Myocardial infarction (MI) is referred to as a heart attack event term in which myocardial cells die because of imbalances between oxygen supply and demand. The general definition of MI consists of five subtypes, among which type 1 and type 2 MI are the widely occurred sorts and also exhibit a tight relationship to clinicians (Gao et al., 2016). Type 1 MI is induced by acute atherosclerotic thrombosis, whereas type 2 MI results from the imbalanced supply and demand of myocardial oxygen without acute atherosclerotic thrombosis (Lu et al., 2015; Sandoval and Jaffe, 2019). The most common cause of MI is blood flow to a part of the heart is reduced or paused, leading to myocardial necrosis. Also, the result of a blood coagulum in the coronary artery is responsible for supplying the heart muscle area. The risk of MI usually increases with age, particularly at the age of more than 65 years (Lu et al., 2015).

Previous research has shown that epigenetic regulation plays importantly in the regulation of cardiovascular repair functions. Typically, as the ubiquitous and abundant transcription modification of messenger RNA (mRNA) and long non-coding RNA in the genome of eukaryotes, N6-methyladenosine (m6A) primarily occurs in the 3′-untranslated regions and nearby the stop codons of mRNAs (Meyer et al., 2012; Wang et al., 2014; Li et al., 2017; Liu et al., 2017; Zhang et al., 2017). Acting as a reversible modification, m6A is methylated by m6A methyltransferases (writers), demethylated by m6A demethylases (erasers), and recognized by m6A binding proteins (readers), which participates in various biological processes. Dysregulated m6A is gradually thought to be the etiopathogenesis of certain diseases, such as carcinomas and cardiovascular disease (CVD). Growing evidence indicated that the continuous dynamic modulation of m6A exerts an impact on specific genes’ expression and some diseases’ physiological and pathological processes, including MI, ischemic heart failure (HF), myocardial hypertrophy, and cardiomyogenesis (Mathiyalagan et al., 2019). For instance, WTAP promotes MI via modulating m6A modification of ATF4 mRNA (Wang et al., 2021). Dorn et al. (2019) showed that N6 adenosine methylation regulated by METTL3 is crucial for hypertrophy’s pathological process in vivo and in vitro. Loss of METTL3 enhanced heart regeneration and repair after myocardial injury (Gong et al., 2021). Nonetheless, the roles of m6A regulators in MI remained largely unclear.

So far, the function of m6A in physiological and biological processes has been largely studied. Nevertheless, the research toward m6A is limited under pathological conditions in MI. Here, we systematically investigated the role of m6A epigenetic regulation in MI. Furthermore, we applied unsupervised consensus clustering on gene expression in MI based on m6A expression. In addition, we identified the potential roles of differentially expressed genes (DEGs) in different clusters based on m6A expression by performing Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and protein–protein interaction (PPI) network analysis. As far as we know, our literature, for the first time, comprehensively analyzed m6A’s roles in MI, which may provide novel clues to identify biomarkers for MI treatment and diagnosis.

MI is still the leading threat to human health. m6A is considered one of the most common and abundant RNA methylation modifications in eukaryotes (Wang et al., 2014; Mathiyalagan et al., 2019; Wen et al., 2019). m6A is regulated by m6A methyltransferases and demethylases and controls the fate of target mRNA by affecting splicing, translation, and decay. Recently, some researches suggested that m6A modification exhibits importantly in the development of cardiac remodeling and cardiomyocyte contractile function (Dorn et al., 2019; Huang et al., 2019; Han et al., 2021; Wang et al., 2021). For example, ablation of METTL3 weakened MI-caused myocardial fibrosis by impeding the activation of cardiac fibroblasts (Dorn et al., 2019). WTAP promotes MI via modulating ATF4 (Wang et al., 2021). ALKBH5 mediated the modulation of heart regeneration via demethylating YTHDF1 mRNA (Han et al., 2021). However, there was lacking the comprehensive analysis of the roles of m6A in MI. In this study, we observed that the levels of FTO, YTHDF3, ZC3H13, and WTAP were dramatically differently expressed in MI tissues compared with non-failing controls, further demonstrating the crucial roles of m6A regulators in MI, which were consistent with previous reports. For example, FTO gene polymorphisms were related to HDL cholesterol concentration and high risk of CVD (Franczak et al., 2018) and could predict the incidence of CVD (Aijala et al., 2015). We also predicted the potential signaling related to m6A regulators and observed that FTO and IGFBP2 are mainly related to glucose measurement, elevated blood glucose level, and chronic schizophrenia. Of note, multiple previous reports had indicated the regulation among FTO and glucose metabolism (Khan et al., 2018; Mizuno, 2018). For example, GWASs showed that FTO mutation is related to impaired fasting glucose (Khan et al., 2018). In the liver, FTO regulated glucose and lipid metabolism, which was modulated by metabolic signals (Mizuno, 2018). HNRNPA2B1 and HNRNPC are mainly related to Astler–Coller B1 rectal carcinoma. IGF2BP3 was related to soft tissue neoplasms and peritoneal neoplasms. Next, we analyzed GWAS data and single-cell sequencing data to confirm the functional importance of m6A regulators in MI. The SNP annotation of the locus found that the m6A regulatory gene WTAP was located in the causal region on chromosome 6, suggesting it may be an important pathogenic gene of MI. Furthermore, we analyzed the single-cell sequencing of the heart tissues and found that WTAP is widely expressed in the heart tissues, whose expression in endothelial cells is the highest. By combining the analysis mentioned earlier that WTAP was significantly lower in the MI group, this suggests that maintaining the normal expression of WTAP may be a prevention or improvement means for the treatment of MI. Very interestingly, our findings were consistent with a recent report. Wang et al. (2021) reported that WTAP promotes MI via modulating ATF4. This study, for the first time, reveals novel clues to understand the mechanism of MI based on m6A expression.

