Open AccessIdentification of differentially expressed genes in asthma by bioinformatics analysis
Author(s) -
Zhaojun Wang,
Zhifeng Mo,
Hongsen Liang,
Qiwei Zhang,
Wei Li,
Dongqing Yan,
Yin Yin,
H Fan,
Liang Zhang,
Donglei Shi,
Junhang Zhang,
Haifeng Li
Publication year - 2021
Publication title -
medical research
Language(s) - English
Resource type - Journals
eISSN - 2664-0341
pISSN - 2664-0333
DOI - 10.6913/mrhk.202106_3(2).0004
Subject(s) - kegg , microrna , gene , computational biology , identification (biology) , gene ontology , asthma , microarray , biology , microarray analysis techniques , gene regulatory network , in silico , bioinformatics , gene expression , genetics , immunology , botany
Objective Asthma is a common inflammatory disease of the airway, and its underlying mechanism is complex. The role of microRNAs (miRNAs) in asthma is unclear. The present study aimed to investigate miRNA-mRNA regulatory networks underlying asthma. Methods One microarray dataset was downloaded from the Gene Expression Omnibus (GEO) database. Differential expression of miRNAs (DEMs) was identified in bronchial epithelial cells (BECs) isolated from healthy donors and patients with asthma. MiRTarBase, mirDIP, and miRDB were used to predict target genes, followed by protein-protein interaction (PPI) network analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, and Gene Ontology (GO) analysis; cytoHubba was used to predict the important nodes in the network. The miRNA-hub genes sub-network of interest was determined. Results This study constructed an asthma-associated miRNA-mRNA network, in which seven key miRNAs and 10 hub genes were identified. Conclusions The novel miRNAs and hub genes identified in the present study could be potential diagnostic and treatment biomarkers for asthma.