Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Department of Mycobacteriology and Pulmonary Research, Pasteur Institute of Iran, Tehran, Iran.
Cytokine. 2024 Dec;184:156775. doi: 10.1016/j.cyto.2024.156775. Epub 2024 Oct 4.
It is critical to examine the pathogenic pathways in coronavirus disease 2019 (COVID-19) that resulted in the development of severe lung injury. Surfactant protein B (SFTPB) is a vital component for sustaining life and serves pivotal functions in the host's defensive mechanisms and alveolar surface tension reduction. Our study aimed to determine the effect of SFTPB rs7316 and rs1130866 variants on the course of disease in COVID-19 patients.
The study cohort comprised 3,184 individuals diagnosed with COVID-19. We employed the RFLP approach to determine the variations of the SFTPB genes.
SFTPB rs7316 did not exhibit a statistically significant correlation with COVID-19 mortality across different inheritance models. But, after making more changes for SARS-CoV-2 variants, it was found that there was a strong link between the TT and TC genotypes of SFTPB rs7316 and death rates, especially for the Delta variant. Furthermore, our study's findings indicate a significant association between the SFTPB rs1130866 G allele and an elevated risk of mortality in COVID-19 across all variants of SARS-CoV-2.
The use of the SFTPB rs1130866 marker has the potential to facilitate the prediction of COVID-19 severity. On the other hand, for SFTPB rs7316, this kind of prediction seems to depend on the particular SARS-CoV-2 variants.
研究导致 2019 年冠状病毒病(COVID-19)严重肺部损伤的致病途径至关重要。表面活性蛋白 B(SFTPB)是维持生命的重要组成部分,在宿主防御机制和肺泡表面张力降低中发挥关键作用。我们的研究旨在确定 SFTPB rs7316 和 rs1130866 变体对 COVID-19 患者疾病进程的影响。
研究队列包括 3184 名确诊为 COVID-19 的个体。我们采用 RFLP 方法确定 SFTPB 基因的变异。
SFTPB rs7316 在不同遗传模式下与 COVID-19 死亡率之间没有统计学意义的相关性。但是,在对 SARS-CoV-2 变体进行更多更改后,发现 SFTPB rs7316 的 TT 和 TC 基因型与死亡率之间存在很强的联系,特别是对于 Delta 变体。此外,我们研究的结果表明,SFTPB rs1130866 的 G 等位基因与所有 SARS-CoV-2 变体的 COVID-19 死亡率升高之间存在显著关联。
使用 SFTPB rs1130866 标志物有可能促进 COVID-19 严重程度的预测。另一方面,对于 SFTPB rs7316,这种预测似乎取决于特定的 SARS-CoV-2 变体。