The general definition of MI usually consists of five subtypes. In this study, we conducted consensus clustering for MI in view of the dysregulated m6A RNA methylation regulators expression in MI. According to m6A regulators’ expression levels, we clustered 499 MI patients into three subtypes. Our findings demonstrated that FTO, YTHDF1, IGF2BP3, RBM15B, YTHDF3, IGF2BP2, and RBM15 were mostly upregulated in cluster 3. WTAP, HNRNPC, YTHDF2, YTHDC2, HNRNPA2B1, METTL3, ZC3H13, and YTHDC1 were most significantly upregulated in cluster 1. Also, WTAP and HNRNPC were significantly downregulated in cluster 3. Furthermore, our results showed that the DEGs in MI were significantly enriched in multiple signalings, such as the chemokine signaling pathway, calcium signaling pathway, and chemokine signaling. Interestingly, Gene Set Enrichment Analysis further demonstrated that DEGs in MI were related to transport activity and calcium signaling. Moreover, by analyzing the relationship among the top 5 enriched signaling, calcium signaling and chemokine signaling play a key role in MI. Calcium (Ca²⁺), as a second messenger, played a key role in regulating cell proliferation, apoptosis, and survival (Sukumaran et al., 2021). Previous studies had demonstrated that calcium signaling served as a key regulator of MI (Vassalle and Lin, 2004; Li et al., 2021). Under physiological conditions, calcium signaling can effectively modulate the activity of vasodilation/contraction in vascular smooth muscle cells (Li et al., 2021). However, under pathological conditions, Ca2 + overload induces apoptosis in cardiomyocytes, thus leading to MI (Vassalle and Lin, 2004; Jiao et al., 2019). Over the past decades, multiple chemokines and their receptors were found to regulate MI (Altara et al., 2016; Wang et al., 2019; Liang et al., 2021). For example, CXCR3 and its ligands were reported to be valid biomarkers for HF (Altara et al., 2016). CXCL16 was reported to modulate the inflammatory responses in MI (Liang et al., 2021). CXCR4 blockade was found to induce tissue repair after MI by modulating immune-regulatory function (Wang et al., 2019).

Also, bioinformatics analysis indicated that the DEGs between these clusters in MI were related to modulating multiple signalings, such as PI3K-Akt, MAPK, and cGMP-PKG signalings. It is well-known that the PI3K-Akt signaling pathway is a survival-associated signal transduction pathway, protecting the myocardium from ischemic damage (Okumura et al., 2004; Quan et al., 2014; Cheng et al., 2018). Additionally, previous researches have shown that this signaling pathway is motivated when the estrogen receptor β is chronically upregulated. ERK1/2, JNK, and p38 were three subfamilies of MAPK (Zhang and Liu, 2002). The MAPK signaling pathway was reported to promote NF-κB, triggering additional inflammatory cytokines and causing extra damage in myocardial tissue (Verma et al., 2019). The ERK signaling pathway is currently the widely studied one, and it exhibited an association with a variety of biological processes’ regulation, containing cell survival, growth and death, and inflammation-associated immune responses (Ren et al., 2019). cGMP-PKG signaling was considered to be a therapeutic target for myocardial ischemia–reperfusion injury (Ren et al., 2019). As previously described, some studies have shown that cGMP-PKG signaling exerted an effect on the function of the myocardial endoplasmic reticulum and decreased the level of endoplasmic reticulum stress under stress (Schlossmann and Desch, 2011). Moreover, the downregulated genes in cluster 1 compared with cluster 3 and cluster 2 compared with cluster 3 exhibited a significant relation to multiple neurodegenerative diseases. Of note, previous studies revealed abnormal regulation of m6A is related to neurodegenerative disease. For example, Han et al. (2020) reported that the m6A methylation enhanced the development of Alzheimer’s disease. In addition, Du et al. (2021) revealed that the expressions of m6A regulators correlate with neurodegenerative pathways. These reports, together with our findings, revealed the potential crucial roles of m6A in MI.

