Wang JN, Zhou YY, Yu YW, Chen J. Profiling and bioinformatics analyses of circular RNAs in myocardial ischemia/reperfusion injury model in mice. World J Cardiol 2025; 17(1): 102147 [PMID: 39866220 DOI: 10.4330/wjc.v17.i1.102147]
Corresponding Author of This Article
Yong-Wei Yu, PhD, Assistant Professor, Department of Critical Care Medicine, The First Affiliated Hospital of Zhejiang University School of Medicine, No. 79 Qingchun Road, Hangzhou 310000, Zhejiang Province, China. yuyongwei@zju.edu.cn
Research Domain of This Article
Biochemistry & Molecular Biology
Article-Type of This Article
Basic Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Jiao-Ni Wang, Department of Diagnostic Ultrasound and Echocardiography, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou 310002, Zhejiang Province, China
Ying-Ying Zhou, Department of Endocrinology, The Second Affliated and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang Province, China
Yong-Wei Yu, Department of Critical Care Medicine, The First Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou 310000, Zhejiang Province, China
Jun Chen, Cardiac Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, Zhejiang Province, China
Co-first authors: Jiao-Ni Wang and Ying-Ying Zhou.
Co-corresponding authors: Yong-Wei Yu and Jun Chen.
Author contributions: Wang JN completed database processing, data export and manuscript writing; Zhou YY was responsible for the final compilation of pictures and tables; Yu YW and Chen J guided the idea of the manuscript; all of the authors read and approved the final version of the manuscript to be published.
Supported by Zhejiang Provincial Natural Science Foundation of China, No. LQ23H020004; The Medical and Health Research Project of Zhejiang province, No. 2024KY983; Basic Medical Health Technology Project of Wenzhou Science and Technology Bureau, No. Y20210818 and No. Y20210140.
Institutional review board statement: Our work was approved by the Ethics Committee of Wenzhou Medical University.
Institutional animal care and use committee statement: All animal operations approved by the Animal Care and Use Committee at the Wenzhou Medical University (No. wydw2024-0565).
Conflict-of-interest statement: The authors declare that they have no competing interests.
ARRIVE guidelines statement: The authors have read the ARRIVE guidelines, and the manuscript was prepared and revised according to the ARRIVE guidelines.
Data sharing statement: Different mRNA, circRNA, lncRNA and microRNA results obtained by sequencing were stored in GSE240842. If you need the R code for specific analysis, you can contact the corresponding author to obtain it.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Yong-Wei Yu, PhD, Assistant Professor, Department of Critical Care Medicine, The First Affiliated Hospital of Zhejiang University School of Medicine, No. 79 Qingchun Road, Hangzhou 310000, Zhejiang Province, China. yuyongwei@zju.edu.cn
Received: October 9, 2024 Revised: November 23, 2024 Accepted: December 19, 2024 Published online: January 26, 2025 Processing time: 103 Days and 14.8 Hours
Abstract
BACKGROUND
Myocardial ischemia/reperfusion (I/R) injury, which is associated with high morbidity and mortality, is a main cause of unexpected myocardial injury after acute myocardial infarction. However, the underlying mechanism remains unclear. Circular RNAs (circRNAs), which are formed from protein-coding genes, can sequester microRNAs or proteins, modulate transcription and interfere with splicing. Authoritative studies suggest that circRNAs may play an important role in myocardial I/R injury.
AIM
To explore the role and mechanism of circRNAs in myocardial I/R injury.
METHODS
We constructed a myocardial I/R injury model using ligation of the left anterior descending coronary artery, and evaluated the success of the validated model using triphenyltetrazolium chloride and hematoxylin-eosin staining. Then, left ventricular samples from different groups were selected for mRNA-sequence, and differential gene screening was performed on the obtained results. The differentially obtained mRNAs were divided into up-regulated and down-regulated according to their expression levels, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analysis were performed, respectively. Then, the obtained circRNA and microRNA (miRNA) were paired for analysis, and the binding sites of miRNA and mRNA were virtual screened. Finally, the obtained circRNA, miRNA and mRNA were constructed by ceRNA mutual most useful network.
