression profile by enabling the efficient synthesis of proteins rich in amino acids with calcium affinity. Subsequent formation of insoluble and stiff calcium oxalate and aggregates confers cellular stress and causes cell senescence. This scenario accounts for sequelae seen in some patients following recovery from COVID-19.

COVID-19 Metabolomic-Guided Amino Acid Therapy Protects from Inflammation and Disease Sequelae

The outbreak of coronavirus disease 2019 (COVID-19) has caused a worldwide pandemic since 2019. A metabolic disorder is a contributing factor to deaths from COVID-19. However, the underlying mechanism of metabolic dysfunction in COVID-19 patients and the potential interventions are not elucidated. Here targeted plasma metabolomic is performed, and the metabolite profiles among healthy controls, and asymptomatic, moderate, and severe COVID-19 patients are compared. Among the altered metabolites, arachidonic acid and linolenic acid pathway metabolites are profoundly up-regulated in COVID-19 patients. Arginine biosynthesis, alanine, aspartate, and glutamate metabolism pathways are significantly disturbed in asymptomatic patients. In the comparison of metabolite variances among the groups, higher levels of l-citrulline and l-glutamine are found in asymptomatic carriers and moderate or severe patients at the remission stage. Furthermore, l-citrulline and l-glutamine combination therapy is demonstrated to effectively protect mice from coronavirus infection and endotoxin-induced sepsis, and is observed to efficiently prevent the occurrence of pulmonary fibrosis and central nervous system damage. Collectively, the data reveal the metabolite profile of asymptomatic COVID-19 patients and propose a potential strategy for COVID-19 treatment.

Statistical methods and resources for biomarker discovery using metabolomics

Metabolomics is a dynamic tool for elucidating biochemical changes in human health and disease. Metabolic profiles provide a close insight into physiological states and are highly volatile to genetic and environmental perturbations. Variation in metabolic profiles can inform mechanisms of pathology, providing potential biomarkers for diagnosis and assessment of the risk of contracting a disease. With the advancement of high-throughput technologies, large-scale metabolomics data sources have become abundant. As such, careful statistical analysis of intricate metabolomics data is essential for deriving relevant and robust results that can be deployed in real-life clinical settings. Multiple tools have been developed for both data analysis and interpretations. In this review, we survey statistical approaches and corresponding statistical tools that are available for discovery of biomarkers using metabolomics.

Oxalic acid blocked the binding of spike protein from SARS-CoV-2 Delta (B.1.617.2) and Omicron (B.1.1.529) variants to human angiotensin-converting enzymes 2

An epidemic of Corona Virus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is spreading worldwide. Moreover, the emergence of SARS-CoV-2 variants of concern, such as Delta and Omicron, has seriously challenged the application of current therapeutics including vaccination and drugs. Relying on interaction of spike protein with receptor angiotensin-converting enzymes 2 (ACE2), SARS-CoV-2 successfully invades to the host cells, which indicates a strategy that identification of small-molecular compounds to block the entry is of great significance for COVID-19 prevention. Our study evaluated the potential efficacy of natural compound oxalic acid (OA) as an inhibitory agent against SARS-CoV-2 invasion, particular on the interaction of the receptor binding domain (RBD) of Delta and Omicron variants to ACE2. By employing a competitive binding assay in vitro, OA significantly blocked the binding of RBDs from Delta B.1.617.2 and Omicron B.1.1.529 to ACE2, but has no effect on the wide-type SARS-CoV-2 strain. Furthermore, OA inhibited the entries of Delta and Omicron pseudovirus into ACE2 high expressing-HEK293T cells. By surface plasmon resonance (SPR) assay, the direct bindings of OA to RBD and ACE2 were analyzed and OA had both affinities with RBDs of B.1.617.2 and B.1.1.529 and with ACE2. Molecular docking predicted the binding sites on the RBD-ACE2 complex and it showed similar binding abilities to both complex of variant Delta or Omicron RBD and ACE2. In conclusion, we provided a promising novel small-molecule compound OA as an antiviral candidate by blocking the cellular entries of SARS-CoV-2 variants.

