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BREAKING NEWS
Source: COVID-19 Research  Sep 07, 2021  20 days ago
BREAKING! Seattle Study Uncovers That SARS-CoV-2 Causes Metabolic Changes In Plasma And Immune Cells Of Human Host!
BREAKING! Seattle Study Uncovers That SARS-CoV-2 Causes Metabolic Changes In Plasma And Immune Cells Of Human Host!
Source: COVID-19 Research  Sep 07, 2021  20 days ago
COVID-19 Research: Yet another alarming study finding has emerged from a research by scientists from the Fred Hutchinson Cancer Research Center-Seattle and the institute for Systems Biology-Seattle in which it has been found that the SARS-CoV-2 coronavirus is able to cause metabolic changes to the plasma and immune cells of the human host!

Furthermore the study findings also show that these changes can be utilized as biomarkers to determine COVID-19 disease severity and mortality risk.

 
According to the study team, a more comprehensive understanding of the metabolic alterations in immune cells during SARS-CoV-2 infection may elucidate the wide diversity of clinical symptoms experienced by individuals with the COVID-19 disease.
 
The study team reported that the metabolic changes associated with the peripheral immune response of 198 individuals with COVID-19 through an integrated analysis of plasma metabolite and protein levels as well as single-cell multiomics analyses from serial blood draws collected during the first week after clinical diagnosis.
 
The team documented the emergence of rare but metabolically dominant T cell subpopulations and find that increasing disease severity correlates with a bifurcation of monocytes into two metabolically distinct subsets. This integrated analysis reveals a robust interplay between plasma metabolites and cell-type-specific metabolic reprogramming networks that is associated with disease severity and could predict survival.
 
The study findings were published in the peer reviewed journal: Nature Biotechnology. https://www.nature.com/articles/s41587-021-01020-4
 
To date it has been found that COVID-19 patients have differing immune responses that lead to disease outcomes ranging from asymptomatic SARS-CoV-2 infection to death.
 
Upon examining the blood samples from nearly 200 COVID-19 patients, the study team had uncovered underlying metabolic changes that regulate how immune cells react to the disease. These changes are associated with disease severity and could be used to predict patient survival.
 
Co-first author Dr Jihoon Lee, a graduate student at Fred Hutchinson Cancer Research Center told Thailand Medical News, "We know that there are a range of immune responses to COVID-19, and the biological processes underlying those responses are not well understood. We analyzed thousands of biological markers linked to metabolic pathways that underlie the immune system and found some clues as to what immune-metabolic changes may be pivotal in severe disease. Our hope is that these observations of immune function will help others piece together the body's response to COVID-19. The deeper understanding gained here may eventually lead to better therapies that can more precisely target the most problematic immune or metabolic changes."
 
The COVID-19 Research team collected 374 blood samples ie two draws per patient during the first week after being diagnosed with SARS-CoV-2 infection and analyzed their plasma and single immune cells.
 
The detailed analysis included 1,387 genes involv ed in metabolic pathways and 1,050 plasma metabolites.
 
Interestingly, in plasma samples, the study team found that increased COVID-19 severity is associated with metabolite alterations, suggesting increased immune-related activity. Furthermore, through single-cell sequencing, researchers found that each major immune cell type has a distinct metabolic signature.
 
The study findings provided interesting insights into COVID-19-associated metabolic reprogramming of the immune response at single-cell resolution. Highly active subpopulations, albeit small, dominated metabolic trends. For example, among CD8+ and CD4+ T cells, metabolic activation corresponding with COVID-19 severity was driven by small, metabolically hyperactive subpopulations not identifiable through analyses of averaged behavior. Similar trends were also observed for B cells, NK cells and monocytes. For monocytes, the team documented metabolic changes between two diverging subpopulations. Inflammatory monocytes increased in number and metabolic activity per cell, while non-classical monocytes behaved oppositely in both respects. These changes occurred not only during the initial polarization of monocytes to these phenotypes as previously reported but also continuously along the spectrum of disease severity.
 
Importantly these collective observations revealed two independent modes of metabolic reprogramming that are likely fundamental to an immune system response. The first corresponds to changes in the quantity of the metabolically active immune cell subpopulations, while the second involves shifts in the metabolism within individual cells within a subpopulation (‘quality’).
 
