Effect of a Functional Phospholipid Metabolome-Protein Association Pathway on the Mechanism of COVID-19 Disease Progression

Lipidomic and metabolomic changes in community-acquired and COVID-19 pneumonia

This prospective observational study compared the 1H NMR blood lipidomes and metabolomes of 71 patients with community-acquired pneumonia (CAP), 75 patients with COVID-19 pneumonia, and 75 healthy controls (matched by age and sex) to identify potential biomarkers and pathways associated with respiratory infections. Both pneumonia groups had comparable severity indices, including mortality, invasive mechanical ventilation, and intensive care unit admission rates. Patients with COVID-19 pneumonia exhibited more pronounced hypolipidemia, with significantly lower levels of total cholesterol and LDL-c compared to patients with CAP. Atherogenic lipoprotein subclasses (VLDL-cholesterol, IDL-cholesterol, IDL-triglyceride, and LDL-triglyceride/LDL-cholesterol) were significantly increased in severe cases of both pneumonia types, while lower HDL-c and small, dense HDL particles were associated with more severe illness. Both infected groups showed decreased esterified cholesterol and increased triglycerides, along with reduced phosphatidylcholine, lysophosphatidylcholine, PUFA, omega-3 fatty acids, and DHA. Additionally, infected patients had elevated levels of glucose, lactate, 3-hydroxybutyrate, and acetone, which are linked to inflammation, hypoxemia, and sepsis. Increased levels of branched-chain amino acids, alanine, glycine, and creatine, which are involved in energy metabolism and protein catabolism, were also observed. Neurotransmitter synthesis metabolites like histidine and glutamate were higher in infected patients, especially those with COVID-19. Notably, severe infections showed a significant decrease in glutamine, essential for lymphocyte and macrophage energy. The severity of COVID-19 pneumonia was also associated with elevated glycoprotein levels (glycoprotein A, glycoprotein B, and glycoprotein F), indicating an inflammatory state. These findings suggest that metabolomic and lipidomic changes in pneumonia are connected to bioenergetic pathways regulating the immune response.

Multi-omics Approach in Kidney Transplant: Lessons Learned from COVID-19 Pandemic

Purpose of Review

Multi-omics approach has advanced our knowledge on transplantation-associated clinical outcomes, such as acute rejection and infection, and emerging omics data are becoming available in kidney transplant and COVID-19. Herein, we discuss updated findings of multi-omics data on kidney transplant outcomes, as well as COVID-19 and kidney transplant.

Recent Findings

Transcriptomics, proteomics, and metabolomics revealed various inflammation pathways associated with kidney transplantation-related outcomes and COVID-19. Although multi-omics data on kidney transplant and COVID-19 is limited, activation of innate immune pathways and suppression of adaptive immune pathways were observed in the active phase of COVID-19 in kidney transplant recipients.

Summary

Multi-omics analysis has led us to a deeper exploration and a more comprehensive understanding of key biological pathways in complex clinical settings, such as kidney transplantation and COVID-19. Future multi-omics analysis leveraging multi-center biobank collaborative will further advance our knowledge on the precise immunological responses to allograft and emerging pathogens.

Developing A Baseline Metabolomic Signature Associated with COVID-19 Severity: Insights from Prospective Trials Encompassing 13 U.S. Centers

Metabolic disease is a significant risk factor for severe COVID-19 infection, but the contributing pathways are not yet fully elucidated. Using data from two randomized controlled trials across 13 U.S. academic centers, our goal was to characterize metabolic features that predict severe COVID-19 and define a novel baseline metabolomic signature. Individuals (n = 133) were dichotomized as having mild or moderate/severe COVID-19 disease based on the WHO ordinal scale. Blood samples were analyzed using the Biocrates platform, providing 630 targeted metabolites for analysis. Resampling techniques and machine learning models were used to determine metabolomic features associated with severe disease. Ingenuity Pathway Analysis (IPA) was used for functional enrichment analysis. To aid in clinical decision making, we created baseline metabolomics signatures of low-correlated molecules. Multivariable logistic regression models were fit to associate these signatures with severe disease on training data. A three-metabolite signature, lysophosphatidylcholine a C17:0, dihydroceramide (d18:0/24:1), and triacylglyceride (20:4_36:4), resulted in the best discrimination performance with an average test AUROC of 0.978 and F1 score of 0.942. Pathways related to amino acids were significantly enriched from the IPA analyses, and the mitogen-activated protein kinase kinase 5 (MAP2K5) was differentially activated between groups. In conclusion, metabolites related to lipid metabolism efficiently discriminated between mild vs. moderate/severe disease. SDMA and GABA demonstrated the potential to discriminate between these two groups as well. The mitogen-activated protein kinase kinase 5 (MAP2K5) regulator is differentially activated between groups, suggesting further investigation as a potential therapeutic pathway.

