Identification of potential biomarkers in dengue via integrated bioinformatic analysis.
Dengue fever virus (DENV) is a global health threat that is becoming increasingly critical. However, the pathogenesis of dengue has not yet been fully elucidated. In this study, we employed bioinformatics analysis to identify potential biomarkers related to dengue fever and clarify their underlying...
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ftdoajarticles:oai:doaj.org/article:1f02be71eb00482fbe215d5158370ea5 2023-05-15T15:10:05+02:00 Identification of potential biomarkers in dengue via integrated bioinformatic analysis. Li-Min Xie Xin Yin Jie Bi Huan-Min Luo Xun-Jie Cao Yu-Wen Ma Ye-Ling Liu Jian-Wen Su Geng-Ling Lin Xu-Guang Guo 2021-08-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0009633 https://doaj.org/article/1f02be71eb00482fbe215d5158370ea5 EN eng Public Library of Science (PLoS) https://doi.org/10.1371/journal.pntd.0009633 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0009633 https://doaj.org/article/1f02be71eb00482fbe215d5158370ea5 PLoS Neglected Tropical Diseases, Vol 15, Iss 8, p e0009633 (2021) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2021 ftdoajarticles https://doi.org/10.1371/journal.pntd.0009633 2022-12-31T07:29:01Z Dengue fever virus (DENV) is a global health threat that is becoming increasingly critical. However, the pathogenesis of dengue has not yet been fully elucidated. In this study, we employed bioinformatics analysis to identify potential biomarkers related to dengue fever and clarify their underlying mechanisms. The results showed that there were 668, 1901, and 8283 differentially expressed genes between the dengue-infected samples and normal samples in the GSE28405, GSE38246, and GSE51808 datasets, respectively. Through overlapping, a total of 69 differentially expressed genes (DEGs) were identified, of which 51 were upregulated and 18 were downregulated. We identified twelve hub genes, including MX1, IFI44L, IFI44, IFI27, ISG15, STAT1, IFI35, OAS3, OAS2, OAS1, IFI6, and USP18. Except for IFI44 and STAT1, the others were statistically significant after validation. We predicted the related microRNAs (miRNAs) of these 12 target genes through the database miRTarBase, and finally obtained one important miRNA: has-mir-146a-5p. In addition, gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were carried out, and a protein-protein interaction (PPI) network was constructed to gain insight into the actions of DEGs. In conclusion, our study displayed the effectiveness of bioinformatics analysis methods in screening potential pathogenic genes in dengue fever and their underlying mechanisms. Further, we successfully predicted IFI44L and IFI6, as potential biomarkers with DENV infection, providing promising targets for the treatment of dengue fever to a certain extent. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 15 8 e0009633 |
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Directory of Open Access Journals: DOAJ Articles |
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ftdoajarticles |
language |
English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Li-Min Xie Xin Yin Jie Bi Huan-Min Luo Xun-Jie Cao Yu-Wen Ma Ye-Ling Liu Jian-Wen Su Geng-Ling Lin Xu-Guang Guo Identification of potential biomarkers in dengue via integrated bioinformatic analysis. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Dengue fever virus (DENV) is a global health threat that is becoming increasingly critical. However, the pathogenesis of dengue has not yet been fully elucidated. In this study, we employed bioinformatics analysis to identify potential biomarkers related to dengue fever and clarify their underlying mechanisms. The results showed that there were 668, 1901, and 8283 differentially expressed genes between the dengue-infected samples and normal samples in the GSE28405, GSE38246, and GSE51808 datasets, respectively. Through overlapping, a total of 69 differentially expressed genes (DEGs) were identified, of which 51 were upregulated and 18 were downregulated. We identified twelve hub genes, including MX1, IFI44L, IFI44, IFI27, ISG15, STAT1, IFI35, OAS3, OAS2, OAS1, IFI6, and USP18. Except for IFI44 and STAT1, the others were statistically significant after validation. We predicted the related microRNAs (miRNAs) of these 12 target genes through the database miRTarBase, and finally obtained one important miRNA: has-mir-146a-5p. In addition, gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were carried out, and a protein-protein interaction (PPI) network was constructed to gain insight into the actions of DEGs. In conclusion, our study displayed the effectiveness of bioinformatics analysis methods in screening potential pathogenic genes in dengue fever and their underlying mechanisms. Further, we successfully predicted IFI44L and IFI6, as potential biomarkers with DENV infection, providing promising targets for the treatment of dengue fever to a certain extent. |
format |
Article in Journal/Newspaper |
author |
Li-Min Xie Xin Yin Jie Bi Huan-Min Luo Xun-Jie Cao Yu-Wen Ma Ye-Ling Liu Jian-Wen Su Geng-Ling Lin Xu-Guang Guo |
author_facet |
Li-Min Xie Xin Yin Jie Bi Huan-Min Luo Xun-Jie Cao Yu-Wen Ma Ye-Ling Liu Jian-Wen Su Geng-Ling Lin Xu-Guang Guo |
author_sort |
Li-Min Xie |
title |
Identification of potential biomarkers in dengue via integrated bioinformatic analysis. |
title_short |
Identification of potential biomarkers in dengue via integrated bioinformatic analysis. |
title_full |
Identification of potential biomarkers in dengue via integrated bioinformatic analysis. |
title_fullStr |
Identification of potential biomarkers in dengue via integrated bioinformatic analysis. |
title_full_unstemmed |
Identification of potential biomarkers in dengue via integrated bioinformatic analysis. |
title_sort |
identification of potential biomarkers in dengue via integrated bioinformatic analysis. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2021 |
url |
https://doi.org/10.1371/journal.pntd.0009633 https://doaj.org/article/1f02be71eb00482fbe215d5158370ea5 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 15, Iss 8, p e0009633 (2021) |
op_relation |
https://doi.org/10.1371/journal.pntd.0009633 https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0009633 https://doaj.org/article/1f02be71eb00482fbe215d5158370ea5 |
op_doi |
https://doi.org/10.1371/journal.pntd.0009633 |
container_title |
PLOS Neglected Tropical Diseases |
container_volume |
15 |
container_issue |
8 |
container_start_page |
e0009633 |
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1766341147012104192 |