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Identification of biomarkers of venous thromboembolism by bioinformatics analyses

Venous thromboembolism (VTE) is a common vascular disease and a major cause of mortality. This study intended to explore the biomarkers associated with VTE by bioinformatics analyses. Based on Gene Expression Omnibus (GEO) database, the GSE19151 expression profile data were downloaded. The different...

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Autores principales: Wang, Guiming, Zhao, Wenbo, Yang, Yudong, Yang, Gaochao, Wei, Zhigang, Guo, Jiansheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5902267/
https://www.ncbi.nlm.nih.gov/pubmed/29620629
http://dx.doi.org/10.1097/MD.0000000000010152
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author Wang, Guiming
Zhao, Wenbo
Yang, Yudong
Yang, Gaochao
Wei, Zhigang
Guo, Jiansheng
author_facet Wang, Guiming
Zhao, Wenbo
Yang, Yudong
Yang, Gaochao
Wei, Zhigang
Guo, Jiansheng
author_sort Wang, Guiming
collection PubMed
description Venous thromboembolism (VTE) is a common vascular disease and a major cause of mortality. This study intended to explore the biomarkers associated with VTE by bioinformatics analyses. Based on Gene Expression Omnibus (GEO) database, the GSE19151 expression profile data were downloaded. The differentially expressed genes (DEGs) between single VTE (sVTE)/recurrent VTE (rVTE) and control were identified. Then, pathway enrichment analysis of DEGs were performed, followed by protein–protein interaction (PPI) network construction. Total 433 upregulated and 222 downregulated DEGs were obtained between sVTE and control samples. For rVTE versus control, 625 upregulated and 302 downregulated DEGs were identified. The overlap DEGs were mainly enriched in the pathways related to ribosome, cancer, and immune disease. The DEGs specific to rVTE were enriched in several pathways, such as nod-like receptor signaling pathway. In the PPI network, 2 clusters of VTE genes, including ribosomal protein family genes and NADH family-ubiquinol-cytochrome genes, were identified, such as ribosomal protein L9 (RPL9), RPL5, RPS20, RPL23, and tumor protein p53 (TP53). The nod-like receptor signaling pathway, ribosomal protein family genes, such as RPL9, RPL5, RPS20, and RPL23, and DEG of TP53 may have the potential to be used as targets for diagnosis and treatment of VTE.
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spelling pubmed-59022672018-04-24 Identification of biomarkers of venous thromboembolism by bioinformatics analyses Wang, Guiming Zhao, Wenbo Yang, Yudong Yang, Gaochao Wei, Zhigang Guo, Jiansheng Medicine (Baltimore) 3400 Venous thromboembolism (VTE) is a common vascular disease and a major cause of mortality. This study intended to explore the biomarkers associated with VTE by bioinformatics analyses. Based on Gene Expression Omnibus (GEO) database, the GSE19151 expression profile data were downloaded. The differentially expressed genes (DEGs) between single VTE (sVTE)/recurrent VTE (rVTE) and control were identified. Then, pathway enrichment analysis of DEGs were performed, followed by protein–protein interaction (PPI) network construction. Total 433 upregulated and 222 downregulated DEGs were obtained between sVTE and control samples. For rVTE versus control, 625 upregulated and 302 downregulated DEGs were identified. The overlap DEGs were mainly enriched in the pathways related to ribosome, cancer, and immune disease. The DEGs specific to rVTE were enriched in several pathways, such as nod-like receptor signaling pathway. In the PPI network, 2 clusters of VTE genes, including ribosomal protein family genes and NADH family-ubiquinol-cytochrome genes, were identified, such as ribosomal protein L9 (RPL9), RPL5, RPS20, RPL23, and tumor protein p53 (TP53). The nod-like receptor signaling pathway, ribosomal protein family genes, such as RPL9, RPL5, RPS20, and RPL23, and DEG of TP53 may have the potential to be used as targets for diagnosis and treatment of VTE. Wolters Kluwer Health 2018-04-06 /pmc/articles/PMC5902267/ /pubmed/29620629 http://dx.doi.org/10.1097/MD.0000000000010152 Text en Copyright © 2018 the Author(s). Published by Wolters Kluwer Health, Inc. http://creativecommons.org/licenses/by-nc-nd/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0
spellingShingle 3400
Wang, Guiming
Zhao, Wenbo
Yang, Yudong
Yang, Gaochao
Wei, Zhigang
Guo, Jiansheng
Identification of biomarkers of venous thromboembolism by bioinformatics analyses
title Identification of biomarkers of venous thromboembolism by bioinformatics analyses
title_full Identification of biomarkers of venous thromboembolism by bioinformatics analyses
title_fullStr Identification of biomarkers of venous thromboembolism by bioinformatics analyses
title_full_unstemmed Identification of biomarkers of venous thromboembolism by bioinformatics analyses
title_short Identification of biomarkers of venous thromboembolism by bioinformatics analyses
title_sort identification of biomarkers of venous thromboembolism by bioinformatics analyses
topic 3400
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5902267/
https://www.ncbi.nlm.nih.gov/pubmed/29620629
http://dx.doi.org/10.1097/MD.0000000000010152
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