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• W4377140652 abstract "COVID-19 is a novel infectious disease for which no specific treatment exists. It is likely that a combination of genetic and non-genetic factors predispose to it. Expression levels of genes that are involved in the interaction with SARS-CoV-2 or the host response are thought to play a role in disease susceptibility and severity. It is crucial to explore biomarkers for disease severity and outcome. Herein, we studied the expression levels and effects of long non-coding metastasis-associated lung adenocarcinoma transcript 1 (lnc-MALAT1) and long non-coding maternally expressed gene 3 (lnc-MEG3) in COVID-19 patients. The study enrolled 35 hospitalized and 35 non-hospitalized COVID-19 patients, and 35 healthy controls. A chest computed tomography (CT) scan, complete blood count (CBC), ferritin, C-reactive protein (CRP), D-dimer and analysis of lnc-MALAT1 and lnc-MEG3 expression were done.There was a significant relation between ferritin, CRP, D-dimer levels, oxygen saturation, CT-CORADS score and disease severity. Lnc-MALAT1 was significantly higher but lnc-MEG3 was significantly lower in patients vs. controls, and in hospitalized vs. non-hospitalized patients. Elevated MALAT1 and reduced MEG3 levels were significantly associated with more elevated ferritin, CRP, D-dimer levels, lower oxygen saturation, higher CT-CORADS score and poor survival. Moreover, MALAT1 and MEG3 levels displayed higher sensitivity and specificity as predictors of COVID-19 severity compared with other prognostic biochemical markers such as ferritin, CRP, and D-dimer.MALAT1 levels are higher, whereas MEG3 levels are lower in COVID-19 patients. Both are linked to disease severity and mortality and could emerge as predictive biomarkers for COVID-19 severity and therapeutic targets." @default.
• W4377140652 created "2023-05-21" @default.
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• W4377140652 date "2023-05-20" @default.
• W4377140652 modified "2023-10-17" @default.
• W4377140652 title "Expression pattern of long non‐coding RNAs MALAT1 and MEG3 in COVID‐19 patients" @default.
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• W4377140652 doi "https://doi.org/10.1002/jgm.3532" @default.
• W4377140652 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37209019" @default.
• W4377140652 hasPublicationYear "2023" @default.
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