Differentially Expressed Genes and Their Clinical Significance in Ischaemic Stroke: An In-Silico Study.
GPM6B
JunD
differential mRNA expression
gene ontology
gene set enrichment analysis
ischaemic stroke
Journal
The Malaysian journal of medical sciences : MJMS
ISSN: 1394-195X
Titre abrégé: Malays J Med Sci
Pays: Malaysia
ID NLM: 101126308
Informations de publication
Date de publication:
Dec 2020
Dec 2020
Historique:
received:
25
05
2020
accepted:
10
10
2020
entrez:
15
1
2021
pubmed:
16
1
2021
medline:
16
1
2021
Statut:
ppublish
Résumé
Ischaemic stroke (IS), a multifactorial neurological disorder, is mediated by interplay between genes and the environment and, thus, blood-based IS biomarkers are of significant clinical value. Therefore, this study aimed to find global differentially expressed genes (DEGs) in-silico, to identify key enriched genes via gene set enrichment analysis (GSEA) and to determine the clinical significance of these genes in IS. Microarray expression dataset GSE22255 was retrieved from the Gene Expression Omnibus (GEO) database. It includes messenger ribonucleic acid (mRNA) expression data for the peripheral blood mononuclear cells of 20 controls and 20 IS patients. The bioconductor-package 'affy' was used to calculate expression and a pairwise GSEA analysis revealed 21 genes to be significantly plausible gene markers, enriched in multiple pathways among all the DEGs ( The identified genes are either associated with the pathophysiology of IS or they affect post-IS neuronal regeneration, thereby influencing clinical outcome. These genes should, therefore, be evaluated for their utility as suitable markers for predicting IS in clinical scenarios.
Sections du résumé
BACKGROUND
BACKGROUND
Ischaemic stroke (IS), a multifactorial neurological disorder, is mediated by interplay between genes and the environment and, thus, blood-based IS biomarkers are of significant clinical value. Therefore, this study aimed to find global differentially expressed genes (DEGs) in-silico, to identify key enriched genes via gene set enrichment analysis (GSEA) and to determine the clinical significance of these genes in IS.
METHODS
METHODS
Microarray expression dataset GSE22255 was retrieved from the Gene Expression Omnibus (GEO) database. It includes messenger ribonucleic acid (mRNA) expression data for the peripheral blood mononuclear cells of 20 controls and 20 IS patients. The bioconductor-package 'affy' was used to calculate expression and a pairwise
RESULTS
RESULTS
GSEA analysis revealed 21 genes to be significantly plausible gene markers, enriched in multiple pathways among all the DEGs (
CONCLUSION
CONCLUSIONS
The identified genes are either associated with the pathophysiology of IS or they affect post-IS neuronal regeneration, thereby influencing clinical outcome. These genes should, therefore, be evaluated for their utility as suitable markers for predicting IS in clinical scenarios.
Identifiants
pubmed: 33447134
doi: 10.21315/mjms2020.27.6.6
pii: 06mjms27062020_oa4
pmc: PMC7785266
doi:
Types de publication
Journal Article
Langues
eng
Pagination
53-67Informations de copyright
© Penerbit Universiti Sains Malaysia, 2020.
Déclaration de conflit d'intérêts
Conflict of Interest None.
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