Maintained imbalance of triglycerides, apolipoproteins, energy metabolites and cytokines in long-term COVID-19 syndrome patients

Background

Deep metabolomic, proteomic and immunologic phenotyping of patients suffering from an infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have matched a wide diversity of clinical symptoms with potential biomarkers for coronavirus disease 2019 (COVID-19). Several studies have described the role of small as well as complex molecules such as metabolites, cytokines, chemokines and lipoproteins during infection and in recovered patients. In fact, after an acute SARS-CoV-2 viral infection almost 10-20% of patients experience persistent symptoms post 12 weeks of recovery defined as long-term COVID-19 syndrome (LTCS) or long post-acute COVID-19 syndrome (PACS). Emerging evidence revealed that a dysregulated immune system and persisting inflammation could be one of the key drivers of LTCS. However, how these biomolecules altogether govern pathophysiology is largely underexplored. Thus, a clear understanding of how these parameters within an integrated fashion could predict the disease course would help to stratify LTCS patients from acute COVID-19 or recovered patients. This could even allow to elucidation of a potential mechanistic role of these biomolecules during the disease course.

Methods

This study comprised subjects with acute COVID-19 (n=7; longitudinal), LTCS (n=33), Recov (n=12), and no history of positive testing (n=73). ¹H-NMR-based metabolomics with IVDr standard operating procedures verified and phenotyped all blood samples by quantifying 38 metabolites and 112 lipoprotein properties. Univariate and multivariate statistics identified NMR-based and cytokine changes.

Results

Here, we report on an integrated analysis of serum/plasma by NMR spectroscopy and flow cytometry-based cytokines/chemokines quantification in LTCS patients. We identified that in LTCS patients lactate and pyruvate were significantly different from either healthy controls (HC) or acute COVID-19 patients. Subsequently, correlation analysis in LTCS group only among cytokines and amino acids revealed that histidine and glutamine were uniquely attributed mainly with pro-inflammatory cytokines. Of note, triglycerides and several lipoproteins (apolipoproteins Apo-A1 and A2) in LTCS patients demonstrate COVID-19-like alterations compared with HC. Interestingly, LTCS and acute COVID-19 samples were distinguished mostly by their phenylalanine, 3-hydroxybutyrate (3-HB) and glucose concentrations, illustrating an imbalanced energy metabolism. Most of the cytokines and chemokines were present at low levels in LTCS patients compared with HC except for IL-18 chemokine, which tended to be higher in LTCS patients.

Conclusion

The identification of these persisting plasma metabolites, lipoprotein and inflammation alterations will help to better stratify LTCS patients from other diseases and could help to predict ongoing severity of LTCS patients.

Multiplatform analyses reveal distinct drivers of systemic pathogenesis in adult versus pediatric severe acute COVID-19

The pathogenesis of multi-organ dysfunction associated with severe acute SARS-CoV-2 infection remains poorly understood. Endothelial damage and microvascular thrombosis have been identified as drivers of COVID-19 severity, yet the mechanisms underlying these processes remain elusive. Here we show alterations in fluid shear stress-responsive pathways in critically ill COVID-19 adults as compared to non-COVID critically ill adults using a multiomics approach. Mechanistic in-vitro studies, using microvasculature-on-chip devices, reveal that plasma from critically ill COVID-19 adults induces fibrinogen-dependent red blood cell aggregation that mechanically damages the microvascular glycocalyx. This mechanism appears unique to COVID-19, as plasma from non-COVID sepsis patients demonstrates greater red blood cell membrane stiffness but induces less significant alterations in overall blood rheology. Multiomics analyses in pediatric patients with acute COVID-19 or the post-infectious multi-inflammatory syndrome in children (MIS-C) demonstrate little overlap in plasma cytokine and metabolite changes compared to adult COVID-19 patients. Instead, pediatric acute COVID-19 and MIS-C patients show alterations strongly associated with cytokine upregulation. These findings link high fibrinogen and red blood cell aggregation with endotheliopathy in adult COVID-19 patients and highlight differences in the key mediators of pathogenesis between adult and pediatric populations.

