| 1. |
- Ambikan, Anoop T., et al.
(författare)
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Multi-omics personalized network analyses highlight progressive disruption of central metabolism associated with COVID-19 severity
- 2022
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Ingår i: Cell systems. - : Elsevier BV. - 2405-4712 .- 2405-4720. ; 13:8, s. 665-681
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Tidskriftsartikel (refereegranskat)abstract
- The clinical outcome and disease severity in coronavirus disease 2019 (COVID-19) are heterogeneous, and the progression or fatality of the disease cannot be explained by a single factor like age or comorbidities. In this study, we used system-wide network-based system biology analysis using whole blood RNA sequencing, immunophenotyping by flow cytometry, plasma metabolomics, and single-cell-type metabolo-mics of monocytes to identify the potential determinants of COVID-19 severity at personalized and group levels. Digital cell quantification and immunophenotyping of the mononuclear phagocytes indicated a sub-stantial role in coordinating the immune cells that mediate COVID-19 severity. Stratum-specific and person-alized genome-scale metabolic modeling indicated monocarboxylate transporter family genes (e.g., SLC16A6), nucleoside transporter genes (e.g., SLC29A1), and metabolites such as a-ketoglutarate, succi-nate, malate, and butyrate could play a crucial role in COVID-19 severity. Metabolic perturbations targeting the central metabolic pathway (TCA cycle) can be an alternate treatment strategy in severe COVID-19.
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| 2. |
- Krishnan, Shuba, et al.
(författare)
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Metabolic Perturbation Associated With COVID-19 Disease Severity and SARS-CoV-2 Replication
- 2021
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Ingår i: Molecular & Cellular Proteomics. - : Elsevier BV. - 1535-9476 .- 1535-9484. ; 20
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Tidskriftsartikel (refereegranskat)abstract
- Viruses hijack host metabolic pathways for their replicative advantage. In this study, using patient-derived multiomics data and in vitro infection assays, we aimed to understand the role of key metabolic pathways that can regulate severe acute respiratory syndrome coronavirus-2 reproduction and their association with disease severity. We used multiomics platforms (targeted and untargeted proteomics and untargeted metabolomics) on patient samples and cell-line models along with immune phenotyping of metabolite transporters in patient blood cells to understand viral-induced metabolic modulations. We also modulated key metabolic pathways that were identified using multiomics data to regulate the viral reproduction in vitro. Coronavirus disease 2019 disease severity was characterized by increased plasma glucose and mannose levels. Immune phenotyping identified altered expression patterns of carbohydrate transporter, glucose transporter 1, in CD8+ T cells, intermediate and nonclassical monocytes, and amino acid transporter, xCT, in classical, intermediate, and nonclassical monocytes. In in vitro lung epithelial cell (Calu-3) infection model, we found that glycolysis and glutaminolysis are essential for virus replication, and blocking these metabolic pathways caused significant reduction in virus production. Taken together, we therefore hypothesized that severe acute respiratory syndrome coronavirus-2 utilizes and rewires pathways governing central carbon metabolism leading to the efflux of toxic metabolites and associated with disease severity. Thus, the host metabolic perturbation could be an attractive strategy to limit the viral replication and disease severity.
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| 3. |
- Selvavinayagam, Sivaprakasam T, et al.
(författare)
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Plasma CXCL8 and MCP-1 as surrogate plasma biomarkers of latent tuberculosis infection among household contacts-A cross-sectional study
- 2023
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Ingår i: PLOS Global Public Health. - : Public Library of Science (PLoS). - 2767-3375. ; 3:11
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Tidskriftsartikel (refereegranskat)abstract
- Early detection of latent tuberculosis infection (LTBI) is critical to TB elimination in the current WHO vision of End Tuberculosis Strategy. The study investigates whether detecting plasma cytokines could aid in diagnosing LTBI across household contacts (HHCs) positive for IGRA, HHCs negative for IGRA, and healthy controls. The plasma cytokines were measured using a commercial Bio-Plex Pro Human Cytokine 17-plex assay. Increased plasma CXCL8 and decreased MCP-1, TNF-a, and IFN-? were associated with LTBI. Regression analysis showed that a combination of CXCL8 and MCP-1 increased the risk of LTBI among HHCs to 14-fold. Our study suggests that CXCL-8 and MCP-1 could serve as the surrogate biomarkers of LTBI, particularly in resource-limited settings. Further laboratory investigations are warranted before extrapolating CXCL8 and MCP-1 for their usefulness as surrogate biomarkers of LTBI in resource-limited settings.
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