A data-driven hypothesis on the epigenetic dysregulation of host metabolism by SARS coronaviral infection: Potential implications for the SARS-CoV-2 modus operandi
dc.creator | Vavougios G.D. | en |
dc.date.accessioned | 2023-01-31T10:30:13Z | |
dc.date.available | 2023-01-31T10:30:13Z | |
dc.date.issued | 2020 | |
dc.identifier | 10.1016/j.mehy.2020.109759 | |
dc.identifier.issn | 03069877 | |
dc.identifier.uri | http://hdl.handle.net/11615/80525 | |
dc.description.abstract | COVID-19, the disease caused by the novel SARS-CoV-2, a betacoronavirus structurally similar to SARS-CoV. Based on both structural and syndromic similarities with SARS-CoV, a hypothesis is formed on SARS-CoV-2 potential to affect the host's metabolism as part of its lifecycle. This hypothesis is evaluated by (a) exploratory analysis of SARS-CoV/human transcriptomic interaction data and gene set enrichment analysis (b) a confirmatory, focused review of the literature based on the findings by (a). A STRING Viruses (available search for human – SARS-CoV (NCBI taxonomy Id: 9606 vs. NCBI taxonomy Id: 694009) genomic interactions reveals ten human proteins, interacting with SARS-CoV: SGTA, FGL2, SPECC1, STAT3, PHB, BCL2L1, PPP1CA, CAV1, JUN, XPO1. Gene set enrichment analyses (GSEA) with STRING on this network revealed their role as a putative protein – protein interaction network (PPI; Enrichment p-value = 0.0296) mediating, viral parasitism, interleukin as well as insulin signaling, diabetes and triglyceride catabolism. In the literature, SARS-CoV has been known to cause de novo diabetes by ACE2-dependent uptake on pancreatic isle cells, and furthermore dysregulate lipid autophagy in favor of the viral lifecycle. Conversely, currently there are only non-causative, observational evidence of worse outcomes for COVID-19 patients with comorbid diabetes or hyperglycemia. No study has reported on the lipid profiles of COVID-19 patients; however, lipid-targeting molecules have been proposed as agents against SARS-CoV-2. Future studies, reporting on lipid and glucose metabolism of COVID-19 patients could help elucidate the disease's seculae and aid drug design. © 2020 Elsevier Ltd | en |
dc.language.iso | en | en |
dc.source | Medical Hypotheses | en |
dc.source.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85083707517&doi=10.1016%2fj.mehy.2020.109759&partnerID=40&md5=b025b92451f9e2c43038b1bce19cab4d | |
dc.subject | angiotensin converting enzyme 2 | en |
dc.subject | cytokine | en |
dc.subject | exportin 1 | en |
dc.subject | STAT3 protein | en |
dc.subject | triacylglycerol | en |
dc.subject | lipid | en |
dc.subject | protein binding | en |
dc.subject | transcriptome | en |
dc.subject | Article | en |
dc.subject | BCL2L1 gene | en |
dc.subject | CAV1 gene | en |
dc.subject | comorbidity | en |
dc.subject | coronavirus disease 2019 | en |
dc.subject | Coronavirus infection | en |
dc.subject | diabetes mellitus | en |
dc.subject | epigenetics | en |
dc.subject | FGL2 gene | en |
dc.subject | gene | en |
dc.subject | gene interaction | en |
dc.subject | human | en |
dc.subject | hyperglycemia | en |
dc.subject | insulin signaling | en |
dc.subject | JUN gene | en |
dc.subject | lipid fingerprinting | en |
dc.subject | lipid metabolism | en |
dc.subject | metabolic disorder | en |
dc.subject | pancreas islet cell | en |
dc.subject | PHB gene | en |
dc.subject | PPP1CA gene | en |
dc.subject | protein protein interaction | en |
dc.subject | SARS-related coronavirus | en |
dc.subject | Severe acute respiratory syndrome coronavirus 2 | en |
dc.subject | SGTA gene | en |
dc.subject | SPECC1 gene | en |
dc.subject | STAT3 gene | en |
dc.subject | transcriptomics | en |
dc.subject | virus virulence | en |
dc.subject | XPO1 gene | en |
dc.subject | autophagy | en |
dc.subject | Betacoronavirus | en |
dc.subject | chemistry | en |
dc.subject | complication | en |
dc.subject | computer simulation | en |
dc.subject | Coronavirus infection | en |
dc.subject | diabetic complication | en |
dc.subject | drug design | en |
dc.subject | genetic epigenesis | en |
dc.subject | genetics | en |
dc.subject | metabolism | en |
dc.subject | pandemic | en |
dc.subject | pathogenicity | en |
dc.subject | proteomics | en |
dc.subject | signal transduction | en |
dc.subject | virology | en |
dc.subject | virus pneumonia | en |
dc.subject | Autophagy | en |
dc.subject | Betacoronavirus | en |
dc.subject | Computer Simulation | en |
dc.subject | Coronavirus Infections | en |
dc.subject | Diabetes Complications | en |
dc.subject | Drug Design | en |
dc.subject | Epigenesis, Genetic | en |
dc.subject | Humans | en |
dc.subject | Hyperglycemia | en |
dc.subject | Lipids | en |
dc.subject | Pandemics | en |
dc.subject | Pneumonia, Viral | en |
dc.subject | Protein Binding | en |
dc.subject | Proteomics | en |
dc.subject | Signal Transduction | en |
dc.subject | Transcriptome | en |
dc.subject | Churchill Livingstone | en |
dc.title | A data-driven hypothesis on the epigenetic dysregulation of host metabolism by SARS coronaviral infection: Potential implications for the SARS-CoV-2 modus operandi | en |
dc.type | journalArticle | en |
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