RESULTS
We used an RNA sequencing array to investigate the expression signatures of circRNAs in myocardial I/R injury using three samples from the I/R group and three samples from the sham group. A total of 142 upregulated and 121 downregulated circRNAs were found to be differentially expressed (fold change ≥ 2, P < 0.05). GO and KEGG functional analyses of these circRNAs were performed. GO analysis revealed that these circRNAs were involved mainly in cellular and intracellular processes. KEGG analysis demonstrated that 6 of the top 20 pathways were correlated with cell apoptosis. Furthermore, a circRNA-miRNA coexpression network and ceRNA network based on these genes were constructed, revealing that mmu-circ-0001452, mmu-circ-0001637, and mmu-circ-0000870 might be key regulators of myocardial I/R injury.
CONCLUSION
This research provides new insights into the mechanism of myocardial I/R, which mmu-circ-0001452, mmu-circ-0001637, and mmu-circ-0000870 are expected to be new therapeutic targets for myocardial I/R injury.
Core Tip: The circular RNA-microRNA coexpression network and ceRNA network revealing that mmu-circ-0001452, mmu-circ-0001637, and mmu-circ-0000870 might be key regulators of myocardial ischemia/reperfusion (I/R) injury. This research provides new insights into the mechanism of myocardial I/R and identifies a new target for the prevention and treatment of myocardial I/R injury.
Citation: Wang JN, Zhou YY, Yu YW, Chen J. Profiling and bioinformatics analyses of circular RNAs in myocardial ischemia/reperfusion injury model in mice. World J Cardiol 2025; 17(1): 102147
Myocardial infarction (MI) can be fatal. The mortality rate during the acute phase of acute MI (AMI) is approximately 10%, and the incidence of heart failure reaches 25% during the chronic phase. Blood vessel blockage in the heart, known as myocardial ischemia, is among the most prevalent causes of mortality worldwide[1]. Percutaneous transluminal coronary angioplasty is currently the most effective treatment option for AMI. However, myocardial ischemia-reperfusion injury may prevent the improvement of this condition. Restoring blood flow to the ischemic myocardium can lead to further myocardial damage, referred to as ischemia/reperfusion (I/R) injury. This phenomenon may account for heart failure in several patients, even after successful reperfusion. Despite various interventions showing protective effects against I/R injury in animal studies, no clear benefits have been demonstrated in clinical trials. This underscores the urgent need to reassess the current approaches or develop new strategies to shield the heart from I/R injury[2].
Noncoding RNAs (ncRNAs), such as microRNAs (miRNAs) and long ncRNAs (lncRNAs), which regulate gene transcription and translation, are abundantly expressed in I/R-injured myocardium[3-5]. Despite these findings, the importance of other classes of ncRNAs in myocardial damage and repair after I/R has not yet been evaluated. Circular RNAs (circRNAs) are a novel class of endogenous circular non-coding RNAs that are formed from protein-coding genes by back-splicing and can mediate the activity of miRNAs by binding and functioning as sponges. The continuous loops of circRNAs are formed by covalent bonding of their 3'-ends and 5'-ends during the back splicing process; therefore, circRNAs are more conserved than linear RNAs[6,7]. Emerging evidence indicates that circRNAs are frequently dysregulated in cardiovascular diseases[8] and may influence disease progression via miRNAs[9]. Beyond cardiovascular diseases, circRNAs have been associated with diverse biological processes and pathological conditions, including oncogenesis[10], immune regulation[11], and neurological disorders[12]. For instance, in cancer, circRNAs modulate tumor growth, metastasis, and chemoresistance by sponging specific miRNAs or interacting with RNA-binding proteins. Furthermore, in the nervous system, circRNAs have been shown to participate in synaptic plasticity and neurodegenerative diseases by regulating gene expression at both the transcriptional and posttranscriptional levels. Burd et al[13] reported that circRNAc_ANRIL affects the pathogenesis of atherosclerotic vascular disease (ASVD) by regulating the expression of INK4/ARF, a susceptibility gene for ASVD, by recruiting Polycomb group proteins. Wang et al[14] demonstrated that the circRNAHRCR might protect the myocardium in mice with myocardial hypertrophy by acting as a sponge for miR-223 and competitively regulating nucleolar protein 3. In conclusion, circRNAs play roles beyond gene expression and co-expression and can specifically and comprehensively influence the signaling pathways involved in cardiovascular diseases. To investigate the role of circRNAs in myocardial I/R injury, we explored the alterations in circRNA expression profiles in myocardial tissues subjected to I/R. A total of 12138 circRNAs were differentially expressed in I/R-induced myocardial tissues of mice. By predicting circRNAs interactions with miRNAs and employing bioinformatics tools, ceRNA networks were constructed to elucidate the regulated genes and their functional roles.
