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microRNAs (miRs) are essential in the development of heart failure. The aim of this study is to investigate the effect of microRNA‐330 (miR‐330) on left ventricular remodeling via the TGF‐β1/Smad3 signaling pathway by targeting the sex‐determining region Y (SRY) in mice with myocardial ischemia–reperfusion injury (MIRI). Differentially expressed gene (DEG) in myocardial ischemia–reperfusion (IR) was screened out and the miR that targeted the DEG was also predicted and verified. A model of MIRI was established to detect the expression of miR‐330, SRY, transforming growth factor‐β (TGF‐β1), and Sekelsky mothers against dpp3 (Smad3). To further investigate the role of miR‐330 in MIRI with the involvement of SRY and TGF‐β1/Smad3 signaling pathway, the modeled mice were treated with different mimic, inhibitor, or small interfering RNA (siRNA) to observe the changes of the related gene expression, as well as the myocardial infarction size and volume of myocardial collagen. SRY was screened out and verified as a target gene of miR‐330. The MIRI mice showed enlarged myocardial infarction size, increased volume of myocardial collagen, increased expression of miR‐330, TGF‐β1 and Smad3, while decreased the expression of SRY. The MIRI mice treated with miR‐330 inhibitor showed decreased myocardial infarction size, the volume of myocardial collagen, and expression of TGF‐β1 and Smad3 but promoted expression of SRY. Our findings demonstrated that downregulated miR‐330 could suppress left ventricular remodeling to inhibit the activation of the TGF‐β1/Smad3 signaling pathway via negatively targeting of SRY in mice with MIRI. This can be a potential target in the strategy to attenuate patient suffering.

Background The immune system plays a vital role in the pathophysiology of acute myocardial infarction (AMI). However, the exact immune related mechanism is still unclear. This research study aimed to identify key immune-related genes involved in AMI. Methods CIBERSORT, a deconvolution algorithm, was used to determine the proportions of 22 subsets of immune cells in blood samples. The weighted gene co-expression network analysis (WGCNA) was used to identify key modules that are significantly associated with AMI. Then, CIBERSORT combined with WGCNA were used to identify key immune-modules. The protein–protein interaction (PPI) network was constructed and Molecular Complex Detection (MCODE) combined with cytoHubba plugins were used to identify key immune-related genes that may play an important role in the occurrence and progression of AMI. Results The CIBERSORT results suggested that there was a decrease in the infiltration of CD8 + T cells, gamma delta (γδ) T cells, and resting mast cells, along with an increase in the infiltration of neutrophils and M0 macrophages in AMI patients. Then, two modules (midnightblue and lightyellow) that were significantly correlated with AMI were identified, and the salmon module was found to be significantly associated with memory B cells. Gene enrichment analysis indicated that the 1,171 genes included in the salmon module are mainly involved in immune-related biological processes. MCODE analysis was used to identify four different MCODE complexes in the salmon module, while four hub genes (EEF1B2, RAC2, SPI1, and ITGAM) were found to be significantly correlated with AMI. The correlation analysis between the key genes and infiltrating immune cells showed that SPI1 and ITGAM were positively associated with neutrophils and M0 macrophages, while they were negatively associated with CD8 + T cells, γδ T cells, regulatory T cells (Tregs), and resting mast cells. The RT-qPCR validation results found that the expression of the ITGAM and SPI1 genes were significantly elevated in the AMI samples compared with the samples from healthy individuals, and the ROC curve analysis showed that ITGAM and SPI1 had a high diagnostic efficiency for the recognition of AMI. Conclusions Immune cell infiltration plays a crucial role in the occurrence and development of AMI. ITGAM and SPI1 are key immune-related genes that are potential novel targets for the prevention and treatment of AMI.