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11 May 2017 : Clinical Research  

Plasma Long Noncoding RNA Urothelial Carcinoma Associated 1 Predicts Poor Prognosis in Chronic Heart Failure Patients

Xuejing Yu1ABCDEF, Tong Zou2ABF, Lihui Zou3BC, Junhua Jin3CD, Fei Xiao3AE, Jiefu Yang1AG*

DOI: 10.12659/MSM.904113

Med Sci Monit 2017; 23:2226-2231

Abstract

BACKGROUND: Chronic heart failure (CHF) is a leading cause of death worldwide. A long noncoding RNA (lncRNA) named urothelial carcinoma associated 1 (UCA1) is important in multiple diseases. However, the role of UCA1 in CHF is still unknown. Our study investigated whether UCA1 could be applied as an ideal marker to diagnose and evaluate prognosis in CHF.

MATERIAL AND METHODS: Total plasma RNA was extracted from 67 CHF patients and 67 controls. Quantitative real-time polymerase chain reaction was used to determine the plasma level of UCA1. Correlations between UCA1 and clinical parameters were analyzed by Pearson correlation. Receiver operating characteristic curves (ROC) were obtained to analyze the predictive power of UCA1 and BNP for CHF. Kaplan-Meier survival curves were used to evaluate prognosis of CHF within 1 year.

RESULTS: There was no significant difference in elementary data between CHF and controls. Plasma UCA1 was much higher in CHF patients compared with controls. Plasma UCA1 was positively and negatively correlated with brain natriuretic peptide (BNP) and left ventricle ejection fraction (LVEF), respectively. Plasma UCA1 diagnosed CHF with a diagnostic power of 0.89 and a sensitivity and specificity of 100% [95% CI (0.9464–1)] and 76.12% [95%CI (0.6414–0.8569)] (P<0.05), respectively. CHF patients with higher plasma UCA1 had a lower survival rate than those with a lower level, and survival rate predicted by UCA1 had a similar tendency with BNP. However, there was no significant difference between these 2 markers in predicting the prognosis of CHF (P>0.05).

CONCLUSIONS: Plasma UCA1 might be an excellent indicator to diagnose CHF and it might predict poor outcomes of CHF.

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750