Cargando…
Identification of key genes and microRNAs for multiple sclerosis using bioinformatics analysis
To better understand the molecular mechanism underlying the pathogenesis of multiple sclerosis (MS), we aimed to identify the key genes and microRNAs (miRNA) associated with MS and analyze their interactions. Differentially expressed genes (DEGs) and miRNAs (DEMs) based on the gene miRNA dataset GSE...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9191563/ https://www.ncbi.nlm.nih.gov/pubmed/35049167 http://dx.doi.org/10.1097/MD.0000000000027667 |
_version_ | 1784726042159611904 |
---|---|
author | Xu, Zhong-bo Feng, Xin Zhu, Wei-na Qiu, Ming-liang |
author_facet | Xu, Zhong-bo Feng, Xin Zhu, Wei-na Qiu, Ming-liang |
author_sort | Xu, Zhong-bo |
collection | PubMed |
description | To better understand the molecular mechanism underlying the pathogenesis of multiple sclerosis (MS), we aimed to identify the key genes and microRNAs (miRNA) associated with MS and analyze their interactions. Differentially expressed genes (DEGs) and miRNAs (DEMs) based on the gene miRNA dataset GSE17846 and mRNA dataset GSE21942 were determined using R software. Next, we performed functional enrichment analysis and constructed a protein–protein interaction network. Data validation was performed to ensure the reliability of hub genes. The miRNA-mRNA regulatory network was constructed. In total, 47 DEMs and 843 DEGs were identified. Protein–protein interaction network analysis identified several hub genes, including JUN, FPR2, AKT1, POLR2L, LYZ, CXCL8, HBB, CST3, CTSZ, and MMP9, especially LYZ and CXCL8. We constructed an miRNA-mRNA regulatory network and found that hsa-miR-142-3p, hsa-miR-107, hsa-miR-140-5p, and hsa-miR-613 were the most important miRNAs. This study reveals some key genes and miRNAs that may be involved in the pathogenesis of MS, providing potential targets for the diagnosis and treatment of MS. |
format | Online Article Text |
id | pubmed-9191563 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-91915632022-06-14 Identification of key genes and microRNAs for multiple sclerosis using bioinformatics analysis Xu, Zhong-bo Feng, Xin Zhu, Wei-na Qiu, Ming-liang Medicine (Baltimore) 5300 To better understand the molecular mechanism underlying the pathogenesis of multiple sclerosis (MS), we aimed to identify the key genes and microRNAs (miRNA) associated with MS and analyze their interactions. Differentially expressed genes (DEGs) and miRNAs (DEMs) based on the gene miRNA dataset GSE17846 and mRNA dataset GSE21942 were determined using R software. Next, we performed functional enrichment analysis and constructed a protein–protein interaction network. Data validation was performed to ensure the reliability of hub genes. The miRNA-mRNA regulatory network was constructed. In total, 47 DEMs and 843 DEGs were identified. Protein–protein interaction network analysis identified several hub genes, including JUN, FPR2, AKT1, POLR2L, LYZ, CXCL8, HBB, CST3, CTSZ, and MMP9, especially LYZ and CXCL8. We constructed an miRNA-mRNA regulatory network and found that hsa-miR-142-3p, hsa-miR-107, hsa-miR-140-5p, and hsa-miR-613 were the most important miRNAs. This study reveals some key genes and miRNAs that may be involved in the pathogenesis of MS, providing potential targets for the diagnosis and treatment of MS. Lippincott Williams & Wilkins 2021-12-03 /pmc/articles/PMC9191563/ /pubmed/35049167 http://dx.doi.org/10.1097/MD.0000000000027667 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) |
spellingShingle | 5300 Xu, Zhong-bo Feng, Xin Zhu, Wei-na Qiu, Ming-liang Identification of key genes and microRNAs for multiple sclerosis using bioinformatics analysis |
title | Identification of key genes and microRNAs for multiple sclerosis using bioinformatics analysis |
title_full | Identification of key genes and microRNAs for multiple sclerosis using bioinformatics analysis |
title_fullStr | Identification of key genes and microRNAs for multiple sclerosis using bioinformatics analysis |
title_full_unstemmed | Identification of key genes and microRNAs for multiple sclerosis using bioinformatics analysis |
title_short | Identification of key genes and microRNAs for multiple sclerosis using bioinformatics analysis |
title_sort | identification of key genes and micrornas for multiple sclerosis using bioinformatics analysis |
topic | 5300 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9191563/ https://www.ncbi.nlm.nih.gov/pubmed/35049167 http://dx.doi.org/10.1097/MD.0000000000027667 |
work_keys_str_mv | AT xuzhongbo identificationofkeygenesandmicrornasformultiplesclerosisusingbioinformaticsanalysis AT fengxin identificationofkeygenesandmicrornasformultiplesclerosisusingbioinformaticsanalysis AT zhuweina identificationofkeygenesandmicrornasformultiplesclerosisusingbioinformaticsanalysis AT qiumingliang identificationofkeygenesandmicrornasformultiplesclerosisusingbioinformaticsanalysis |