MicroRNA Expression Profiles Identify Biomarker for Differentiating the Embolic Stroke from Thrombotic Stroke.

In order to identify potential biomarkers that distinguish the embolic stroke (ES) from thrombotic stroke (TS), a profile of microRNA expression was analyzed. The GSE60319 expression profile was downloaded from the Gene Expression Omnibus (GEO) database. The GEO2R was applied to screen for different...

Full description

Bibliographic Details
Published in:BioMed Research International pp. 1 - 7
Main Authors: Chen, Lai-Te, Jiang, Chen-Yang
Format: pictorial research tables/charts Journal Article
Published: Wiley-Blackwell 12/6/2018
Online Access:View this record in EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=133421352&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 133421352
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        23146133
        FT2T
      jtl: BioMed Research International
      issn: 23146133
      maglogo: N
    pubinfo:
      dt: 12/6/2018
      pid: 480
      pub: Wiley-Blackwell
      place: Malden, Massachusetts
    artinfo:
      ui:
        133421352
        133421352
        133421352
        10.1155/2018/4514178
        133421352
      ppf: 1
      ppct: 6
      formats:
        fmt:
          – @attributes:
              type: T
          – @attributes:
              type: P
      tig:
        atl: MicroRNA Expression Profiles Identify Biomarker for Differentiating the Embolic Stroke from Thrombotic Stroke.
      aug:
        au:
          Chen, Lai-Te
          Jiang, Chen-Yang
        affil: Zhejiang University, School of Medicine, Hangzhou, Zhejiang Province, China
      sug:
        subj:
          MicroRNA Analysis
          Gene Expression
          Biological Markers
          Stroke Diagnosis
          Embolism Diagnosis
          Thrombosis Diagnosis
          Human
          Genomics
          Reference Databases
          Metabolic Networks and Pathways
          Biochemical Phenomena
          Atrial Fibrillation
          Mitral Valve Stenosis
          Myocardial Infarction
          Aortic Dissections
          Enzymes
          Transcription Factors
          Cell Cycle
          Prostatic Neoplasms
          Carcinoma, Non-Small-Cell Lung
          Insulin Resistance
          Hepatitis B
          Neoplastic Processes
          Vasopressins
          Absorption
          Water
      ab: In order to identify potential biomarkers that distinguish the embolic stroke (ES) from thrombotic stroke (TS), a profile of microRNA expression was analyzed. The GSE60319 expression profile was downloaded from the Gene Expression Omnibus (GEO) database. The GEO2R was applied to screen for differentially expressed microRNAs (DEmiRNAs) between the embolic stroke group and thrombotic stroke group. The miRWalk was utilized to predict the target genes of DEmiRNAs. Genes associated with embolic stroke were downloaded from the Comparative Toxicogenomics Database. Cross reference of target genes to disease related genes was conducted to construct the DEmiRNA-gene network. The protein-protein interaction (PPI) network of overlapping genes was evaluated by STRING, using the MCODE and CytoHubba plugin of Cytoscape to identify the modules and hub genes. The enrichment of Kyoto Encyclopedia of Genes and Genomes (KEGG) in modules was performed. There were 30 microRNAs in total identified as DEmiRNAs between embolic stroke and thrombotic stroke groups, of which 8 were upregulated and 22 were downregulated. Among these differentially expressed miRNAs, miR-15a-5p, miR-17-5p, miR-19b-3p, and miR-20a-5p were significantly associated with an ES to TS. Using the miRWalk 3.0 online tool, target genes regulated by DEmiRNAs were predicted. In addition, disease related genes were predicted and compared with target genes of DEmiRNAs. 166 overlapped genes regulated by miR-15a-5p, miR-17-5p, miR-19b-3p, and miR-20a-5p were identified, suggesting their association with diseases that contributed to ES, mainly including atrial fibrillation, mitral valve stenosis, myocardial infarction, and aortic dissection. Therefore, miR-15a-5p, miR-17-5p, miR-19b-3p, and miR-20a-5p were promising candidate biomarkers for differentiating an ES from TS. The PPI network demonstrated that miR-15a-5p, miR-17-5p, miR-19b-3p, and miR-20a-5p were associated with an ES by mainly regulating "CCND1, E2F2, E2F3, ITCH, UBE4A, UBE3C, RBL2, FBXO31, EIF2C4, and EIF2C1". Furthermore, miR-15a-5p and miR-17-5p may function through "cell cycle, prostate cancer, and small cell lung cancer" while miR-19b-3p and miR-20a-5p function through "insulin resistance, hepatitis B, and viral carcinogenesis" and "vasopressin-regulated water reabsorption", respectively. However, these results were approached in the manner of bioinformatics analysis; therefore, further verification is required.
      pubtype: Academic Journal
      doctype:
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N