Circular RNAs to predict clinical outcome after cardiac arrest.

Abstract

BACKGROUND:

Cardiac arrest (CA) represents the third leading cause of death worldwide. Among patients resuscitated and admitted to hospital, death and severe neurological sequelae are frequent but difficult to predict. Blood biomarkers offer clinicians the potential to improve prognostication. Previous studies suggest that circulating non-coding RNAs constitute a reservoir of novel biomarkers. Therefore, this study aims to identify circulating circular RNAs (circRNAs) associated with clinical outcome after CA.

RESULTS:

Whole blood samples obtained 48 h after return of spontaneous circulation in 588 survivors from CA enrolled in the Target Temperature Management trial (TTM) were used in this study. Whole transcriptome RNA sequencing in 2 groups of 23 sex-matched patients identified 28 circRNAs associated with neurological outcome and survival. The circRNA circNFAT5 was selected for further analysis using quantitative PCR. In the TTM-trial (n = 542), circNFAT5 was upregulated in patients with poor outcome as compared to patients with good neurological outcome (p < 0.001). This increase was independent of TTM regimen and sex. The adjusted odds ratio of circNFAT5 to predict neurological outcome was 1.39 [1.07-1.83] (OR [95% confidence interval]). CircNFAT5 predicted 6-month survival with an adjusted hazard ratio of 1.31 [1.13-1.52].

CONCLUSION:

We identified circulating circRNAs associated with clinical outcome after CA, among which circNFAT5 may have potential to aid in predicting neurological outcome and survival when used in combination with established biomarkers of CA.

• Authors: Francesca M Stefanizzi, Lu Zhang, Antonio Salgado-Somoza, Josef Dankiewicz, Pascal Stammet, Christian Hassager, Matthew P Wise, Hans Friberg, Tobias Cronberg, Alexander Hundt, Jesper Kjaergaard, Niklas Nielsen, Yvan Devaux
• Journal: Intensive care medicine experimental (Intensive Care Med Exp) Vol. 10 Issue 1 Pg. 41 (Oct 28 2022) ISSN: 2197-425X [Print] Germany
• PMID: 36303007 (Publication Type: Journal Article)
• Copyright: © 2022. The Author(s).