Circulating exosomal long non-coding RNAs in patients with acute myocardial infarction.
Mei-Li ZhengXiao-Yan LiuRui-Juan HanWen YuanKai SunJiu-Chang ZhongXin-Chun YangPublished in: Journal of cellular and molecular medicine (2020)
Exosomes are attracting considerable interest in the cardiovascular field as the wide range of their functions is recognized in acute myocardial infarction (AMI). However, the regulatory role of exosomal long non-coding RNAs (lncRNAs) in AMI remains largely unclear. Exosomes were isolated from the plasma of AMI patients and controls, and the sequencing profiles and twice qRT-PCR validations of exosomal lncRNAs were performed. A total of 518 differentially expressed lncRNAs were detected over two-fold change, and 6 kinds of lncRNAs were strikingly elevated in AMI patients with top fold change and were selected to perform subsequent validation. In the two validations, lncRNAs ENST00000556899.1 and ENST00000575985.1 were significantly up-regulated in AMI patients compared with controls. ROC curve analysis revealed that circulating exosomal lncRNAs ENST00000556899.1 and ENST00000575985.1 yielded the area under the curve values of 0.661 and 0.751 for AMI, respectively. Moreover, ENST00000575985.1 showed more significant relationship with clinical parameters, including inflammatory biomarkers, prognostic indicators and myocardial damage markers. Multivariate logistic model exhibited positive association of ENST00000575985.1 with the risk of heart failure in AMI patients. In summary, our data demonstrated that circulating exosomal lncRNAs ENST00000556899.1 and ENST00000575985.1 are elevated in patients with AMI, functioning as potential biomarkers for predicting the prognosis of pateints with AMI.
Keyphrases
- acute myocardial infarction
- long non coding rna
- percutaneous coronary intervention
- left ventricular
- heart failure
- end stage renal disease
- newly diagnosed
- ejection fraction
- stem cells
- transcription factor
- prognostic factors
- poor prognosis
- oxidative stress
- patient reported outcomes
- atrial fibrillation
- genome wide identification
- machine learning
- big data
- patient reported
- cardiac resynchronization therapy
- real time pcr