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Title
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A dynamic mucin mRNA signature associates with COVID-19 disease presentation and severity
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Author
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Abstract
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| BACKGROUND. SARS-CoV-2 infection induces mucin overexpression further promoting disease. As mucins are critical components of the innate immunity, unravelling their expression profiles that dictate the course of disease could greatly enhance our understanding and management of COVID-19. METHODS. Using validated RT-PCR assays, we assessed mucin mRNA expression in the blood of symptomatic COVID-19 patients compared to symptomatic non-COVID-19 patients and healthy controls and correlated the data to clinical outcome parameters. Additionally, we analyzed mucin expression in mucus and lung tissue from COVID-19 patients and investigated the effect of drugs for COVID-19 treatment on SARS-CoV-2-induced mucin expression in pulmonary epithelial cells. RESULTS. We identified a dynamic blood mucin mRNA signature that clearly segregates symptomatic COVID-19 from non-COVID-19 patients based on expression of MUC1, MUC2, MUC4, MUC6, MUC13, MUC16 and MUC20 (AUCROC of 91.8 %; sensitivity and specificity of respectively 90.6% and 93.3%); and that discriminates between mild and critical COVID-19 based on the expression of MUC16, MUC20 and MUC21 (AUCROC of 89.1 %; sensitivity and specificity of respectively 90.0% and 85.7%). Differences in the transcriptional landscape of mucins in critical cases compared to mild cases even identify associations with COVID-19 symptoms, respiratory support, organ failure, secondary infections and mortality. Furthermore, we identified different mucins in mucus and lung tissue of critically ill COVID-19 patients and showed the ability of baricitinib, tocilizumab, favipiravir and remdesivir to suppress expression of the SARS-CoV-2-induced mucins. CONCLUSION. This multifaceted blood mucin mRNA signature shows the potential role of mucin profiling in diagnosing, estimating severity and guiding treatment options in COVID-19 patients. |
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Language
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English
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Source (journal)
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JCI Insight
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Publication
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2021
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DOI
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10.1172/JCI.INSIGHT.151777
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Volume/pages
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6
:19
(2021)
, 21 p.
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Article Reference
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e151777
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ISI
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000706302600001
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Pubmed ID
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34448730
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Medium
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E-only publicatie
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Full text (Publisher's DOI)
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Full text (open access)
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