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Bioinformatic analysis of key pathways and genes involved in pediatric atopic dermatitis
Tianyi Wang1, Bingxin Zhang1, Danhui Li2
1Department of Dermatology, First Teaching Hospital of Tianjin University of TCM, China.
Insights
This study identified unique gene signatures in pediatric atopic dermatitis (AD) by comparing gene expression in children versus adults. These findings may lead to new diagnostic markers and treatments for early-onset AD.
Area of Science:
- Immunology
- Genetics
- Dermatology
Background:
- Atopic dermatitis (AD) often begins in childhood, yet most research focuses on adult AD.
- Understanding pediatric-specific AD mechanisms is crucial for effective early intervention.
Purpose of the Study:
- To identify gene expression signatures distinguishing pediatric AD from adult AD.
- To uncover potential therapeutic targets and diagnostic biomarkers for pediatric AD.
Main Methods:
- Analysis of four public gene expression datasets (GSE32924, GSE36842, GSE58558, GSE107361).
- Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses.
- Construction of a protein-protein interaction (PPI) network using Cytoscape.
Main Results:
- Identified 654 differentially expressed genes (DEGs) between pediatric and adult AD.
- Up-regulated DEGs were linked to granulocyte/neutrophil migration and chemotaxis; down-regulated DEGs to biological adhesion.
- Key pathways involved included chemokine signaling, cytokine-cytokine interaction, and regulation of the actin cytoskeleton.
Conclusions:
- Distinct gene expression profiles characterize pediatric AD compared to adult AD.
- Identified hub genes and pathways offer potential targets for pediatric AD therapies and diagnostics.
- This research highlights the need for age-specific approaches in AD research and treatment.
Abstract:
The initiation of atopic dermatitis (AD) typically happens very early in life, but most of our understanding of AD is derived from studies on AD patients in adult. The aim of the present study was to identify gene signature speficic to pediatric AD comapred with adult AD. The gene expression profiles of four datasets (GSE32924, GSE36842, GSE58558, and GSE107361) were downloaded from the GEO database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed, and protein-protein interaction (PPI) network was constructed by Cytoscape software. Total 654 differentially expressed genes (DEGs) (394 up-regulated and 260 down-regulated) were identified in pediatric AD samples with adult AD samples as control. The up-regulated DEGs were significantly enriched in the migration and chemotaxis of granulocyte and neutrophil, while down-regulated DEGs were significantly enriched in biological adhesion. KEGG pathway analysis showed that up-regulated DEGs participated in chemokine signaling pathway while down-regulated DEGs participated in adherens junction, focal adhesion, and regulation of actin cytoskeleton. The top 10 hub genes GAPDH, EGFR, ACTB, ESR1, CDK1, CXCL8, CD44, KRAS, PTGS2, and SMC3 were involved in chemokine signaling pathway, cytokine-cytokine receptor interaction, interleukin-17 signaling pathway, and regulation of actin cytoskeleton. In conclusion, we identified DEGs and hub genes involved in pediatric AD, which might be used as therapeutic targets and diagnostic biomarkers for pediatric AD.
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