Exploring the miRNA-mRNA regulatory network in schizophrenia based on GEO database
10.11886/scjsws20211206001
- VernacularTitle:基于GEO数据库构建精神分裂症miRNA-mRNA调控网络
- Author:
Mei HE
1
;
Xu YOU
1
;
Yunbin YANG
1
;
Yanping LI
1
;
Lifen ZHANG
1
;
Zixiang LU
1
;
Yunqiao ZHANG
1
;
Qing LONG
2
;
Xiao MA
2
;
Yong ZENG
2
Author Information
1. The Second People's Hospital of Honghe Prefecture， Honghe 654300， China
2. The Sixth Affiliated Hospital of Kunming Medical University， Yuxi 653100， China
- Publication Type:Journal Article
- Keywords:
Schizophrenia;
miRNA;
mRNA;
Regulatory network;
Bioinformatics;
GEO
- From:
Sichuan Mental Health
2022;35(2):120-125
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo provide a new idea for exploring the molecular genetic approach to the pathogenesis of schizophrenia via construction of microRNA-messenger RNA （miRNA-mRNA） regulatory network in schizophrenia. MethodsThe microarray datasets of GSE54578 miRNA expression profiles in peripheral blood and GSE145554 mRNA expression in the anterior cingulate in postmortem brain of schizophrenic subjects were downloaded from Gene Expression Omnibus （GEO） database since July 2021. The GEO2R was used to identify the differentially expressed miRNAs and mRNAs， screen the miRNA with target differentially expressed mRNA， and predict their potential upstream transcription factors. The overlapping genes from the mRNA targeted by the differentially expressed miRNA and the mRNA differentially expressed in GSE145554 dataset were collected. Then the biological features of hub genes were analyzed via Gene Ontology （GO） analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis， and the protein-protein interaction （PPI） network and miRNA-mRNA regulatory network of hub genes were constructed. ResultsA total of 8 up-regulated differentially expressed miRNAs with targeted mRNA were screened out in GSE54578 datasets regarding schizophrenia， which involved in the regulation of 10 transcription factors， 247 down-regulated differentially expressed mRNAs were screened out in GSE145554 datasets， and 17 overlapping mRNAs were obtained. GO analysis showed that the target mRNAs were mainly involved in astrocyte differentiation and development. KEGG pathway enrichment analysis showed that the target mRNAs were mainly involved in Rap1 and Ras signaling pathways. PPI network analysis showed that the mRNAs （KRAS and CD28） might be key genes in schizophrenia. ConclusionThe integrated bioinformatics analysis based on GEO database can identify potential susceptibility genes in schizophrenia， and it also contributes to the construction of miRNA-mRNA regulatory network in schizophrenia.