MATERIALS AND METHODS
Mouse model
Male C57BL/6J mice (6–7 weeks, 20–25 g, Weitong Lihua Experimental Animal Technology Co., Ltd., Beijing, China) fed in a specific pathogen-free room were randomly divided into two groups, the sham group and myocardial ischemia-reperfusion injury (MIRI) group, with 12 mice in each group.
Myocardial I/R injury in C57BL/6J mice was induced as described previously[15,16]. First, the mice were anaesthetized via isoflurane inhalation. Second, a lateral cut along the upper edge of the third or fourth intercostal space was made to expose the heart. Third, the left anterior descending (LAD) was ligated using a 7-0 silk suture to ligate the distal 1/3 of the vascular artery to induce coronary artery ischaemia for 30 minutes. Then, for reperfusion, the ligation was stopped for 4 hours. Shan surgery without coronary artery occlusion was performed in the sham group of mice. After MIRI or sham surgery, the mice were euthanized via isoflurane inhalation (2%–5%) or intraperitoneal injection of 150 mg/kg to 200 mg/kg sodium pentobarbital, after which the hearts were collected and stored at -80 °C for further use. The methods were approved by the Animal Care and Use Committee of Wenzhou Medical University.
Triphenyltetrazolium chloride staining
We utilized triphenyltetrazolium chloride (TTC) staining to assess the myocardial infarct area. Following reperfusion, a second thoracotomy was performed to ligate the LAD artery, followed by laparotomy to expose the inferior vena cava for injection of 0.3 mL of 2% Evans blue dye solution to delineate the area at risk (AAR). Once the mouse skin and organs turned blue, indicating successful dye distribution, the heart was excised, snap-frozen, sectioned into five 1-mm-thick slices, and incubated in 1% TTC in phosphate-buffered saline at 37 °C for 15 minutes. The percentage of infarcted area (white) relative to the total AAR (red and white) was quantified using ImageJ software.
RNA extraction and qualification
The collected mouse heart tissues were prepared for RNA extraction. Then, the RNA was quantified and quantified as described below (Novogene Experimental Department). RNA degradation and contamination were monitored on 1% agarose gels. RNA purity was assessed using a NanoPhotometer® spectrophotometer (Implen, CA, United States). The RNA concentration was measured using a Qubit® RNA Assay Kit in a Qubit® 2.0 Fluorometer (Life Technologies, CA, United States). RNA integrity was assessed using the RNA Nano 6000 Assay Kit of the Bioanalyzer 2100 system (Agilent Technologies, CA, United States).