Phenylalanine metabolism and tetrahydrobiopterin bio-availability in COVID-19 and HIV

Various metabolomics studies have reported increased phenylalanine serum concentrations in SARS-CoV-2 positive cases and have correlated increased phenylalanine with COVID-19 severity. In this study, we report similar results based upon metabolomics analysis of serum collected from a South African cohort of adults with confirmed COVID-19. The novelty of this study is the inclusion of HIV positive cases in the African context. We found that pre-existing HIV co-infection exacerbates the disruption of phenylalanine metabolism in COVID-19. What is lacking in literature is biological context and deeper understanding of perturbed phenylalanine metabolism in COVID-19. We delve deep into the metabolism of phenylalanine in COVID-19 and posit new insights for COVID-19 cases co-infected with HIV; namely, HIV-COVID-19 co-infected individuals do not have sufficient bioavailability of tetrahydrobiopterin (BH₄). Hence, we identify BH₄ as a potential supplement to alleviate/lessen COVID-19 symptoms.

2 Hydroxybutyric Acid-Producing Bacteria in Gut Microbiome and Fusobacterium nucleatum Regulates 2 Hydroxybutyric Acid Level In Vivo

2-hydroxybutyric acid (2HB) serves as an important regulatory factor in a variety of diseases. The circulating level of 2HB in serum is significantly higher in multiple diseases, such as cancer and type 2 diabetes (T2D). However, there is currently no systematic study on 2HB-producing bacteria that demonstrates whether gut bacteria contribute to the circulating 2HB pool. To address this question, we used BLASTP to reveal the taxonomic profiling of 2HB-producing bacteria in the human microbiome, which are mainly distributed in the phylum Proteobacteria and Firmicutes. In vitro experiments showed that most gut bacteria (21/32) have at least one path to produce 2HB, which includes Aspartic acid, methionine, threonine, and 2-aminobutyric acid. Particularly, Fusobacterium nucleatum has the strongest ability to synthesize 2HB, which is sufficient to alter colon 2HB concentration in mice. Nevertheless, neither antibiotic (ABX) nor Fusobacterium nucleatum gavage significantly affected mouse serum 2HB levels during the time course of this study. Taken together, our study presents the profiles of 2HB-producing bacteria and demonstrates that gut microbiota was a major contributor to 2HB concentration in the intestinal lumen but a relatively minor contributor to serum 2HB concentration.

Potential for Early Noninvasive COVID-19 Detection Using Electronic-Nose Technologies and Disease-Specific VOC Metabolic Biomarkers

The established efficacy of electronic volatile organic compound (VOC) detection technologies as diagnostic tools for noninvasive early detection of COVID-19 and related coronaviruses has been demonstrated from multiple studies using a variety of experimental and commercial electronic devices capable of detecting precise mixtures of VOC emissions in human breath. The activities of numerous global research teams, developing novel electronic-nose (e-nose) devices and diagnostic methods, have generated empirical laboratory and clinical trial test results based on the detection of different types of host VOC-biomarker metabolites from specific chemical classes. COVID-19-specific volatile biomarkers are derived from disease-induced changes in host metabolic pathways by SARS-CoV-2 viral pathogenesis. The unique mechanisms proposed from recent researchers to explain how COVID-19 causes damage to multiple organ systems throughout the body are associated with unique symptom combinations, cytokine storms and physiological cascades that disrupt normal biochemical processes through gene dysregulation to generate disease-specific VOC metabolites targeted for e-nose detection. This paper reviewed recent methods and applications of e-nose and related VOC-detection devices for early, noninvasive diagnosis of SARS-CoV-2 infections. In addition, metabolomic (quantitative) COVID-19 disease-specific chemical biomarkers, consisting of host-derived VOCs identified from exhaled breath of patients, were summarized as possible sources of volatile metabolic biomarkers useful for confirming and supporting e-nose diagnoses.

Integrated Metabolic and Inflammatory Signatures Associated with Severity of, Fatality of, and Recovery from COVID-19

