Analyzing the expression pattern of the noncoding RNAs (HOTAIR, PVT‐1, XIST, H19, and miRNA‐34a) in PBMC samples of patients with COVID‐19, according to the disease severity in Iran during 2022–2023: A cross‐sectional study

Abstract

Background and aims

MicroRNAs (miRNAs) and long noncoding RNAs (lncRNAs) are well‐known types of noncoding RNAs (ncRNAs), which have been known as the key regulators of gene expression. They can play critical roles in viral infection by regulating the host immune response and interacting with genes in the viral genome. In this regard, ncRNAs can be employed as biomarkers for viral diseases. The current study aimed to evaluate peripheral blood mononuclear cell (PBMC) ncRNAs (lncRNAs‐homeobox C antisense intergenic RNA [HOTAIR], ‐H19, X‐inactive‐specific transcript [XIST], plasmacytoma variant translocation 1 [PVT‐1], and miR‐34a) as diagnostic biomarkers to differentiate severe COVID‐19 cases from mild ones.

Methods

Candidate ncRNAs were selected according to previous studies and assessed by real‐time polymerase chain reaction in the PBMC samples of patients with severe coronavirus disease 2019 (COVID‐19) ( n = 40), healthy subjects ( n = 40), and mild COVID‐19 cases ( n = 40). Furthermore, the diagnostic value of the selected ncRNAs was assessed by analyzing the receiver‐operating characteristic (ROC).

Results

The results demonstrated that the expression pattern of the selected ncRNAs was significantly different between the studied groups. The levels of HOTAIR, XIST, and miR‐34a were remarkably overexpressed in the severe COVID‐19 group in comparison with the mild COVID‐19 group, and in return, the PVT‐1 levels were lower than in the mild COVID‐19 group. Interestingly, the XIST expression level in men with severe COVID‐19 was higher compared to women with mild COVID‐19. ROC results suggested that HOTAIR and PVT‐1 could serve as useful biomarkers for screening mild COVID‐19 from severe COVID‐19.

Conclusions

Overall, different expression patterns of the selected ncRNAs and ROC curve results revealed that these factors can contribute to COVID‐19 pathogenicity and can be considered diagnostic markers of COVID‐19 severe outcomes.