Despite the well-established role of long non-coding RNAs (lncRNAs) across various biological processes, their mechanisms in acute
myocardial infarction (AMI) are not fully elucidated. The GSE34198 dataset from the Gene Expression Omnibus (GEO) database, which comprised 49 specimens from individuals with AMI and 47 specimens from controls, was extracted and analysed using the weighted gene co-expression network analysis (WGCNA) package. Twenty-seven key genes were identified through a combination of the degree and gene significance (GS) values, and the CDC42 (degree = 64), JAK2 (degree = 41), and CHUK (degree = 30) genes were identified as having the top three-degree values among the 27 genes. Potential interactions between
lncRNA,
miRNAs and mRNAs were predicted using the starBase V3.0 database, and a
lncRNA-
miRNA-
mRNA triple network containing the
lncRNA XIST, twenty-one
miRNAs and three hub genes (CDC42, JAK2 and CHUK) was identified. RT-qPCR validation showed that the expression of the JAK2 and CDC42 genes and the
lncRNA XIST was noticeably increased in samples from patients with AMI compared to normal samples. Pearson's correlation analysis also proved that JAK2 and CDC42 expression levels correlated positively with
lncRNA XIST expression levels. The area under ROC curve (AUC) of
lncRNA XIST was 0.886, and the diagnostic efficacy of the
lncRNA XIST was significantly better than that of JAK2 and CDC42. The results suggested that the
lncRNA XIST appears to be a risk factor for AMI likely through its ability to regulate JAK2 and CDC42 gene expressions, and it is expected to be a novel and reliable
biomarker for the diagnosis of AMI.