Screening of key genes and pathways of ischemic stroke and prediction of traditional Chinese medicines based on bioinformatics.
10.19540/j.cnki.cjcmm.20210218.401
- Author:
Yun CAO
1
;
Ling-Bo KONG
1
;
Xing HUANG
1
;
Xiao-Lin LI
1
;
Jing-Ling CHANG
1
;
Ying GAO
2
Author Information
1. Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine Beijing 100700, China.
2. Department of Neurology, Dongzhimen Hospital, Beijing University of Chinese Medicine Beijing 100700, China Institute for Brain Disorders, Beijing University of Chinese Medicine Bejing 100700, China.
- Publication Type:Journal Article
- Keywords:
bioinformatics;
differentially expressed genes;
ischemic stroke;
prediction of traditional Chinese medicine
- MeSH:
Brain Ischemia;
China;
Computational Biology;
Gene Expression Profiling;
Humans;
Ischemic Stroke;
Medicine, Chinese Traditional;
Stroke/genetics*
- From:
China Journal of Chinese Materia Medica
2021;46(7):1803-1812
- CountryChina
- Language:Chinese
-
Abstract:
The aim of this paper was to explore the key genes and pathogenesis of ischemic stroke(IS) by bioinformatics, and predict the potential traditional Chinese medicines for IS. Based on the gene-chip raw data set of GSE22255 from National Center of Biotechnology Information(NCBI), the article enrolled in 20 patients with ischemic stroke and 20 sex-and age-matched controls, and differentially expressed genes(DEGs) were screened based on R language software. The DAVID tool and R language software were used to perform gene ontology(GO) biological process enrichment analysis and Kyoto encyclopedia of genes and gnomes(KEGG) pathway enrichment analysis. The DEGs were imported into STRING to construct a protein-protein interaction network, and the Molecular Complexity Module(MCODE) plug-in of Cytoscape software was used to visualize and analyze the key functional modules. Moreover, the core genes and the medical ontology information retrieval platform(Coremine Medical) were mapped to each other to screen the traditional Chinese medicines and construct drug-active ingredient-target network. Compared with healthy controls, 14 DEGs were obtained, of which 12 genes were up-regulated and 2 genes were down-regulated. DEGs were mainly involved in immune response, inflammatory process, signal transduction, and cell proliferation regulation. The interleukin-17(IL-17), nuclear factor kappaB(NF-κB), tumor necrosis factor(TNF), nucleotide binding oligomerization domain(NOD)-like receptor and other signaling pathways were involved in KEGG pathway enrichment analysis. The key modules of the DEGs-encoding protein interaction network mainly focused on 7 genes of TNF, JUN, recombinant immediate early response 3(IER3), recombinant early growth response protein 1(EGR1), prostaglandin-endoperoxide synthase 2(PTGS2), C-X-C motif chemokine ligand 8(CXCL8) and C-X-C motif chemokine ligand 2(CXCL2), which were involved in biological processes widely such as neuroinflammation and immunity. TNF and JUN were the key nodes in this module, which might become potential biological markers for diagnosis and prognosis evaluation of IS. The potential traditional Chinese medicines for the treatment of IS includes Salviae Miltiorrhizae Radix et Rhizoma, Croci Stigma, Scutellariae Radix, and Cannabis Fructus. The occurrence of stroke was the result of multiple factors. Dysregulation of genes and pathways related to immune regulation and inflammation may be the key link for the development of IS. This study provided research direction and theoretical basis for further exploring the mechanism of action of traditional Chinese medicine in the treatment of IS and searching for potential drug targets.
