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Predicting diagnostic gene biomarkers in allergic asthma
Weihua Liu1,2, Shuanglan Xu3, Quan He4
1Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital, Nanjing Medical University, Nanjing, Jiangsu, China.
Medicine
|May 1, 2026
Summary
This study identifies four key genes (MBOAT1, LRIG1, LOC401357, GPRIN3) linked to immune cell infiltration in allergic asthma (AA). These genes show potential as biomarkers and therapeutic targets for AA immunotherapy.
Area of Science:
- Immunology
- Bioinformatics
- Genetics
Background:
- Allergic asthma (AA) is a complex chronic inflammatory airway disease.
- Understanding the genetic underpinnings of immune cell infiltration in AA is crucial for developing effective treatments.
Purpose of the Study:
- To identify critical genes associated with immune cell infiltration in allergic asthma using bioinformatics.
- To establish a novel predictive diagnostic model for allergic asthma.
Main Methods:
- Retrospective analysis of public transcriptome datasets (GSE73482, GSE40889).
- Functional enrichment analyses (GO, KEGG) via Metascape.
- Least Absolute Shrinkage and Selection Operator (LASSO) regression for feature gene selection and model construction.
- Weighted Gene Co-expression Network Analysis (WGCNA) to identify relevant gene modules.
- Immune cell infiltration estimation using ssGSEA.
- Gene Set Enrichment Analysis (GSEA) to explore biological functions and pathways.
- Transcription factor prediction using Cistrome Data Browser.
Main Results:
- Identified four significant genes: MBOAT1, LRIG1, LOC401357, and GPRIN3 within a key gene module.
- GSEA revealed significant enrichment of these genes in immune-related signaling pathways.
- A regulatory network of these genes and their predicted transcription factors was visualized.
Conclusions:
- MBOAT1, LRIG1, LOC401357, and GPRIN3 are identified as candidate genes associated with allergic asthma.
- These genes represent potential biomarkers and therapeutic targets for AA immunotherapy.
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