Comprehending these two modes of metabolic reprogramming may yield more precise strategies for promoting more effective protective responses, because specific immune cell subpopulations are identified to be manipulated. Importantly, these two modes were only resolved through analyzing metabolism at single-cell resolution. Kinetic studies may provide more insight on the trajectories leading to such reprogramming.
 
Also the integration of cell-type-specific COVID-19-associated metabolic alterations with changes in plasma metabolite levels proved useful for classifying disease severity and predicting clinical outcomes. Broader categories of metabolic activity in the peripheral immune response were revealed, and the team found cell-type-specific interplay between cellular metabolic programs and distinct sets of metabolic products and byproducts. This analysis guided the classification of individuals with COVID-19 by disease severity or other clinical measurements (for example, level of respiratory support) with greater precision than by using individual omics layers alone, suggesting the importance of examining this interplay between plasma and cells. The study team identified subsets of metabolic pathways and plasma metabolites that correlated with clinical biomarkers associated with inflammation and immune activation.
 
Past studies distilled individual features to predict concurrent disease status.
 
The study team resolved a few plasma metabolites for predicting future outcome of newly diagnosed individuals with COVID-19. The clinical significances of these metabolites, such as acetoacetate and α-ketobutyrate, are known in other diseases, perhaps suggesting a pathophysiology shared with COVID-19. For instance, acetoacetate is produced in response to impaired cellular glucose uptake, while α-ketobutyrate is involved in the production of α-hydroxybutyrate34, an early insulin resistance biomarker. Given the potential of these metabolites for predicting COVID-19 survival,  the study team speculates that diabetes may affect COVID-19 by a related mechanism. For example, insulin resistance may impair glucose uptake needed by immune cells for upregulated metabolism and function. However, the metabolite signatures reported here may differ depending on comorbidities, interventions and other factors reflecting the complexity of human disease and thus require additional validations with multiple independent datasets.
 
A significant perspective of this study is that it updates metabolic changes studied in bulk with single-cell resolution to unveil what subpopulations are specifically responsible for driving these changes. Despite recent advances in single-cell methods, single-cell metabolomic analyses have been limited. For example, previous single-cell metabolic studies used custom-designed assays or cytometry by time of flight, limiting the number of simultaneously quantifiable metabolic markers.
 
This new study approach combining large-scale, single-cell transcriptomic data with an extensive panel of plasma metabolites/proteins widens the view to permit the study of metabolic changes within the context of detailed, known metabolic pathways in the setting of acute viral infection and likely other diseases. Label-free methods of metabolite measurement, permitting general rather than selective detection of metabolites in live single cells, may provide another insightful omics layer.
 
Co-first and co-corresponding author Dr Yapeng Su, a research scientist at Institute for Systems Biology further added, "We have found metabolic reprogramming that is highly specific to individual immune cell classes (e.g. "killer" CD8+ T cells, "helper" CD4+ T cells, antibody-secreting B cells, etc.) and even cell subtypes, and the complex metabolic reprogramming of the immune system is associated with the plasma global metabolome and are predictive of disease severity and even patient death. Such deep and clinically relevant insights on sophisticated metabolic reprogramming within our heterogeneous immune systems are otherwise impossible to gain without advanced single-cell multi-omic analysis."
 
Dr Jim Heath, president and professor of ISB and co-corresponding author on the paper added, “This study provides significant insights for developing more effective treatments against COVID-19. It also represents a major technological hurdle. Many of the data sets that are collected from these patients tend to measure very different aspects of the disease, and are analyzed in isolation. Of course, one would like these different views to contribute to an overall picture of the patient. The approach described here allows for the sum of the different data sets to be much greater than the parts, and provides for a much richer interpretation of the disease."
 
The study team added, “Our analysis resolved significant alterations in metabolic pathways in the COVID-19 immune response and resolved their contrasts with PBMCs in sepsis and HIV. The function and molecular interactions of many of the involved individual metabolites and metabolic pathways, and how they relate to disease, are often poorly understood, but the data and methodology provided here should guide hypothesis development to further elucidate immune metabolic mechanisms for identifying therapeutic targets against COVID-19 and other diseases.”
 
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