Identification of lncRNA-NR_104160 as a biomarker and construction of a lncRNA-related ceRNA network for essential hypertension

Wenjuan Peng; Han Cao; Kuo Liu; Chunyue Guo; Yanyan Sun; Han Qi; Zheng Liu; Yunyi Xie; Xiaohui Liu; Bingxiao Li; Ling Zhang

Identification of lncRNA-NR_104160 as a biomarker and construction of a lncRNA-related ceRNA network for essential hypertension

Am J Transl Res. 2020 Oct 15;12(10):6060-6075. eCollection 2020.

Authors

Wenjuan Peng¹, Han Cao¹, Kuo Liu¹, Chunyue Guo¹, Yanyan Sun¹, Han Qi², Zheng Liu³, Yunyi Xie¹, Xiaohui Liu¹, Bingxiao Li¹, Ling Zhang¹

Affiliations

¹ Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing Municipal Key Laboratory of Clinical Epidemiology Beijing 100069, People's Republic of China.
² The National Clinical Research Center for Mental Disorders and Beijing Key Laboratory of Mental Disorders and The Advanced Innovation Center for Human Brain Protection, Beijing Anding Hospital, School of Mental Health, Capital Medical University Beijing 100088, People's Republic of China.
³ Science Department, Peking University People's Hospital Beijing 100044, People's Republic of China.

PMID: 33194014
PMCID: PMC7653565

Abstract

Objectives: To identify long noncoding RNAs (lncRNAs) and construct a competing endogenous RNA (ceRNA) network for essential hypertension.

Methods: An RNA microarray and two-step quantitative real-time PCR were applied to identify differentially expressed RNAs (DE-RNAs), and a luciferase assay was performed to explore the binding relationship between RNAs. A generalized linear model and logistic regression model were used to analyze the associations between different RNAs and of RNAs with hypertension. Receiver operating characteristic curve analysis was executed to evaluate the diagnostic performance. Bioinformatics analysis was applied for network construction.

Results: In total, 439 DE-RNAs (387 lncRNAs and 52 mRNAs) were identified in the microarray, and 71 'lncRNA-miRNA-mRNA' loops formed the ceRNA network. The first validation confirmed that five RNAs (NR_104160, lnc-GPR63-8:1, lnc-HPRT1-9:1, ID1 and RSL24D1) were significantly upregulated in hypertensives (P < 0.05). NR_104160 was significantly associated with hypertension (OR = 2.863, 95% CI: 1.143-7.172; P = 0.025) after adjusting for confounding factors. NR_104160 was included in the hypertension diagnostic model, with an area under the curve of 0.852 (95% CI: 0.761-0.944). In the second validation, NR_104160 showed a constant significant difference (P = 0.001). An elevated expression level of NR_104160 was associated with the expression of ID1 (β = 0.2235, P = 0.005). Luciferase assays showed hsa-miR-101-3p stimulation significantly inhibited the reporter gene activation ability of the NR_104160 wild-type plasmid (P < 0.001).

Conclusions: Our study constructed a ceRNA network to provide hypotheses regarding the mechanism of hypertension development. lncRNA-NR_104160 was identified as a hub element that participates in hypertension transcriptional regulation and as a potential biomarker.

Keywords: biomarker; ceRNA; hypertension; lncRNA; network.