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Identification of novel genes in Behcet’s disease using integrated bioinformatic analysis
Behcet’s disease (BD) is a chronic vascular inflammatory disease. However, the etiology and molecular mechanisms underlying BD development have not been thoroughly understood. Gene expression data for BD were obtained from the Gene Expression Omnibus database. We used robust rank aggregation (RRA) t...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273552/ https://www.ncbi.nlm.nih.gov/pubmed/35364782 http://dx.doi.org/10.1007/s12026-022-09270-3 |
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author | Chen, Si Li, Haolong Zhan, Haoting Zeng, Xiaoli Yuan, Hui Li, Yongzhe |
author_facet | Chen, Si Li, Haolong Zhan, Haoting Zeng, Xiaoli Yuan, Hui Li, Yongzhe |
author_sort | Chen, Si |
collection | PubMed |
description | Behcet’s disease (BD) is a chronic vascular inflammatory disease. However, the etiology and molecular mechanisms underlying BD development have not been thoroughly understood. Gene expression data for BD were obtained from the Gene Expression Omnibus database. We used robust rank aggregation (RRA) to identify differentially expressed genes (DEGs) between patients with BD and healthy controls. Gene ontology functional enrichment was used to investigate the potential functions of the DEGs. Protein–protein interaction (PPI) network analysis was performed to identify the hub genes. Receiver operating characteristic analyses were performed to investigate the value of hub genes in the diagnosis of BD. GSE17114 and GSE61399 datasets were included, comprising 32 patients with BD and 26 controls. The RRA integrated analysis identified 44 significant DEGs among the GSE17114 and GSE61399 CD4 + T lymphocytes. Functional enrichment analysis revealed that protein tyrosine/threonine phosphatase activity and immunoglobulin binding were enriched in BD. PPI analysis identified FCGR3B as a hub gene in the CD4 + T lymphocytes of BD patients. Our bioinformatic analysis identified new genetic features, which will enable further understanding of the pathogenesis of BD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12026-022-09270-3. |
format | Online Article Text |
id | pubmed-9273552 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-92735522022-07-13 Identification of novel genes in Behcet’s disease using integrated bioinformatic analysis Chen, Si Li, Haolong Zhan, Haoting Zeng, Xiaoli Yuan, Hui Li, Yongzhe Immunol Res Original Article Behcet’s disease (BD) is a chronic vascular inflammatory disease. However, the etiology and molecular mechanisms underlying BD development have not been thoroughly understood. Gene expression data for BD were obtained from the Gene Expression Omnibus database. We used robust rank aggregation (RRA) to identify differentially expressed genes (DEGs) between patients with BD and healthy controls. Gene ontology functional enrichment was used to investigate the potential functions of the DEGs. Protein–protein interaction (PPI) network analysis was performed to identify the hub genes. Receiver operating characteristic analyses were performed to investigate the value of hub genes in the diagnosis of BD. GSE17114 and GSE61399 datasets were included, comprising 32 patients with BD and 26 controls. The RRA integrated analysis identified 44 significant DEGs among the GSE17114 and GSE61399 CD4 + T lymphocytes. Functional enrichment analysis revealed that protein tyrosine/threonine phosphatase activity and immunoglobulin binding were enriched in BD. PPI analysis identified FCGR3B as a hub gene in the CD4 + T lymphocytes of BD patients. Our bioinformatic analysis identified new genetic features, which will enable further understanding of the pathogenesis of BD. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12026-022-09270-3. Springer US 2022-04-02 2022 /pmc/articles/PMC9273552/ /pubmed/35364782 http://dx.doi.org/10.1007/s12026-022-09270-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Article Chen, Si Li, Haolong Zhan, Haoting Zeng, Xiaoli Yuan, Hui Li, Yongzhe Identification of novel genes in Behcet’s disease using integrated bioinformatic analysis |
title | Identification of novel genes in Behcet’s disease using integrated bioinformatic analysis |
title_full | Identification of novel genes in Behcet’s disease using integrated bioinformatic analysis |
title_fullStr | Identification of novel genes in Behcet’s disease using integrated bioinformatic analysis |
title_full_unstemmed | Identification of novel genes in Behcet’s disease using integrated bioinformatic analysis |
title_short | Identification of novel genes in Behcet’s disease using integrated bioinformatic analysis |
title_sort | identification of novel genes in behcet’s disease using integrated bioinformatic analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9273552/ https://www.ncbi.nlm.nih.gov/pubmed/35364782 http://dx.doi.org/10.1007/s12026-022-09270-3 |
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