Library preparation and RNA sequencing
For circRNA sequencing, 5 μg of total RNA per sample was prepared. First, ribosomal RNA was removed using an Epicentre Ribo-zero™ rRNA Removal Kit (Epicentre, United States), and the free residues of rRNA were removed by ethanol precipitation. For circRNA sequencing, linear RNA was digested with 3 U of RNase R (Epicentre, United States) per µg of RNA. Subsequently, sequencing libraries were created, and cDNA fragments 150 bp to 200 bp in length were isolated. Then, 3 μL of USER Enzyme (NEB, United States) was used before PCR with the selected, adaptor-ligated cDNA at 37 °C for 15 minutes and then 95 °C for 5 minutes. PCR was then performed using Phusion High-Fidelity DNA polymerase, universal PCR primers, and Index (X) Primer. Finally, the product was purified, and library quality was evaluated on an Agilent Bioanalyzer 2100 system. Clustering of the indexed samples was performed in the cBot Cluster Generation System using the TruSeq PE Cluster Kit v3-cBot-HS (Illumina). After the cluster was generated, the libraries were sequenced on the Illumina HiSeq 4000 platform to generate 150 bp paired-end reads.
Differential expression analysis
The circRNAs were detected and identified using find_circ[6] and CIRI2[17]. Circos software was used to construct the circos plot. The raw counts were first normalized using two-phase model. Normalized expression level = (readcount × 1000000)/libsize (libsize is the sum of circRNA readcount). Differential expression analysis of two conditions/groups was performed using the DESeq R package (1.10.1). DESeq provides statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution. The resulting P values were adjusted using Benjamini and Hochberg’s approach for controlling the false discovery rate. Genes with adjusted P values according to DESeq were considered to be differentially expressed.
Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis
Gene Ontology (GO) enrichment analysis for host genes of differentially expressed circRNAs was performed using the GOseq R package, which adjusts for gene length bias. GO terms with adjusted P values below 0.05 were considered to be significantly enriched among differentially expressed genes. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database provides insights into the high-level functions and utilities of biological systems, including cells, organisms, and ecosystems, based on molecular data, especially large-scale datasets derived from genome sequencing and other high-throughput experiments (http://www.genome.jp/kegg/). We applied KOBAS software to assess the statistical enrichment of differentially expressed genes or circRNA host genes in KEGG pathways.
MicroRNA target site analysis and circRNA-miRNA-gene network analysis
To investigate the potential interactions between circRNAs, miRNAs, and mRNAs in myocardial tissues subjected to I/R injury, we performed circRNA sequencing and miRNA sequencing using mouse myocardial tissue samples. Potential miRNA binding sites on the circRNAs were predicted based on target binding sites annotated in non-coding RNA databases (miRBase). Specifically, miRanda was used for animal species to predict circRNA-miRNA interactions. Pairing was performed by aligning the binding sequences of differentially expressed miRNAs with differentially expressed circRNAs identified in our sequencing data. Subsequently, Cytoscape software was utilized to construct a circRNA-miRNA-mRNA interaction network.
Statistical analysis
All experiments were repeated three times. The results are presented as the means ± SD. Student's t test was performed to compare the differences between two groups. P < 0.05 indicated a significant difference.
RESULTS
Generation of a murine myocardial I/R injury model
Compared to the sham group, the myocardial infarct area in the myocardial I/R group appeared pale in color (Figure 1A). The infract size was quantitatively analyzed using the ratio of the infarct area to the risk area [international normalized ratio (INR)/AAR]. The results showed a significant increase in the INR/AAR ratio in the I/R group (Figure 1B). Hematoxylin-eosin staining revealed the destruction of myocardial structure, disruption of myocardial fibers, and a large amount of inflammatory cell infiltration in I/R-induced myocardial tissues (Figure 1C). Additionally, the levels of myocardial enzyme creatine kinase (CK)-myocardial bound (MB) were determined in both groups. As shown in Figure 1D, I/R obviously increased the myocardial CK-MB level (I/R vs sham, 114.8 U/L ± 15.6 U/L vs 21.5 U/L ± 4.5 U/L, P < 0.0001). All the above results indicate that the myocardial ischemia-reperfusion injury mouse model was successfully constructed.
Figure 1 Ischemia/reperfusion induced myocardial injury in mice.
