Identification of Key Genes as Early Warning Signals of Acute Myocardial Infarction Based on Weighted Gene Correlation Network Analysis and Dynamic Network Biomarker Algorithm

Abstract

PurposeThe specific mechanisms and biomarkersunderlying the progression of stable coronary artery disease (CAD) to acute myocardial infarction (AMI) remain unclear. The current study aims to explore novel gene biomarkers associated with CAD progression by analyzing the transcriptomic sequencing data of peripheral blood monocytes in different stages of CAD.Material and MethodsA total of 24 age- and sex- matched patients at different CAD stages who received coronary angiography were enrolled, which included 8 patients with normal coronary angiography, 8 patients with angiographic intermediate lesion, and 8 patients with AMI. The RNA from peripheral blood monocytes was extracted and transcriptome sequenced to analyze the gene expression and the differentially expressed genes (DEG). A Gene Oncology (GO) enrichment analysis was performed to analyze the biological function of genes. Weighted gene correlation network analysis (WGCNA) was performed to classify genes into several gene modules with similar expression profiles, and correlation analysis was carried out to explore the association of each gene module with a clinical trait. The dynamic network biomarker (DNB) algorithm was used to calculate the key genes that promote disease progression. Finally, the overlapping genes between different analytic methods were explored.ResultsWGCNA analysis identified a total of nine gene modules, of which two modules have the highest positive association with CAD stages. GO enrichment analysis indicated that the biological function of genes in these two gene modules was closely related to inflammatory response, which included T-cell activation, cell response to inflammatory stimuli, lymphocyte activation, cytokine production, and the apoptotic signaling pathway. DNB analysis identified a total of 103 genes that may play key roles in the progression of atherosclerosis plaque. The overlapping genes between DEG/WGCAN and DNB analysis identified the following 13 genes that may play key roles in the progression of atherosclerosis disease: SGPP2, DAZAP2, INSIG1, CD82, OLR1, ARL6IP1, LIMS1, CCL5, CDK7, HBP1, PLAU, SELENOS, and DNAJB6.ConclusionsThe current study identified a total of 13 genes that may play key roles in the progression of atherosclerotic plaque and provides new insights for early warning biomarkers and underlying mechanisms underlying the progression of CAD.

Detecting early‐warning biomarkers associated with heart‐exosome genetic‐signature for acute myocardial infarction: A source‐tracking study of exosome

“… 21 The link between OST4 and the p53 signalling pathway suggests that OST4 in exosomes might interact with the p53 signalling pathway to affect the fate of CMs. Compared with the study of Song et al., which used the transcriptome data of peripheral blood mononuclear cells to screen gene‐related early warning markers, 1 the indicators selected in our study can not only be used as early warning indicators of disease deterioration at the macroscopic level, but also accurately reflect the changes of genetic information inside myocardial cells in the state of myocardial infarction.…”

“…If left untreated, SCAD could progress to AMI. When myocardial remodelling begins, irreversible myocardial‐tissue injury occurs due to obstructive ischemia after AMI 1 . In clinical practice, well‐established heart biomarkers are currently used for diagnosing AMI.…”

“…When myocardial remodelling begins, irreversible myocardial‐tissue injury occurs due to obstructive ischemia after AMI. 1 In clinical practice, well‐established heart biomarkers are currently used for diagnosing AMI. Unfortunately, no effective methods currently exist for providing early warnings for AMI occurrence.…”

Acute ischemia induces spatially and transcriptionally distinct microglial subclusters

“…Specifically, MS4A6C might regulate the immune function of microglia [ 34 ], while GPR65 (TDAG8) was reportedly present in a portion of microglia, and exerts neuroprotective effects by attenuating post-ischemic inflammatory responses [ 35 ]. In terms of ICAM, PLAU reportedly regulates inflammation-related signalling and exacerbates deleterious post-ischemia processes [ 36 , 37 ]. Using ICAM (e.g., LGALS3) and IPAM (e.g., PIK3IP1) markers, ICAM and IPAM localization was confirmed through immunofluorescent staining.…”