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Gene expression and polymorphisms of Toll-like receptor 7 among Iraqi COVID-19 patients

Year: 2026
Type: article
Abstract: The immune system's defenses against viruses are boosted by releasing inflammatory cytokines and antiviral mediators by toll-like receptor families (TLRs). TLR7 is one of the members of this family (TLRs). Thus, this study aimed to look into its function and genetic variation in the development of COVID-19 disease and its recovery. The study was conducted on 90 patients (45 severe-critical cases and 45 mild-moderate cases), 50 recovered cases, and 89 healthy people using quantitative real-time and allele-specific PCR for gene expression and gene polymorphisms determination, respectively. The relative TLR7 gene expression ratio was significantly higher in COVID-19 patients compared to recovered and healthy controls. The present study showed that the folding rate of TLR7 gene expression in the severely critically ill group (58.3±28.6) was significantly higher (p < 0.046) than in the mild to moderate patient group (41.7±24.39). The same can be said for the Ct values ​​(16-26) and (27-36), which were (51.9±27.7) and (37.5±23.4), respectively, with a significant value (p<0.01). Moreover, it has been found that there was a positive correlation between classical biomarkers and gene expression of this receptor. Interestingly, the present study showed no significant difference in TLR7 gene SNPs, rs179010 C and T allele, and rs3853839 C and G allele (p = 0.801 and 0.461, respectively). Moreover, the rs179008-TLR7 mutant C allele was not found in the present study population. We therefore recommend the detection of the rs179008- TLR7 mutant T allele and other TLR7 SNP alleles in the Iraqi population. TLR7 gene expression is positively associated with the disease and its severity. Conversely, down-regulating TLR7 gene expression is linked to a quicker recovery from the illness mentioned above. However, the SNPs under investigation did not affect the disease's severity or the patient's ability to recover from it.
Language: English
Subfield: Immunology
Open Access status: diamond
OpenAlex ID: W7223542571
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