A: Representative images of the infract area international normalized ratio (INR) (white), area at risk (AAR) (red and white), and normal area (blue); B: Quantitative analysis of infarct size and the ratio of INF/AAR; C: Representative images of myocardial tissues from the myocardial ischemia/reperfusion group and sham group; D: Quantitative analysis of creatine kinase-myocardial bound level. All Data are shown as means ± SD. aP < 0.05, bP < 0.01 vs sham group, n = 6 per group. AAR: Area at risk; CK-MB: Creatine kinase-myocardial bound; HE: Hematoxylin-eosin; INR: International normalized ratio; I/R: Ischemia/reperfusion.
CircRNA expression profiles in mouse myocardial I/R tissues
RNA sequencing was performed to identify differentially expressed circRNAs between the myocardial I/R and sham groups. A heatmap of the hierarchical clustering results was generated to visualize the distinguishable circRNAs expression (Figure 2A). In total, 18664 circRNAs were identified across the two groups, of which 12138 were co-expressed (Figure 2B). The volcano plot (Figure 2C) provides an overview of the differentially expressed RNAs. The box plot shows the distribution of circRNAs in the I/R and sham groups (Figure 2D), indicating no differences in circRNA expression patterns between the two groups and the six samples. Compared to the sham group, 263 circRNAs exhibited > 2-fold differential expression in the I/R group (P < 0.05), with 142 upregulated and 121 downregulated circRNAs (Figure 2C). The top ten upregulated and downregulated circRNAs are listed in Table 1.
Figure 2 Circular RNA expression profile comparison between the ischemia/reperfusion group (ischemia/reperfusion 1-3) and sham group (C 1-3).
A: Hierarchical clustering demonstrates the differential circular RNA (circRNA) expression profiling between the ischemia/reperfusion group and sham group; B: The number of circRNAs identified in the two groups; C: Volcano plot shows a difference of circRNA expression between the two groups. In the volcano plots, the red and green points represent the circRNAs with log 20-fold changes (up and down regulated) with statistical significance (P < 0.05); D: Box plot shows the distribution of circRNA expression patterns of two group of samples was not different. I/R: Ischemia/reperfusion.
Table 1 The top 10 upregulated and downregulated circular RNAs.
Sequence name
Log2FC
P value
Top 10 up-regulated circRNAs
Novel_circ_0020886
2.7206
6.53E-12
Novel_circ_0008516
2.2022
3.95E-08
Novel_circ_0025511
1.5733
4.62E-05
Novel_circ_0022589
1.5316
1.32E-06
Mmu_circ_0001290
1.3554
0.00061303
Mmu_circ_0000870
1.2797
0.0013428
Novel_circ_0026528
1.2441
0.001626
Novel_circ_0019820
1.2241
0.0018669
Novel_circ_0020045
1.109
0.002537
Novel_circ_0014497
1.1016
0.005504
Top 10 down-regulated circRNAs
Novel_circ_0002498
-1.3136
0.00057559
Novel_circ_0006830
-1.1768
0.0030546
Novel_circ_0006541
-1.1122
0.0053885
Novel_circ_0006620
-1.0508
0.0070328
Novel_circ_0014429
-1.0484
0.008729
Novel_circ_0007664
-1.0239
0.0097902
Novel_circ_0018781
-1.0181
0.0047702
Novel_circ_0029344
-0.99288
0.0090555
Novel_circ_0000538
-0.98605
0.013754
Novel_circ_0024374
-0.98138
0.014229
GO and KEGG pathway analyses
To further investigate the regulatory roles of circRNAs in myocardial I/R injury, we conducted GO and KEGG pathway analyses on the host genes of the differentially expressed circRNAs. The top 10 enriched GO terms for biological processes, cellular components, and molecular functions are presented in Figure 3. GO biological process analysis revealed that most host genes were involved in cellular, primary, and organic substance metabolic processes. Cellular component analysis revealed that host genes were related to cell parts and intracellular, cytoplasmic, and intracellular organelle processes. KEGG pathway analysis was subsequently performed to confirm the main biochemical, metabolic, and signal transduction pathways associated with the host genes of circRNAs. The top 20 enriched pathways are shown in Figure 4. Among these, some significant pathways with high enrichment scores were correlated with cell apoptosis, including the gap junction, thyroid hormone signaling, and Rap1, mitogen activated protein kinase, and Ras pathways.
