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Assessing the suitability of long non-coding RNAs as therapeutic targets and biomarkers in SARS-CoV-2 infection.
Zhong, Yichen; Ashley, Caroline L; Steain, Megan; Ataide, Sandro Fernandes.
  • Zhong Y; School of Life and Environmental Sciences, University of Sydney, Sydney, NSW, Australia.
  • Ashley CL; School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
  • Steain M; School of Medical Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, Australia.
  • Ataide SF; School of Life and Environmental Sciences, University of Sydney, Sydney, NSW, Australia.
Front Mol Biosci ; 9: 975322, 2022.
Article in English | MEDLINE | ID: covidwho-2022799
ABSTRACT
Long non-coding RNAs (lncRNAs) are RNA transcripts that are over 200 nucleotides and rarely encode proteins or peptides. They regulate gene expression and protein activities and are heavily involved in many cellular processes such as cytokine secretion in respond to viral infection. In severe COVID-19 cases, hyperactivation of the immune system may cause an abnormally sharp increase in pro-inflammatory cytokines, known as cytokine release syndrome (CRS), which leads to severe tissue damage or even organ failure, raising COVID-19 mortality rate. In this review, we assessed the correlation between lncRNAs expression and cytokine release syndrome by comparing lncRNA profiles between COVID-19 patients and health controls, as well as between severe and non-severe cases. We also discussed the role of lncRNAs in CRS contributors and showed that the lncRNA profiles display consistency with patients' clinic symptoms, thus suggesting the potential of lncRNAs as drug targets or biomarkers in COVID-19 treatment.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Topics: Long Covid Language: English Journal: Front Mol Biosci Year: 2022 Document Type: Article Affiliation country: Fmolb.2022.975322

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Observational study Topics: Long Covid Language: English Journal: Front Mol Biosci Year: 2022 Document Type: Article Affiliation country: Fmolb.2022.975322