Hu Zhuozheng, Xu Peihao, Wu Jiajun, Zhou Weijun, Zhou Yajie, Xie Lei, Zhang Wenxiong, Cheng Yong
Department of Thoracic Surgery, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
School of Stomatology, Jiangxi Medical College, Nanchang University, Nanchang, China.
Clin Respir J. 2025 Jun;19(6):e70097. doi: 10.1111/crj.70097.
Considerable evidence suggests a strong link between immune cell traits (ICTs) and asthma development via plasma metabolites (PMs), but the causality between ICTs and asthma is still unclear, mainly due to issues like selection bias. Our research was designed to investigate the causality between ICTs, PMs, and asthma and to provide a clearer explanation of these relationships.
Utilizing the GWAS database, this study employed a two-step, two-sample Mendelian randomization (MR) approach and the inverse variance weighted (IVW) method to investigate the causality between ICTs and asthma, as well as between PMs and asthma. Lastly, we calculated the mediated proportion of PMs as mediators in the link between ICTs and asthma.
Excluding heterogeneity and pleiotropy, MR analysis identified 13 ICTs (CD14 on CD33br HLA DR+ CD14dim, etc.) and asthma causality, and no reverse causality was observed. In addition, 27 PMs (androsterone sulfate levels, succinate levels, etc.) were also causally associated with asthma. Mediate MR indicated -9.81% (-1.2%, -18.4%) of the effect of CD24 on IgD+ CD38br on asthma is mediated by S-methylcysteine sulfoxide levels, with a mediated effect value (p = 0.006) is 0.003 (0.0004, 0.006); 21.4% (6.2%, -36.6%) of the effect of CD3 on CD28+ CD4+ on asthma is mediated by 1-myristoyl-2-arachidonoyl-GPC (14:0/20:4) levels, with a mediated effect value (p = 0.025) is 0.004 (0.001, 0.007).
We identified two pathways by which ICTs can impact asthma through PMs, which might help in identifying potential targets for personalized treatment approaches.
大量证据表明免疫细胞特征（ICTs）与通过血浆代谢物（PMs）引发的哮喘之间存在紧密联系，但ICTs与哮喘之间的因果关系仍不明确，主要是由于选择偏倚等问题。我们的研究旨在调查ICTs、PMs与哮喘之间的因果关系，并对这些关系给出更清晰的解释。
本研究利用全基因组关联研究（GWAS）数据库，采用两步两样本孟德尔随机化（MR）方法和逆方差加权（IVW）方法，来研究ICTs与哮喘之间以及PMs与哮喘之间的因果关系。最后，我们计算了PMs作为ICTs与哮喘之间联系的中介的中介比例。
排除异质性和多效性后，MR分析确定了13种ICTs（CD33br HLA DR+ CD14dim上的CD14等）与哮喘的因果关系，未观察到反向因果关系。此外，27种PMs（硫酸雄酮水平、琥珀酸水平等）也与哮喘存在因果关联。中介MR表明，CD24对IgD+ CD38br对哮喘的影响中有-9.81%（-1.2%，-18.4%）由S-甲基半胱氨酸亚砜水平介导，中介效应值（p = 0.006）为0.003（0.0004，0.006）；CD3对CD28+ CD4+对哮喘的影响中有21.4%（6.2%，-36.6%）由1-肉豆蔻酰-2-花生四烯酰-GPC（14:0/20:4）水平介导，中介效应值（p = 0.025）为0.004（0.001，0.007）。
我们确定了两条ICTs可通过PMs影响哮喘的途径，这可能有助于确定个性化治疗方法的潜在靶点。