Figure 3 Top 10 classes of Gene Ontology enrichment terms.
A: Upregulated Gene Ontology (GO) terms; B: Downregulated GO terms. The GO terms were classified into three parts including biological processes, cellular components, and molecular functions. BP: Biological processes; CC: Cellular components; GO: Gene Ontology; MF: Molecular functions; I/R: Ischemia/reperfusion.
Figure 4 Top 20 classes of Kyoto Encyclopedia of Genes and Genomes pathway enrichment terms.
A: Upregulated gene pathways; B: Downregulated gene pathways. The size of the points represents the number of genes mapped, and the lower q value is, the more significant the pathway was enriched. VEGF: Vascular endothelial growth factors.
Construction of the circRNA-miRNA co-expression network
CircRNAs can act as miRNA sponges or inhibitors of interacting miRNA partners. The top three differentially expressed circRNAs associated with apoptosis and autophagy were used to construct a representative circRNA-miRNA network. Figure 5 illustrates the interactions between the three circRNAs and the miRNAs.
Figure 5 Construction of circular RNA–miRNA interaction networks.
This network was based on the expression profile results and the related software. The 3 dysregulated circular RNAs, mmu_circ_0001637, mmu_circ_0001452, and mmu_circ_0000870 (purple red nodes) having the highest magnitude of change, were predicted to be functionally connected with their targeted microRNAs in the network.
CeRNA network analysis
Based on the ceRNA hypothesis, non-coding RNAs that competitively interact with miRNAs can mitigate their regulatory effects on mRNAs. Starting from these miRNAs, we performed ceRNA analysis on differentially expressed circRNAs using the miRanda software to predict RNAs that may bind to miRNAs and indirectly affect autophagy-related mRNAs. We constructed a ceRNA network (Figure 6) based on the identified mRNA-miRNA and circRNA-miRNA interactions. This network included autophagy-related miRNAs, with three circRNAs predicted to function as ceRNAs.
Figure 6 CeRNA network.
Circular RNA (circRNA)- microRNAs (miRNA)-mRNA interaction pairs were calculated using miRanda. The network was generated using Cytoscape software. The yellow nodes represent for circRNAs, the red nodes represent for mRNAs, the blue nodes represent for miRNA.
DISCUSSION
Myocardial dysfunction due to I/R injury is common in patients with ischemic heart disease. Over the last four decades, novel strategies to attenuate lethal myocardial I/R injury, such as ischemic preconditioning (a short sequence of I/R before an index of prolonged ischemia), repetitive short periods of I/R applied during early reperfusion (postconditioning, PoC), or several pharmacological interventions during late infarction, immediately prior to reperfusion, or at the onset of reperfusion, have been intensively investigated[18-21]. However, their therapeutic effects remain unclear. Therefore, exploring the probable mechanisms underlying myocardial I/R injury and identifying new and effective treatments are urgently required.
Myocardial I/R injury is a complicated process involving multiple mechanisms that occur in both the intracellular and extracellular environments. The potential mechanism of MIRI may involve imbalances in mitochondrial function, intracellular calcium overload, and the overproduction of reactive oxygen species[22,23]. These processes eventually result in cell death. To date, the pathogenesis of myocardial I/R injury has not been fully elucidated. As part of the superfamily of lncRNAs, circRNAs are emerging as new regulatory molecules that participate in the regulation of gene expression. Several studies have investigated the role of circRNAs in cardiovascular diseases[24]. CircRNA expression profiling has been performed in cardiovascular and blood tissues. These results indicate that circRNAs could serve as biomarkers for cardiovascular diseases. Additionally, some studies have functionally identified circRNAs as effectors in cardiovascular disease[25-27]. Additionally, some studies have focused on specific RNA-binding proteins that regulate mRNA splicing and have been linked to cardiovascular pathophysiology in mouse knockout or transgenic models[28,29]. In conclusion, circRNAs are linked to various types of cardiovascular disease and have been identified as intracellular effector molecules contributing to pathophysiological changes in cardiovascular tissues, and cardiovascular biomarkers. However, few circRNAs have been found to be correlated with myocardial I/R injury.
