A bioinformatic approach to investigating cytokine genes and their receptor variants in relation to COVID-19 progression.

Severe acute respiratory syndrome coronavirus 2 infection produces a wide spectrum of manifestations, ranging from no symptom to viral pneumonia. This study aimed to determine the genetic variations in cytokines and their receptors in relation to COVID-19 pathogenesis using bioinformatic tools. Single nucleotide polymorphisms (SNPs) of genes encoding the cytokines and cytokine receptors elevated in patients with COVID-19 were determined from the National Biotechnology Information Center website (using the dbSNP database). Missense variants were found in 3 cytokine genes and 10 cytokine receptor genes. Computational analyses were conducted to detect the effects of these missense SNPs via cloud-based software tools. Also, the miRSNP database was used to explore whether SNPs in the 3'-UTR altered the miRNA binding efficiency for genes of cytokines and their receptors. Our in silico studies revealed that one SNP in the vascular endothelial growth factor receptor 2 (VEGFR2) gene was predicted as deleterious using sorting intolerant from tolerant. Also, the stability of VEGFR2 decreased in the I-Mutant2.0 (biotool for predicting stability changes upon mutation from the protein sequence or structure) prediction. It was suggested that the decrease in VEGFR2 function (due to the rs1870377 polymorphism) may be correlated with the progression of COVID-19 or contribute to the pathogenesis. Moreover, 27 SNPs were determined to affect miRNA binding for the genes of cytokine receptors. CXCR2 rs1126579, TNFRSF1B rs1061624 and IL10RB rs8178562 SNPs were predicted to break the miRNA-mRNA binding sites for miR-516a-3, miR-720 and miR-328, respectively. These miRNAs play an important role in immune regulation and lung damage repair. Further studies are needed to evaluate the importance of these miRNAs and the SNPs.