Interplay of LncRNAs NEAT1 and TUG1 in Incidence of Cytokine Storm in Appraisal of COVID-19 Infection.
Int J Biol Sci
; 18(13): 4901-4913, 2022.
Article
in English
| MEDLINE | ID: covidwho-1964519
ABSTRACT
Background:
In 2019, the coronavirus pandemic emerged, resulting in the highest mortality and morbidity rate globally. It has a prevailing transmission rate and continues to be a global burden. There is a paucity of data regarding the role of long non-coding RNAs (lncRNAs) in COVID-19. Therefore, the current study aimed to investigate lncRNAs, particularly NEAT1 and TUG1, and their association with IL-6, CCL2, and TNF-α in COVID-19 patients with moderate and severe disease.Methods:
The study was conducted on 80 COVID-19 patients (35 with severe and 45 with moderate infection) and 40 control subjects. Complete blood count (CBC), D-dimer assay, serum ferritin, and CRP were assayed. qRT-PCR was used to measure RNAs and lncRNAs.Results:
NEAT1 and TUG1 expression levels were higher in COVID-19 patients compared with controls (P<0.001). Furthermore, CCL2, IL-6, and TNF-α expressions were higher in COVID-19 patients compared to controls (P<0.001). CCL2 and IL-6 expression levels were significantly higher in patients with severe compared to those with moderate COVID-19 infection (P<0.001). IL-6 had the highest accuracy in distinguishing COVID-19 patients (AUC=1, P<0.001 at a cutoff of 0.359), followed by TUG1 (AUC=0.999, P<0.001 at a cutoff of 2.28). NEAT1 and TUG1 had significant correlations with the measured cytokines, and based on the multivariate regression analysis, NEAT1 is the independent predictor for survival in COVID-19 patients (P=0.02).Conclusion:
In COVID-19 patients, significant overexpression of NEAT1 and TUG1 was observed, consistent with cytokine storm. TUG1 could be an efficient diagnostic biomarker, whereas NEAT1 was an independent predictor for overall survival.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
RNA, Long Noncoding
/
Cytokine Release Syndrome
/
COVID-19
Type of study:
Observational study
/
Prognostic study
Topics:
Long Covid
Limits:
Humans
Language:
English
Journal:
Int J Biol Sci
Journal subject:
Biology
Year:
2022
Document Type:
Article
Affiliation country:
Ijbs.72318
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