Department of Hematology, Nanjing Lishui People's Hospital, Zhongda Hospital Lishui Branch, Southeast University, Nanjing, China.
Department of Gastroenterology, Jiangsu Province People's Hospital, Nanjing, China.
Front Cell Infect Microbiol. 2024 Aug 19;14:1393432. doi: 10.3389/fcimb.2024.1393432. eCollection 2024.
The immune response regulates the severity of COVID-19 (sCOVID-19). This study examined the cause-and-effect relationship between immune cell traits (ICTs) and the risk of severe COVID-19. Additionally, we discovered the potential role of plasma metabolome in modulating this risk.
Employing data from a genome-wide association study (GWAS), we conducted a two-sample Mendelian randomization (MR) assessment of 731 genetic ICTs and sCOVID-19 (5,101 cases, 1,383,241 controls) incidence. The MR analysis was utilized to further quantitate the degree of plasma metabolome-mediated regulation of immune traits in sCOVID-19.
The inverse variance weighted method recognized 2 plasma metabolites (PMs) responsible for casual associations between immune cells and sCOVID-19 risk. These included Tridecenedioate (C13:1-DC) which regulated the association between CD27 on IgD- CD38br (OR 0.804, 95% CI 0.699-0.925, p = 0.002) and sCOVID-19 risk (mediated proportion: 18.7%); arginine to citrulline ratio which controlled the relationship of CD39 on monocyte (OR 1.053, 95% CI 1.013-1.094, p = 0.009) with sCOVID-19 risk (mediated proportion: -7.11%). No strong evidence that genetically predicted sCOVID-19 influenced the aforementioned immune traits.
In this study, we have successfully identified a cause-and-effect relationship between certain ICTs, PMs, and the likelihood of contracting severe COVID-19. Our findings can potentially improve the accuracy of COVID-19 prognostic evaluation and provide valuable insights into the underlying mechanisms of the disease.
免疫反应调节 COVID-19(sCOVID-19)的严重程度。本研究探讨了免疫细胞特征(ICTs)与严重 COVID-19 风险之间的因果关系。此外,我们发现了血浆代谢组在调节这种风险方面的潜在作用。
利用全基因组关联研究(GWAS)的数据,我们对 731 种遗传 ICTs 和 sCOVID-19(5101 例病例,1383241 例对照)的发病率进行了两样本 Mendelian 随机化(MR)评估。MR 分析用于进一步量化血浆代谢组在 sCOVID-19 中对免疫特征的调节程度。
反向方差加权法识别出与免疫细胞和 sCOVID-19 风险之间的因果关系相关的 2 种血浆代谢物(PMs)。这包括十三碳二烯酸(C13:1-DC),它调节了 IgD-CD38br 上 CD27 与 sCOVID-19 风险之间的关联(OR 0.804,95%CI 0.699-0.925,p = 0.002)(介导比例:18.7%);精氨酸到瓜氨酸的比值控制单核细胞上 CD39 与 sCOVID-19 风险的关系(OR 1.053,95%CI 1.013-1.094,p = 0.009)(介导比例:-7.11%)。没有强有力的证据表明遗传预测的 sCOVID-19 会影响上述免疫特征。
在这项研究中,我们成功地确定了某些 ICTs、PMs 与感染严重 COVID-19 的可能性之间的因果关系。我们的发现有可能提高 COVID-19 预后评估的准确性,并为该疾病的潜在机制提供有价值的见解。