Abstract
OBJECTIVE: Stanford-A Aortic dissection (TAAD) is a rare and fatal disease, genetic factors remains poorly known. Study has confirmed that lncRNA play an important role in various physiological and pathological processes. This study attempts to elucidate the underlying molecular mechanisms of TAAD through lncRNA-associated competitive endogenous RNA (ceRNA) networks. METHODS: In this study, aortic vascular of 5 TAAD and 5 control (ischemic heart disease) were subjected to lncRNA and mRNA microarray analysis, and differentially expressed mRNAs (DEGs) and differentially expressed lncRNAs (DELs) were identified. The differentially expressed miRNAs (DEmiR) were screened by GSE98770 dataset. The ceRNA network (lncRNA-miRNA-mRNA) was constructed by bioinformatics analysis. The accuracy of hub genes as biomarkers for predicting TAAD was evaluated by receiver operating characteristic (ROC) curve. Finally, the biomarkers were verified by assessing their mRNA levels using real-time quantitative PCR (RT-qPCR). RESULTS: This study revealed 161 DELs, 87 DEmiRs and 103 DEGs between TAAD and control. We constructed ceRNA networks based on the screened 1 lncRNA, 4 miRNAs and 7 mRNAs. We identified three lncRNA-miRNA-mRNA regulatory axes, namely the VCAN axis (LINC01355 - hsa-miR-186-5p / hsa-miR-30a-5p /hsa-miR-30c-5p - VCAN), LOX axis (LINC01355-hsa-miR-145-5p/hsa-miR-186-5p/ hsa-miR-30a-5p / hsa-miR-30c-5p - LOX), and CTSS axis (LINC01355 - hsa-miR-186-5p - CTSS) based on gene ontology, pathway enrichment and protein-protein interaction (PPI) network, which may play an important role in TAAD. The clinical performance of VCAN, CTSS, and LOX in TAAD diagnosis was evaluated, and the AUCs of VCAN, CTSS, and LOX were 0.920 (p<0.001), 0.880 (p=0.002) and 0.840 (p=0.011), respectively. Furthermore, mRNA expression of VCAN in human aortic tissue significantly overexpressed in the TAAD patients (p<0.001). CONCLUSION: This study identifies three ceRNA interaction axes, especially VCAN associated with TAAD pathogenesis, providing fundamentals of bioinformatics for understanding the molecular mechanisms of TAAD pathogenesis and developing potential therapeutic strategies for TAAD.