Yang Han, Wu Xuanyu, Xiao Xiang, Chen Jiajing, Yu Xiaomin, Zhao Wen, Wang Fei
Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
Front Immunol. 2025 Jan 17;15:1437984. doi: 10.3389/fimmu.2024.1437984. eCollection 2024.
Growing evidence indicates an association between circulating immune cell phenotypes and idiopathic pulmonary fibrosis (IPF). Although studies have attempted to elucidate the causal relationship between the two, further clarification of the specific mechanisms and causal linkages is warranted.
We aimed to conduct a two-sample Mendelian randomization (MR) analysis with transcriptomics data analysis to elucidate the causal relationship between circulating immune cells and IPF and to explore potential biomarkers.
We first explored the bidirectional causal association between IPF and immune cell phenotypes using two-sample MR analysis. Genome-wide association studies data for immune cell phenotype and IPF were obtained from publicly available databases. A standardized instrumental variable screening process was used to select single nucleotide polymorphisms (SNPs) for inclusion in the MR. Five methods represented by IVW were used to assess causal effects. Subsequently, SNP-nearest genes combined with the transcriptomics data of IPF were subjected to multiple bioinformatics analyses such as TIMER, WGCNA, functional enrichment analysis, protein-protein interaction analysis, and ROC to identify IPF biomarkers. Finally, the single-cell RNA sequencing (scRNA-seq) data was used to validate our findings by single-cell analysis.
The MR study identified 27 immune cell phenotypes causally associated with IPF, of which 20 were associated with a decreased risk of developing IPF and 7 were associated with an increased risk. (AUC=0.98), (AUC=0.83), and (AUC=0.87) were identified as promising biomarkers of IPF. Single cell analysis showed differences in CD14 CD16 monocytes, CD16 monocytes and Granulocyte-monocyte progenito between the IPF group and the healthy control group. The three hub genes were highly expressed in three immune cell subsets of IPF patients. It underscores the potential feasibility of three genes as biomarkers.
Our study demonstrates the causal associations of specific immune cell phenotypes with IPF through genetic methods and identifies , , and as biomarkers of IPF through bioinformatics analysis. These findings provide guidance for future clinical and basic research.
越来越多的证据表明循环免疫细胞表型与特发性肺纤维化（IPF）之间存在关联。尽管已有研究试图阐明两者之间的因果关系，但仍需进一步明确具体机制和因果联系。
我们旨在通过转录组学数据分析进行两样本孟德尔随机化（MR）分析，以阐明循环免疫细胞与IPF之间的因果关系，并探索潜在的生物标志物。
我们首先使用两样本MR分析探索IPF与免疫细胞表型之间的双向因果关联。免疫细胞表型和IPF的全基因组关联研究数据来自公开可用的数据库。采用标准化的工具变量筛选过程选择单核苷酸多态性（SNP）纳入MR。使用以IVW为代表的五种方法评估因果效应。随后，将SNP最近基因与IPF的转录组学数据相结合，进行TIMER、WGCNA、功能富集分析、蛋白质-蛋白质相互作用分析和ROC等多种生物信息学分析，以鉴定IPF生物标志物。最后，使用单细胞RNA测序（scRNA-seq）数据通过单细胞分析验证我们的发现。
MR研究确定了27种与IPF有因果关联的免疫细胞表型，其中20种与IPF发病风险降低相关，7种与风险增加相关。（AUC=0.98）、（AUC=0.83）和（AUC=0.87）被确定为有前景的IPF生物标志物。单细胞分析显示，IPF组与健康对照组之间的CD14 CD16单核细胞、CD16单核细胞和粒细胞-单核细胞祖细胞存在差异。这三个枢纽基因在IPF患者的三个免疫细胞亚群中高表达。这强调了这三个基因作为生物标志物的潜在可行性。
我们的研究通过遗传方法证明了特定免疫细胞表型与IPF之间的因果关联，并通过生物信息学分析确定、和为IPF的生物标志物。这些发现为未来的临床和基础研究提供了指导。
