Elucidating the causal associations and mechanisms between circulating immune cells and idiopathic pulmonary fibrosis: new insights from Mendelian randomization and transcriptomics.

BACKGROUND

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.

OBJECTIVE

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.