Severe manifestations of coronavirus disease 2019 (COVID-19) and mortality have been associated with physiological alterations that provide insights into the pathogenesis of the disease. Moreover, factors that drive recovery from COVID-19 can be explored to identify correlates of protection. The cellular metabolism represents a potential target to improve survival upon severe disease, but the associations between the metabolism and the inflammatory response during COVID-19 are not well defined. We analyzed blood laboratorial parameters, cytokines, and metabolomes of 150 individuals with mild to severe disease, of which 33 progressed to a fatal outcome. A subset of 20 individuals was followed up after hospital discharge and recovery from acute disease. We used hierarchical community networks to integrate metabolomics profiles with cytokines and markers of inflammation, coagulation, and tissue damage. Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) promotes significant alterations in the plasma metabolome, whose activity varies according to disease severity and correlates with oxygen saturation. Differential metabolism underlying death was marked by amino acids and related metabolites, such as glutamate, glutamyl-glutamate, and oxoproline, and lipids, including progesterone, phosphocholine, and lysophosphatidylcholines (lysoPCs). Individuals who recovered from severe disease displayed persistent alterations enriched for metabolism of purines and phosphatidylinositol phosphate and glycolysis. Recovery of mild disease was associated with vitamin E metabolism. Data integration shows that the metabolic response is a hub connecting other biological features during disease and recovery. Infection by SARS-CoV-2 induces concerted activity of metabolic and inflammatory responses that depend on disease severity and collectively predict clinical outcomes of COVID-19. IMPORTANCE COVID-19 is characterized by diverse clinical outcomes that include asymptomatic to mild manifestations or severe disease and death. Infection by SARS-CoV-2 activates inflammatory and metabolic responses that drive protection or pathology. How inflammation and metabolism communicate during COVID-19 is not well defined. We used high-resolution mass spectrometry to investigate small biochemical compounds (<1,500 Da) in plasma of individuals with COVID-19 and controls. Age, sex, and comorbidities have a profound effect on the plasma metabolites of individuals with COVID-19, but we identified significant activity of pathways and metabolites related to amino acids, lipids, nucleotides, and vitamins determined by disease severity, survival outcome, and recovery. Furthermore, we identified metabolites associated with acute-phase proteins and coagulation factors, which collectively identify individuals with severe disease or individuals who died of severe COVID-19. Our study suggests that manipulating specific metabolic pathways can be explored to prevent hyperinflammation, organ dysfunction, and death.

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.

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.

Gas Chromatography-Mass Spectrometry Technology: Application in the Study of Inflammatory Mechanism in COVID-19 Patients

SARS-CoV-2 infection in the human body induces a severe storm of inflammatory factors. However, its specific mechanism is still not clear. Gas chromatography-mass spectrometry (GC-MS) technology is expected to explain the possible mechanism of the disease by detecting differential metabolites. 15 COVID-19 patients and healthy controls were included in this study. Immune indicators such as hs CRP and cytokines were detected to reflect the level of inflammation in patients with COVID-19. The distribution of lymphocytes and subpopulations in peripheral whole blood were detected using flow cytometry to assess the immune function of COVID-19 patients. The expression of differential metabolites in serum was analyzed using GC-MS non-targeted metabolomics. The results showed that hs CRP, IL-5/6/8/10 and IFN-α in the serum of COVID-19 patients increased to varying degrees, and CD3/4/8+ T lymphocytes decreased. Additionally, 53 metabolites in the serum of COVID-19 patients were up regulated, 18 metabolites were down regulated, and 8 metabolites remained unchanged. Increased Cholesterol, Lactic Acid and 1-Monopalmitin may be the mechanism that causes excessive inflammation in COVID-19 patients. The increase of D-Allose may be involved in the process of lymphocyte decrease. In conclusion, the significance of our study is to reveal the possible mechanism of inflammatory response in patients with COVID-19 from the perspective of metabolomics. This provided a new idea for the treatment of COVID-19.

Graphical Abstract

Understanding metabolic alterations after SARS-CoV-2 infection: insights from the patients' oral microenvironmental metabolites

BACKGROUND

Coronavirus disease 2019 is a type of acute infectious pneumonia and frequently confused with influenza since the initial symptoms. When the virus colonized the patient's mouth, it will cause changes of the oral microenvironment. However, few studies on the alterations of metabolism of the oral microenvironment affected by SARS-CoV-2 infection have been reported. In this study, we explored metabolic alterations of oral microenvironment after SARS-CoV-2 infection.

METHODS

Untargeted metabolomics (UPLC-MS) was used to investigate the metabolic changes between oral secretion samples of 25 COVID-19 and 30 control participants. To obtain the specific metabolic changes of COVID-19, we selected 25 influenza patients to exclude the metabolic changes caused by the stress response of the immune system to the virus. Multivariate analysis (PCA and PLS-DA plots) and univariate analysis (students' t-test) were used to compare the differences between COVID-19 patients and the controls. Online hiplot tool was used to perform heatmap analysis. Metabolic pathway analysis was conducted by using the MetaboAnalyst 5.0 web application.