ERC-BiP Functional Protein Pathway for Assessing Endoplasmic Reticulum Stress Induced by SARS-CoV-2 Replication after Cell Invasion

Background

SARS-CoV-2 induces apoptosis and amplifies the immune response by continuously stressing the endoplasmic reticulum (ER) after invading cells. This study aimed to establish a protein-metabolic pathway associated with ER dysfunction based on the invasion mechanism of SARS-CoV-2.

Methods

This study included 17 healthy people and 46 COVID-19 patients, including 38 mild patients and 8 severe patients. Proteomics and metabolomics were measured in the patient plasma collected at admission and one week after admission. The patients were further divided into the aggravation and remission groups based on disease progression within one week of admission.

Results

Cross-sectional comparison showed that endoplasmic reticulum molecular chaperone-binding immunoglobulin protein (ERC-BiP), angiotensinogen (AGT), ceramide acid (Cer), and C-reactive protein (CRP) levels were significantly increased in COVID-19 patients, while the sphingomyelin (SM) level was significantly decreased (P  <  0.05). In addition, longitudinal comparative analysis found that the temporal fold changes of ERC-BiP, AGT, Cer, CRP, and SM were significantly different between the patients in the aggravation and remission groups (P  <  0.05). ERC-BiP, AGT, and Cer levels were significantly increased in aggravation patients, while SM was significantly decreased (P  <  0.05). Meanwhile, ERC-BiP was significantly correlated with AGT (r = 0.439; P  <  0.001).

Conclusions

ERC-BiP can be used as a core index to reflect the degree of ER stress in COVID-19 patients, which is of great value for evaluating the functional state of cells. A functional pathway for AGT/ERC-BiP/glycolysis can directly assess the activation of unfolded protein reactions. The ERC-BiP pathway is closer to the intracellular replication pathway of SARS-CoV-2 and may help in the development of predictive protocols for COVID-19 exacerbation.

COVID-19, Blood Lipid Changes, and Thrombosis

Although there is increasing evidence that oxidative stress and inflammation induced by COVID-19 may contribute to increased risk and severity of thromboses, the underlying mechanism(s) remain to be understood. The purpose of this review is to highlight the role of blood lipids in association with thrombosis events observed in COVID-19 patients. Among different types of phospholipases A₂ that target cell membrane phospholipids, there is increasing focus on the inflammatory secretory phospholipase A₂ IIA (sPLA₂-IIA), which is associated with the severity of COVID-19. Analysis indicates increased sPLA₂-IIA levels together with eicosanoids in the sera of COVID patients. sPLA₂ could metabolise phospholipids in platelets, erythrocytes, and endothelial cells to produce arachidonic acid (ARA) and lysophospholipids. Arachidonic acid in platelets is metabolised to prostaglandin H2 and thromboxane A₂, known for their pro-coagulation and vasoconstrictive properties. Lysophospholipids, such as lysophosphatidylcholine, could be metabolised by autotaxin (ATX) and further converted to lysophosphatidic acid (LPA). Increased ATX has been found in the serum of patients with COVID-19, and LPA has recently been found to induce NETosis, a clotting mechanism triggered by the release of extracellular fibres from neutrophils and a key feature of the COVID-19 hypercoagulable state. PLA2 could also catalyse the formation of platelet activating factor (PAF) from membrane ether phospholipids. Many of the above lipid mediators are increased in the blood of patients with COVID-19. Together, findings from analyses of blood lipids in COVID-19 patients suggest an important role for metabolites of sPLA₂-IIA in COVID-19-associated coagulopathy (CAC).

Status of Inflammatory and Coagulation Factors in COVID-19 and Its Relation with the Disease Severity

Background

The role of activation of inflammatory processes in the exacerbation of COVID-19 disease has been fully confirmed. In addition, the occurrence of thromboembolic events in patients with COVID-19 is expected even long after recovery from the disease. However, which factors are essentially prognostic for this disease is still not theoretically agreed upon. What we did in the present study was to evaluate the prognostic role of some inflammatory and coagulation factors in predicting the severity of COVID-19 disease. In this study, the need for ICU admission was considered as a symbol of disease severity.

Materials and Methods

Forty-six cases were studied in this cross-sectional study. Patients over 18 years of age with a definitive diagnosis of COVID-19 were assessed in terms of coagulation profiles and inflammatory and cytokine markers. Regarding laboratory data, serum levels of D-dimer, protein S, protein C, FDP, and fibrinogen were measured using an automated coagulation analyzer, and serum levels of interleukin-6 were measured using the ELISA technique.

Results

In total, 21 patients (45.7%) were admitted to the ICU due to the severity of the disease. In comparing inflammatory and coagulation factors between the two groups of patients, with and without ICU admission, a significant difference was revealed between fibrinogen (P=0.023), D-dimer (P=0.047), protein C (P=0.001), and protein S level (P=0.014). The decrease in protein C level had the highest value for predicting the severity of the disease and therefore the need for ICU admission.

Conclusion

Among various inflammatory and coagulation factors, the role of fibrinogen, D-dimer, protein C, and protein S in predicting the severe form of COVID-19 and the patient's need for ICU admission was confirmed.

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.