Qinghe Huang1, Cuiyu Huang2, Yan Luo3, Fuyun He3, Rongfang Zhang3. 1. Department of Intensive Care Unit, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China. Electronic address: huang_qinghe@126.com. 2. Department of Surgery, Yongan Municipal Hospital, Yongan, China. 3. Department of Intensive Care Unit, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China.
Abstract
OBJECTIVE: To investigate the correlation of circulating long non-coding RNA nuclear-enriched abundant transcript 1 (lncRNA NEAT1) expression with disease risk, severity, prognosis and inflammatory cytokine levels in sepsis patients. METHODS: 152 sepsis patients and 150 health controls (HCs) were enrolled in this study. Plasma and serum samples were obtained from sepsis patients and HCs, and lncRNA NEAT1 expression in plasma was determined by quantitative polymerase chain reaction, while levels of inflammatory cytokines in serum were detected by enzyme linked immune sorbent assay. RESULTS: LncRNA NEAT1 expression was remarkably higher in sepsis patients than in HCs (P < 0.001). Receiver operating characteristic (ROC) curve disclosed a good predictive value of lncRNA NEAT1 expression for sepsis risk with area under curve (AUC) of 0.730 (95% CI: 0.740-0.861). Subsequent multivariate logistic regression analysis demonstrated that lncRNA NEAT1 expression was independently associated with higher sepsis risk (P < 0.001). In sepsis patients, lncRNA NEAT1 expression was also observed to be positively correlated with Acute Physiology and Chronic Health Evaluation (APACHE) II score (P < 0.001), serum tumor necrosis factor-α (P < 0.001), interleukin (IL)-1β (P = 0.043), IL-6 (P = 0.001) and IL-8 (P = 0.038), while negatively correlated with IL-10 (P < 0.001). In addition, lncRNA NEAT1 expression was increased in non-survivors compared to survivors (P = 0.006), and ROC curve revealed a good prognostic value of lncRNA NEAT1 for non-survivor risk with AUC 0.641 (95% CI: 0.536-0.746). CONCLUSION: Circulating lncRNA NEAT1 correlates with increased disease risk, elevated severity and unfavorable prognosis as well as higher expression of pro-inflammatory cytokines in sepsis patients.
OBJECTIVE: To investigate the correlation of circulating long non-coding RNA nuclear-enriched abundant transcript 1 (lncRNA NEAT1) expression with disease risk, severity, prognosis and inflammatory cytokine levels in sepsispatients. METHODS: 152 sepsispatients and 150 health controls (HCs) were enrolled in this study. Plasma and serum samples were obtained from sepsispatients and HCs, and lncRNA NEAT1 expression in plasma was determined by quantitative polymerase chain reaction, while levels of inflammatory cytokines in serum were detected by enzyme linked immune sorbent assay. RESULTS: LncRNA NEAT1 expression was remarkably higher in sepsispatients than in HCs (P < 0.001). Receiver operating characteristic (ROC) curve disclosed a good predictive value of lncRNA NEAT1 expression for sepsis risk with area under curve (AUC) of 0.730 (95% CI: 0.740-0.861). Subsequent multivariate logistic regression analysis demonstrated that lncRNA NEAT1 expression was independently associated with higher sepsis risk (P < 0.001). In sepsispatients, lncRNA NEAT1 expression was also observed to be positively correlated with Acute Physiology and Chronic Health Evaluation (APACHE) II score (P < 0.001), serum tumor necrosis factor-α (P < 0.001), interleukin (IL)-1β (P = 0.043), IL-6 (P = 0.001) and IL-8 (P = 0.038), while negatively correlated with IL-10 (P < 0.001). In addition, lncRNA NEAT1 expression was increased in non-survivors compared to survivors (P = 0.006), and ROC curve revealed a good prognostic value of lncRNA NEAT1 for non-survivor risk with AUC 0.641 (95% CI: 0.536-0.746). CONCLUSION: Circulating lncRNA NEAT1 correlates with increased disease risk, elevated severity and unfavorable prognosis as well as higher expression of pro-inflammatory cytokines in sepsispatients.
Authors: Jingshu Chen; Shu Tang; Sui Ke; James J Cai; Daniel Osorio; Andrei Golovko; Benjamin Morpurgo; Shaodong Guo; Yuxiang Sun; Melanie Winkle; George A Calin; Yanan Tian Journal: Redox Biol Date: 2022-06-18 Impact factor: 10.787
Authors: J Sadri Nahand; F Bokharaei-Salim; M Karimzadeh; M Moghoofei; S Karampoor; H R Mirzaei; A Tabibzadeh; A Jafari; A Ghaderi; Z Asemi; H Mirzaei; M R Hamblin Journal: HIV Med Date: 2019-11-22 Impact factor: 3.180