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JCR 2016
جستجوی مقالات
پنجشنبه 27 آذر 1404
Cell Journal
، جلد ۲۵، شماره ۶، صفحات ۴۱۸-۴۲۶
عنوان فارسی
چکیده فارسی مقاله
کلیدواژههای فارسی مقاله
عنوان انگلیسی
Psoriasis Associated Hub Genes Revealed by Weighted Gene Co-Expression Network Analysis
چکیده انگلیسی مقاله
Objective:
Psoriasis, an immune-mediated disorder, is a multifactorial disease of unidentified cause. This study aims to discover the possible biomarkers of this papulosquamous skin disease.
Materials and Methods:
The gene chip GSE55201, resulted from an experimental study, including 44 psoriasis patients and 30 healthy controls was downloaded from GEO and weighted gene co-expression network analysis was utilized to identify the hub genes. The key modules were determined using the module eigenvalues. We used biological functions, cellular components, and molecular functions in the Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes enrichment analysis in the gene metabolic pathway were used for enrichment analysis.
Results:
Adjacency matrix was built by using power adjacency function and the power to turn the correlation to adjacency matrix was 4 with a topology fit index of 0.92. Using the weighted gene co-expression network analysis, 11 modules were identified. The green-yellow module eigenvalues were significantly associated with psoriasis (Pearson correlation=0.53, p<0.001). Candidate hub genes were determined by their higher connectivity and relationship with module eigenvalue. The genes including SIGLEC8, IL5RA, CCR3, RNASE2, CPA3, GATA2, c-KIT, and PRSS33 were recorded as the hub genes.
Conclusion:
In summary we can conclude that SIGLEC8, IL5RA, CCR3, RNASE2, CPA3, GATA2, c-KIT, and PRSS33 have an important role in the immune response regulation and could be considered as a potential diagnostic biomarker and therapeutic target for Psoriasis.
کلیدواژههای انگلیسی مقاله
gene, Gene Modules, Gene network, Psoriasis
نویسندگان مقاله
Zeinab Darvish |
Department of Biostatistics and Epidemiology, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
Saeed Ghanbari |
Department of Biostatistics and Epidemiology, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
Saeid Afshar |
Research Center for Molecular Medicine, Hamadan University of Medical Sciences, Hamadan, Iran
Leili Tapak |
Department of Biostatistics, School of Public Health and Modeling of Non-communicable Disease Research Center, Hamadan University of Medical Sciences, Hamadan, Iran
Payam Amini |
Department of Biostatistics and Epidemiology, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
نشانی اینترنتی
https://www.celljournal.org/article_703143_0022ee189e348fd13b9559f0618b67e4.pdf
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