Serum exosomal long noncoding RNA nuclear-enriched abundant transcript 1 predicts 90-day mortality in acute-on-chronic hepatitis B liver failure
: Acute-on-chronic hepatitis B liver failure (ACHBLF) is characterized by high short-term mortality, calling for accurate prognostic biomarkers. This study aims to evaluate the predictive value of serum exosomal long noncoding RNA nuclear-enriched abundant transcript 1 (lncRNA NEAT1) for 90-day mort...
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Published in | Expert review of clinical immunology Vol. 17; no. 7; p. 789 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
England
03.07.2021
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Subjects | |
Online Access | Get more information |
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Summary: | : Acute-on-chronic hepatitis B liver failure (ACHBLF) is characterized by high short-term mortality, calling for accurate prognostic biomarkers. This study aims to evaluate the predictive value of serum exosomal long noncoding RNA nuclear-enriched abundant transcript 1 (lncRNA NEAT1) for 90-day mortality of ACHBLF.
: This prospective study consisted of 113 ACHBLF patients from June 2013 to June 2017 as a training cohort and 72 ACHBLF patients from July 2017 to June 2020 as a validating cohort. LncRNA NEAT1 was detected using quantitative real-time polymerase chain reaction from serum exosomes.
: LncRNA NEAT1 levels were higher in non-survivors than survivors (
< 0.01). In the training cohort, lncRNA NEAT1 (HR 1.049, 95%CI 1.023-1.075,
< 0.001) was an independent predictor for 90-day mortality of ACHBLF. Meanwhile, lncRNA NEAT1 showed significantly higher area under the curve of receiver operating characteristic (AUC) than MELD score in the training and validation cohort (
< 0.05, respectively). However, no significant difference was found in AUC between lncRNA NEAT1 and NEAT1 plus MELD score (
> 0.05). ACHBLF patients with lncRNA NEAT1 levels above 1.92 showed poorer survival condition than those below (
< 0.01).
: The serum exosomal lncRNA NEAT1 might be a better prognostic biomarker than MELD score for 90-day mortality of ACHBLF. |
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ISSN: | 1744-8409 |
DOI: | 10.1080/1744666X.2021.1933442 |