RESULTS

PLS-DA plots showed significant separation of COVID-19 patients and the controls. A total of 45 differential metabolites between COVID-19 and control group were identified. Among them, 35 metabolites were defined as SARS-CoV-2 specific differential metabolites. Especially, the levels of cis-5,8,11,14,17-eicosapentaenoic acid and hexanoic acid changed dramatically based on the FC values. Pathway enrichment found the most significant pathways were tyrosine-related metabolism. Further, we found 10 differential metabolites caused by the virus indicating the body's metabolism changes after viral stimulation. Moreover, adenine and adenosine were defined as influenza virus-specific differential metabolites.

CONCLUSIONS

This study revealed that 35 metabolites and tyrosine-related metabolism pathways were significantly changed after SARS-CoV-2 infection. The metabolic alterations of oral microenvironment in COVID-19 provided new insights into its molecular mechanisms for research and prognostic treatment.

An untargeted metabolomic approach to investigate antiviral defence mechanisms in memory leukocytes secreting anti-SARS-CoV-2 IgG in vitro

Evidence shows that individuals infected by SARS-CoV-2 experience an altered metabolic state in multiple organs. Metabolic activities are directly involved in modulating immune responses against infectious diseases, yet our understanding of how host metabolism relates to inflammatory responses remains limited. To better elucidate the underlying biochemistry of the leukocyte response, we focused our analysis on possible relationships between SARS-CoV-2 post-infection stages and distinct metabolic pathways. Indeed, we observed a significant altered metabolism of tryptophan and urea cycle pathways in cultures of peripheral blood mononuclear cells obtained 60-90 days after infection and showing in vitro IgG antibody memory for spike-S1 antigen (n = 17). This work, for the first time, identifies metabolic routes in cell metabolism possibly related to later stages of immune defence against SARS-CoV-2 infection, namely, when circulating antibodies may be absent but an antibody memory is present. The results suggest reprogramming of leukocyte metabolism after viral pathogenesis through activation of specific amino acid pathways possibly related to protective immunity against SARS-CoV-2.

Metabolomic analysis-identified 2-hydroxybutyric acid might be a key metabolite of severe preeclampsia

This study set out to determine the key metabolite changes underlying the pathophysiology of severe preeclampsia (PE) using metabolic analysis. We collected sera from 10 patients with severe PE and from 10 healthy pregnant women of the same trimester and analyzed them using liquid chromatography mass spectrometry. A total of 3,138 differential metabolites were screened, resulting in the identification of 124 differential metabolites. Kyoto encyclopedia of genes and genomes pathway analysis revealed that they were mainly enriched in the following metabolic pathways: central carbon metabolism in cancer; protein digestion and absorption; aminoacyl-transfer RNA biosynthesis; mineral absorption; alanine, aspartate, and glutamate metabolism; and prostate cancer. After analysis of 124 differential metabolites, 2-hydroxybutyric acid was found to be the most critical differential metabolite, and its use allowed the differentiation of women with severe PE from healthy pregnant women. In summary, our analysis revealed that 2-hydroxybutyric acid is a potential key metabolite for distinguishing severe PE from healthy controls and is also a marker for the early diagnosis of severe PE, thus allowing early intervention.

Red ginseng dietary fiber promotes probiotic properties of Lactiplantibacillus plantarum and alters bacterial metabolism

Korean red ginseng has been widely used as an herbal medicine. Red ginseng dietary fiber (RGDF) is a residue of the processed ginseng product but still contains bioactive constituents that can be applied as prebiotics. In this study, we evaluated changes on fermentation profiles and probiotic properties of strains that belong to family Lactobacillaceae with RGDF supplementation. Metabolomic analyses were performed to understand specific mechanisms on the metabolic alteration by RGDF and to discover novel bioactive compounds secreted by the RGDF-supplemented probiotic strain. RGDF supplementation promoted short-chain fatty acid (SCFA) production, carbon source utilization, and gut epithelial adhesion of Lactiplantibacillus plantarum and inhibited attachment of enteropathogens. Intracellular and extracellular metabolome analyses revealed that RGDF induced metabolic alteration, especially associated with central carbon metabolism, and produced RGDF-specific metabolites secreted by L. plantarum, respectively. Specifically, L. plantarum showed decreases in intracellular metabolites of oleic acid, nicotinic acid, uracil, and glyceric acid, while extracellular secretion of several metabolites including oleic acid, 2-hydroxybutanoic acid, hexanol, and butyl acetate increased. RGDF supplementation had distinct effects on L. plantarum metabolism compared with fructooligosaccharide supplementation. These findings present potential applications of RGDF as prebiotics and bioactive compounds produced by RGDF-supplemented L. plantarum as novel postbiotic metabolites for human disease prevention and treatment.

