1. Medical Biochemistry and Molecular Biology Department, Faculty of Medicine, Menoufia University 32511, Shebin El-Kom, Egypt.
2. Medical Biochemistry Unit, College of Medicine, Al Baha University, Al Baha 65779, Saudi Arabia.
3. Microbiology and Immunology Unit, Department of Pathology, College of Medicine, Jouf University, Sakaka 72388, Saudi Arabia.
4. Medical Microbiology and Immunology Department, Faculty of Medicine, Menoufia University, Shebin El Kom 32511, Egypt.
5. Chest Department, Faculty of Medicine, Menoufia University, Shebin El Kom 32511, Egypt.
6. Tropical Medicine Department, Faculty of Medicine, Menoufia University, Shebin El Kom 32511, Egypt.
7. Internal Medicine Department, College of Medicine, King Faisal University, Al-Ahsaa 31982, Saudi Arabia.
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: COVID-19, IL-6, NEAT1, TNF-α, TUG1