THE NOVEL LINCRNA JUNI FIND BY COMPUTATIONAL INVESTIGATION OF THE EXPRESSION PATTERNS OF LNCRNAS IN CORONARY ARTERY DISEASE

Abstract

Background: Long non-coding RNAs (lncRNAs) have emerged as important regulators of cardiovascular pathology and may serve as promising biomarkers for coronary artery disease (CAD). However, the contribution of many lncRNAs to CAD remains unclear. We aimed to identify novel CAD-associated lncRNAs by integrating publicly available transcriptomic datasets.

Methods: Three Gene Expression Omnibus (GEO) datasets were analyzed to identify differentially expressed lncRNAs between CAD patients and healthy controls. To explore the potential functions of the identified lncRNAs, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using lncRNA-associated genes. The expression of JUNI was further validated by quantitative real-time PCR (qRT-PCR).

Results: We identified 107 differentially expressed genes across the three datasets, including 14 dysregulated lncRNAs (11 upregulated and 3 downregulated) in CAD patients relative to controls. Functional enrichment analysis suggested that these lncRNAs are associated with transcriptional regulation, apoptotic signaling, and pathways potentially involved in CAD pathogenesis. qRT-PCR analysis confirmed significant upregulation of JUNI in CAD samples.

Conclusions: JUNI may represent a novel CAD-associated lncRNA. Our findings provide several of candidate lncRNAs for further investigation as potential biomarkers and regulatory molecules in CAD, although independent validation and mechanistic studies are required before clinical application.