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

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

Integrative transcriptome analysis of SARS-CoV-2 human-infected cells combined with deep learning algorithms identifies two potential cellular targets for the treatment of coronavirus disease

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) quickly spread worldwide, leading coronavirus disease 2019 (COVID-19) to hit pandemic level less than 4 months after the first official cases. Hence, the search for drugs and vaccines that could prevent or treat infections by SARS-CoV-2 began, intending to reduce a possible collapse of health systems. After 2 years, efforts to find therapies to treat COVID-19 continue. However, there is still much to be understood about the virus' pathology. Tools such as transcriptomics have been used to understand the impact of SARS-CoV-2 on different cells isolated from various tissues, leaving datasets in the databases that integrate genes and differentially expressed pathways during SARS-CoV-2 infection. After retrieving transcriptome datasets from different human cells infected with SARS-CoV-2 available in the database, we performed an integrative analysis associated with deep learning algorithms to determine differentially expressed targets mainly after infection. The targets found represented a fructose transporter (GLUT5) and a component of proteasome 26s. These targets were then molecularly modeled, followed by molecular docking that identified potential inhibitors for both structures. Once the inhibition of structures that have the expression increased by the virus can represent a strategy for reducing the viral replication by selecting infected cells, associating these bioinformatics tools, therefore, can be helpful in the screening of molecules being tested for new uses, saving financial resources, time, and making a personalized screening for each infectious disease.

Urine Metabolites Enable Fast Detection of COVID-19 Using Mass Spectrometry

The COVID-19 pandemic boosted the development of diagnostic tests to meet patient needs and provide accurate, sensitive, and fast disease detection. Despite rapid advancements, limitations related to turnaround time, varying performance metrics due to different sampling sites, illness duration, co-infections, and the need for particular reagents still exist. As an alternative diagnostic test, we present urine analysis through flow-injection-tandem mass spectrometry (FIA-MS/MS) as a powerful approach for COVID-19 diagnosis, targeting the detection of amino acids and acylcarnitines. We adapted a method that is widely used for newborn screening tests on dried blood for urine samples in order to detect metabolites related to COVID-19 infection. We analyzed samples from 246 volunteers with diagnostic confirmation via PCR. Urine samples were self-collected, diluted, and analyzed with a run time of 4 min. A Lasso statistical classifier was built using 75/25% data for training/validation sets and achieved high diagnostic performances: 97/90% sensitivity, 95/100% specificity, and 95/97.2% accuracy. Additionally, we predicted on two withheld sets composed of suspected hospitalized/symptomatic COVID-19-PCR negative patients and patients out of the optimal time-frame collection for PCR diagnosis, with promising results. Altogether, we show that the benchmarked FIA-MS/MS method is promising for COVID-19 screening and diagnosis, and is also potentially useful after the peak viral load has passed.

Mendelian Randomization Study on Causal Association of Pyroglutamine with COVID-19

Background

Glutamine family amino acids such as glutamate, pyroglutamate, and glutamine have been shown to play important roles in COVID-19. However, it is still unclear about the role of pyroglutamate in COVID-19. Thus, we use a two-sample Mendelian randomization (MR) study to identify the genetic causal link between blood pyroglutamine levels and COVID-19 risk.

Methods

Pyroglutamine genetic instrumental variables (IVs) were chosen from the largest pyroglutamine-associated genome-wide association studies (GWAS). The largest COVID-19 GWAS dataset was employed to evaluate the causal link between blood pyroglutamine levels and COVID-19 risk using two-sample MR analysis.

Results

We found no significant pleiotropy or heterogeneity of pyroglutamine-associated genetic IVs in COVID-19 GWAS. Interestingly, we found that as pyroglutamine genetically increased, the risk of COVID-19 decreased using inverse variance weighted (IVW) (Beta = − 0.644, p = 0.003; OR = 0.525, 95% CI [0.346–0.798]) and weighted median (Beta = − 0.609, p = 0.013; OR = 0.544, 95% CI [0.337–0.878]).