In this study, we performed RNA sequencing to identify differentially expressed transcripts, including mRNAs, lncRNAs, and circRNAs, in MIRI mice compared to those in control mice. Three samples from each group were selected for circRNA profiling. A total of 263 differentially expressed circRNAs were identified, of which 142 were upregulated and 121 were downregulated. These results indicated that changes in circRNA expression are associated with MIRI pathogenesis. CircRNA–miRNA interactions were assessed to further reveal how circRNAs function as miRNA sponges. Generally, two forms of myocardial cell death occur during myocardial ischemia–reperfusion injury: (1) Apoptosis; and (2) Necrosis. Apoptosis is a key biological event in cardiomyocytes in MIRI and was observed in I/R-induced myocardial tissue in this study. However, studies by others and us have confirmed that there is a third mechanism by which cardiomyocytes regulate cell survival or death: Autophagy[30-32].
CircRNAs are involved in autophagy by regulating transcriptional and post-transcriptional modifications of autophagy-related genes. In the context of MIRI, autophagy has a dual nature, it is protective during the ischemic phase by eliminating metabolic waste and maintaining myocyte survival, and is potentially detrimental during reperfusion because of excessive autophagic activity[33]. Zhang et al[34] revealed the role of circPAN3 in regulating autophagy and apoptosis during MIRI and found that circpan3 was downregulated and overexpressed in mouse MIRI models, significantly inhibiting autophagy and reducing MI size. Huang et al[35] reported that circZNF512 silencing in cardiomyocytes disrupts its interaction with miR-181d-5p, thereby affecting early growth response protein 1 expression, promoting autophagy, and alleviating myocardial damage. Our research group confirmed[36] that mmu_circ_0005874 and mmu-miR-543-3p affect the translation of Map3k8 through a ceRNA mechanism, thus affecting the production of autophagosomes. In this study, we confirmed the findings mentioned above and found that many differentially expressed circRNAs in MIRI tissues were correlated with cell autophagy. Based on these results, we explored the ceRNA mechanisms of several autophagy-related circRNAs. Three circRNAs that interact with miRNAs that transcriptionally regulate autophagy were selected and annotated (circRNA_0000870, circRNA_0001452, and circRNA_0001637), including the most downregulated circRNA, circRNA_0001637. Furthermore, a ceRNA network based on the selected circRNAs was constructed and GO enrichment and KEGG pathway analyses revealed the functional roles of the target genes.
However, in the field of myocardial I/R injury, circRNAs have unique advantages that make them potential key regulatory factors and therapeutic targets: (1) Structural stability[37]: CircRNA has a closed circular structure without 5'-ends and 3'-ends, which makes it more stable than linear RNA and less susceptible to nuclease degradation. Therefore, circRNAs can exist more persistently in the myocardial I/R injury environment and participate in the regulation of related molecular mechanisms; (2) Gene expression regulation[38]: CircRNAs can regulate the effect of miRNAs on target mRNA by sponging microRNA (miRNA). During myocardial I/R injury, several miRNAs are closely associated with myocardial cell apoptosis, oxidative stress, and inflammation. CircRNAs can indirectly affect the expression of related genes by regulating their activity; (3) Participation in the regulation of cell survival and death[38]. Studies have shown that certain circRNAs can affect the processes of autophagy, apoptosis, and necrosis of cardiomyocytes, which are closely related to myocardial I/R injury. For example, specific circRNAs can protect cardiomyocytes from ischemic injury and promote their recovery; (4) Potential biomarkers[39]: Owing to their stability and specific expression, circRNAs are expected to serve as biomarkers of myocardial I/R injury. Their differential expression patterns in cardiovascular diseases enable their use in diagnosing the extent of myocardial injury and evaluating treatment efficacy; and (5) Potential therapeutic targets[40]: CircRNAs can be used as novel targets for the treatment of myocardial I/R injury to alleviate reperfusion-induced injury by regulating key molecular pathways. By targeting specific circRNAs, it is possible to regulate myocardial protection mechanisms, reduce myocardial cell damage, and improve recovery following reperfusion.
