Tong Yiqing, Yang Yanping, Feng Qiming
Emergency Department, Shanghai Jiaotong University Affiliated Sixth People's Hospital, Shanghai, China.
Evid Based Complement Alternat Med. 2022 Jun 21;2022:1485033. doi: 10.1155/2022/1485033. eCollection 2022.
Sepsis is one of the most common reasons for hospitalization and in-hospital mortality each year. Noncoding RNAs have been reported not only as diagnostic and prognostic indicators but also as therapeutic targets of sepsis. Herein, we used an integrative computational approach to identify miRNA-mediated ceRNA crosstalk between lncRNAs and genes in sepsis based on the "ceRNA hypothesis" and investigated prognostic roles of hub genes in sepsis.
Two good-quality gene expression datasets with more than 10 patient samples, GSE89376 and GSE95233, were employed to obtain differentially expressed lncRNAs (DElncRNAs) and genes (DEGs) in sepsis. The DElncRNA-miRNA-DEG regulatory network was constructed using a combination of DElncRNA-miRNA pairs and miRNA-DEmRNA pairs. The protein-protein interaction (PPI) network was constructed by mapping DEGs into the STRING database to identify hub genes in sepsis. The clinical and prognostic significance of hub genes was validated in 89 patients with post-traumatic sepsis.
The integrative computational approach identified 311 DEGs and 19 DElncRNAs between septic patients and healthy volunteers. Results yielded 122 downDElncRNA-miRNA-downDEG networks based on two lncRNAs, HCP5, and HOTAIRM1, and 36 upDElncRNA-miRNA-upDEG network based on BASP1-AS1. The PPI network identified serum/glucocorticoid regulated kinase 1 (SGK1), arrestin beta 1 (ARRB1), and G protein-coupled receptor 183 (GPR183) as located at the core of the network, and three of them were downregulated in sepsis. SGK1, ARRB1, and GPR183 were all involved in lncRNA HCP5-based ceRNA network. The quantitative real-time PCR revealed that the patients with post-traumatic sepsis exhibited reduced relative mRNA levels of SGK1, ARRB1, and GPR183 compared to the patients without sepsis. The nonsurvivor group, according to the 28-day mortality, showed lower relative mRNA levels of SGK1, ARRB1, and GPR183 than the survivor group. We also demonstrated reduced mRNA levels of SGK1, ARRB1, and GPR183 were associated with sepsis-related death after trauma.
Our integrative analysis and clinical validation suggest lncRNA HCP5-based ceRNA networks with SGK1, ARRB1, and GPR183 involved were associated with the occurrence and progression of sepsis.
脓毒症是每年住院和院内死亡的最常见原因之一。非编码RNA不仅被报道为脓毒症的诊断和预后指标，还被作为脓毒症的治疗靶点。在此，我们基于“ceRNA假说”，采用综合计算方法来识别脓毒症中lncRNA与基因之间的miRNA介导的ceRNA串扰，并研究核心基因在脓毒症中的预后作用。
使用两个包含超过10个患者样本的高质量基因表达数据集GSE89376和GSE95233，以获取脓毒症中差异表达的lncRNA（DElncRNA）和基因（DEG）。通过结合DElncRNA-miRNA对和miRNA-DEmRNA对构建DElncRNA-miRNA-DEG调控网络。通过将DEG映射到STRING数据库构建蛋白质-蛋白质相互作用（PPI）网络，以识别脓毒症中的核心基因。在89例创伤后脓毒症患者中验证核心基因的临床和预后意义。
综合计算方法在脓毒症患者和健康志愿者之间识别出311个DEG和19个DElncRNA。基于两个lncRNA，即HCP5和HOTAIRM1，得到了122个downDElncRNA-miRNA-downDEG网络，基于BASP1-AS1得到了36个upDElncRNA-miRNA-upDEG网络。PPI网络确定血清/糖皮质激素调节激酶1（SGK1）、抑制蛋白β-1（ARRB1）和G蛋白偶联受体183（GPR183）位于网络核心，且它们在脓毒症中均下调。SGK1、ARRB1和GPR183均参与基于lncRNA HCP5的ceRNA网络。定量实时PCR显示，创伤后脓毒症患者的SGK1、ARRB1和GPR183相对mRNA水平低于无脓毒症患者。根据28天死亡率，非存活组的SGK1、ARRB1和GPR183相对mRNA水平低于存活组。我们还证明，SGK1、ARRB1和GPR183的mRNA水平降低与创伤后脓毒症相关死亡有关。
我们的综合分析和临床验证表明，涉及SGK1、ARRB1和GPR183的基于lncRNA HCP5的ceRNA网络与脓毒症的发生和进展有关。