Conclusion

Our analysis suggests a causal link between genetically increased pyroglutamine and reduced risk of COVID-19. Thus, pyroglutamine may be a protective factor for patients with COVID-19.

Metabolomics-based investigation of SARS-CoV-2 vaccination (Sinovac) reveals an immune-dependent metabolite biomarker

SARS-CoV-2 and its mutant strains continue to rapidly spread with high infection and fatality. Large-scale SARS-CoV-2 vaccination provides an important guarantee for effective resistance to existing or mutated SARS-CoV-2 virus infection. However, whether the host metabolite levels respond to SARS-CoV-2 vaccine-influenced host immunity remains unclear. To help delineate the serum metabolome profile of SARS-CoV-2 vaccinated volunteers and determine that the metabolites tightly respond to host immune antibodies and cytokines, in this study, a total of 59 sera samples were collected from 30 individuals before SARS-CoV-2 vaccination and from 29 COVID-19 vaccines 2 weeks after the two-dose vaccination. Next, untargeted metabolomics was performed and a distinct metabolic composition was revealed between the pre-vaccination (VB) group and two-dose vaccination (SV) group by partial least squares-discriminant and principal component analyses. Based on the criteria: FDR < 0.05, absolute log2 fold change greater than 0.25, and VIP >1, we found that L-glutamic acid, gamma-aminobutyric acid (GABA), succinic acid, and taurine showed increasing trends from SV to VB. Furthermore, SV-associated metabolites were mainly annotated to butanoate metabolism and glutamate metabolism pathways. Moreover, two metabolite biomarkers classified SV from VB individuals with an area under the curve (AUC) of 0.96. Correlation analysis identified a positive association between four metabolites enriched in glutamate metabolism and serum antibodies in relation to IgG, IgM, and IgA. These results suggest that the contents of gamma-aminobutyric acid and indole in serum could be applied as biomarkers in distinguishing vaccinated volunteers from the unvaccinated. What’s more, metabolites such as GABA and taurine may serve as a metabolic target for adjuvant vaccines to boost the ability of the individuals to improve immunity.

Metabolomics analysis identifies glutamic acid and cystine imbalances in COVID-19 patients without comorbid conditions. Implications on redox homeostasis and COVID-19 pathophysiology

It is well known that the presence of comorbidities and age-related health issues may hide biochemical and metabolic features triggered by SARS-CoV-2 infection and other diseases associated to hypoxia, as they are by themselves chronic inflammatory conditions that may potentially disturb metabolic homeostasis and thereby negatively impact on COVID-19 progression. To unveil the metabolic abnormalities inherent to hypoxemia caused by COVID-19, we here applied gas chromatography coupled to mass spectrometry to analyze the main metabolic changes exhibited by a population of male patients less than 50 years of age with mild/moderate and severe COVID-19 without pre-existing comorbidities known to predispose to life-threatening complications from this infection. Several differences in serum levels of particular metabolites between normal controls and patients with COVID-19 as well as between mild/moderate and severe COVID-19 were identified. These included increased glutamic acid and reduced glutamine, cystine, threonic acid, and proline levels. In particular, using the entire metabolomic fingerprint obtained, we observed that glutamine/glutamate metabolism was associated with disease severity as patients in the severe COVID-19 group presented the lowest and higher serum levels of these amino acids, respectively. These data highlight the hypoxia-derived metabolic alterations provoked by SARS-CoV-2 infection in the absence of pre-existing co-morbidities as well as the value of amino acid metabolism in determining reactive oxygen species recycling pathways, which when impaired may lead to increased oxidation of proteins and cell damage. They also provide insights on new supportive therapies for COVID-19 and other disorders that involve altered redox homeostasis and lower oxygen levels that may lead to better outcomes of disease severity.

