Expression profiles of long noncoding RNAs and messenger RNAs in the border zone of myocardial infarction in rats

Identification of important genes related to anoikis in acute myocardial infarction

Acute myocardial infarction (AMI) increasingly precipitates severe heart failure, with diagnoses now extending to progressively younger demographics. The focus of this study was to pinpoint critical genes linked to both AMI and anoikis, thereby unveiling potential novel biomarkers for AMI detection and intervention. Differential analysis was performed to identify significant differences in expression, and gene functionality was explored. Weighted gene coexpression network analysis (WGCNA) was used to construct gene coexpression networks. Immunoinfiltration analysis quantified immune cell abundance. Protein-protein interaction (PPI) analysis identified the proteins that interact with theanoikis. MCODE identified key functional modules. Drug enrichment analysis identified relevant compounds explored in the DsigDB. Through WGCNA, 13 key genes associated with anoikis and differentially expressed genes were identified. GO and KEGG pathway enrichment revealed the regulation of apoptotic signalling pathways and negative regulation of anoikis. PPI network analysis was also conducted, and 10 hub genes, such as IL1B, ZAP70, LCK, FASLG, CD4, LRP1, CDH2, MERTK, APOE and VTN were identified. IL1B were correlated with macrophages, mast cells, neutrophils and Tcells in MI, and the most common predicted medications were roxithromycin, NSC267099 and alsterpaullone. This study identified key genes associated with AMI and anoikis, highlighting their role in immune infiltration, diagnosis and medication prediction. These findings provide valuable insights into potential biomarkers and therapeutic targets for AMI.

Genetic and Epigenetic Regulation of Lipoxygenase Pathways and Reverse Cholesterol Transport in Atherogenesis

Atherosclerosis is one of the most important medical and social problems of modern society. Atherosclerosis causes a large number of hospitalizations, disability, and mortality. A considerable amount of evidence suggests that inflammation is one of the key links in the pathogenesis of atherosclerosis. Inflammation in the vascular wall has extensive cross-linkages with lipid metabolism, and lipid mediators act as a central link in the regulation of inflammation in the vascular wall. Data on the role of genetics and epigenetic factors in the development of atherosclerosis are of great interest. A growing body of evidence is strengthening the understanding of the significance of gene polymorphism, as well as gene expression dysregulation involved in cross-links between lipid metabolism and the innate immune system. A better understanding of the genetic basis and molecular mechanisms of disease pathogenesis is an important step towards solving the problems of its early diagnosis and treatment.

Integrated Multichip Analysis and WGCNA Identify Potential Diagnostic Markers in the Pathogenesis of ST-Elevation Myocardial Infarction

Background

ST-elevation myocardial infarction (STEMI) is a myocardial infarction (MI) with ST-segment exaltation of electrocardiogram (ECG) caused by vascular occlusion of the epicardium. However, the diagnostic markers of STEMI remain little.

Methods

STEMI raw microarray data are acquired from the Gene Expression Omnibus (GEO) database. Based on GSE60993 and GSE61144, differentially expressed genes (DEGs) are verified via R software, and key modules associated with pathological state of STEMI are verified by weighted correlation network analysis (WGCNA). Take the intersection gene of key module and DEGs to perform the pathway enrichment analyses by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Construct the protein-protein interaction (PPI) network by Cytoscape. Then, select and identify the diagnostic biomarkers of STEMI by least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination (SVM-RFE) algorithms. Finally, assess the infiltration of immune cells of STEMI by CIBERSORT and analyze the correlation between diagnostic markers and infiltrating immune cells.

Results

We get 710 DEGs in the STEMI group and 376 genes associated with STEMI in blue module. 92 intersection genes were concentrated in 30 GO terms and 2 KEGG pathways. 28 hub genes involved in the development of STEMI. Moreover, upregulated ALOX5AP (AUC = 1.00) and BST1 (AUC = 1.00) are confirmed as diagnostic markers of STEMI. CD8+T cells, regulatory T (Treg) cells, resting natural killer (NK) cells, M0 macrophages, resting mast cells, and neutrophils are related to the procession of STEMI. Moreover, ALOX5AP and BST1 are positively related to resting NK cells, M0 macrophages, and neutrophils, while ALOX5AP and BST1 are negatively related to CD8+ T cells, Treg cells, and resting mast cells.

Conclusion

ALOX5AP and BST1 may be the diagnostic markers of STEMI. Immune cell infiltration plays a key role in the development of STEMI.

Epigenetic State Changes Underlie Metabolic Switch in Mouse Post-Infarction Border Zone Cardiomyocytes

Myocardial infarction causes ventricular muscle loss and formation of scar tissue. The surviving myocardium in the border zone, located adjacent to the infarct, undergoes profound changes in function, structure and composition. How and to what extent these changes of border zone cardiomyocytes are regulated epigenetically is not fully understood. Here, we obtained transcriptomes of PCM-1-sorted mouse cardiomyocyte nuclei of healthy left ventricle and 7 days post myocardial infarction border zone tissue. We validated previously observed downregulation of genes involved in fatty acid metabolism, oxidative phosphorylation and mitochondrial function in border zone-derived cardiomyocytes, and observed a modest induction of genes involved in glycolysis, including Slc2a1 (Glut1) and Pfkp. To gain insight into the underlying epigenetic regulatory mechanisms, we performed H3K27ac profiling of healthy and border zone cardiomyocyte nuclei. We confirmed the switch from Mef2- to AP-1 chromatin association in border zone cardiomyocytes, and observed, in addition, an enrichment of PPAR/RXR binding motifs in the sites with reduced H3K27ac signal. We detected downregulation and accompanying epigenetic state changes at several key PPAR target genes including Ppargc1a (PGC-1α), Cpt2, Ech1, Fabpc3 and Vldrl in border zone cardiomyocytes. These data indicate that changes in epigenetic state and gene regulation underlie the maintained metabolic switch in border zone cardiomyocytes.