eISSN: 2299-0046
ISSN: 1642-395X
Advances in Dermatology and Allergology/Postępy Dermatologii i Alergologii
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SCImago Journal & Country Rank
6/2022
vol. 39
 
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abstract:
Original paper

Integrated bioinformatics-based identification of potential diagnostic biomarkers associated with atopic dermatitis

Guanghua Chen
1
,
Jia Yan
2

  1. Department of Dermatology, Children’s Hospital of Chongqing Medical University, National Clinical Research Centre for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
  2. Digestive Department, University-Town Hospital of Chongqing Medical University, Chongqing, China
Adv Dermatol Allergol 2022; XXXIX (6): 1059-1068
Online publish date: 2022/03/27
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Introduction
In-depth analysis of the rambling genes of atopic dermatitis may help to identify the pathologic mechanism of this disease. However, this has seldom been performed.

Aim
Using bioinformatics approaches, we analysed 3 gene expression profiles in the gene expression omnibus (GEO) database, identified the differentially expressed genes (DEGs), and found out the overlapping DEGs (common DEGs, cDEGs) in the above 3 profiles.

Material and methods
We identified 91 upregulated cDEGs, which were then arranged into a protein-protein interaction (PPI) network, and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) term enrichment analyses were performed to explore the functional roles of these genes.

Results
GO analyses revealed these DEGs to be significantly enriched in biological processes including immune system process, immune response, defence response, leukocyte activation, and response to the biotic stimulus. These DEGs were also enriched in the KEGG pathway, including influenza A, amoebiasis, primary immunodeficiency, cytokine-cytokine receptor interaction, and IL-17 signalling pathway. PPI analysis showed that 9 genes (PTPRC-CTLA4-CD274-CD1C-IL7R-GZMB-CCL5-CD83, and CCL22) were probably the novel hub genes of atopic dermatitis.

Conclusions
Together, the findings of these bioinformatics analyses thus identified key hub genes associated with AD development.

keywords:

atopic dermatitis, GEO database, bioinformatics, hub genes, pathways

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