Grossamide attenuates inflammation by balancing macrophage polarization through metabolic reprogramming of macrophages in mice

Macrophages exhibited different phenotypes in response to environmental cues. To meet the needs of rapid response to stimuli, M1-activated macrophages preferred glycolysis to oxidative phosphorylation (OXPHOS) in mitochondria to quickly produce energy and obtain ample raw materials to support cell activation at the same time. Activated macrophages produced free radicals and cytokines to eradicate pathogens but also induced oxidative damage and enhanced inflammation. Grossamide (GSE), a lignanamide from Polygonum multiflorum Thunb., exhibited notable anti-inflammatory effects. In this study, the potential of GSE on macrophage polarization was explored. GSE significantly down-regulated the levels of M1 macrophage biomarkers (Cd32a, Cd80 and Cd86) while increased the levels of M2 indicators (Cd163, Mrc1 and Socs1), showing its potential to inhibit LPS-induced M1 polarization of macrophages. This ability has close a link to its effect on metabolic reprogramming of macrophage. GSE shunted nitric oxide (NO) production from arginine by up-regulation of arginase and down-regulation of inducible nitric oxide synthase, thus attenuated the inhibition of NO on OXPHOS. LPS created three breakpoints in the tricarboxylic acid cycle (TCA) cycle of macrophage as evidenced by down-regulated isocitrate dehydrogenase, accumulation of succinate and the inhibited SDH activity, significantly decreased level of oxoglutarate dehydrogenase expression and its substrate α-ketoglutarate. Thus GSE reduced oxidative stress and amended fragmented TCA cycle. As a result, GSE maintained redox (NAD⁺/NADH) and energy (ATP/ADP) state, reduced extracellular acidification rate and enhanced the oxygen consumption rate. In addition, GSE decreased the release of inflammatory cytokines by inhibiting the activation of the LPS/TLR4/NF-κB pathway. These findings highlighted the central role of immunometabolism of macrophages in its functional plasticity, which invited future study of mode of action of anti-inflammatory drugs from viewpoint of metabolic reprogramming.

Circulating pyruvate is a potent prognostic marker for critical COVID-19 outcomes

Background

Coronavirus-19 (COVID-19) disease is driven by an unchecked immune response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus which alters host mitochondrial-associated mechanisms. Compromised mitochondrial health results in abnormal reprogramming of glucose metabolism, which can disrupt extracellular signalling. We hypothesized that examining mitochondrial energy-related signalling metabolites implicated in host immune response to SARS-CoV-2 infection would provide potential biomarkers for predicting the risk of severe COVID-19 illness.

Methods

We used a semi-targeted serum metabolomics approach in 273 patients with different severity grades of COVID-19 recruited at the acute phase of the infection to determine the relative abundance of tricarboxylic acid (Krebs) cycle-related metabolites with known extracellular signaling properties (pyruvate, lactate, succinate and α-ketoglutarate). Abundance levels of energy-related metabolites were evaluated in a validation cohort (n=398) using quantitative fluorimetric assays.

Results

Increased levels of four energy-related metabolites (pyruvate, lactate, a-ketoglutarate and succinate) were found in critically ill COVID-19 patients using semi-targeted and targeted approaches (p<0.05). The combined strategy proposed herein enabled us to establish that circulating pyruvate levels (p<0.001) together with body mass index (p=0.025), C-reactive protein (p=0.039), D-Dimer (p<0.001) and creatinine (p=0.043) levels, are independent predictors of critical COVID-19. Furthermore, classification and regression tree (CART) analysis provided a cut-off value of pyruvate in serum (24.54 µM; p<0.001) as an early criterion to accurately classify patients with critical outcomes.

Conclusion

Our findings support the link between COVID-19 pathogenesis and immunometabolic dysregulation, and show that fluorometric quantification of circulating pyruvate is a cost-effective clinical decision support tool to improve patient stratification and prognosis prediction.

Serum metabolomic abnormalities in survivors of non-severe COVID-19

Metabolic reprogramming is a distinctive characteristic of SARS-CoV-2 infection, which refers to metabolic changes in hosts triggered by viruses for their survival and spread. It is current urgent to understand the metabolic health status of COVID-19 survivors and its association with long-term health consequences of infection, especially for the predominant non-severe patients. Herein, we show systemic metabolic signatures of survivors of non-severe COVID-19 from Wuhan, China at six months after discharge using metabolomics approaches. The serum amino acids, organic acids, purine, fatty acids and lipid metabolism were still abnormal in the survivors, but the kynurenine pathway and the level of itaconic acid have returned to normal. These metabolic abnormalities are associated with liver injury, mental health, energy production, and inflammatory responses. Our findings identify and highlight the metabolic abnormalities in survivors of non-severe COVID-19, which provide information on biomarkers and therapeutic targets of infection and cues for post-hospital care and intervention strategies centered on metabolism reprogramming.