A novel lncRNA-miRNA-mRNA triple network identifies lncRNA XIST as a biomarker for acute myocardial infarction

Abstract

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.

Identifying patterns of immune related cells and genes in the peripheral blood of acute myocardial infarction patients using a small cohort

“…The chi-square test was used to analyse measurement data, such as the number of drinkers and smokers, and the sex ratio. Based on previous studies [21], MedCalc software (MedCalc Software, Mariakerke, Belgium, version 19.7.4) was used to perform nonparametric receiver operating characteristic (ROC) curve analysis. R software (version 4.1.0) was used to perform the bioinformatics analysis.…”

“…The genes with the top 25% of variance were selected for the WGCNA analysis. In this study, the appropriate soft threshold was defined as 18, and the WGCNA analysis was carried out according to methods detailed in our latest publication [21].…”

Identification of m6A regulator-mediated RNA methylation modification patterns and key immune-related genes involved in atrial fibrillation

“…Genes with the top 25% of variance were selected for the WGCNA. In the current research, the appropriate soft threshold was defined as 14, and detailed WGCNA steps refer to the method described in our recently published article [ 47 ].…”

The Common LncRNAs of Neuroinflammation-Related Diseases

“…(Yao et al, 2022) XIST is a potential diagnostic marker of triple-negative breast cancer, colorectal cancer, and acute myocardial infarction, and 53BP1 combined with XIST is a prognostic marker of BRCA1-like breast cancer. (Lan et al, 2021;Schouten et al, 2016;Yu et al, 2020a;Zheng et al, 2022) XIST plays a proinflammatory role in epilepsy and neuropathic pain by acting as a ceRNA of miRNA. Zhang et al observed the expression of XIST and NFAT5 in CTX-TNA2 astrocyte cell line treated by LPS was significantly increased, while the expression of miR-29c-3p was decreased.…”