This study investigated the protective effect of metoprolol on cardiomyocytes in rabbits with heart failure and its possible mechanism. Sixty New Zealand white rabbits were randomly divided into infarction group and non-infarction group, 30 in each group. Myocardial infarction was constructed by ligation of anterior descending branch of coronary artery. Coronary artery threading without ligation after thoracotomy was performed for rabbits in non-infarction group. After model construction, rabbits in each group were further divided into control group (n=15) and metoprolol group (n=15), and fed with normal diet and normal diet + metoprolol. Animals were sacrificed 8 weeks later, and ventricular tissue around infarction area was collected. Expression of connexin 43 (Cx43) in myocardium was detected by immunohistochemistry. Expression of Cx43 protein and mRNA in each group was detected by western blot and reverse transcription PCR. The Cx43 protein was positively expressed in non-infarction group and was evenly distributed in intercellular space. Compared with non-infarction group, expression of Cx43 in infarction group was significantly decreased or even disappeared, while the decrease in expression level of Cx43 and the degree of dispersion were lower in metoprolol group than in control group. There was no significant difference in expression of level of Cx43 protein and mRNA between the subgroups of non-infarction group (P>0.05). In infarction group, expression level of Cx43 protein and mRNA in the metoprolol group were significantly higher than those in control group (P<0.05). The results showed that metoprolol can protect cardiomyocytes after myocardial infarction, and the possible mechanism is related to the regulation of Cx43 expression in cardiomyocytes.
The ability of blood transcriptome analysis to identify dysregulated pathways and outcome-related genes following myocardial infarction remains unknown. Two gene expression datasets (GSE60993 and GSE61144) were downloaded from Gene Expression Omnibus (GEO) Datasets to identify altered plasma transcriptomes in patients with ST-segment elevated myocardial infarction (STEMI) undergoing primary percutaneous coronary intervention. GEO2R, Gene Ontology/Kyoto Encyclopedia of Genes and Genomes annotations, protein–protein interaction analysis, etc., were adopted to determine functional roles and regulatory networks of differentially expressed genes (DEGs). Dysregulated expressomes were verified at transcriptional and translational levels by analyzing the GSE49925 dataset and our own samples, respectively. A total of 91 DEGs were identified in the discovery phase, consisting of 15 downregulated genes and 76 upregulated genes. Two hub modules consisting of 12 hub genes were identified. In the verification phase, six of the 12 hub genes exhibited the same variation patterns at the transcriptional level in the GSE49925 dataset. Among them, S100A12 was shown to have the best discriminative performance for predicting in-hospital mortality and to be the only independent predictor of death during follow-up. Validation of 223 samples from our center showed that S100A12 protein level in plasma was significantly lower among patients who survived to discharge, but it was not an independent predictor of survival to discharge or recurrent major adverse cardiovascular events after discharge. In conclusion, the dysregulated expression of plasma S100A12 at the transcriptional level is a robust early prognostic factor in patients with STEMI, while the discrimination power of the protein level in plasma needs to be further verified by large-scale, prospective, international, multicenter studies.
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