A novel circRNA-miRNA-mRNA network identifies circ-YOD1 as a biomarker for coronary artery disease

• Published in: Scientific reports Vol. 9; no. 1; pp. 18314 - 12
• Main Authors: Miao, Liu, Yin, Rui-Xing, Zhang, Qing-Hui, Liao, Pei-Juan, Wang, Yong, Nie, Rong-Jun, Li, Hui
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 04-12-2019; Nature Publishing Group
• Subjects: 38; 631/208/721; 692/4019/592/2727; 692/53/2421; Adult; Aged; Biomarkers; Biomarkers - blood; Cardiovascular disease; Coronary artery; Coronary Artery Disease - blood; Coronary Artery Disease - genetics; Coronary vessels; DNA microarrays; Endopeptidases - genetics; Female; Gene expression; Heart diseases; Humanities and Social Sciences; Humans; Male; MicroRNAs; MicroRNAs - blood; Middle Aged; miRNA; multidisciplinary; Polymerase chain reaction; Population studies; RNA, Circular - blood; RNA, Messenger - blood; Science; Science (multidisciplinary); Thiolester Hydrolases - genetics
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-019-54603-2

Circular RNAs (circRNAs) are involved in many physiological functions. Whether circulating circRNAs serve as markers for coronary artery disease (CAD) is unknown. Seven CAD-related microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database and were analyzed using clustering and functional enrichment to identify hub mRNAs and miRNAs. StarBase V3.0 and circinteractome databases were used to predict interactions between circRNAs and miRNAs whereas miRwalk and DIANA TOOLS were used to predict interactions between miRNAs and mRNAs. Altogether, this helped establish a circRNA-miRNA-mRNA triple network for diagnosis of CAD. Five non-coding RNAs (ncRNAs) were identified in our study population with the use of quantitative real-time PCR (RT-PCR). The prognostic values of circYOD1, hsa-miR-21-3p and hsa-miR-296-3p were evaluated using a receiver operating characteristic (ROC) curve. A CAD circRNA-miRNA-mRNA network was established from our analyses containing one circRNA, four miRNAs and thirteen mRNAs. After performing RT-PCR validation between CAD and non-CAD samples, only three ncRNAs of five ncRNAs showed significance for further analysis. The area under ROC curve (AUC) of circ-YOD1 was 0.824, the AUC of hsa-miR-21-3p was 0.731 and hsa-miR-296-3p was 0.776. The pairwise comparison results showed that circ-YOD1 had statistical significance (
P
YOD1-21
 < 0.01 and
P
YOD1-296
 < 0.05). The results of functional enrichment analysis of interacting genes and microRNAs showed that the shared circ-YOD1 may act as a new biomarker for CAD. Our investigation of the triple regulatory networks of circRNA-miRNA-mRNA in CAD revealed circ-YOD1 as a potential biomarker for CAD.