Although circRNA has shown great potential in the field of myocardial I/R injury, they have some obvious shortcomings and deficiencies in research and application: (1) Functional research is still in its early stages[37], and although the potential role of circRNA is being explored, its specific biological functions and mechanisms are not yet fully understood. Compared to mRNA and miRNAs, the study of circRNAs began late, especially in myocardial I/R injury, where there is still a lack of in-depth understanding of their specific functions and regulatory mechanisms; (2) Complex regulatory network[41]: CircRNAs not only regulate gene expression by sponging miRNA but also interact with other proteins, RNA, or DNA. Their diverse modes of action result in the formation of complex regulatory networks. Accurate analysis of the specific roles and regulatory pathways of circRNAs in myocardial I/R injury remains challenging; (3) Difficulty in function prediction[42]: Although bioinformatics tools can predict the potential binding of circRNAs to miRNAs or proteins, the accuracy and reliability of these predictions are limited by several factors. In myocardial I/R injury, many circRNA functional predictions lack experimental validation, and the complexity of the circRNA-miRNA-mRNA regulatory axis further increases the difficulty of experimental validation; (4) Tissue-specific expression[39]: The expression of circRNAs has strong tissue and spatiotemporal specificity. Specific circRNAs in myocardial tissue may not be expressed or may exhibit different functions in other tissues, limiting their potential application as broad therapeutic targets. In addition, it is difficult to accurately regulate circRNA expression in the myocardium; (5) Obstacles to clinical application[43]: Although circRNAs have shown potential in laboratory research, there are still many challenges in their translation into clinical applications. For example, the effective delivery of circRNAs or their regulators to the cardiac tissue, avoidance of off-target effects, and ensuring their safety and long-term stability in vivo require further research and verification; (6) Lack of standardized detection methods[44]: Standardization of circRNA detection methods remains a technical challenge. Although current detection technologies, such as qPCR and RNA sequencing, can detect circRNA expression, the results often vary between laboratories. In addition, given the similarity between circRNAs and their linear precursor sequences, accurately distinguishing between the two places higher requirements on detection; and (7) Difficulty in verifying biological effects[37]: Owing to the complex and diverse functions of circRNAs, their specific biological effects on myocardial I/R injury are difficult to verify through a single experiment. This requires the use of multiple technologies and models, such as gene knockout and overexpression models, and involves multilevel molecular and cellular experimental verification.
CONCLUSION
This study links circRNA expression profiling to MIRI, predicts the regulatory role of circRNAs in MIRI progression, and contributes to a new field of knowledge in MIRI research. This study has several limitations. The effects of circRNAs on miRNAs and mRNAs have only been computationally analyzed and have not been experimentally proven. Further studies on loss-of-function or transgenic overexpression of specific circRNAs, especially autophagy-correlated circRNAs, in MIRI progression in vivo are needed.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Cardiac and cardiovascular systems
Country of origin: China
Peer-review report’s classification
Scientific Quality: Grade B, Grade B
Novelty: Grade B, Grade B
Creativity or Innovation: Grade B, Grade B
Scientific Significance: Grade A, Grade A
P-Reviewer: Chao T S-Editor: Luo ML L-Editor: A P-Editor: Wang WB
Zhou M, Bao Y, Li H, Pan Y, Shu L, Xia Z, Wu D, Lam KS, Vanhoutte PM, Xu A, Jia W, Hoo RL. Deficiency of adipocyte fatty-acid-binding protein alleviates myocardial ischaemia/reperfusion injury and diabetes-induced cardiac dysfunction.Clin Sci (Lond). 2015;129:547-559.
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