In our study, we also investigated changes in gene expression among different clusters in MI based on the expression change of the GSE5406 dataset. As present in Figure 7, we observed that approximately 45.7% of DEGs in MI compared with non-failing samples were differently expressed in more than two different clusters. Venn diagram showed four common DEGs among all clusters in MI, including BAG2, CD74, GOLGA8N, and PDK4. Also, those genes were probably regarded as potential indicators for the prediction and diagnosis of MI. For example, BAG3 belongs to the BAG protein family acting as a chaperone molecular via physical interaction with Hsp70, HSPBs. It was shown that mutated BAG3 caused DCM, leading to systolic dysfunction, HF, and myofibrillar myopathy (Sturner and Behl, 2017; Diofano et al., 2020). BAG2 was also a member of the human BAG protein family and is expressed in brown adipose, lung, heart, and other tissues. It is shown that BAG2 presented a highly similar sequence and domain to BAG3, indicating BAG2 could compensate for the loss function upon the absence of BAG3 (Sturner and Behl, 2017). PDH kinases, including PDK1–4 mediated the phosphorylation and inactivation of PDH (Vary and Randle, 1985). It proves that the selectively overexpressed PDK4 in the heart gave rise to an obvious alteration in energy metabolism, including the increase in the utilization of fatty acids and the decrease in carbohydrate consumption with the increased pyruvate concentration. These results suggested that overexpressed PDK4 is sufficient to dramatically bring about the change of substrate utilization in the heart (Zhao et al., 2008). CD74 was reported to mediate the effect of macrophage migration inhibitory factor on inflammation and cell proliferation. Migration inhibitory factor–CD74 agonism supplied a potential treatment for acute myocardial ischemia by enhancing AMPK activation (Miller et al., 2008). These results indicated that targeting these genes may provide novel therapy strategies for MI.

Utilizing the STRING database, we constructed the PPI network. The module analysis filtered out several genes, including BAG2, BAG3, MMP2, FGF1, HSPB1, CXL12, PJA2, UBE2M, RNF14, RNF16, KLHL2, LTN1, RBM17, LSM2, TRIM37, UBA3, etc. Some of these genes in acute MI (AMI) have been reported, indicating that our conclusions were consistent with previous integrated bioinformatics analysis data. For instance, Wei Gong et al. (2018) revealed that trimetazidine could prevent cardiac rupture in AMI mice by inhibiting matrix metalloproteinase-2 (Mmp2) and Mmp9 expression levels, indicating that the MMP family was probably related to cardiac remodeling after AMI. Fibroblast growth factor 1 (FGF1), also named acidic FGF, took part in several physiological processes, e.g., development, morphogenesis, and others (Engel et al., 2006; Beenken and Mohammadi, 2009). Overexpression of FGF1 or intramyocardial infusion of FGF1 mimic could exert cardioprotective effects on MI mice models (Htun et al., 1998). Heat-shock proteins (HSPs) are largely expressed in various cells of the cardiovascular system, including endothelial cells, cardiomyocytes, monocytes, and platelets. Kraemer et al. (2019) for the first time, showed the upregulation and phosphorylation of HSP27 (HSPB1) of human platelets during MI on a cellular level ex vivo, showing a typical intracellular translocation pattern. Therefore, HSP27 (HSPB1) phenotype in platelets was a measurable stress response indicator in MI and other acute ischemic events [38,39]. After MI, the increased expression of CXCL12 was observed in the infarct area and served as a homing signal for endothelial progenitor cells (Jiao et al., 2019). To understand the potential functions involved in the hub networks and the connection between hub genes and biological functions, we performed ClueGO analysis of these hub networks in MIs. We found that MI-related network was significantly related to positive and negative regulation of angiogenesis and response to heat. The hub networks in MI clusters were significantly related to antigen processing and ubiquitin-mediated proteolysis, RNA splicing, and stability. These results indicated that the abnormal regulation of RNAs splicing and stability might contribute to the development of MI.

In summary, we observed levels of FTO, YTHDF3, ZC3H13, and WTAP were dramatically differently expressed in MI tissues compared with non-failing controls, further demonstrating the crucial roles of m6A regulators in MI. Bioinformatics analysis showed that m6A regulators were related to regulating glucose measurement and elevated blood glucose levels. Furthermore, GWAS data analysis showed that WTAP SNP was significantly related to the progression of MI. In addition, the single-cell sequencing of the heart tissues found that WTAP is widely expressed in the heart tissues. By combining the analysis mentioned earlier that WTAP was significantly lower in the MI group, this suggests that maintaining the normal expression of WTAP may be a prevention or improvement means for the treatment of MI. Furthermore, three subtypes with different clinical characteristics were constructed based on m6A regulators’ expression profiles, indicating that they were potential therapeutic strategies for MI patients. This study could provide more information for us to understand the roles of m6A in MI, which may provide novel clues to identify biomarkers for clinical treatment and diagnosis.

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

BnH and L-HS conceived and designed the project and are responsible for the overall content. YC, XZ, CG, H-WN, FL, JX, and ZW analyzed and interpreted the data. XS, CG, BrH, and BnH prepared the manuscript. XS, YC, XZ, YL, JX, XW and ZC contributed to revising the manuscript. All authors contributed to discussed the results, critically reviewed the manuscript, read and approved the final manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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