ArticleFrontiers in immunology2024
Elucidating the causal associations and mechanisms between circulating immune cells and idiopathic pulmonary fibrosis: new insights from Mendelian randomization and transcriptomics.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Ablation-immunotherapy synergy in cancer: mechanisms of the abscopal effect, emerging clinical applications, and translational roadmaps for next-generation onco-immunology.Medical oncology (Northwood, London, England) · 2026Review
- Immunosenescence in Idiopathic Pulmonary Fibrosis.Journal of inflammation research · 2026Review
- Mendelian randomization and mediation analysis reveal the role of immune cells in the pathways between inflammatory factors and glioblastoma.The Journal of international medical research · 2025Article
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Authors and funding
7 authors.
Funding
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Abstract
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. Conclusions: Our study demonstrates the causal associations of specific immune cell phenotypes with IPF through genetic methods and identifies
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