Cargando…
Identification of key genes and pathways between mild-moderate and severe asthmatics via bioinformatics analysis
Severe asthma is the main reason for death and disability caused by asthma. However, effective biomarkers for severe asthma have not been identified. Here, we aimed to identify potential biomarkers in severe asthma. We identified 202 differentially expressed genes (DEGs) between severe asthma and mi...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8847662/ https://www.ncbi.nlm.nih.gov/pubmed/35169275 http://dx.doi.org/10.1038/s41598-022-06675-w |
_version_ | 1784652091865694208 |
---|---|
author | Wu, Xiaolu Li, Ran Xu, Qu Liu, Feng Jiang, Yue Zhang, Min Tong, Meiling |
author_facet | Wu, Xiaolu Li, Ran Xu, Qu Liu, Feng Jiang, Yue Zhang, Min Tong, Meiling |
author_sort | Wu, Xiaolu |
collection | PubMed |
description | Severe asthma is the main reason for death and disability caused by asthma. However, effective biomarkers for severe asthma have not been identified. Here, we aimed to identify potential biomarkers in severe asthma. We identified 202 differentially expressed genes (DEGs) between severe asthma and mild-moderate asthma after integrating the results from GSE69683 and GSE27011 datasets. The enrichment analysis indicated that 202 DEGs were associated with metabolism- and immune-related processes. 10 hub genes were identified by Cytoscape and five of these genes’ AUC (area under the curve) values were greater than 0.6 in GSE69683. The AUC value reached to 0.701 when combined SEC61A1 and ALDH18A1 expression. The expression of the five hub genes was verified in an external dataset. The network analysis revealed that transcription factor (TF) WT1, ZEB1, RERE, FOSL1, and miR-20a may be involved in the development of asthma. In addition, we found cyclosporine and acetaminophen could interact with these hub genes and may be negatively associated with most of the five hub genes according to previous reports. Overall, key genes were identified between mild-moderate and severe asthmatics, which contributed to the understanding of the development of asthma. |
format | Online Article Text |
id | pubmed-8847662 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-88476622022-02-17 Identification of key genes and pathways between mild-moderate and severe asthmatics via bioinformatics analysis Wu, Xiaolu Li, Ran Xu, Qu Liu, Feng Jiang, Yue Zhang, Min Tong, Meiling Sci Rep Article Severe asthma is the main reason for death and disability caused by asthma. However, effective biomarkers for severe asthma have not been identified. Here, we aimed to identify potential biomarkers in severe asthma. We identified 202 differentially expressed genes (DEGs) between severe asthma and mild-moderate asthma after integrating the results from GSE69683 and GSE27011 datasets. The enrichment analysis indicated that 202 DEGs were associated with metabolism- and immune-related processes. 10 hub genes were identified by Cytoscape and five of these genes’ AUC (area under the curve) values were greater than 0.6 in GSE69683. The AUC value reached to 0.701 when combined SEC61A1 and ALDH18A1 expression. The expression of the five hub genes was verified in an external dataset. The network analysis revealed that transcription factor (TF) WT1, ZEB1, RERE, FOSL1, and miR-20a may be involved in the development of asthma. In addition, we found cyclosporine and acetaminophen could interact with these hub genes and may be negatively associated with most of the five hub genes according to previous reports. Overall, key genes were identified between mild-moderate and severe asthmatics, which contributed to the understanding of the development of asthma. Nature Publishing Group UK 2022-02-15 /pmc/articles/PMC8847662/ /pubmed/35169275 http://dx.doi.org/10.1038/s41598-022-06675-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This 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 | Article Wu, Xiaolu Li, Ran Xu, Qu Liu, Feng Jiang, Yue Zhang, Min Tong, Meiling Identification of key genes and pathways between mild-moderate and severe asthmatics via bioinformatics analysis |
title | Identification of key genes and pathways between mild-moderate and severe asthmatics via bioinformatics analysis |
title_full | Identification of key genes and pathways between mild-moderate and severe asthmatics via bioinformatics analysis |
title_fullStr | Identification of key genes and pathways between mild-moderate and severe asthmatics via bioinformatics analysis |
title_full_unstemmed | Identification of key genes and pathways between mild-moderate and severe asthmatics via bioinformatics analysis |
title_short | Identification of key genes and pathways between mild-moderate and severe asthmatics via bioinformatics analysis |
title_sort | identification of key genes and pathways between mild-moderate and severe asthmatics via bioinformatics analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8847662/ https://www.ncbi.nlm.nih.gov/pubmed/35169275 http://dx.doi.org/10.1038/s41598-022-06675-w |
work_keys_str_mv | AT wuxiaolu identificationofkeygenesandpathwaysbetweenmildmoderateandsevereasthmaticsviabioinformaticsanalysis AT liran identificationofkeygenesandpathwaysbetweenmildmoderateandsevereasthmaticsviabioinformaticsanalysis AT xuqu identificationofkeygenesandpathwaysbetweenmildmoderateandsevereasthmaticsviabioinformaticsanalysis AT liufeng identificationofkeygenesandpathwaysbetweenmildmoderateandsevereasthmaticsviabioinformaticsanalysis AT jiangyue identificationofkeygenesandpathwaysbetweenmildmoderateandsevereasthmaticsviabioinformaticsanalysis AT zhangmin identificationofkeygenesandpathwaysbetweenmildmoderateandsevereasthmaticsviabioinformaticsanalysis AT tongmeiling identificationofkeygenesandpathwaysbetweenmildmoderateandsevereasthmaticsviabioinformaticsanalysis |