Serum exosomal long noncoding RNA nuclear-enriched abundant transcript 1 predicts 90-day mortality in acute-on-chronic hepatitis B liver failure

ABSTRACT

Objectives: 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.

Methods: 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.

Results: LncRNA NEAT1 levels were higher in non-survivors than survivors (P< 0.01). In the training cohort, lncRNA NEAT1 (HR 1.049, 95%CI 1.023–1.075, P< 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 (P< 0.05, respectively). However, no significant difference was found in AUC between lncRNA NEAT1 and NEAT1 plus MELD score (P> 0.05). ACHBLF patients with lncRNA NEAT1 levels above 1.92 showed poorer survival condition than those below (P< 0.01).

Conclusions: The serum exosomal lncRNA NEAT1 might be a better prognostic biomarker than MELD score for 90-day mortality of ACHBLF.

KEYWORDS:

• Biomarker
• exosome
• LncRNA
• NEAT1
• prognosis

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewers disclosure

Peer reviewers on this manuscript have no relevant financial relationships or otherwise to disclose.

Author contributions

All authors approved the publication and agreed to be accountable for all aspects of the work. Shuai Gao and Kai Wang contributed to the study designed and drafting of the paper. Shuai Gao and Yu-Chen Fan contributed to the majority of the experiments and data collection. Yu-Chen Fan contributed to statistical analysis and interpretation of data. Li-Yan Han contributed to revision of the paper for intellectual content.

Kai Wang was responsible for study supervision.

Additional information

Funding

This work was supported by the Key Project of Chinese Ministry of Science and Technology [2017ZX10202202], the National Natural Science Foundation of China [81600494], Natural Science Foundation of Shandong Province [ZR2016HQ42].