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ORIGINAL ARTICLE
Year : 2022  |  Volume : 40  |  Issue : 3  |  Page : 162-167

Identification of immune-related genes in atopic dermatitis, contact dermatitis, and psoriasis: A bioinformatics analysis


1 Department of Dermatology Clinnic, The Affiliated Hospital to Changchun University of Chinese Medicine, Changchun, Jilin Province, China
2 Department of Pain, Jilin Academy of Chinese Medicine Sciences, Changchun, Jilin Province, China
3 College of Basic Medicine, Changchun University of Chinese Medicine, Changchun, Jilin Province, China

Correspondence Address:
Dr. Lei Gao
College of Basic Medicine, Changchun University of Chinese Medicine, 1035 Boshuo Road, Jingyue District, Changchun City, Jilin Province, 130117
China
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ds.ds_26_22

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Background: The exact mechanisms and targeted therapies for atopic dermatitis (AD), contact dermatitis (CD), and psoriasis (PS) remain unknown. Objectives: This study aimed to identify the biomarkers related to immune and novel therapeutic drugs for AD, CD, and PS. Methods: The GSE153007 dataset including 12 AD, 9 CD, and 14 PS samples and 40 control samples, which was obtained from the Gene Expression Omnibus database and analyzed. The immune infiltration level of each sample was then evaluated using the single-sample gene set enrichment analysis (ssGSEA). Then, we screened for immune-related differentially expressed genes (DEGs) that overlapped. The Database for Annotation, Visualization, and Integrated Discovery database was used to perform the gene ontology (GO) biological process. Furthermore, using search tool for the retrieval of interaction gene (STRING), the protein-protein interaction (PPI) was predicted on immune-related DEGs. We also searched the DGIdb database for novel therapeutic drugs for AD, CD, and PS. Results: According to ssGSEA results, most immune cells were highly infiltrated in the disease group. GO analysis indicated that AD, CD, and PS were enriched in signal transduction, inflammatory response, immune response, and innate immune response. We further found hub genes related to AD (CD4, ITGAM), CD (CD8A, CD86), and PS (CD4, CD8A) from PPI network. Moreover, the drug prediction indicated that drugs targeting CSF1R was the most effective for AD, whereas drugs targeting FCGR3A and CD86 were more effective for CD and PS. Conclusion: These immune-associated genes such as FCGR3A, CD86, and CSF1R might be regarded as therapeutic targets for patients with AD, CD, and PS.


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