Literature DB >> 32892409

MiR-98-5p promotes ischemia/reperfusion-induced microvascular dysfunction by targeting NGF and is a potential biomarker for microvascular reperfusion.

Yisen Hu1, Jingjie Xiong1, Hong Wen1, Heng Wei1, Xiaocong Zeng1.   

Abstract

OBJECTIVE: This study examined the correlation between serum miR-98-5p levels and indices of microvascular reperfusion in patients undergoing primary percutaneous coronary intervention (pPCI) after ST-segment elevation myocardial infarction (STEMI). Additionally, we evaluated the mechanisms by which miR-98-5p promoted ischemia/reperfusion (I/R)-induced injury in both cultured cell lines and an animal model.
METHODS: Circulating miR-98-5p levels were measured and compared from 171 STEMI patients undergoing pPCI, who were divided into two groups: no-reflow and reflow. The levels of miR-98-5p, nerve growth factor (NGF), and transient receptor potential vanilloid 1 (TRPV1) were analyzed in cultured human coronary endothelial cells (HCECs) exposed to hypoxia/reoxygenation (H/R). The effects of antagomir-98-5p on myocardial I/R-induced microvascular dysfunction in vivo were evaluated. Target gene expression and activity were assessed.
RESULTS: Higher miR-98-5p levels were associated with compromised indices of microvascular reperfusion. In vitro experiments on HCECs showed that exposure to H/R significantly increased miR-98-5p levels. We identified NGF as a novel target of miR-98-5p. Further, antagomir-98-5p relieved microvascular dysfunction and enhanced the expression of NGF and TRPV1 in the rat myocardial I/R model.
CONCLUSIONS: MiR-98-5p promotes microvascular dysfunction by targeting the NGF-TRPV1 axis. Serum miR-98-5p serves as a potential biomarker for microvascular reperfusion.
© 2020 John Wiley & Sons Ltd.

Entities:  

Keywords:  ST-segment elevation myocardial infarction; ischemia/reperfusion; miR-98-5p; microvascular dysfunction; nerve growth factor

Year:  2020        PMID: 32892409     DOI: 10.1111/micc.12657

Source DB:  PubMed          Journal:  Microcirculation        ISSN: 1073-9688            Impact factor:   2.628


  1 in total

1.  Machine learning to predict no reflow and in-hospital mortality in patients with ST-segment elevation myocardial infarction that underwent primary percutaneous coronary intervention.

Authors:  Lianxiang Deng; Xianming Zhao; Xiaolin Su; Mei Zhou; Daizheng Huang; Xiaocong Zeng
Journal:  BMC Med Inform Decis Mak       Date:  2022-04-24       Impact factor: 3.298

  1 in total

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