ArticleJournal of inflammation research2025
Screening and Validation of Potential Biomarkers of Immune Cells in Childhood Asthma Patients via Mendelian Randomization and Machine Learning.
Article in Journal of inflammation research, 2025. 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.
- Immune Cell-Mediated Causal Link Between Gut Microbiota Traits and Childhood Asthma: Evidence From Mendelian Randomization and Metagenomic Sequencing.The clinical respiratory journal · 2026Article
- Evolution, hotspots, and future directions of artificial intelligence in asthma research: a Web of Science-based bibliometric analysis [2016-2026].Journal of thoracic disease · 2026Article
- Integrative multi-omics reveals that downregulation of HLA-DPA1/DPB1 drives macrophage immune-metabolic dysregulation in pediatric asthma.Frontiers in immunology · 2026Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Asthma is one of the most common chronic respiratory diseases affecting children, and there is currently no clear remedy. Immune cells play a key role in childhood asthma. Therefore, a deeper investigation of the correlation between immune cells and childhood asthma could lead to a better understanding of asthma's origin, the identification of potential treatment targets, and the development of personalized treatment strategies. Patients and Methods: We used a two-sample Mendelian randomization (MR) analysis to investigate the possible causal relationship between childhood asthma and a total of 731 immune cells, including B cell (190), Maturation stages of T cell (79), Monocyte (43), Myeloid cell (64), TBNK (124), Treg (167), and CDC (64). LASSO logistic regression and SVM algorithms were used to identify key genes associated with childhood asthma. Specific signaling pathways associated with these key genes were further explored through gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA). Subsequently, the four key genes FCGR3A, TCTN3, ALOX5, and IL4R were verified in an established asthma mouse model using quantitative real-time PCR and Western blotting. Results: MR analysis showed that 60 immune cells were associated with childhood asthma, of which 32 were associated with high risk and 28 were associated with low risk. LASSO logistic regression and SVM algorithm identified six key genes that affect childhood asthma as ATF4, FCGR3A, GAS5, MGAT3, TAB1, and TCTN3. In addition, four genes, FCGR3A, TCTN3, ALOX5, and IL4R, were verified through animal experiments. Conclusion: Our findings confirmed that immune cells contribute to childhood asthma, highlighting the importance of key genes in the role of the immune microenvironment in this disease. These insights provide a new path for the exploration of the biological underpinnings of childhood asthma and the development of early intervention therapies.
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