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Application of microRNA Database Mining in Biomarker Discovery and Identification of Therapeutic Targets for Complex Disease.
Major, Jennifer L; Bagchi, Rushita A; Pires da Silva, Julie.
Afiliação
  • Major JL; Department of Medicine, Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
  • Bagchi RA; Department of Medicine, Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
  • Pires da Silva J; Department of Medicine, Division of Cardiology, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA.
Methods Protoc ; 4(1)2020 Dec 30.
Article em En | MEDLINE | ID: mdl-33396619
Over the past two decades, it has become increasingly evident that microRNAs (miRNA) play a major role in human diseases such as cancer and cardiovascular diseases. Moreover, their easy detection in circulation has made them a tantalizing target for biomarkers of disease. This surge in interest has led to the accumulation of a vast amount of miRNA expression data, prediction tools, and repositories. We used the Human microRNA Disease Database (HMDD) to discover miRNAs which shared expression patterns in the related diseases of ischemia/reperfusion injury, coronary artery disease, stroke, and obesity as a model to identify miRNA candidates for biomarker and/or therapeutic intervention in complex human diseases. Our analysis identified a single miRNA, hsa-miR-21, which was casually linked to all four pathologies, and numerous others which have been detected in the circulation in more than one of the diseases. Target analysis revealed that hsa-miR-21 can regulate a number of genes related to inflammation and cell growth/death which are major underlying mechanisms of these related diseases. Our study demonstrates a model for researchers to use HMDD in combination with gene analysis tools to identify miRNAs which could serve as biomarkers and/or therapeutic targets of complex human diseases.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Prognostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article