4.5 Article

Circulating exosomal long non-coding RNAs in patients with acute myocardial infarction

Journal

JOURNAL OF CELLULAR AND MOLECULAR MEDICINE
Volume 24, Issue 16, Pages 9388-9396

Publisher

WILEY
DOI: 10.1111/jcmm.15589

Keywords

acute myocardial infarction; biomarkers; exosomal lncRNAs; heart failure; prognosis

Funding

  1. National Natural Science Foundation of China [81800304, 81500038, 81770253]
  2. National Major Research Plan Training Program of China [91849111]
  3. Open Foundation from Beijing Key Laboratory of Hypertension Research [2019GXY-KFKT-03, 2019GXY-KFKT-02]

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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.

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