Identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis

Abstract Background The pathogenic mechanisms of venous thromboembolism (VT) remain to be defined. This study aimed to identify differentially expressed genes (DEGs) that could serve as potential therapeutic targets for VT. Methods Two human datasets (GSE19151 and GSE48000) were analyzed by the robu...

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Autores principales:	Guoju Fan, Zhihai Jin, Kaiqiang Wang, Huitang Yang, Jun Wang, Yankui Li, Bo Chen, Hongwei Zhang
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Venous thromboembolism Hub genes Prognosis Prediction Biomarker Diseases of the circulatory (Cardiovascular) system RC666-701
Acceso en línea:	https://doaj.org/article/64d5a2fae88e42f1a490d451f46998c4
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spelling	oai:doaj.org-article:64d5a2fae88e42f1a490d451f46998c42021-12-05T12:05:20ZIdentification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis10.1186/s12872-021-02409-41471-2261https://doaj.org/article/64d5a2fae88e42f1a490d451f46998c42021-12-01T00:00:00Zhttps://doi.org/10.1186/s12872-021-02409-4https://doaj.org/toc/1471-2261Abstract Background The pathogenic mechanisms of venous thromboembolism (VT) remain to be defined. This study aimed to identify differentially expressed genes (DEGs) that could serve as potential therapeutic targets for VT. Methods Two human datasets (GSE19151 and GSE48000) were analyzed by the robust rank aggregation method. Gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analyses were conducted for the DEGs. To explore potential correlations between gene sets and clinical features and to identify hub genes, we utilized weighted gene coexpression network analysis (WGCNA) to build gene coexpression networks incorporating the DEGs. Then, the levels of the hub genes were analyzed in the GSE datasets. Based on the expression of the hub genes, the possible pathways were explored by gene set enrichment analysis and gene set variation analysis. Finally, the diagnostic value of the hub genes was assessed by receiver operating characteristic (ROC) analysis in the GEO database. Results In this study, we identified 54 upregulated and 10 downregulated genes that overlapped between normal and VT samples. After performing WGCNA, the magenta module was the module with the strongest negative correlation with the clinical characteristics. From the key module, FECH, GYPA, RPIA and XK were chosen for further validation. We found that these genes were upregulated in VT samples, and high expression levels were related to recurrent VT. Additionally, the four hub genes might be highly correlated with ribosomal and metabolic pathways. The ROC curves suggested a diagnostic value of the four genes for VT. Conclusions These results indicated that FECH, GYPA, RPIA and XK could be used as promising biomarkers for the prognosis and prediction of VT.Guoju FanZhihai JinKaiqiang WangHuitang YangJun WangYankui LiBo ChenHongwei ZhangBMCarticleVenous thromboembolismHub genesPrognosisPredictionBiomarkerDiseases of the circulatory (Cardiovascular) systemRC666-701ENBMC Cardiovascular Disorders, Vol 21, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Venous thromboembolism Hub genes Prognosis Prediction Biomarker Diseases of the circulatory (Cardiovascular) system RC666-701
spellingShingle	Venous thromboembolism Hub genes Prognosis Prediction Biomarker Diseases of the circulatory (Cardiovascular) system RC666-701 Guoju Fan Zhihai Jin Kaiqiang Wang Huitang Yang Jun Wang Yankui Li Bo Chen Hongwei Zhang Identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis
description	Abstract Background The pathogenic mechanisms of venous thromboembolism (VT) remain to be defined. This study aimed to identify differentially expressed genes (DEGs) that could serve as potential therapeutic targets for VT. Methods Two human datasets (GSE19151 and GSE48000) were analyzed by the robust rank aggregation method. Gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analyses were conducted for the DEGs. To explore potential correlations between gene sets and clinical features and to identify hub genes, we utilized weighted gene coexpression network analysis (WGCNA) to build gene coexpression networks incorporating the DEGs. Then, the levels of the hub genes were analyzed in the GSE datasets. Based on the expression of the hub genes, the possible pathways were explored by gene set enrichment analysis and gene set variation analysis. Finally, the diagnostic value of the hub genes was assessed by receiver operating characteristic (ROC) analysis in the GEO database. Results In this study, we identified 54 upregulated and 10 downregulated genes that overlapped between normal and VT samples. After performing WGCNA, the magenta module was the module with the strongest negative correlation with the clinical characteristics. From the key module, FECH, GYPA, RPIA and XK were chosen for further validation. We found that these genes were upregulated in VT samples, and high expression levels were related to recurrent VT. Additionally, the four hub genes might be highly correlated with ribosomal and metabolic pathways. The ROC curves suggested a diagnostic value of the four genes for VT. Conclusions These results indicated that FECH, GYPA, RPIA and XK could be used as promising biomarkers for the prognosis and prediction of VT.
format	article
author	Guoju Fan Zhihai Jin Kaiqiang Wang Huitang Yang Jun Wang Yankui Li Bo Chen Hongwei Zhang
author_facet	Guoju Fan Zhihai Jin Kaiqiang Wang Huitang Yang Jun Wang Yankui Li Bo Chen Hongwei Zhang
author_sort	Guoju Fan
title	Identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis
title_short	Identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis
title_full	Identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis
title_fullStr	Identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis
title_full_unstemmed	Identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis
title_sort	identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis
publisher	BMC
publishDate	2021
url	https://doaj.org/article/64d5a2fae88e42f1a490d451f46998c4
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_version_	1718372258870722560

Identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis

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