Identification of gene expression profiles in myocardial infarction: a systematic review and meta-analysis.


Kontou P., Pavlopoulou A., Braliou G., Bogiatzi S., Dimou N., Bangalore S., ...More

BMC medical genomics, vol.11, no.1, pp.109, 2018 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 11 Issue: 1
  • Publication Date: 2018
  • Doi Number: 10.1186/s12920-018-0427-x
  • Journal Name: BMC medical genomics
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.109
  • Keywords: Myocardial infarction, Gene-expression, Meta-analysis, Differentially expressed genes, Biomarkers, Risk prediction, GRANULOCYTE CHEMOTACTIC PROTEIN-2, CORONARY-ARTERY-DISEASE, FALSE DISCOVERY RATE, NETWORK ANALYSIS, MICROARRAY DATA, HEART-DISEASE, ASSOCIATION, PREDICTION, BIOMARKERS, CHEMOKINES
  • Dokuz Eylül University Affiliated: Yes

Abstract

Background: Myocardial infarction (MI) is a multifactorial disease with complex pathogenesis, mainly the result of the interplay of genetic and environmental risk factors. The regulation of thrombosis, inflammation and cholesterol and lipid metabolism are the main factors that have been proposed thus far to be involved in the pathogenesis of MI. Traditional risk-estimation tools depend largely on conventional risk factors but there is a need for identification of novel biochemical and genetic markers. The aim of the study is to identify differentially expressed genes that are consistently associated with the incidence myocardial infarction (MI), which could be potentially incorporated into the traditional cardiovascular diseases risk factors models.