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Psoriasis Associated Hub Genes Revealed by Weighted Gene Co-Expression Network Analysis
OBJEVTIVE: Psoriasis, an immune-mediated disorder, is a multifactorial disease with unidentified cause(s). This study aimed to discover possible biomarkers of this papulosquamous skin disease. MATERIALS AND METHODS: The gene chip GSE55201, resulted from an experimental study, including 44 Psoriasis...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Royan Institute
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10331440/ https://www.ncbi.nlm.nih.gov/pubmed/37434459 http://dx.doi.org/10.22074/CELLJ.2023.1982769.1191 |
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author | Darvish, Zeinab Ghanbari, Saeed Afshar, Saeid Tapak, Leili Amini, Payam |
author_facet | Darvish, Zeinab Ghanbari, Saeed Afshar, Saeid Tapak, Leili Amini, Payam |
author_sort | Darvish, Zeinab |
collection | PubMed |
description | OBJEVTIVE: Psoriasis, an immune-mediated disorder, is a multifactorial disease with unidentified cause(s). This study aimed to discover 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 hub genes. Key modules were determined using the module eigenvalues. We used biological functions (BFs), cellular components, and molecular functions in the Gene Ontology (GO) 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 four 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: We can conclude that SIGLEC8, IL5RA, CCR3, RNASE2, CPA3, GATA2, c-KIT, and PRSS33 have an important role in the immune response regulation and they could be considered as a potential diagnostic biomarker and therapeutic target for Psoriasis. |
format | Online Article Text |
id | pubmed-10331440 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Royan Institute |
record_format | MEDLINE/PubMed |
spelling | pubmed-103314402023-07-11 Psoriasis Associated Hub Genes Revealed by Weighted Gene Co-Expression Network Analysis Darvish, Zeinab Ghanbari, Saeed Afshar, Saeid Tapak, Leili Amini, Payam Cell J Original Article OBJEVTIVE: Psoriasis, an immune-mediated disorder, is a multifactorial disease with unidentified cause(s). This study aimed to discover 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 hub genes. Key modules were determined using the module eigenvalues. We used biological functions (BFs), cellular components, and molecular functions in the Gene Ontology (GO) 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 four 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: We can conclude that SIGLEC8, IL5RA, CCR3, RNASE2, CPA3, GATA2, c-KIT, and PRSS33 have an important role in the immune response regulation and they could be considered as a potential diagnostic biomarker and therapeutic target for Psoriasis. Royan Institute 2023-06 2023-06-28 /pmc/articles/PMC10331440/ /pubmed/37434459 http://dx.doi.org/10.22074/CELLJ.2023.1982769.1191 Text en Any use, distribution, reproduction or abstract of this publication in any medium, with the exception of commercial purposes, is permitted provided the original work is properly cited. https://creativecommons.org/licenses/by-nc/3.0/This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial 3.0 (CC BY-NC 3.0) License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Darvish, Zeinab Ghanbari, Saeed Afshar, Saeid Tapak, Leili Amini, Payam Psoriasis Associated Hub Genes Revealed by Weighted Gene Co-Expression Network Analysis |
title | Psoriasis Associated Hub Genes Revealed by Weighted Gene
Co-Expression Network Analysis |
title_full | Psoriasis Associated Hub Genes Revealed by Weighted Gene
Co-Expression Network Analysis |
title_fullStr | Psoriasis Associated Hub Genes Revealed by Weighted Gene
Co-Expression Network Analysis |
title_full_unstemmed | Psoriasis Associated Hub Genes Revealed by Weighted Gene
Co-Expression Network Analysis |
title_short | Psoriasis Associated Hub Genes Revealed by Weighted Gene
Co-Expression Network Analysis |
title_sort | psoriasis associated hub genes revealed by weighted gene
co-expression network analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10331440/ https://www.ncbi.nlm.nih.gov/pubmed/37434459 http://dx.doi.org/10.22074/CELLJ.2023.1982769.1191 |
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